25. Multiple Imputation for Nonresponse in Surveys. By D. B. Rubin. ISBN 0 471 08705 X. Wiley, Chichester, 1987. 258 pp. £30.25.

Multiple Imputation for Nonresponse in Surveys

The Theory of Matrices. By F R. Gantmacher. Two volumes, pp. 374 and 276. 1959. (Translated from the Russian by K. A. Hirsch; Chelsea Publishing Company, New York)

A critical question facing experimental economists is whether behavior inside the laboratory is a good indicator of behavior outside the laboratory. To address that question, we build a model in which the choices that individuals make depend not just on financial implications, but also on the nature and extent of scrutiny by others, the particular context in which a decision is embedded, and the manner in which participants and tasks are selected. We present empirical evidence demonstrating the importance of these various factors. To the extent that lab and naturally occurring environments systematically differ on any of these dimensions, the results obtained inside and outside the lab need not correspond. Focusing on experiments designed to measure social preferences, we discuss the extent to which the existing laboratory results generalize to naturally-occurring markets. We summarize cases where the lab may understate the importance of social preferences as well as instances in which the lab might exaggerate their importance. We conclude by emphasizing the importance of interpreting laboratory and field data through the lens of theory.

/pdf/what-do-laboratory-experiments-measuring-social-preferences-178u4j8nii.pdf

What Do Laboratory Experiments Measuring Social Preferences Reveal About the Real World

Equality of Educational Opportunity.

Teacher training, teacher quality and student achievement

http://public.econ.duke.edu/~psarcidi/arcidimetrics.pdf

Ability sorting and the returns to college major

Modeling College Major Choices using Elicited Measures of Expectations and Counterfactuals. NBER Working Paper No. 15729.

We adapt the expectation–maximization algorithm to incorporate unobserved heterogeneity into conditional choice probability (CCP) estimators of dynamic discrete choice problems. The unobserved heterogeneity can be time-invariant or follow a Markov chain. By developing a class of problems where the difference in future value terms depends on a few conditional choice probabilities, we extend the class of dynamic optimization problems where CCP estimators provide a computationally cheap alternative to full solution methods. Monte Carlo results confirm that our algorithms perform quite well, both in terms of computational time and in the precision of the parameter estimates.

https://www.jstor.org/stable/pdfplus/41336537.pdf

Conditional choice probability estimation of dynamic discrete choice models with unobserved heterogeneity

http://public.econ.duke.edu/~psarcidi/subjective.pdf

Modeling college major choices using elicited measures of expectations and counterfactuals

This paper addresses how changing the admission and financial aid rules at colleges affects future earnings. I estimate a structural model of the following decisions by individuals: where to submit applications, which school to attend, and what field to study. The model also includes decisions by schools as to which students to accept and how much financial aid to offer. Simulating how black educational choices would change were they to face the white admission and aid rules shows that race-based advantages had little effect on earnings. However, removing race-based advantages does affect black educational outcomes. In particular, removing advantages in admissions substantially decreases the number of black students at top-tier schools, while removing advantages in financial aid causes a decrease in the number of blacks who attend college.

/pdf/affirmative-action-in-higher-education-how-do-admission-and-2brbdkfulb.pdf

Peter Arcidiacono

Papers

Ability sorting and the returns to college major

Modeling College Major Choices using Elicited Measures of Expectations and Counterfactuals. NBER Working Paper No. 15729.

Conditional choice probability estimation of dynamic discrete choice models with unobserved heterogeneity

Modeling college major choices using elicited measures of expectations and counterfactuals

Affirmative Action in Higher Education: How do Admission and Financial Aid Rules Affect Future Earnings?