border delays and economic impact to the freight … · since economic costs fall into a large...

BORDER DELAYS AND ECONOMIC IMPACT TO THE FREIGHT SECTOR: AN EXPLORATION OF THE EL PASO PORTS OF ENTRY by Sharada R. Vadali, Ph.D. Dong Hun Kang, Ph.D. Karen Fierro Project performed by

Center for International Intelligent Transportation Research Report No: 186041-00005 July 2011 Report prepared by Center for International Intelligent Transportation Research Texas Transportation Institute 4050 Rio Bravo, Suite 151 El Paso, Texas 79902 TEXAS TRANSPORTATION INSTITUTE The Texas A&M University System College Station, Texas 77843-3135

Center for International Intelligent Transportation Research Texas Transportation Institute Page i

Table of Contents

Page

List of Figures ............................................................................................................................... iii List of Tables ................................................................................................................................ iv Disclaimer and Acknowledgments .............................................................................................. v

Executive Summary ...................................................................................................................... 1 Chapter I: Texas Ports of Entry and Nature of Freight Movements in the El Paso-

Juarez Bi-National Region ........................................................................................................... 3 Introduction ................................................................................................................................. 3

Texas Border Ports of Entry ................................................................................................... 3 Trading Partners and Trade through El Paso Border Ports of Entry ....................................... 4

Understanding the Nature of Freight Movements in the El Paso-Juarez Bi-National Region

and Other Ports – Regional Integration Perspectives and Gateway Corridor Types .............. 9

Chapter II: El Paso Ports of Entry and Borders as Components of Transport Costs

and Economic Costs .................................................................................................................... 13 Ports are not Identical ............................................................................................................... 13

Passenger Ports ..................................................................................................................... 13

Commercial and Passengers Ports ........................................................................................ 13 Ports Vary in Terms of Commodity/Trade Profiles .............................................................. 14

Ports Vary in Terms of Transport Corridors They Serve ..................................................... 17 Ports Vary in Terms of How They Move Goods .................................................................. 17

Ports Vary in Terms of final Destinations they Serve/Trading Partners (Truck Trade flow

Distributions) ............................................................................................................................ 19 Borders as Components of Transport Costs and Links to Logistical Efficiency ...................... 21

Factors Causing Delays ......................................................................................................... 21 Prior Literature, Perspectives in Assessing Economic Costs of Delay ................................. 24

Types of Economic Costs ..................................................................................................... 26

Chapter III: El Paso Freight Movements ................................................................................ 27 Freight Movement Trends – El Paso Ports of Entry ................................................................. 27

Proximity of Maquilas to Border Ports of Entry ....................................................................... 37

Chapter IV: Perceptions on Border Delays: Evidence from Shippers in the El Paso

Juarez Region .............................................................................................................................. 38 Shipper Surveys ........................................................................................................................ 38

Issues Identified by Shippers ................................................................................................ 38

Chapter V: Framework to Evaluate Direct Costs of Border Crossing Inefficiencies

to Shippers and carriers ............................................................................................................. 44 Framework Components ........................................................................................................... 44

Commodity/Trade Profiles by Direction of Flow ................................................................. 44

Data Needs to Quantify Direct Costs and Definitions of Delay ........................................... 44 Other Critical Data Elements .................................................................................................... 54

Chapter VI: Direct Costs Categories ....................................................................................... 56 Variable Direct Cost Categories: Shipper ................................................................................. 56 Variable Direct Cost Category: Carrier .................................................................................... 56 Commodity Classifications and Ports of Entry ......................................................................... 56

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Shipper Costs ............................................................................................................................ 57

Variable Carrier Costs .............................................................................................................. 60

Chapter VII: Model Structure .................................................................................................. 63 Structure of the Spreadsheet Tool ............................................................................................. 63

Schematic Data Flows ........................................................................................................... 64

Chapter VIII: Bridge of the Americas Illustration ................................................................. 68 Number of Freight Truck Crossings ......................................................................................... 68 User Input Values in the Spreadsheet Tool .............................................................................. 68 Output Results from the Simulation ......................................................................................... 70

Results ....................................................................................................................................... 71 Conclusions ............................................................................................................................... 72

References .................................................................................................................................... 74 Appendix 1: Bridge of the Americas’ Details .......................................................................... 77

Appendix 2: Commodity Profiles (Ports of Entry) (By Value [2008]) .................................. 79 Appendix 3: Interview Instrument ........................................................................................... 89

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LIST OF FIGURES

Page

Figure I-1. Texas-Mexico Border Ports of Entry (Commercial and Passenger) ............................ 3 Figure III-1. Trends in Import Value through El Paso Ports of Entry (with USA and with Texas

Alone) ................................................................................................................................... 29 Figure III-2. Trends in Import Trade Weight through El Paso Ports of Entry (with Entire USA

and with Texas Alone) (Short Tons) ..................................................................................... 29 Figure III-3. Location Distribution of Juarez Maquiladoras Relative to Border Ports of Entry

(Source: http://www.pdnmapa.org/pdnmapa/index.htm) ..................................................... 37 Figure IV-1. Typical Supply Chains of Shippers of Respondents Indicating Movements of Raw

Materials/Intermediate Goods and Final Goods (Number Responding) .............................. 40

Figure IV-2. Shipper Responses on Variation in Crossing Times (By Respondent Number) .... 41 Figure IV-3. Daily Peaks Identified by Respondents .................................................................. 42

Figure IV-4. Seasonal Peaks Identified by Shippers ................................................................... 42

Figure IV-5. Impacts on Delay on Supply Chains ....................................................................... 43 Figure IV-6. Shipper Responses on Ability to Pass Cost Increases ............................................ 43 Figure V-1. Map of BOTA Crossing Facilities (2009) ................................................................ 46

Figure V-2. Number of RFID Readings at El Paso BOTA Entering and Exiting Points

(Weekday BOTA RFID Readings between July and December 2009) ................................. 48

Figure V-3. Monthly NB Truck Crossing and RFID Counts at BOTA ....................................... 48 Figure V-4. Monthly NB Truck Volumes and RFID Average of Crossing Times at BOTA

(2009) .................................................................................................................................... 49

Figure V-5. Hourly Average of Crossing Time and Standard Deviations (BOTA RFID Data

July-December 2009) ............................................................................................................ 49

Figure V-6. Hourly Average of Crossing Times: Comparison by Month (2009) ....................... 50 Figure V-7. Average of Crossing Times by Day of Week (July-December, 2009) .................... 51

Figure V-8. Fitted Lognormal Distributions of RFID Observations by Time Periods ................ 51 Figure V-9. Performance Measures from RFID Observations (Weekday Crossing Time by

Minute, September 2009) (BOTA) ....................................................................................... 53

Figure V-10. Crossing Time Distribution (BOTA) and Performance Measures/Statistics

(July-September 2009 BOTA) .............................................................................................. 54

Figure V-11. Various Components of the Framework (by Direction of Flows) ......................... 55 Figure VII-1. Structure of the Delay Cost Estimation Tool ......................................................... 64 Figure VII-2. Schematic Data Flow Diagram of the Spreadsheet Tool ....................................... 65

Figure VII-3. Delay Measures ..................................................................................................... 66 Figure VIII-1. Main Input Screen − DCET ................................................................................. 69

Figure VIII-2. Sample Screenshots of Output Reports − BOTA Illustration .............................. 70 Figure VIII-3. Ninety-Five Percent Confidence Interval Cost Estimates − BOTA Illustration .. 71

Figure IX-1. BOTA Land Port of Entry: View from the Mexican Side ...................................... 78

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LIST OF TABLES

Page

Table I-1. Truck Volumes through All US-Mexico Ports of Entry (2010) ................................... 8 Table II-1. Summary of Perspectives Adopted in Assessing Economic Costs of Delay ............. 25 Table II-2. Additional Perspectives on Wider Economic Implications and General Port

Efficiencies ........................................................................................................................... 26

Table III-1. Imports Total Weight by Land Mode (Trade with USA and Texas) (Value and

Weight) ................................................................................................................................. 28 Table III-2. Northbound Crossing Volumes (Trucks) (El Paso Ports of Entry) and by

Loaded or Empty................................................................................................................... 30 Table III-3. El Paso Ports Import Classification and Value (2010) ............................................. 31

Table III-4. El Paso Port Export Classification and Value (2010) .............................................. 34 Table IV-1. Origin/Destination of Commodities Identified by Shippers .................................... 40

Table V-1. Fitted Crossing Time Distribution Parameters .......................................................... 52

Table VI-1. Average Imports Cargo Value per Loaded Truck (Northbound

Crossings El Paso) ................................................................................................................ 57 Table VI-2. Imports through El Paso Ports (2009) ...................................................................... 58

Table VI-3. Commercial Vehicle Values of Time in the United States ...................................... 62 Table VIII-1. Default Values − Bridge of the Americas, El Paso ............................................... 69

Table XI-1. Commodity Profile Brownsville Exports to Mexico ................................................ 79 Table XI-2. Commodity Profile Eagle Pass Exports to Mexico (Primarily Agriculture) ............ 80 Table XI-3. Commodity Profile El Paso Exports to Mexico (Primarily Maquila Products) ....... 81

Table XI-4. Commodity Profile Hidalgo Exports to Mexico ...................................................... 82 Table XI-5. Commodity Profile Laredo Exports to Mexico ........................................................ 83

Table XI-6. Commodity Profile Brownsville Imports to United States ...................................... 84 Table XI-7. Commodity Profile Eagle Pass Imports to United States ......................................... 85

Table XI-8. Commodity Profile El Paso Imports to United States .............................................. 86 Table XI-9. Commodity Profile Hidalgo Imports to United States ............................................. 87 Table XI-10. Commodity Profile Laredo Imports to United States ............................................. 88

Center for International Intelligent Transportation Research Texas Transportation Institute Page v

DISCLAIMER AND ACKNOWLEDGMENTS

This research was performed by the Center for International Intelligent Transportation

Research (CIITR), a part of the Texas Transportation Institute. The contents of this report reflect

the views of the authors, who are responsible for the facts and the accuracy of the data presented

herein.

The authors acknowledge the funding graciously provided by the Center for International

Intelligent Transportation Research, Texas Transportation Institute and the shipper and carriers

who shared their views.

Center for International Intelligent Transportation Research Texas Transportation Institute Page 1

EXECUTIVE SUMMARY

This research examined trading and commodity profiles of El Paso ports of entry in an

attempt to understand economic implications attributable to delays in the border crossing

process. Based on an exhaustive literature review, examination of trends, and commodity

profiles in the bi-national region (El Paso-Juarez), a generic framework was developed to address

economic implications of border-related delays. Since economic costs fall into a large category

and can embrace administrative, direct, indirect and induced costs, this report focused only on

direct costs alone that are attributable to shippers and carriers, but as part of a larger framework

comprising other costs. The innovative elements of this framework are the combination of

archived crossing time information from radio frequency tag data along with information on

crossing volumes, values and weights to develop an innovative interactive spreadsheet tool

called Direct Cost Estimation Tool (DCET). Since a normal border crossing process does

involve some time, this research focused on the development of baseline delay measures using

statistical benchmarks like minimum crossing time, mean and other measures based on the

distribution of crossing times. The other features of the tool are an explicit consideration of

reliability of crossing times through the development of buffer time measures which impact

inventory costs of shippers. This tool also allows for consideration of a delay metrics reflecting

the reliability of the crossing time. These novel elements make this research an advancement

over prior work in this area. More specifically, this report makes several advances in two

specific areas:

Advances in combining near real time delay measures with other data sources to

estimate direct variable costs of delay to shippers and carriers. The costs to shippers

are largely inventory related and can be broken down into holding costs, costs from

damage/perishability/obsolescence and finally, inventory costs from variability in

crossing times. The last cost category arises when shipper’s buffer time windows are

not included as part of trip planning or when planned buffers fall short of the

statistically estimated buffer window. The cost to carriers comprises time variable

costs and relate to labor costs and vehicle operating costs.

Advances in the use of archived innovative data to quantify performance measures

communicating ‘delay” in the border crossing process for assessing near real time

trends. The delay measures include minimum, mean and 95th

percentile crossing

times. A buffer time is developed to reflect trip reliability and the time cushion

needed to ensure on-time arrival.

Additionally, given the levels of uncertainty stemming from a variety of sources, risk

analysis via Monte Carlo simulation and sensitivity analysis are integral parts of this tool. The

analysis allows 90 percent confidence levels as part of the cost assessment process. Finally,

DCET is a highly transparent tool since default parameters and values may be viewed and

updated.

The methodology for cost assessment adopted in this research is based on the factor cost

method that involves identifying the components of vehicle costs, which vary with the amount of

elapsed time (mostly wages, interest on capital employed or tied up in inventory on wheels, and

licensing fees). It also considers inventory costs.


The Bridge of the Americas (BOTA) border crossing was adopted as a case example to

illustrate the assessment of delay measures and cost implications. This choice of port of entry

does not impact the validity of the application in any way. BOTA was selected for illustration

because it provides a unique opportunity to draw upon near real time and archived radio

frequency identification (RFID) data on bridge crossing times. RFID data for the duration July

through September 2009 in the northbound direction from Mexico to the United States were used

in this report.

The value of high quality of data is important since the economic analysis is highly

dependent on primary and secondary data sources to establish defaults and trends. At the front

end, high quality crossing time data should allow improved delay performance measures. In

regard to economic assessments, the research shows that direct costs of variability can be rather

high for those in just-in-time systems and more than twice the cost of wages and other operating

costs. In the case of BOTA northbound flows, the total daily costs for shippers and carriers

jointly are estimated at $17,452 (delay evaluated relative to the mean) in the year 2009. These

are direct variable costs to shippers and carriers. The cost per hour per truck for labor and other

variable costs (not including other costs) is estimated at $39. The broader economic

implications, administrative costs and social costs were not considered in this research.

Economic costs and economic implications are important. Policy initiatives impacting delays

must consider the balance. Security is critical at the borders, and a variety of other operational

strategies may be adopted to manage delays but economic consequences are sometimes non-

trivial. Hence, a balance must be struck.

Center for International Intelligent Transportation Research

Texas Transportation Institute Page 3

CHAPTER I: TEXAS PORTS OF ENTRY AND NATURE OF FREIGHT MOVEMENTS IN THE EL PASO-JUAREZ BI-NATIONAL REGION

INTRODUCTION

This research report is an attempt to develop a quantitative assessment of potential economic

impacts to the freight sector from border-related delays and wait times. While border security

practices tend to increase wait times in the larger interest of safety and security of the nation, it is

equally important to obtain an understanding of the potential implications to the freight sector

and passengers from these practices so that appropriate measures may be undertaken at the

border regions. This report focuses on the implications to the freight sector in the El Paso region

with an aim to develop a quantitative simple and transparent model to ascertain the direct impact

on the freight community that could indirectly spillover to the region.

Texas Border Ports of Entry

Figure I-1 shows the location of Texas border ports of entry. El Paso specifically has four

international border ports of entry (POE). Appendix I-A discusses salient aspects of each POE in

El Paso.

Figure I-1. Texas-Mexico Border Ports of Entry (Commercial and Passenger)

(Source: Texas State Comptroller)

http://texas/



Trading Partners and Trade through El Paso Border Ports of Entry

Texas is the United States’ top trading partner both in terms of value and weight of imports

and exports (Figures I-2 and I-3). Of the trade across the US-Mexico border, trade through El

Paso ports ranks second in terms of trade value and fifth in terms of trade weight based on

Bureau of Transportation Statistics, Transborder Statistics (BTS-TBS) 2009 statistics, and the

pattern is similar in 2010. World Trade Magazine, 2010, also notes that El Paso ranks fifth in

land trade compared to all major US-foreign trade gateways and points out that 25 percent of all

US-Mexico trade crosses through the El Paso ports. The BTS data, however, suggests that

approximately 18-19 percent of all US-Mexico trade crosses through the El Paso ports. The

largest volume of trade passes through the Laredo ports both by value and weight. This pattern

has been holding steady over the past few years, as Figures I-4 and I-5 clearly show. Texas ports

jointly process more that 80 percent of the total value of US-Mexico trade compared to other

ports. Table I-1 shows the volumes of trucks moving through all US-Mexico ports, with Texas

ports covering 67 percent of all commercial freight volumes. Figure I-6 shows Laredo ports

servicing the highest volumes of commercial traffic at 50 percent in 2010, followed by El Paso

ports at 22 percent.



Figure I-2. Top Trading Partners (by Value and Weight − 2009) (Source: BTS-TBS)

-

–



Figure I-3. Top Border Port Trading Partners (by Value and Weight − 2009)

–

–



Figure I-4. Total Trade Flows for US-Mexico Ports (2005-2008) (Source: Texas Center for

Border Enterprise and Economic Development (TCBEED; texascenter.tamiu.edu)

Figure I-5. Quarterly Trade Flows for US-Mexico Ports (2008) (Seasonal Peaks) (Source:

Texas Center for Border Enterprise and Economic Development (texascenter.tamiu.edu)



Table I-1. Truck Volumes through All US-Mexico Ports of Entry (2010)

Port Name Year Trucks Percentage Percentage

AZ:Douglas 2010 25,504 0.5%

AZ:Lukeville 2010 90 0.0%

AZ:Naco 2010 2,512 0.1%

AZ:Nogales 2010 307,510 6.5%

AZ:San Luis 2010 37,103 0.8%

AZ:Sasabe 2010 0 0.0%

Arizona total:

7.9%

CA:Andrade 2010 342 0.0%

CA:Calexico 2010 0 0.0%

CA:Calexico East 2010 303,552 6.4%

CA:Otay Mesa 2010 729,605 15.4%

CA:San Ysidro 2010 0 0.0%

CA:Tecate 2010 55,208 1.2% California: 23%

NM:Columbus 2010 8,411 0.2%

NM:Santa Teresa 2010 78,879 1.7%

New Mexico:

1.8%

TX:Brownsville 2010 207,408 4.4%

TX:Del Rio 2010 55,852 1.2%

TX:Eagle Pass 2010 95,028 2.0%

TX:El Paso 2010 710,363 15.0%*

TX:Fabens 2010 0 0.0%

TX:Hidalgo 2010 459,331 9.7%

TX:Laredo 2010 1,585,682 33.4%

TX:Presidio 2010 9,298 0.2%

TX:Progreso 2010 43,327 0.9%

TX:Rio Grande City 2010 21,503 0.5%

TX:Roma 2010 6,417 0.1% Texas: 67.3%

Total 2010 4,742,925

* The highlighted categories show the regions with highest percentage of truck crossing volumes.



