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Source: Journal of Business and Economic Statistics
Resulting in 12 citations.
1. Angrist, Joshua D.
Newey, Whitney K.
Over-Identification Tests in Earnings Functions with Fixed Effects
Journal of Business and Economic Statistics 9,3 (July 1991): 317-323.
Also: http://www.jstor.org/stable/1391296
Cohort(s): NLSY79
Publisher: American Statistical Association
Keyword(s): Earnings; Education; Educational Attainment; Educational Returns; Modeling, Fixed Effects; Research Methodology; Unions; Wages

The fixed-effects model for panel data imposes restrictions on coefficients from regressions of all leads and lags of the dependent variable on all leads and lags of right-side variables. In the standard fixed-effects model, the omnibus goodness-of-fit statistic is shown to simplify to the degree of freedom times the R square from a regression analysis of covariance residuals on all leads and lags on the right-side variables. This result is applied to test models for the union-wage effect using data from the NLSY. Although schooling is often treated as time-invariant, schooling increases over a 5-year period for nearly 20 percent of continuously employed men in the NLSY. The analysis of covariance estimate of the returns to schooling is precisely estimated and roughly twice as large as the ordinary least squares estimate. In contrast to the union-wage-effects equation, the omnibus goodness-of-fit tests suggest that the fixed-effects assumption may be inappropriate for human capital earnings functions. [ABI/INFORM]
Bibliography Citation
Angrist, Joshua D. and Whitney K. Newey. "Over-Identification Tests in Earnings Functions with Fixed Effects." Journal of Business and Economic Statistics 9,3 (July 1991): 317-323.
2. Chen, Xuerong
Leung, Denis Heng-Yan
Qin, Jing
Non-ignorable Missing Data, Single Index Propensity Score and Profile Synthetic Distribution Function
Journal of Business and Economic Statistics published online (7 December 2020): DOI: 10.1080/07350015.2020.1860065.
Also: https://www.tandfonline.com/doi/full/10.1080/07350015.2020.1860065
Cohort(s): Children of the NLSY79
Publisher: American Statistical Association
Keyword(s): Missing Data/Imputation; Peabody Picture Vocabulary Test (PPVT); Propensity Scores

In missing data problems, missing not at random is difficult to handle since the response probability or propensity score is confounded with the outcome data model in the likelihood. Existing works often assume the propensity score is known up to a finite dimensional parameter. We relax this assumption and consider an unspecified single index model for the propensity score. A pseudo-likelihood based on the complete data is constructed by profiling out a synthetic distribution function that involves the unknown propensity score. The pseudo-likelihood gives asymptotically normal estimates. Simulations show the method compares favourably with existing methods.
Bibliography Citation
Chen, Xuerong, Denis Heng-Yan Leung and Jing Qin. "Non-ignorable Missing Data, Single Index Propensity Score and Profile Synthetic Distribution Function." Journal of Business and Economic Statistics published online (7 December 2020): DOI: 10.1080/07350015.2020.1860065.
3. Durlauf, Steven
Kourtellos, Andros
Tan, Chih Ming
Status Traps
Journal of Business and Economic Statistics 35,2 (2017): 265-287.
Also: http://www.tandfonline.com/doi/abs/10.1080/07350015.2016.1189339
Cohort(s): Children of the NLSY79, NLSY79, NLSY79 Young Adult
Publisher: American Statistical Association
Keyword(s): Earnings; Intergenerational Patterns/Transmission; Mobility, Economic; Panel Study of Income Dynamics (PSID); Peabody Individual Achievement Test (PIAT- Math); Peabody Picture Vocabulary Test (PPVT); Pearlin Mastery Scale; Personality/Big Five Factor Model or Traits; Personality/Ten-Item Personality Inventory-(TIPI); Poverty; Rosenberg Self-Esteem Scale (RSES) (see Self-Esteem)

