naod mekonnen : agriculture and rural transport in ethiopia panel study (2)

By Naod Mekonnen Anega (Lecturer II, Addis Abeba unviverity )

[email protected]@bdscdr.com

The Effect of Rural Road Transport on Crop Productivity, Efficiency, and Commercialization of Smallholder Farmers

in Ethiopia : Evidence from ERHS Panel Data

ADDIS ABABA UNIVERSITYCDS presnetation

mailto:[email protected]

mailto:[email protected]

Introduction Background to the study Statement of the problem Research objectives Working definitions Conceptual framework Materials and Methods The data source and type Sampling Frame Sampling Design Methods of Data analysis Descriptive methods Econometric modelResult and Discussion Descriptive result Econometric result Accessibility and Mobility vs. production and partial productivity Accessibility and mobility vs. total factor productivity Accessibility and mobility vs. technical efficiency Accessibility and mobility vs. commercialization Accessibility and mobility vs. consumption summary of the finding Conclusion and Policy implication

Outline

2

Background• Rural people are poor mainly due their isolation from socio

economic activities and opportunities (Carney, 1999).

• Lack of access to road transport is also one of the factors explaining low agricultural growth.

• Globally, there are still 1 billion people in rural areas without adequate access to all-weather roads ( IBRD, 2014).

• Rural isolation are more real in developing countries in general and Sub Saharan Africa (SSA) in particular(Faiz, 2012)

Introduction

3

Introduction

4

challenges ?

• The average Rural Access Index (RAI) for SSA was just 34 % (RAI for middle-income countries is 94 %).

• The road-to-population ratio of Africa was just 26 km per 10,000 inhabitants• Less than one-fourth of total SSA road network is paved•Only 14 per cent of rural households have access to a paved road

African countries invested 15 % of GDP in transport infrastructure over the period 2005–2012, on average ( India and China invested about 32 %t and 42 % of GDP, respectively (Double as compared to Africa)

The, rural farmers hardly use motor vehicle as a result they spent significant time, energy and effort in moving small loads over relatively short distances. This could have been saved for agriculture

Low Investment

Low access

Low mobility

Rural road transport In SSA Africa

Accounts 80 % of freight and 90 % of passenger traffic

Statement of the problem

5

Road density per 1000 sq.km is 49.1 km (ERA,2014)

14675 kms of Gravel road

Road density per 1000 population is 0.66 km (ERA,2013)

Account for 90 to 95 % of motorized inter-urban freight and passenger movements (ERA,2013)

Road Transport Profile of Ethiopia

The total road network of the country is 63083 kms which consists of :

31550 kms of rural roads and 6983km of Woreda

roads (ERA,2013)

(9875 kms of Asphalt (15 percent of the road network), (EARA,2013)


6

the role rural road transport in Ethiopia in improving rural livelihoods and agricultural growth is expected to be tremendous because : Agriculture is the dominant sector

(employing 80 % of the labour force)

Rural road transport accounts 90 % of rural transport

About 83 percent of the population lives in rural area


7

Rural road transport in Ethiopia is characterized by low physical access and mobility

Physical accessibility

Low transport (mobility) facilitates

• Proportion of area further than 5 km from all-weather roads is 40.5percent• The average distance to all-weather roads is 6 kms • Close to 70 percent of the rural population in Ethiopia still need to travel about six hours to

reach all weather roads • Most of these roads are dry weather roads that cannot be passable by any formal transport

modes during the wet season • The average rural accessibility index (RAI) for the country is around 50 percent • The proportion of number of rural population within 2km access is only 28 percent

• Mainly rely upon pack animals and majority carrying loads on their own heads


8

This poor access and Mobility has been a…

• Major impendent to rural development• Major impendent to agricultural

development • Major constraint to the overall efforts to

improve agricultural growth and reduce poverty … (World Bank (2004); Wondemu (2015).Moreover, the agriculture

sector didn’t witnessed significant change in terms of

…… • Production

• Productivity

• Market Integration

• Empirical studies shows that rural roads can play a meaningful role in fostering consumption; improving rural income; and reducing poverty in Ethiopia(Worku 2011; Decron, 2009; Wondimu, 2013; Kiflet et al 2012; Lulit, 2012).

• However, much less has been studied on the effect and role of rural road access and mobility on agricultural productivity, efficiency and commercialization of smallholder farmers. On top that, the pro-poorness of rural roads access has not been addressed in this studies.

• Although there are few empirical studies on the effect of rural road on agricultural productivity (for example, Kassali et al, 2012; Wondemu, 2015; Tunde & Adeniyi, 2012; Lee, 2010), these studies did not show the effect of mobility.


9

• Investigate the contribution of road access and mobility to crop production and productivity (partial and total productivity )

• Estimate the effects of rural road access and mobility on technical efficiency of smallholder farmers ;

• Analyze the contribution of rural road access and mobility to market participation and level of commercialization in smallholder farmers in Ethiopia;

• Investigate the contribution of rural road access to consumption and;

• Analyze whether rural accessibility in rural roads is pro-poor or not.

