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<p> The human capital accumulation is an important production factor to promote the economic growth of the countries. In this thesis the role of the universities of Puerto Rico in the creation of human capital stock at the regional level is studied, based on a panel data analysis of 15 areas of labor market during the census years 1960 to 2010. The stock of human capital refers to the knowledge generated by the universities through the production of degrees and the R&amp;D activities. Three variables as proxies were designed to measure the rate of accumulation of human capital (HCAP), the rate of new professional degrees (NGRAD) and research and development activities (DRES). The results obtained showed that NGRAD had a positive but very small impact on the rate of human capital stock, while that the R&amp;D did not show any impact. The significant determinants to the growth of HCAP in the regional labor market were the real income per capita and federal tax exemption under Section 936. It's presumed that this incentive promoted by foreign investments generated knowledge spillovers and induced positive externalities for innovation and local economic development. To increase the productivity of the regions it is suggested that universities must be more proactive in the strategic and economic development of the regions in which they are located. This implies that the universities need to reassess their roles so as to actively contribute to the formulation of regional plans of action, promote entrepreneurship activities for professionals who are not being absorbed by the economy, and promote collaboration and knowledge spillovers with regional businesses.</p>

<p> Freshmen at baccalaureate-granting institutions cite being able to secure a more attractive job and earn a higher income among the most important factors that influenced their decision to pursue a college or university education. Indeed, higher education has been cast as a reliable on-ramp to the American Dream, a mechanism for reducing income inequality, and a key to enhancing economic competitiveness and growth of states and the nation. These benefits have been emphasized by a chorus of individuals calling for dramatically increasing college degree attainment levels in the United States (U.S.). Yet to what extent and how consistently has higher education delivered these trumpeted outcomes for individuals, states, and the nation? </p><p> U.S. Census American Community Survey microdata and typical education requirements of occupations published by the U.S. Bureau of Labor Statistics were utilized to quantitatively analyze employment outcomes of college graduates. A special focus was placed on the incidence of malemployment (the phenomenon of college graduates working in occupations that do not require a college degree), relationships between undergraduate degree fields and labor market outcomes, and variations across states in the employment outcomes of college graduates. </p><p> The benefits of higher education for individuals and states were found to be highly uneven. Analyses revealed that approximately 31% of adults in the labor force with a bachelor&rsquo;s degree or higher are malemployed, a rate that varies by undergraduate degree field, educational attainment, race/ethnicity, and age. College earnings premiums generally are far lower for malemployed individuals than for graduates who have secured college-level occupations, and they vary dramatically by undergraduate degree field and state. </p><p> Myths about higher education and the labor market were dispelled, such as the notion that malemployment affects only recent graduates and that there generally is an insufficient supply of STEM graduates. The principal propositions of the national attainment agenda were evaluated in light of the study&rsquo;s findings, and a new framework for that agenda was offered, including a greater focus on the traded sector of the economy, a shift from state leadership to a state/federal partnership, and a suggestion for attainment agenda proponents to embrace a learning quality agenda.</p>

