hispanic business growth in oregon by kendra gramlich and...

Latino Business Growth in Oregon June 2013 Page ii

Hispanic Business Growth in Oregon

By

Kendra Gramlich David Perrin

June 13, 2013

Abstract

Oregon is experiencing a rapid increase in Hispanic population. In conjunction with this rise in population is the concern that Hispanics may find limited economic opportunities in the future. One means to evaluate this concern is to understand how an increase in the Hispanic population effects the growth of Hispanic-‐owned businesses. As with other segments of the population, business ownership is one path toward larger incomes and increased economic security for Hispanic individuals. This study used ordinary least squares regressions to create an econometric model to determine how Hispanic business growth is affected by the economic and demographic characteristics of an area. This study determined that total population, Hispanic population, total average education, and Hispanic average education have a positive relationship with the number and total sales of Hispanic businesses. In addition, it was determined that an educational gap exists between the total population and the Hispanic population in Oregon, and this gap effects Hispanic business growth. To evaluate the effect of this gap on the future of the number and sales of Hispanic businesses, a forecasting model using future projected population estimates was used while varying the educational attainment gap between the Hispanic population and the total population. It was shown through this forecasting model that the educational attainment gap between the two populations has a dramatic effect on the future number and total sales of Hispanic businesses in Oregon, or Hispanic business growth overall. This demonstrates a need for the enactment of policies geared toward closing the educational gap by increasing the average educational attainment for the Hispanic population in order to help Hispanic businesses flourish in the future.

Under the Supervision of Bruce Blonigen

Paper prepared in

Partial Fulfillment of Requirements for Honors in Economics

Latino Business Growth in Oregon June 2013 Page i

Acknowledgements: We would like to thank Bruce Blonigen for his immensely helpful input. Without his expertise this project would not have been possible. Also, we would like to say thanks to Bob Parker, the inspiration for this paper, and David Sheldon for his help in deciphering the Census Beau data.

Table of Contents I. INTRODUCTION ......................................................................................................................................... 1

II. FACTS AND FIGURES ON HISPANIC BUSINESSES ...................................................................................... 2

III. LITERATURE REVIEW ............................................................................................................................... 3

General Small Business Growth Studies .................................................................................................. 3

Ethnic Business Growth Studies .............................................................................................................. 6

Hispanic Businesses in Oregon ................................................................................................................ 7

IV. STATISTICAL ANALYSIS HYPOTHESES ...................................................................................................... 8

Population ............................................................................................................................................... 8

Per Capita Income .................................................................................................................................... 8

Education ................................................................................................................................................. 9

V. METHODOLOGY ..................................................................................................................................... 10

Natural log of Hispanic Business Sales Regression ................................................................................ 10

Share of Hispanic Business Sales Regression ......................................................................................... 10

Share of Hispanic Businesses Regression .............................................................................................. 10

VI. DATA AND SOURCES ............................................................................................................................. 11

VII. RESULTS AND INTERPRETATION .......................................................................................................... 14

Natural log of Hispanic Business Sales Regressions ............................................................................... 15

Share of Hispanic Business Sales Regressions ....................................................................................... 17

Share of the Number of Hispanic Businesses Regressions .................................................................... 18

VIII. FORECASTING ..................................................................................................................................... 20

X. CONCLUSION ......................................................................................................................................... 24

XI. CLOSING REMARKS ............................................................................................................................... 24

Suggestions for Future Research ........................................................................................................... 25

XII. REFERENCES ......................................................................................................................................... 27

XIII. APPENDICES ........................................................................................................................................ 29

A.1 Data Construction Step-‐by-‐Step ...................................................................................................... 29

A.2 Explanation of Observations Eliminated and/or Modified .............................................................. 35

Latino Business Growth in Oregon June 2013 Page i

A.3 Tables for Least-‐Squares Coefficient Estimates with Values ........................................................... 40

A.4. Error Terms ..................................................................................................................................... 41

Latino Business Growth in Oregon June 2013 Page ii

List of Tables Table 1. Census 2000 and ACS Data Sets Used for the Independent Variables ........................................ 14

Table 2. Sign and Statistical Significance of OLS Regression Coefficient Estimates for the Dependent Variable of the Log of Hispanic Business Sales .......................................................................................... 15

Table 3. Marginal Effect on Hispanic Business Sales for the Preferred Regression .................................. 17

Table 4. Sign and Statistical Significance of OLS Regression Coefficient Estimates for the Dependent Variable of the Share of Hispanic Business Sales ....................................................................................... 17

Table 5. Marginal Effect on Share of Hispanic Business Sales for the Preferred Regression ..................... 18

Table 6. Sign and Statistical Significance of OLS Regression Coefficient Estimates for the Dependent Variable of the Share of the Number of Hispanic Businesses .................................................................... 19

Table 7. Marginal Effect on Share of the Number of Hispanic Business Sales for the Preferred Regression ................................................................................................................................................................... 19

Table 8. Hispanic Population, Hispanic Sales Share, and Hispanic Business Share for 2007 ..................... 20

Table 9. Hispanic Population, Hispanic Sales Share, and Number of Hispanic Business Share Forecasts Using 2007 Hispanic Education Share ........................................................................................................ 21

Table 10. Hispanic Population, Hispanic Sales Share, and Number of Hispanic Business Share Forecasts Growing Hispanic Education Share by 0.1 from 2007 to 2040 .................................................................. 22

Table 11. Hispanic Population, Hispanic Sales Share, and Number of Hispanic Business Share Forecasts Growing Hispanic Education Share to Match Total Population Education Share by the year 2030 .......... 23

Table 12. List of California Counties Modified or Eliminated From Final Data Set .................................... 35

Table 13. List of Oregon Counties Modified or Eliminated From Final Data Set ....................................... 36

Table 14. List of Washington Counties Modified or Eliminated From Final Data Set ............................... 38

Table 15. Value of Least-‐Squares Coefficient Estimates for the Log of Hispanic Business Sales Regressions (Standard Errors in Parentheses) ............................................................................................................... 40

Table 16. Value of Least-‐Squares Coefficient Estimates for the Share of Hispanic Business Sales Regressions (Standard Errors in Parentheses) ........................................................................................... 41

Table 17. Value of Least-‐Squares Coefficient Estimates for the Share of Hispanic Businesses Regressions (Standard Errors in Parentheses) ............................................................................................................... 41

Table 18. Error Terms for Share of Sales and Share of Hispanic Business Models .................................... 42

Latino Business Growth in Oregon June 2013 Page 1

I. INTRODUCTION

The current demographic and cultural changes to the economic climate in Oregon generate questions regarding the economic outlook for Oregon as a whole. Hispanic population growth in the state of Oregon is at an all-‐time high. According to the 2010 Census, during the decade from 2000 to 2010 the Hispanic population in Oregon grew five times faster than the total population of the state (Oregon Office of Economic Analysis, 2011). During a time in which the entire country was slowly recovering from a severe economic recession, the implications of a rapidly growing Hispanic market are significant. Small businesses are important for job creation and provide about half of United States employment and non-‐farm GDP (Fadahunsi, 2012). Studying Hispanic businesses with regard to where they are formed, the number of workers they employ, and their current and projected sales can shed light on an important and growing portion of Oregon’s small business future. Studies on the growth of Hispanic businesses in the United States have been very limited. This is especially true for the state of Oregon. This thesis quantifies the growth of Hispanic businesses in Oregon by statistical analysis using ordinary least squares (OLS) regressions. The OLS regressions model the effects of population and education on the number of Hispanic businesses, as well as the total sales of Hispanic businesses, for the west coast of the U.S., specifically, California, Oregon, and Washington. A forecast is made about the future of Hispanic businesses growth in Oregon through analysis of the results of the regressions in combination with population projections from Oregon’s Office of Economic Analysis (OEA). Data from the American FactFinder web site, developed and maintained by the U.S. Census Bureau, is used to estimate the model. Data from the Survey of Business Owners (SBO), 2000 Census, and American Community Survey (ACS) is used. Understanding how these economic factors affect the growth of Hispanic businesses is useful for the formation of policies to foster the growth of the Hispanic business community. The results of this study found that total population, Hispanic population, average education, and Hispanic average education have a positive relationship with Hispanic business growth. Average education was found to have a larger effect on total business sales than Hispanic business sales. That is, Hispanic average education was a limiting factor of Hispanic business growth. In addition, it was seen that an education gap exists between the Hispanic population of Oregon and the total population of the state. The effects of this education gap were studied through a parametric analysis of different gap closure rates on the projected future performance of Hispanic businesses in the years 2015, 2020, 2030, and 2040. Closing the education gap significantly improved Hispanic business growth by 2030. The forecasting model developed for this study provides a good macroeconomic base understanding of how the demographics in different counties of the west coast effect Hispanic business growth. It is important to note that this model is based on 2000 and 2007 demographic variables. As the demographic landscape changes, it is imperative to perform a similar study again and create an updated forecasting model.


II. FACTS AND FIGURES ON HISPANIC BUSINESSES

In 2011 there were approximately 50.7 million Hispanics residing in the United States constituting 16% of the total population.1 In 2007 there were 2.3 million Hispanic businesses in the U.S. comprising about 8.3% of all businesses.2 These statistics are even more enlightening when growth rates are considered. Between 1997 and 2002, Hispanic businesses grew 31% in the U.S. – three times the national average for all businesses regardless of ethnicity.3 Capturing a sizeable and growing portion of the population, Hispanics have a strong presence in the United States economy. Review of SBO, 2000 Census, and ACS data showed that the ethnic profile of the combined states of California, Oregon, and Washington is 22% Hispanic with only 5% of businesses Hispanic-‐owned. In addition, Hispanic businesses account for only 1.6% of business sales. The average education for the total population is 16 years of education, while the average education for the Hispanic population is 13 years. There is a three year education gap between the two populations. In Oregon, the number of businesses compared to the population are nearly halved with 9.6% of the population being Hispanic and only 2.8% of the all the businesses in Oregon being Hispanic-‐owned. In addition, these Hispanic-‐owned businesses account for only 0.7% of total business sales of all businesses in Oregon. Based on the population of Hispanics in Oregon these numbers are much lower than what would be expected. These disproportionate numbers indicate that some demographic or economic factor is stunting Hispanic business growth in Oregon. In its report, Hispanic Contributions to Oregon: Strengthening Our State Economy,4 Causa, the largest Hispanic immigrant rights organization in the Pacific Northwest,5 provides some interesting figures on Hispanic population and Hispanic business growth in Oregon. The report is a compilation of data from the 2010 Decennial Census, the 2010 3-‐year estimates from the ACS, and the 2007 SBO. It provides a nice summary of statistics on Hispanic demographics in Oregon. For example, it documents that the Hispanic population grew from 275,314 to 450,052 between 2000 and 2010, a 63% growth rate. The report explains that Hispanic population growth accounted for 43% of Oregon’s population growth for the decade. It also documents

1 United States Census Bureau, “ACS Demographic and Housing Estimates 2009-‐2011,” American Community Survey 3-‐Year Estimates, http://factfinder2.census.gov/faces/tableservices/jsf/pages/productview.xhtml?pid=ACS_11_3YR_DP05&prodType=table.

2 United States Census Bureau, “Statistics for All U.S. Firms by Industry, Gender, Ethnicity, and Race for the U.S., States, Metro Areas, Counties, and Places: 2007,” 2007 Survey of Business Owners, http://factfinder2.census.gov/faces/tableservices/jsf/pages/productview.xhtml?pid=SBO_2007_00CSA01&prodType=table.

3 Robles, 2007. 4 Causa, “Report: Latino Contributions to Oregon,” http://org2.democracyinaction.org/o/5535/p/salsa/web/common/public/signup?signup_page_KEY=6929.