Research objectives

10

• Rural accessibility: According to Faiz (2012), physical accessibility in rural context can be defined by the type of road quality or access to all weather roads. This definition has been used by various empirical studies (Wondemu et al, 2012; Dercon et al,2011; Arethun et al,2012).

• Rural mobility: Mobility is the means with which people choose to move themselves or their goods around or simply mobility refers to the mode of transport used for economic activities by a particular household Maunder et al, (2000). This definition has been used by other empirical studies (Kassali et al, 2011).

• Commercialization: ratio of gross value of all crop sales over gross value of all crop production multiplied by hundred (Strasberg et al.,1999 in Abera, ,2009

Key Definitions

11

Data source • The empirical data used for this study were drawn from panel

survey of Ethiopian Rural Socioeconomic survey (ERSS) prepared by the CSA and the World Bank Living Standards Measurement Study- Integrated Surveys of Agriculture (LSMS-ISA) team. While the first survey was conducted in 2011, the second round was conducted after two years later in 2013.

Sampling frame• The sampling frame for both rounds surveys of the Ethiopia Socio

Economic Survey (ESS) is constructed based on Central Statistics Agency (CSA) survey sampling frame containing Enumerations Area (EAs) representing rural Ethiopia

Materials and Methods

12

13

Total EAs Rural EAs Small town EAs Mid and Large Town EAs

National 433 290 43 100

Tigray 49 30 4 15

Afar 13 10 2 1

Amhara 86 61 10 15

Oromiya 85 55 10 20

Somali 26 20 3 3

Benishangul-Gumuz 11 10 1 0

SNNP 99 74 10 15

Gambela 12 10 1 1

Harari 14 10 1 3

Dire Dawa 18 10 1 7

Addis Ababa 20 NA NA 20

Materials and Methods First stage sampling of Enumeration Areas

14


EAs HHs

Amhara 58 678

Afar 5 103

Tigray 30 345

Oromia 55 638

Somalie 20 199

Benshangul_Gumz 10 113

SNNP 70 863

Gambella 10 102

Harari 10 120

Diredawa 10 115

Country level 278 3276

Sampling of rural EAs and households

• Panel data was crated using the following criterions:

• observation from small towns and mid towns were excluded

• households who did not produce in both production periods were also excluded

• for consumption analysis hhs with missing and partial information were excluded

• for total factor productivity analysis observation with missing inputs values were excluded as the DEA wouldn't give values for missing values


15

Method of data analysis : a. Descriptive Statistics• The study used Descriptive statistics • a special STATA software program developed by the World Bank

for the impact elevation of the project called “Ethiopian Rural Capacity Building Program“(RCBP) is also used to make mean comparison test.


16


17

b. Summary Econometric Model Objectives Model

Investigate the contribution of road access and mobility to crop production and productivity (partial and total productivity )

• Fixed effect and random effect model with Hausman test • For TFP first the total factor productivity index was estimated using the Malmquist Index (DEA) , then run regression to investigate the effect of accessibility, mobility other socio economic variables

Estimate the effects of rural road access and mobility on technical efficiency of smallholder farmers

Using the Stochastic production frontier , then estimate the effect of accessibility , mobility and other socio economic variables using Battese and Coelli (1995) one step procedure

Analyze the contribution of rural road access and mobility to market participation and level of commercialization in smallholder farmers in Ethiopia;

Craggit Double hurdle model to estimate effect of accessibility, mobility and other variables on market participation and the level of commercialization to control unobserved heterogeneity and testing endogeneity in commercialization estimation the CRE and CFA were used .

Investigate the contribution of rural road access to consumption

Fixed effect and random effect model + Hausman test to select between fixed and random effect

Analyze whether rural accessibility in rural roads transport is pro-poor or not.

A new fixed quintile model developed by Powell (2015) was used to analyze the effect of accessibility across different consumption groups

Microsoft Office Word Document

Microsoft Office Word Document


18

Definitions Type of data Age yearsGender ( 1 male =0 Female)Education years of schooling Household size changed based on nutrition scales prepared FAO

number

Farm size Hectare Fertilizer kg Seed kgConsumption changed to real consumption using CSA CPI Real consumption per adult equivalent Labour Man days oxen Number of used for ploughingNumber of livestock owned Tropical livestock units Irrigation use 1 =users 0 =non usersSoil fertility Index Access to credit 1= yes 0=No Access to ext. 1=yes 0= noDistance to market KmMobility (mode of transport used for agricultural purposes) 1=foot 2=IMT 3= Animal drawn cart Farm income ETBOutput changed to real output using CSA producer price

Real value of output

Value of sold ETB

Definition of variables used

Result and Discussion

19

Descriptive resultVariables Obs. Mean SD Min Max

Total value of output in (ETB) 5050 5196 8638 138815

Sex of the household head (male =1) 5050 0.804 0.397 0 1

Age of the household head in year 5050 45.61 14 17 99Years of schooling of the household head 5050 1.863 2.709 0 19Family size in adult equivalent 5050 4.573 1.952 0.74 13.22Land size (ha) 5050 2.247 2.046 0 9.98Total amount of fertilizer used (kg) 5048 56.61 88.59 0 768.4Total amount of seed used (kg) 5050 27.3 40.52 0 200Total labour used (man days) 5050 388.7 332.2 0 1,353Extension access (yes=1) 5050 0.35 0.474 0 1Credit accesses (yes =1) 5051 0.218 0.413 0 1Irrigation access (yes=1) 5049 0.12 0.336 0 1Number of ploughing oxen 5050 1.012 1.241 0 14

