Estimation of a transformation model with truncation, interval observation and time-varying covariates
Abrevaya (1999b) considered estimation of a transformation model in the presence of left-truncation. This paper observes that a cross-sectional version of the statistical model considered in Frederiksen, Honor, and Hu (2007) is a generalization of the model considered by Abrevaya (1999b) and the generalized model can be estimated by a pairwise comparison version of one of the estimators in Frederiksen, Honor, and Hu (2007). Specifically, our generalization will allow for discretized observations of the dependent variable and for piecewise constant time- varying explanatory variables.
Prenatal sex selection and girls’ well-being? evidence from India
The paper studies the impact of prenatal sex selection on the well-being of girls by analyzing changes in children?s nutritional status and mortality during the years since the diffusion of sex-selective abortion in India. We use the ratio of male to female births in the year and state in which a child was born as a proxy for parental access to prenatal sex-selection. Using repeated cross-sections from a rich survey dataset, we show that high sex ratios at birth reflect the practice of sex-selective abortion. We then exploit the large regional and time variations in the incidence of ...
Easy Bootstrap-Like Estimation of Asymptotic Variances
The bootstrap is a convenient tool for calculating standard errors of the parameter estimates of complicated econometric models. Unfortunately, the bootstrap can be very time-consuming. In a recent paper, Honor and Hu (2017), we propose a ?Poor (Wo)man's Bootstrap? based on one-dimensional estimators. In this paper, we propose a modified, simpler method and illustrate its potential for estimating asymptotic variances.
Selection Without Exclusion
It is well understood that classical sample selection models are not semiparametrically identified without exclusion restrictions. Lee (2009) developed bounds for the parameters in a model that nests the semiparametric sample selection model. These bounds can be wide. In this paper, we investigate bounds that impose the full structure of a sample selection model with errors that are independent of the explanatory variables but have unknown distribution. We find that the additional structure in the classical sample selection model can significantly reduce the identified set for the parameters ...
Estimation of panel data regression models with two-sided censoring or truncation
This paper constructs estimators for panel data regression models with individual specific heterogeneity and two-sided censoring and truncation. Following Powell (1986) the estimation strategy is based on moment conditions constructed from re-censored or re-truncated residuals. While these moment conditions do not identify the parameter of interest, they can be used to motivate objective functions that do. We apply one of the estimators to study the effect of a Danish tax reform on household portfolio choice. The idea behind the estimators can also be used in a cross sectional setting.
The Effect of the Patient Protection and Affordable Care Act Medicaid Expansions on Financial Wellbeing
We examine the effect of the Medicaid expansions under the 2010 Patient Protection and Affordable Care Act (ACA) on consumer, financial outcomes using data from a major credit reporting agency for a large, national sample of adults. We employ the synthetic control method to compare individuals living in states that expanded Medicaid to those that did not. We find that the Medicaid expansions significantly reduced the number of unpaid bills and the amount of debt sent to third-party collection agencies among those residing in zip codes with the highest share of low-income, uninsured ...
Rushing into American Dream? House Prices, Timing of Homeownership, and Adjustment of Consumer Credit
In this paper we use a large panel of individuals from Consumer Credit Panel dataset to study the timing of homeownership as a function of credit constraints and expectations of future house price. Our panel data allows us to track individuals over time and we model the transition probability of their first home purchase. We find that in MSAs with highest quartile house price growth, the median individual become homeowners earlier by 5 years in their lifecycle compared to MSAs with lowest quartile house price growth. The result suggests that the effect of expectation dominates the effect of ...
Displacement, asymmetric information and heterogeneous human capital
In a seminal paper Gibbons and Katz (1991; GK) develop and empirically test an asymmetric information model of the labor market. The model predicts that wage losses following displacement should be larger for layoffs than for plant closings, which was borne out by data from the Displaced Workers Survey (DWS). In this paper, we take advantage of many more years of DWS data to examine how the difference in wage losses across plant closing and layoff varies with race and gender. We find that the differences between white males and the other groups are striking and complex. The "lemons" ...
Simpler Bootstrap Estimation of the Asymptotic Variance of U-statistic Based Estimators
The bootstrap is a popular and useful tool for estimating the asymptotic variance of complicated estimators. Ironically, the fact that the estimators are complicated can make the standard bootstrap computationally burdensome because it requires repeated re-calculation of the estimator. In Honor and Hu (2015), we propose a computationally simpler bootstrap procedure based on repeated re-calculation of one-dimensional estimators. The applicability of that approach is quite general. In this paper, we propose an alternative method which is specific to extremum estimators based on U-statistics. ...
Poor (Wo)man’s Bootstrap
The bootstrap is a convenient tool for calculating standard errors of the parameters of complicated econometric models. Unfortunately, the fact that these models are complicated often makes the bootstrap extremely slow or even practically infeasible. This paper proposes an alternative to the bootstrap that relies only on the estimation of one-dimensional parameters. The paper contains no new difficult math. But we believe that it can be useful.