Lifecycle Working Group
The Lifecycle Working Group, organized by James Heckman, Steven Durlauf, and Jin Zhou, invites faculty, researchers and graduate students to present work that applies the comprehensive lifecycle approach to the study of human flourishing. The workshop takes place on Tuesdays at 1:30PM on Zoom. This interdisciplinary workshop is open to the campus research community.
This workshop is sponsored by the The Research Network On The Determinants Of Life Course Capabilities And Outcomes.
Working Group Schedule 2021-2022
January 25, 2022, 1:30pm, Zoom
February 1, 2022, 1:30pm, Zoom
February 8, 2022, 1:30pm, Zoom
What Accounts for the Racial Gap in Time Allocation and Intergenerational Transmission of Human Capital?
George-Levi Gayle, Washington University in St Louis
Abstract: This paper analyzes the sources of the racial difference in the intergenerational transmission of human capital by developing and estimating a dynastic model of parental time and monetary inputs in early childhood with endogenous fertility, home hours, labor supply, marriage, and divorce. It finds that the racial differences in the marriage matching patterns lead to racial differences in labor supply and home hours of couples. Although both the black-white labor market earnings and marriage market gaps are important sources of the black-white achievement gap, the assortative mating and divorce probabilities racial gaps accounts for a larger fraction of it.
February 15, 2022, 1:30pm, Zoom
February 22, 2022, 1:30pm, Zoom
The Nurture of Nature and the Nature of Nurture: How Genes and Investments Interact in the Formation of Skills
Victor Ronda Checchia, The University of Chicago
Abstract: It is widely recognised that genetics and family investments both matter for children’s development. However, the two are often treated as separate factors where the higher importance of one implies a lesser role of the other. In this paper, we challenge this view and show that genes and family resources are closely interrelated in the process of skill formation. We incorporate genetic endowments into a dynamic latent factor model, as in Cunha and Heckman (2008). The model allows us to identify different genetic mechanisms and control for measurement error in skills and investments. To identify the independent effect of a child’s genes, we explicitly control for parental genes. We exploit the fact that conditional on parental genes, variation in children’s genes is random. Using a longitudinal British data set, the Avon Longitudinal Study of Parents and Children (ALSPAC), we document the importance of three distinct genetic mechanisms: the direct effect of child genes on skills, the indirect effect of child genes via parental investments (nurture of nature), and the effect of parental genes on parental investments (nature of nurture). Using two counterfactual simulations, we argue that the existence of genetic effects is not at odds with the value of social policies in reducing inequality in skills. In fact, we show that the relative importance of genes depends on how parental (or public) investments are allocated across children. Thus, skill disparities due to genetic differences may be mitigated via social policy. Download the paper (.pdf)
March 1, 2022, 1:30pm, Zoom
Employer Accommodation and the Design of Social Insurance: Evidence from Return to Work after Workplace Disability
Noaki Aizawa, University of Wisconsin-Madison
Abstract: This paper studies the impact of firm accommodation decisions on labor market outcomes for individuals with workplace disabilities and assesses the implications for optimal social insurance against workplace disability. We leverage detailed administrative data from a unique workers’ compensation program in Oregon that provides wage subsidies to firms for workplace accommodation. Exploiting a policy change to the wage subsidy, we find that a five-percentage point decrease in the wage subsidy rate led to a 5.5 percentage point decrease in accommodation and corresponding effects on employment and earnings through eight quarters after injury. We then develop and estimate a frictional labor market model with work-related disability and firm accommodation in which worker turnover and imperfect experience rating can lead to under-accommodation and inefficient labor market outcomes after workplace disability. We use the quasi-experimental estimates to help identify key parameters of the model. Counterfactual analyses show that a wage subsidy of 40% maximizes overall worker welfare, with higher welfare gains for workers with low disutility of work during an injury in labor markets with inefficiently low accommodation rates. Download the paper (.pdf)
March 8, 2022, 1:30pm, Zoom
Demand and Welfare Analysis in Discrete Choice Models with Social Interactions
Debopam Bhattacharya, University of Cambridge
Abstract: Many real-life settings of individual choice involve social interactions, causing targeted policies to have spillover effects. This paper develops novel empirical tools for analyzing demand and welfare effects of policy interventions in binary choice settings with social interactions. Examples include subsidies for health product adoption and vouchers for attending a high-achieving school. We show that even with fully parametric specifications and unique equilibrium, choice data, that are sufficient for counterfactual demand prediction under interactions, are insufficient for welfare calculations. This is because distinct underlying mechanisms producing the same interaction coefficient can imply different welfare effects and deadweight-loss from a policy intervention. Standard index restrictions imply distribution-free bounds on welfare. We propose ways to identify and consistently estimate the structural parameters and welfare bounds allowing for unobserved group effects that are potentially correlated with observables and are possibly unbounded. We illustrate our results using experimental data on mosquito-net adoption in rural Kenya. Download the paper (.pdf)
January 18, 2022
Causality in the Time of Cholera: John Snow and the Process of Scientific Inquiry
Thomas S. Coleman, The University of Chicago
Abstract: John Snow in 1849 proposed the intestinal fecal-oral theory for cholera and provided substantial evidence supporting the theory and particularly the prediction that cholera was waterborne. Snow's analysis fits naturally within a Neyman-Rubin causal framework, and Snow is credited with two tools (randomization as an instrumental variable and difference-in-differences design) widely used in causal analysis today. Nonetheless, although water was widely accepted in the 1850s as a causal factor, Snow's theory was not. This seeming puzzle cannot be resolved within the Neyman-Rubin framework and requires a broader conception of scientific inquiry, as advocated by C. S. Peirce (and more recently Heckman and Singer 2017). The methodology of scientific research programmes of Lakatos (1980) provides a concrete framework for such a broader conception of scientific inquiry, and for understanding the competition among theories in the 1850s. A “rational reconstruction” of the case of cholera illustrates the logic of inquiry: alternative theories (rationally) protected against refutation by incorporating water as a causal factor, but Snow's theory was superior (progressive in Lakatos's terms) – producing new predictions corroborated by new facts. On a practical level, Snow's research provides an exemplar and template for falsification and corroboration within the process of causal inquiry. Download the paper (.pdf)
January 11, 2022
Inequality, Information, Modeling and Inference
Amos Golan, American University
Abstract: Modeling income distribution and economic inequality should be based on primitive principles of economic and social inequality. Info-metrics – the science of modeling, reasoning, and drawing inferences under conditions of noisy and insufficient information – provides a consistent, logical and efficient framework for constructing models and theories based on fundamental principles with minimal assumptions. It builds on Bernoulli’s and Laplace’s principle of insufficient reason and on Jaynes’s formalism of the maximum entropy formalism. Inequality measures emerge naturally in models constructed via the info-metric framework. They are directly linked to the decision function used in the optimization. As a result, once a model is constructed, evaluating the impact of policies and other exogenous effects on the distribution of inequality or any other welfare measure is easily done by studying the Lagrange multipliers that emerge in the optimization. These multipliers, or “shadow prices,” are associated with the information (and data) used in the optimization. They capture the impact of each piece of information on economic inequality. They also provide a way for studying causal inference, such as external forces that may impact mobility and migrations.
My talk is based on my recent book Foundations of Info-Metrics: Modeling, Inference, and Imperfect Information, http://info-metrics.org/ in which I develop and examine the theoretical underpinning of info-metrics and provide extensive interdisciplinary applications. In this talk I will discuss the basic info-metrics framework via a nonmathematical description of the theoretical framework, and then I will present a number of artificial and real-world examples of using that framework for modeling and inference, as well as modeling of inequality within that framework.