Number of farm capital 5051 4.725 3.465 0 31Total livestock units (TLU) 5051 6.899 7.42 0 169.8

Descriptive statistics of household’s characteristics Source: Own depiction from the Ethiopian Socio-economic survey data


20

Mean comparison by survey periods

Variables Obs 2011(=0) 2013(=1) (1-0) P valueReal value of production (ETB) 5050 4737.99 5558 820 0.000***Number of farm capital owned 5050 4.4782 4.9826 0.504 0.000***Years of schooling of household 5050 1.8591 1.8657 0.007 0.9318Age of the head 5045 44.7406 46.3056 1.565 0.0002Land size (Ha) 5049 2.153 2.3979 0.245 0.000***Amount of fertilizer used (Kg) 5048 52.6175 61.5589 8.941 0.004***Family size in adult equivalent 5050 4.5017 4.8086 0.307 0.000***Amount of seed used (Kg) 5050 26.7971 32.3969 5.6 0.00***Total labour used in mandays 5050 383.741 392.642 8.901 0.3445Extension contact(Yes=1) 5050 0.3293 0.3786 0.049 0.003***Access to credit 5050 0.2584 0.1793 -0.079 0.000***Irrigation access (Yes=1) 5049 0.1293 0.1305 0.001 0.90001Total livestock units (TLU) 5050 6.2447 7.3794 1.135 0.000***Number of ploughing oxen 5050 1.4186 1.4993 0.081 0.002***

Significance level *=10%**=5% ***=1%Source: Own depiction from the Ethiopian Socio-economic survey data


21

Explanatory Variable 2013 2011 Difference P-Value

Real consumption per capita 138.12 126.011 11.587 0.0002 ***

Land to family labor ratio 0.5924 0.6316 -0.039 0.0334 **

Dependency ratio 0.7329 0.6987 0.034 0.0767 *

Participation in off farm income 0.2472 0.2578 -0.011 0.4224

Sex of the head 0.8111 0.8226 -0.011 0.3273

Age of the head 46.3625 44.7499 1.613 0.0003 ***

Head’s years of schooling 1.8888 1.8617 0.027 0.7384

Access to credit 0.1788 0.2597 -0.081 0.000 ***

Access to irrigation 0.1443 0.1553 -0.011 0.3081

Road Quality 0.3079 0.3024 0.006 0.6929

Oxen in tropical livestock units (TLUs) 7.1992 6.3639 0.835 0.000 ***

Logarithm of agricultural yield 7.9254 6.8532 1.072 0.000 ***

Family size in Adult equivalent 4.8731 4.5382 0.335 0.000 *** Level of significance *10% ; **5% ; ***1%

mean comparison for consumption


22

Heterogeneity in rural accessibility and mobility

2011

2013

610

842

1619

1980

Poor access Good access

On Foot

Modern mode of trasport

Tradional mode of transport

3816

321

914

75.55%

6.36 %

18.1 %Percent Frequency

Rural accessibility Rural mobility


23

Road quality indicator Year Frequency Percent

Good access 2011 610 27.37

Good access 2013 842 29.84

Good access Polled 1452 28.75

Poor access 2011 1619 72.63

Poor access 2013 1,980 70.16

Poor access Polled 3599 71.25

Variable Obs 2013 2011 Difference P-value

Good access 5051 0.298 0.2737

0.025 0.0541*

Level of significance *=10%**=5% ***=1%

Rural road quality condition


24

Mode of transport used by households in villages with good access (=1)

mode of transport Freq. Percenton foot 1095 75.41Modern mode of transport 98 6.75

Traditional mode of transport 259 17.84Mode of transport used by households in villages with poor

access (=0)

Type of mode of transport used Freq. Percenton foot 2721 75.6Modern mode of transport 223 6.2Traditional mode… 655 18.2

Mode of transport used ( period =2011)

Mode of transport used Freq. Percent

On foot 1808 81.11

Modern mode of transport 125 5.61

Traditional mode of transport 296 13.28

Mode of transport used ( period =2013)

Mode of transport used Freq. Percent

On foot 2008 71.16

Modern mode of transport 196 6.95

Traditional mode of transport 618 21.9


25

Variable Obs Good access(=1) Poor access(=0) (1)-(0) P-Value

Age of the head 5045 46.4745.268

1.205 0.0098 ***Years of schooling 5050 2.018 1.799 0.219 0.0094 ***Land size(ha) 5049 2.409 2.241 0.167 0.0042 ***Quantity of fertilizer 5048 60.42 55.67 4.752 0.0142 **Number of labour 5050 381.7 391.53 -9.824 0.3415Access to credit 5050 0.23 0.212 0.027 0.0354 **Irrigation use 5049 0.14 0.123 0.026 0.0114 **Quantity of seed 5050 30.17 29.82 0.349 0.7817Number of oxen 5050 1.49 1.450 0.045 0.1198Real value of output 5050 5606 5030.77 575.31 0.0322 **Value of output sold 5050 1256 938.99 317.03 0.0007 ***No. of farm capital 5050 5.25 4.561 0.692 0.0000 ***Family size 5050 4.77 4.6311 0.146 0.0159 **No. of livestock (TLU) 5050 6.70 6.9476 -0.24 0.3037Commercialization index 5050 0.19 0.171 0.023 0.0020 ***Nonfarm income 5040 846.69 688.964 157.73 0.1251Extension contact 5050 0.43 0.324 0.113 0.0000 ***

