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A Quantitative Analysis of Human Capital as an Economic Development Tool for the South

Dissertation
Author: Bethany Parker Mullin
Abstract:
Alabama has been one of the poorest states since the U.S. Census began gathering data in 1790. The purpose of the quantitative study was to evaluate human capital as an economic development tool in Alabama. The study evaluated relationships between human capital and economic development from 1950-2000 within the context of human capital theory. The research questions addressed the relationship between human capital and economic development at the county level and were analyzed using cross-sectional longitudinal analyses. Multilevel regressions were used to estimate the relationships at the p < .05 level. Government records provided the data. Results indicated a significant causal relationship from investment in human capital to economic development. Every one percentage point increase in human capital investment caused an increase of 13,440 jobs per county. Non-rural counties added 34,786 jobs for every one percentage point increase in human capital, but rural counties did not gain a significant return on human capital investment. The extremely low populations of the rural counties, coupled with outmigration of educated workers, were likely causes of this outcome. Results demonstrated that the gap between economic development in counties that invest in human capital and those who do not has been widening since 1950, and that human capital was the most significant variable in determining economic development. Increasingly strong correlations between human capital and economic development were found in each decade and were significant at the p < .01 level. The results help policy makers in economic development efforts by quantifying returns to human capital investments. Policy recommendations include increasing human capital investment, promoting stable in-tact families, and attracting educated workers back to rural counties once they finish their education. Recommendations for future research include how family environments contribute to a county's business, labor, and economic landscapes, and how human capital and family social capital interact to improve economic outcomes.

viii Table of Contents List of Tables ................................................................................................................... x

List of Figures ................................................................................................................. xi

Chapter 1: Introduction .................................................................................................... 1 Background ................................................................................................................ 2 Problem Statement ..................................................................................................... 4 Purpose ....................................................................................................................... 6 Research Questions .................................................................................................. 16 Hypotheses ............................................................................................................... 17 Nature of the Study .................................................................................................. 20 Significance of the Study ......................................................................................... 23 Definitions................................................................................................................ 25 Summary .................................................................................................................. 27

Chapter 2: Literature Review ......................................................................................... 28 Introduction .............................................................................................................. 28 Overview of Human Capital .................................................................................... 29 Human Capital and Income Levels .......................................................................... 34 Human Capital and Job Growth ............................................................................... 45 Family Structure and Maternal Education ............................................................... 55 Other Variables Associated with Economic Growth or Income .............................. 63 Summary of Literature Review ................................................................................ 66

Chapter 3: Research Method.......................................................................................... 70 Research Methods and Design ................................................................................. 76 Participants ............................................................................................................... 87 Materials and Instruments ........................................................................................ 88 Operational Definition of Variables ......................................................................... 89 Data Collection, Processing, and Analysis .............................................................. 93 Methodological Assumptions, Limitations, and Delimitations ............................. 102 Ethical Assurances ................................................................................................. 106 Summary ................................................................................................................ 109

Chapter 4: Findings ...................................................................................................... 111 Results .................................................................................................................... 112 Evaluation of Findings ........................................................................................... 138 Summary ................................................................................................................ 160

Chapter 5: Implications, Recommendations, and Conclusions ................................... 165 Implications............................................................................................................ 167 Recommendations .................................................................................................. 184 Conclusions ............................................................................................................ 188

ix References .................................................................................................................... 194