January 4, 2022
The Returns to College(s): Relative Value-Added and Match Effects in Higher Education
Jack Mountjoy, The University of Chicago
Abstract: Students who attend different colleges in the U.S. end up with vastly different economic outcomes. We study the role of relative value-added across colleges within student choice sets in producing these outcome disparities. Linking administrative high school records, college applications, admissions decisions, enrollment spells, degree completions, and quarterly earnings spanning the Texas population, we identify relative college value-added by comparing the outcomes of students who apply to and are admitted by the same set of institutions, as this approach strikingly balances observable student potential across college treatments and renders our extensive set of covariates irrelevant as controls. Methodologically, we develop a framework for identifying and interpreting value-added under varying assumptions about match effects and sorting gains, generalizing the constant treatment effects assumption typically employed in the value-added literature. Empirically, we estimate a relatively tight, though non-degenerate, distribution of relative value-added across the wide diversity of Texas public universities. Selectivity poorly predicts value-added within student choice sets: a fleeting selectivity earnings premium fades to zero after a few years in the labor market, and more selective colleges tend to have lower value-added on STEM degree completion. Non-peer college inputs like instructional spending more strongly predict value-added, especially conditional on selectivity. Educational impacts predict labor market impacts: colleges with larger earnings value-added also tend to be colleges that boost persistence, BA completion, and STEM degrees along the way. Finally, we probe the potential for (mis)match effects by allowing each college’s relative value-added to vary flexibly by student characteristics. At first glance, Black students appear to face small negative returns to choosing more selective colleges, but this pattern of modest “mismatch” is entirely driven by the availability of two large historically Black universities with low selectivity but above-average value-added. Across the non-HBCUs, Black students face similar returns to selectivity, and indistinguishable value-added schedules more generally, compared to their peers from other backgrounds. Download the paper (.pdf)
December 7, 2021
Cognitive Endurance as Human Capital
Christina Brown, The University of Chicago
Abstract: Schooling may build human capital not only by teaching academic skills, but by expanding the capacity for cognition itself. We explore this hypothesis with a focus on cognitive endurance: the ability to sustain effortful mental activity over a continuous stretch of time. As motivation, we document that globally and in the US, the poor exhibit cognitive fatigue more quickly than the rich across a variety of field settings; they also attend schools that offer fewer opportunities to practice thinking for continuous stretches. Using a field experiment with 1,600 Indian primary school students, we randomly increase the amount of time students spend in sustained cognitive activity during the school day—using either math problems (mimicking good schooling) or non academic games (providing a pure test of our mechanism). Each approach markedly improves cognitive endurance: students show 22% less decline in performance over time when engaged in intellectual activities—listening comprehension, academic problems, or IQ tests. They also exhibit increased attentiveness in the classroom and score higher on psychology measures of sustained attention. Moreover, each treatment improves students’ school performance by 0.09 standard deviations. This indicates that the experience of effortful thinking itself—even when devoid of any subject content—increases the ability to accumulate traditional human capital. Finally, we complement these results with quasi-experimental variation indicating that an additional year of schooling improves cognitive endurance, but only in higher quality schools. Our findings suggest that schooling disparities may further disadvantage poor children by hampering the development of a core mental capacity. Download the paper (.pdf)
November 23, 2021
Sequential choices, option values, and the returns to education
Philipp Eisenhauer, University of Bonn
Abstract: Drop out, re-enrollment, and track switching are common phenomena, highlighting the uncertainty associated with human capital investments. Using Norwegian administrative data with life-cycle earnings and detailed education histories, we set up a dynamic structural model of schooling decisions that captures the rich patterns of schooling choices for individuals. We distinguish ex-ante and ex-post returns to schooling, estimate the contribution of option values to overall returns and document substantial heterogeneity in returns associated with academic and vocational tracks across individuals with different abilities. The model is validated against variation in educational choices induced by a compulsory schooling reform. Mechanisms explaining the patterns of interruptions in educational careers by ability and inframarginal responses to schooling reforms are discussed. Our results indicate that option value of schooling, together with re-enrollment opportunities, are crucial to understanding these responses. Finally, we contrast our findings to standard estimates of returns to schooling.
November 16, 2021, 1:30pm - 3:00pm, Zoom,
What Determines the Success of Housing Mobility Programs?
Dionissi Aliprantis, Federal Reserve Bank of Cleveland
Abstract: This paper studies how design features influence the success of Housing Mobility Programs (HMPs) in reducing racial segregation. Targeting neighborhoods based on previous residents' outcomes does not allow for targeting race-specific outcomes, generates uncertainty when targeting income-specific outcomes, and generates bias in ranking neighborhoods' effects. Moreover, targeting opportunity bargains based on previous residents' outcomes selects tracts with large disagreements in current and previous residents' outcomes, with such disagreements predicted by sorting since 1990. HMP success is aided by the ability to port vouchers across jurisdictions, access to cars, and relaxing supply constraints, perhaps by targeting lower-ranked neighborhoods. Download the paper (.pdf)
November 9, 2021
Tasks, Automation, and the Rise in U.S. Wage Inequality
Daron Acemoglu, MIT
Abstract: We document that between 50% and 70% of changes in the US wage structure over the last four decades are accounted for by relative wage declines of worker groups specialized in routine tasks in industries experiencing rapid automation. We develop a conceptual framework where tasks across industries are allocated to different types of labor and capital. Automation technologies expand the set of tasks performed by capital, displacing certain worker groups from jobs for which they have comparative advantage. This framework yields a simple equation linking wage changes of a demographic group to the task displacement it experiences. We report robust evidence in favor of this relationship and show that regression models incorporating task displacement explain much of the changes in education wage differentials between 1980 and 2016. The negative relationship between wage changes and task displacement is unaffected when we control for changes in market power, deunionization, and other forms of capital deepening and technology unrelated to automation. We also propose a methodology for evaluating the full general equilibrium effects of automation, which incorporate induced changes in industry composition and ripple effects due to task reallocation across different groups. Our quantitative evaluation explains how major changes in wage inequality can go hand-in-hand with modest productivity gains. Download the paper (.pdf)
November 2, 2021
A Task-Based Theory of Occupations with Multidimensional Heterogeneity
Sergio Ocampo, Western University in London, Ontario
Abstract: I develop an assignment model of occupations with multidimensional heterogeneity in production tasks and worker skills. Tasks are distributed continuously in the skill space, whereas workers have a discrete distribution with a finite number of types. Occupations arise endogenously as bundles of tasks optimally assigned to a type of worker. The model allows us to study how occupations evolve—e.g., changes in their boundaries, wages, and employment—in response to changes in the economic environment, making it useful for analyzing the implications of automation, skill-biased technical change, offshoring, and skill upgrading by workers, among others. I characterize how the wages, the marginal product of workers, the substitutability between worker types, and the labor share depend on the assignment. In particular, I show that these properties depend on the productivity of workers in tasks along the boundaries of their occupations. I introduce automation as a choice of the optimal size and location of a mass of identical robots in the task space. Automation displaces workers by replacing them in the performance of tasks. This generates a cascading effect on other workers as the boundaries of occupations are redrawn. Download the paper (.pdf)
October 26, 2021
Barbara Biasi, Yale University
Abstract: This paper examines the diffusion of frontier knowledge through higher education courses. Using the text of 1.7 million college and university syllabi and 20 million articles published in top scientific journals since 1975, we construct a new measure: the “education-innovation gap,” defined as the ratio of textual similarities between each syllabus and (i) articles published 15 years before and (i) articles published 1 to 3 years before. We use this measure to document four findings. First, the gap varies substantially both across and within schools, with instructors accounting for 40 to 50 percent of the variation. Second, the gap is lower in schools that are more selective and serve fewer disadvantaged and minority students. Third, the gap decreases after the instructor of a course changes, and it is lower for courses taught by research-active faculty. Fourth, the gap is correlated with students’ graduation rates and incomes after graduation. These findings are robust to the use of alternative measures of course novelty. Download the paper (.pdf)
October 19, 2021
How Automation that Substitutes for Labor Affects Production Networks, Growth, and Income Inequality
Zafer Kanik, University of Glasgow
Abstract: We study how automation affects wages and productivity in a society’s supply network. A standard production network approach, which ignores the substitutability of inputs, focuses on how technological advances affect the production level but ignores their effects on production processes, employment and wages. In a tractable model, we characterize the propagation of technological advances through the production network, and show that it consists of two parts: standard input-output effect and substitution effect. In a networked economy, the substitution effect (that we call “automation-effect”) explains the input-output effect of automation on productivity and wages, where automation frees up labor which can be used throughout the rest of the economy. Wage adjustments lead automation to occur gradually. As automation (gradually) displaces more labor, the substitution effect rises, network centralities of producers of automation and their direct/indirect suppliers increase, and the production network becomes denser. Moreover, the differences in the substitution effects of technological advances shed light into how “seemingly similar” forms of automation have different macroeconomic impacts depending on the employment and supply chain characteristics that they interact with.
October 12, 2021
Partial Identification in Nonseparable Binary Response Models with Endogenous Regressors
Jiaying Gu, The University of Toronto
Abstract: This paper considers (partial) identification of a variety of counterfactual parameters in binary response models with possibly endogenous regressors. Our framework allows for nonseparable index functions with multi-dimensional latent variables, and does not require parametric distributional assumptions. We leverage results on hyperplane arrangements and cell enumeration from the literature on computational geometry in order to provide a tractable means of computing the identified set.We demonstrate how various functional form, independence, and monotonicity assumptions can be imposed as constraints in our optimization procedure to tighten the identified set, and we show how these assumptions can be assigned meaningful interpretations in terms of restrictions on latent response types. Finally, we apply our method to study the effects of health insurance on the decision to seek medical treatment. Download the paper (.pdf)
October 5, 2021
Market Power and Wage Inequality
Jan Eeckhout, Barcelona School of Economics
Abstract: We investigate how market power affects wage inequality. Market power is driven by the market structure in the goods and the labor market as well as in the distribution of firm-specific technology. We ask how these contribute to the rise in the Skill Premium, the premium of the average college wage relative over the average non-college wage and within and between-firm inequality. We estimate the firm-specific technology as well as the market structure and find that the increase in market power contributes thirteen percent to the rise in the skill premium. We also find that it explains approximately half of the rise in between-firm wage inequality in the US. Market structure also accounts for the rise in the markup, as well as the decline in equilibrium wages and welfare.
