Sharp Bounds and Testability of a Roy Model of STEM Major Choices
Bibliographic Data
| ID | 10173251 |
|---|---|
| Authors | Ismaël Mourifié (0000-0002-6765-6288, University of Toronto), Marc Henry (0000-0003-2047-9058), Romuald Méango |
| Year | 2020 |
| Volume | 128 |
| Issue | 8 |
| Pages | 3220-3283 |
| Publication date | 2020-02-24 |
| Peer Reviewed | Yes |
| Open Access | No |
| Type | ARTICLE |
| Venue | Journal of Political Economy (JOURNAL) |
| Journal identifiers | ISSN: 0022-3808 • E-ISSN: 1537-534X |
| Publisher | University of Chicago Press (PUBLISHER • US) |
| DOI | 10.1086/708724 |
| OpenAlex | W3006856757 |
| Language | EN |
| Citations received | 5 |
| References cited | 77 |
We analyze the empirical content of the Roy model, stripped down to its essential features, namely sector specific unobserved heterogeneity and self-selection on the basis of potential outcomes. We characterize sharp bounds on the joint distribution of potential outcomes and testable implications of the Roy self-selection model under an instrumental constraint on the joint distribution of potential outcomes we call stochastically monotone instrumental variable (SMIV). We show that testing the Roy model selection is equivalent to testing stochastic monotonicity of observed outcomes relative to the instrument. We apply our sharp bounds to the derivation of a measure of departure from Roy self-selection to identify values of observable characteristics that induce the most costly misallocation of talent and sector and are therefore prime targets for intervention. Special emphasis is put on the case of binary outcomes, which has received little attention in the literature to date. For richer sets of outcomes, we emphasize the distinction between pointwise sharp bounds and functional sharp bounds, and its importance, when constructing sharp bounds on functional features, such as inequality measures. We analyze a Roy model of college major choice in Canada and Germany within this framework, and we take a new look at the under-representation of women in~STEM
Constraint (computer-aided design · Distribution (mathematics · Econometrics · Economics · Instrumental variable · Joint probability distribution · Mathematical economics · Monotone polygon · Monotonic function · Pointwise · Representation (politics · Selection (genetic algorithm · Statistics · Artificial Intelligence · Computer Science · Economic Policies and Impacts · Fiscal Policy and Economic Growth · Labor market dynamics and wage inequality · Mathematics
Multi-Dimensional Skills and Gender Differences in STEM Majors
Structural bounds on group differences in treatment effects
Partial identification and inference for conditional distributions of treatment effects
Marginal Treatment Effects in the Absence of Instrumental Variables
Scrutinizing the Monotonicity Assumption in IV and fuzzy RD designs
Selection, Investment, and Women's Relative Wages Over Time
Do Faculty Serve as Role Models? The Impact of Instructor Gender on Female Students
Unionism and Wage Rates
Monotone Instrumental Variables
Structural Equations, Treatment Effects, and Econometric Policy Evaluation1
Estimating the Return to Schooling
Local instrumental variables and latent variable models for identifying and bounding treatment effects
Job Preferences, College Major, and the Gender Gap in Earnings
Formulating, Identifying and Estimating the Technology of Cognitive and Noncognitive Skill Formation
Partial observability in bivariate probit models
Mobility and the Return to Education
Shadow Prices, Market Wages, and Labor Supply
Women in STEM
Some Thoughts on the Distribution of Earnings 1
Maternal Education, Home Environments, and the Development of Children and Adolescents
Ability sorting and the returns to college major
Making The Most Out Of Programme Evaluations and Social Experiments
The Empirical Content of the Roy Model
College Major Choice and the Gender Gap
The Technology of Skill Formation
Regression Models and Life-Tables
Healthy, Wealthy, and Wise
Estimating the Technology of Cognitive and Noncognitive Skill Formation
Formulating, Identifying and Estimating the Technology of Cognitive and Noncognitive Skill Formation
The Economics of Human Development and Social Mobility
Why the Apple Doesn’t Fall Far
A Test for Superior Predictive Ability
Nonparametric Identification and Estimation in a Roy Model With Common Nonpecuniary Returns
Choosing the Field of Study in Postsecondary Education
The Selection of High-Skilled Emigrants
Micro Data, Heterogeneity, and the Evaluation of Public Policy
Education and Self-Selection
Productivity Spillovers in Health Care
Heterogeneity, Aggregation, and Market Wage Functions
Selection on Observed and Unobserved Variables
Wage Comparisons--A Selectivity Bias
Returns to Education
The Generalized Roy Model and the Cost-Benefit Analysis of Social Programs
| Unique citing works | 5 |
|---|---|
| Citations per year | 1 |
| Citation span | 2021 - 2026 (6) |
| Citation velocity | current |
| Highly cited | No |
| Citation types | Neutral: 5 |