5 Causa, http://causaoregon.org/.


that Hispanics in the workforce in 2010 numbered over 200,000, accounting for just over 10% of the workforce. The report shows that the numbers for Hispanic entrepreneurs are very impressive. During the years 2002 through 2007 Hispanic-‐owned businesses in Oregon grew from 6,360 to 11,338, a 78% increase. This rate of growth is four times larger than total business growth in the state. An increase in the sales receipts of Hispanic businesses is just as important as an increase in the number of Hispanic businesses. The Causa report states that Hispanic-‐owned business receipts reached approximately $1.7 billion in 2007, a 16.9% increase from 2002. Although this is only 0.5% of the $324.4 billion of total receipts for Oregon, it does indicate that Hispanic businesses are growing both in number and in sales. The report concludes that with their rapidly growing population and Hispanics’ propensity for entrepreneurship, Hispanic businesses will continue to change the economic landscape of Oregon counties. The impressive figures on the growth of both the number of Hispanic businesses and Hispanic business sales during the 2000 to 2010 decade became the basis of this study. This study uses OLS regressions to model the effects of population and education on the growth as seen. And, from the model, it predicts how much growth can be expected in future years.

III. LITERATURE REVIEW

General Small Business Growth Studies

There has been extensive research on small business growth because of its importance to economic health. The term ‘small business’ is really a misnomer and can even create an unwarranted aura of triviality. A small business is defined as any business employing less than 500 people. In the U.S., small businesses account for approximately 99% of all firms. These firms employ about half of the American workforce (Fadahunsi, 2012 & Brock and Evans, 1989). Thus, while corporations and other large businesses are often considered more important, small businesses have a large impact on the economic climate of the U.S. In addition, the evolution of the computer has brought with it a decrease in the operating size of businesses and rapidly developing industries are being populated by smaller businesses (Brock and Evans, 1989). Therefore, the number of small businesses is expected to rise. Much of the research on small business growth uses time and resource intensive methods for collecting data such as surveys of small business owners in an area along with detailed area-‐specific demographic and economic profiling. The methods often employed are out of the scope of this study. However, general small business growth studies provide valuable insights on the variables used to measure business growth. Although this study is focused on Hispanic business growth, incorporating factors that affect general small business growth is crucial for forming an accurate model.


Literature on small business growth is fragmented among numerous theoretical perspectives. One paper summarizes five of the main perspectives on small business growth and attempts to integrate these perspectives into a conceptual model that could be used to study business growth in general (Wiklund et al., 2009). The paper explains that at the beginning of their study, through phone and mail interviews, the authors gathered information from 465 businesses to obtain data on independent variables including entrepreneurial attitudes, industry, environment, and firm age. They followed up one year later collecting data on the dependent variables of sales and employment. The paper provided some valuable insights on what was studied previously. It also provided a concise summary of literature on small business growth. Wiklund affirms that the two most popular indicators of business growth are sales and employee growth, which supports the dependent variable of sales by Hispanic businesses chosen for this study. In addition, one of the main theoretical perspectives mentioned in their paper is the effect of the business environment, including the demographic landscape of an area, on small business growth. Demographic variables are used in the statistical model for this study, as well. Similar to Wiklund, Fadahunsi (2012) attempts to create a central framework for researching small business growth. According to Fadahunsi, there exists no overarching model of small business growth as the factors that affect small business growth are quite varied and context-‐specific. Often the objective of a study differs from the context of the business such as its environment or the business type. That is, small business studies usually have a specific objective and do not seek to explain business growth for the sake of explaining business growth. This narrow approach to small business studies diminishes the usefulness of these studies to those interested in how these businesses grow including policymakers. In addition, Fadahunsi explains that many studies on small business growth are not longitudinal. Finding robust data on small or privately owned businesses is relatively difficult compared to finding data for publicly-‐traded companies. Ultimately, a lack of central small business growth theory along with relatively limited or incomplete data are major roadblocks which have stood in the way of past studies. This study uses SBO, Census, and ACS data at the county level as a means to address relative environmental factors of small business growth. Fadahunsi (2012) also provides a nice summary and explanation of the most common factors influencing growth that are used in studies of small businesses. The summary cites factors including education, ethnicity/race, location, and local and national factors. Fadahunsi explains how these factors affect small business growth. In one example, Fadahunsi states that educated business owners are likely to foster faster business growth due to more developed business acumen. In another example, Fadahunsi states that ethnicity and race are connected to the growth orientation of firms by enhancing the ability of firms to tap into ethnic resources, such as an ethnic consumer base. However, Fadahunsi warns that an ethnic-‐oriented business model by itself does not guarantee positive business growth as it provides no information about a business owner’s skillset. Furthermore, Fadahunsi explains that location differs from study to study and its effect is usually open-‐ended. Therefore, the impact of environmental factors is commonly studied through surveys of the local population. This study did not use survey methods due to time and resource constraints. Instead, environmental analysis was performed


using factors obtained through American FactFinder at the county level. These factors, including per capita income, population total, and ethnic composition, contextualized the environments in which these businesses operate to aid in providing a better model of Hispanic business growth. Kean et al. (1998) explain that measures of the economic climate are factors that affect business growth and likely entrepreneurship. The authors surveyed 456 retailers in 48 different communities. They used market size, purchasing power, competitive strategies, and type of business environment as independent variables. In addition, per capita income was used as a measure for purchasing power. Their analysis revealed that per capita income had a significant and positive relationship with business performance. Bartik (1989) also used per capita income in his research on the characteristics of states and their effect on small business start-‐ups. Thus, per capita income as a measure of purchasing power is a worthwhile independent variable and was used in this study. Education is a common factor that is cited in many business growth studies and is often singled out for analysis. Education is considered a pillar of social improvement in the United States, so the economic impacts of education are closely scrutinized. Bartik (1989) studied the effect of education on business start-‐ups in the U.S. He found a positive relationship between the number of high school graduates and the number of start-‐ups. In contrast, he found that the number of college graduates did not have a significant effect on the number of start-‐ups. Bartik explained that the data for the college graduate variable in his research was imprecise, so he cautioned that this variable could, in reality, have a large positive or negative effect that he did not see. Reddy (2007) found that education boosts the income potential of a business. However, most of the business owners surveyed in the Reddy paper had low levels of formal education. Armington and Acs (2000) used two measures of educational attainment in their study on firm birth rates as variables to explain new firm formation; adults with no high school degree and college graduates. “Absence of a high school diploma” was used as a proxy for unskilled and semi-‐skilled labor while “college graduate” was used as a proxy for both technical skills and entrepreneurial skills such as marketing and complex reasoning. Their research found no high school degree to be negatively correlated with firm birth rates and college graduates positively correlated with firm birth rates. Data on educational attainment was included in this study to further investigate the effect of education on Hispanic business growth. One common characteristic of most research on business performance and new firm formation is the division of the data by geographical areas. For instance, Armington and Acs (2000) compared industrial regions against technologically progressive regions. Gartner and Bhat (2000) studied neighborhood factors around San Francisco in their research on small business development. Bartik (1989) used the traits of different states in the U.S. in his study on business start-‐ups. Geographical segregation of data is important to account for differences in the economic landscape of diverse regions. This study uses data at the county level as the geographical unit to control for differences in economic and demographic characteristics.


Ethnic Business Growth Studies

Many of the same variables that are used in general business growth research are used when researching ethnic entrepreneurship or the performance of ethnically-‐owned businesses. Additional variables are incorporated to capture particular aspects of the ethnic effect under investigation. These variables may include percent of the population that is of a particular ethnicity or specific dependent variables such as the amount of business sales for businesses owned by an ethnic group. A study on Hispanic business growth largely parallels studies on general business growth as the factors behind business growth are ubiquitous. A focused literature review on ethnic or immigrant business growth helped to pinpoint key variables that are known to affect ethnic business growth and to aid in the development of hypotheses behind these variables. Evans (1989) performed a study of immigrant groups as an economic niche for small business. Using the 1981 Australian Census, he predicted the probability of business ownership by an immigrant individual as a function of the immigrant market size, percent of the immigrant group who speak English poorly, and native language skills and human capital of the immigrant individual. Two hypotheses were supported by this study: the group size hypothesis and the isolated labor pool hypothesis. The group size hypothesis states that the larger an immigrant group, the more likely are its members to establish their own business. The isolated labor pool hypothesis states that the greater the percent of adults in an immigrant group who are not fluent in the host country’s language, the more likely are group members to start their own businesses. Mora and Dávila (2005) found results contrary to Evans (1989). Empirical results from research they performed on immigrant entrepreneurship in the United States indicated that the size of the local ethnic population did not enhance immigrant self-‐employment. They separated immigrants into two groups: limited English proficient (LEP) and those that spoke English. Their observations confirmed that the language ability difference between these two groups was the greatest factor in immigrant self-‐employment success. That is, those who speak English have a competitive advantage in that they are able to attract both ethnic and non-‐ethnic customers with their fluency in English; their success did not directly depend on the size of the ethnic population. In response to the antithetical findings by Mora and Dávila, this study incorporates an ethnic group size independent variable to determine if ethnic group size affects Hispanic business growth. Just as education is often used as a factor in research on general business growth, educational attainment is commonly cited in research on firm formation and business performance of ethnic-‐based businesses. Mora and Dávila (2005) used years of education in the U.S. and literacy measures to study immigrant entrepreneurship. Education had a positive relationship with entrepreneurship in the years of 1910 and 1920. Interestingly, it had a negative relationship in 1980 and 1990. Hammarstedt (2001) used education as a determinant for self-‐employment. He discovered that individuals with low education levels had a higher probability of being self-‐employed. Due to the varying empirical results of education on business growth


and firm formation in both general and ethnic business growth studies, measures of educational attainment are used in the model developed for this study on Hispanic business growth to understand the extent to which education effects business growth.

Hispanic Businesses in Oregon

The sudden growth of Hispanic businesses in the city of Woodburn in Marion County, Oregon motivated this research. There have been no formal quantitative studies on Hispanic businesses and the prospects for Hispanic business growth in Woodburn to date. What has been documented is the influence of Hispanic businesses in the downtown Woodburn area. The study, Hispanic Small Businesses and Downtown Development (2012), was conducted by the Community Planning Workshop at the University of Oregon. Along with explaining the effects of Hispanic businesses on the downtown area, it also suggested possible policy implementations that could help support business growth and economic development. The Workshop study explained that Hispanic businesses in Woodburn contribute economically and culturally to the downtown area. Economically, Hispanic businesses fill storefronts and office spaces that would otherwise be vacant as the economic downturn in recent years has prompted an exodus from the area. Moreover, as is common with business ownership, these business owners take pride in their shops, investing in their spaces by creating visually appealing storefronts. Both the interior and exterior of their businesses are kept presentable, upkeep that would otherwise not occur if the area was vacant. In addition, Hispanic business owners often look to the future when considering their business base. For example, even during years of negative growth, Hispanic businesses tend to keep their prices competitive in an attempt to bolster their future customer base. Furthermore, these ethnic businesses draw in a larger consumer base from out of town. The business owners interviewed in Woodburn said that about half of their customer base was from out of town with 80-‐90% of the customers being Hispanic. In addition to economic effects, the Workshop study explained that Hispanic businesses also have a profound cultural and social effect in Woodburn. Hispanic business owners are a valuable networking and advising base for the population of Woodburn. Those looking for jobs, or those needing help with financial or legal issues, often turn to these business owners for assistance. This is especially true for non-‐native Hispanics who find comfort communicating with Hispanic business owners. By their very presence, these businesses also create a safe area in downtown Woodburn. An active downtown area reduces crime and creates a space for social and culture events to be held. Although the Community Planning Workshop study focused on Woodburn, these findings likely mirror other communities with a large presence of ethnic businesses. Moreover, the Community Planning Workshop research project highlights some of the tangible effects of Hispanic businesses on communities, perceptions and effects that are often lost in overarching studies on business growth. This study seeks to create a statistical model useful for predicting future Hispanic business growth in Oregon so counties may be proactive in support for Hispanic


business development, and, of course, to enable the opportunity for communities to understand and reap the benefits of their presence.