Level of significance *=10%**=5% ***=1%

Mean comparison of key variables by road quality


26

Mean comparison of dependent variables by road quality

Dependent variables Good access=(1) Poor access (=1) Diff.(1-0) P-Value

Total value Production 5606.1 5030.772 575.309 0.0322**

Yield (Q/ha) 7.49 7.4 0.08 0.236

Total factor productivity 1.3881 1.344 0.044 0.2748

Technical efficiency 0.5828 0.392 0.191 0.00***

Commercialization index 0.1945 0.171 0.023 0.002***

Market patciaption 0.6508 0.612 0.039 0.0102**

Tota value of quantity sold 1256 938.993 317.026 0.0007***

Real consumption 173.7248 113.395 60.33 0.00***


27

Mean comparison real value output by survey period

Period Good access(=1) Poor access(=0) Diff(1-0) P-Value

[overall] 5606.08 5030.772 575.309 0.0322**

2011 4877.75 4685.330 192.415 0.6794

2013 6133.74 5313.232 820.503 0.008***

Mean comparison of output by mode of transport used

Mode of transport used Good access(=1) Poor access(=0) Diff(1-0) P-Value

Foot 4114.84 3444.522 670.319 0.006***

Modern mode 15840.51 16435.907 -595.395 0.7729

Traditional mode 8038.26 7737.404 300.854 0.5793


28

2011 20130

1000

2000

3000

4000

5000

6000

7000

Good road qualityPoor road quality

2011 20136.46.66.8

77.27.47.67.8

8

Good road qualityPoor road quality Trend in mean value of crop production

Trend in mean values of agricultural productivity

Mean value of output sold (2011) Mean value of output sold (2013) 0

200

400

600

800

1000

1200

1400

Good accessPoor access

Trend in mean value of output sold

Percentage of Market participation (2011)

Percentage Market participation (2013)

0

0.2

0.4

0.6

0.8

Good accessPooor acccess

Trend in mean value of market participation

Commercialization index(2011)

Commercialization index(2013)

0

0.05

0.1

0.15

0.2

0.25

Good accessPoor access

Trend in commercialization index in 2011 and 213


29

050

000

1000

0015

0000

R

eal v

alue

of o

utpu

t

0 100 200 300

HH Distance in (KMs) away from Nearest Market

60000

020

000

4000

0

0 100 200 300HH Distance in (KMs) away from Nearest MarketRe

al

valu

e o

f out

put s

old

020

040

060

080

010

00

Real

con

sum

ption

per

cap

ita

0 50 100 150 200 250HH Distance in (KMs) away from the Nearest major Market

2011 20130

20406080

100120140160180200

Good AccessPoor access

Trends in real consumption per capita


30

Mean comparison Variables

Good

access Poor access Diff.(1-0) P-Value

Market participation (pulled) 5051 0.6508 0.6121 0.039 0.0102**

Market participation (2011) 2229 0.5344 0.5028 0.032 0.1828

Market participation (2013) 2822 0.7352 0.7015 0.034 0.0712*

Market participation (foot=1) 3816 0.6137 0.5821 0.032 0.0729*

Market participation (Modern mode 2) 321 0.6429 0.4798 0.163 0.0069***

Market participation (Traditional mode) 914 0.8108 0.7817 0.029 0.3305

Commercialization index(polled) 5051 0.1945 0.171 0.023 0.002***

Commercialization index(2011) 2229 0.21 0.1559 0.054 0.000***

Commercialization index(2013) 2822 0.1832 0.1834 0 0.9856

Commercialization index(MT=1) 3816 0.1744 0.1567 0.018 0.039**

Commercialization index(MMT=2) 321 0.2501 0.1772 0.073 0.0271**

Commercialization index(TMT=3 914 0.2582 0.2284 0.03 0.0904* Level of significance *10% ; **5% ; ***1%

Commercialization variables by road quality


31

Variables Year Good Access Poor access Difference P value

Consumption per capita2011

166.47 108.471 58.003 0.00

consumption per capita2013

180.85 118.35 62.488 0.00

Econometric Result

32

Explanatory variables Fixed effect Random effectLogarithm labour(mandays) 0.0662*** 0.153***

(0.0176) (0.0123) Logarithm farm size 0.0793*** 0.124***

(0.0159) (0.0101) Logarithm fertilizer 0.0650*** 0.0703***

(0.0199) (0.0117) Logarithm seed -0.00622 -0.00857

(0.0177) (0.0129) Logarithm oxen 0.173* 0.126**

(0.102) (0.0572) Age of the head -0.00106 -0.000159

(0.00709) (0.00155) Sex of the head -0.240 0.290***

(0.211) (0.0615) Years of schooling 0.0123 0.0309***

Accessibility and mobility vs. crop production

Result and Discussion(0.0119) (0.00785)