Figure I-6. Truck Volumes Serviced through Texas Ports of Entry (2010)

Understanding the Nature of Freight Movements in the El Paso-Juarez Bi-National Region and Other Ports – Regional Integration Perspectives and Gateway Corridor Types

The majority of freight shipped through the El Paso-Ciudad Juarez POE system is

maquiladora trade. A maquiladora plant is a manufacturing facility located in Mexico that

temporarily imports materials for assembly on a duty-free basis, provided the product is re-

exported. This arrangement has evolved into a system of transfer stations, distribution centers

and warehouses on the United States side of the border, and manufacturing plants in Mexico.

Below are two perspectives on ports of entry that are important to consider in any quantitative

assessments of potential economic implications of delays. The first viewpoint is one of the

patterns of regional integration that exist across border city pairs, including the El Paso-Juarez

region. The second viewpoint is one that pertains to the nature of movements across the ports of

entry and delay within the context of supply chain processes.

TX:Brownsville 7%

TX:Del Rio 2% TX:Eagle Pass

3%

TX:El Paso 22%

TX:Fabens 0% TX:Hidalgo

14%

TX:Laredo 50%

TX:Presidio 0%

TX:Progreso 1%

TX:Rio Grande City 1%

TX:Roma 0%

Truck Volumes through Texas Ports 2010



A Regional Economic Integration Perspective (Hansen, 2001) (1)

Hansen notes that border cities appear to specialize in different tasks. Small border cities,

such as Nogales in Arizona and Laredo in Texas, are mainly transshipment points in North

American trade, while large border cities, such as San Diego, California, and El Paso, Texas, are

major manufacturing sites. Smaller U.S. border cities function as intermediaries in U.S.-Mexico

trade, providing transportation and distribution services. This specialization pattern may be

determined, in part, by geography and preexisting supply networks. Laredo, for instance, is

located on Interstate Highway 35, which is the major roadway linking Mexico to the eastern

United States. It is perhaps not too surprising that intermediary services on the border expand

with Mexican exports to the United States. Hansen also notes that there is anecdotal evidence

that maquiladoras are an important source of demand for the output of manufacturing firms in

U.S. border cities. Reports in the Twin Plant News, a trade publication that covers U.S. border

industry, suggest that a large fraction of manufacturers in El Paso, McAllen, and Brownsville

supply maquiladoras in Mexico with parts and components for the assembly of apparel,

automotive products, and electronic appliances. These manufacturing activities represent a

specific segment of the production process activities closely tied to product assembly.

This line of research suggests that POE’s can be differentiated along lines of freight activity

they support: manufacturing as in El Paso Ports (McAllen and Brownsville) and intermediary

goods transshipment as in Laredo. Regional integration suggests that futures for immediate

neighbors in border pairs are connected. An impact on export manufacturing south of the border

has effects on the economy in the neighboring border city. Degree indicates the strength of that

effect. In the case of North America, Mexico’s largest trading partner, the degree of integration

is gradually increasing and based on access. US-Mexico border trade is currently somewhat less

integrated than US-Canada trade.

The implication is that cross-border trade, and across border city pairs occurs within

regionally integrated systems and border delays must be considered in that specific context. At

the least, this theory would suggest that the more regionally integrated the trade, the greater the

potential broader economic implications and consequences from trade disruptions for tariff, non-

tariff barriers and transportation disruptions. However, that said, it remains a changing dynamic.

Cambridge Systematics Study (2007) (2)

According to a more recent North American Free Trade Agreement (NAFTA) study report

by Cambridge Systematics et al. (2007), border POE’s in Texas serve as intermediate activity

centers in typically much longer distance moves between Mexican and U.S. origins and

destinations. Texas gateway communities—including their Mexican counterparts—typically

function in one of two ways in NAFTA supply chains—either as a support center for

transportation of locally produced manufactured goods or as an intermediate service center for

goods transported long distances. El Paso and McAllen are the best examples of the first type of

gateway community—supporting local manufacturing in the fast-growing maquillage production

cities of Ciudad Juarez, Chihuahua, and Reynosa, Tamaulipas, respectively. Laredo and Eagle

Pass typify the long-distance service center typology. In most of these cases, warehouses and

industrial distribution centers are located on either side of the border. Upon arrival in the border

community southbound truck shipments, for example, are typically dropped in industrial parks



from which they are subsequently transferred across the U.S.-Mexico border by a local drayage

carrier to a similar transfer or warehousing or manufacturing facility on the Mexican side. The

same is true of northbound moves—which are typically dropped off by a Mexican long-haul

carrier at a brokerage warehouse in Mexico and then drayed to a similar facility on the U.S. side

where a U.S. long-haul carrier retrieves the load and travels northward. Laredo is the best

example of this type of move. Manufacturing-based gateway communities such as Ciudad

Juarez or Reynosa generate fewer long-haul moves because the manufacturing or distribution

activities occur near the border and serve growing urban populations (the Lower Rio Grande

Valley and El Paso regions are home to more than 1 million and 750,000 residents, respectively).

The report also notes that most long-haul freight that moves through El Paso heads to the West

Coast.

As it pertains to delays and freight movements, the Cambridge Systematics study points out

the following:

Trucking companies, brokers, and shippers realize that border congestion is an inevitable

part of doing international business. Border delays differ at each port of entry, but are

generally longer during peak crossing periods. At the crossings near Reynosa and Juarez,

for example, the border delays correspond to production shifts at large border maquilas.

Because the border crossing is part of the production supply chain infrastructure, the

delays are tolerated and there is not yet enough delay to adversely affect production to the

degree manufacturers would be spurred to action. Final assembled products travel north

into the United States to a distribution center in the border region or other large Texas

City. Southbound raw materials are either shipped directly to Mexican destinations or

they are temporarily stored in warehouse facilities north of the border for shipment

consolidation.

A dray operator is typically used to move the shipment through the border for both

northbound movements to US or southbound to Mexico. When maquila facilities are

close to the border (Juarez or Reynosa, for example) southbound industrial inputs are

transported by dray operators through the border directly to maquiladora facilities. These

dray trips average 30-40 miles in between warehouse/transfer and manufacturing

facilities. Long-haul trips (Guadalajara or Puebla, for example) are transferred to

Mexican long-haul carriers from dray operators after crossing the border. According to

interviewees in the Cambridge study (5), raw materials bound for maquila facilities

account for the majority of southbound NAFTA trips, with the remaining shipments

comprised of consumer goods and general merchandise destined for interior Mexico. In

both cases, shipments typically originate in the Midwest or the Southeast United States.

Southbound commodities and assembly inputs originating in the United States commonly

include automotive components from the Midwest, electrical components from the East

Coast, textiles, aluminum, and steel. From overseas, paper, packaging materials and

chemicals, heavy machinery and building materials. Northbound movements from

Mexico include finished products include computers, auto parts, appliances, frozen and

fresh produce, building materials such as lumber and stone, and a small percentage of

handicrafts.



Both these studies suggest that freight movement patterns are significantly different across

POE’s. The critical identifiers across POE’s are:

The type of gateway corridor.

Types of commodities traversing the border.

The direction of movement with northbound flows comprised of finished goods and

southbound toward Mexico characterized by intermediate goods.

In regard to El Paso POE, the researchers have noted that:

The freight movements support the manufacturing process.

The trip lengths associated with border crossing movements are very short-haul

movements from the wholesale transfer facilities on either side of the border. Despite

part of a longer supply chain originating in different parts of the country, the movements

around the border maquilas are typically self-contained.

Delays might be tolerated within bounds because of the short-haul trip nature and

because of the stage of the production supply chain that is involved in these movements.

Kristjansson et al. (2010) (3)

In the context of regional integration, Kristjansson et al. evaluate intra-industry trade along

two cross-border trade gateways (Cascade Gateway and Great Lakes Corridor) along the US-

Canadian border by way of the Grubel Lloyd index. One of their key findings based on the

index is that the Great Lakes corridor is more integrated than the Cascade Gateway and much

more reliant on truck transportation, making the corridor even more vulnerable to delay related

economic costs and uncertainty in crossing times. While it is a well-accepted point that regions

are regionally integrated in various degrees, this article shows that individual corridors may

themselves vary in levels of intra-industry trade and extent of regional integration.

A central thesis emerging from these studies is that levels of regional integration are strongly

correlated with extent of economic impact—in this case, economic implication from frictions or

delays at the border. While individual corridors have not yet been evaluated for levels of

regional integration along the US-Mexico border, there is evidence that indicates that United

States’ trade with Mexico is much less regionally integrated than with Canada.



CHAPTER II: EL PASO PORTS OF ENTRY AND BORDERS AS COMPONENTS OF TRANSPORT COSTS AND ECONOMIC COSTS

PORTS ARE NOT IDENTICAL

Economic implications of delays and improvements to port infrastructure are all strongly

related to what is moved and the nature of those movements. This is especially true for direct,

indirect as well as induced effects of border inefficiencies. There are several freight related

POE’s along the Texas-Mexico border. Along the El Paso portion of the US-Mexico border, a

length of approximately 45 miles, there are six ports-of-entry. Of these, only two ports, Bridge

of the Americas (BOTA) and Ysleta-Zaragoza, handle commercial freight (Figure II-1).

Passenger Ports

• Santa Teresa is located in Doña Ana County, New Mexico. The port of entry is

connected to I-10 via the Pete Domenici Highway. Santa Teresa is a non-tolled facility.

• Paso Del Norte International Bridge (PDN) handles northbound and southbound

automobile and pedestrian traffic. It connects to U.S. 85 via El Paso Street and Santa Fe

Street.

• Stanton Street Bridge lies just east of the Paso Del Norte Bridge. It handles mostly

southbound vehicular traffic but has one northbound Dedicated Commuter Lane.

• Fabens-Casita International Bridge is a small, light-duty bridge constructed in 1938. It

connects to I-10 via FM 1109, Texas 20, FM 76, and FM 793.

Commercial and Passengers Ports

• Bridge of the Americas is the primary port of entry in the El Paso region, handling more

than half of all international crossing traffic (passenger and commercial).

• Ysleta-Zaragoza (Zaragoza) is located in eastern El Paso. It connects to I-10 via State

Highway 375 (North Americas Avenue). This is a tolled crossing and accommodates

both passengers and commercial freight. Commercial vehicles are tolled at $3.50 per

axle, and pedestrians at $0.50. Northbound tolls are 23 pesos for passenger vehicles,

137 pesos for commercial vehicles (five axles), and 5 pesos for pedestrians.



Figure II-1. El Paso Border Ports of Entry

Ports Vary in Terms of Commodity/Trade Profiles

The freight related ports along the border are fundamentally different based on the kinds

of freight movements they service. Figures I-4 and I-5 are indications of how ports can

vary in terms of the value and weight they serve. For instance, Laredo serves high value

cargo and also processes the most cargo by weight. El Paso ports rank second in terms of

value moved but fifth in terms of weight. Laredo and El Paso serve high value

maquiladora shipments. Laredo also serves a large fraction of non-maquila shipments

that were originally under the IMMEX program of Mexico†. Appendix 2 provides

commodity profiles for some Texas ports of entry for both United States exports to

Mexico (southbound flows) and Mexican imports to the United States (northbound

flows). A significant portion of trade flows through El Paso ports (both directions,

northbound and southbound) are maquila-related and a small percentage (<10 percent is

agriculture-based) based on value data from Texas Center for Border Economics and

Enterprise Development (TCBEED). The BTS data based on all traded commodities for

† Currently, however both Programa de Importación Temporal para Producir Artículos de Exportación- PITEX and

IMMEX have merged under the broader regulatory category of IMMEX industry programs (which is more broadly

known as the maquiladora industry) .



2010 provide similar conclusions both in terms of value and weight. The value and

weight profiles for El Paso ports are shown below in Figures II-2 (Total Import Weight

Traded 2.9 million in US Short Tons or 2.6 billion Kilograms), II-3 (Total Import Value

$27.2 billion), and II-4 (Total Export Value at $21 billion) and provide an indication of

the industries being served. In fact, based on the full value and weight profile of all

traded commodities, the following broad distribution of commodities appears to traverse

through El Paso ports:

o Manufacturing (maquila) (primarily intra-industry trade), Manufacturing

(non-maquila), small percentage of agriculture, apparel and other

products.

Figure II-2. El Paso Ports’ Imports Weight Profile (2010) (US-Mexico Imports—

Northbound Flows) (Top Ten of 98 Truck Traded Commodities) (Source: BTS-TBS and

Weight in US Short Tons)

Electrical Machinery; Equipment and

Parts, 26.7%

Computer-Related Machinery and Parts,

19.3% Vehicles Other than Railway, 7.2%

Ceramic Products, 6.1%

Furniture; Lamps and Prefabricated

Buildings, 5.3%

Special Classification Provisions, 4.2%

Plastics and Articles, 3.6%

Sugars and Sugar Confectionery, 2.8%

Measuring and Testing Instruments,

2.1%

Wood and Articles, 1.9%

, 0 , 0 , 0 , 0



Figure II-3. El Paso Ports’ Imports Value Profile (2010) (US-Mexico Imports—

Northbound Flows) (Top Eleven of 87 Truck Traded Commodities) (Source: BTS-TBS)

Figure II-4. El Paso Ports’ Exports Value Profile (2010) (Top Eleven of 93 Truck Traded

Commodities) (Source: BTS-TBS)

Electrical Machinery; Equipment and Parts, 42.97%


25.89%


8.73%

Furniture; Lamps and Prefabricated

Buildings, 5.34%

Vehicles Other than Railway, 5.06%

Special Classification Provisions, 3.30% Not Knitted or

Crocheted Apparel, 1.42%

Plastics and Articles, 1.21% Other Made up

Textile Articles, 0.48%

Impregnated Fabrics, 0.46%

Electrical Machinery; Equipment and

Parts, 36.0%


23.2%

Plastics and Articles, 7.8%


5.1%

Copper and Articles, 3.2%

Vehicles Other than Railway, 2.7%

Articles of Iron and Steel, 2.6%

Paper and Paperboard, 2.2% Aluminum and

Articles, 2.1%

Impregnated Fabrics, 1.2%

Meat and Edible Offal, 1.2% Dairy Products, 0.9%



Ports Vary in Terms of Transport Corridors They Serve

Mexico has four major transportation corridors: the Pacific, Chihuahua, Central and Gulf

Coast. The El Paso ports serve the Chihuahua corridor that historically has been more significant

for maquila trade. The Laredo crossing serves the Central Trade Corridor that is the most

significant non-maquila corridor‡.

Ports Vary in Terms of How They Move Goods

Transport Components of Supply Chain Processes across Ports of Entry in Texas

Transportation components of supply chain processes at work are of equal importance while

attempting to understand any direct and broader economic implications from delays. Not all

ports are identical in terms of the linkages they serve and/or the types of transport chains that

have emerged/evolved in these regions over time. The supply chain for freight entering the U.S.

from Mexico is a rather complicated one, because Mexican trucks are currently not permitted by

law to operate beyond a 20-mile zone extending from the U.S.-Mexico border. Typically, goods

coming from the interior regions of Mexico are shipped to a warehouse near the border, where

they are offloaded into a warehouse. These warehouses are often owned by customs brokers or

freight forwarders. Once paperwork is submitted for the goods to clear customs, a drayage

carrier is notified to pick up the goods so the border crossing process can begin. Once the

drayage carrier completes the inspection processes on both sides of the border, it delivers the

goods to a warehouse on the U.S. side of the border (located within the 20-mile zone mentioned

previously). At this point, the goods are ready to be transported by a U.S. carrier to their

ultimate destination within the U.S. Figure II-5 below is a graphical representation of this

process and is most representative of the second type of long-distance service center gateway

corridor (Laredo, Eagle Pass). In such cases, there are possibilities of a bottleneck in one part of

a transport chain to spill over to other parts with a cumulative effect.

‡ U.S.-Mexico Trade and Transportation: Corridors, Logistics Practices, and Multimodal Partnerships, LBJ School

of Public Affairs, Policy Research Paper 113, 1995.



Figure 0-5. Mexican Import Supply Chain (Shipments Originating in Mexico’s Interior)

Not all of the shipments transiting through Laredo and Eagle Pass gateways are maquila. A

large part of the shipments coming from inner Mexico regions are non-maquila type trade. On

the other hand, a large majority of freight shipped through the El Paso-Juarez POE system is

maquiladora trade. Figure II-6 below is a graphic representation of maquiladora trade supply

chain (in El Paso, Texas.). Essentially, this movement may be considered a self-limiting part of

an entire flow. Consequently, economic consequences may also be self- limiting even for a

fairly regionally integrated system. This, however, will not be the case for more integrated

supply chains or integrated systems, where a shock in one segment could have a ripple effect on

other related moves.



Figure II-6. Maquiladora Supply Chains, El Paso-Juarez Region

PORTS VARY IN TERMS OF FINAL DESTINATIONS THEY SERVE/TRADING PARTNERS (TRUCK TRADE FLOW DISTRIBUTIONS)

Understanding the extent of trade is an important component of broader economic

implications. Figure II-7 indicates that a large percentage of imports from Mexico flowing

through El Paso ports remain within Texas (58 percent of total value) and other leading

destinations include Michigan (10.5 percent) and California (6 percent of value). A somewhat

similar distribution emerges by inbound weight flowing through El Paso ports (Figure II-8).