IV. STATISTICAL ANALYSIS HYPOTHESES

The literature reviewed for this study helped to identify the variables chosen to forecast Hispanic business growth. In addition, the literature explained some of the possible effects of these variables aiding in the formulation of a number of hypotheses. For this study, all variables are measured by county and year. The independent variables include:

• total population • Hispanic population share • per capita income • Hispanic per capita income • level of education

The dependent variables are:

• total sales by Hispanic businesses • share of Hispanic businesses • share of Hispanic business sales

The following is a description of the hypotheses used in this study along with an explanation of how the variables supported the hypotheses.

Population

Total population and Hispanic population share are hypothesized to have a positive relationship with Hispanic business growth. Total population is considered a measure of the consumer base because as the population increases, so does consumption. The percent Hispanic population share is expected to a have large impact on Hispanic business growth as people of Hispanic ethnicity are likely to frequent Hispanic businesses over non-‐Hispanic businesses especially if language is a barrier. In addition, with a larger Hispanic population there is more incentive for an entrepreneur to open a Hispanic establishment in order to serve this customer base. This is supported by the group size hypothesis as described by Evan (1989), though it is noted that Mora and Dávila (2005) found that size of the ethnic population did not enhance immigrant entrepreneurship.

Per Capita Income

The effect of per capita income on the growth of Hispanic businesses is ambiguous. On the one hand, per capita income is hypothesized to be positively correlated with Hispanic business growth. Per capita income is a measure of the general economic health and buying power of a region, and it represents the potential general business demand. As per capita income grows, the initial hypothesis is that the patronage of local businesses grows as well. On the other


hand, higher per capita income may negatively affect Hispanic business growth because it can also be hypothesized that as areas become wealthier, ethnic businesses may be excluded or pushed out. These two competing forces may neutralize the effect of per capita income on Hispanic business growth.

Education

The effect of education is difficult to determine as research has shown mixed results. As described above, Armington and Acs (2000) used the number of adults without a high school diploma and the number of adults with college degrees as educational attainment factors in their study of business entrepreneurship. A higher number of adults without a high school diploma was found to be negatively correlated, while a higher number with a college degree was positively correlated. Mora and Dávila used number of years of education as their measure for educational attainment. Their results were mixed with more years of education positively correlated to entrepreneurship in the years of 1910-‐1920 and negatively correlated in 1980-‐1990. Hammarstedt (2001) found that those with low education levels had a higher probability of being self-‐employed. In their research, Armington and Acs (2000) lumped those who graduated college into one group. College graduates are a highly heterogeneous segment of the population with educational attainment levels ranging from associates to doctoral degrees. Therefore, five measures of college educational attainment were included in this study to better differentiate the effects of different levels of higher education. The measures of educational attainment included:

• no high school diploma • high school diploma • some college • bachelor’s degree • advanced degree

Each level of educational attainment is mutually exclusive and data is used for both total population educational attainment and Hispanic educational attainment. As with Armington and Acs (2000), the number of people without a high school diploma is hypothesized to have a negative relationship with Hispanic business growth. Individuals who did not graduate high school are less likely to possess the skills and resources to open up their own business or have fewer resources to patronize Hispanic businesses. Higher levels of education increase a person’s human capital and provide more skills to open up a successful business. Higher educational attainment also opens up doors for employment and a higher income as a person becomes more marketable. Those with higher degrees may have the resources to open a business or can more easily find a well-‐paying job. The effect of some college and above is hypothesized to have a positive relationship with Hispanic business growth since both of these outcomes will foster business growth.


V. METHODOLOGY

Multivariate ordinary least-‐squares regressions are used to develop the forecasting model. These regressions are estimated with data from counties in California, Oregon, and Washington. Counties in California and Washington provide an important control group that exhibit substantial variation in amount of Hispanic business growth and presence. California is of particular interest in that it is most likely farther along in its Hispanic business economic development cycle with its larger Hispanic population and closer proximity to the Mexican border. Hispanic business sales and the number of Hispanic businesses were used as a means to understand Hispanic business presence in a county. A number of alternative measures of Hispanic business presence in a county were used to estimate a statistical model to explain each measure, the dependent variable, with the explanatory factors described above, the independent variables. Regressions were run for counties with populations of at least 100,000 due to data availability. A description of the forecasting models follows.

Natural log of Hispanic Business Sales Regression

𝑇𝑜𝑡𝑎𝑙 𝐻𝑖𝑠𝑝𝑎𝑛𝑖𝑐 𝑆𝑎𝑙𝑒𝑠 = 𝛼 + 𝛽′𝑋!" + 𝜀!" where 𝑋 is a matrix that contains the following variable vectors for county, 𝑖 and year, 𝑡:

𝐼𝑛_𝑡𝑜𝑡𝑎𝑙_𝑝𝑜𝑝!": Natural log of total population 𝐼𝑛_ℎ𝑖𝑠𝑝_𝑝𝑜𝑝!": Natural log of Hispanic population 𝐼𝑛_𝑡𝑜𝑡𝑎𝑙_𝑖𝑛𝑐𝑜𝑚𝑒!" : Per capita income 𝐼𝑛_ℎ𝑖𝑠𝑝_𝑖𝑛𝑐𝑜𝑚𝑒!": Natural log of Hispanic per capita income 𝐼𝑛_𝑎𝑣𝑔_𝑒𝑑𝑢𝑐: Average education of total population (measured in years) 𝐼𝑛_ℎ𝑖𝑠𝑝_𝑎𝑣𝑔_𝑒𝑑𝑢𝑐!": Average education of Hispanic population (measured in years) 𝐼𝑛_𝑒𝑑𝑢𝑐_𝑠ℎ𝑎𝑟𝑒!": Natural log of Hispanic average education divided by total population average education 𝑦𝑒𝑎𝑟2000!": Dummy variable for the year 2000

The natural log specification allows for changes in total Hispanic sales to be interpreted as relative percent changes in the independent variables.

Share of Hispanic Business Sales Regression

𝑇𝑜𝑡𝑎𝑙 𝐻𝑖𝑠𝑝𝑎𝑛𝑖𝑐 𝑆𝑎𝑙𝑒𝑠!𝑇𝑜𝑡𝑎𝑙 𝑆𝑎𝑙𝑒𝑠 (𝑎𝑙𝑙 𝑏𝑢𝑠𝑖𝑛𝑒𝑠𝑠𝑒𝑠)!"

= 𝛼 + 𝛽!𝑋!" + 𝜀!"

Share of Hispanic Businesses Regression

𝑁𝑢𝑚𝑏𝑒𝑟 𝑜𝑓 𝐻𝑖𝑠𝑝𝑎𝑛𝑖𝑐 𝐵𝑢𝑠𝑖𝑛𝑒𝑠𝑠𝑒𝑠!"𝑇𝑜𝑡𝑎𝑙 𝑁𝑢𝑚𝑏𝑒𝑟 𝑜𝑓 𝐵𝑢𝑠𝑖𝑛𝑒𝑠𝑠𝑒𝑠!"

= 𝛼 + 𝛽′𝑋!" + 𝜀!"


where 𝑋 is a matrix that contains the following variable vectors for county, 𝑖 and year, 𝑡:

𝑝𝑒𝑟𝑐_ℎ𝑖𝑠𝑝_𝑝𝑜𝑝!": Percent Hispanic population ℎ𝑖𝑠𝑝_𝑎𝑣𝑔_𝑒𝑑𝑢𝑐!": Average education of Hispanic population (measured in years) 𝑒𝑑𝑢𝑐_𝑠ℎ𝑎𝑟𝑒!": Hispanic average education divided by total population average education 𝑦𝑒𝑎𝑟2000!": Dummy variable for the year 2000

Both shares regressions included the same independent variables as described above. That is, share of Hispanic businesses, share of Hispanic business sales, and total Hispanic business sales are the dependent variables used to measure Hispanic business growth. Growing sales in businesses and number of establishments indicate an expanding business environment. Total population and Hispanic population are included in the regression because they provide the economic substrate for Hispanic businesses. However, counties with a small population may not exhibit as much business growth. Educational share, the variable for the average education of the Hispanic population relative to the average education of the total population, should positively correlate with Hispanic business growth as a stronger skillset in needed in order to start a business. A dummy variable for the year 2000 is included in the regression so as to control for time effects such as inflation. OLS techniques were used to estimate the coefficients on the independent variables in the regression equations above. In this way, the effect of each independent variable on the dependent variables was determined. Thus, this statistical model can be used to predict future growth of Hispanic businesses at the county level. Population estimates for up to the year 2040 from Oregon’s Office of Economic Analysis were used in a forecasting model to simulate the future demographic conditions in each of the counties in Oregon. Understanding the basic effect of a variable (whether it has a positive or negative effect on business growth) and the magnitude of the effect allows for more informed and effective future policy decisions regarding business growth in counties on the west coast.

VI. DATA AND SOURCES

A reliable and robust data set was required to develop a strong and dependable model of future Hispanic business growth. The data used for this study was from the U.S. Census Bureau American FactFinder web site. The web site has a search engine which allows searches of population sample characteristics by geographic area and year. It also has specific surveys that can be parsed and downloaded such as the two surveys used as a part of the data collection for this study; the SBO for small business statistics and the ACS for 2005-‐2007 demographic information. Both of these surveys have disclosure constraints and differing variables across years. As a result, some observations were ultimately removed.


The most important data needed for this study was the data for the dependent variables: share of Hispanic business, share of Hispanic sales, and total Hispanic business sales. To determine future estimates of Hispanic business growth, data on past total sales by Hispanic businesses and past number of Hispanic businesses was required. Total sales receipts for Hispanic businesses was used as an indicator of how well existing Hispanic businesses in a given area perform over time. The number of Hispanic businesses was used as an indicator of the overall growth in the volume of Hispanic businesses. As described above, data from counties in California and Washington was used, as well as data from counties in Oregon. While this study is interested in the future of Hispanic business growth in Oregon, counties in California, which has a more established Hispanic population, proved useful in modeling the growth rates of Hispanic businesses. Also, counties from Washington were included to provide a larger data set as Hispanic economic profiles and demographics are very similar to Oregon. Data on the number and sales of Hispanic businesses is collected by the United States Census Bureau under the SBO. For this study, data for businesses is based on the SBO for the years 2002 and 2007. While an SBO was conducted in 2012, the data from that survey was not available at the time this study was completed. A final survey data set was decided upon after determining which data set contained the most complete information for each state in each year. The data set chosen for the SBO master file was “Statistics for All U.S. Firms by Industry, Gender, Ethnicity, and Race for the U.S., States, Metro Areas, Counties, and Places.” Separate data sets were downloaded based on year and state. To keep data sets consistent the “three-‐year estimates” data sets were used for each master file. The SBO categorizes businesses in a number of different ways. First, it defines them by whether or not they are ethnically classifiable. A business is classifiable if it can be determined who holds ownership. For example, businesses that are publically held, such as government entities like the Post Office, are not classifiable. Second, the SBO categorizes businesses by ethnicity. In the case of Hispanic businesses, the categories include not only Hispanic businesses where the owner or owners are Hispanic, but also non-‐Hispanic businesses where the owners are not Hispanic, but can be of any other ethnicity including white, and equally Hispanic and non-‐Hispanic businesses which are businesses that have equal ownership between a person or persons of Hispanic heritage and those who are not Hispanic. Some data manipulation was required to utilize the data from the SBO to meet the needs of the study. For some counties, the number of all businesses, the number of classifiable businesses, the number of non-‐Hispanic businesses, the number of equally Hispanic and non-‐Hispanic businesses, and the number of Hispanic businesses was available. In these cases, all of the information needed for the regressions was given. However, for other counties, the number of all businesses was given, but the number of Hispanic businesses was not provided. In order to create the number of Hispanic businesses, both the number of non-‐Hispanic businesses and the number of equally Hispanic and non-‐Hispanic businesses were subtracted from the number of classifiable businesses. In order to verify this process was correct, this method was performed