33

Access to credit(yes=1) -0.117* -0.174*** (0.0684) (0.0509)

Access to extension(yes=1) 0.275*** 0.305*** (0.0785) (0.0544)

Access to irrigation(yes=1) -0.0328 0.176*** (0.112) (0.0643)

Year (Hickman neutral ) 0.446*** 0.368*** (0.0473) (0.0398)

Logarithm number of farm capital 0.0444 0.284*** (0.0589) (0.0357)

Road accessibility (1=good access) 0.0544 0.0309 (0.0642) (0.0457)

Modern mode of transport 1.542*** 1.596*** (0.117) (0.0856)

Traditional mode of transport 0.988*** 0.975*** (0.0803) (0.0567)

Family size (Adult equivalent) 0.0445 0.0896*** (0.0447) (0.0130)

Constant 6.2*** 4.475*** Level of significance *=10%**=5% ***=1%

Cont’d ………

34

Accessibility and mobility vs. agricultural productivity Explanatory variables Fixed effect Random effectLog of labour per unit of land in hectare 0.121** 0.377***

(0.0498) (0.0329)Log of seed per unit of land in hectare 0.00212 0.00168

(0.0180) (0.0129)Log of fertilizer per unit of land in hectare 0.0887*** 0.0845***

(0.0203) (0.0119)Log of number of plough oxen per unit of land 0.727*** 0.418***

(0.0539) (0.0340)Family size (Adult equivalent) 0.183*** 0.115***

(0.0433) (0.0128)Age of the household head 0.0179** 0.00115

(0.00701) (0.00159)Sex of the household head (1=male) -0.424** 0.334***

(0.215) (0.0620)Years of schooling of the head 0.0156 0.0327***

(0.0122) (0.00800)Access to credit (yes=1) -0.179** -0.206***

(0.0697) (0.0514)Access to extension(yes=1) 0.309*** 0.324***

(0.0802) (0.0551)Access to irrigation (yes=1) -0.0254 0.178***

(0.115) (0.0657)Access to all weather road (yes=1) 0.0391 0.0393

(0.0657) (0.0465)Modern mode of transport 1.606*** 1.628***

(0.120) (0.0870)Traditional mode of transport 1.118*** 1.050***

(0.0808) (0.0568)Constant 5.216*** 5.271***

(0.408) (0.118)Level of significance *=10%**=5% ***=1%


35

Accessibility and mobility vs. total factor productivity

Variable Good access Poor access Diff. P-Value

TFP change 1.3881 1.3441 0.044 0.2748

Efficiency change 1.2254 1.1824 0.043 0.2246

Technological change 1.1354 1.1391 -0.004 0.2541

Geometric Mean of Total Factor Productivity

Geometric mean comparisons by type of rural road accessibility

Period Efficiency change Technical change PECH SECH TFPCH2011 1.00 1.00 1.00 1.00 1.002013 1.035 1.136 1.154 0.897 1.170


36

Explanatory Variables Fixed effect Random effect Age of the head 0.000828 -0.000654

(0.00330) (0.000631)Years of schooling of the head 0.00541 0.00485

(0.00566) (0.00352)Logarithm of family size 0.167** 0.0246

(0.0817) (0.0206)Extension contact 0.224*** 0.184***

(0.0366) (0.0232)Logarithm of oxen 0.244*** 0.218***

(0.0290) (0.0225)Road quality -0.432*** -0.306***

(0.0853) (0.0620)Road quality *time 0.280*** 0.208***

(0.0527) (0.0386)Logarithm of farm size 0.0258*** 0.0144***

(0.00758) (0.00498)Irrigation access 0.0123 0.00643

(0.0537) (0.0273)Logarithm of mandays -0.0257*** -0.0176***

(0.00816) (0.00563)Logarithm of fertilizer 0.00409 -0.0206***

(0.0105) (0.00550)Modern mode of transport 0.00721 0.0477

(0.0559) (0.0385)Traditional model of transport 0.0301 -0.00445

(0.0379) (0.0249)Constant 0.787*** 1.101***

(0.201) (0.0531)R-squared 0.163

Total factor productivity: fixed and random effect model


37

Accessibility and Mobility vs. Technical efficiency

Hypothesis tests for model specification and inefficiency assumptions

Null Hypothesis Likelihood Ratio test df P-value Decision

Full model -8939.543 - - -

Cobb Douglas model -9120.502 21 0.000 Reject

H0: δ0 = δ1 = …. = δ10 =0 121.96 8 0.000 Reject

Hypothesis tests for model specification and inefficiency

Akaike's information criterion and Bayesian information criterion

df AIC BIC

Cobb Douglas production

22 18225 18428

Translog production 32 17965.09 18245.6

38

Explanatory variables Coef. Std.Err. Z P>z Coef. Std.Err. Z P>z Coef. Std.Err. Z P>z

Logarithm of land size 0.51704 0.0415 12.46 0.00 0.525331 0.0413 12.72 0.00 0.44991 0.039446 11.4 0.000