In this paper, we explore nonlinearities in the intergenerational mobility process using threshold regression models. We uncover evidence of threshold effects in children's outcomes based on parental education and cognitive and non-cognitive skills as well as their interaction with offspring characteristics. We interpret these thresholds as organizing dynastic earnings processes into "status traps". Status traps, unlike poverty traps, are not absorbing states. Rather, they reduce the impact of favorable shocks for disadvantaged children and so inhibit upward mobility in ways not captured by linear models. Our evidence of status traps is based on three complementary datasets; i.e., the PSID, the NLSY, and US administrative data at the commuting zone level, which together suggest that the threshold-like mobility behavior we observe in the data is robust for a range of outcomes and contexts.
Bibliography Citation
Durlauf, Steven, Andros Kourtellos and Chih Ming Tan. "Status Traps." Journal of Business and Economic Statistics 35,2 (2017): 265-287.
4. Ferrall, Christopher
Unemployment Insurance Eligibility and the Transition from School to Work in Canada and the United States
Journal of Business and Economic Statistics 15,2 (April 1997): 115-129.
Also: http://www.jstor.org/stable/1392300
Cohort(s): NLSY79
Publisher: American Statistical Association
Keyword(s): Benefits, Insurance; Job Search; Labor Market Demographics; Transition, School to Work; Unemployment Insurance

To study how the design of unemployment insurance affects people leaving school to find jobs, a model of job search in the presence of UI is developed and estimated for the U.S. and Canada. The level of UI benefits depends upon previous earnings, a fact which creates opposing incentives for unemployed people not receiving benefits. Which of these opposing incentives dominates the other is found to differ across demographic groups within each country. Changes in UI policy therefore can have very different effects on different individuals. The major differences found in the transition from school to work in Canada and the U.S. are a lower rate of job offer arrivals and a lower rate of offer rejections in Canada. Within each country, offer arrival rates differ across individuals much more than offer rejection rates.
Bibliography Citation
Ferrall, Christopher. "Unemployment Insurance Eligibility and the Transition from School to Work in Canada and the United States." Journal of Business and Economic Statistics 15,2 (April 1997): 115-129.
5. Flinn, Christopher Jay
Equilibrium Wage and Dismissal Processes
Journal of Business and Economic Statistics 15,2 (April 1997): 221-236.
Also: http://www.jstor.org/stable/1392307
Cohort(s): NLSY79
Publisher: American Statistical Association
Keyword(s): Wage Dynamics; Wage Equations; Wage Theory; Wages

An equilibrium model is developed and estimated of the labor market in which inefficient employees are systematically eliminated from the sector of the market characterized by asymmetric information and moral hazard. Systematic selection on the distribution of productivity characteristics produces wage sequences that are increasing in tenure for employees never previously terminated even in the absence of long-term contracting between employees and individual firms. Sufficient conditions are provided for there to exist a unique termination-contract type of equilibrium. The equilibrium model is estimated using microlevel data from the national Longitudinal Survey of Youth panel. Photocopy available from ABI/INFORM
Bibliography Citation
Flinn, Christopher Jay. "Equilibrium Wage and Dismissal Processes." Journal of Business and Economic Statistics 15,2 (April 1997): 221-236.
6. Frandsen, Brigham R.
Testing Censoring Point Independence
Journal of Business and Economic Statistics 37,3 (2019): 496-505.
Also: https://www.tandfonline.com/doi/full/10.1080/07350015.2017.1383261
Cohort(s): NLSY79
Publisher: American Statistical Association
Keyword(s): Panel Study of Income Dynamics (PSID); Statistical Analysis; Survey of Income and Program Participation (SIPP); Unemployment Duration

Identification in censored regression analysis and hazard models of duration outcomes relies on the condition that censoring points are conditionally independent of latent outcomes, an assumption which may be questionable in many settings. This article proposes a test for this assumption based on a Cramer-von Mises-like test statistic comparing two different nonparametric estimators for the latent outcome cdf: the Kaplan-Meier estimator, and the empirical cdf conditional on the censoring point exceeding (for right-censored data) the cdf evaluation point. The test is consistent and has power against a wide variety of alternatives. Applying the test to unemployment duration data from the NLSY, the SIPP, and the PSID suggests the assumption is frequently suspect.
Bibliography Citation
Frandsen, Brigham R. "Testing Censoring Point Independence." Journal of Business and Economic Statistics 37,3 (2019): 496-505.
7. Huber, Martin
Causal Pitfalls in the Decomposition of Wage Gaps
Journal of Business and Economic Statistics 33,2 (2015): 179-191.
Also: http://www.tandfonline.com/doi/abs/10.1080/07350015.2014.937437
Cohort(s): NLSY79
Publisher: American Statistical Association
Keyword(s): Ethnic Differences; Racial Differences; Wage Gap