September 28, 2021
A Unified Empirical Framework to Study Segregation
Gregorio Caetano, University of Georgia
Abstract: We study the determinants of race and income segregation in the San Francisco Bay area from 1990 to 2004. Our framework incorporates the endogenous feedback loop at the core of the seminal Schelling (1969) model of segregation into a dynamic model of neighborhood choice, thus allowing for data to be observed in transition toward a steady state. We assess the relative importance of a variety of mechanisms that generate segregation – endogenous sorting on the basis of the socioeconomic composition of neighbors, sorting on the basis of other neighborhood amenities, differential responses to prices – and the frictions that mediate these mechanisms – moving costs and incomplete information. Identification of households’ endogenous responses to the socioeconomic compositions of neighbors is facilitated by novel instrumental variables that exploit the logic of a dynamic choice model with frictions. Sorting based on unobserved neighborhood amenities is the most important factor generating segregation followed distantly by endogenous sorting on the basis of the socioeconomic composition of neighbors. Frictions, primarily moving costs, play a central role in keeping segregation in check as they disproportionately mitigate endogenous sorting.
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Working Group Schedule 2020-2021
June 8, 2021
Measuring systemic discrimination among large US employers
Patrick Kline, University of California, Berkeley
Abstract: We study the results of a massive nationwide correspondence experiment sending more than 83,000 fictitious applications with randomly generated characteristics to geographically dispersed jobs posted by 108 of the largest U.S. employers. Distinctively Black names reduce the probability of an employer callback by 2.1 percentage points relative to distinctively white names. The magnitude of this racial gap in contact rates differs substantially across firms, exhibiting a between-company standard deviation of 1.8 percentage points. Despite an insignificant average gap in contact rates between male and female applicants, we find a between company standard deviation in gender contact gaps of 2.7 percentage points, implying that some firms favor male applicants while others favor women. Company-specific contact gaps are temporally and spatially persistent and negatively correlated with firm profitability and racial diversity among store managers and board members. Job-level contact gaps exhibit little geographical dispersion, but two digit industry explains more than half of the cross-firm variation in both racial and gender contact gaps. Distributional estimates reveal that racial discrimination is highly concentrated in particular companies, with firms in the top quintile responsible for roughly 50% of the lost callbacks to Black applicants in our study. Controlling false discovery rates to the 5% level, 23 companies are found to discriminate against Black applicants, while one discriminates against male applicants. Our findings reveal a stable organizational structure to employment discrimination.
May 25, 2021
Optimal Long-Term Health Insurance Contracts
Ben Handel, University of California, Berkeley
Abstract: Reclassification risk is a major concern in health insurance where contracts are typically one year in length but health shocks often persist for much longer. We theoretically characterize optimal long-term insurance contracts with one-sided commitment, and use our characterization to provide a simple computation algorithm for computing optimal contracts from primitives. We apply this method to derive empirically-based optimal long-term health insurance contracts using all-payers claims data from Utah, and then evaluate the potential welfare performance of these contracts. We find that optimal long-term health insurance contracts that start at age 25 can eliminate over 94% of the welfare loss from reclassification risk for individuals who arrive on the mar- ket in good health, but are of little benefit to the worst age-25 health risks. As a result, their ex ante value depends significantly on whether pre-age-25 health risk is otherwise insured. Their value also depends on individuals’ expected income growth.
May 11, 2021
Earning Dynamics and Firm-Level Shocks
Luigi Pistaferri, Stanford University
Abstract: We use matched employer-employee data from Sweden to study the role of the firm in affecting the stochastic properties of wages. Our model accounts for endogenous participation and mobility decisions. We find that firm-specific permanent productivity shocks transmit to individual wages, but the effect is mostly concentrated among the high-skilled workers; firm-specific temporary shocks mostly affect the low-skilled. The updates to worker-firm specific match effects over the life of a firm-worker relationship are small. Substantial growth in earnings variance over the life cycle for high-skilled workers is driven by firms accounting for 44% of cross-sectional variance by age 55.
May 4, 2021 at 1:30-3:00pm, Location: Zoom
The Long-Term Effects of Universal Preschool in Boston
Chris Walters, University of California, Berkeley
Abstract: We use admissions lotteries to estimate the effects of large-scale public preschool in Boston on college-going and college completion, standardized test scores, and several non-cognitive outcomes. Preschool enrollment boosts college-going and on-time college graduation, and decreases interaction with the criminal justice system and several school-based disciplinary measures. Preschool enrollment has mixed effects on MCAS test outcomes, but increases SAT test-taking and high school graduation. Our findings illustrate possibilities for large-scale modern, public preschool and highlight the importance of measuring long-term outcomes in evaluating the effectiveness of education programs.
April 27, 2021
How important is Social Capital for well-being, life satisfaction, adult and educational outcomes?
Isi Dunietz, The University of Chicago
Abstract: Using the British Cohort Study (BCS) and other longitudinal data, Borghans, Golsteyn, Heckman and Humphries (2016) [BGHH] highlighted the importance of a set of non-cognitive skills beyond cognitive ones in predicting important life outcomes. I build on BGHH and am investigating the predictive power of adding Social Capital--defined here as the subjective sense of belonging and significance of the individual to their communities and social environments. Using factor analysis, I create latent variables for Social Capital and for Parenting Styles from the BCS data to complement BGHH. Are these additional factors increasing the predictive power of important life and educational outcomes?
April 20, 2021
Measuring Racial Discrimination in Bail Decisions
Peter Hull, The University of Chicago
Abstract: We develop new quasi-experimental tools to measure racial discrimination, due to either racial bias or statistical discrimination, in the context of bail decisions. We show that the omitted variables bias in observational release rate comparisons can be purged by using the quasi-random assignment of judges to estimate average race-specific misconduct risk. We find that nearly two-thirds of the average release rate disparity between white and Black defendants in New York City is due to racial discrimination. We then develop a hierarchical marginal treatment effects model to study the drivers of discrimination, finding evidence of both racial bias and statistical discrimination.
April 13, 2021
Economics and Measurement: new measures to model decision making
Orazio Attanasio, Yale University
April 6, 2021
Migration and Informal insurance: Evidence from a randomized controlled trial and a strucutral model
Costas Meghir, Yale University
Abstract: Do new migration opportunities for rural households change the nature and extent of informal risk sharing? We experimentally document that randomly offering poor rural households subsidies to migrate leads to a 40% improvement in risk sharing in their villages. We explain this finding using a model of endogenous migration and risk sharing. When migration is risky, the network can facilitate migration by insuring that risk, which in turn crowds-in risk sharing when new migration opportunities arise. We estimate the model and find that welfare gains from migration subsidies are 42% larger, compared with the welfare gains without spillovers, once we account for the changes in risk sharing. Our analysis illustrates that (a) ignoring the spillover effects on the network gives an incomplete picture of the welfare effects of migration, and (b) informal risk sharing may be an essential determinant of the takeup of new income-generating technologies.
March 9, 2021
Can Mentoring Alleviate Family Disadvantage in Adolescence? A Field Experiment to Improve Labor-Market Prospect
Ludger Woessmann, University of Munich
Abstract: We study a mentoring program that aims to improve the labor-market prospects of youths from disadvantaged families by offering them a university-student mentor. Our RCT shows that for low-SES adolescents, the one-to-one mentoring increases an index of labor-market prospects by half a standard deviation after one year. There are significant effects for all three index components – math grades, patience and social skills, and labor-market orientation. By contrast, the mentoring is not effective for higher-SES adolescents. Part of the low-SES treatment effect is mediated by establishing mentors as attachment figures who provide guidance for the future. The program’s projected lifetime earnings impact by far exceeds its costs. The results suggest that substituting lacking family support by other adults can help disadvantaged youths at adolescent age.
March 2, 2021 at 1:30-3:00pm
Essays in Human Capital in Developing Countries
Laia Navarro-Sola, Stockholm University
Abstract: In areas where there is an insufficient supply of qualified teachers, delivering instruction through technology may be a solution to meet the demand for education. This paper analyzes the educational and labor market impacts of an expansion of junior secondary education in Mexico through telesecundarias - schools using televised lessons, currently serving 1.4 million students. To isolate the effects of telesecundarias, I exploit their staggered rollout from 1968 to present. I show that for every additional telesecundaria per 50 children, ten students enroll in junior secondary education and two pursue further education. Using the telesecundaria expansion as an instrument, I find that an additional year of education induced by telesecundaria enrollment increases average income by 17.6%. This increase in income comes partly from increased labor force participation and a shift away from agriculture and the informal sector. Since schooling decisions are sequential, the estimated returns combine the direct effect of attending telesecundarias and the effects of further schooling. I decompose these two effects by interacting the telesecundaria expansion with baseline access to upper secondary institutions. Roughly 84% of the estimated returns come directly from junior secondary education, while the remaining 16% are returns to higher educational levels.