Logarithm of mandays 0.33781 0.03202 10.55 0.00 0.343933 0.0317 10.84 0.00 0.32286 0.02977 10.9 0.000

Logarithm of fertilizer 0.07135 0.05784 1.23 0.217 0.089146 0.0576 1.55 0.122 0.09632 0.054591 1.76 0.078

Logarithm of seed 0.0254 0.08591 0.32 0.767 0.042817 0.0857 0.5 0.617 0.09357 0.082852 1.13 0.259

Logarithm of oxen 0.7292 0.21714 3.36 0.001 0.703994 0.2163 3.26 0.001 0.64086 0.198747 3.22 0.001

Logarithm of farm capital 0.90236 0.12939 6.97 0.00 0.922782 0.1282 7.20 0.00 0.85362 0.121712 7.01 0.00

Years 0.04927 0.04182 1.18 0.239 0.037942 0.0423 0.9 0.369 -0.00991 0.044894 -0.22 0.825

0.5[lnmandays]2 -0.0004 0.02167 -0.02 0.985 0.000875 0.0211 0.04 0.967 -0.00271 0.020017 -0.13 0.893

0.5Lnland size]2 0.06915 0.02288 3.02 0.003 0.070787 0.0223 3.17 0.002 0.056129 0.021203 2.65 0.008

o.5LnFertilizer]2 0.08702 0.02014 4.32 0.00 0.079688 0.0201 3.97 0.00 0.057078 0.019009 3.00 0.003

0.5[LnSeed] 2 0.00584 0.03196 0.18 0.855 -0.0036 0.0319 -0.11 0.91 -0.03149 0.031017 -1.02 0.31

0.5[Lnoxen]2 -0.0305 0.15818 -0.19 0.847 -0.02036 0.1584 -0.13 0.898 -0.03166 0.145408 -0.22 0.828

0.5[Lnfarm capita]2 0.11363 0.06925 -1.64 0.101 -0.10258 0.069 -1.49 0.137 -0.10029 0.06646 -1.51 0.131

Ln(Mandays)*Ln(Land size) -0.0257 0.00888 -2.89 0.004 -0.0256 0.0088 -2.92 0.003 -0.02568 0.00831 -3.09 0.002

Ln(Mandays)*Ln(Fertilizer) 0.02868 0.00462 -6.21 0.00 -0.02922 0.0046 -6.37 0.00 -0.02664 0.004251 -6.27 0.00

LnMandays)*Ln(Seed) -0.0147 0.00593 -2.49 0.013 -0.01458 0.0059 -2.48 0.013 -0.01322 0.005444 -2.43 0.015

Ln(Mandays)*Ln(Oxen) -0.0801 0.02373 -3.38 0.001 -0.07573 0.0237 -3.2 0.001 -0.07304 0.02172 -3.36 0.001

Ln(Mandays)*Ln(Farm capital) -0.0925 0.01587 -5.83 0.00 -0.09538 0.0158 -6.05 0.00 -0.09002 0.014696 -6.13 0.00

Ln(Landsize)* Ln(Fertilizer) -0.0139 0.00507 -2.74 0.006 -0.01399 0.0051 -2.76 0.006 -0.01179 0.004839 -2.44 0.015

Ln(Landsize)*Ln(Seed) 0.0199 0.00617 -3.22 0.001 -0.01953 0.0062 -3.18 0.001 -0.01883 0.005866 -3.21 0.001

Ln(Landsize)*Ln(Oxen) -0.0591 0.02355 -2.51 0.012 -0.06143 0.0238 -2.58 0.01 -0.03788 0.0214 -1.77 0.077

Ln(Landsize)*Ln(Farm capital) -0.0234 0.01444 -1.62 0.105 -0.02364 0.0144 -1.64 0.101 -0.02467 0.013854 -1.78 0.075

Ln(Fertillizer)*Ln(Oxen) -0.0391 0.02118 -1.85 0.065 -0.03567 0.0212 -1.69 0.092 -0.02947 0.019592 -1.5 0.132

Ln(Fertillizer)*Ln(Farm capital) -0.029 0.01402 -2.07 0.038 -0.03298 0.014 -2.36 0.018 -0.0308 0.01328 -2.32 0.02

Ln(Seed)*Ln(Oxen) 0.07968 0.02805 2.84 0.004 0.078491 0.028 2.81 0.005 0.069327 0.025884 2.68 0.007

Ln(Seed)*Ln(Farm capital) -0.0005 0.01933 -0.03 0.979 -0.00061 0.0192 -0.03 0.975 0.005214 0.018233 0.29 0.775

Constant 6.3236 0.23202 27.26 0.00 6.317529 0.2299 27.47 0.000 6.954448 0.222343 31.3 0.00


39

Gender -1.2354 0.34147 -3.62 0.00 -1.07488 0.2846 -3.78 0.000 -0.51674 0.123781 -4.17 0.00

Age of the head -0.0921 0.04614 -2.00 0.046 -0.07845 0.0395 -1.99 0.047 -0.03376 0.018647 -1.81 0.07