Appendices................................................................................................................... 200 Appendix A: Descriptive Statistics of the Population of Alabama ........................ 201 Appendix B: Model 1, Unconditional Means, Random Intercept Model .............. 203 Appendix C: Model 2, Unconditional Means, Random Slope Model ................... 204 Appendix D: Model 3, Autoregressive Covariances to Test Residuals ................. 205 Appendix E: Model 4, Independence, Homogeneity of Residual Variance .......... 207 Appendix F: Model 5, Add in Covariates Except HC and Rural........................... 209 Appendix G: Model 6, Random Slope Model, Add Interactions with Time ......... 211 Appendix H: Model 7, Random Slope Model, Insignificant Variables Removed 214 Appendix I: Model 8, Add in Rural Main Effect and Interaction with Time ........ 216 Appendix J: Model 9, Add HC Main Effect and Interaction with Time ............... 219 Appendix K: Model 10, Final Model with HC-Rural-Time Interaction ................ 222 Appendix L: Model 11, Final Model with HC-Rural-Time Interaction ................ 225 Appendix M: Model 12, Random Slope Model with Slope Change in 1990 ........ 228 Appendix N: Human Capital's Increasing Role in Economic Development ......... 232 Appendix O: Descriptive Statistics of the Rural Counties..................................... 233 Appendix P: Descriptive Statistics of the Non-Rural Counties ............................. 234 Appendix Q: Regression Statistics for Dallas and Jefferson Counties .................. 235

x List of Tables Table 1 Educational Attainment of Adults Over 25 Years Old, 2000 ................................. 3 Table 2 Descriptions of Subsets of Independent Variables ............................................. 91 Table 3 Descriptions of Subsets of the Dependent Variables .......................................... 93 Table 4 General Descriptive Statistics of the Population of Alabama ......................... 112 Table 5 Correlation Analysis for Hypothesis 1 Lagged Variables ............................... 115 Table 6 Multilevel Regression Statistics ....................................................................... 118 Table 7 Correlation Analysis for Hypothesis 2............................................................. 121 Table 8 Multilevel Regression Statistics for Hypothesis 2............................................ 122 Table 9 T-test for Comparison of Means by Type of County ........................................ 125 Table 10 Correlation Analysis for Rural Counties ....................................................... 127 Table 11 Correlation Analysis for Non-Rural Counties ............................................... 127 Table 12 Multilevel Regression Statistics for Hypothesis 3.......................................... 129 Table 13 Descriptive Statistics for Dallas and Jefferson Counties .............................. 135 Table 14 OLS Regression Statistics for Hypothesis 4 ................................................... 137 Table 15 Multilevel Regression Statistics for Model 9, Hypothesis 1 .......................... 143 Table 16 Correlation Analysis for Hypothesis 2........................................................... 148 Table 17 Multilevel Regression Statistics for Hypothesis 3.......................................... 155 Table 18 Alabama's Largest Private Employers, 2000 ................................................ 171

xi List of Figures Figure 1. Human capital model (Krugman & Wells, 2009). .............................................. 8 Figure 2. Procedures for current research ......................................................................... 94 Figure 3. Job Growth in the Slowest and Fastest Growing Counties ............................. 132 Figure 4. Human Capital Levels of Dallas and Jefferson Counties ............................... 133 Figure 5. Human Capital and Job Growth, Dallas and Jefferson ................................... 134 Figure 6. Human Capital's Increasing Role in Job Growth ............................................ 149

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Chapter 1: Introduction In the last half of the twentieth century, the needs of American employers shifted away from the low-skilled labor used in farming and manufacturing towards a more highly-educated workforce required in industries such as engineering, computer science, healthcare, and other growing industries. Alabama, however, has not embraced these changing labor requirements as rapidly or thoroughly as other areas of the United States. Despite voluminous research touting the benefits of an educated workforce, Alabama continues to lag behind the rest of the country in terms of educational attainment levels. In addition to lower educational attainment levels, the citizens of Alabama, especially in rural areas of Alabama, possess low job growth and a low labor force participation rate (United States Census Bureau, 2009). These factors are associated with a high poverty rate that has persisted for generations (Levernier, 2003). The poverty of Alabama’s citizens cannot be alleviated without a vibrant labor force able to secure employment. Therefore, the primary focus of a county’s economic development programs is to attract employers to the county (Gibbs, 2005). Identifying the variables that entice employers to locate in a certain area is crucial in the fight against poverty. From 2000 to 2005, the rate of employment growth in Alabama was less than half the rate of employment growth in the rest of the country (U.S. Census Bureau, 2009). Some researchers have suggested that the slow growth is caused by the lack of an educated workforce (Gibbs & Beaulieu, 2005). Many researchers have examined economic development, and more specifically, rural economic development (Gibbs & Beaulieu, 2005; Baldwin & Borrelli, 2009; Barkley, Henry, & Li, 2005). Regression analysis has been used in studies that examine