Figure II-7. Top 12 of 48 Trading Partners by Import Value 2010 (Truck Inbound Flows-

El Paso POE’s) (Source: BTS-TBS)

Figure II-8. Top 12 of 48 Trading Partners by Import Weight 2010 (Truck Inbound Flows-

El Paso POE’s) (Source: BTS-TBS)

Texas(USA), 57.7% Michigan(USA),

10.5%

California(USA), 6.0%

Ohio(USA), 3.7%

Minnesota(USA), 2.8%

Pennsylvania(USA), 2.4%

Illinois(USA), 2.1%

Missouri(USA), 1.9%

Florida(USA), 1.6% Wisconsin(USA),

1.6% New Jersey(USA),

1.2% Tennessee(USA),

1.1%

Texas(USA), 51.6%

Michigan(USA), 9.1%

California(USA), 5.9%

Connecticut(USA), 3.5%

Pennsylvania(USA), 3.1%

Ohio(USA), 3.0%

Minnesota(USA), 2.9%

Wisconsin(USA), 2.7%

Illinois(USA), 2.0%

Missouri(USA), 2.0% New Mexico(USA), 1.9% Georgia(USA), 1.2%

Massachusetts(USA), 1.2%



BORDERS AS COMPONENTS OF TRANSPORT COSTS AND LINKS TO LOGISTICAL EFFICIENCY

Moving commodities across national borders can add costs (sometimes quite significant) to

freight shipments between countries. These additional transportation costs result from several

policy aspects including procedural, infrastructural, and political difficulties often encountered in

the border clearance process (Anderson and van Wincoop, 2001, Beilock et al., 1996 (4, 5)).

Costs associated with passing through border gateways include congestion and transit delays that

stem from the processing capacity of crossing checkpoints, increased security inspections,

customs clearance, and drayage . It has been noted that as countries enter into trade agreements

with each other, trade facilitation measures become important to facilitate smooth flows of

goods. Border-related processes are often viewed as a trade facilitation measure (Matisziw, 2005

(6). For a more regionally integrated trade like US-Canadian trade, Anderson and van Wincoop

(1) estimate that border-related barriers can be equated to a tariff of 50 percent and that if such

barriers are removed, a trade increase of up to 79 percent could result. For freight shipments,

issues involved in crossing international borders translate into increased transportation costs. As

stated in Fox et al. (2004) (7), and Haralambides et al. (2004) (8) , given the shipping/handling

fees paid at border crossings, a very small span of road may economically become the

geographic equivalent of several hundred miles, especially in the case of supply chain processes

characterized by long-haul movements and with links to intermodal transfers.

Factors Causing Delays

Matisziw (6) provides an excellent discussion on various aspects leading to delays. He notes

physical factors such as:

design and layout of checkpoints,

lack of adequate facilities to handle intermodal cargo transfers,

number of open inspection and processing stations,

limited capacity of road lanes on the approach (and departure) to the crossings,

and sometimes,

inadequate capacity to process vehicles. Also, noted in this category are

topographic conditions surrounding border crossings as in Arizona.

Matisziw notes note that these types of physical limitations tend to exacerbate traffic

problems and delays.

A second factor that is responsible for delays could be a slowdown in one of the various steps

involved in the crossing process. Figure II-9 shows the various steps and a breakdown in any

stage that can lead to delays. Figure II-10 is a schematic of the crossing process from a 2002

Texas Transportation Institute (TTI) study (Ojah,, 2002) (9).



Figure II-9. Typical Border Crossing Stages for US-Mexico Border Crossings (Source,

Matisziw, 2005)



Figure II-10. Border Crossing Stages for US-Mexico Border (Source: Ojah et al., TTI

Report 2002)

A third aspect cited as a contributory factor is procedural aspects. For instance, trucks must

pass through security and customs inspections along with processing of documents, which adds

to delays. These procedural and security aspects increased after September 2001. Matisziw

notes that lack of good interagency coordination/cooperation and information sharing increases

process times.

Other factors cited include capacity related issues like hours of operation in dealing with

secondary inspections (Matisziw, 2005 (6); Taylor et al., 2003 (10)), inadequate staffing and a

general notion that shipping speed is not critical.



Prior Literature, Perspectives in Assessing Economic Costs of Delay

Based on what has been discussed, economic costs of delays must be motivated within the

broader context of regionally integrated trade (which could be corridor-region specific) and

supply chains of goods transiting national borders. Much of the literature attempting to focus on

economic costs of delay fails to take into account these aspects. Based on a prior literature

review report, Table II-1 summarizes the specific context or approach within which economic

costs were examined.



Table II-1. Summary of Perspectives Adopted in Assessing Economic Costs of Delay

Authors Approach Costs Region Aspects Considered

Ojah et al.

(2002) (9)

Factor cost/Direct costs

Social Cost

Congestion delays to

others in queue.

(Focus on effects of

coordination to one or

more stakeholders)

Direct- Inputs and

Environment

Delay data, fuel

prices, literature,

time valuation,

pollution costs.

Several Ports

along US-

Mexico

Border

Delay is measured as

excess over free flow time

with travel time data

collected from surveys.

Use of Highway Design

Model to obtain vehicle

operating costs. Emission

cost monetary values from

Wang and Santini's study.

HLB Decision

Economics

(2006, 2007–

Mexicali):

Economic

Impacts &

True North

(11-17)

Static/Microeconomic

−Partial equilibrium

perspective

Indirect costs −

output and

employment costs

(macroeconomic)

Mexicali Cargo type

Directional aspect.

Delays treated as a cost

increase.

Risk analysis.

Direct, indirect and

induced effect

FAST lanes.

HLB (2004)

(Detroit–

Windsor

[D-W]) (18)

Same as HLB 2006, 2007

Indirect costs

(macroeconomic)

Detroit-

Windsor

Use of STRATBENCOST

to develop volume and

time forecasts for analysis

of three bridges at the D-W

border.

Belzer, 2003

(19, 20)

Factor costs Direct Ambassador

Bridge and

other bridges

Operating costs for trucks

valued at $2.32 per minute

and inventory transit costs.

RTI

International

(2007) (21)

Similar to HLB studies

Indirect costs

(macroeconomic)

FAST lanes,

Nogales,

Arizona

Impact of the FAST lanes

is the specific analysis goal

(FAST lanes introduced in

Nogales, in 2006)

Taylor et al.

(2003) (10)

Administrative costs

perspective

Agency costs and

other administrative

crossing costs from

uncertainties and

delays (fees, duties)

General Carrier costs and

manufacturer/shipper

costs

OCC (2004)

(22,23)

Similar to HLB Canadian

context

Goodchild et al.

(2007) (24)

Variability in delays

No costs Specific

Gateways

No economic costs

reported. Links delay

variability to output

elasticity

Kristjansson et

al. (2010) (3)

Regional integration-

intra-industry trade

(Grubel Lloyd Index)

(GLI)

No costs Specific

Gateways;

Cascade

Gateway,

Great Lakes

Corridor

Implications of variations

in GLI across corridors to

economic costs of delays.

No actual cost analysis

conducted.

Fischer, 2010

(Cambridge

Systematics)

(25)

Vehicle hours traveled

(delay) and partial

equilibrium methods

Indirect costs

(macroeconomic)

Canadian

context

Actual estimates of delays

not reported.

Methodology discussed.



Table II-2. Additional Perspectives on Wider Economic Implications and

General Port Efficiencies

Authors Approach Implications

Limao and Venables

(1999) (26)

10% increase in

transport costs

associated with 20%

reduction in trade

volume.

Trade: Indirect benefit

Hummels (2001) (27) Inventory costs due

to transport delays

equivalent to 0.8%

per day of delay of

the value of goods

delivered.

Inventory management:

Direct cost from

uncertainties.

Kent and Fox (2004)

(28)

Effects of port

inefficiency on

welfare

Applicable to ports like

Laredo that are associated

with longer haul moves.

Haralambides and Kent

(2004) (8)

Effects of port

inefficiency on

welfare

Applicable to ports like

Laredo that are associated

with longer haul moves.

Huang and Whalley

(2008) (29)

Effects of port

inefficiency on

welfare

Added inventory costs

directly related to variance

of delays. Under certainty,

time costs are equal to

inventory costs but under

uncertainty, inventory costs

are much higher.

Types of Economic Costs

The literature is clear in identifying at least five types of costs, as seen in Tables II-1 and II-2.

These include:

Direct costs owing to factors often assessed using factor cost methods.

Administrative costs stemming from delays to agencies and stakeholders. Taylor et al.

adopt this approach.

Indirect costs or broader economic costs (partial equilibrium, general equilibrium

approaches). Each approach makes implicit assumptions on trade relations between

trading partners and on output responses with partial equilibrium methods typically

having an upward bias in relaying effects of shocks.

Social cost-environmental cost and includes costs stemming from emissions from trucks.

Finally, there are further direct costs that accrue from more integrated systems from

inventory management in just-in-time systems and costs from multi-modal transfers.



CHAPTER III: EL PASO FREIGHT MOVEMENTS

FREIGHT MOVEMENT TRENDS – EL PASO PORTS OF ENTRY

El Paso, Texas, is currently the sixth largest city in the state of Texas and the twenty-first

largest city in the United States. Ciudad Juarez, El Paso’s sister city across the border, is the

largest city in the state of Chihuahua and the fifth largest city in all of Mexico. The metropolitan

area of Ciudad Juarez and El Paso, Texas, comprises more than 2.2 million people, making it the

largest bi-national metropolitan area in the world. The large population is mostly due to the

amount of jobs that the local manufacturing industry in the region produces. These

manufacturing facilities, often referred to as “maquiladoras,” not only produce jobs but also

produce goods that are ultimately shipped to and from the United States of America in

significant volumes. Following the implementation of NAFTA, trade between the United States

and Mexico increased substantially. The tables that follow show the trade patterns through El

Paso Ports of Entry. The trends reflect trade through all ports of entry in the El Paso Bi-National

Region and not of single POE. Table III-1 and Figures III-1 and III-2 indicate the trade trends by

value and weight through the El Paso POE’s with the entire United States and with Texas alone.

With the exception of a dramatic change in weight profile of imports (inbound into the United

States) from 2003 through 2007, the patterns of value and weight are generally similar. This

could be due to a shift in distribution of composition of goods, or a variety of other

considerations.

Center for International In

telligent Transportation R

esearch

Texas T

ransportation Institute

P

age 28

Table III-1. Imports Total Weight by Land Mode (Trade with USA and Texas) (Value and Weight)§

Year Trader Partner

Port/District

Code

Port/District

Description

Imports Value by Truck

(US Short Tons)

Imports

Weight by

Truck (US

Short Tons) Trader

Imports Value by

Truck

Imports Weight by

Truck (US Short

Tons)

1995 USA MEXICO 2402 El Paso - Texas $11,815,007,045 1,453,483 Texas $5,253,472,161 769,132

1996 USA MEXICO 2402 El Paso - Texas $11,601,370,475 1,938,915 Texas $5,635,791,343 1,050,210















§ Source; BTS-Transborder Statistics.


Figure III-1. Trends in Import Value through El Paso Ports of Entry (with USA and with

Texas Alone)

Figure III-2. Trends in Import Trade Weight through El Paso Ports of Entry (with Entire

USA and with Texas Alone) (Short Tons)

$0

$5,000,000,000

$10,000,000,000

$15,000,000,000

$20,000,000,000

$25,000,000,000

$30,000,000,000

1995 1997 1999 2001 2003 2005 2007 2009

Imports Value byTruck_Entire USA

Imports Value byTruck_Entire Texas

Linear ( Imports Value byTruck_Entire USA)

Linear ( Imports Value byTruck_Entire Texas)

0

500,000

1,000,000

1,500,000

2,000,000

2,500,000

3,000,000

3,500,000

4,000,000

1995 1997 1999 2001 2003 2005 2007 2009

Imports Weight by Truck (USShort Tons)_Entire USA

Imports Weight by Truck (USShort Tons)_Entire Texas

Linear ( Imports Weight byTruck (US Short Tons)_EntireUSA)

Linear ( Imports Weight byTruck (US Short Tons)_EntireTexas)


Table III-2. Northbound Crossing Volumes (Trucks) (El Paso Ports of Entry) and by

Loaded or Empty

Port Year

Trucks

(Number)

Bridge of

America

(BOTA) Ysleta

Loaded Truck

Containers

(Number)

Empty Truck

Containers

(Number)

TX:El Paso 1995 606,742 296,000 281,000 NA NA

TX:El Paso 1996 556,134 245,000 340,000 280,867 287,479

TX:El Paso 1997 582,707 308,000 289,000 297,663 296,006

TX:El Paso 1998 605,980 312,000 294,000 256,236 163,036

TX:El Paso 1999 673,003 343,000 329,000 360,982 305,394

TX:El Paso 2000 720,406 363,000 365,000 361,412 326,812

TX:El Paso 2001 660,583 335,000 330,000 360,517 306,638

TX:El Paso 2002 705,199 375,000 329,000 382,193 332,738

TX:El Paso 2003 659,614 346,000 314,000 368,562 296,860

TX:El Paso 2004 719,545 383,000 337,000 409,093 308,152

TX:El Paso 2005 740,654 393,000 341,000 430,768 304,083

TX:El Paso 2006 744,951 373,000 371,000 418,026 339,769

TX:El Paso 2007 782,936 398,000 382,000 402,456 356,863

TX:El Paso 2008 758,856

316,731 315,947 384,586 367,988

TX:El Paso 2009 644,272

316,731 315,947 336,119 303,777

SOURCE: U.S. Department of Transportation (USDOT), Research and Innovative Technology Administration, Bureau of Transportation

Statistics, Border Crossing/Entry Data; based on data from U.S. Department of Homeland Security, Customs and Border Protection, Operations Management Report database. The University of Texas at El Paso (University of Texas El Paso) Border Region Modeling

Project.

The total number of trucks crossing the ports from Juarez shows a steady incremental rise

with a dip in 2009 reflective of the recession. The total number is nearly evenly distributed

between the Bridge of the Americas and Ysleta Bridge. The splits between loaded and unloaded

truck containers show a large percentage of empty trucks transiting the ports. From an economic

standpoint, empty trucks are reflective of a pickup/delivery system and need to be treated

differently relative to loaded carriers.


Table III-3. El Paso Ports Import Classification and Value (2010)**

Commodity Code Commodity Description 2010 Percentage of Total Import

1 Live Animals $3,000 0.0%

3 Fish and Crustaceans $2,705 0.0%

4 Dairy Products $675,382 0.0%

5 Products of Animal Origin $2,277,675 0.0%

6 Live Trees and Plants $258,439 0.0%

7 Edible Vegetables and Roots $14,365,683 0.1%

8 Edible Fruit and Nuts $116,794,167 0.4%

9 Coffee; Tea and Spices $921,026 0.0%

10 Cereals $10,154 0.0%

11 Malts; Starches and Inulin $388,347 0.0%

12 Oil Seeds and Oleaginous Fruits $196,477 0.0%

14 Vegetable Plaiting Materials $127,001 0.0%

16 Preparations of Fish and Meat $3,427,461 0.0%

17 Sugars and Sugar Confectionery $49,897,376 0.2%

18 Cocoa and Cocoa Preparations $14,545,289 0.1%

19 Preparations of Cereals and Flour $19,920,538 0.1%

20 Preparations of Vegetables; Fruits and Nuts $19,308,834 0.1%

21 Miscellaneous Edible Preparations $898,630 0.0%

22 Beverages; Spirits and Vinegar $1,872,182 0.0%

23 Food Residues and Waste $23,665 0.0%

25 Salt; Sulfur; Plaster and Cement $2,938,182 0.0%

26 Ores; Slag and Ash $11,193 0.0%

27 Mineral Fuels; Oils and Waxes $347,079 0.0%

28 Inorganic Chemicals $10,296,191 0.0%

30 Pharmaceutical Products $8,398,650 0.0%

31 Fertilizers $880,601 0.0%

32 Tanning or Dyeing Extracts $564,018 0.0%

33 Essential Oils and Resinoids $791,387 0.0%

34 Soap and Organic Surface-Active Agents $11,183,301 0.0%

35 Albuminoidal Substances; Glues and Enzymes $49,831 0.0%

36 Explosives $649,421 0.0%

37 Photographic Goods $382,835 0.0%

38 Miscellaneous Chemical Products $32,471,973 0.1%

39 Plastics and Articles $329,079,049 1.2%

**

BTS-TBS Data and 2-digit commodity codes as defined by BTS. These are northbound flows from Mexico to

United States.


Table III-3. El Paso Ports Import Classification and Value (2010)†† (continued) Commodity Code Commodity Description 2010 Percentage of Total

40 Rubber and Articles $101,930,921 0.4%

41 Raw Hides and Skins $8,399,698 0.0%

42 Articles of Leather and Handbags $5,054,872 0.0%

43 Furskins and Artificial Fur $1,208 0.0%

44 Wood and Articles $62,730,334 0.2%

47 Pulp of Wood and Paperboard $1,401,108 0.0%

48 Paper and Paperboard $83,986,751 0.3%

49 Printed Books $75,800,657 0.3%

52 Cotton $1,470,664 0.0%

54 Man-made Filaments $2,951,932 0.0%

55 Man-made Staple Fibers $1,054,544 0.0%

56 Wadding; Felt and Nonwovens $15,382,943 0.1%

57 Carpets and Other Textile Floor Coverings $190,308 0.0%

58 Special Woven Fabrics $2,243,501 0.0%

59 Impregnated Fabrics $124,937,859 0.5%

60 Knitted or Crocheted Fabrics $195,738 0.0%

61 Knitted or Crocheted Apparel $74,376,453 0.3%

62 Not Knitted or Crocheted Apparel $387,018,098 1.4%

63 Other Made up Textile Articles $130,098,548 0.5%

64 Footwear $7,580,074 0.0%

65 Headgear $1,298,161 0.0%

66 Umbrellas and Walking Sticks $148,151 0.0%

67 Feathers and Down $6,341 0.0%

68 Stone; Plaster; Cement and Asbestos $31,767,316 0.1%

69 Ceramic Products $37,894,499 0.1%

70 Glass $40,882,410 0.2%

71 Pearls; Stones; Metals and Imitation Jewelry $14,239,047 0.1%

72 Iron and Steel $13,745,410 0.1%

73 Articles of Iron and Steel $87,341,056 0.3%

74 Copper and Articles $40,785,155 0.2%

75 Nickel and Articles $795,991 0.0%

76 Aluminum and Articles $115,592,924 0.4%

78 Lead and Articles $858,313 0.0%

††


United States.