Age square 0.00091 0.00045 2.02 0.043 0.000798 0.0004 2.07 0.039 0.000335 0.000182 1.84 0.066

Years of schooling -0.1676 0.05553 -3.02 0.003 -0.13957 0.0456 -3.06 0.002 -0.07644 0.019199 -3.98 0.000

Extension access (1=yes) -1.5365 0.37941 -4.05 0.00 -1.2512 0.2987 -4.19 0.000 -0.61228 0.122903 -4.98 0.000

Irrigation access (1=Yes) -1.0925 0.43117 -2.53 0.011 -0.86558 0.3554 -2.44 0.015 -0.48385 0.153203 -3.16 0.002

Access to all weather road (1=yes) 0.15934 0.24862 0.64 0.522 ***********************************************************

Distance to market ******************************* 0.01419 0.0028 5.05 0.000 0.006691 0.001003 6.67 0.000

Modern mode of transport ******************************* ****************************** -4.62565 0.594241 -7.78 0.000

Traditional mode of transport **************************** ****************************** -2.90985 0.34733 -8.38 0.000

Family size in adult equivalent -0.3424 0.09273 -3.69 0.00 -0.28504 0.0739 -3.86 0.000 -0.14322 0.030494 -4.7 0.000

Number of Livestock owned 0.03774 0.01439 2.62 0.009 0.03472 0.0123 2.81 0.005 0.026015 0.006403 4.06 0.000

soil index 0.15219 0.03474 4.38 0.000 0.15333 0.0309 4.96 0.000 0.059484 0.012951 4.59 0.000

Year -0.7291 0.25116 -2.9 0.004 -0.72879 0.218 -3.34 0.001 -0.36078 0.104 -3.47 0.001

Constant 3.19411 1.12417 2.84 0.004 2.23487 1.0194 2.19 0.028 3.342273 0.504833 6.62 0.000

Log likelihood = -8939.5429; Wald chi2(28) = 878.78; Prob > chi2 = 0.0000 Log likelihood = -8681.2090; Wald chi2(28) = 699.30; Prob > chi2 = 0.0000


40

Input variable Elasticity Logarithm of land size 0.68

Logarithm of mandays 0.481

Logarithm of fertilizer 0.2

Logarithm of seed 0.14

Logarithm of oxen 1.03

Logarithm of number of farm capital 1.2

Descriptive statistics summary of Technical efficiency

Variable Mean Std. Dev Min Max

Technical efficiency 0.404397 0.206729 0.0002304 0.828512

Variable 2913 2011 Difference P-Val

Technical efficiency 0.4255 0.3776 0.048 0.00***

Variable Good access No access Difference P-Val

Technical efficiency 2011 0.3744 0.3788 -0.004 0.6591

Technical efficiency 2013 0.4359 0.4211 0.015 0.0747*

Technical efficiency (polled ) 0.4101 0.4021 0.008 0.2161

Variable Modern Traditional Difference P-Val

Technical efficiency 0.5828 0.3923 0.191 0.00***Level of significance *** p<0.01, ** p<0.05, * p<0.1

Elasticity of inputs from the translog production model


41

Result of commercialization Craggit model

Delta-method Delta-method

Explanatory variables AME Std. Err. Z P>z [95% Conf. Interval] AME Std. Err. Z P>z [95% Conf. Interval]

Total value of output 0.000011 2.24E-06 5.03 0.00 6.88E-06 1.6E-05 -0.0000295 1.01E-06 -2.91

4.00E-

03 -4.93E-06-9.62E-

07

Age of the head 0.001972 0.0019784 1.00 0.319 -0.0019 0.00585 0.0054111 0.0022904 2.36 0.018 0.000922 0.0099

Gender (male=1) 0.040853 0.0180839 2.26 0.024 0.00541 0.0763 -0.0298729 0.0184918 -1.62 0.106 -0.066116 0.00637

Years of schooling 0.006705 0.0035303 1.92 0.058 -0.0002 0.01362 0.0046072 0.0038265 1.2 0.229 -0.002893 0.01210

Land size 0.016944 0.0060821 2.79 0.005 0.00502 0.02887 0.0059657 0.0075642 0.79 0.43 -0.00886 0.02079

No of livestock in TLU -0.005089 0.0009913 -5.13 0.00 -0.007 -0.0031 -0.0038075 0.0013878 -2.74 0.006 -0.006528 -0.00109

Extension access 0.009548 0.0143859 0.66 0.507 -0.0186 0.03774 -0.091595 0.0156895 -5.84 0.00 -0.122346 -0.06084

Credit access -0.066562 0.0157423 -4.23 0.00 -0.0974 -0.0357 -0.0627387 0.0187457 -3.35 0.001 -0.09948 -0.026

Access to irrigation 0.126516 0.0205842 6.15 0.00 0.08617 0.16686 0.0832991 0.0170876 4.87 0.00 0.0498081 0.11679

Road access (1=yes) 0.026497 0.014339 1.85 0.065 -0.0016 0.0546 0.0289445 0.0138178 2.09 0.036 0.0018622 0.05602

Modern mode -0.22899 0.0322904 -7.09 0.00 -0.2923 -0.1657 0.195317 0.0268289 7.28 0.00 0.1427332 0.24790