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economic development, and income serves as a common dependent variable (Li, 2005; Goetz & Ruphasinga, 2005). Other studies have used the poverty rate or job growth as dependent variables (Pandey & Zahn, 2006; Barkley et al., 2005). Differing geographic areas have also been analyzed, including nations, regions, states, metropolitan statistical areas, and counties. The measurement methods in many previous studies were effectively applied in the current examination of Alabama, where the returns to human capital investment at the county level were quantified. The study differed from previous studies by analyzing job growth at the county level in Alabama. Chapter 1 begins with a brief background of the issue, followed by a problem statement and a purpose statement. Research questions and hypotheses are introduced next. The nature and significance of the study will be presented, and then the chapter will end with the definitions of terms that will be used throughout the discussion of the research. Background A generation ago Southern communities could be economically viable without a high level of human capital investment because employment in manufacturing and farming did not require such investment. However, employers are now requiring higher levels of education and training to work in growing industries such as health care, computer sciences, finance, and communication (U.S. Bureau of Economic Analysis, 2009). As a result of the changing labor market, communities cannot thrive without a well-educated workforce. Many counties, especially rural counties, have not yet embraced this change. Despite extensive research touting the benefits of an educated

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workforce, Alabama continues to lag behind the rest of the country in terms of educational attainment levels. Table 1 shows the difference in educational attainment levels among various groups of adults over 25 years of age. Alabama’s significantly lower levels of education are associated with lower economic growth. In fact, many researchers have concluded that the failure to adequately invest in education is the most significant cause of poverty in America (Levernier, 2003; Gibbs, 2005; Gibbs & Beaulieu, 2005; Hill, 1998). The results of the current research serve to improve awareness among policy makers about the increased importance of human capital as an economic development tool. This awareness could lead to the development of policies to increase the human capital attainment within communities. Table 1 Educational Attainment of Adults Over 25 Years Old, 2000 Category United States Rural United States Non-Rural Alabama Rural Alabama Percent of Adults with High School Diploma

81% 75% 77% 67% Percent of Adults with College Degree 25% 16% 20% 11% Note. Figures are derived from data provided by the U.S. Census Bureau (2009). The notion that more education leads to greater economic well-being is not a new one. In fact, Adam Smith, the renowned British scholar, discussed the concept in 1776 (Krugman & Wells, 2009). The human capital theory developed by Barry Chiswick and Gary Becker in the 1960s explained increases in economic well-being in terms of higher human capital accumulation (Becker, 1992). Human capital has been traditionally

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defined as investment in education, nutrition, and other factors affecting physical, financial, and emotional well-being, but education is the primary determinant of human capital (Becker, 1964). Human capital theory will be discussed at length in chapter 2 of this document. In their human capital theory, Becker and Chiswick relate human capital investments to economic growth and other economic issues, such as poverty. Other researchers have repeatedly validated the theory (Barkley et al., 2005; Hill, 1998; Gibbs, 2005; Lehrer, 2004; Seo, 2005). Proponents of human capital theory contend that people make decisions about their education and training by comparing the benefits and costs (Becker, 1992). Individuals will increase their human capital investments if they perceive benefits from such investments. The results of the current research quantified the benefits of human capital investments and may encourage individuals and communities to increase investments in human capital. Problem Statement Alabama lags behind the United States in every significant economic, business, and social measure. Alabama is ranked 49 th in labor force participation, 46 th in percentage of students who graduate from high school, and 45 th in percentage of citizens who graduate from college (U.S. Census Bureau, 2009). These variables contribute to high intergenerational poverty (Goetz, 2008). Income levels in Alabama have consistently been lower than almost every other state (U.S. Census Bureau, 2009). In fact, Alabama has been among the ten poorest states since the United states began measuring and tracking census data in 1790 (Gauthier, 2003). Alabama is ranked 44 th in median family income, which places the