Table III-3. El Paso Ports Import Classification and Value (2010)‡‡ (continued) Commodity Code Commodity Description 2010 Percentage of Total

79 Zinc and Articles $372,000 0.0%

80 Tin and Articles $1,271,850 0.0%

81 Other Base Metals and Cermets $611,350 0.0%

82 Tools of Base Metal $1,457,264 0.0%

83 Miscellaneous Articles of Base Metals $104,995,101 0.4%

84 Computer-Related Machinery and Parts $7,032,763,057 25.9%

85 Electrical Machinery; Equipment and Parts $11,674,763,562 43.0%

86 Locomotives and Traffic Signals $584,055 0.0%

87 Vehicles Other than Railway $1,374,454,791 5.1%

88 Aircraft; Spacecraft and Parts $39,320,563 0.1%

89 Ships and Boats $8,360,190 0.0%

90 Measuring and Testing Instruments $2,370,886,166 8.7%

91 Clocks; Watches and Parts $34,503,793 0.1%

92 Musical Instruments and Parts $126,357 0.0%

93 Arms and Ammunition and Parts $3,505,220 0.0%

94 Furniture; Lamps and Prefabricated Buildings $1,451,488,208 5.3%

95 Toys; Games and Sport Equipment $37,710,197 0.1%

96 Miscellaneous Manufactured Articles $17,283,986 0.1%

97 Works of Art and Antiques $278,142 0.0%

98 Special Classification Provisions $897,872,636 3.3%

TOTAL $27,168,727,215 100.0%

‡‡


United States.


Table III-4. El Paso Port Export Classification and Value (2010)§§

Commodity Code Commodity Description 2010 Percentage of Total

1 Live Animals $4,851,141 0.0%

2 Meat and Edible Offal $246,555,140 1.2%

3 Fish and Crustaceans $1,902,449 0.0%

4 Dairy Products $184,849,952 0.9%

5 Products of Animal Origin $15,392,651 0.1%

6 Live Trees and Plants $257,877 0.0%

7 Edible Vegetables and Roots $24,580,614 0.1%

8 Edible Fruit and Nuts $65,628,706 0.3%

9 Coffee; Tea and Spices $596,350 0.0%

10 Cereals $6,001,216 0.0%

11 Malts; Starches and Inulin $4,312,701 0.0%

12 Oil Seeds and Oleaginous Fruits $14,270,125 0.1%

13 Lac; Gums; Resins and Saps $52,172 0.0%

14 Vegetable Plaiting Materials $35,670 0.0%

15 Animal or Vegetable Fats and Oils $30,810,045 0.1%

16 Preparations of Fish and Meat $9,088,630 0.0%

17 Sugars and Sugar Confectionery $59,646,667 0.3%

18 Cocoa and Cocoa Preparations $11,012,116 0.1%

19 Preparations of Cereals and Flour $27,588,410 0.1%

20 Preparations of Vegetables; Fruits and Nuts $15,018,552 0.1%

21 Miscellaneous Edible Preparations $37,880,085 0.2%

22 Beverages; Spirits and Vinegar $16,444,818 0.1%

23 Food Residues and Waste $7,824,443 0.0%

24 Tobacco and Manufactured Tobacco $153,928 0.0%

25 Salt; Sulfur; Plaster and Cement $4,049,652 0.0%

26 Ores; Slag and Ash $60,762,287 0.3%

27 Mineral Fuels; Oils and Waxes $140,444,191 0.7%

28 Inorganic Chemicals $24,900,954 0.1%

29 Organic Chemicals $23,167,421 0.1%

30 Pharmaceutical Products $53,307,090 0.3%

31 Fertilizers $2,937,834 0.0%

32 Tanning or Dyeing Extracts $49,241,588 0.2%

33 Essential Oils and Resinoids $6,506,994 0.0%

34 Soap and Organic Surface-Active Agents $20,689,673 0.1%

35 Albuminoidal Substances; Glues and Enzymes $27,680,657 0.1%

§§

Southbound flows from United States to Mexico.


Table III-4. El Paso Port Export Classification and Value (2010)*** (continued) Commodity Code Commodity Description 2010 Percentage of Total

36 Explosives $62,163 0.0%

37 Photographic Goods $39,781,566 0.2%

38 Miscellaneous Chemical Products $49,224,991 0.2%

39 Plastics and Articles $1,640,134,462 7.8%

40 Rubber and Articles $169,182,932 0.8%

41 Raw Hides and Skins $29,377,861 0.1%

42 Articles of Leather and Handbags $33,051,434 0.2%

43 Furskins and Artificial Fur $79,836 0.0%

44 Wood and Articles $61,238,659 0.3%

45 Cork and Articles $41,215 0.0%

47 Pulp of Wood and Paperboard $21,050,859 0.1%

48 Paper and Paperboard $453,054,448 2.2%

49 Printed Books $58,330,869 0.3%

50 Silk $15,160 0.0%

51 Wool and Animal Hair $2,243,987 0.0%

52 Cotton $81,663,210 0.4%

53 Other Vegetable Fibers and Paper Yarn $79,228 0.0%

54 Man-made Filaments $88,002,586 0.4%

55 Man-made Staple Fibers $36,816,256 0.2%

56 Wadding; Felt and Nonwovens $104,832,381 0.5%

57 Carpets and Other Textile Floor Coverings $20,631,409 0.1%

58 Special Woven Fabrics $31,693,187 0.2%

59 Impregnated Fabrics $261,441,836 1.2%

60 Knitted or Crocheted Fabrics $23,356,498 0.1%

61 Knitted or Crocheted Apparel $36,680,680 0.2%

62 Not Knitted or Crocheted Apparel $39,933,076 0.2%

63 Other Made up Textile Articles $46,200,073 0.2%

64 Footwear $447,155 0.0%

65 Headgear $1,594,783 0.0%

66 Umbrellas and Walking Sticks $720,996 0.0%

67 Feathers and Down $231,219 0.0%

68 Stone; Plaster; Cement and Asbestos $23,037,927 0.1%

69 Ceramic Products $20,532,441 0.1%

70 Glass $73,092,864 0.3%

71 Pearls; Stones; Metals and Imitation Jewelry $25,754,700 0.1%

***

Southbound flows from United States to Mexico.


Table III-4. El Paso Port Export Classification and Value (2010)††† (continued) Commodity Code Commodity Description 2010 Percentage of Total

72 Iron and Steel $156,779,489 0.7%

73 Articles of Iron and Steel $541,659,538 2.6%

74 Copper and Articles $677,844,279 3.2%

75 Nickel and Articles $12,543,749 0.1%

76 Aluminum and Articles $436,644,670 2.1%

79 Zinc and Articles $9,723,301 0.0%

80 Tin and Articles $14,851,983 0.1%

81 Other Base Metals and Cermets $20,677,378 0.1%

82 Tools of Base Metal $50,877,969 0.2%

83 Miscellaneous Articles of Base Metals $109,689,443 0.5%

84 Computer-Related Machinery and Parts $4,875,763,075 23.2%

85 Electrical Machinery; Equipment and Parts $7,568,936,682 36.0%

86 Locomotives and Traffic Signals $2,774,547 0.0%

87 Vehicles Other than Railway $565,377,537 2.7%

88 Aircraft; Spacecraft and Parts $54,933,025 0.3%

89 Ships and Boats $143,610 0.0%

90 Measuring and Testing Instruments $1,082,382,595 5.1%

91 Clocks; Watches and Parts $2,193,128 0.0%

92 Musical Instruments and Parts $345,269 0.0%

93 Arms and Ammunition and Parts $2,572,392 0.0%

94 Furniture; Lamps and Prefabricated Buildings $118,578,721 0.6%

95 Toys; Games and Sport Equipment $22,842,336 0.1%

96 Miscellaneous Manufactured Articles $17,276,975 0.1%

97 Works of Art and Antiques $143,215 0.0%

98 Special Classification Provisions $796,649 0.0%

TOTAL $21,020,132,352 100.0%

Imports and exports to the United States—El Paso region in 2010 are predominantly

composed of computer and electronic equipment. Appendix 2 Tables VIII-4 and VIII-8 describe

the breakdowns further based on TCBEED data and indicate that exports are broadly comprised

of parts and intermediate goods, while imports are comprised mostly of parts and finished

consumer durables.

†††

Southbound flows from the United States to Mexico.


PROXIMITY OF MAQUILAS TO BORDER PORTS OF ENTRY

An interesting point to be made is the proximity of Juarez maquiladoras to specific border

ports—more specifically to industrial zones bounded by the Bridge of the Americas and

Zaragoza (shown in Figure III-3). The implications of this location suggest the following:

With current networks, delays and inefficiencies at BOTA and Zaragoza will be of

importance to maquila stakeholders.

One of the major goals of maquilas as profit maximizing entities striving for competitive

positions is the maximization of truck trips (pickups and deliveries) in any given day.‡‡‡

Most of these companies operate short-haul trips with approximately 2-3 round trips (or

4-6 individual crossings per day). This observation is similar to that reported by the 2007

Cambridge Systematics Study.

Figure III-3. Location Distribution of Juarez Maquiladoras Relative to Border Ports of

Entry (Source: http://www.pdnmapa.org/pdnmapa/index.htm)

‡‡‡

Source: Maquila Stakeholder meeting with Cambridge Systematics, TTI in El Paso, November 2010.

http://www.pdnmapa.org/pdnmapa/index.htm


CHAPTER IV: PERCEPTIONS ON BORDER DELAYS: EVIDENCE FROM SHIPPERS IN THE EL PASO JUAREZ REGION

SHIPPER SURVEYS

Shipper interviews were developed to understand the nature of freight movements in the El

Paso-Juarez border region and with intent to understand the implications of border-related

delays. The focus of the interviews was to capture information related to cross-border operations

in the El Paso-Ciudad Juarez region. Interviews were conducted both in person and over the

phone. The actual interview instrument is included in Appendix 3.

Given the characteristics of the border crossing activity, a convenience sample of nine

shippers was selected to analyze border activities. Seven of the eight companies listed below

were maquiladora companies and the actual names are not indicated per Institutional Review

Board guidelines. The selected interviewees comprised of:

Three companies involved in the production of television sets (consumer durables) and

other appliances,

Two companies dedicated to computer parts and components;

One company dedicated to automotive parts production;

One company dedicated to the production of telecommunication devices and one

company dedicated to food production—specifically including refreshments and edible

goods.

One company dedicated to data and information services.

Most of the respondents were certified under Customs-Trade Partnership against Terrorism

(C-TPAT) at the time of the interviews. However, two of the shippers were not certified and had

issues with certification at the time of the interview.

Issues Identified by Shippers

Seasonal Fluctuations and Peak Periods: Maquiladora managers that produce appliances

and electrical components have observed peak crossing wait times at 8:00am and then again

from 3:00pm to 6:00pm, and seasonal peaks from October to November. For those that produce

refreshments, the demand was noted to peak during June to September. For data services, the

peak season was noted to be during the holiday season, while the rest did not observe major

fluctuations.

Contract Terms Do Not Allow Cost-Shifting: In many cases, freight terms are freight-on-

board (FOB) in El Paso warehouses. When cargo arrives in El Paso, costs of delays are a sender

cost typically. Final costs are rarely ever passed on to final consumers.


Average Truck Costs: Shippers provided a range of responses on average per hour truck

costs ranging from $30- $100.

Additional Administrative Fees: In addition, maquiladora senders do incur additional costs

that go from 12 to 100 dollars at customs offices, depending on specific procedures followed

there.

Cross-Cutting Issues: The logistical requirements and complexities faced by businesses and

maquiladoras vary significantly. There are a few cross-cutting issues that emerged frequently in

discussions with shippers and carriers. These issues have important implications for the business

climate and economic future of the region precisely because they bear directly on either the cost

of doing business or the ability to expand business operations to meet the demands of the bi-

national region. The most significant cross-cutting issues include the following:

Unpredictable/Variable Crossing Times are an Issue for Some Shippers. Depending on

the bridge and the hour, most managers agreed that the waiting times can go from

30 minutes to up to five hours. Such delays affect maquiladoras where some managers

usually have to increase the buffer time. Some shippers have adjusted to the delays and

congestion at ports by building in buffer times in their business process. For instance, a

few shippers indicated buffer times from 1 hour to 2 hours in the interviews. This is an

effective strategy, however, given the need to maintain a profit maximizing number of

truck trips the variability in the border crossing process may impact the number of trips.

As trade volumes rise, these variabilities can impose costs on operations.

Increased Costs of Inventory Management and Control for Some Shippers/Businesses.

Most of the efficiencies in supply chain management over the past decade have been

attributable to advances in inventory control and management of materials, components,

and finished goods in the supply chain. Tight inventory controls and accurate accounting

for inventory flows are a factor in both achieving profit margins and, arguably, the ability

of the national and regional economies in many parts of the US to weather business

cycles. However, the effects of delays tend to erode the significant progress made in

inventory management and control by reintroducing uncertainty in shipping and receiving

attributable to the border crossing process. The result can be a fallback to looser

scheduling, lower targets and additional inventory to allow for uncertainty in delivery

time.


Figure IV-1. Typical Supply Chains of Shippers of Respondents Indicating Movements of

Raw Materials/Intermediate Goods and Final Goods (Number Responding)

Table IV-1. Origin/Destination of Commodities Identified by Shippers

Product Origin

Location/

Facility

Destination

Location/

Facility

Product Origin

Location/

Facility

Destinati

on

Location/

Facility

# Shippers

Responding

Inbound(I) Outbound

(O)

Raw

Materials

Electronic

parts

I Asia Ciudad

Juarez

Finished

Goods,

Electronics

O Ciudad

Juarez

USA 5/9

Raw

Materials

Electronic

parts, and

Textiles

I USA Ciudad

Juarez

Finished

Goods,

Electronics

O Ciudad

Juarez

USA 3/9

Raw

Materials

I Inner

Mexico

Ciudad

Juarez

Refresh-

mint

O Ciudad

Juarez

USA 1/9

02

46

8

Typical Supply Chain

Raw materials and componentscome from Asia to Californiaand from California to El Pasoand Juarez. Finished productgoes from Juarez to El Paso andto the rest of the U.S.Raw materials and componentscome from inner Mexico toJuarez. Finished product goesfrom Juarez to El Paso and tothe rest of Texas and California.

Raw materials and componentscome fromEl Paso to Juarez.Finished product goes fromJuarez to El Paso.


Figure IV-2. Shipper Responses on Variation in Crossing Times (By Respondent Number)

minimum

maximum

average

0

5

10

15

20

1 2 3 4 5 6 7 8 9

Ho

urs

Variation in Travel Times


Figure IV-3. Daily Peaks Identified by Respondents

Figure IV-4. Seasonal Peaks Identified by Shippers

0

0.5

1

1.5

2

2.5

3

Daily Fluctuation

No Significant Variation

Peak in the morning around8.00 am

Peak in the afternoon around4.30 pm

Varies all through the day

0

0.5

1

1.5

2

2.5

3

3.5

4

4.5

5

Seasonal Fluctuation

No Significant Variation

June-September

October-December

Daily Variation


Figure IV-5. Impacts on Delay on Supply Chains

Figure IV-6. Shipper Responses on Ability to Pass Cost Increases

12%

50%

13%

25%

How the Supply Chain is Affected

Incur delay

Hire air carrier

No major disruption

Adjust supply chains

02

46

8

Who Absorbs the Costs of Delays?

Costs absorbed by Company

Costs absorbed by client for expedited delivery

Cost absorbed by the final customer


CHAPTER V: FRAMEWORK TO EVALUATE DIRECT COSTS OF BORDER CROSSING INEFFICIENCIES TO SHIPPERS AND CARRIERS

FRAMEWORK COMPONENTS

Based on the El Paso trade and commodity profiles, Chapter II provides a broad framework

for evaluating direct economic implications that would accrue to shippers and carriers as system

users and stakeholders and as part of a regional economy. Much of this can be subsequently

related to broader implications in later stages, to broader social impacts, and to other costs;

however, that discussion is not part of this research report. Quantifying impacts to other

stakeholders is also not part of this report.

Commodity/Trade Profiles by Direction of Flow

Broad findings from earlier chapters suggest that:

El Paso is a significant crossing point both in terms of value and weight for all US-

Mexico trade. Laredo ports supersede El Paso ports in terms of their economic

significance.

A significant portion of trade through El Paso ports is Maquila related trade. Truck

crossings involve a number of short trips to shippers/receivers on the other side of the

border that transport the product to other destinations. A very small percentage of cargo

traversing the borders is non-maquila trade and is comprised of other manufacturing

products, textiles and agriculture. In other words, the broad commodity pattern of flows

is somewhat similar for both directions of travel—northbound and southbound. The

fundamental difference is that just-in-time characteristics are more significant with

finished good products relative to intermediate goods that travel to the shipper /receiver

for final shipment. Other POE’s can be analyzed similarly for their trade profiles.

Appendix 2 profiles trade profiles for other POE’s along the Texas-Mexico border based

on Texas Center for Border Economic and Enterprise Development (TCBEED) data for

imports and exports for several ports of entry. This may be complemented by BTS data

since TCBEED data only cover the top 25 products in value.