February 23, 2021 at 1:30-3:00pm
Strategic Network Formation with Many Agents
Konrad Menzel, New York University
Abstract: We consider a random utility model of strategic network formation, where we derive a tractable approximation to the distribution of network links using many-player asymptotics. Our framework assumes that agents have heterogeneous tastes over links, and allows for anonymous and non-anonymous interaction effects among links. The observed network is assumed to be pairwise or cyclically stable, and we impose no restrictions regard-ing selection among multiple stable outcomes. Our main results concern convergence of the link frequency distribution from finite pairwise stable networks to the many-player limiting distribution. The set of possible limiting distributions is shown to have a fairly simple form and is characterized through aggregate equilibrium conditions, which may permit multiple solutions. We analyze identification of link preferences and propose a method for estimation of preference parameters.
February 16, 2021 at 1:30-3:00pm
Identification of Firms' Beliefs in Structural Models of Market Competition
Victor Aguirregabiria, The University of Toronto
Abstract: Firms make decisions under uncertainty and differ in their ability to collect and process information. As a result, in changing environments, firms have heterogeneous beliefs on the behavior of other firms. This heterogeneity in beliefs can have important implications on market outcomes, efficiency, and welfare. This paper studies the identification of firms' beliefs using their observed actions – a revealed preference and beliefs approach. I consider a general structural model of market competition where firms have incomplete information and their beliefs and profits are nonparametric functions of decisions and state variables. Beliefs may be out of equilibrium. The framework applies both to continuous and discrete choice games and includes as particular cases models of competition in prices or quantities, auction models, entry games, and dynamic games of investment decisions. I focus on identification results that exploit an exclusion restriction that naturally appears in models of competition: an observable variable that affects a firm's cost (or revenue) but does not have a direct effect on other firms' profits. I present identification results under three scenarios – common in empirical IO – on the data available to the researcher.
February 9, 2021 at 1:30-3:00pm
Discrimination and Racial Disparities in Labor Market Outcomes: Evidence from WWII
Anna Aizer, Brown University
Abstract: The 1940s witnessed substantial reductions in the Black-white earnings gap. We study the role that domestic WWII defense production played in reducing this gap. Exploiting variation across labor markets in the allocation of war contracts to private firms, we find that war production contracts resulted in significant increases in the earnings of Black workers and declines in the racial wage gap, with no effect on white workers. This was achieved via occupational upgrading among Black men to skilled occupations. The gains largely persisted through at least 1970. Using a structural model, we show that declines in discrimination (and not migration or changes in productivity) account for all of the occupational upgrading and half of the estimated wage gains associated with the war production effort. Additionally, the war production effort explains one quarter (one seventh) of the overall improvements in racial gaps in occupation allocations (wages) witnessed over this decade. Finally, war spending led to an increase in the high school graduation rate of Black children, suggesting important intergenerational spillovers associated with declines in labor market discrimination.
February 2, 2021
Long-Term Health Insurance: Theory Meets Evidence
Hanming Fang, University of Pennsylvania
Abstract: To insure policyholders against contemporaneous health expenditure shocks and future reclassification risk, long-term health insurance constitutes an alternative to community-rated short-term contracts with an individual mandate. Relying on unique claims panel data from a large private insurer in Germany, we study a real-world long-term health insurance application with a life-cycle perspective. We show that German long-term health insurance (GLTHI) achieves substantial welfare gains compared to a series of risk-rated short-term contracts. Although, by its simple design, the premium setting of GLTHI contract departs significantly from the optimal dynamic contract, surprisingly we only find modest welfare differences between the two. Finally, we conduct counterfactual policy experiments to illustrate the welfare consequences of integrating GLTHI into a system with a “Medicare-like” public insurance that covers people above 65.
January 26, 2021 at 1:30-3:00pm
Inaccurate Statistical Discrimination: An Identification Problem
Alex Imas, The University of Chicago
Abstract: Discrimination has been widely studied in the social sciences. Economists often categorize the source of discrimination as either taste-based or statistical—a valuable distinction for policy design and welfare analysis. In this paper, we highlight that in many situations economic agents may have inaccurate beliefs, and demonstrate that the possibility of inaccurate statistical discrimination generates an identification problem for attempts to isolate the source of differential treatment. We introduce isodiscrimination curves—which represent the set of preferences and beliefs that generate the same level of discrimination—to formally outline the identification problem: when not accounted for, inaccurate statistical discrimination can be mistaken for taste-based discrimination, accurate statistical discrimination, or their combination. A review of the empirical discrimination literature in economics, spanning 1990-2018, reveals the scope of this issue. While most papers discuss and attempt to distinguish between taste and statistical discrimination, a small minority—fewer than 7%—consider inaccurate beliefs in the analysis. An experiment illustrates a methodology for differentiating between the three sources of discrimination, demonstrating the pitfalls of the identification problem while presenting a portable solution.
January 19, 2021 at 1:30-3:00pm
Can Early Intervention have a Sustained Effect on Human Capital into Middle Childhood?
Orla Doyle, University College, Dublin
Abstract: Evidence on the sustained effect of early intervention is inconclusive, with many studies experiencing a dissolution of treatment effects once the program ends. Using a randomized trial, this paper examines the impact of Preparing for Life, a pregnancy to age five home visiting and parenting program, on outcomes in middle childhood. We find little evidence of cognitive fade-out at age nine, with significant treatment effects on cognitive skills (0.67SD) and school achievement tests (0.47-0.74SD). There is no impact on socio-emotional skills. Mediation analysis suggests that ~46 percent of the treatment effect on cognitive skills is explained by improvements in early parental investment.
January 12, 2021
Optimal Contracting with Altruistic Agents
Nirav Mehta, Western University
Abstract: We study physician agency and optimal payment policy in the context of an expensive medication used in dialysis care. Using Medicare claims data we estimate a structural model of treatment decisions, in which physicians differ in their altruism and marginal costs, and this heterogeneity is unobservable to the government. In a novel application of nonlinear pricing methods, we theoretically characterize the optimal unrestricted contract in this screening environment with multidimensional heterogeneity. We combine these results with the estimated model to construct the optimal contract and simulate counterfactual outcomes. The optimal contract is a flexible fee-for-service contract, which pays for reported treatments but uses variable marginal payments instead of constant reimbursement rates, resulting in substantial health improvements and reductions in costs. Our structural approach also yields important qualitative findings, such as rejecting the optimality of any linear contract, and may be employed more broadly to analyze a variety of applications.
January 5, 2021
Consumption and Income Inequality across Generations
Giovanni Gallipoli, University of British Columbia
Abstract: We characterize the joint evolution of cross-sectional inequality in earnings, other sources of income and consumption across generations in the U.S. To account for cross-sectional dispersion, we estimate a model of intergenerational persistence and separately identify the influences of parental factors and of idiosyncratic life-cycle components. We find evidence of family persistence in earnings, consumption and saving behaviours, and marital sorting patterns. However, the quantitative contribution of idiosyncratic heterogeneity to cross-sectional inequality is significantly larger than parental effects. Our estimates imply that intergenerational persistence is not high enough to induce further large increases in inequality over time and across generations.
December 8, 2020 at 1:30-3:00pm
Intergenerational Mobility of Immigrants in the US over Two Centuries
Ran Abramitzky, Stanford University
Abstract: Using millions of father-son pairs spanning more than 100 years of US history, we find that children of immigrants from nearly every sending country have higher rates of upward mobility than children of the US-born. Immigrants’ advantage is similar historically and today despite dramatic shifts in sending countries and US immigration policy. In the past, this advantage can be explained by immigrants moving to areas with better prospects for their children and by “under-placement” of the first generation in the income distribution. These findings are consistent with the “American Dream” view that even poorer immigrants can improve their children’s prospects.
December 1, 2020 at 1:30-3:00pm
Does Eviction Cause Poverty? Quasi-experimental Evidence from Cook County, IL
Winnie van Dijk, Harvard University
Abstract: "Each year, more than two million U.S. households have an eviction case filed against them. Many cities have recently implemented policies aimed at reducing the number of evictions, motivated by research showing strong associations between being evicted and subsequent adverse economic outcomes. Yet it is difficult to determine to what extent those associations represent causal relationships, because eviction itself is likely to be a consequence of adverse life events. This paper addresses that challenge and offers new causal evidence on how eviction affects financial distress, residential mobility, and neighborhood quality. We collect the near-universe of Cook County court records over a period of seventeen years, and link these records to credit bureau and payday loans data. Using this data, we characterize the trajectory of financial strain in the run-up and aftermath of eviction court for both evicted and non-evicted households, finding high levels and striking increases in financial strain in the years before an eviction case is filed. Guided by this descriptive evidence, we employ two approaches to draw causal inference on the effect of eviction. The first takes advantage of the panel data through a difference-in-differences design. The second is an instrumental variables strategy, relying on the fact that court cases are randomly assigned to judges of varying leniency. We find that eviction negatively impacts credit access and durable consumption for several years. However, the effects are small relative to the financial strain experienced by both evicted and non-evicted tenants in the run-up to an eviction filing."