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state in 8 th place for the percentage of people living below the federally defined poverty level (U.S. Bureau of Economic Analysis, 2007). Citizens in Alabama are 30% more likely to live in poverty than citizens elsewhere in the country (U.S. Bureau of Economic Analysis). Alabama citizens are also 68% more likely to be unemployed. Creating more jobs in Alabama would improve the income and poverty levels of the state. However, the rate of employment growth in Alabama is less than half the rate of U.S. growth. Localities struggle with determining the most effective method of attracting employers (Goetz, 2008; Hoogstra, Van Dijk, & Florax, 2005). According to many researchers, such as Goetz (2008), Levernier (2003), and Li (2005), increasing the level of human capital of the workforce is one of the most effective ways to attract new businesses to a community. However, few researchers have analyzed the relationship quantitatively at the county level in Alabama. The results of the current study contribute to human capital theory by quantifying the returns to human capital investment, which will assist counties in economic development programs by providing them with measurable investment returns. Demonstrating a clear benefit to investing in human capital will cause an increase in the amount of human capital obtained, a result that has far-reaching applications outside of the state of Alabama. Localities everywhere are constrained by finite resources needed to satisfy infinite needs, the classic economizing problem (McConnell & Brue, 2008). The current study assists localities by providing a measurable return on investment in their limited resources.

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Purpose The purpose of the quantitative study was to determine the nature of the relationship between human capital investment and economic development in Alabama counties. The research had three objectives. The first was to identify whether human capital investments have a causal relationship to economic growth, and to assess whether the causal relationship has increased over time. The second objective was to determine whether the return to human capital investment differs in rural counties versus non-rural counties. The third objective was to analyze differences in the county with the highest growth in economic development and the county with the lowest growth. The strength of the relationship was examined from 1950 to 2000, in decade intervals as well as over the 50-year span. The longitudinal aspect of the study allowed an examination of human capital’s changing role as an economic development tool. The geographic area examined was the 67 counties in the state of Alabama, and the population studied included the approximately 4,000,000 residents in Alabama in each time period. Data were derived from U.S. Census Bureau and Bureau of Economic Analysis (BEA) publications. The main methodology employed was multilevel regression modeling, MLM, to develop multilevel growth models. MLM analysis is an extension of traditional single- level regression models such as OLS and GLS and is commonly used on populations that have a hierarchical or nested structure (Dedrick et al., 2009). Multilevel models analyze the levels of these structures simultaneously. Multilevel models, also called mixed models, analyze levels simultaneously by handling random effects, which corrects for the

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problem of correlated error terms. Simple correlation, descriptive statistics, and OLS regression analysis were also used. The dependent variable was economic development as measured by job growth in each time period. The independent variable in each objective was the human capital investment of the population. The statistical models also included other variables that have shown in prior research to be related to economic development (Baldwin & Borelli, 2007; Siqueira, 2007; Seo, 2005; Li, 2005; Gibbs & Beaulieu, 2005). The additional variables included in the analysis were labor force participation, the population of each county, geographic mobility of the population, natural amenities, land area of the county, the rural status of the county, and highway access. The variables will be defined in detail in chapter 3. Theoretical Framework The purpose of this section is to discuss the theoretical framework that was used for the current study. The section will begin with a historical overview of the theoretical framework, its early development, and the major contributors to the theory. A discussion of current issues and perspectives will follow the overview. This section will conclude with a brief review of the relevant literature. A more comprehensive literature review will be provided in chapter 2. The human capital theoretical model developed by Barry Chiswick (1966) and Gary Becker (1967) provides an appropriate theoretical framework with which to study educational attainment (See Figure 1, p. 8). In the early 1960s, Becker and Chiswick began to relate human capital investments to income growth and other economic issues, such as poverty and unemployment. The two economists proposed that people make

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decisions about their education and training by comparing the benefits and costs (Becker, 1992). The benefits of investing in human capital include monetary gains, such as better earnings and occupations, along with non-monetary gains, such as improved health, personal fulfillment and appreciation for culture. The costs of investing in human capital include the income that individuals forego while they spend time investing in their education.