The decomposition of gender or ethnic wage gaps into explained and unexplained components (often with the aim to assess labor market discrimination) has been a major research agenda in empirical labor economics. This paper demonstrates that conventional decompositions, no matter whether linear or non-parametric, are equivalent to assuming a (probably too) simple model of mediation (aimed at assessing causal mechanisms) and may therefore lack causal interpretability. The reason is that decompositions typically control for post-birth variables that lie on the causal pathway from gender/ethnicity (which are determined at or even before birth) to wage but neglect potential endogeneity that may arise from this approach. Based on the newer literature on mediation analysis, we therefore provide more attractive identifying assumptions and discuss non-parametric identification based on reweighting.
Bibliography Citation
Huber, Martin. "Causal Pitfalls in the Decomposition of Wage Gaps." Journal of Business and Economic Statistics 33,2 (2015): 179-191.
8. Ishihara, Takuya
Panel Data Quantile Regression for Treatment Effect Models
Journal of Business and Economic Statistics published online (1 April 2022): DOI: 10.1080/07350015.2022.2061495.
Also: https://www.tandfonline.com/doi/full/10.1080/07350015.2022.2061495
Cohort(s): Children of the NLSY79
Publisher: American Statistical Association
Keyword(s): Cognitive Development; Modeling; Monte Carlo; Peabody Individual Achievement Test (PIAT- Reading); Statistical Analysis; Television Viewing

In this study, we develop a novel estimation method for quantile treatment effects (QTE) under rank invariance and rank stationarity assumptions. Ishihara (2020) explores identification of the nonseparable panel data model under these assumptions and proposes a parametric estimation based on the minimum distance method. However, when the dimensionality of the covariates is large, the minimum distance estimation using this process is computationally demanding. To overcome this problem, we propose a two-step estimation method based on the quantile regression and minimum distance methods. We then show the uniform asymptotic properties of our estimator and the validity of the nonparametric bootstrap. The Monte Carlo studies indicate that our estimator performs well in finite samples. Finally, we present two empirical illustrations, to estimate the distributional effects of insurance provision on household production and TV watching on child cognitive development.
Bibliography Citation
Ishihara, Takuya. "Panel Data Quantile Regression for Treatment Effect Models." Journal of Business and Economic Statistics published online (1 April 2022): DOI: 10.1080/07350015.2022.2061495.
9. Levine, Phillip B.
Zimmerman, David J.
The Benefit of Additional High School Math and Science Classes for Young Men and Women: Evidence from Longitudinal Data
Journal of Business and Economic Statistics 13,2 (April 1995): 137-149.
Also: http://www.jstor.org/stable/1392368
Cohort(s): NLSY79
Publisher: American Statistical Association
Keyword(s): Armed Forces Qualifications Test (AFQT); Armed Services Vocational Aptitude Battery (ASVAB); College Graduates; Family Background and Culture; GED/General Educational Diploma/General Equivalency Degree/General Educational Development; High School Curriculum; Labor Market Outcomes; Occupational Choice; Training; Wage Dynamics

This paper examines the effects of more technical training in high school on labor market outcomes for men and women. We consider the effect of taking more high school math and science classes on wages, occupational choice, and college major. The results show a positive return to additional courses in math for women who eventually go on to graduate from college. No significant return to math is consistently observed for other groups of workers and high school science courses have no effect on wages for any group of workers. The effect of additional math classes for female college graduates may be attributed to their increased propensity to major in technical fields in college and to enter more technical, male-dominated jobs.
Bibliography Citation
Levine, Phillip B. and David J. Zimmerman. "The Benefit of Additional High School Math and Science Classes for Young Men and Women: Evidence from Longitudinal Data." Journal of Business and Economic Statistics 13,2 (April 1995): 137-149.
10. Molinari, Francesca
Missing Treatments
Journal of Business and Economic Statistics 28,1 (January 2010): 82-95.
Also: http://pubs.amstat.org/doi/abs/10.1198/jbes.2009.07161
Cohort(s): NLSY79
Publisher: American Statistical Association
Keyword(s): Drug Use; Employment; Nonresponse; Treatment Response: Monotone, Semimonotone, or Concave-monotone