A large percentage of trucks travel empty based on Table III-2 in the northbound (NB)

direction. This has direct implications as a social/environmental cost but is not a direct

cost to a shipper/carrier. This can be easily approximated using simple methods based on

emission factors of trucks and damage cost parameters. (See Ojah et al., 2002) (25).

There will be no further discussion of this aspect in this report.

Data Needs to Quantify Direct Costs and Definitions of Delay

The time spent in crossing a border is an important element in assessing direct costs and

other costs. However, not all time spent in the crossing process translates to a cost. The

economic implications stem from inefficiencies in the process or time in excess of a threshold

crossing time—in other words, the focus is only on “unanticipated delay.” Prior research like

that conducted by Ojah et al. (2002) has noted this as well. Unanticipated delay is generally


more costly than the same amount of anticipated delay. In terms of trucking costs, unanticipated

delays can result in cost increases because of missed connections, as when a vehicle arrives too

late for a pickup, leaving the vehicle and driver with some dead time. In practice, carriers cope

with the risk of unanticipated delays by building buffer time into their schedules. Whatever the

carrier’s strategy, difficulty in predicting delays adds to the costs of trucking operations. (Ojah

et al., 2002).

More recently, because of costs to several stakeholders, there have been significant initiatives

in terms of data inventories of crossing time data based on innovative data collection methods

(see Rajbhandari et al., 2009, for instance (31)). This research relies on radio frequency

identification data collected at El Paso Ports of Entry to be used to develop measures of delay.

More specifically, this report focuses on the development of the approach based on RFID data.

The actual measures developed for delay are dependent on the RFID collection itself and the

placement of the readers. At the time of the report development, there were only two tags

collecting the data (one on either sides of the border).

General Layout of the Inbound (NB) Traffic at BOTA POE

The BOTA land POE is a gateway between El Paso, Texas, and Ciudad Juarez, Chihuahua.

The bridge is used for truck and passenger vehicle movements. The northbound passenger

vehicles and commercial trucks cross the bridge by separated lanes. Commercial vehicles enter

the Mexican export facility through the entering point where the first RFID reader is located, as

shown in Figure V-1 (R1). After crossing the bridge, trucks advance to the U.S. federal

inspection facility where the entering lanes are split into FAST traffic and non-FAST traffic.

After clearing the federal and state inspection facilities they merge onto Gateway Boulevard

North, which provides access to US 54 or I-10. The second reader (R2) is located right after the

trucks cross the state inspection facility. The operational hours for commercial traffic at BOTA

are from 6 AM to 6 PM Monday through Friday and from 6 AM to 2 PM on Saturday. More

details are available in Appendix 1.


Figure V-1. Map of BOTA Crossing Facilities (2009)

Crossing Times by Direction of Flow — RFID Data Collection

BOTA is equipped with two RFID reader stations, R1 few miles south of the Mexican export

inspection facility and R2 at the exit of the state inspection facility on the U.S. side. The readers

read RFID tags installed in trucks with time stamps and send the data to a central location via a

data communication link. The collected RFID raw data are filtered in the central system at the

Texas Transportation Institute’s El Paso, Texas, office to match the unique IDs from R1 and R2

stations. The crossing time of a truck is then calculated from the time difference from R1 to R2.

In order to avoid the outliers among the matched RFID crossing time data, a 120-minute cap was

used by the RFID collection team (Rajbhandari et.al, 2009, 30) to filter RFID records with longer

than the cap. This report used the same filtered data to evaluate and build upon. After a

matching and filtering process, a set of 23,381 records was collected between July 2009 and

December 2009 at BOTA (Rajbhandari; TTI, Battelle et al, 2008, 2010) (31,32, 33).

It is currently planned to have an additional RFID reader station installed near the federal

inspection booths. The third reader would allow capturing more detailed crossing time

observations by segment and by FAST and Non-FAST lanes. Usually, FAST trucks have shorter

border wait times at the federal inspection facility compared to standard laden trucks and,

therefore, will have less delay costs. Compared to the RFID crossing times, it should be

mentioned that U.S. Customs and Border Protection (CBP) posts border wait times for

28 Canadian border ports of entry and 42 Mexican border ports of entry on their website

(http://apps.cbp.gov/bwt/). The border crossing time is defined by CBP as “wait time to reach

the primary inspection booth, the first point of contact with CBP when crossing the Canada/U.S.

RFID Reader R2

RFID Reader R1

U.S. Federal Inspection

Facility

Texas State Inspection

Facility

Mexican

Export Facility

http://apps.cbp.gov/bwt/


and Mexico/U.S. land borders.” In contrast, with RFID data the crossing time is noted as time

between the bridges to the primary inspection booth. The CBP border wait time is useful to

understand the travel behaviors in general as it contains the information about the maximum

lanes, number of current open lanes, and wait times by modes such as standard/FAST

commercial vehicles, standard/SENTRI passenger vehicles and pedestrians. However, CBP

border wait time does not include the crossing times before U.S. border from the Mexican

exporting lots. Another limitation of CBP border wait times is temporal resolution of one-hour.

Current one-hour refresh rate is perhaps inadequate to capture the dynamic changes of the border

crossing activities.

RFID Counts of NB Truck Crossings

Figure V-2 shows the hourly number of RFID readings collected from July 2009 through

December 2009 at the Mexican entering point and the El Paso exit point. In Figure V-2 (A), it is

generally observed that there are peak periods in the morning hours and in the late afternoon

hours at the Mexican entering point. This observation is consistent with the stakeholder

observations we received. However, the second graph (B) shows a more uniformly distributed

exiting truck volume, though there are still peak periods in the morning hours. The reason for

flattened peaks is because the incoming trucks have to pass the federal and state inspection

stations after they across the bridge. Even though service rates of the federal and state inspection

stations are not known, it is known that the number of booths are managed dynamically to cope

with the changes of incoming traffic volume. Notice that the graphs do not necessarily show the

true patterns of the influx and efflux at the POE. It is because the RFID readers capture only part

of the whole truck volumes. Not all trucks have RFID installed and some observations are lost

during the matching/filtering process. Figure V-3 shows the numbers of 2009 NB truck

crossings at BOTA along with the RFID counts after July 2009. As shown in the plot, the RFID

samples captured about 13 percent of the whole NB truck crossings during the sampling period.


(A) At Entering Point (B) At Exit Point

Figure V-2. Number of RFID Readings at El Paso BOTA Entering and Exiting Points

(Weekday BOTA RFID Readings between July and December 2009)

Figure V-3. Monthly NB Truck Crossing and RFID Counts at BOTA

Border Crossing Times Measured by RFID System

Figure V-4 shows the average northbound truck crossing times from RFID data collected

between July 7, 2009, and December 31, 2009, at the BOTA POE. The crossing times are

averaged values and are not able to discriminate empty and nonempty trucks or FAST and Non-

FAST trucks just yet. However, advances in filtering and classification methods applied to RFID

data may soon be able to provide that disaggregation. Note that the pattern of average crossing

time in Figure V-4 does not necessarily match the pattern of number of northbound trucks since

capacity or the number of open lanes is altered at CBP’s discretion in order to handle incoming

traffic volumes. In Figure V-4, the month of October has the highest traffic volume, while

average border crossing time by RFID observations shows a decrease from the previous month.

0

100

200

300

400

500

600

700

6 7 8 9 10 11 12 13 14 15 16 17 18

Total Hourly RFID Counts at Entering Point

July

Aug

Sep

Oct

Nov

Dec

0

100

200

300

400

500

600

700

6 7 8 9 10 11 12 13 14 15 16 17 18 19

Total Hourly RFID Counts at Exit Point

July

Aug

Sep

Oct

Nov

Dec

0

5000

10000

15000

20000

25000

30000

Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec

2009 Monthly NB Truck Crossings at BOTA

Actual NB Trucks RFID Counts


Figure V-4. Monthly NB Truck Volumes and RFID Average of Crossing Times at BOTA

(2009)

Figure V-5 shows the average crossing time increasing until the 9:00AM-10:00AM period

and has a decreasing pattern until the end of the operation hours. The graph shows a fairly stable

pattern of standard deviation—about half of the average values. Figure V-6 compares the hourly

average crossing times from July to December 2009. It indicates that August had the longest

crossing time during the 9:00-10:00 AM duration, while November showed the best performance

in terms of average border crossing time.

Figure V-5. Hourly Average of Crossing Time and Standard Deviations (BOTA RFID

Data July-December 2009)

0

10

20

30

40

50

60

70

80

90

0

5,000

10,000

15,000

20,000

25,000

30,000

35,000

Cro

ssin

g Ti

me

(m

inu

tes)

Nu

mb

er

of

NB

Tru

cks

NB Truck Volume Avg. Crossing Time (RFID Obs.)

0

10

20

30

40

50

60

70

6 7 8 9 10 11 12 13 14 15 16 17 18

Ave

rage

Cro

ssin

g Ti

me

(m

inu

tes)

Period (Hour)

Average of Crossing Time StdDev of Crossing Time


Figure V-6. Hourly Average of Crossing Times: Comparison by Month (2009)

Figure V-7 illustrates the average of crossing times and RFID counts by day of week during

the whole sample period. The average crossing times range between 45 minutes and 50 minutes.

This is consistent with the findings of a recent study by Accenture Group et al. (34) who note,

BOTA’s mean wait time12

of 48 minutes in 2008. The same report also notes Ysleta’s mean

wait time as 47 minute with Free and Secure Trade (FAST) trucks wait times lower than empty

and non-FAST trucks. Based on the graph, there does not appear to be a significant “day-of-the-

week” effect just by looking at average times. As mentioned earlier, the RFID counts do not

necessarily reflect the actual trend of the traffic volumes.

12

The Accenture Group Report (2008) uses wait time interchangeably with crossing times. www.bta.org

0

10

20

30

40

50

60

70

6:00 7:00 8:00 9:00 10:00 11:00 12:00 13:00 14:00 15:00 16:00 17:00

Aver

age

Cros

sing

Tim

e (m

inut

es)

Period (hour)

July

Aug

Sep

Oct

Nov

Dec


Figure V-7. Average of Crossing Times by Day of Week (July-December, 2009)

Fitting Border Crossing Times Distribution

In order to run Monte Carlo simulation, hourly travel time distributions were fitted from the

RFID data. Figure V-8 shows the histograms skewed to the right and the fitted lognormal

distributions of the RFID data by time periods. The statistical distributions of arrival patterns

were used in the Monte Carlo simulation to represent the uncertainty in the border crossing time.

(a) AM Peak (b) Off Peak (c) PM Peak

Figure V-8. Fitted Lognormal Distributions of RFID Observations by Time Periods

0

1000

2000

3000

4000

5000

6000

0

10

20

30

40

50

60

70

80

Monday Tuesday Wednesday Thursday Friday

RFI

D C

ou

nts

Ave

rage

Cro

ssin

g Ti

me

(m

inu

tes)

Average of Crossing Time Count of RFID


Table V-1 represents the fitted parameter values with lognormal distributions.

Table V-1. Fitted Crossing Time Distribution Parameters

Period

Number of

Samples

Lognormal Distribution

Mean Crossing Time (minutes)

Standard Deviation (minutes)

AM Peak (06:00 - 10:00)

9,049 57.0 27.8

Off Peak (10:00 - 16:00)

10,270 49.0 29.5

PM Peak (16:00 - 19:00)

2,548 32.9 25.9

Whole Day (06:00 – 19:00)

21,867 49.5 28.9

Performance Measures for Border Crossing Times

Following the discussion on definitions of “delay,” it is noted here that there are many

different ways to represent the performance of border crossings (Rajbhandari et al., 2009 (30)).

In this report, it is how to define the delay and reliability so that the economic implications may

be better estimated. Figure V-9 illustrates the weekday crossing time observations during a

representative month of September 2009. It shows a wide range of border crossing times from

8 minutes to 120 minutes over the sample period. The minimum crossing time is the fastest

possible crossing time from the first reader at the entering point on the Mexican side and the

second reader at the exit point of the state inspections facility in El Paso. Since every truck

passes through the inspection stations between the readers, this minimum crossing time is

different from the physical free flow time between the two points. Other measures, average

crossing time, median crossing and 95th

percentile crossing time, capture various aspects of the

distribution of times and the variability of the border crossing time. The buffer time, 50 minutes

in Figure V-9, is the difference between 95th

percentile travel time and average travel time. It

can be expressed as the amount of extra time needed to be on time for 95 percent of the trips.13

13

Travel Time Reliability Measures.

http://www.ops.fhwa.dot.gov/perf_measurement/reliability_measures/index.htm. (35)

http://www.ops.fhwa.dot.gov/perf_measurement/reliability_measures/index.htm


Figure V-9. Performance Measures from RFID Observations (Weekday Crossing Time by

Minute, September 2009) (BOTA)

Measure of Border Crossing Time Delay

Unlike much of the earlier work in this arena, this study notes that delay is measured in

reference to a baseline or benchmark measure since the crossing process takes a minimal length

of time. This length of time will be different for different classes of trucks. For instance these

identifiers will include at a minimum:

FAST or non-FAST

Empty or loaded

Cargo type

Inspection stages a) (to secondary inspection) b) secondary to primary and c)

through primary inspection.

In reality, however, the available data rarely allows that fine a classification unless

measurements follow using those criteria. Hence, a single mean or average might represent that

benchmark.

Several benchmarks are used to calculate the delay and the travel time reliability. The mean

is the simplest known baseline or benchmark to assess delay. In Figure V-10 the median

crossing time and average crossing time are used as threshold values to measure the delay. For

example, by using median crossing time (41 minutes) threshold, any RFID record with a crossing

time lower than 41 minutes was considered a “no delay” or normal trip. If a trip is identified

with times higher than 41 minutes then the excess time over 41 minutes is treated as delay. By

the same token, any crossing time over the current average of 48 minutes is measured as delay

when using the average crossing time threshold. The other important measure is 95th

percentile

0

20

40

60

80

100

120

140

Cro

ssin

g Ti

me

(m

inu

tes)

RFID obervations during weekdays of September 2009

95th Pecentile Crossing Time

Average Crossing TimeBuffer Time

MinimumCrossing Time


travel time. Certain commodities such as just-in-time products and perishable products are likely

to incur additional costs when the delay exceeds a given buffer time (damages for perishable

goods, for instance). In the current sample statistics, 95th

percentile crossing time was 98

minutes and the buffer time was calculated as 40 minutes, as shown in the Figure V-10.

Figure V-10. Crossing Time Distribution (BOTA) and Performance Measures/Statistics

(July-September 2009 BOTA)

OTHER CRITICAL DATA ELEMENTS

The framework draws upon several additional components and data aspects that are of value

in determining direct economic implications. These include:

Truck Volumes by Direction of Flow,

Loaded and Empty Trucks by Direction of Flow, and

Weight and Value of Cargo Flows by Direction of Flow.

These aspects are discussed in detail in the following chapters. Figure V-11 is a visual

representation of the various elements of the framework that are incorporated in the development

of a border delay direct cost estimation tool. This framework was developed based on the

stakeholder feedback combined with an assessment of freight movement patterns at the ports of

El Paso. As such, the framework is transferable and may be adapted to other POE’s.

Lognorm(49.525, 28.949) Shift=-1.6951

Value

s x 10

^-2

0.0

0.5

1.0

1.5

2.0

2.5

0 20 40 60 80 100

120

< >5.0% 5.0%90.0%

15.8 102.6

Delay by Median Crossing Time

Delay by Average Crossing Time

Buffer Time

Med

ian

CT

Ave

rage

CT

95th

Per

cent

ile C

T


Figure V-11. Various Components of the Framework (by Direction of Flows)

Crossing Time (Archived/Near Real Time)

Trade Profiles at Ports of Entry & Freight Movement

Patterns

Crossing Volumes Cargo information (Loaded,

Value, Weight)

Direct Economic Variable Costs


CHAPTER VI: DIRECT COSTS CATEGORIES

In this research, only direct monetary delay costs were considered in terms of shippers and

carriers. The various cost categories were combined with performance measures from RFID data

into an interactive spreadsheet tool that allows users to arrive at direct cost consequences.

Furthermore, while the statistics and data are primarily reflective of northbound flows into the

United States, it must be noted that the framework is only limited at this time by the availability

of data on archived time. Hence, with additional data, the framework may be adapted to other

ports. The costs are all variable, in the sense that they are all functions of time.

VARIABLE DIRECT COST CATEGORIES: SHIPPER

Shippers incur inventory costs such as inventory capital cost, inventory risk cost, and cost of

delayed schedule due to extraordinary border crossing times. Those inventory cost parameters

are set to account for the different commodity groups. Manufactured just-in-time (JIT) products

have the most expensive logistic costs for schedule delay since a delay in one manufacturing part

may lead to disturbances in the downstream of production schedules. Maquila production that is

so highly represented in the El Paso ports is one that falls in this category. In the interactive

spreadsheet tool, the following cost components are considered in regard to shippers:

inventory capital costs

inventory damage/risk costs for perishables and JIT products, and finally

additional logistics costs from excess variability or when times exceed buffer times.

VARIABLE DIRECT COST CATEGORY: CARRIER

Carrier related time dependent costs include:

Vehicle Operating Costs (Fuel, Maintenance, Wear and Tear)

Labor costs

COMMODITY CLASSIFICATIONS AND PORTS OF ENTRY

Based on the commodity profile of ports of entry evaluated in earlier chapters, it was decided

that a five-fold breakdown of commodities would meet the trading profile of most ports for the

evaluation of direct costs and subsequently broader costs. This five-fold breakdown is:

manufactured JIT products (Referenced as “Comm-1” henceforth),

manufactured non-JIT products (Comm-2),

agricultural perishable products (Comm-3),

agricultural non-perishable products (Comm-4), and

other products (Comm-5).