on observations in which all the data was available. When the number of Hispanic businesses created by this method was compared to the actual data provided, it was never off by more than 0.0042%. It should be noted that equally Hispanic and non-‐Hispanic businesses were not included in the data used for Hispanic businesses in this study. As with the number of Hispanic businesses, in some instances the variable for sales receipts by Hispanic businesses had to be derived from the given data. The SBO categorizes sales receipts in a manner identical to number of businesses. That is, the SBO includes data on sales receipts for all businesses, classifiable business, non-‐Hispanic businesses, equally Hispanic and non-‐Hispanic businesses, and Hispanic businesses. As with the number of businesses, data may or may not be specifically available. Thus, in the cases where data was not specifically available, the total sales by Hispanic businesses was determined by subtracting the total sales receipts of non-‐Hispanic and equally Hispanic and non-‐Hispanic from the total sales receipts of classifiable businesses. Some counties were missing equally Hispanic and non-‐Hispanic data. In these cases, the created number for the Hispanic variables may be slightly inflated over data that would have been provided if the equally Hispanic and non-‐Hispanic data had been available. This minimally impacted the data and was accepted in order to keep more observations in the data set. A list of the counties in which the sales and number of Hispanic businesses was created from the limited existing data is found in the Appendix. Data for the independent variables was acquired from either the 2000 Census or the ACS. Unlike the SBO, there was no single data set that provided all the information needed. Therefore, the data had to be compiled from different data sets on the American FactFinder web site. A list of the files used to provide data for each variable is shown in Table 1.


Table 1. Census 2000 and ACS Data Sets Used for the Independent Variables Variable Year Ethnicity Data ID Data Set Filename Data Origination

Population 2000 All DP-‐1 Profile of General Demographic Census 2000

Population 2007 All DP-‐05 Demographic and Housing Estimates ACS 2005-‐2007

Income 2000 All P082 Per Capita Income in 1999 (Dollars) Census 2000

Income 2000 Hispanic P157H Per Capita Income in 1999 (Dollars) (Hispanic or Hispanic) Census 2000

Income 2007 All B19301 Per Capita Income in the Past 12 Months (in 2007 inflation-‐adjusted dollars)

ACS 2005-‐2007

Income 2007 Hispanic B19301I Per Capita Income in the Past 12 Months (in 2007 inflation-‐adjusted dollars) (Hispanic or Hispanic)

ACS 2005-‐2007

Education 2000 All PCT064 Sex by Educational Attainment for the Population 25 Years and Over Census 2000

Education 2000 Hispanic P148H Sex by Educational Attainment for the Population 25 Years and Over (Hispanic or Hispanic)

Census 2000

Education 2007 All S1501 Educational Attainment ACS 2005-‐2007

Education 2007 Hispanic B15002I Sex by Educational Attainment for the Population 25 Years and Over (Hispanic or Hispanic)

ACS 2005-‐2007

An important note is that while the SBO had data for the year 2002, demographic data was not available for that year. For this reason, 2000 Census data was used as this was the year with data closest to 2002. The two data sets were merged as if the 2000 and 2002 observations were from the same year. The year was labeled 2000 in the combined data set file used for the regression for ease of data management. In some cases, data were not available at all. This was especially true in SBO and ACS data collected mid-‐decade (i.e., 2005). In this case, all data for the county was eliminated prior to the regression. Additionally, counties with populations of less than 100,000 were eliminated in all of the regressions. A list of excluded counties, along with the reason(s) for their exclusion, is found in A.2 of the Appendix. The Appendix also provides a step-‐by-‐step guide on how the data was obtained and cleaned in section A.1.

VII. RESULTS AND INTERPRETATION

OLS, ordinary least squares, statistical regressions were run using both the sales of Hispanic businesses and the number of Hispanic businesses as the dependent variables. These regressions produced estimates of the effect of each independent variables on the dependent variable, holding all other independent variable effects constant. In each of the following sections below, a table of the regressions as they evolved to the preferred regression is


provided. The chosen preferred regressions for the forecasting models are the last regressions specified in each of the tables. For simplicity, the signs of the effects of the independent variables are given along with their statistical significance. The actual values of the coefficients and their standard errors can be found in Appendix A.3 in Tables 15, 16 and 17.

Natural log of Hispanic Business Sales Regressions

The results from the log of Hispanic business sales regressions are shown in Table 2. The first and most simple regression includes independent variables for total population, total income, average education, and the dummy year variable. A dummy year variable is used to correct for time-‐dependent changes to the variables, such as inflation. The total population and the average education variables proved statistically significant. This specific regression has an R2 of 0.801. Thus, this regression found that 80.1% of the variation of the dependent variable, Hispanic business sales, was due to the independent variables in the regression. Total population and total income have a positive effect on businesses, while average education has a negative effect.

Table 2. Sign and Statistical Significance of OLS Regression Coefficient Estimates for the Dependent Variable of the Log of Hispanic Business Sales

Variables Log of Hispanic Sales Regression #1

Log of Hispanic Sales Regression #2


In_total_pop +*** + In_total_income +** In_avg_educ -‐** Year2000 -‐ -‐ -‐* In_hispanic_pop +*** +*** In_hisp_income + In_hisp_avg_educ +*** +*** In_educ_share -‐* Counties 88 88 88 Goodness of Fit (R2) 0.801 0.93 0.933

*p<0.05, **p<0.01, ***p<0.001 It is likely that independent variables specific to the Hispanic population have an increased effect on Hispanic business sales relative to effects of the total population. Therefore, a second regression was performed identical to the first regression, except changing each of the independent variables to be Hispanic-‐specific; i.e., Hispanic population, per-‐capita Hispanic income, and average Hispanic education. Assuming Hispanic businesses serve the Hispanic population more than the total population, it is expected that these Hispanic-‐specific variables would be a better predictor of Hispanic business sales growth than analogous measures for the total population. An increase in the R2 value to 0.93 verifies this claim. Use of these Hispanic-‐specific independent variables explains 93% of the change in the log of Hispanic business sales. Interestingly, all three Hispanic-‐specific variables have positive effects, though the income effect is not statistically significant.


The final regression includes both total population and Hispanic population levels, as well as well as a measure of overall education levels and a measure of Hispanic average education relative to overall education levels, Hispanic relative average education. The Hispanic relative average education variable is the average education for the Hispanic population divided by the average education for the total population. It measures the educational attainment gap between the Hispanic population and total population. For example, a value of 0.8 in a county means that Hispanics, on average, have only 80% of the education years of the average person in the county. A value of 1 means that average Hispanic educational attainment is equal to the average educational attainment of the total population, or that there is no educational attainment gap. The Hispanic relative average education variable aids in the development of a forecasting model to evaluate the effect of the educational attainment gap on Hispanic business growth. A model to show these effects was developed and is discussed in more depth in the forecasting sections. As stated at the beginning of this section, regression coefficients are given with all other variables held constant. By holding the Hispanic average education variable constant, the effect of moving the educational gap closer to 1, by decreasing the total population’s education level relative to the Hispanic population’s education, would produce coefficients that show the effect of the educational gap variable on Hispanic business growth, measured in the number and sales of Hispanic businesses. A few other variables were added to the regression but were found not to have any statistical significance and not to change the R2, or the explanation of the variation of the dependent variable. Adding squared population variables, which allow for the effect of population to change as population grows, did not change the R2 value significantly and reduced the number of statistically significant variables in the regression. Similarly, adding income and education together did not increase R2 and added noise to the regression. 3 Since education and income are likely to be highly correlated, income was removed from the forecasting model. The R2 value remains near 0.93, which continues to be a high degree of explanation in the dependent variable and in addition, all variables except for total population come through statistically significant. Therefore, this regression is the preferred equation for this set of regressions. Table 3 provides the marginal effects on Hispanic Business Sales of the statistically significant variables from Regression #3 in Table 2 above, the preferred regression. As predicted by the hypotheses, average education of Hispanics and Hispanic population have positive relationships with Hispanic business sales. Hispanics with higher educational attainment have more disposable income to spend at Hispanic businesses. Hispanic individuals with higher levels of educational attainment are more likely to possess the skills required to successfully run a business. In addition to being a predictor of income, education also serves as a measure of English proficiency. As a person goes through higher levels of education it is likely that he or she acquires greater proficiency in English communication skills.


Table 3. Marginal Effect on Hispanic Business Sales for the Preferred Regression

Hispanic Population (1% point increase)

Hispanic Average Education

(1% point increase)

Hispanic Education Relative to Total

Population (1% point increase)

% Increase in Hispanic Business Sales 1.05% 4.70% -‐1.21%

The negative effect of the educational attainment gap variable on Hispanic business sales is seen because both the average Hispanic education and the Hispanic education relative to the total population variables are in the regression equation together. If the Hispanic education is held at the same level, closing the educational attainment gap would mean decreasing the number of years of the average education of the total population. If the top part of the ratio, the average education of the Hispanic population, must be held constant, then the bottom part, the average education of the total population must then be decreased in order to being the ratio closer to 1. Therefore, the population as a whole, both the Hispanic population and the rest of the population, would have lower education levels relative before the gap was closed. Lower overall education levels for total population would explain the decrease in the share of the sales of Hispanic businesses. However, negative effect of decreasing the total population’s average education is not conducive to the intentions of this paper and thus this model is not used in forecasting Hispanic business growth, therefore this negative relationship is not realized in the other forecasting models.

Share of Hispanic Business Sales Regressions

The next regressions were performed using share of Hispanic businesses sales as the dependent variable. Table 4 provides the results from these regressions. The first regression includes only the variable for the percent share of the population that is Hispanic. It is statistically significant and has a positive effect on share of Hispanic business sales. This result reaffirms the hypothesis that a growing Hispanic population has a positive effect on the sales of Hispanic businesses. This variable generates an R2 of 0.61.

Table 4. Sign and Statistical Significance of OLS Regression Coefficient Estimates for the Dependent Variable of the Share of Hispanic Business Sales

Variables Share of Hispanic Sales Regression #1

Share of Hispanic Sales Regression #2

perc_hispanic_pop +*** +*** hisp_avg_educ +** educ_share +*** year2000 -‐ + Counties 88 88 Goodness of Fit (R2) 0.610 0.688

*p<0.05, **p<0.01, ***p<0.001


The second regression includes variables for the share of the population that is Hispanic, average education of the Hispanic population, and Hispanic relative average education. As with the regressions on the log of Hispanic business sales, adding income variables does not change the R2 significantly and adding a percent Hispanic population squared variable incurs substantial noise, making the other independent variables no longer statistically significant. Therefore, those variables are not included in the second regression. The R2 for this model grows to 0.688 when the education variables are included. Regression #2 is the preferred model and is used in the forecasting of future Hispanic business sales below. Table 5 shows the marginal effects on the share of Hispanic business sales for the statistically significant variables from the second, preferred regression. Share of Hispanic business sales increases as both Hispanic population and Hispanic average education grow. As Hispanic population grows so does the core customer base for these Hispanic businesses. Hispanic average education, with its relationship to income and business skills, has a positive effect on Hispanic business sales share.