November 24, 2020 at 1:30-3:00pm
On the Use of Outcome Tests for Detecting Bias in Decision Making
Jack Mountjoy, The University of Chicago
Abstract: The decisions of judges, lenders, journal editors, and other gatekeepers often lead to disparities in outcomes across affected groups. An important question is whether, and to what extent, these group-level disparities are driven by relevant differences in underlying individual characteristics, or by biased decision makers. Becker (1957) proposed an outcome test for bias leading to a large body of related empirical work, with recent innovations in settings where decision makers are exogenously assigned to cases and vary progressively in their decision tendencies. We carefully examine what can be learned about bias in decision making in such settings. Our results call into question recent conclusions about racial bias among bail judges, and, more broadly, yield four lessons for researchers considering the use of outcome tests of bias. First, the so-called generalized Roy model, which is a workhorse of applied economics, does not deliver a logically valid outcome test without further restrictions, since it does not require an unbiased decision maker to equalize marginal outcomes across groups. Second, the more restrictive "extended" Roy model, which isolates potential outcomes as the sole admissible source of analyst-unobserved variation driving decisions, delivers both a logically valid and econometrically viable outcome test. Third, this extended Roy model places strong restrictions on behavior and the data generating process, so detailed institutional knowledge is essential for justifying such restrictions. Finally, because the extended Roy model imposes restrictions beyond those required to identify marginal outcomes across groups, it has testable implications that may help assess its suitability across empirical settings.
November 17, 2020
Teacher-to-Classroom Assignment and Student Achievement
Bryan Graham, University of Berkeley
Abstract: We study the effects of counterfactual teacher-to-classroom assignments on average student achievement in elementary and middle schools in the US. We use the Measures of Effective Teaching (MET) experiment to semiparametrically identify the average reallocation effects (AREs) of such assignments. Our findings suggest that changes in within-district teacher assignments could have appreciable effects on student achievement. Unlike policies which require hiring additional teachers (e.g., class-size reduction measures), or those aimed at changing the stock of teachers (e.g., VAM-guided teacher tenure policies), alternative teacher-to-classroom assignments are resource neutral; they raise student achievement through a more efficient deployment of existing teachers.
November 10, 2020
Household Labour Search, Spousal Insurance, and Health Care Reform
Andrew Shephard, University of Pennsylvania
Abstract: Health insurance in the United States for the working age population has traditionally been provided in the form of employer-sponsored health insurance (ESHI). If employers of- fered ESHI to their employees, they also typically extended coverage to their spouse and dependents. Provisions in the Affordable Care Act (ACA) significantly alter the incentive for firms to offer insurance to the spouses of employees. We evaluate the long-run impact of the ACA on firms’ insurance offerings and on household outcomes by developing and estimat- ing an equilibrium job search model in which multiple household members are searching for jobs. The distribution of job offers is determined endogenously, with compensation packages consisting of a wage and menu of insurance offerings (premiums and coverage) that workers select from. Using our estimated model we find that households’ valuation of employer- sponsored spousal health insurance is significantly reduced under the ACA, and with an “employee-only” health insurance contract emerging among low productivity firms. We re- late these outcomes to the specific provisions in the ACA.
Canceled: November 3, 2020
Identification of Firms' Beliefs in Structural Models of Market Competition
Victor Aguirregabiria, The University of Toronto
Abstract: Firms make decisions under uncertainty and di§er in their ability to collect and process information. As a result, in changing environments, firms have heterogeneous beliefs on the behavior of other firms. This heterogeneity in beliefs can have important implications on market outcomes, efficiency, and welfare. This paper studies the identification of firms' beliefs using their observed actions - a revealed preference and beliefs approach. I consider a general structural model of market competition where firms have incomplete information and their beliefs and profits are nonparametric functions of decisions and state variables. Beliefs may be out of equilibrium. The framework applies both to continuous and discrete choice games and includes as particular cases models of competition in prices or quantities, auction models, entry games, and dynamic games of investment decisions. I focus on identification results that exploit an exclusion restriction that naturally appears in models of competition: an observable variable that affects a firms' cost (or revenue) but does not have a direct effect on other firms' profits. I present identification results under three scenarios - common in empirical IO - on the data available to the researcher.
October 27, 2020
Longitudinally Adaptive Assessment and Instruction Increase Numerical Skills of Preschool Children
Stephen Raudenbush, The University of Chicago
Abstract: Social inequality in mathematical skill is apparent at kindergarten entry and persists during elementary school. To level the playing field, we trained teachers in 24 randomly assigned preschool classrooms to assess children’s numerical and spatial skills every 10 weeks. Each assessment enabled teachers to examine each assessed child’s growth trajectory on each skill, evaluate the success of past instruction, design the next phase of instruction, and set learning targets. A key constraint is that teachers have limited time to assess each individual student during each assessment period. To maximize the information provided by each assessment under constrained time, we adapted the difficulty of each assessment based on each child’s age and accumulated evidence about the child’s skill. Compared to children in 25 randomly assigned control classrooms, children of the trained teachers scored 0.26 SD higher on numerical skills at posttest (p=.004). We observed no effect on spatial skills. The intervention also positively influenced children’s verbal comprehension skills (0.28 SD, p<.001) but did not affect their print-literacy skills. Findings suggest that preschoolers’ numerical learning improves when teachers enact a dynamic regime consisting of iteratively assessing children’s skill and planning and implementing instruction to support the next phase of growth. Findings also suggest that preschool math instruction does not subtract from verbal and literacy learning, but rather, may benefit verbal comprehension skills. We consider the potential contribution of this approach to the reduction of social inequality in numerical skill and discuss possible explanations for the absence of an effect on spatial reasoning.
October 20, 2020
Deep Learning Inference on Semi-nonparametric Conditional Moment Models with Weakly Dependent Data
Xiaohong Chen, Yale University
October 13, 2020
Skill Prices, Occupations, and Changes in the Wage Structure for Low Skilled Men
Chris Taber, University of Wisconsin, Madison
Abstract: This paper studies the effect of the change in occupational structure on wages for low skilled men. We develop a model of occupational choice in which workers have multi-dimensional skills that are exploited differently across different occupations. We allow for a rich specification of technological change which has heterogenous effects on different occupations and different parts of the skill distribution. We estimate the model combining four datasets: (1) O*NET, to measure skill intensity across occupations, (2) NLSY79, to identify life-cycle supply effects, (3) CPS (ORG), to estimate the evolution of skill prices and occupations over time, and (4) NLSY97 to see how the gain to specific skills has changed. We find that while changes in the occupational structure have affected wages of low skilled workers, the effect is not dramatic. First, the wages in traditional blue collar occupations have not fallen substantially relative to other occupations-a fact that we can not reconcile with a competitive model. Second, our decompositions show that changes in occupations explain only a small part of the patterns in wage levels over our time period. Price changes within occupation are far more important. Third, while we see an increase in the payoff to interpersonal skills, manual skills still remain the most important skill type for low educated males.
October 6, 2020
What Determines School Segregation? The Crucial Role of Neighborhood Factors
Hugh Macartney, Duke University
Abstract: We develop a novel strategy to identify the relative importance of school and neighbor- hood factors in determining school segregation. Using detailed student enrollment and residential location data, our research design compares differences in student composition between adjacent Census blocks served by different schools to analogous differences between those schools. Our findings indicate that neighborhood factors explain around 62% of racial segregation and 44% of economic segregation across all schools, playing an even more pronounced role in urban areas, where school segregation has been especially acute. These findings suggest that the involvement of urban planners is essential when attempting to confront inequality of opportunity through education.
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Working Group Schedule 2019-2020
March 10, 2020 at 5:15-6:30pm, Location: CEHD 180
Simon Mongey, The University of Chicago
Abstract:We study the role of technological change in driving trends in within-occupation wage inequality. In our model, heterogeneous workers have multiple skills and supply their skills as an indivisible bundle when they choose an occupation. In equilibrium, a given skill can command a premium in occupations that are relatively intensive in its use. The pattern of occupation-specifi c skill prices is determined by the interac- tion between the joint distribution of worker skills and the different skill intensities in different occupations. Changes in technology increase skill premia and increase within-occupation wage inequality when occupations become more specialized in their primary skills but decrease skill premia and decrease within-occupation wage inequality when occupations become less specialized in their primary skills. We show how such changes in skill intensity can emerge endogenously when fi rms choose technologies that are appropriate for the skill prices they face. We show that skill-biased technical change can increase wage-inequality in some occupations while at the same time decreasing wage-inequality in other occupations.
March 3, 2020 at 5:15-6:30pm, Location: CEHD 180
Are Neighborhood Effects Explained by Differences in School Quality?