Traditional mode 0.1367539 0.0195089 7.01 0.00 0.09852 0.17499 0.1274118 0.0159798 7.97 0.00 0.096092 0.15873

distance to market 0.0016449 0.0016576 0.99 0.321 -0.0016 0.00489 -0.0071745 0.0058455 -1.23 0.22 -0.018632 0.00428

Year -0.169079 0.012123 -14.00 0.00 -0.1928 -0.1453 0.1246998 1.30E-02 9.58 0.00 9.92E-02 0.15022

Off farm income -0.000008 5.01E-06 -1.71 0.088 -2E-05

1.26E-

06 0.00000613 4.18E-06 1.47 0.142 -2.05E-06 1.43E-05

Commercialization Craggit double hurdle model

42

Explanatory variables Fixed effect Random effect

Land to family labor ratio 0.0664** 0.0895***

(0.0278) (0.0203)

Participation in off farm activities (yes=1) 0.105*** 0.0878***

(0.0316) (0.0246)

Dependency ratio -0.0744** -0.100***

(0.0297) (0.0184)

Age of the head 0.00388 -0.00333***

(0.00315) (0.000865)

Sex of the head (male=1) 0.0527 0.0587*

(0.0972) (0.0335)

Years of schooling -0.00677 0.0209***

(0.00547) (0.00412)

Access to irrigation (yes=1) 0.369*** 0.315***

(0.0480) (0.0317)

Result and DiscussionRural accessibility and pro poor growth in Ethiopia


43

Access to extension (yes=1) 0.0841** 0.106***(0.0347) (0.0238)

Access to credit (yes=1) 0.00383 0.0471*(0.0318) (0.0257)

Oxen owned in TLU 0.0102*** 0.0140***(0.00292) (0.00187)

Family size in adult equivalent units -0.0802*** -0.0694***(0.0197) (0.00733)

Road quality (access to all weather road =1) 0.100*** 0.195***(0.0288) (0.0231)

Distance to market -0.00767 -0.00389***(0.0121) (0.000274)

Logarithm of yield per hectare 0.0198*** 0.0319***(0.00616) (0.00487)

Constant 4.934*** 4.763***(0.811) (0.0753)

R-squared 0.13


44

1 2 3 40

10

20

30

40

50

60

70

80

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1

Welfare trend

Percentiles

wel

fare

coffi

cien

ts o

f ac

cess

abili

ty

perc

entil

es

Welfare coefficients, accessibility trend and rural road access

Percentiles Welfare effect Std.Err Z P>|z|

0.2 3.126336 17.949 0.17 0.862

0.3 9.468921 26.186 0.36 0.718

0.4 12.93196 13.430 0.96 0.336

0.5 10.00797 17.821 0.84 0.4

0.6 20.47958 34.328 0.6 0.551

0.7 26.62714 16.762 1.59 0.112

0.8 34.00285 10.297 3.3 0.00

0.9 77.25115 12.008 3.5 0.00

Rural transport indictors

Road quality

Rural Mobility

Poor access

Modern mode of transport

Traditional mode of transport

Partial productivity: by 3% not significant

TFP: negative and significant but with time positive and significant

Inefficiency: by 4.6(p<0.01))

Effects

Production: by 0.09 and p<0.01

Productivity: by 1.6 p<(0.01)

TFP: not significant

Commercialization: by 22 %( p<0.01)

Technical efficiency: positive not significant

Production: by 1.5 and p<0.01)

Productivity: by 1.18 (p<0.01)

TFP: by 3% not significant

Commercialization: by 13 percent (p<0.01)

Inefficiency: by 2.9 (p<0.01)

Consumption: by 10 % (p<0.01)

Effects Summary Commercialization by 2 %

(p<0.05)

• Rural communities in Ethiopia have different level of accessibility and mobility and access to all weather roads is still low.

• There still exists low utilization of modern mode of transport• Heterogeneity in rural accessibility and mobility can explain

difference in crop, productivity, commercialization, technical efficiency and consumption.

• HHs in villages with good access tend to more access to credit , extension contact. They also tend to use more fertilizer as compared to HHs in villages with poor road quality.

• Increasing either access to a level of all weather roads and provision of transport facilitates can foster crop production , productivity, TFP, commercialization and consumption , however, However, the study didn’t find any support of pro-poorness of rural roads

Conclusion

46

• The lack evidence for pro poorness of rural road investment calls for an inclusive growth.

• To bring significant change in agricultural productivity, market participation and commercialization, investment in rural transport must take an integrated approach that targets both mode of transport and infrastructure.

• the use (adoption) of transport facilities transport is important the and cost of adoption can be addressed by provision of incentives through credit schemes to rural transport operators and group management of transport services .

• policies geared towards integrating remote areas through integrated rural transport infrastructure development that meets both access and mobility demand of rural communities is recommended.

• Traditional mode of transport are still the second most dominant mode of transport facilities that can still play a significant role in improving market integration and commercialization. However, focus should be given to improve and modernize the existing traditional mode

Policy implication

47

Thank You God Bless you

48

naod mekonnen : agriculture and rural transport in ethiopia panel study (2)

Technology