Table 5. Marginal Effect on Share of Hispanic Business Sales for the Preferred Regression

Hispanic Population

Share (1% point increase)


(1 year increase)

Hispanic Relative Average Education (if Hispanic Average Education / Total

Population Average Education = 1)

% Increase in Share of Hispanic Business Sales

0.09% 0.31% 6.76%

If the educational attainment gap between the two populations was to close, i.e., the educational attainment of the Hispanic population became the same as that of the total population, there would be a 6.76% increase in Hispanic business sales. However, this effect only holds true if the total population’s average education were to decrease. Again, Hispanic education is held constant, so the effects of closing the gap would be from bringing the total population’s average education down to the average education of the Hispanic population. The effect is discussed in greater detail in the forecasting section.

Share of the Number of Hispanic Businesses Regressions

Table 6 shows the results of the regressions using the share of the number of Hispanic businesses as the dependent variable. The independent variables used in these two regressions are identical to those used in the Hispanic business sales regressions described above. The first regression equation has an extremely high R2 of 0.9. This means that the independent variable of percent of the population that is Hispanic explains much of the variation in change of the share of the number of Hispanic businesses. The coefficient on this variable is positive and statistically significant.


Table 6. Sign and Statistical Significance of OLS Regression Coefficient Estimates for the Dependent Variable of the Share of the Number of Hispanic Businesses

Variables Share of Number of Hispanic Businesses Regression #1

Share of Number of Hispanic Businesses Regression #2

perc_hispanic_pop +*** +*** hisp_avg_educ +*** educ_share +*** year2000 -‐ -‐ Counties 88 88 Goodness of Fit (R2) 0.900 0.939

*p<0.05, **p<0.01, ***p<0.001 The second regression includes variables for the share of the population that is Hispanic, the Hispanic average education, and the Hispanic relative average education. These are the same variables used in the second regression for the share of Hispanic business sales. The R2 for this regression increases to 0.939, making it the preferred regression for the forecasting model for the future share of the number of Hispanic businesses. As with both of the previous regression results, adding income variables did not change the R2 significantly. A squared percent of Hispanic population rendered other variables statistically insignificant and did not increase the R2 substantially. Table 7 provides the marginal effects on the share of the number of Hispanic businesses for the statistically significant variables from the second, preferred regression. Hispanic population share and Hispanic average education continue to have a positive relationship with share of the number of Hispanic businesses.

Table 7. Marginal Effect on Share of the Number of Hispanic Business Sales for the Preferred Regression

Hispanic Population

Share (1% point increase)


(1 year increase)

Hispanic Relative Average Education (if Hispanic Average Education / Total

Population Average Education = 1)

% Increase in Share of Hispanic Businesses 0.56% 1.12% 24.32%

The variable for the Hispanic education share has a substantial effect on the share of Hispanic businesses. If the educational gap were closed, a possible 24.32% increase in share of Hispanic businesses could be realized. As the forecasting models are based on future population predictions, the fact that the percentage of the population explains so much of the change in the dependent variable means that the forecasting models should provide accurate results.


VIII. FORECASTING

The preferred regressions from the share of the number of Hispanic and the share of the sales of Hispanic businesses models described in the previous section were used to determine the effects of population growth and changes in the relative education of the Hispanic population on Hispanic business growth. Table 8 provides a benchmark for where Hispanic business growth was in the year 2007. It gives the Hispanic population share of the total population, the total number of Hispanic individuals, the Hispanic business sales share and the number of Hispanic businesses share for three geographic areas in Oregon including Corvallis, Portland, and Salem. As the city of Salem is divided into three counties, Marion, Polk, and Yamhill, and includes Woodburn, the Salem area is used to show the results of the forecasting model. Throughout the remainder of this paper the Salem area will be the focus as the city of Woodburn is the driving force behind this study. In addition, the share of the number of Hispanic businesses will also be the main focus. As shown above, the R2 is higher from the regressions for the share of the number of businesses relative to the regressions for the share of the sales of Hispanic businesses. Therefore, the forecasting results for the share of the number of Hispanic businesses are believed to be more accurate.

Table 8. Hispanic Population, Hispanic Sales Share, and Hispanic Business Share for 2007

Area Hispanic Share of Population

Hispanic Population

Share of Hispanic

Business Sales

Share of the Number of Hispanic

Businesses 2007

Corvallis 5.7% 10,876 0.64% 3.47% Portland 10.3% 167,159 0.44% 3.46% Salem 15.1% 85,342 1.84% 4.46% A parametric analysis was performed by varying the growth rate of educational attainment for the Hispanic population. Three growth rates were used: the growth rate as seen between 2000 and 2007, a 0.1 increase in the growth rate of educational attainment for the Hispanic population over total that for total population, and a growth rate that closes the gap between Hispanic population and total population education attainment by 2030. Results were derived for the years 2015, 2020, 2030, and 2040. The three different forecasting models are presented in the following tables. Hispanic population share is calculated by interpolating the growth of Hispanic population share from 2000-‐2007 for each area. Total projected population estimates for the forecasted years using Oregon Office of Economic Analysis population forecasts are multiplied by Hispanic population share to obtain the Hispanic population. Share of Hispanic sales and share of Hispanic businesses are calculated using the preferred models from the regressions for both the share of Hispanic sales and the share of the number of Hispanic businesses forecasting. Each independent variables, percent share of the population that is Hispanic, Hispanic education


share, and Hispanic average education, are calculated by interpolating their growth from 2000-‐2007 for each area. Table 9 presents the forecasted population and its share of the total population, Hispanic sales share, and the share of the number of Hispanic business for 2015, 2020, 2030, and 2040. If the educational gap were to remain the same, and only the Hispanic population was to change, then the effects only the population change are presented in Table 9.

Table 9. Hispanic Population, Hispanic Sales Share, and Number of Hispanic Business Share Forecasts Using 2007 Hispanic Education Share


Hispanic Population

Share of Hispanic

Business Sales

Share of Hispanic Businesses

2015 Corvallis 7.01% 14,315 1.60% 6.61% Portland 13.14% 231,159 0.37% 3.59% Salem 18.45% 99,012 0.65% 5.76%



2040 Corvallis 11.11% 27,352 3.24% 13.36% Portland 21.91% 522,310 0.96% 7.63% Salem 28.93% 217,353 1.77% 12.07% Figure 1 shows that the share of the number of Hispanic businesses will increase by 5.08% by the year 2030 in the Salem area solely because of the population increase predicted by the Oregon Office of Economic Analysis. The forecasts shown in Table 10 are based upon allowing Hispanic education share in each area to grow by 0.1 from 2007 to 2040, without ever closing the educational gap completely. A 0.1 increase of Hispanic education share means that Hispanics are obtaining more education relative to the total population. In the Salem area,

Figure 1. Forecasted Share of Number of Hispanic

Businesses with Population Change

0

2

4

6

8

10

12

14

16

18

20

2007 2015 2020 2030 2040

% Sha

re of N

umbe

r of H

ispa

nic B

usinesses

Year

Corvallis

Portland

Salem


this translates to a 6.78% increase in the share of the number of Hispanic businesses from 2007 to 2030. This is seen as a 1.7% increase in the share of the number of Hispanic businesses during this time period above the increase seen by population growth alone.

Table 10. Hispanic Population, Hispanic Sales Share, and Number of Hispanic Business Share Forecasts Growing Hispanic Education Share by 0.1 from 2007 to 2040


Hispanic Population

Share of Hispanic

Business Sales





2040 Corvallis 11.11% 27,352 4.12% 15.79% Portland 21.91% 522,310 2.65% 10.06% Salem 28.93% 217,353 3.39% 14.50% The forecasts shown in Table 11 are based upon allowing Hispanic education share to increase to match the total population education share by 2040. Share of Hispanic sales and share of Hispanic businesses grow more relative to a static Hispanic education as indicated by comparing Tables 9, 10, and 11.


Table 11. Hispanic Population, Hispanic Sales Share, and Number of Hispanic Business Share Forecasts Growing Hispanic Education Share to Match Total Population Education Share by the year 2030


Hispanic Population

Share of Hispanic

Business Sales





2040 Corvallis 11.11% 27,352 3.91% 16.52% Portland 21.91% 522,310 1.64% 13.71% Salem 28.93% 217,353 2.44% 17.90% When the educational gap is completely closed by the year 2030, the share of Hispanic businesses jumps to 15.38%. The number of Hispanic businesses would then be almost two-‐thirds of total Hispanic population in 2030. This is much higher than the little-‐over one-‐third of the Hispanic population the businesses would make up if the educational gap continued on the 2007 trajectory. Figure 2 shows the effects of the parametric analysis of the educational attainment gap on the share of the number of Hispanic businesses. Closing the educational attainment gap has a much larger effect on Hispanic business growth. As education attainment is something that can be influenced by policy, it is important to know that increasing Hispanic average education relative to the average education of the total population could have large and positive effects on overall Hispanic business development.

Figure 2. Forecasted Share of Number of Hispanic Businesses in

Salem

0

2

4

6

8

10

12

14

16

18

20

2007 2015 2020 2030 2040

% Sha

re of N

umbe

r of H

ispa

nic B

usinesses

Year

Population Only

Shrink Education Gap

Eliminate Education Gap


X. CONCLUSION

With a rapidly growing Hispanic population and the corollary influx of Hispanic businesses, as exemplified by the growth of Hispanic businesses in the downtown Woodburn area, the future of the economic landscape of Oregon is sure to change. This growing population could be a nexus for new economic development. An interest in predicting this growth and forecasting its effects for other counties sparked this study, in particular how demographic variables in counties along the west coast of the U.S. affect Hispanic business growth. The forecasting models developed under this study suggest that, among large counties in Oregon, California, and Washington, that is counties with populations greater than 100,000, population and education variables have a positive relationship with Hispanic business growth. Demographic variables provided high R2 of 0.9 and 0.93 in the Hispanic business sales and share of the number of Hispanic businesses regressions, suggesting that these variables are a good predictor of Hispanic sales behavior. While growth in total population and Hispanic population explained much of the variation in measures for Hispanic business growth, Hispanic average education repeatedly came out as the variable with the strongest effect. This finding suggests that the human capital, income, and English language skills that come with higher education are paramount for Hispanic businesses to thrive. In Oregon, the Hispanic population is undereducated when compared to the educational attainment of the population as a whole. There is a three year disparity of Hispanic average education versus total average education. This study performed a parametric analysis to determine the effect of this education gap. It was determined that as the gap was closed, the effect on Hispanic business growth was significant and positive. Therefore, resources and policies to help Hispanics achieve higher education could have a major impact on the health of Hispanic businesses.

XI. CLOSING REMARKS

Although this study provides clean and easy to interpret forecasting model results, improvements could be made on its design. Time restrictions required that only data from the U.S. Census Bureau be used for the statistical analysis. This provides a nice baseline to understand how general demographic variables in counties affect business growth. However, the understanding of business growth is limited using a technique such as this. What this study does not capture are the intimate details of each county, details that absolutely effect business development in an area. For example, Woodburn, Oregon had an influx of Hispanics in the 1980s and 1990s that revitalized its downtown area. These business owners vary in education, immigrant generation state, and cultural upbringing. Signs around the Woodburn area are written in Spanish due to its high share of Hispanics in the area, a trait that makes Woodburn relatively unique. Census Bureau data does not capture these effects. Statistical analysis, although impartial and unbiased, has the effect of dehumanizing an issue. In addition, it is


suggested that another forecasting model be conducted to determine the effects of increasing the average Hispanic education while holding the educational gap constant. It would be helpful to understand the effects of policies could be implemented to improve Hispanic educational attainment and bring it closer to that of the total population’s. Below are some suggestions for future research that may be used to capture these more human details that are not measurable by a nation-‐wide survey.