Geoffrey Wodtke, The University of Chicago
Abstract: Although it is widely hypothesized that neighborhood effects are explained by differences in the schools to which children have access, few prior studies have investigated the explanatory role of school quality. In this study, we examine whether school quality mediates or interacts with the effects of neighborhood context on academic achievement. With data from the Early Childhood Longitudinal Study, we operationalize a school’s quality as the difference between the school-year and summer learning rates among its 1st grade students. We then decompose the total effect of neighborhood context on achievement at the end of 3rd, 5th, and 8th grade into components due to mediation versus interaction, which we estimate using novel counterfactual methods. Results indicate that living in a disadvantaged neighborhood substantially reduces academic achievement. But contrary to expectations, we find no evidence that neighborhood effects are mediated by or interact with school quality. The school environment does not mediate the effects of neighborhood context because differences in the socioeconomic composition of neighborhoods are not, in fact, strongly linked with differences in school quality. The school environment also does not interact with neighborhood context because attending a high-quality school is similarly beneficial whether children reside in advantaged or disadvantaged neighborhoods.
February 21, 2020 at 4:00-5:20pm, Location: Saieh Hall 112
Human Capital and Migration: A Cautionary Tale
Salvador Navarro, University of Western Ontario
*This lecture is part of the University of Chicago's Workshop in Family Economics, Room SHFE 112
Abstract: We analyze the impact that the option of migration might have on human capital accumulation. We show that, as long as the return to human capital for migrants individuals is lower in the destiny than in the origin, this will reduce the overall incentive to accumulate human capital, compared to a situation in which migration is harder or impossible. We illustrate, both with quasi-experimental and structural methods, that this indeed happened in China after the 1983 reform that eliminated the strong restrictions that existed for rural-urban migration. Since the return to education for rural migrants in the city is very low, the reform resulted in a reduction in average years of schooling of almost half a year for rural people.
February 11, 2020 at 5:15-6:30pm, Location: CEHD 180
Labor Market Consequences of Grandparenthood
Felix Elwert, University of Wisconsin Madison
Abstract: Grandparenthood is a near universal experience. But little is known about the the labor market consequences of grandparenthood. We estimate dynamic models of grandparenthood effects using multi-generational data from 15 complete Danish birth cohorts. Results indicate that grandparenthood effects result from spillovers of parenting burdens on grandparents. Spillovers, in turn, depend on parental capacity and the gender division of labor. Therefore, grandparenthood reduces earnings and hours worked, especially when the grandparent is female, even more so when the parent is also female, and most when the daughter gives birth as a teenager.
February 4, 2020 at 5:15-6:30pm, Location: CEHD 180
Intergenerational educational mobility in 20th century-Denmark
Rasmus Landersø, Rockwool Foundation
Abstract: This paper studies educational mobility in Denmark for cohorts born across the entire 20th century. We show that, whereas cohorts born in the first half of the century experienced very low levels of educational mobility, cohorts born during the 1950s and 1960s experienced much higher levels of mobility as a result of major schooling reforms that significantly lifted the lower parts of the schooling distribution. As the educational expansion shifted from lower secondary and high school completion to college and university degrees for cohorts born during the 1970s and 1980s, educational mobility has been decreasing monotonically at a relatively fast rate. Our findings thus suggest that mobility is highly dependent on how distributions change over time. Compression in the lower tail leads to increasing mobility whereas expansion at the upper tail leads to lower mobility. We also find that, as the educational system expands, the link between education and human capital also changes. On the one hand, the compression at the lower tail resulting from schooling reforms reduced the association between education and cognitive skills by 25 percent. On the other hand, for the younger cohorts affected by education expansion at the upper tail, our analyses of the interrelationship between education, skills, and life outcomes such as crime, earnings, marriage rates, and health suggest that noncognitive skills play an increasingly large role. Thus, differences in estimated social mobility between or within countries, or across time, may reflect fundamental differences in underlying distributions and mechanisms.
January 21, 2020 at 5:15-6:30pm, Location: CEHD 180
Sources of Women’s Underrepresentation in US Politics: A Model of Election Aversion and Voter Discrimination
Ethan Bueno de Mesquita, The University of Chicago
Abstract: A central question animating the study of women in American politics is why so few women hold elected office. The literature exploring this phenomenon has uncovered three empirical facts that require explanation: (i) women are under-represented in the pool of candidates, (ii) conditional on winning, women perform better than men in office, and (iii) conditional on running (and controlling for incumbency), women and men win at equal rates. The literature also posits two key explanatory mechanisms: election aversion and voter bias. We study a formal model of elections that endogenizes male and female potential candidates’ strategic decision to enter politics in order to explore the explanatory power of these mechanisms relative to the empirical facts. Our analysis shows that neither mechanism, on its own, can explain all three facts. But it also shows that a model incorporating both election aversion and voter discrimination can. The reason is that each mechanisms implies each of the first two facts and so they are mutually reinforcing. However, each mechanism is inconsistent with the third fact, but in off-setting ways—election aversion implies that women should win at higher rates than men while voter bias implies that women should win at lower rates than men. Hence, it takes a combination of the two mechanisms to make sense of all three empirical facts.
December 4, 2019 at 5:15-6:30pm, Location: CEHD 180
Layered Policy Analysis using Marginal Treatment Effect
Ismael Mourifie, University of Toronto
November 20, 2019 at 5:15-6:30pm, Location: CEHD 180
Interpreting Signals in the Labor Market
Heather Sarsons, University of Chicago Booth
November 13, 2019 at 5:15-6:30, Location: CEHD 180
Democracy Without Redistribution: The Sense of Injustice, Perceived Inequality, and Preferences for Redistribution
Yeonju Lee, Harvard University
November 6, 2019 at 5:15-6:30, Location: CEHD 180
Fertility and Family Policies in Germany: Optimal Policy Design in a Dynamic Framework
Hanna Wang, Universitat Autònoma de Barcelona, MOVE and Barcelona GSE
October 30, 2019 5:15-6:30, Location: CEHD 180
Examining the Economic Content of Monotonicity Criteria in Multiple Choice Models
Rodrigo Pinto, UCLA
October 23, 2019 5:15-6:30pm, Location: CEHD 180
Mothers working during preschool years and child skills?
Kjell Salvanes, Norwegian School of Economics
October 9, 2019 at 5:15-6:30pm, Location: CEHD 180
General Equilibrium Theory and Empirical Analysis of Immigrants’ Neighborhood Sorting and Social Integration
Yujung Hwang, University of Geneva
Working Group Schedule 2018-2019
June 7, 2019 (Friday) at 4:00pm, Location: Saieh Hall 112
Actors in the Child Development Process
Ewout Verriest, NYU
Abstract: We construct and estimate a model of child development in which both the parents and children make investments in the child’s skill development. In each period of the development process, partially altruistic parents act as the Stackelberg leader and the child the follower when setting her own study time. We then extend this non-cooperative form of interaction by allowing parents to offer incentives to the child to increase her study time, at some monitoring cost. We show that this incentive scheme, a kind of internal conditional cash transfer, produces efficient outcomes and, in general, increases the child’s cognitive ability. In addition to heterogeneity in resources (wage offers and non-labor income), the model allows for heterogeneity in preferences both for parents and children, and in monitoring costs. Like their parents, children are forward-looking, but we allow children and parents to have different preferences and for children to have age-varying discount rates, becoming more “patient” as they age. Using detailed time diary information on the allocation of parent and child time linked to measures of child cognitive ability, we estimate several versions of the model. Using model estimates, we explore the impact of various government income transfer policies on child development.
May 31, 2019 (Friday) at 5:30pm, Location: Saieh Hall 112
Environmental Neuroscience: Uncovering the extensive interactions between neurobiology, psychology, behavior and the environment
Marc Berman, The University of Chicago
May 24, 2019 (Friday) at 5:30pm, Location: Saieh Hall 112
(Not) Playing Favorites: An Experiment on Parental Preferences for Educational Investment
Rebecca Dizon-Ross, University of Chicago Booth
Abstract: How do parents choose to allocate investments across children? Do they maximize the returns to their investments (total household earnings), or equalize across their children because of an aversion to cross-sibling inequality? In this paper, we conduct the first experiment that identifies parents’ preferences for investing in their children’s education. The experiment exogenously varies the short-run returns to educational investments to identify the degree to which parents care about (a) maximizing total household earnings, (b) minimizing cross-sibling inequality in “outcomes” (i.e., child- level earnings), and (c) minimizing cross-sibling inequality in “inputs” (i.e., the inves- tments each child receives). We find that while parents care about both maximizing total household earnings and minimizing inequality in inputs, they place a high value on equality of inputs. Parents choose exactly equal inputs 35% of the time and forego 40-50% of their potential experimental earnings due to inequality aversion in inputs. In contrast, we find no evidence that parents are averse to inequality in outcomes.
May 17, 2019 (Friday) at 5:30pm, Location: Saieh Hall 112
The Marginal Labor Supply Disincentives of Welfare Reforms
Robert Moffitt, Johns Hopkins University
Abstract: Existing research on the static effects of the manipulation of welfare program benefit parameters on supply has allowed only restrictive forms of heterogeneity in preferences. Yet preference heterogeneity implies that the marginal effects of welfare reforms on labor supply may differ in different time periods with different populations and which sweep out different portions of the marginal distributions of preferences. A new examination of the heavily studied AFDC program shows that changes in its tax rates and guarantees in 1967, the 1970s, 1981, 1996, and 2010 had different marginal effects on labor supply because of differing heterogeneity of marginal participants in each case. The models used to estimate these effects allow for a nonparametric specification of how changes in welfare program participation affect labor supply on the margin. Estimates of the model using a form of local instrumental variables show that the effects of each of the historical reforms on labor supply differed because of differences in the composition of who was on the program and who was not, and who the marginal person was, in each period.