This dissertation consists of three essays in Behavioral Labor Economics. The first two chapters contribute to the understanding of non-standard preferences of individuals in the workplace, and the third studies how cultural values affect firm behavior. The first chapter studies the incentive effects of top-down favoritism in employee promotions on workers and its organization-wide productivity consequences, and provides evidence on social preferences and fairness concerns among co-workers. Using data from public high schools in four Chinese cities, I first show that teachers with hometown or college ties to the school principal are twice as likely to be promoted, after controlling for characteristics on their application profiles and their value-added in teaching. I then use the results from a survey in which I asked teachers to select anonymous peers to promote from a pool of applicants applying for promotion to infer each teacher’s revealed fairness views regarding promotion qualifications. Contrasting these with actual past promotions in turn allows me to measure if and when a teacher might have observed unfair promotions in her own school in the past. Exposure to unfair promotions adversely affects non-applicant teachers’ output, lowering their value-added and raising the probability that high-value-added teachers quit. The value-added effect appears to be driven primarily by teachers’ social preferences for peer workers and the consequent erosion of their morale when peers suffer unfair treatment, while the quitting effect comes mainly from non-favored prospective applicants’ career concerns as they learn about the principal’s bias and leave due to poor promotion prospects. These adverse spillover incentive effects lead to a substantial reduction in school-wide output, which is only slightly mitigated by increased productivity among favored teachers. Finally, a transparency reform that required principals to disclose to their peers the profiles of teachers that apply for promotion reduced the principals’ bias and improved the overall productivity of schools. The second chapter documents daily targeting behavior in workers’ labor supply decisions. Using a novel dataset on the daily production of a group of piece-rate manufacturing workers combined with their quasi-random daily income shocks from lunch break card game gambling, I show that the workers’ afternoon labor supply responds negatively to instantaneously-paid quasi-random gambling income, although wages are paid monthly. The workers’ labor supply decisions were consistent with daily mental accounting and reference dependence where the target was set on the sum of the face - valued daily (receivable) labor and (paid) unearned income, as opposed to the neoclassical model of inter-temporal labor supply. Estimation of two structural models of daily labor supply yields a coefficient of loss aversion parameter of 1.8 to 2.0, significantly different from the neoclassical value of 1; and individual specific loss aversion structural estimates correlate positively with survey measures. Using estimated preference parameters, I back out the implied total wage elasticity of daily labor supply as well as a sizable negative reference-dependent component of it. This study overcomes the common identification issues in the daily labor supply literature by exploiting high-frequency, actively taken-up and unanticipated income shifters that are independent of other labor supply and demand confounders. In the third chapter, we show that many employers anchor their wages at establishments outside of the home region to headquarter levels, and begin to study the consequences. Our analysis makes use of an unusual 2005-2015 establishment-year level dataset of average wages by narrowly-defined occupation. The dataset covers 1,800 large employers that span many different sectors and each operate in a subset of 170 observed capital city locations. We show that, across the occupational skill range—including for low-skill support staff— the average wage multinationals pay domestic workers in a given occupation at foreign establishments is robustly and remarkably highly correlated with the average wage they pay workers in the same occupation in the home country. We then instrument for headquarter wage levels with changes in home country minimum wage laws and show that externally imposed wage increases at home causally raise wages abroad. The relationships we establish between headquarters’ and their foreign establishments’ wage levels and wage changes are both driven by employers from inequality-averse societies. Occupations are more (less) likely to be removed from, and less (more) likely to be added to the foreign establishments (headquarters) of such employers after a (minimum wage-induced) wage increase originating at the headquarter. Our results point towards the existence of “wage cultures” that influence how production is organized across space.

This dissertation is comprised of three essays on the economics of high school-to-college transition programs and teacher effectiveness. The first essay studies the two largest credit-based transition programs in the United States: Advanced Placement and Dual Enrollment. While these programs are distinct, both of them allow students to earn college credits while in high school. Using student-level statewide data from Florida, I examine the relative power of these two programs for predicting students' college access and success. In the second essay, I gauge the causal effect of one of the programs, Dual Enrollment, exploiting Florida's eligibility requirements for participation. I conduct two regression discontinuity analyses. The first analysis evaluates the effect of dual enrollment using a general grade point average requirement for participation in any course. The second analysis measures the effect of one particular challenging and popular dual enrollment course, college algebra, using an eligibility criterion that is specific to that course. While the standard regression-discontinuity methods are appropriate for the first analysis, the participation criterion for college algebra is used not only for dual enrollment but also for college students. I therefore propose an extension of standard regression-discontinuity methods to account for sequential treatments. My third essay, coauthored with Jonah Rockoff, considers ways in which policymakers can improve teacher accountability systems. Using data from New York City public schools, we study the relative predictive power of value-added performance data and subjective evaluations (made by mentors or hiring committees) on teachers' future performance as measured by students' achievement gains.

After the fall of the Soviet Union and its transition in the 1990s towards a democratic form of government, Mongolia was forced to embark upon a complete series of reforms within society, including within its education sector. Mongolia's higher education sector was significantly affected by this change. Private higher education institutions mushroomed and the number of university graduates increased significantly. At the same time, the rapid expansion of the sector had serious implications for the quality of education in the country. The declining quality of higher education in Mongolia has now become a major political issue and has caused much heated public debate. Using a mixed-methods approach, this study aims at understanding the gaps between Mongolia's educational needs and the policies the Mongolian government have implemented in response to the expansion of higher education. By analyzing the socio-political background of the expansion of higher education in Mongolia, it is hoped that some light may be shed on (1) the existence and magnitude of overeducation and its impact on individual earnings, (2) perceptions of overeducation among key stakeholders (e.g., government officials, employers and university deans) and (3) related policy interventions in Mongolia. It is also hoped that this study contributes to deepen understanding of overeducation from a policy borrowing/education transfer perspective. Quantitative analyses were conducted using datasets from the Living Standards Measurement Survey (2002/2003) and the Household Socio-Economic Survey (2007/2007). Qualitative analyses were conducted using information collected through 14 individual interviews with key stakeholders (senior officials, university personnel, private employers and staff from international organizations) as well as from key policy and project documents from the Government and development agencies.