Figure 1. Human capital model (Lehrer, 2004). A main tenet of human capital theory is that the optimal level of educational attainment occurs at the point where the demand for funds to invest in education intersects the supply of such funds (Krugman & Wells, 2009). The demand curve represents the marginal rate of return derived from each additional dollar spent on education. The supply curve demonstrates the marginal interest rate on funds borrowed to invest in education. Individuals invest in their education and training up until the point where the benefit derived from increases in education no longer exceeds the cost of the education. Marginal rate of return, marginal costs of funds (r) Dollars invested in education (E)

S D E 0 r 0

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According to proponents of human capital theory, individuals will invest in more education only if they believe that the benefits of doing so outweigh the costs. A substantial amount of data lends support to the theory at the individual level (Lehrer, 2004; Becker, 1992; Arellano & Fullerton, 2005; Baldwin & Borrelli, 2008). In other words, people who anticipate a relatively high future payoff of their education invest a relatively high amount in their education. The behavior is rational, given that the body of research on the subject supports the fact that better educated people do have better economic outcomes than those with lower levels of education. The origin of the concept of human capital dates back to the late 18 th century, when British economist and philosopher, Adam Smith, published his landmark Wealth of Nations (Siqueira, 2007). In his publication Smith suggested that humans are productive capital and, as such, are an important input to economic growth and development. Similar to the way that physical capital contributes to the productivity of a business, humans could also improve their productivity through education and training. And just as a business owner considers the long-term benefits and costs of a machine, business owners and workers alike should consider the long-term benefits and costs of education and training (McFadyen, 2006). However, the concept of humans as capital was not widely embraced until more than a century later. In 1891, Irving Fisher earned the first Ph.D. in Economics from Yale University and was the first economist to distinguish between real and nominal interest rates (Krugman & Wells, 2009). Among other accomplishments, Fisher developed his theory of capital, investment, and interest rates, which addressed how individuals and organizations invest in different types of capital based on their expected

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rates of return. His theory, which is still widely accepted today, includes human capital as an investment in future earnings potential (McFadyen, 2005). The University of Chicago, which John D. Rockefeller established in 1892, also espoused the theory of human productivity as capital. However, the concept of human capital did not become widely accepted right away. In fact, the notion that people were capital, like machines, was deemed offensive by some academics and practitioners (Krugman & Wells, 2009). A worker’s skills and productivity were considered to be a given, and therefore, not able to be improved. British economist Alfred Marshall and British philosopher John Stuart Mills led the backlash against human capital theory. They believed that humans should be dignified by being considered in a separate category than other types of productive capital and that human beings themselves were not marketable (Krugman & Wells). Human capital became widely accepted in the 1960s, when more University of Chicago researchers, such as Nobel laureates Milton Friedman and Theodore Shultz, analyzed and strengthened the concept of human capital. The subject experienced a substantial resurgence (McFadyen, 2005). Schultz and Friedman, among others, began studying the relationship between human capital and economic growth (Becker, 1992). Schultz’s main theoretical development was his expansion of the meaning of investment to include all activity that improved a worker’s skills and productivity. Schultz included direct costs of education, improvements in health, and migration, as well as indirect costs such as foregone earnings and lost leisure time while obtaining the human capital (Siqueira, 2007). Barry Chiswick and Gary Becker (1966) further