Suggestions for Future Research

Near the end of conducting this study, the authors attended a meeting in Salem with the Hispanic Entrepreneur Collaboration for Action organization. In attendance were entrepreneurs and those in business support services from around Oregon, though mainly the Salem and Woodburn areas were represented. Through discussions with the organization members, ideas for possible future research were developed. Language and cultural barriers are clear obstacles for Hispanic business growth. The core clientele for Hispanic businesses are Hispanic customers. While stores cater to this core group, as exemplified by the Spanish signage in Woodburn, Oregon, they have a tendency to ostracize non-‐Hispanic consumers. Only a few counties in the data set had a majority population of Hispanics making any analysis of this cultural bias impossible. This language and cultural barrier is seen to be generational. That is, first generation Hispanic business owners in Oregon have a relatively difficult time catering to non-‐Hispanics, while third or fourth generation Hispanics are much less conscious of the ethnicity of the consumer. A study to determine the effect of generation of Hispanic business owner on Hispanic business growth may help to quantify this prejudice, enabling first-‐generation business owners to overcome the tendency to isolate. The language barrier also affects the ability of a business owner to seek and utilize business resources. If the resources available to the business owner are marketed only in English or if the resources do not perform the necessary outreach, a Hispanic business owner has a smaller chance of taking advantage of the resources. Through discussions with the business owners and support personnel at the meeting, it was clear that many business owners simply were not aware of the resources available. Business education, not just general education, is also an important factor. A possible study to include surveying business owners in places such as Woodburn to determine the effects of limited business education, resource availability, and resource utilization on Hispanic business growth could provide some interesting results. Attendees at this meeting also suggested a study on the development of a set of best practices for business resources. The need for a study of this type was made clear during the meeting when a question was asked of the whole group soliciting knowledge on, or implementation of, business support strategies that helped to grow individual businesses. Only one person was able to answer the question. Providing a study to determine which practices of business development resource groups are most effective in supporting Hispanic business development could not only help the Hispanic businesses, but also aid the business resource organizations to better serve the Hispanic business community.


XII. REFERENCES

Acs, Zoltan J. and Catherine Armington, 2003. "Endogenous Growth and Entrepreneurial Activity in Cities," Working Papers 03-‐02, Center for Economic Studies, U.S. Census Bureau.

Timothy J. Bartik, 2002. "Small Business Start-‐Ups in the United States: Estimates of the Effects of Characteristics of States," Book chapters authored by Upjohn Institute researchers, in: Norris F. Krueger (ed.), Entrepreneurship: Critical Perspectives on Business and Management. 0:191-‐210. Originally authored in 1989.

Brock, William A. and David S. Evans, 1989. “Small Business Economics,” Small Business Economics 1, Kluwer Academic Publishers. 7-‐20.

Evans, M. D. R. Immigrant entrepreneurship: Effects of ethnic market size and isolated labor pool. (1989). American Sociological Review, 56(6), 950-‐962.

Fadahunsi, A., 2012. “The growth of small businesses: Towards a research agenda.” Am. J. Econ. Bus. Admin. 4: 105-‐115.

Gartner, W. B., & Bhat, S. Environmental and ownership characteristics of small businesses and their impact on development. (2000). Journal of Small Business Management, 38(3), 14-‐26.

Hammarstedt, Mats, 2001. “Immigrant Self-‐employment in Sweden – Its variation and some possible determinants.” Entrepreneurship & Regional Development. 13:147-‐161.

Kean, R., Gaskill, L., et al. “Effects of community characteristics, business environment, and competitive strategies on rural retail business performance.” (1998). Journal of Small Business Management, 36(2), 45-‐57.

Mora, T. M. and A. Davila, 2005. “Ethnic Group Size, Linguistic Isolation, and Immigrant Entrepreneurship in the U.S.” Entrepreneurship & Regional Development. 17:389-‐404.

Mueller, P., Stel, A., & Storey, D. J. The effects of new firm formation on regional development over time: The case of Great Britain. (2008). Small Business Economics, 30(1), 59-‐71. Retrieved from http://www.jstor.org/stable/40650894

Reddy, M. Small business in small economies: Constraints and opportunities for growth. (2007).Social and Economic Studies, 56(1/2), 304-‐321. Retrieved from http://www.jstor.org/stable/27866505


Robles, B. J., & Cordero-‐Guzman, H. (n.d.). Latino self-‐employment and entrepreneurship in the United States: An overview of the literature and data sources. (2007). Annals of the American Academy of Political and Social Science, 613, 18-‐31. R

Roper, S. Modelling small business growth and profitability. (1999). Small Business Economics,13(3), 235-‐252.

Wiklund, Johan, Andreas Rauch, George T. Lumpkin, and Michael Frese, 2009. “Entrepreneurial orientation and business performance: An assessment of past research and suggestions for the future.” Entrepreneurship Theory and Practice. 33:761-‐787.Causa: Oregon's Immigrant Rights Organization, (2010).Latino contributions to Oregon: Strengthening our state economy.

Latino small business and downtown development. (2012). Informally published manuscript, Community Planning Workshop, University of Oregon, Eugene.

Office of Economic Analysis, Department of Administrative Services. (2011). Oregon's demographic trends.

Oregon Office of Economic Analysis, (n.d.). State and county population forecasts and components of change, 2000 to 2004.


XIII. APPENDICES

A.1 Data Construction Step-‐by-‐Step

Steps to Obtain 2000 Population Statistics

1. Create a master file in Microsoft Excel to house 2000 population data for all counties of the three states. Create headers labeled “State,” “County,” “Year,” “Total Population,” “Percent Total Population,” “Hispanic Population,” and “Percent Hispanic Population.” Save the file as “Population Data – 2000.”

2. At the American FactFinder website (http://factfinder2.census.gov/faces/nav/jsf/pages/index.xhtml) select “Advanced Search” followed by “Show me all.” A new screen pops up with three search selection steps and a sidebar of search options. Under Step 1 in the “topic or table name” box enter “2000” while keeping the default radial button “topics” selected. Next, click on the “Geographies” sidebar box. A window will pop up with four tabs; remain on the default tab “List.” Two select options are provided. For the first select option, keep the default of “most requested geographic types.” For the second select option “Select a geographic type,” use the arrow on the right side of the bar to select “County-‐050” from the pull-‐down menu. Next, select Oregon under the “Select a state” pull-‐down menu. Finally, select “All counties within Oregon.” Click the “Add to your selections” box then close the pop-‐up window using the close button in the upper right corner. A document list is generated. Select “Profile of General Demographic Characteristics: 2000,” ID DP-‐1. A table of the population information for all counties within Oregon for 2000 is created.

3. A “Table Tools” option is available under the “Table View” tab above the table. It is part of a group of table view options labeled “Actions.” Clicking on this option opens a tab that includes the option “Transpose Rows/Columns.” It also enables arrow select buttons within the table. Select “Transpose” to modify the table to transpose the data and use the select buttons to de-‐select any non-‐pertinent information. Download the table by clicking the “Download” button under the “Actions” options menu. A new pop-‐up window opens listing available table format options. Under the “Presentations-‐ready formats” category, select “Microsoft Excel (.xls),” then click “OK.” The pop-‐up window closes and a new pop-‐up window opens. This window indicates that the file is being generated. Once completed, a message states that the file is complete and ready for download. Click the download button. An Excel spreadsheet containing the 2000 population data opens. Transfer the data to the spreadsheet built in Step 1 being sure to enter “2000” under the year column.

4. Once the 2000 population data for Oregon has been downloaded, select “Back to Advanced Search.” The previous selections of “2000” and “All Counties within Oregon” will remain. This is visible at the “Search Selections” information window on the upper left side of the web page. Click on the “X” radial button next to the “All Counties within Oregon” selection. Click on the “Geographies” box, select “County-‐050,” select state “California,” and select “All Counties within California.” Under the “Refine your search results” box, enter 2000 and click “Go.” The table, as formatted for collecting the Oregon information, will reappear. Repeat the process described in Step 3 to download the California data.

5. Repeat Step 4 to obtain the 2000 population data for Washington. 6. The master population file for 2000 includes all population data for all counties of Oregon,

California, and Washington.


Steps to Obtain 2007 Population Statistics

1. Create a master file in Microsoft Excel to house all 2007 population data for all counties of the three states. Create headers labeled “State,” “County,” “Year,” “Total Population,” “Percent Total Population,” “Hispanic Population,” and “Percent Hispanic Population.” Save the file as “Population Data – 2007.”

2. Under the “Advanced Search” window of American FactFinder, enter “ACS 2007” at Step 1 in the “topic or table name” box while keeping the default radial button “topics” selected. Do not enter “American Community Survey.” Next, click on the “Geographies” box in the sidebar. Under the second search option “Select a geographic type,” select “County-‐050” from the pull-‐down menu. Next, select Oregon under the “Select a state” pull-‐down menu. Finally, select “All counties within Oregon.” Click the “Add to your selections” box then close the pop-‐up window using the close button in the upper right corner. Next, click the “go” button at Step 1. A list of tables and files is returned by the web site. Choose the 2007 ACS 3-‐year estimates “ACS Demographic and Housing Estimates: 2005-‐2007,” document ID DP05.

3. A new screen opens under the “Table Viewer.” As the 2005 data is mid-‐decade information, data is not available for all of the counties. A “Geography” pull-‐down box lists the counties. Select each county one-‐by-‐one to access the data or to determine if data is not available.

4. For the counties for which data is available, a new screen opens with a table of the demographic and housing data. Use the “Table Tools” option “Transpose” to transpose the table. Deselect “Margin of Error” under both Number and Percent. Detailed data such as age breakdowns and ethnic information other than Hispanic/Hispanic data can also be deselected. Once all de-‐selections are set, download the table into an Excel spreadsheet.

5. Select and copy the salient data (total population, percent total population, Hispanic population, percent Hispanic population) from the file into the spreadsheet created in Step 1. Enter “2007” under the year column. Close the downloaded file.

6. Return to American Factfinder and select the next county using the “Geography” box. The table will change to reflect the data from the next county. Repeat step 4 and 5 to download and save off the data.

7. Once all of the population data from the counties in Oregon have been downloaded, select “Back to Advanced Search.” The previous selections of “ACS 2007” and “All Counties within Oregon” remain at the “Search Selections” information window on the upper left side of the web page. Deselect “All Counties within Oregon.” Click on the “Geographies” box, select “County-‐050,” select state “California,” and select “All Counties within California.” Under the “Refine your search results” box, enter 2007 and click “Go.” The table, as formatted for when collecting the Oregon information, will reappear. Repeat the process described in steps 4 and 5 to download the California data county by county.

8. Repeat Step 7 to obtain the population data for Washington. 9. The master population file for 2007 includes all population data available for all counties of

Oregon, California, and Washington with data.

Steps to Obtain 2000 Income Characteristics

1. Create a master file in Microsoft Excel to house the 2000 income data for all counties of Oregon, California, and Washington. Create headers labeled “State,” “County,” “Year,” “Per Capita Income (dollars) – Total Population,” “Per Capital Income (dollars) -‐ Hispanic Population.” Save the file as “Per Capita Income Data – 2000.”


2. Selected “Income/Earnings (Individuals)” under the “People>Income & Earnings” subcategory of the “Topics” category on the left side of the American FactFinder “Advanced Search” web page. Enter 2000 for year in the box at the “Refine your search results” window. Under the “Geographies” search option, select the area as “County-‐050,” the state as “Oregon,” and the “All counties within Oregon” option. Click “go.” Transpose and download the table titled “Per Capita Income in 1999 (Dollars),” ID P082. Insert the data from the downloaded table into the master file created in Step 1.