Paper 1: Missing at Random? An Analysis of the Effect of Sample Selection on Intergenerational Earnings Elasticities by Race Utilizing the Panel Study of Income Dynamics, I assess the effect of sample selection bias on estimates of intergenerational earnings elasticities for white and black father-son pairs, regressing log child earnings on log parent earnings. Estimating four increasingly less selected models, I assess the robustness of estimates to alternative methods of handling sons who are missing data due to periods of unemployment or part-time employment. The results indicate that the assumption of exogenous selection into full-time employment significantly biases the estimates for blacks, although it does not have a large impact on estimates for whites. As a consequence, selection bias will understate the magnitude of the black-white mobility gap. The results also indicate that two methods substantially mitigate this selection bias: having a long panel, or imputing data in a short panel. Paper 2: Measuring the Black-White Mobility Gap: A Comparison of Datasets and Methods Chapter 3 utilizes both the National Longitudinal Survey of Youth (NLSY) and the Panel Study of Income Dynamics (PSID) to analyze the magnitude and nature of black-white gaps in intergenerational earnings and income mobility in the United States. This chapter finds that relying on different datasets or measures will lead to different conclusions about the relative magnitudes of black versus white elasticities and correlations, but using directional mobility matrices consistently reveals a sizable mobility gap between black and white families, with low-income black families disproportionately trapped at the bottom of the income distribution and more advantaged black children more likely to lose that advantage in adulthood than similarly situated white children. I find the family income analyses to be most consistent and estimate the upward mobility gap as between 19.1 and 20.3 percentage points and the downward gap between -20.9 and -21.0. Additionally, I find that racial disparities are much greater among sons than daughters and that incarceration and being raised in a female-headed household have much larger impacts on the mobility prospects of blacks than whites. Paper 3: Can Parental Wealth Explain the Black-White Mobility Gap? Utilizing longitudinal data from the Panel Study of Income Dynamics (PSID), this chapter examines the relationship between parental wealth and intergenerational income mobility for black and white families. I find that total parental wealth promotes upward mobility for low-income white families, but does not protect against downward mobility for white families from the top half of the income distribution. Conversely, I find that total parental wealth does not assist low-income black families while home ownership may have negative associations with the likelihood of upward mobility for these families. However, for black families from the top half of the income distribution home equity is protective against downward mobility suggesting a heterogeneous relationship between home ownership and mobility for black families.

New-teacher induction programs are widely used as non-monetary interventions, with the reduction of teacher turnover being one of their purposes. During the last three decades, states have been active in legislation to mandate induction programs for new teachers in public schools. Motivated by the discrepancy of the estimated program effects on teacher turnover in the existing literature, this study attempts to examine whether analytical methods used to address the endogeneity of induction-program participation matter in explaining this inconsistency in the estimation of the effect of new-teacher induction programs and how mandatory induction legislation and/or policy are linked with new-teacher induction programs and teacher turnover. Specifically, three key research questions are examined, including what are the determinants of new teachers' turnover, whether new-teacher induction programs have effects on teacher turnover, and whether state induction legislation and/or local mentoring policy have effects on teacher turnover. Two main sources of data are employed, including multiple cycles of Schools and Staffing Survey and Teacher Follow-up Survey, the largest nationally representative sample surveys on teachers and their schools in the United States, as well as New York City Department of Education administrative data, the longitudinal data concerning public school new teachers and their job status in the largest public education system in the United States. In order to address the potential endogeneity problem that may be associated with the induction program participation, this study employs identification strategies such as propensity-score matching, instrumental variable, and difference-in-difference methods. Particularly, in estimation, the difference-in-differences strategy is incorporated with the instrumental variable method as well as nonlinear models. The current study finds that, after addressing the endogeneity problem, new-teacher induction programs hardly have any effects on reducing teacher turnover, which is different from what most previous studies have found. It is also implied that if a mandatory induction/mentoring law/policy does not encourage new teachers' participation in a comprehensive induction/mentoring program, it may not work in terms of reducing teachers' exit turnover at best. This study contributes in literature on new-teacher induction programs and teacher turnover in terms of analytical methods, generalizability of findings, understanding of induction legislation and policy, and proper research design considerations for future studies.