May 10, 2019 (Friday) at 5:30pm, Location: Saieh Hall 112
A Dynamic Model of Personality, Schooling and Occupational Choice
Petra Todd, University of Pennsylvania
April 26, 2019
Econographics: Clustering of Preferences from a Representative US Sample
Colin Camerer, Caltech
Professor Colin Camerer will visit the University of Chicago to participate in the Policy Forum: Assessing the Contributions of Behavioral Economics to Economic Science, hosted by the Center for the Economics of Human Development and the Macro Finance Research Program. He will give a special lecture on Econographics: Clustering of Preferences from a Representative US Sample at the Lifecycle Working Group.
April 12, 2019 (Friday), Location: Saieh Hall 112
Marriage market dynamics, gender, and the age gap
Andrew J. Shephard, University of Pennsylvania
Abstract: We present a general discrete choice framework for analysing household formation and dissolution decisions in an equilibrium limited-commitment collective framework that allows for marriage both within and across birth cohorts. Using Panel Study of Income Dynamics and American Community Survey data, we apply our framework to empirically implement a time allocation model with labour market earnings risk, human capital accumulation, home production activities, fertility, and both within- and across-cohort marital matching. Our model replicates the bivariate marriage distribution by age, and explains some of the most salient life-cycle patterns of marriage, divorce, remarriage, and time allocation behaviour. We use our estimated model to quantify the impact of the significant reduction in the gender wage gap since the 1980s on marriage outcomes.
March 26, 2019
The New Findings of Preparing for Life Program
Orla Doyle, University College Dublin
Register here to attend.
March 19, 2019
Separating Skills from Effort in the Identification of Factor Models and Implications for the Gender Gap
Jake Torcasso, The University of Chicago
Abstract: We apply new results in the identification of factor models to separate the effects of effort and skills in measures of task performance. We provide two empirical applications. First, we utilize detailed data on test scores, grades and self-reports of personality from Project Talent, a national longitudinal survey representative of the U.S. high school population in 1960. For our second example, we use the computer-based test of the 2015 PISA study. In both cases, we compare estimates of skill gaps among demographic groups before and after adjusting for effort.
March 12, 2019
Grandparents, Moms, or Dads? Why Children of Teen Mothers Do Worse in Life
Kjell Salvanes, NHH Norwegian School of Economics
Abstract: Women who give birth as teens have worse subsequent educational and labor market outcomes than women who have first births at older ages. However, previous research has attributed much of these effects to selection rather than a causal effect of teen childbearing. Despite this, there are still reasons to believe that children of teen mothers may do worse as their mothers may be less mature, have fewer financial resources when the child is young, and may partner with fathers of lower quality. Using Norwegian register data, we compare outcomes of children of sisters who have first births at different ages. Our evidence suggests that the causal effect of being a child of a teen mother is much smaller than that implied by the cross-sectional differences but that there are still significant long-term, adverse consequences, especially for children born to the youngest teen mothers. Unlike previous research, we have information on fathers and find that negative selection of fathers of children born to teen mothers plays an important role in producing inferior child outcomes. These effects are particularly large for mothers from higher socio-economic groups.
March 5, 2019
Human Capital, Child Well-being, and Child Protection
Fred Wulczyn, Chapin Hall
Abstract:In this paper, we propose a framework that adds human capital and human capital formation to the list of outcomes child welfare agencies think about when their attention turns to child well-being. Human capital and human capital formation, we argue, offer a conceptual language for bringing greater focus to well-being as an inherently developmental construct. The framework also provides a useful guide to research.
Feburary 26, 2019
Childhood Investments, Ability, and Endogenous Maternal Age
Sadegh Eshaghnia, Arizona State University
Abstract: The maternal age has been increasing in the US over the past few decades, which has raised concerns about the health impacts on children. To assess the effect of a mother’s age at childbirth on the child’s skill level, I develop and estimate a life-cycle model of child development that endogenizes the timing of childbearing. When choosing the timing of childbearing, women balance the impacts of fertility decisions on their labor market outcomes with the potential negative effects of bearing children at a later age on the child’s ability. Mothers also make labor supply decisions and provide time and money as inputs into the child’s skill formation process. Although delayed childbearing negatively affects a child’s ability to acquire skills, postponing parenthood benefits children by providing them with more resources during childhood. This trade-off determines both childbearing age and the amount of investments in the child. Using the estimated model, I decompose the impacts of postponement on the child into the negative effect of reproductive aging and the positive effect of higher investments. The results indicate that a five-year (1 std) decrease in the maternal age of educated women, ceteris paribus, results in over 11% (0.5 std) increase in the child's skill level, and 15% increase in the child's future earnings, which is due to a higher ability to acquire skills. However, if one adjusts child investments according to individuals' wage profile conditional on the reduced maternal age, then the average child's skill level decreases by 1.6%. This reduction in children's skill highlights the impact of lower inputs that children of younger mothers receive from their parents. The negative effect of foregone wages may be reduced through policy approaches. My policy analysis indicates that implementing a maternity leave policy that freezes mothers' wages at the level before childbirth can reduce average maternal age at the first birth by about two years, while also increasing the average child's skill level by about 5% and future earnings by over 6%. This increase in skill stems from both the lower maternal age and the higher child investments.
Feburary 19, 2019
Prosociality: Hard to Build but Easy to Destroy
Fabian Kosse, LMU Munich & briq
Abstract: A large literature indicates the importance of prosocial behavior and beliefs for the success of groups or countries, e.g., regarding growth and tax compliance, but also for the well-being of individuals, e.g., regarding health, happiness and even income. While recent studies indicate that intensive interaction with positive role models is able to foster prosociality, little is known about aspects of the social environment which potentially diminish prosocial behavior and beliefs. Psychological and economic theories suggest that competitive environments could potentially lower prosociality. To test this hypothesis, we analyze the effects of a large scale RCT in the education context in Chile which increased the level of competition as part of an affirmative action program. We show that students in treated school are less prosocial at the end of high school. Our results show that even policies which were designed in order to support the development of children can negatively affect prosocial behavior and beliefs.Please register for this lecture here.
Feburary 12, 2019
Relative Age and Investment in Human Capital
Pablo Pena, World Bank
February 5, 2019
Lowering Welfare Benefits: Intended and Unintended Consequences for Migrants and their Families
Rasmus Landersø, Rockwool Foundation Research Unit
Abstract: We study the effects of Denmark's Start Aid welfare reform for refugee immigrants, which reduced benefits by 50 percent for those granted residency after the reform. While leading to a sharp increase in labor earnings and employment, the reform also caused a persistent withdrawal of women from the labor force, and a large drop in average disposable income for the majority of households. A particular feature of the reform is randomization of couples into two treatments where the same overall transfer reduction on the household level is differently distributed across partners, which leads to large differences in responses. Studying the reform's unintended consequences, we show that it increases property crime among females and property and violent crime among males. Children's likelihood of being enrolled in childcare or preschool, their performance in Danish language tests, and the number of years of education obtained decrease, while teenagers' likelihood of claiming welfare and the likelihood that youths commit crime increase.
January 24, 2019
Are Economists' Preferences Psychologists' Personality Traits
Tomas Jagelka, École Polytechnique - CREST
Abstract: This paper establishes an empirical mapping between economic preferences and psychological personality traits. I use the Random Preference Model to estimate distributions of risk and time preferences complete with their individual-level stability and people’s propensity to make mistakes from unique experimental data. Using factor analysis to extract information on individuals’ ability and personality, I show that their link with preferences is much stronger than previously documented. I explain up to 50% of the variation in both average preferences and in individuals’ capacity to make consistent rational choices using four factors related to cognitive ability and three of the Big Five personality traits.
January 8, 2019
The Socio-Economic Consequences of Housing Assistance
Winnie Van Dijk, The University of Chicago
Abstract: This paper analyzes the effect of Europe’s largest public housing program on socio-economic outcomes for low-income households. Using lotteries for housing units in the Netherlands and data linking national registers to application choices, I show that the average move into public housing negatively affects labor market outcomes and proxies for neighborhood quality, and increases public assistance receipt. However, consistent with a model of labor supply responses to conditional in-kind transfers, average impacts miss substantial heterogeneity both across neighborhoods and, within neighborhood, across recipients. Moves into high-income neighborhoods generate positive effects, which are driven by ‘upward’ moves made by individuals previously living in low- or middle-income neighborhoods. Lateral and ‘downward’ moves have the opposite effect. To evaluate whether these results generalize to non-recipients, I develop a model of application behavior that utilizes panel data on application choices and exploits variation induced by the housing allocation mechanism. Using the model, I recover the distribution of heterogeneity that drives selection into and returns from lotteries, and estimate that selection on gains is limited. This suggests that targeting public housing in high-income neighborhoods based on observable characteristics can increase economic self-sufficiency.