SHIPPER COSTS

Cargo Values

Average cargo values per truck trip are important for assessing inventory capital costs for

loaded trucks. These values are obtained from secondary sources. However, it is important to

note that there is currently no readily available information about average cargo values, and in

many cases this is an imputed parameter or one that a user may choose to provide. Currently,

TCBEED provides export and import values for the top 25 (2-digit Standard Industrial

classification Code SITC) traded commodities by POE region. The Bureau of Transportation

Statistics also publishes export and import values and weights by 2-digit Harmonized Tariff

Schedule (HTS) codes by ports. The average cargo value is the dollar amount of shipments

carried by a loaded commercial truck. Since this not directly available, it is estimated from the

annual imports value by truck through El Paso and the number of annual loaded truck

containers.

.

Table VI-1 shows the calculated average cargo values per truck since 2004 in the last

column. The analysis of values is kept to year 2009 to maintain consistency with RFID dates.

Table VI-1. Average Imports Cargo Value per Loaded Truck

(Northbound Crossings El Paso)

PORT YEAR

Imports Value by All Land Modes (Destination in Texas)

Imports Value by Truck (Destination in Texas)

# LOADED TRUCK CONTAINERS

Average Cargo Value per loaded truck container ($/truck)

EL PASO

2004 $12,469,348,486 $12,155,269,000 409,093 $29,713

2005 $11,309,017,253 $11,246,227,000 430,768 $26,107

2006 $11,513,235,758 $11,429,703,000 418,026 $27,342

2007 $12,493,795,483 $12,320,196,000 402,456 $30,613

2008 $13,923,529,950 $13,251,291,000 384,586 $34,456

2009 $12,250,863,192 $11,579,415,114 336,119 $34,450

SOURCE: U.S. Department of Transportation, Research and Innovative Technology Administration, Bureau of

Transportation Statistics, Transborder Freight Data; U.S. Department of Homeland Security, Customs and Border

Protection, OMR database; UTEP Border Region Modeling Project.

The El Paso-Juarez region shows highly industrialized characteristics. Table VI-2 shows the

top 25 traded imports by value. 78 percent is represented by machinery and transport equipment

(SITC 7), 15 percent by miscellaneous manufactured articles (SITC 8) and less than 2 percent is

represented by food and live animals (SITC 1). The majority of the imports are JIT related and

over 90 percent of the imports are manufactured products.


Table VI-2. Imports through El Paso Ports (2009)

POE 1-Digit SITC

5-Digit SITC

Top 25 RANK

TRADE VALUE

POE 1-Digit SITC

5-Digit SITC

Top 25 RANK

TRADE VALUE

EL PASO

7

76160 1 $3,610,013,86

8

EL PASO

7

71322 20 $191,113,402

75230 2 $2,807,041,80

9 77884 23 $165,804,360

78120 3 $1,552,590,99

7 77551 24 $163,832,342

77313 4 $1,478,732,33

6

8

82119 8 $695,905,824

78439 6 $725,377,610 87229 9 $661,838,844

78219 7 $696,582,383 87221 11 $445,923,612

77521 10 $455,037,963 84140 17 $259,295,113

77261 12 $372,816,644 87465 21 $180,015,882

76412 13 $339,980,659 89399 22 $165,947,083

77316 15 $280,367,521 87461 25 $147,282,365

71631 16 $260,017,133 9 93100 5 $911,418,487

75197 18 $230,873,563 1 11230 14 $285,973,546

74780 19 $212,998,471 Sum of Top 25 Import $17,296,781,817

SOURCE: Texas Center for Border Economic & Enterprise Development

Inventory Costs: Ownership Aspects and Whose Costs?

In attempting to discern relevant costs of delay, it is important to recognize that inventory

costs are costs to either the shipper or the receiver depending on when the change of hands takes

place. If the ownership change occurs at the very beginning of a movement, the cost reflects a

cost to the receiver. On the other hand, if the ownership change occurs at the end, the costs

reflect a shipper cost throughout. While in principal this is very difficult to assess across the

board and is likely to vary across goods and shippers and linked to terms of trade, this report

makes an assumption that the inventory cost is a shipper cost. This is corroborated by shipper

responses discussed in Chapter 4. Research by Cambridge Systematics (2) indicates that the El

Paso bi-national gateway region acts largely as a support center for locally manufactured goods

(maquila industry), and yet other research suggests that a large percentage of shippers are also

receivers in the El Paso-Juarez bi-national region. This suggests that the assumption of assigning

costs to the shipper is perhaps not an onerous assumption.

Inventory Cost Components

Capital Cost – This component represents the cost of goods in transit. It is usually an

internal cost of funds rate multiplied by the value of the product. Because value is added

to the product as it moves along the supply chain, this cost tends to increase as the

product moves downstream. Holding inventory ties up money that could be used for

other types of investments. Consequently, a shipper’s true opportunity cost of capital of

any time related delay is reflected in the capital costs. Since this cost is associated with a

direct move through the chain, this component is therefore a critical component of

traditional cost-benefit analysis.


Storage Cost − Units in inventory take up physical space, and may incur costs for storage,

heating, refrigeration, insurance, etc. This is of particular import for goods requiring

refrigeration.

Quality Cost − High levels of inventory usually increase the chance of product damage

and create slower feedback loops between supply chain partners. The result: lower levels

of quality and a rise in the myriad costs associated with low quality. These costs are

difficult to quantify precisely, but the current consensus is that they can be quite

significant. This is of particular import for perishables.

Typically, all these costs are rolled together into a single inventory cost rate, expressed as a

percentage of the value of the product or material per unit time (e.g., 20 percent of the value per

year). The Council of Supply Chain Management places this value at 18 percent, for instance.

Other equivalent terms for this same cost rate are inventory holding cost rate and inventory

carrying cost rate.

Border Delays and Relevant Inventory Costs

The social costs of the border delays can be captured by the interest carrying (capital) costs

of inventories and/or the wastage (perishing) of inventories in addition to the time costs. It is

important to point out there are two factors that determine which of these components become

important, including the following:

Nature of freight movements traversing the region: Gateways and ports characterized

by primarily short-haul movements could risk the capital cost of goods/value in transit.

Capital cost components accrue to all goods in transit and can be influenced by travel

time delays and efficiencies and has been therefore included in most benefit cost analysis

related to transportation movement. On the other hand, ports characterized by longer

origins and destinations could potentially incur additional logistic cost components

because of longer supply chains. The size of these added interest carrying or capital costs

depend on value assumptions as well as the interest rate.

Nature of cargo: This determines if elements of storage costs or quality costs become

relevant. Perishables, for instance, loose value. In the case of the Canadian borders, the

Ontario Chamber of Commerce noted that storage of inventory was a significant cost in

the automotive sector due to delays at the Ontario-U.S. border crossings (OCC, 2005).

The size of this cost depends on rate of decay of goods.

The hourly inventory capital cost of a truckload of commodity is given by i:

Where, Hi = annual unit holding cost per $1 value of inventory. Si = dollar value of a

truckload of commodity i. Currently default values of Hi are approximated by market interest

rates to proxy the cost of capital. It can be adjusted by a user to include more general inventory

carrying cost terms in the spreadsheet tool if necessary.


Inventory Damage/Risk Costs for Perishables and JIT Products

In concept, JIT production is designed to keep minimum possible inventory and to rely on a

punctual supply chain for running the production lines. If assembly parts are not delivered on

time due to unexpected delays at the border, JIT production lines could be affected by the

shortage. Similarly, perishable products decay in the event of excess delays. Hence, JIT

products and perishable products have higher inventory costs due to the more stringent time

constraints within the supply chain. In the current spreadsheet tool, it is assumed that 9 percent

to 18 percent of inventory value on hand is used to account for the damage/risk costs for

perishables and JIT products.14

Additional Logistics Costs from Variability in Crossing Times

Uncertainty comes with a cost and this is approximated by using the value of reliability and

is only valued for just-in-time production systems using buffer times (based on 95th

percentile

time). Shippers usually schedule ahead considering this extra buffer time in their regular

business process, but excess delays may occur. Additional logistics costs are calculated as

follows:

Truck-hour over 95% tile crossing time*VOR

Where VOR = value of reliability.

Since region-specific reliability estimates are not available, this parameter is approximated

by work done by Small. Hence, in the spreadsheet tool VOR ranges from $144.22 to $192.83

(Small et al, 1999) (36). This term is heavily influenced by shipper/carrier perceptions on time

spent traversing borders and their built in buffer times for the crossing. Another interpretation is

that 95% percent of the times, these costs would not apply but when they do- they are high.

VARIABLE CARRIER COSTS

Fuel Costs

One of the key components of carrier variable operating costs is fuel consumption due to

delay. Fuel costs are treated analogous to dealing with congestion and stuck in traffic. When a

truck approaches the border inspection facilities, it reduces its speed to creeping mode until it is

inspected and cleared at the booths. This slow movement usually starts at the beginning of the

Mexican export inspection facility through the U.S. federal inspections facility and the state

inspections facility. At these border delay segments, additional fuel is needed to deal with the

slow speed and the extra time due to delay. The fuel cost due to delay is calculated by the

product of fuel consumption rate, delay time, and the fuel price. This estimate includes taxes,

but may be netted out by adjusting the fuel price.

14

The typical range cited by these authors for risk costs ranges from 9-18% of value while storage costs range from

7-16% of value. (Richardson, 1995) (37)


Fuel Cost = Fuel consumption rate * Truck fuel price * Delay hours.

Labor Costs

Labor cost is defined as the direct cost that carriers have to spend for hourly wages. The

USDOT guidance recommends the use of $22.15 in the year 2009 as the basis of benefit cost

analysis and 100 percent of wages as recommended value of time savings. Table VI-3 shows the

commercial vehicle values of time in the United States. Because of the wide discrepancy shown

in the table, current 2009 statewide wages were used as a basis of Texas value-of-time

conditions. According to the Texas Workforce Commission (TWC), the 2009 median hourly

wage statistics for truck transportation was $17.11 for general freight trucking and $14.38 for

specialized trucking. These values are upgraded to include 25 percent fringe and vehicle

occupancy of 1.1, suggesting wages of $24.90 in generalized freight and $23.00 in specialized

trucking. Mexican trucker wages are known to be lower than for US-based trucks and many of

them may have wages in the range of $6-$10 per hour. However, the range of costs entered are

consistent with initial shipper response noted in Chapter 4. For these reasons, the design of the

tool is such that it is extremely transparent, and user-developed inputs may enable better

assessment of costs. For this report, the US-based values are currently used as defaults. In prior

studies (Ojah et al., 2002), a California toll study estimate was to approximate time costs.

Instead, this study assumes a more conservative approach and bases it purely on wage costs.

The benefit-cost model Highway Economic Requirements System (HERS) (38), for instance,

uses a similar concept of wage-based assessment but also adjusts these costs by cargo type and

by adding in inventory carrying costs based on cargo value and hourly discount rate factors. The

approach developed in this report, on the hand, breaks up the various components into individual

elements so that inventory costs may be assessed separate from wage-based costs. Finally, this

separation also allows for inventory to be linked directly to variance in delays.


Table VI-3. Commercial Vehicle Values of Time in the United States

Source Specific

Purpose

Values Reported

Dollars per hour

Updated to

2009 Dollar

Amount

(/hour)

Comments

Haning &

MacFarland

(1963) (39)

Project

evaluation

17.4 - 22.6 (in 1998

dollars)

21.5 – 27.97 First study to estimate commercial

value of time. Truck operators.

Minimum and maximum values of

time based on low to high utilization

of time.

McFarland and

Chui (1986)

(40)

Project

evaluation

8.03 (1985 dollars) 14.99 For small cars, large, medium cars,

and pickup trucks.

Waters et al.

(1995) (41)

14.5 - 35.6 (in 1998

dollars)

17.9 – 44.05 Cargo vehicles. Minimum value =

40% of driver wages. Maximum = all

time savings converted to additional

business.

Buffington &

MacFarland

(1975) (42)

Evaluation Single unit 2-4 axles =

15.59

Other singles unit =

18.61

Semi combination ≤ 4

axles = 23.20

All others ≥ 5 axles =

25.75 (in 1985 dollars)

= 29.11

= 34.75

= 43.30

= 48.08

Updated American Association of

State Highway and Transportation

Officials (AASHTO) values.

Average = $38.80/hour (in 2006

dollars)

Kawamura

(1999) (43)

Toll road

application

a) 26.8 (std dev=43.68)

b) 23.4 (std. de=32)

= 32.30

= 28.30

California truck operators

Lewis NCHRP

2-18 (1994)

(44)

> 100 (in 1994 dollars) 135.69 Scheduling benefits

HERS

(FHWA) (38)

21.95 for drivers + 9.63

for vehicle/inventory

carrying costs (in 1997

dollars)

27.59 + 12.10

= 39.69

Wage costs and inventory carrying

costs


CHAPTER VII: MODEL STRUCTURE

STRUCTURE OF THE SPREADSHEET TOOL

The DCET tool was designed to utilize the historical freight flow statistics and direct input

from users to run Monte Carlo simulation experiments on various parameters with uncertainties.

Figure VII-1 demonstrates overall modules and data flows between the modules in a schematic

diagram. The key features of this proposed economic impact tool are as follows:

It is designed to provide a current assessment of delay related economic impact in terms

of shippers and carriers separately.

It allows users to change the default input parameters easily to see the influence of an

input parameter on the direct delay costs.

It is designed to consider different commodity groups.

It is designed to permit interface with archived travel time/near real time data collection

efforts.

It is currently NOT designed to directly handle influence of port strategies since it works

with crossing times. In other words, capacity changes can only be analyzed ex-post

through their influence on times, but not in an ex-ante sense as in typical simulation

studies.

In Figure VII-1, the data flows can be grouped by the following three main components:

time component,

volume or number of truck component, and

cost component.

Since the direct delay cost is a function of volume, delay hours, and per-hour unit costs, the

information flows from the three components are gathered together in the input parameters

worksheet to be used in the calculation module generating the direct delay cost estimations by

different delay criteria.


Figure VII-1. Structure of the Delay Cost Estimation Tool

Schematic Data Flows

In the spreadsheet tool many input parameters are based on the historical freight flow

statistics that can be changed by direct user inputs. In the user input screen most of the input

items are already filled with default values drawn from the various transportation statistics

sources. Users can change any of the default values based on the current observations at the port

of entry to see the effect of the changes. The input values are processed by several intermediate

calculations. These are subjected to risk analysis via Monte Carlo simulation to deal with the

underlying inherent uncertainties about the costs and delays. The current spreadsheet framework

is designed to be flexible to handle different types of commodity groups and also different types

of traffic flows to represent the actual border crossing conditions as close as possible.

Figure VII-2 shows the schematic diagram of data flow of the spreadsheet tool.

REPORT_Cost

Calculation

Input Parameters

No.TruckComponent TimeComponent CostComponent

Base_Stats

RFID_Sample

REPORT_Time REPORT_TrkVol

Default

User Input

Daily costs

Delay costs, Average delay, No. trucks delayed

Delay cutoff times, % of trucks delayed

Delay costs by commodity group

No. NB trucks Delay hours by cutoff criteria

Stat

s ab

ou

t C

ross

ing

tim

es a

nd

Del

ays

Mo

nth

ly N

B T

ruck

C

ross

ings

at

BO

TA

Daily NB Trucks

An

nu

al/m

on

thly

NB

tr

uck

s at

BO

TA

Avg. cargo value, commodity distribution, etc.

Cost parameter values

Monte Carlo Simulation

crossing times

SimResults

Sim

ula

tio

n R

esu

lts

fro

m e

ach

iter

atio

n


Figure VII-2. Schematic Data Flow Diagram of the Spreadsheet Tool

Basic Input Parameters

Crossing Time and Delay: What Represents a Delay?

Border crossing times are measured by RFID readers installed at the entering point of the

Mexican export facility and the exit of the state inspection facility. Since crossing time is a

travel time between the two RFID readers, it can be partitioned into normal travel time and

delay. Delay can be viewed in many different ways by how the regular travel time is defined. In

some cases, free flow travel time could be considered as regular travel time. In other cases,

average travel time could be regarded as normal travel time. In order to deal with the range of

delay measures, the current spreadsheet tool uses several different delay measures to calculate

the impact of delay. The different delay criteria are shown in Figure VII-3.

RISK ANALYSIS (MONTE CARLO SIMULATION)

Main INPUT SCREEN

NB Truck Volume Distribution Average Cargo Value Inventory Cost Parameters Logistics Cost Parameters Carrier Cost Parameters Operating Cost Parameters

Intermediate Process Shipper Costs Carrier Costs Delay Time Truck Crossings

Total Daily Cost Caused by Delays at POE = function [(Unit Delay Cost x Daily # Trucks) by (Loaded Truck / Empty Truck) by (Commodity Category)]

OUTPUT REPORTS

Total Delay Costs, Total Delay Hours, Truck Volumes, etc.

Historical Freight Flow Statistics &

RFID Observations


(a) by average CT (b) by median CT (c) by 95%tile CT

Figure VII-3. Delay Measures

Freight Traffic Volume

Annual freight traffic volumes by ports of entry from BTS were used to derive the daily truck

crossings since the daily traffic volumes were not available. They were divided by the number

of the yearly weekday equivalent. The average freight traffic volume on Saturday at BOTA

observed 30 percent of the average weekday volume from the RFID data. Hence, the yearly

number of weekday equivalent was translated as follows:

(52 weeks/year * 5 weekdays/week) + (52 Saturdays/year * 0.3) = 275.6 days/year

In the BOTA case example, the northbound truck traffic in the year 2009 was 316,731 trucks,

and the average daily traffic was estimated as follows:

316,731 trucks / 275.6 = 1,149 trucks/day.

Laden-Empty Truck Ratio

The BTS annual freight traffic volumes table includes the data about loaded and empty truck

containers. The ratio between the loaded and empty containers was used in the tool to calculate

the daily loaded and empty freight truck crossings. The number of loaded trucks is important to

assess shipper costs such as inventory cost and additional logistic costs from variability in

crossing times.

