A Note on Adapting Propensity Score Matching and Selection Models to Choice Based Samples

The probability of selection into treatment plays an important role in matching and selection models. However, this probability can often not be consistently estimated, because of choice-based sampling designs with unknown sampling weights. This note establishes that the selection and matching procedures can be implemented using propensity scores fit on choice-based samples with misspecified weights, because the odds ratio of the propensity score fit on the choice-based sample is monotonically related to the odds ratio of the true propensity scores.choice-based sampling, matching models, propensity scores, selection models

Earnings Functions and Rates of Return

The internal rate of return to schooling is a fundamental economic parameter that is often used to assess whether expenditure on education should be increased or decreased. This paper considers alternative approaches to estimating marginal internal rates of return for different schooling levels. We implement a general nonparametric approach to estimate marginal internal rates of return that take into account tuition costs, income taxes and nonlinearities in the earnings-schooling-experience relationship. The returns obtained by the more general method differ substantially from Mincer returns in levels and in their evolution over time. They indicate relatively larger returns to graduating from high school than from graduating from college, although both have been increasing over time.schooling, marginal internal rate of return, nonparametric estimation

Fifty Years of Mincer Earnings Regressions

The Mincer earnings function is the cornerstone of a large literature in empirical economics. This paper discusses the theoretical foundations of the Mincer model and examines the empirical support for it using data from Decennial Censuses and Current Population Surveys. While data from 1940 and 1950 Censuses provide some support for Mincer's model, data from later decades are inconsistent with it. We examine the importance of relaxing functional form assumptions in estimating internal rates of return to schooling and of accounting for taxes, tuition, nonlinearity in schooling, and nonseparability between schooling and work experience. Inferences about trends in rates of return to high school and college obtained from our more general model differ substantially from inferences drawn from estimates based on a Mincer earnings regression. Important differences also arise between cohort-based and cross-sectional estimates of the rate of return to schooling. In the recent period of rapid technological progress, widely used cross-sectional applications of the Mincer model produce dramatically biased estimates of cohort returns to schooling. We also examine the implications of accounting for uncertainty and agent expectation formation. Even when the static framework of Mincer is maintained, accounting for uncertainty substantially affects the return estimates. Considering the sequential resolution of uncertainty over time in a dynamic setting gives rise to option values, which fundamentally changes the analysis of schooling decisions. In the presence of sequential resolution of uncertainty and option values, the internal rate of return - a cornerstone of classical human capital theory - is not a useful guide to policy analysis.

Feeder Cattle Basis in South Carolina 2000-2004

Livestock Production/Industries,

EARNINGS FUNCTIONS AND RATES OF RETURN

The internal rate of return to schooling is a fundamental economic parameter that is often used to assess whether expenditure on education should be increased or decreased. This paper considers alternative approaches to estimating marginal internal rates of return for different schooling levels. We implement a general nonparametric approach to estimate marginal internal rates of return that take into account tuition costs, income taxes and nonlinearities in the earnings-schooling-experience relationship. The returns obtained by the more general method differ substantially from Mincer returns in levels and in their evolution over time. They indicate relatively larger returns to graduating from high school than from graduating from college, although both have been increasing over time.

Earnings Functions, Rates of Return and Treatment Effects: The Mincer Equation and Beyond

This paper considers the interpretation of "Mincer rates of return." We test and reject the Mincer model. It fails to track the time series of true returns. We show how repeated cross section and panel data improves the ability of analysts to estimate the ex ante and ex post marginal rate of returns. Accounting for sequential revelation of information calls into question the validity of the internal rate of return as a tool for policy analysis. The large estimated psychic costs of schooling found in recent work helps to explain why persons do not attend school even though the financial rewards for doing so are high. We present methods for computing distributions of ex post and ex ante returns.

Tests of an Indifference Rule in Variable-Delay and Double-Reward Choice Procedures with Humans

Four-hundred and fifty participants were recruited from Amazon Mechanical Turk across three experiments to test the predictions of a hyperbolic discounting equation in accounting for human choices involving variable delays or multiple rewards (Mazur, 1984, 1986). In Experiment 1, participants made hypothetical choices between two monetary alternatives, one consisting of a fixed delay and another consisting of two delays of equal probability (i.e., a variable-delay procedure). In Experiment 2, participants made hypothetical monetary choices between a single, immediate reward and two rewards, one immediate and one delayed (i.e., a double-reward procedure). Experiment 3 also used a double-reward procedure, but with two delayed rewards. Participants in all three experiments also completed a standard delay-discounting task. Finally, three reward amounts were tested in each type of task ($100,$1000, and $5000). In the double-reward conditions (Experiments 2 and 3), the results were in good qualitative and quantitative agreement with Mazur’s model (1984, 1986). In contrast, when participants made choices involving variable delays (Experiment 1), there was relatively poor qualitative and quantitative agreement with this model. These results, along with our previous findings, suggest the structure of questions in hypothetical tasks with humans can be a strong determinant of the choice pattern

Human Choices Between Variable and Fixed Rewards in Hypothetical Variable-Delay and Double-Reward Discounting Procedures

Prior research has shown that nonhumans show an extreme preference for variable- over fixed-delays to reinforcement. This well-established preference for variability occurs because a reinforcer’s strength or “value” decreases according to a curvilinear function as its delay increases. The purpose of the present experiments was to investigate whether this preference for variability occurs with human participants making hypothetical choices. In three experiments, participants recruited from Amazon Mechanical Turk made choices between variable and fixed monetary rewards. In a variable-delay procedure, participants repeatedly chose between a reward delivered either immediately or after a delay (with equal probability) and a reward after a fixed delay (Experiments 1 and 2). In a double-reward procedure, participants made choices between an alternative consisting of two rewards, one delivered immediately and one after a delay, and a second alternative consisting of a single reward delivered after a delay (Experiments 1 and 3). Finally, all participants completed a standard delay-discounting task. Although we observed both curvilinear discounting and magnitude effects in the standard discounting task, we found no consistent evidence of a preference for variability—as predicted by two prominent models of curvilinear discounting (i.e., a simple hyperbola and a hyperboloid)—in our variable-delay and double-reward procedures. This failure to observe a preference for variability may be attributed to the hypothetical, rule-governed nature of choices in the present study. In such contexts, participants may adopt relatively simple strategies for making more complex choices

A note on adapting propensity score matching and selection models to choice based samples

The probability of selection into treatment plays an important role in matching and selection models. However, this probability can often not be consistently estimated, because of choice-based sampling designs with unknown sampling weights. This note establishes that the selection and matching procedures can be implemented using propensity scores fit on choice-based samples with misspecified weights, because the odds ratio of the propensity score fit on the choice-based sample is monotonically related to the odds ratio of the true propensity scores