James Heckman

2030 Agenda, 6, 22 accelerator, 289, 292, 311, 355 actor-oriented model, 13 agent computing, 13, 27 agent-based modelling, 13 ai Page 1 Index 2030 Agenda, 6, 22 accelerator, 289, 292, 311, 355 actor-oriented model, 13 agent computing, 13, 27 agent-based modelling, 13 aid data, 240 aid effectiveness, 231 aid-to-governmentexpenditure ratio, 240 Akamatsu, Kaname, 151 allocation profile, 26, 111 Arthur, Brian, 8 Axelrod, Robert, 14, 150 Axtell, Robert, 13, 14 behavioural rules, 30 benchmark analysis, 85 big push theory, 291 bottleneck, 25, 189, 289, 311, 352 idiosyncratic bottleneck, 189 systemic bottleneck, 313 bottom-up multi-agent models, 13 Boudon, Raymond, 30 budgetary frontier, 190 bureaucrat, 110 calibration, 130 Carley, Kathleen, 144 causal inference, 34 central authority, 117 Coleman’s boat, 31 Coleman, James, 30 collateral indicator, 56, 106 collective action, 210 complexity science, 24 …

This paper evaluates the causal impacts of an early childhood home visiting program for which treatment is randomly assigned. We estimate multivariate latent skill profiles for individual children and compare treatments and controls. We identify average treatment effects of skills on performance in a variety of tasks. The program substantially improves child language and cognitive, fine motor, and social-emotional skills development. Impacts are especially strong in the most disadvantaged communities. We go beyond reporting treatment effects as unweighted sums of item scores. Instead, we examine how the program affects the latent skills generating item scores and how the program affects the mapping between skills and item scores. We find that enhancements in latent skills explain at least 90% of conventional unweighted treatment effects on language and cognitive tasks. The program enhances some components of the function mapping latent skills into item scores. This can be interpreted as a measure of enhanced productivity in using given bundles of skills to perform tasks. This source explains at most 10% of the average estimated treatment effects.

This study explores relationships between parental resource trajectories and child development, and their implications for intergenerational mobility. By modifying the child skill formation technology to incorporate new skills during adolescence, we analyze the importance of the timing of family resources on life outcomes, educational attainment and participation in crime. Parental financial resources partially offset deficiencies in nonpecuniary inputs to children's human capital. Estimates of the intergenerational influence on child outcomes are strongly influenced by the choice of lifetime versus snapshot parental income measures. The most predictive ages of children when family resources are measured vary by the outcome analyzed.

This paper develops a new framework for estimating the causal impacts on child skills and the mechanisms producing these impacts using data from a randomized control study of a widely evaluated early-childhood home visiting program. We show the feasibility of replicating the program at scale. We report estimates from standard procedures for reporting treatment effects as unweighted averages item scores and compare them with estimates adjusting for item difficulties. Such adjustments produce more interpretable estimates. We go beyond treatment effects and estimate individual-specific latent skills, comparing treatment and control skills and their impacts on test scores.

This paper examines the econometric causal model and the interpretation of empirical evidence based on thought experiments that was developed by Ragnar Frisch and Trygve Haavelmo. We compare the econometric causal model with two currently popular causal frameworks: the Neyman–Rubin causal model and the Do-Calculus. The Neyman–Rubin causal model is based on the language of potential outcomes and was largely developed by statisticians. Instead of being based on thought experiments, it takes statistical experiments as its foundation. The Do-Calculus, developed by Judea Pearl and co-authors, relies on Directed Acyclic Graphs (DAGs) and is a popular causal framework in computer science and applied mathematics. We make the case that economists who uncritically use these frameworks often discard the substantial benefits of the econometric causal model to the detriment of more …

We analyze the role of maternal endowments and investments in delivering small for gestational age babies. We estimate the effect of maternal endowments on birth outcomes and decompose it into a direct, “biological” effect and a “choice” effect mediated by maternal behaviors. We estimate the causal effects of maternal education and prenatal smoking and whether women with different traits have different returns. The findings highlight the importance of maternal cognition, personality traits, and physical fitness in influencing birth outcomes, with significant heterogeneity in the effects of education and smoking across different maternal physical traits, suggesting targeted prenatal interventions for less healthy women.

This paper considers the problem of making inferences about the effects of a program on multiple outcomes when the assignment of treatment status is imperfectly randomized. By imperfect randomization we mean that treatment status is reassigned after an initial randomization on the basis of characteristics that may be observed or unobserved by the analyst. We develop a partial identification approach to this problem that makes use of information limiting the extent to which randomization is imperfect to show that it is still possible to make nontrivial inferences about the effects of the program in such settings. We consider a family of null hypotheses in which each null hypothesis specifies that the program has no effect on one of many outcomes of interest. Under weak assumptions, we construct a procedure for testing this family of null hypotheses in a way that controls the familywise error rate – the probability of even …

OBJECTIVESDelayed child skill development is a common phenomenon in low-and middle-income countries. Effective and low-cost strategies suitable for application to less-developed countries are needed. We summarize empirical findings from recent papers that study a replication of the Jamaica Reach Up and Learn home visiting program in China, China REACH, and compare child skill growth profiles in the China Reach Up and Jamaica interventions.METHODSDifferent interventions often use different measures for assessing early childhood skill development. To estimate the growth of underlying skills across programs, we address the challenge that different programs use different assessments. We use a modified version of the Rasch model to anchor scores on common items to estimate skill development.RESULTSLanguage skill growth curves are comparable for both interventions. This pattern is …