Distribution of Commodities

Commodities were grouped into three major categories of commodities: Manufactured,

Agricultural, and Other commodity groups. Manufactured items were then further divided into

Just-In-Time and Non-JIT commodities. Agricultural items consist of Perishable and Non-

Lognorm(49.303, 28.949) Shift= -1.5571

Va

lue

s x 1

0^

-2

0.0

0.5

1.0

1.5

2.0

2.5

0

20

40

60

80

10

0

12

0

< >5.0% 5.0%90.0%

15.8 102.5

Delay by Average Crossing Time

Average Crossing Time

Delay

Lognorm(49.303, 28.949) Shift= -1.5571

Va

lue

s x 1

0^

-2

0.0

0.5

1.0

1.5

2.0

2.5

0

20

40

60

80

10

0

12

0

< >5.0% 5.0%90.0%

15.8 102.5

Delay by Median Crossing Time

MedianCrossing Time

Delay

Lognorm(49.303, 28.949) Shift= -1.5571

Va

lue

s x 1

0^

-2

0.0

0.5

1.0

1.5

2.0

2.5

0

20

40

60

80

10

0

12

0

< >5.0% 5.0%90.0%

15.8 102.5

95%tile Buffer Time

95%tileCrossing Time

Average

BufferTime

Delay


perishable commodities. This break up allows the consideration of variability in delays. Some

of the default input values of these commodities were collected by one-digit SITC codes from

various sources such as U.S. Department of Commerce Bureau of the Census, Foreign Trade

Division and Texas Center for Border Economic and Enterprise Development. Unfortunately,

there were no available data for the number of truck crossings by SITC for the border ports of

entry by commodity type. The default truck volume distribution was therefore approximated

from the import value distribution obtained from TCBEED. Superior user-based information, or

survey based data may override these defaults, if they are available and will enable more

accurate assessments.

Just-in-Time Freight

In order to demonstrate, characteristics of any POE, the spreadsheet tool uses truck volume

distributions of five commodity groups. As mentioned in the previous chapter, JIT related

products represent a large portion of the freight traffic volume in the El Paso region with the

assumed default value of 78.3 percent. Since the JIT products are more sensitive to unexpected

delays, the simulation model allows users to input inventory risk cost in addition to the common

capital cost.

Perishable Commodities

Another commodity group that needs special attention is perishable items. Even though

perishable items are a very small percentage of overall northbound flows through El Paso ports,

they should be considered explicitly for additional holding cost due to delay because they need

more resources to offset decay of the freight until they are delivered to final destinations. Like

just-in-time freight, perishable commodities have separate input values for inventory holding

cost to yield final inventory costs.

Average Cargo Values

Cargo values are critical for the determination of inventory costs. Due to lack of common

public domain source, the following values are imputed from BTS data:

Average Cargo Value = Imports value by truck / Number of loaded trucks.

Currently the BTS tables show only aggregated values at the port region level by mode.


CHAPTER VIII: BRIDGE OF THE AMERICAS ILLUSTRATION

NUMBER OF FREIGHT TRUCK CROSSINGS

Even though there has been tremendous innovation in technology for data collection and for

archiving travel time or crossing time, the methods available to date are still inadequate to

identify other factors that are critical for economic assessments. For instance, RFID readings

give vital information about the border crossing times; they are not sufficient enough to estimate

the freight traffic volumes due to the partiality of the RFID observations and the lack of ability to

distinguish loaded and empty trucks. In the current framework, freight traffic volumes are

estimated from the historical statistics published by BTS based on Table III-2.

In the current BOTA case example, daily loaded trucks are estimated by the following

equation:

Daily loaded NB trucks = Daily NB Trucks * Loaded truck % at El Paso

USER INPUT VALUES IN THE SPREADSHEET TOOL

The input values in the current BOTA example are based on the historical data as default

values. Even though the spreadsheet tool will be able to generate the output reports with those

default values, it is designed so that superior information provided by users may override

defaults.

Figure VIII-1 and Table VIII-1 illustrate the main input screen and the default input

parameters used in the simulation model.


Figure VIII-1. Main Input Screen − DCET

Table VIII-1. Default Values − Bridge of the Americas, El Paso

Parameter Value Parameter Value

Crossing Times

Average CT 47.5 minutes

Delay Times

by Average CT 26.7 minutes

Median CT 41.0 minutes by Median CT 27.2 minutes

95%tile CT 98.0 minutes by 95%tile CT 28.6 minutes

% of Trucks Delayed

by Average CT 42.80% Truck Volume Distribution by

Commodity Group (by Top

25 imports)

JIT 78.30%

by Median CT 53.50% Non-JIT 20.00%

by 95%tile CT 6.00% Perishable 0%

Idling/Creeping Fuel

Consumption

Loaded 4 gallons/hour Non-perishable 0%

Empty 3.5

gallons/hour Other 1.70%


OUTPUT RESULTS FROM THE SIMULATION

1,000 replications were used in the simulation experiment. Each replication represents the

daily border crossing activities. The simulation results were summarized in the separate output

reports pertaining to the three components: cost, time, and truck volume. Notice that the figures

of the output reports shown in Figure VIII-2 and Figure VIII-3 are subjects to the assumed

conditions in the previous section and are therefore only a proxy to the costs of delay.

Figure VIII-2. Sample Screenshots of Output Reports − BOTA Illustration

(50%tile+) (95%tile+)

Average Median

Reliability Cost -

Buffer Time

$4,809,890 $5,469,138 $2,387,898

Just-In-Time $3,237,843 $3,512,196 $2,229,905Carrier Costs $987,252 $1,255,974

Shipper Costs $2,250,591 $2,256,222 $2,229,905

Non-JIT $399,544 $468,569 $145,956Carrier Costs $252,778 $321,583

Shipper Costs $146,766 $146,986 $145,956

Perishable $0 $0 $0Carrier Costs $0 $0

Shipper Costs $0 $0 $0

Non-Perishable $0 $0 $0Carrier Costs $0 $0

Shipper Costs $0 $0 $0

Other $32,950 $38,643 $12,037Carrier Costs $20,847 $26,521

Shipper Costs $12,104 $12,122 $12,037

Empty Trucks $1,139,553 $1,449,730(Carrier Costs Only) $0 $0

Delay Cutoff Time 48 minutes 41 minutes 98 minutes

PER-HOUR COSTS BY COMMODITY GROUP

Per-hour

Delay Cost

($/hour)

$39.88

$0.84

$564.16

$39.88

$0.13

$144.22

$39.88

$0.48

$192.83

$39.88

$0.13

$144.22

$39.88

$0.13

$144.22

$39.88

Estimated Annual

Cost

Carrier Cost

Commodity Group

JIT (Comm 1)

Carrier Cost

Regualr Shipper Cost (Typical delay)

Non-JIT (Comm 2)

Delay Cutoff Time Criteria

Reliability Cost (Delay over 95%tile)

Carrier Cost


Empty Truck

Carrier Cost

Non-perishable (Comm 4)

Carrier Cost




Other (Comm 5)



Perishable (Comm 3)

Carrier Cost




Figure VIII-3. Ninety-Five Percent Confidence Interval Cost Estimates − BOTA

Illustration

RESULTS

Figure VIII-2 shows a range of reliability based inventory costs per hour ($564.4-$144)

based on commodity grouping. Labor/fuel/maintenance wear and tear costs are assessed at

approximately $39 dollars per hour. Based on commodity splits, the actual estimated costs per

day based on July – September (2009) archived crossing time information and evaluated at delay


based on mean or average crossing time, and including buffer time (also based on mean time) are

as follows:

$8,166 for those in just-in-time production systems for a total of $189,455 for one month.

These costs assume that shippers hold less than one hour in buffer time to combat

variance in delay. In the event that buffer times of 1 hour or more are held, these costs

may be significantly lower. Per our initial stakeholder feedback, a few hold buffers of

one hour or so, while others do not. Anticipating and understanding travel patterns may

be in the interest of shippers wishing to maximize their trips or optimize their

productions. Combining the archived data on crossing times to communicate meaningful

statistics may be of value in enabling shippers to take action on all fronts. Some portions

of these costs will be borne entirely by shippers themselves and may represent a clear

loss with much broader economic implications.

The monthly and daily costs for other manufacturing shippers is much lower at

$12,355and $533, respectively.

The total daily costs for shippers and carriers jointly are estimated at $17,452 (delay

evaluated relative to the mean). Other benchmarks will obviously change these

estimates.

CONCLUSIONS

This research conducted an evaluation of El Paso ports of entry. Based on an exhaustive

literature review, a framework and tool was developed to develop the direct economic

implications of border-related delays. This report focused on direct costs (those are time

variable) and developed an interactive spreadsheet tool (DCET) that allows users to investigate

how a variety of freight performance measures may be quantified in terms of economic

consequences to the freight industry (shippers, carriers). In particular, the Bridge of the Americas

was adopted as a case example. This choice of POE does not impact the validity of the

application in any way. BOTA was selected for illustration because it provides a unique

opportunity to draw upon archived RFID data on bridge crossing times and utilize those in the

development of freight performance measures, including measures reflecting trip reliability.

The value of the high quality of data is important since the analysis is highly dependent on

primary and secondary data sources to establish distributions and defaults. Given this aspect, the

spreadsheet was designed as flexible with defaults that users could override. Given the high

levels on uncertainty in many inputs, including crossing times (the most critical input), risk

analysis via Monte Carlo simulation was an integral element of the tool as well as sensitivity

analysis. This interactive element was also crucial to maintaining transparency of the tool to

users.

The method adopted in this research was based on the factor cost method. This involved

identifying the components of vehicle costs that vary with the amount of elapsed time (mostly

wages, interest on capital employed or tied up in inventory on wheels, and licensing fees). It also

considered inventory costs.


The research shows that direct costs of variability can be rather high for those in JIT systems

and more than twice the cost of wages and other operating costs. This is consistent with

observations in the literature (Huang and Whalley, 2008). The research suggests that economic

costs and economic implications are important and can be significant. Policy initiatives

impacting delays must consider the balance since there is a strong correlation between delay and

economic outcomes for the bi-national regions. Security is critical at the borders, and a variety

of operational strategies may be adopted to manage delays but economic consequences are

sometimes non-trivial. Hence, a balance must be struck. Future research along several directions

may enhance the assessment of economic costs:

Enhanced data sources, if available especially pertaining to crossing time fine-tuned by

category.

Better estimates of shipper based reliability at border ports of entry.

Improved assessment of direct cost reliability based on alternative theories based on

preferred arrival and departure and those sensitive to built-in buffers.

In addition, the current work is based on near real time/archived data. In subsequent

work, this could be extended to real time applications. The El Paso Regional

Management Information System (RMIS) developed by researchers at the Center for

Intelligent International Transportation Research at Texas Transportation Institute

provides a framework for enabling this process.

Conduct a study of broader economic implications. Prior research along these lines has

primarily focused on the partial equilibrium methods with several assumptions made in

regard to substitution elasticities and other elasticities. These assumptions will need to be

reviewed in light of current economic situations as well as other assumptions used to

extrapolate broader impacts.

Consider policy sensitivity aspects and their direct implications to costs.


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APPENDIX 1: BRIDGE OF THE AMERICAS’ DETAILS

Infrastructure and the Services Available at the Bridge of the Americas

Bridge Details:

BOTA consists of two adjacent bridges, one for northbound and one for southbound

traffic. There are two dedicated truck lanes on the outside of each bridge –four lanes total.

Inspection Booth:

BOTA is open 24 hours a day, 7 days a week to both passenger vehicle and pedestrian traffic.

Commercial traffic services are limited to 6:00 am to 6:00 pm for northbound traffic and 8:00 am

to 9:00 pm for southbound traffic.

Tolls:

By treaty, there are no tolls on the BOTA.

Capacity:

There are a total of three northbound commercial lanes exiting the Cordova Mexican Aduana Ex

port lot in Cd. Juarez, Mexico – one Fast Lane and two regular commercial lanes. The United

States side of the bridge is owned by the International Boundary Water Commission (IBWC)

and the Commission de Limites y Aguas (CILA).

There are a total of 14 primary inspection stations for passenger vehicles entering the United

States. Passenger vehicles undergo Customs, Immigration and Agricultural inspection at the

primary inspection points. At the discretion of the inspector, passenger vehicles may be pulled

aside into a stall for secondary inspection.

There are a total of 4 primary inspection stations for pedestrians entering the United States.

Pedestrians needing to go through agricultural or secondary inspections either enter this area

once they have crossed the bridge (following signage), or they are directed to the secondary

inspection areas after going through primary inspection.

There are a total of eight passenger vehicle lanes (four northbound and four southbound), and

four (two northbound and two southbound) commercial vehicle lanes crossing on the bridge.

There are Customs, Immigration, and Agricultural inspections performed going northbound on

the U.S. side.

Programs:

Free and Secure Trade (FAST)


Figure IX-1. BOTA Land Port of Entry: View from the Mexican Side


APPENDIX 2: COMMODITY PROFILES (PORTS OF ENTRY) (BY VALUE [2008])

Tables XI-1 to XI-10 shows the commodity profiles of several POE’s.

Table XI-1. Commodity Profile Brownsville Exports to Mexico

BROWNSVILLE Soya beans 10.3% Other parts and accessories 8.3% Petroleum oils and oils obtained from bituminous minerals (other than crude) and preparations containing by weight 70% or more of petroleum oils or of oils obtained from bituminous minerals, these oils being the basic constituents of the preparations, other than waste oils

8.0%

Natural gas, in the gaseous state 7.3% Hearing-aids (excluding parts and accessories) 5.5% Processors and controllers, whether or not combined with memories, converters, logic circuits, amplifiers, clock and timing circuits, or other circuits

5.4%

Transmission apparatus 5.1% Articles of iron or steel 4.5% Optical media 3.3% Polyethylene having a specific gravity of 0.94 or more 3.2% Parts and accessories suitable for use solely or principally with the apparatus of division 76 - with the apparatus and equipment of groups 761 and 762 and subgroups 764.3 and 764.8

3.0%

Injection- or compression-types of moulds for rubber or plastics

3.0%

Cotton (other than linters), not carded or combed 3.0% Other apparatus 3.0% Other polyethers 2.9% Other articles 2.8% Rape or colza seeds, whether or not broken 2.6% Tantalum, unwrought (including bars and rods obtained simply by sintering); waste and scrap; powders

2.5%

Flat-rolled products of iron or non-alloy steel, not clad, plated or coated, not further worked than hot-rolled - of a width of 600 mm or more, in coils

2.4%

Articles for the conveyance or packing of goods.; stoppers, lids, caps and other closures

2.4%

Paraffin wax, microcrystalline petroleum wax, slack wax, ozokerite, lignite wax, peat wax, other mineral waxes, and similar products obtained by synthesis or by other processes, whether or not colored

2.4%

Polycarbonates 2.3% Parts and accessories for machines, appliances, instruments and apparatus.

2.3%

Whey and modified whey, whether or not concentrated or containing added sugar or other sweetening matter

2.3%

Plugs and sockets 2.2%


Table XI-2. Commodity Profile Eagle Pass Exports to Mexico (Primarily Agriculture)

EAGLE PASS Soya beans 21.0% Other parts and accessories 7.7% Maize (not including sweet corn), unmilled other 7.3% Polyethylene having a specific gravity of 0.94 or more 6.0% Flours and meals of oil-seeds or oleaginous fruits (excluding mustard flour), non-defatted, partially defatted, or defatted and wholly or partially refatted with their original oils

5.4%

Brewing or distilling dregs and waste 4.6% Knitted or crocheted fabrics. 4.5% Propane, liquefied 4.1% Polypropylene 3.6% Reciprocating piston engines of a cylinder capacity exceeding 1,000 cc

3.3%

Articles for the conveyance or packing of goods.; stoppers, lids, caps and other closures

3.1%

Prepared explosives (other than propellant powders) 2.9% Polyethylene having a specific gravity of less than 0.94 2.5% Textile fabrics impregnated, coated, covered or laminated with plastics, other than those of heading 657.93.

2.3%

Bituminous 2.3% Motor vehicles for the transport of persons. 2.2% Other fructose and fructose syrup, containing in the dry state more than 50% by weight of fructose

2.2%

Oil-cake and other solid residues (except dregs), whether or not ground or in the form of pellets, resulting from the extraction of fats or oils from oil-seeds, oleaginous fruits and germs of cereals of soya beans

2.1%

Other wheat (including spelt) and meslin, unmilled 2.0% Crude oil, whether or not degummed 1.9% Polystyrene other 1.9% Milk, in solid form, of a fat content, by weight, not exceeding 1.5%

1.9%

Motor vehicles for the transport of goods. 1.8% Trousers, bib and brace overalls, breeches and shorts 1.8% Malt, whether or not roasted (including malt flour) 1.6%


Table XI-3. Commodity Profile El Paso Exports to Mexico (Primarily Maquila Products)

EL PASO Parts and accessories (other than covers, carrying cases and the like) suitable for use solely or principally with the machines of subgroups 751.1, 751.2, 751.9 and group 752 -for the machines of group 752

20.9%

Other electric conductors, for a voltage not exceeding 1,000 V

6.1%

Motor vehicles for the transport of persons. 5.7% Other parts and accessories 5.4% Petroleum oils and oils obtained from bituminous minerals (other than crude) and preparations., containing by weight 70% or more of petroleum oils or of oils obtained from bituminous minerals, these oils being the basic constituents of the preparations, other than waste oils

4.9%

Other articles 4.3% Parts suitable for use solely or principally with the apparatus falling within subgroups 772.4, 772.5 and 772.6 - Other parts

4.0%

Processors and controllers, whether or not combined with memories, converters, logic circuits, amplifiers, clock and timing circuits, or other circuits

3.9%

Other instruments and appliances 3.9% Other electrical apparatus for switching or protecting electrical circuits, or for making connections to or in electrical circuits

3.9%

Articles of iron or steel. 3.7% Other wheat (including spelt) and meslin, unmilled 3.5% Parts and accessories 3.4% Electronic integrated circuits - Other 3.2% Copper wire - of refined copper 3.0% Articles for the conveyance or packing of goods.; stoppers, lids, caps and other closures

2.8%

Maize (not including sweet corn), unmilled other 2.6% Vacuum cleaners - parts 2.2% Textile fabrics impregnated, coated, covered or laminated with plastics, other than those of heading 657.93.