Industrial cluster literature has traditionally focused on work-place upgrading, clusters' ability to promote firm productivity, economic growth, and benefits that firm owners can or will give to workers. However, even in growing, productive clusters, such a work-place focus leaves out questions about how to situate the contribution of the firm and cluster in improving living standards in the wider socio-economic and spatial context of the region. By providing a systematic examination of the relationship between industrial clusters and poverty analyzed within a multidimensional frame, this dissertation attempts to close this bridge. It asks under what conditions firms in productive clusters pass on benefits to workers in ways that improve their living standards, even when they are not required by law to do so. Three hypotheses are put forward. First, firms in their own interest boost worker productivity by providing certain kinds of work-place benefits such as overall capability, proxied by various types of internal technological knowledge and skills. Second, firms choose not to give other place-based and work-based benefits like health or housing because social policies do not demand it and it has no direct benefit to the firm. Third, firms pass on these benefits because it costs little, and tend to deepen employee loyalty. The study analyses the case of the Otigba Information and Communications Technology cluster in Lagos, Nigeria and uses survey questionnaires, interviews, and archival research. Results confirm that clustering promotes not just firm-level productivity as literature on agglomeration economy highlights, but also raises workers' living standards compared to non-clustered firms in the same sector. Older employees, and those with prior experience in other firms report improvements in their living standards since working in their firms. Furthermore, firms in the cluster give a diverse number of non-income benefits such as housing, health insurance, feeding and transportation allowance, training, child care, funding for further education, pension and company products, based on the length of service in the firm, age of employee, and size of the firm. Additionally, while formal state-supported social protection institutions are largely absent, monetary and non-monetary benefits such as employment, provision of skills through apprenticeships, housing, transportation, and feeding allowance are channeled to employees through firms and informal institutions based on social and kinship ties. A high level of horizontal and collective cooperation based on professional lines has also emerged within the cluster in the absence of formal state institutions. The dissertation makes a theoretical contribution by bridging studies on industrial clusters with those on social protection policy instruments. The study gives greater evidence to the diversity of social protection available, as well as the opportunity for economic development planners to explore ways in which firm-driven social protection can be integrated into social policy.

Chapter 1, “The Impact of Trade Shocks on Local Labor Markets” estimates the effects of increased trade with China on Brazilian local labor markets using longitudinal individual data on the universe of Brazilian formal sector workers. First, I use reduced-form estimation strategies commonly found in the literature to compare my results to previous findings. I show that my results at the regional level mirror those found in prior studies based on cross-sectional data. I argue that these estimates are potentially biased as they do not take into account the flows of factors and goods between regions. I complement the reduced-form approach with a structural analysis based on the model by Caliendo et al. (2015) in order to endogenize such flows and to study welfare effects. I find that in the absence of the Chinese shock the Brazilian Commodities sector would have shrunk while Manufacturing and Services would have expanded. Relative to this baseline, the employment effect of increased trade with China at the national level was a slower reduction in the share of the Commodities sector and a slower growth in the Manufacturing subsectors that were relatively more exposed to Chinese import competition. My analysis suggests that while the average Brazilian worker benefitted from this shock, the welfare effects were very heterogeneous across sectors and across locations. I find that this heterogeneity is vastly underestimated if instead of using data at the level of metropolitan areas I use data aggregated by States and I explain why the choice of spatial units affects these results. Chapter 2, “Agglomeration: A Long-Run Panel Data Approach” studies the sources of agglomeration economies in cities. We begin by incorporating within and cross-industry spillovers into a dynamic spatial equilibrium model in order to obtain a panel data estimating equation. This gives us a framework for measuring a rich set of agglomeration forces while controlling for a variety of potentially confounding effects. We apply this estimation strategy to detailed new data describing the industry composition of 31 English cities from 1851-1911. Our results show that industries grew more rapidly in cities where they had more local suppliers or other occupationally-similar industries. We find no evidence of dynamic within-industry effects, i.e., industries generally did not grow more rapidly in cities in which they were already large. Once we control for these agglomeration forces, we find evidence of strong dynamic congestion forces related to city size. We also show how to construct estimates of the combined strength of the many agglomeration forces in our model. These results suggest a lower bound estimate of the strength of agglomeration forces equivalent to a city-size divergence rate of 1.6-2.3% per decade. Chapter 3, “Gravity estimation with unobserved bilateral flow data” adapts the methodology by Miscio & Soares (2016) to predict domestic trade flows by sector between Brazilian metropolitan areas. This methodology, initially developed to infer commuting flows from aggregate data on population by place of residence and by place of work, relies on moment conditions derived from a general gravity equation and it is consistent with a large class of trade models. I show that it can also be applied to infer domestic trade flows by sector. Before using the methodology on Brazilian data, where we only observe flows between States, I test it on US data from the Commodity Flow Survey, where we observe both flows between States and between finer spatial units similar to metropolitan areas. I argue that the predicted bilateral flows obtained from this methodology are highly correlated with actual flows. Alternative approaches found in the recent literature differ from the one presented here in that they require stronger assumptions and deliver weaker results. In particular, the other approaches only describe aggregate flows (i.e. summing across all sectors) and cannot be used to predict sectoral flows.