3. Return to the “Advanced Search” web page and select the table “Per Capita Income in 1999 (Dollars) (Hispanic or Hispanic,” ID P157H. Perform the download and save the data to the master file.

4. Repeat Steps 2 and 3 for California and Washington. 5. The master income file for 2000 includes all total population and Hispanic income data for all

counties of Oregon, California, and Washington.

Steps to Obtain 2007 Income Characteristics

1. Create a master file in Microsoft Excel to house the 2007 income data for all counties of Oregon, California, and Washington. Create headers labeled “State,” “County,” “Year,” “Per Capita Income (dollars) – Total Population,” “Per Capital Income (dollars) -‐ Hispanic Population.” Save the file as “Per Capita Income Data – 2007.”

2. Selected “Income/Earnings (Individuals)” under the “People>Income & Earnings” subcategory of the “Topics” category on the left side of the American FactFinder “Advanced Search” web page. Enter 2007 for year in the box at the “Refine your search results” window. Under the “Geographies” search option, select the area as “County-‐050,” the state as “Oregon,” and the “All counties within Oregon” option. Transpose and download the 3-‐year ACS estimates table titled “Per Capita Income in the Past 12 Months (In 2007 Inflation-‐Adjusted Dollars),” ID B19301. Insert the data from the downloaded table into the master file created in Step 1. As with the population data, some of the counties for the mid-‐decade sampling do not have income information. In that case, the master file will not include the counties with missing income data. The counties excluded were the same counties excluded in the population data. The counties that do not have enough data seem to be counties with a total population of 25,000 or less.

3. Return to the “Advanced Search” web page and select the table “Per Capita Income in the Past 12 Months (In 2007 Inflation-‐Adjusted Dollars) (Hispanic or Hispanic),” ID B19301I. Perform the download and save the data to the master file.

4. Repeat Steps 2 and 3 for California and Washington. 5. The master income file for 2007 will include all total population and Hispanic income data

available for all counties of Oregon, California, and Washington with data.

Steps to Obtain 2000 Educational Attainment

1. Create a master file in Microsoft Excel to house the 2000 educational attainment data for all counties of Oregon, California, and Washington. Create two worksheets with headers labeled “County,” “State,” “Year,” “ Population,” “Less than 9th Grade,” “9th to 12th Grade, No Diploma,” “High School Graduate,” “Some College, No Degree,” “Associate’s Degree,” “Bachelor’s Degree,” “Graduate or Professional Degree,” “High School Graduate or Higher,” “Bachelor’s Degree or Higher.” Name one sheet “Total Population” and the second sheet “Hispanic Population.” Save the file as “Educational Attainment – 2000.”

2. Select “Educational Attainment” under the “Topics>People>Education” sidebar in American FactFinder. Under the “Geographies” sidebar, chose the geographic type “County-‐050,” the


state of Oregon, and “All counties within” Oregon. At the “Refine your search results” box, enter 2000 under the “topics or table name” box. Click “go.”

3. Transpose, deselect unwanted data, and download “Sex by Educational Attainment for the Population 25 Years and Over,” ID PCT064 for total population. Insert the data from this download into the Excel worksheet labeled “Total Population.” Close the downloaded data file.

4. Perform Step 3 by selecting the table “Sex by Educational Attainment for the Population 25 years and over (Hispanic or Hispanic),” ID P148H to obtain Hispanic population educational attainment data. Save the downloaded data into the second worksheet labeled “Hispanic Population.

5. Repeat Steps 2 through 4 to obtain 2000 education attainment data for the counties of Washington and California adding the resulting data to the corresponding worksheets in the master Excel file.

6. Once the data has been collected for the three states, create a third worksheet in the Excel file with two sets of column headings identical to the headings listed in Step 1. Incorporate designation distinctions in the headings. For example, use “Total Population” and “Hispanic Population” in lieu of “Population.” Transfer the data from the other two worksheets into this worksheet combining total population and Hispanic population into a single worksheet.

Steps to Obtain 2007 Educational Attainment

1. Create a master file in Microsoft Excel to house the 2007 educational attainment data for all counties of Oregon, California, and Washington. Create two sheets with headers labeled “County,” “State,” “Year,” “Population,” “Less than 9th Grade,” “9th to 12th Grade, No Diploma,” “High School Graduate,” “Some College, No Degree,” “Associate’s Degree,” “Bachelor’s Degree,” “Graduate or Professional Degree,” “High School Graduate or Higher,” “Bachelor’s Degree or Higher.” Rename one sheet as “Total Population” and the second sheet as “Hispanic Population.” Save the file as “Educational Attainment – 2007.”

2. Selected “Educational Attainment” under the “Topics>People>Education” sidebar in American FactFinder. Under the “Geographies” tab, chose the geographic type of “County-‐050” and “All counties within” each state.

3. For each state, download “Educational Attainment,” ID S1501 to obtain 3-‐year estimates for total population education attainment data and “Sex by Educational Attainment for the Population 25 Years and Over (Hispanic or Hispanic),” ID B15002I for Hispanic population into the master file. The tables will need to be transposed and unnecessary data deselected prior to download.

4. Create a new worksheet in the file with the same column headings for total population and a second set of column headings for Hispanic population being sure to designate the Hispanic data headings as such. Transfer the data from the other two spreadsheets into this spreadsheet combining total population and Hispanic population into a single spreadsheet.

Steps to Obtain Survey of Business Owners Data

2002 1. Create a master file in Microsoft Excel to house the 2002 SBO data for all counties in each of the

three states. Incorporate headers labeled “County,” “State,” “Year,” “Number of Firms with or without paid employees,” “Sales, receipts, and value of shipments of firms with or without paid employees ($1,000),” “Number of Firms with paid employees,” “Sales, receipts, and value of shipments of firms with paid employees ($1,000).” Name the sheet “Oregon 2002.” Make two


copies of the sheet naming each “California 2002” and “Washington 2002.” Save the file as “SBO – 2002.”

2. On American FactFinder choose “Survey of Business Owners” under the “Topics > Program” sidebar. Search for 2002 in the “Refine your search” box. Under the “Geographies” sidebar, enter the geographic area of “County-‐50” and “All counties within Oregon.” Select the file “Survey of Business Owners (SBO): Geographic Area Series: Economy-‐Wide Estimates of Business Ownership by Gender, Hispanic or Hispanic Origin, and Race: 2002,” ID SB0200A1. Select the “Modify Table” option. Different header selections will appear. Under the “Meaning of SBO Group” header, select the “Filter” icon. A filtering pop-‐up screen will appear. On this screen, pick codes 00 – All Firms, 20 – Hispanic or Latino, 29 – Not Hispanic or Latino, and 98 -‐ Publicly held and other firms not classifiable by gender, Hispanic or Latino origin, and race. Under the “Meaning of Gender Code” header, select the filter icon and the codes 00 – All Firms and 04 -‐ Publicly held and other firms not classifiable by gender, Hispanic or Latino origin, and race. Download the file in Excel format. Copy the pertinent data from the downloaded file into the Excel file generated in Step 1 under the Oregon spreadsheet.

3. Repeat Step 2 selecting the California counties. Download the data into the California spreadsheet.

4. Repeat Step 2 for the Washington counties. 2007

1. Create a Microsoft Excel file to house the 2007 SBO data for all counties in each of the three states. Incorporate headers labeled “County,” “State,” “Year,” “Number of Firms with or without paid employees,” “Sales, receipts, and value of shipments of firms with or without paid employees ($1,000),” “Number of Firms with paid employees,” “Sales, receipts, and value of shipments of firms with paid employees ($1,000).” Name the sheet “Oregon 2007.” Make two copies of the sheet naming each “California 2007” and “Washington 2007.” Save the file as “SBO – 2007.”

2. On American FactFinder choose “Survey of Business Owners” under the “Topics > Program” sidebar. Search for 2007 data in the “Refine your search” box. Under the “Geographies” sidebar, choose a geographic area of “County-‐50” and “All counties within Oregon.” Select and download the file “Statistics for All U.S. Firms by Industry, Gender, Ethnicity, and Race for the U.S., States, Metro Areas, Counties, and Places: 2007,” ID SB0700CSA01. Select the “Modify Table” option. Different header selections will appear. Under the “Meaning of Ethnicity code” header, select the “Filter” icon. A filtering pop-‐up screen will appear. On this screen, pick codes 001 – All firms, 020 – Hispanic, 028 – Equally Hispanic/non-‐Hispanic, 029 – Not Hispanic, 096 -‐ All firms classifiable by gender, ethnicity, race, and veteran status, and 098 -‐ Publicly held and other firms not classifiable by gender, Hispanic or Latino origin, and race. Under the “Meaning of Gender code” header, select the filter icon and the codes 001 – All firms, 096 -‐ All firms classifiable by gender, ethnicity, race, and veteran status, and 098 -‐ Publicly held and other firms not classifiable by gender, Hispanic or Latino origin, and race. Deselect the NAICS code column and all columns with relative % information. Download the file in Excel format. Copy the pertinent data from the downloaded file into the Excel file generated in Step 1 under the Oregon spreadsheet.

3. Repeat Step 2 selecting the California counties. Download the data into the California spreadsheet.


4. Repeat Step 2 for the Washington counties.

Overall Data

1. Once all of the data is collected, it needs to be formatted into one master Excel file that is used by Stata. Open a new blank Excel workbook. Save the workbooks as “Master Data File – Stata Ready.” Create a series of headers labeled “County,” “State,” “Year,” “Total Population,” “Hispanic or Latino Population (of any race),” “Percent Hispanic,” “Number of All Firms (with / without paid employees),” “Number of Hispanic Firms (with / without paid employees,” “Number of Equally Hispanic / Non-‐Hispanic Firms (with / without paid employees),” “Number of Non-‐Hispanic Firms (with / without paid employees),””Total Number of Classifiable Firms,” “Total Number of Publically Held Firms,” “Sales, receipts, and value of shipments of all firms with or without paid employees ($1,000),” “Sales, receipts, and value of shipments of Hispanic firms with or without paid employees ($1,000),” “Sales, receipts, and value of shipments of equally Hispanic and non-‐Hispanic firms with or without paid employees ($1,000),” “Sales, receipts, and value of shipments of non-‐Hispanic firms with or without paid employees ($1,000),” “Sales, receipts, and value of shipments of classifiable firms ($1,000),” “Sales, receipts, and value of shipments of publically held firms ($1,000),” “Per Capita Income (dollars) -‐ Total Population,” “Per Capita Income (dollars) -‐ Hispanic,” “Total Population 25 years and over,” ”Less than 9th grade – All population 25 years and over,” “9th to 12th grade, no diploma – All population 25 years and over,” “High school graduate (includes equivalency) -‐ All population 25 years and over,” “Some college, no degree – All population 25 years and over,” “Associate's degree – All population 25 years and over,” “Bachelor's degree -‐ All population 25 years and over,” “Graduate or professional degree -‐ All population 25 years and over,” “High school graduate or higher -‐ All population 25 years and over,” “Bachelor's degree or higher – All population 25 years and over,” “Hispanic Population 25 years and over,” ”Less than 9th grade – Hispanic population 25 years and over,” “9th to 12th grade, no diploma – Hispanic population 25 years and over,” “High school graduate (includes equivalency) -‐ Hispanic population 25 years and over,” “Some college, no degree – Hispanic population 25 years and over,” “Associate's degree – Hispanic population 25 years and over,” “Bachelor's degree -‐ Hispanic population 25 years and over,” “Graduate or professional degree -‐ Hispanic population 25 years and over,” “High school graduate or higher -‐ Hispanic population 25 years and over,” “Bachelor's degree or higher – Hispanic population 25 years and over.” When complete, there are forty-‐one columns.