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expanded on the idea by including an important cost-benefit analysis into the discussion of human capital accumulation (Becker, 1964). Chiswick and Becker proposed that people make decisions about investment in their training, healthcare, and education by weighing the benefits and costs. They will invest in the human capital accumulation as long as the marginal benefits of doing so outweigh the costs (Becker, 1964). In addition to the benefit of increased future income, benefits analyzed by Chiswick and Becker included improvements in living conditions, emotional and physical well-being, and increased leisure pursuits. The researchers differed from traditional economic analysis by including social and cultural issues in their studies. However, despite well-published and widely-acknowledged benefits of education, individuals in Alabama are not investing in their education at the same levels as individuals in other states. The job growth is Alabama is also lower than that in other states. The study analyzed this phenomenon within the human capital theory framework and added to that framework by expanding the analysis to aggregate outcomes at the county level. Every study in the literature review cited some form of human capital as the main determinant of income and poverty levels, economic growth and development, and general well-being of individuals, communities, and national economies alike. Although human capital includes other investments in earning potential, such as training and emotional well-being, information about these variables is difficult to measure (Becker, 1992). Therefore, researchers commonly use investments in education as a proxy for investments in human capital. Measured this way, human capital has consistently been

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shown to be an important determinant of economic status (Becker, 1992; Hill, 1998; Pandey et al., 2006; Siqueira, 2007). Smith (2006), Song (2005), and Siqueira (2007) examined economic outcomes of immigrant populations and their relationships to the immigrants’ human capital accumulation. The results of their studies suggested that a person’s human capital, regardless of ethnic background, is the strongest indication of a person’s earning potential. Therefore, according to Siqueira (2007), any study of economic well-being should not ignore human capital. Research conducted by Hill (1998) and Levernier (2003) also supports the assertion. Researchers have also examined other variables that affect income (Casey & Christ, 2005; Goetz & Rupasingha, 2005; McGrath, Swisher, Elder, & Conger, 2001). These variables included classroom size, population, single-parent families, education of one’s parents, interstate access, percentage of the population that is of working age, parents who are involved in children’s schools, health and nutrition, labor force participation rate, and percentage of county residents who recently immigrated to the United States (Becker, 1992; Blank, 2000; Gibbs, 2005; Gibbs & Beaulieu, 2005; Hill, 1998; Levernier, 2003). However, the majority of the research points to a handful of variables as the main components of a county’s economic status. Human capital is one of these variables (Gibbs & Beaulieu, 2005; Seo, 2005). Many researchers have examined economic development in Southern communities. Levernier (2003) suggested that the historically low educational attainment, combined with low labor force participation, deters job growth and economic development. Other researchers such as Gibbs (2005), Gibbs and Beaulieu (2005), and

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Hill (1998), have suggested that the ability to attract new business to any geographic area depends largely on the educational level of that area’s citizens. Therefore, any economic development endeavor must include policies that improve the community’s educational attainment. Hoogstra, Van Dijk, & Florax (2005) undertook a large-scale meta-analysis to examine whether companies move to areas with an adequate workforce or whether workers move to where jobs already are. The purpose of their research was to determine which comes first, the jobs or the workforce. Applying a comprehensive meta-analysis of 37 studies using the Carlino-Mills two equation system, the researchers examined 308 regression results of previous studies. The majority of the results indicated that jobs move to where the educated workforce is already located (Hoogstra, Van Dijk, & Florax, 2005). Their analysis has implications for community leaders seeking to attract employers to their areas. Many researchers have evaluated the effect that family structure and maternal education have on economic well-being of both individuals and communities (Casey & Christ, 2003; Goetz & Rupashingha, 2005; Jones, Snelgrove, & Muckosy, 2006; Lehrer, 2004; Pandey et al., 2006). The human capital accumulation of a child has been shown to be highly correlated to both growing up in a two-parent family and to the human capital attainment of parents, especially mothers. Blank (2000), Pandey, Zhan, & Kim (2006), and Seo (2005) all examined the relationship between female-headed households and various measures of economic well-being. Families headed by a single female are more than four times as likely to live in poverty as families with two parents present (Pandey et al., 2006).