This article analyzes the problem of identifying a treatment effect with imperfect observability of the treatment received by the population. Imperfect observability may be due to item/survey nonresponse or to noncompliance with randomly assigned treatments. I derive sharp worst-case bounds that are a function of the available prior information on the distribution of missing treatments. Under the assumption of monotone treatment response, I show that prior information on the distribution of missing treatments is not necessary to get sharp informative bounds. I illustrate the results with an empirical analysis of drug use and employment using data from the National Longitudinal Survey of Youth. [ABSTRACT FROM AUTHOR]

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Bibliography Citation
Molinari, Francesca. "Missing Treatments." Journal of Business and Economic Statistics 28,1 (January 2010): 82-95.
11. Rendon, Silvio Roberto
Does Wealth Explain Black-White Differences in Early Employment Careers?
Journal of Business and Economic Statistics 25,4 (October 2007): 484-500.
Also: http://pubs.amstat.org/doi/abs/10.1198/073500107000000124
Cohort(s): NLSY79
Publisher: American Statistical Association
Keyword(s): Discrimination; Economics of Minorities; Income; Job Search; Labor Market Demographics; Racial Differences; Wage Gap; Wealth

In this article I inquire about the effects initial wealth has on black-white differences in early employment careers. I set up a dynamic model in which individuals simultaneously search for a job and accumulate wealth, and fit it to data from the National Longitudinal Survey (1979-cohort). Regime changes and decompositions of racial differences reveal that differences in the labor market environment and in preferences account fully for racial gaps in wealth and in wages persisting several years after high school graduation. Differences in initial wealth partially explain differences in early employment careers.
Bibliography Citation
Rendon, Silvio Roberto. "Does Wealth Explain Black-White Differences in Early Employment Careers?" Journal of Business and Economic Statistics 25,4 (October 2007): 484-500.
12. Sun, Baoluo
Tan, Zhiqiang
High-Dimensional Model-Assisted Inference for Local Average Treatment Effects With Instrumental Variables
Journal of Business and Economic Statistics published online (27 September 2021): DOI: 10.1080/07350015.2021.1970575.
Also: https://www.tandfonline.com/doi/full/10.1080/07350015.2021.1970575
Cohort(s): Young Men
Publisher: American Statistical Association
Keyword(s): Educational Returns; Modeling, Instrumental Variables; Statistical Analysis

Consider the problem of estimating the local average treatment effect with an instrument variable, where the instrument unconfoundedness holds after adjusting for a set of measured covariates. Several unknown functions of the covariates need to be estimated through regression models, such as instrument propensity score and treatment and outcome regression models. We develop a computationally tractable method in high-dimensional settings where the numbers of regression terms are close to or larger than the sample size. Our method exploits regularized calibrated estimation for estimating coefficients in these regression models, and then employs a doubly robust point estimator for the treatment parameter. We provide rigorous theoretical analysis to show that the resulting Wald confidence intervals are valid for the treatment parameter under suitable sparsity conditions if the instrument propensity score model is correctly specified, but the treatment and outcome regression models may be misspecified. In this sense, our confidence intervals are instrument propensity score model based, and treatment and outcome regression models assisted. For existing high-dimensional methods, valid confidence intervals are obtained for the treatment parameter if all three models are correctly specified. We evaluate the proposed method via extensive simulation studies and an empirical application to estimate the returns to education. The methods are implemented in the R package RCAL.
Bibliography Citation
Sun, Baoluo and Zhiqiang Tan. "High-Dimensional Model-Assisted Inference for Local Average Treatment Effects With Instrumental Variables." Journal of Business and Economic Statistics published online (27 September 2021): DOI: 10.1080/07350015.2021.1970575.