2. Open the files of collected data: Population Data – 2000, Population Data – 2007, Per Capita Income – 2000, Per Capita Income – 2007, Educational Attainment – 2000, Educational Attainment – 2007, SBO – 2002, and SBO -‐ 2007. Copy the pertinent data from each of these files into the master file by state and year.

3. Search for missing or incomplete information including “S,” “D,” and “?.” Delete the content of the cells with these indicators.

The next appendix lists the counties of each state that were either eliminated or required data modification. In addition, the Stata script was programmed to ignore any counties with less than 100,000 people. Of the 135 counties that make up the composition of the three states, 88 were used in the final regressions.


A.2 Explanation of Observations Eliminated and/or Modified

Tables 12, 13, and 14 list the counties in California, Oregon, and Washington that were either eliminated from the data set or were modified to provide more complete data for the data set. The tables indicate whether the county listed was eliminated or data was modified. They also include explanations of the reason for elimination or how the data was modified. An asterisk next to the name indicates that the county was eliminated by the regression as the population was less than 100,000.

Table 12. List of California Counties Modified or Eliminated From Final Data Set

County Modified / Eliminated Reason

Alpine* Eliminated No population, Hispanic business sales information, or education data for 2007.

Amador* Modified

For 2007, the number of Hispanic businesses and Hispanic business sales were determined by subtracting classifiable business data from non-‐Hispanic business data. No equally Hispanic / non-‐Hispanic data was available.

Butte Eliminated No minority business data available for 2000.

Calaveras* Modified


Colusa* Eliminated Cannot create number of Hispanic businesses out of data available. No classifiable, non-‐Hispanic or equally Hispanic / non-‐Hispanic business data available for 2007.

Del Norte* Eliminated No minority business data available for 2000. Glenn* Eliminated No minority business data available for 2000. Humboldt Eliminated No minority business data available for 2000.

Inyo* Eliminated No population, Hispanic business sales information, or education data for 2007.

Lake* Eliminated No minority business data available for 2000.

Lassen* Modified


Madera Eliminated No minority business data available for 2000.

Marin Modified For 2007, the number of Hispanic businesses was generated by subtracting non-‐Hispanic businesses and equally Hispanic / non-‐Hispanic businesses from classifiable businesses.

Mariposa* Eliminated No minority business data available for 2000. Mendocino* Eliminated No minority business data available for 2000.

Modoc* Eliminated No population, Hispanic business sales information, or education data for 2007.

Mono* Eliminated No population, Hispanic business sales information, or education data for 2007.



Nevada* Eliminated No minority business data available for 2000.

Plumas* Eliminated No population, Hispanic business sales information, or education data for 2007.

San Benito* Eliminated No minority business data available for 2000.

San Mateo Eliminated No population, Hispanic business sales information, or education data for 2007.

Santa Cruz Eliminated No minority business data available for 2000.

Shasta Eliminated Total number of businesses and total number of classifiable businesses data was unavailable for 2007.

Sierra* Eliminated No population, Hispanic business sales information, or education data for 2007.

Siskiyou* Eliminated No minority business data available for 2000. Sutter* Eliminated No minority business data available for 2000. Tehama* Eliminated No minority business data available for 2000.

Trinity* Eliminated Total number of businesses and total number of classifiable businesses data was unavailable for 2007.

Tuolumne* Eliminated No non-‐Hispanic, Hispanic, or classifiable businesses data available for 2007.

Yola Modified For 2007, the number of Hispanic businesses was generated by subtracting non-‐Hispanic businesses and equally Hispanic / non-‐Hispanic businesses from classifiable businesses.

Yuba* Eliminated No minority business data available for 2000. Also, in 2002, the number of Hispanic businesses for Amador, Calaveras, Lassen, and Yuba counties in California were zero based on subtracting the number of non-‐Hispanic businesses from all businesses.

Table 13. List of Oregon Counties Modified or Eliminated From Final Data Set


Baker* Eliminated No population, Hispanic business sales information, or education data for 2007.

Benton* Modified


Clatsop* Modified


Columbia* Modified


Coos* Modified For 2007, the number of Hispanic businesses and Hispanic business



sales were determined by subtracting classifiable business data from non-‐Hispanic business data. No equally Hispanic / non-‐Hispanic data was available.

Crook* Eliminated No population, Hispanic business sales information, or education data for 2007.

Curry* Eliminated No population, Hispanic business sales information, or education data for 2007.

Deschutes Eliminated No data available for sales in Hispanic businesses for 2002.

Douglas Modified


Gilliam* Eliminated No population, Hispanic business sales information, or education data for 2007.

Grant* Eliminated No population, Hispanic business sales information, or education data for 2007.

Harney* Eliminated No population, Hispanic business sales information, or education data for 2007.

Jefferson* Eliminated No Hispanic population, Hispanic business sales information, or education data for 2007.

Josephine* Eliminated No minority business data available for 2000.

Klamath* Modified For 2007, the number of equally Hispanic / non-‐Hispanic businesses was generated by subtracting non-‐Hispanic businesses and Hispanic businesses from classifiable businesses.

Lake* Eliminated No population, Hispanic business sales information, or education data for 2007.

Lane Eliminated No Hispanic minority business data available for 2000.

Lincoln* Modified


Linn Modified For 2007, the number of equally Hispanic / non-‐Hispanic businesses was generated by subtracting non-‐Hispanic businesses and Hispanic businesses from classifiable businesses.

Malheur* Eliminated No minority business data available for 2000.

Marion Modified For 2007, the number of equally Hispanic / non-‐Hispanic businesses was generated by subtracting non-‐Hispanic businesses and Hispanic businesses from classifiable businesses.

Morrow* Eliminated No population, Hispanic business sales information, or education data for 2007.

Polk* Modified For 2007, the number of equally Hispanic / non-‐Hispanic businesses was generated by subtracting non-‐Hispanic businesses and Hispanic businesses from classifiable businesses.

Sherman* Eliminated No population, Hispanic business sales information, or education data for 2007.

Tillamook* Modified For 2007, the number of Hispanic businesses and Hispanic business




Umatilla* Modified For 2007, the number of equally Hispanic / non-‐Hispanic businesses was generated by subtracting non-‐Hispanic businesses and Hispanic businesses from classifiable businesses.

Union* Modified


Wallowa* Eliminated No population, Hispanic business sales information, or education data for 2007.

Wasco* Modified


Wheeler* Eliminated No population, Hispanic business sales information, or education data for 2007.

Yamhill* Modified For 2007, the number of Hispanic businesses was generated by subtracting non-‐Hispanic businesses and equally Hispanic / non-‐Hispanic businesses from classifiable businesses.

Also, in 2002, the number of Hispanic businesses for Benson, Clatsop, Columbia, Hood, Klamath, Lincoln, Tillamook, Union, Wasco, and Yamhill counties in Oregon were zero based on subtracting the number of non-‐Hispanic businesses from all businesses. Table 14. List of Washington Counties Modified or Eliminated From Final Data Set


Adams* Eliminated No population, Hispanic business sales information, or education data for 2007.

Astoin* Eliminated No Hispanic population or education data for 2007. Chelan* Eliminated No minority business data available for 2000. Clallam* Eliminated No minority business data available for 2000.

Clark Modified


Columbia* Eliminated No population or education data for 2007.

Cowlitz* Modified


Ferry* Eliminated No population or education data for 2007. Franklin* Modified For 2007, the number of Hispanic businesses and Hispanic business




Garfield* Eliminated No population or education data for 2007. Grant* Eliminated No minority business data available for 2000.

Grays Harbor* Modified


Island* Modified


Jefferson* Modified


Kitsap Eliminated No minority business data available for 2000.

Klickitat* Modified


Lincoln* Eliminated No population or education data for 2007.

Mason* Modified


Okanogan* Modified


Pacific* Modified


Pend Oreille* Eliminated No population or education data for 2007.

Pierce Eliminated No population or education data for 2007. San Juan* Eliminated No population or education data for 2007. Skamania* Eliminated No population or education data for 2007.

Stevens* Modified


Thurston Eliminated No minority business data available for 2000. Wahkiakum* Eliminated No population or education data for 2007.



Walla Walla* Eliminated No minority business data available for 2000.

Whatcom Eliminated No minority business data available for 2000.

Whitman* Modified


Yakima Modified


Also, in 2002, the number of Hispanic businesses for <> counties in Washington were zero based on subtracting number of non-‐Hispanic businesses from all businesses.

A.3 Tables for Least-‐Squares Coefficient Estimates with Values Tables 15, 16, and 17 correspond to Tables 2, 4, and 6 respectively. The actual values obtained in the regressions are provided.

Table 15. Value of Least-‐Squares Coefficient Estimates for the Log of Hispanic Business Sales Regressions (Standard Errors in Parentheses)

Variables Log of Hispanic Sales Regression #1



In_total_pop 1.452*** (0.0825) 0.0529

(0.123)

In_total_income 2.255** (1.028)

In_avg_educ -‐6.948** (2.667)

Year2000 -‐0.091 (0.226)

-‐0.142 (0.122)

-‐0.178* (0.097)

In_hispanic_pop 1.084*** (0.038)

1.048*** (0.085)

In_hisp_income 0.157 (0.428)

In_hisp_avg_educ 4.549*** (1.137)

4.696*** (0.888)

In_educ_share -‐1.205* (0.687)

Counties 88 88 88 Goodness of Fit (R2) 0.801 0.93 0.933

*p<0.05, **p<0.01, ***p<0.001


Table 16. Value of Least-‐Squares Coefficient Estimates for the Share of Hispanic Business Sales Regressions (Standard Errors in Parentheses)

Variables Share of Hispanic Sales Regression #1

Share of Hispanic Sales Regression #2

perc_hispanic_pop 0.086*** (0.008)

0.094*** (0.009)

hisp_avg_educ 0.314** (0.141)

educ_share 6.757*** (2.082)

year2000 -‐0.066 (0.249)

0.032 (0.233)

Counties 88 88 Goodness of Fit (R2) 0.610 0.688

*p<0.05, **p<0.01, ***p<0.001

Table 17. Value of Least-‐Squares Coefficient Estimates for the Share of Hispanic Businesses Regressions (Standard Errors in Parentheses)

Variables Share of Hispanic Businesses Regression #1

Share of Hispanic Businesses Regression #2

perc_hispanic_pop 0.528*** (0.019)

0.556*** (0.020)

hisp_avg_educ 1.119*** (0.318)

educ_share 24.322*** (4.699)

year2000 -‐0.633 (0.642)

-‐0.286 (0.525)

Counties 88 88 Goodness of Fit (R2) 0.900 0.939

*p<0.05, **p<0.01, ***p<0.001

A.4. Error Terms

Using the final forecasting models for share of Hispanic business sales and share of number of Hispanic businesses, comparisons can be made between actual shares of number of Hispanic businesses and sales versus what is predicted by the models. Data for actual shares are from 2007. Counties used for this comparison are from the Corvallis area (Benton and Linn County), Portland Metro Area (Washington, Clackamas, and Multnomah County), and Salem area (Marion, Polk, and Yamhill County).


Table 18. Error Terms for Share of Sales and Share of Hispanic Business Models

Area Actual Predicted by Model Error (Actual – Predicted) Share of Hispanic Sales Model

Corvallis 0.64% 1.11% -‐0.47% Portland 0.44% 0.18% 0.26% Salem 1.83% 0.29% 1.54%

Share of Hispanic Business Model Corvallis 3.48% 4.65% -‐1.17% Portland 3.46% 2.23% 1.23% Salem 4.46% 3.72% 0.74%

hispanic business growth in oregon by kendra gramlich and...

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