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In fact, many studies of economic outcomes of children of both married and unmarried women suggested that the mother’s human capital attainment was the single most important determinant of the economic well-being of her children (Hill, 1998; Gibbs & Beaulieu, 2005; McGrath et al., 2001; Seo, 2003). Women without a college degree are nine times more likely to live in poverty than women who graduate from college (Pandey et al., 2006). The finding is relevant to the current research in Alabama, since over 20% of families in Alabama are headed by single females, a percentage that is 13% higher than the rest of the country (U.S. Census Bureau, 2007). Jones, Snelgrove, & Muckosy (2006) examined how investments in human capital among women affect a community's economic growth as well as the women’s economic status. They demonstrated that with a relatively low investment of resources, women become able to contribute to the growth of the economy (Jones et al., 2006). Lehrer (2004) included religious upbringing as an explanatory variable for a woman’s human capital investment. Lehrer suggested that women from highly religious families accumulate more human capital than their non-religious counterparts, which allows them to achieve a higher economic status (Lehrer, 2004). The benefits of investments of human capital have been consistently shown to accrue to both individuals and to societies in the form of increased income, cultural awareness, improved health, and other benefits. The statistical link between increases in human capital and increases in income is very strong and well-documented (Arellano & Fullerton, 2005; Becker, 1992; Betts, 2001; Gibbs, 2005; Li, 2005; and Siqueira, 2007). Most of the prior quantitative research has focused on link between human capital and

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income, but few studies have examined the link between human capital and economic growth at the county level. Current issues in the human capital field of research include how to best allocate elementary and secondary education funds in order to reduce the student drop-out rate and increase overall educational attainment. Due to the empirical evidence indicating the importance of investment in human capital, the question of how to ensure that more people have access to quality education becomes a pressing one. Researchers and policymakers alike are concerned over the widening income gap between the high- income earners and the low-income earners (Gibbs, 2005; Levernier, 2004; Waldorf, 2009). The main difference between the two groups is the level of human capital that each group invests in. The income earning potential of the highly educated group continues to grow, while the earning potential of the uneducated remains virtually stagnate (Jones et al., 2006; Pandey et al., 2006). The income division will not improve without improving the human capital levels of the lowest earners. Debate continues over how best to do just that. Some policy makers have suggested increasing technology in the classrooms, increasing teacher credentials and teacher pay, increasing the number of schools days required per year, decreasing pupil- teacher ratios, or requiring more years of schooling (Baldwin & Borelli, 2008). Increasing overall education spending has not resulted in helping students stay in school, so more research into the subject is necessary. Analyzing ways to more efficiently allocate education funding would improve the field of research.

Full document contains 247 pages
Abstract: Alabama has been one of the poorest states since the U.S. Census began gathering data in 1790. The purpose of the quantitative study was to evaluate human capital as an economic development tool in Alabama. The study evaluated relationships between human capital and economic development from 1950-2000 within the context of human capital theory. The research questions addressed the relationship between human capital and economic development at the county level and were analyzed using cross-sectional longitudinal analyses. Multilevel regressions were used to estimate the relationships at the p < .05 level. Government records provided the data. Results indicated a significant causal relationship from investment in human capital to economic development. Every one percentage point increase in human capital investment caused an increase of 13,440 jobs per county. Non-rural counties added 34,786 jobs for every one percentage point increase in human capital, but rural counties did not gain a significant return on human capital investment. The extremely low populations of the rural counties, coupled with outmigration of educated workers, were likely causes of this outcome. Results demonstrated that the gap between economic development in counties that invest in human capital and those who do not has been widening since 1950, and that human capital was the most significant variable in determining economic development. Increasingly strong correlations between human capital and economic development were found in each decade and were significant at the p < .01 level. The results help policy makers in economic development efforts by quantifying returns to human capital investments. Policy recommendations include increasing human capital investment, promoting stable in-tact families, and attracting educated workers back to rural counties once they finish their education. Recommendations for future research include how family environments contribute to a county's business, labor, and economic landscapes, and how human capital and family social capital interact to improve economic outcomes.