2.2%

Plugs and sockets 2.0% Aluminum alloys 1.9% Refined copper 1.8% Winding wire 1.7% Syringes, needles, catheters, cannulae and the like 1.6% Soya beans 1.6%


Table XI-4. Commodity Profile Hidalgo Exports to Mexico

HIDALGO

Video games of a kind used with a television receiver 19.2%

Petroleum oils and oils obtained from bituminous minerals

(other than crude) and preparations., containing by weight

70% or more of petroleum oils or of oils obtained from

bituminous minerals, these oils being the basic constituents of

the preparations, other than waste oils

10.4%

Parts and accessories suitable for use solely or principally

with the apparatus of division 76 - with the apparatus and

equipment of groups 761 and 762 and subgroups 764.3 and

764.8

9.5%

Telephone sets, including telephones for cellular networks or

for other wireless networks

9.3%

Parts and accessories for machines, appliances, instruments 5.3%

Parts suitable for use solely or principally with the apparatus 5.0%

Parts, suitable for use solely or principally with the machines

falling within group 716

3.8%

Other articles 3.7%

Telephone sets, including telephones for cellular networks or

for other wireless networks; other apparatus

3.5%

Parts for the appliances of group 747 3.3%

Machines and mechanical appliances having individual

functions.

2.5%

Other parts and accessories of bodies (including cabs) 2.4%

Parts and accessories (other than covers, carrying cases and

the like) suitable for use solely or principally with the

machines of subgroups 751.1, 751.2, 751.9 and group 752 -for

the machines of group 752

2.3%

Parts and accessories suitable for use solely or principally

with the machine tools of groups 731 and 733 - for machines

of group 733

2.0%

Cartons, boxes and cases, of corrugated paper or paperboard 1.9%

Other regulating or controlling instruments and apparatus 1.9%

Parts for boring or sinking machinery of heading 723.37 or

723.44

1.8%

Articles of iron or steel. 1.8%

Guts, bladders and stomachs of animals (other than fish),

whole and pieces thereof

1.8%

Other electric conductors, for a voltage not exceeding 1,000 V 1.7%

Syringes, needles, catheters, cannulae and the like 1.5%

Reception apparatus for television, whether or not

incorporating radio-broadcast receivers or sound or video

recording or reproducing apparatus

1.5%

Articles for the conveyance or packing of goods; stoppers,

lids, caps and other closures

1.3%

Storage units 1.3%

Other electrical apparatus for switching or protecting

electrical circuits, or for making connections to or in electrical

circuits

1.2%


Table XI-5. Commodity Profile Laredo Exports to Mexico

LAREDO Motor vehicles for the transport of persons. 14.8% Other parts and accessories 10.9% Other parts and accessories of bodies (including cabs) 7.9% Compression-ignition internal combustion piston engines (diesel or semi-diesel engines) of a kind used for the propulsion of vehicles of division 78

6.6%

Gearboxes and parts thereof 4.4% Maize (not including sweet corn), unmilled other 4.2% Parts and accessories 4.1% Copper wire - of refined copper 3.8% Polypropylene 3.6% Petroleum oils and oils obtained from bituminous minerals (other than crude) and preparations, containing by weight 70% or more of petroleum oils or of oils obtained from bituminous minerals, these oils being the basic constituents of the preparations, other than waste oils

3.4%

Other automatic data processing machines 3.2% Reciprocating piston engines of a cylinder capacity exceeding 1,000 cc

2.9%

Meat of bovine animals, fresh or chilled, boneless 2.8% Chemical wood pulp, soda or sulphate, other than dissolving grades, semi-bleached or bleached coniferous

2.7%

Milk, in solid form, of a fat content, by weight, not exceeding 1.5%

2.5%

Polyethylene having a specific gravity of 0.94 or more 2.5% Aluminum plates, sheets and strip, of a thickness exceeding 0.2 mm

2.4%

Motor vehicles for the transport of goods. 2.4% Parts, for the internal combustion piston engines of subgroups 713.2, 713.3 and 713.8 - suitable for use solely or principally with spark-ignition internal combustion piston engines.

2.4%

Other wheat (including spelt) and meslin, unmilled 2.2% Polyethylene having a specific gravity of less than 0.94 2.1% Articles for the conveyance or packing of goods.; stoppers, lids, caps and other closures

2.1%

Telephone sets, including telephones for cellular networks or for other wireless networks

2.1%

Tires, pneumatic, new, of a kind used on motor cars (including station wagons and racing cars).

2.1%

Other electric conductors, for a voltage not exceeding 1,000 V

2.0%


Table XI-6. Commodity Profile Brownsville Imports to United States

BROWNSVILLE Ceramic dielectric fixed capacitors, multilayer 9.2% Other parts and accessories 7.8% Special transactions and commodities not classified according to kind

7.5%

Other parts and accessories of bodies (including cabs) 5.4% Ballasts for discharge lamps or tubes 5.4% Static converters (e.g., rectifiers) 5.3% Flat-rolled products of stainless steel, not further worked than cold-rolled (cold-reduced) - of a width of 600 mm or more and of a thickness of 0.5 mm or more but not exceeding 1 mm

5.1%

Parts of the seats 4.8% Parts for boring or sinking machinery of heading 4.7%

Tantalum fixed capacitors 4.6% Parts of the equipment of heading 4.2% Flat-rolled products of stainless steel, not further worked than cold-rolled (cold-reduced) - of a width of 600 mm or more and of a thickness exceeding 1 mm but less than 3 mm.

4.0%

Styrene-butadiene rubber (SBR); carboxylated styrene-butadiene rubber (XSBR)

3.9%

Other inorganic acids 3.4% Radio-broadcast receivers not capable of operating without an external source of power, of a kind used in motor vehicles - combined with sound-recording or reproducing apparatus

2.7%

Fire extinguishers, whether or not charged 2.6% Motors (other than motors of an output not exceeding 37.5 W) and generators, direct current

2.5%

Brakes and servo-brakes and parts thereof 2.5% Other switches 2.3% Other parts for the machinery of group 2.3%

Thyristors, diacs and triacs (excluding photosensitive devices)

2.2%

Rock-drilling or earth-boring tools 2.1% Articles of iron or steel. 1.9% Binders (other than book covers), folders and file covers 1.9% Multiple-walled insulating units of glass 1.8%


Table XI-7. Commodity Profile Eagle Pass Imports to United States

EAGLE PASS Motor vehicles for the transport of goods. 28.8% Other parts and accessories 11.7% Motor vehicles for the transport of persons. 10.5% Trousers, bib and brace overalls, breeches and shorts 7.2% Springs and leaves for springs, of iron or steel 5.2% Bars and rods of iron or non-alloy steel, not further worked than hot-rolled, hot-drawn or hot-extruded, but including those twisted after rolling - of iron or non-alloy steel, containing indentations, ribs, grooves or other deformations produced during the rolling process or twisted after rolling

4.6%

Beer made from malt (including ale, stout and porter) 4.6% Parts of the seats of subgroup 4.4% Polyethylene terephthalate 3.9% Drive-axles with differential, whether or not provided with other transmission components, and non-driving axles; parts thereof

2.1%

Parts for the internal combustion piston engines of subgroups 713.2, 713.3 and 713.8

1.8%

Ignition wiring sets and other wiring sets of a kind used in vehicles, aircraft or ships

1.8%

Jerseys, pullovers, cardigans, waistcoats and similar articles, knitted or crocheted

1.7%

Unrefined copper (including blister copper but excluding cement copper); copper anodes for electrolytic refining

1.7%

AC motors (including universal (AC/DC) motors, but excluding motors of an output not exceeding 37.5 W)

1.3%

Trousers, bib and brace overalls, breeches and shorts 1.1% Reciprocating piston engines of a cylinder capacity exceeding 1,000 cc

1.1%

Line pipe of a kind used for oil or gas pipelines. 1.0% Flat-rolled products of iron or non-alloy steel, not clad, plated or coated, not further worked than hot-rolled - of a width of 600 mm or more, in coils

1.0%

Special transactions and commodities not classified according to kind

0.9%

Other hosiery 0.8% Other electric conductors, for a voltage not exceeding 1,000 V

0.8%

Other parts and accessories of bodies (including cabs) 0.8% Zinc, not alloyed 0.7% Parts for the air-conditioning machines of subgroup 741.5 0.7%


Table XI-8. Commodity Profile El Paso Imports to United States

EL PASO Reception apparatus for television, whether or not incorporating radio-broadcast receivers or sound or video recording or reproducing apparatus

18.7%

Other automatic data processing machines 13.0% Ignition wiring sets and other wiring sets of a kind used in vehicles, aircraft or ships

12.5%

Motor vehicles for the transport of persons. 6.0% Other parts and accessories 6.0% Parts of the seats of subgroup 821.1 5.7% Special transactions and commodities not classified according to kind

4.3%

Motor vehicles for the transport of goods. 4.1% Other instruments and appliances 2.8% Boards, panels (including numerical control panels), consoles, desks, cabinets and other bases, equipped with two or more apparatus of subgroup 772.4 or 772.5, for electrical control or the distribution of electricity (including those incorporating instruments or apparatus of groups 774, 881, 884 or of division 87, but excluding the switching apparatus of subgroup 764.1) - for a voltage not exceeding 1,000 V

2.8%

Refrigerators, household-type (electric or other), whether or not containing a deep-freeze compartment

2.5%

Other monitors 2.3% Other electric conductors, for a voltage not exceeding 1,000 V

2.2%

Parts and accessories 1.9% AC motors (including universal (AC/DC) motors, but excluding motors of an output not exceeding 37.5 W)

1.8%

Syringes, needles, catheters, cannulae and the like 1.8% Other apparatus for transmission or reception of voice, images or other data, including apparatus for communication in a wired or wireless network (such as a local or wide area network)

1.6%

Trousers, bib and brace overalls, breeches and shorts 1.5% Beer made from malt (including ale, stout and porter) 1.4% Reciprocating piston engines of a cylinder capacity exceeding 1,000 cc

1.4%

Taps, cocks, valves and similar appliances. 1.2% Parts for the internal combustion piston engines of subgroups 713.2, 713.3 and 713.8 - suitable for use solely or principally with spark-ignition internal combustion piston engines.

1.2%

Vacuum cleaners - with self-contained electric motor 1.1% Mowers for lawns, parks or sports grounds 1.1% Electrical lighting or signaling equipment (excluding articles of subgroup 778.2), windscreen wipers, defrosters and demisters, of a kind used for cycles or motor vehicles

1.1%


Table XI-9. Commodity Profile Hidalgo Imports to United States

HIDALGO Reception apparatus for television, whether or not incorporating radio-broadcast receivers or sound or video recording or reproducing apparatus

11.3%


8.4%

Radio-broadcast receivers not capable of operating without an external source of power, of a kind used in motor vehicles - combined with sound-recording or reproducing apparatus

7.2%


7.0%

Petroleum oils and oils obtained from bituminous minerals (other than crude) and preparations

6.6%

Other parts and accessories of bodies (including cabs) 4.6% Other parts and accessories 4.4% Boards, panels (including numerical control panels), consoles, desks, cabinets and other bases

4.3%

Parts for the pumps, compressors, fans and hoods 4.1%

Avocados, guavas, mangoes and mangosteens, fresh or dried

4.0%


3.8%


3.7%

Orange juice 3.5% Other apparatus for transmission or reception of voice, images or other data, including apparatus for communication in a wired or wireless network (such as a local or wide area network)

3.0%

Other switches 2.9% Drills of all kinds 2.7% Vacuum cleaners - with self-contained electric motor 2.6% Lemons and limes fresh or dried 2.5% Other tools 2.1% Syringes, needles, catheters, cannulae and the like 1.9% Parts for the air-conditioning machines of subgroup 741.5 1.9% Portable automatic data processing machines, weighing not more than 10 kg, consisting of a least a central processing unit, a keyboard and a display

1.9%

Tomatoes, fresh or chilled 1.9% Radar apparatus, radio navigational aid apparatus and radio remote control apparatus

1.8%

Strawberries, raspberries, blackberries, mulberries, loganberries, cranberries, bilberries, and other fruits of the genus Vaccinium, fresh

1.7%


Table XI-10. Commodity Profile Laredo Imports to United States

HIDALGO Reception apparatus for television, whether or not incorporating radio-broadcast receivers or sound or video recording or reproducing apparatus

11.3%


8.4%

Radio-broadcast receivers not capable of operating without an external source of power, of a kind used in motor vehicles - combined with sound-recording or reproducing apparatus

7.2%


7.0%

Petroleum oils and oils obtained from bituminous minerals (other than crude) and preparations., containing by weight 70% or more of petroleum oils or of oils obtained from bituminous minerals, these oils being the basic constituents of the preparations, other than waste oils

6.6%

Other parts and accessories of bodies (including cabs) 4.6% Other parts and accessories 4.4% Boards, panels (including numerical control panels), consoles, desks, cabinets and other bases,

4.3%

Parts for the pumps, compressors, fans and hoods of subgroups 743.1 and 743.4

4.1%

Avocados, guavas, mangoes and mangosteens, fresh or dried

4.0%


3.8%


3.7%

Orange juice 3.5% Other apparatus for transmission or reception of voice, images or other data, including apparatus for communication in a wired or wireless network (such as a local or wide area network)

3.0%

Other switches 2.9% Drills of all kinds 2.7% Vacuum cleaners - with self-contained electric motor 2.6% Lemons and limes fresh or dried 2.5% Other tools 2.1% Syringes, needles, catheters, cannulae and the like 1.9% Parts for the air-conditioning machines of subgroup 741.5 1.9% Portable automatic data processing machines, weighing not more than 10 kg, consisting of a least a central processing unit, a keyboard and a display

1.9%

Tomatoes, fresh or chilled 1.9% Radar apparatus, radio navigational aid apparatus and radio remote control apparatus

1.8%

Strawberries, raspberries, blackberries, mulberries, loganberries, cranberries, bilberries, and other fruits of the genus Vaccinium, fresh

1.7%


APPENDIX 3: INTERVIEW INSTRUMENT

Interview Guide for Operations Contact Information

Name _________________________________________________________

Organization _________________________________________________________

Position _________________________________________________________

Address _________________________________________________________

_________________________________________________________

Telephone ______________________ Email address________________________

I. Cross-Border Operations.

1. Please describe your typical supply chain.

2. Do you currently have C-TPAT certification?

3. What are the primary products, volume, and origin/destination that your company moves by

truck across the border?

Product Inbound(I)

Outbound(O)

Origin

Location/Facility

Destination

Location/Facility

FAST

Non-

FAST

# of shipments

per month

(truckloads)

# Empty

Trips

4. Do you experience any seasonal fluctuations in your cross-border operations?

5. Do you hold any inventory? If yes, where (El Paso or Ciudad Juarez)?


6. What are the terms of sale for your products/cargo? Where does cargo change

ownership?

A) FOB B) Mid-bridge C) Other (list)

7. Do you have any plans for future developments? If so, could you provide more detail?

8. What are the main impediments to your cross-border operations (delays, costs, current

infrastructure, access roads, etc.)?

II. Trip Characteristics

9. Are carriers bound to schedules and bridge selections made?

10. What is the variation in travel time from origin to destination for your crossing? (Max

and min time)

11. Which bridge do you typically use for your cross-border operations?

12. What factors are important for deciding a) trip timing b) bridge selection, and who

makes these decisions?

13. What is the average travel time from origin to destination for your crossing?

Time of

Day Origin Destination

FAST /

Non-FAST

Range of Travel

Times (minutes)

Average Travel Time

(minutes)

14. Does travel time vary during the day?

15. How does this variability affect the supply chain and decisions?


16. Do you adopt specific strategies to deal with crossing delays at your port of entry?

A) Change buffer time; B) Change delivery time; C) Change route; D) Change POE; E) Other

17. Do you pass on the delay cost to your ultimate customer?

III. Cost and Performance Parameters to Attract Sustaining Levels of

Traffic

18. Currently, how do you manage your company’s shipments?

□ Shipments are carried by the company (internal transportation)

□ Hire one carrier company

□ Hire two or more carrier companies

19. Approximately how much is the actual cost of every shipment/container per unit (MX-

Pesos)? □ 0 to 499

□ 500 to 999

□ 1,000 to 1,499

□ 1,500 to 1,999

□ 2,000 or more

20. Are there any other costs related to your shipments?

□ Yes

□ No

21. If Yes, what are those other costs and how much do you pay for each?

Additional Costs Description Estimated Cost $


22. Please mark the cell(s) with the parameters that most influence your decision-making

process regarding your border crossing operations:

Parameter Cost Crossing

Time Reliability

Inspection

Simplification

Number

of Trips

per day

Distance

from the

POE

Type of

Commodity

Cost

Crossing Time

Reliability

Inspection

Simplification

Number of

Trips per Day

Distance from

the POE

Type of

Commodity

23. Would you use a New Border Crossing System if:

the New Border Crossing System and Increase Costs

Significantly improves border-crossing

times?

□ Yes

□ No

Increases the number of crossings per

day?

□ Yes

□ No

Has an excellent trip and schedule

reliability?

□ Yes

□ No

24. If Yes, how much are you willing to pay for said system?

Expected Increase

in Cost (Pesos) Yes/No

200 or less

200 to 400

400 to 600

600 to 800

800 to 1000

More


IV. Information System

25. What border-crossing information does your company use on a regular basis?

26. What information elements would you like to have in a border-crossing information

system?

27. In what format would you prefer for the information to be provided?

border delays and economic impact to the freight … · since economic costs fall into a large...

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