December 11, 2018
Complementarities in High School and College Investments
Gregory F. Veramendi, Arizona State University
Abstract: The process of skill specialization starts before college, with different skills affecting students’ choice of major and later labor market returns. This paper studies the role of multi-dimensional ability and high school track choices in college preparedness and labor market outcomes. We do so by estimating a sequential choice model of education using Swedish administrative data. Individuals sort at each stage based on prior choices and three dimensions of ability: cognitive, interpersonal, and grit. We find strong absolute and differential sorting on abilities in both high school and college choices. Both abilities and high school track choices are important determinants of college enrollment, college major choice, college graduation, and labor market outcomes. The labor market returns to abilities and high school track choices vary considerably by degree and major. Not accounting for multidimensional abilities and high school choices can overstate the role of preferences and understate selection on gains and the heterogeneous returns to different abilities across different college majors. While high school track choices tend to exacerbate inequality, we show that policies encouraging students to take more challenging high school tracks can help ameliorate it.
November 27, 2018
Causality in the Time of Cholera: John Snow as a Prototype for Identification and Causal Inference
Thomas Coleman, Harris School of Public Policy
Abstract: Snow's 1855 treatise "On the mode of communication of cholera" can be viewed as a sustained effort to convince skeptics, through argument and a wide variety of evidence, of the waterborne theory of cholera that he articulated in his 1849 essay of the same name. Snow's data and analysis provide a prototype for how to convincingly demonstrate causal effects, as applicable today as in 1855. I consider two of strands of Snow's evidence - the Broad Street outbreak and the south London "Grand Experiment" - as pedagogical examples for using non-experimental data as evidence in support of a causal effect. In doing so I discuss extensions to Snow's south London analysis using modern techniques and tools: difference-in-differences regression and quasi-randomized treatment designs. These provide clear and compelling examples of the modern techniques and tools, while confirming and strengthening Snow's original conclusion on the causal effect of water supply on cholera mortality.
November 20, 2018
Breaking the Links: Natural Resource Booms and Intergenerational Mobility
Kjell Salvanes, Norwegian School of Economics
Abstract: Do large economic shocks increase intergenerational earnings mobility through creating new economic opportunities? Alternatively, do they reduce mobility by reinforcing the links between generations? In this paper, we estimate how the Norwegian oil boom starting in the 1970s affected intergenerational mobility. We find that this resource shock increased intergenerational mobility for cohorts entering the labor market at the beginning of the oil boom in those labor markets most affected by the growing oil industry. In particular, we show that individuals born to poor families in oil-affected regions were more likely to move to the top of their cohort's earnings distribution. Importantly, we reveal that preexisting local differences in intergenerational mobility did not drive these findings. Instead, we show that changes in the returns to education offer the best explanation for geographic differences in intergenerational mobility following the oil boom. In addition, we find that intergenerational mobility was significantly higher in oil-affected labor markets across three generations and that the oil boom broke the earnings link between grandfathers and their grandsons.
November 6, 2018
Social Capital and the Local Structure of Human Mobility in Chicago
James Saxon, Harris School of Public Policy
Abstract: A vast literature establishes the importance of social capital to neighborhoods. Jane Jacobs famously argued that this capital is maintained through “cross-use of space,” and James Coleman formalized it as the “closure” of human interactions. Many of these interactions require human mobility, so neighborhoods with higher social capital should be distinguishable by more cohesive mobility networks. To test this hypothesis, I observe the mobility of Chicago residents through a large dataset of smartphone users. I construct a neighborhood-level mobility network for the city and characterize neighborhoods according to their local graph structure. Neighborhoods that are well integrated with their surroundings have higher income and educational attainment. Consistent with social capital theory and routine activity theory in criminology, higher local network integration independently predicts lower rates of violent and property crime. Outliers with higher integration than their neighbors are comprehensible through their social, economic, institutional, and historical context. The methodologies presented provide a new, meaningful, replicable, and inexpensive approach to the structural measurement of neighborhood social capital.
October 30, 2018
Parental Rearing Practices, Cultural Transmission, and Cognitive Development
Avner Seror, Chapman University
Abstract: This paper presents a theory of child development and parental rearing practices. In the model, a benevolent parent seeks to transmit cultural norms to her child, who acquires cognitive skills and develops a capital of appreciation for adopting behaviors that accord with these norms. Our cultural perspective on the issue of cognitive development provides an interpretation grid for various results established in the empirical literature. It also permits to identify the parental characteristics that are conducive to various parenting styles, to child neglect and to child maltreatment.
October 23, 2018
Gender Development and the Brain
Lise Eliot, The Chicago Medical School of Rosalind Franklin University of Medicine & Science
Abstract: Dr. Eliot’s research is centered on brain and gender development, especially the role of neuroplasticity in shaping neural circuitry and behavior. She received an A.B. degree in History & Science from Harvard University, a Ph.D. in Cellular Physiology & Biophysics from Columbia University, and completed a post-doctoral fellowship in the Division of Neuroscience at Baylor College of Medicine. Her studies range from cellular neurophysiology to meta-analyses of brain sex difference and include two highly-praised trade books, What's Going On in There? How the Brain and Mind Develop in the First Five Years of Life, and Pink Brain, Blue Brain: How Small Differences Grow Into Troublesome Gaps. Through both empirical and scholarly research, Dr. Eliot analyzes the interplay between innate biology, sociocultural factors, and individual experience in molding our brains and behavior across the lifespan.
October 16, 2018
Understanding Peer Effects in Educational Decisions: Evidence from Theory and a Field Experience
Karen Ye, The University of Chicago
Abstract:While a large literature documents the presence of peer effects in teenage decision-making, researchers know very little about the underlying mechanisms. In this paper, I focus on the decision to participate in an educational program for high school students. I use a field experiment conducted in three Chicago high schools to disentangle two peer effect channels: social learning (where a peer’s decision is informative about the value of a program) and social utility (where a peer’s participation directly affects the value of a program). I measure students’ sign-up rates for an educational program when I randomize (a) whether a student sees a peer’s decision, and (b) which type of peer’s decision they see. I find large peer effects in the participation decision that are entirely driven by seeing a peer choose not to participate – seeing a peer choose “No” decreases the sign-up rate by 26.9 percentage points. The peer effects are driven by social utility, and seeing a peer choose “No” informs students about the social norms of participation. In this context, smart students’ decisions are especially influential. Finally, while students want to conform to the social norm, I find that they have very biased beliefs about (they drastically underestimate) their peers’ participation.
October 12, 2018
Early Childhood Development in Low Income Settings
Alexandra Brentani, University of Sao Paulo
Abstract: The present study aims to analyze the psychometric properties and general validity of the Caregiver Reported Early Development Instruments (CREDI) short form for the population-level assessment of early childhood development for Brazilian children under age 3. The study analyzed the acceptability, test-retest reliability, internal consistency and discriminant validity of the CREDI short-form tool. The study also analyzed the concurrent validity of the CREDI with a direct observational measure (Inter-American Development Bank's Regional Project on Child Development Indicators; PRIDI). The full sample includes 1,265 Brazilian caregivers of children from 0 to 35 months (678 of which comprising an in-person sample and 587 an online sample). Results from qualitative interviews suggest overall high rates of acceptability. Most of the items showed adequate test-retest reliability, with an average agreement of 84%. Cronbach's alpha suggested adequate internal consistency/inter-item reliability (α > 0.80) for the CREDI within each of the six age groups (0–5, 6–11, 12–17, 18–23, 24–29 and 30–35 months of age). Multivariate analyses of construct validity showed that a significant proportion of the variance in CREDI scores could be explained by child gender and family characteristics, most importantly caregiver-reported cognitive stimulation in the home (p < 0.0001). Regarding concurrent validity, scores on the CREDI were significantly correlated with overall PRIDI scores within the in-person sample at r = 0.46 (p < 0.001). The results suggested that the CREDI short form is a valid, reliable, and acceptable measure of early childhood development for children under the age of 3 years in Brazil.
October 9, 2018
Multi-Generational Approaches to the Study of Social Mobility
Xi Song, The University of Chicago
October 2, 2018
Economics of Parent-Child Interactions and Child Development
Jun Hyung Kim, The University of Chicago
Abstract: Parent-child interactions are determined endogenously by child behavior, making identification of causal effects challenging. We overcome this endogeneity by analyzing a randomized, universal parent-training intervention on parents of preschool children. Evaluation of adolescent outcomes 10 years after the program suggests improvements to externalizing behaviors and wellbeing of children in the intervention group, mediated by changes to parenting during early childhood. These outcomes are not explained adequately by extant models of parent-child interactions, and so we explore alternative explanations. We show that benefits of early childhood interventions extend beyond low-socioeconomic households.
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