We analyze four methods to measure unexplained gaps in mean outcomes: three decompositions based on the seminal work of Oaxaca (1973) and Blinder (1973) and an approach involving a seemingly naive regression that includes a group indicator variable. Our analysis yields two principal findings. We...

Taking as our point of departure a model proposed by David Card (2001), we suggest new methods for analyzing wage dispersion in a partially unionized labor market. Card's method disaggregates the labor population into skill categories, which procedure entails some loss of information....

An important goal when analyzing the causal effect of a treatment on an outcome is to understand the mechanisms through which the treatment causally works. We define a causal mechanism effect of a treatment and the causal effect net of that mechanism using the potential outcomes framework. These...

We present a theorem helpful in estimating the mean and variance of a linear function with arbitrary multivariate randomness in its coefficients and variables. We derive a generalized decomposition result from two random linear functions in which the result can be applied to most models using...

In the book Myth and Measurement, Card and Krueger (1995) examine the economic impact of the 1989 minimum wage hike on the welfare of 110 firms which employ a disproportionate number of minimum-wage workers. Their results show mixed evidence that excess returns associated with news about the...

This paper introduces a new and simple decomposition method for a binary choice model that is equivalent to the Blinder-Oaxaca decomposition analysis for wage differentials. The decomposition method is first developed for a single probit model and later generalized to a simultaneous equations...

In the time domain, the observed cyclical behavior of the real wage hides a range of economic influences that give rise to cycles of differing lengths and amplitudes. This may serve to produce a distorted picture of wage cyclicality. Here, we employ frequency domain methods that allow us...

We address the bias from using potential vs. actual experience in earnings models. Statistical tests reject the classical errors-in-variable framework. The nature of the measurement error is best viewed as a model misspecification problem. We correct for this by modeling actual experience as a...

We analyze the role of selection bias in generating the changes in the observed distribution of female hourly wages in the United States using CPS data for the years 1975 to 2020. We account for the selection bias from the employment decision by modeling the distribution of the number of working...

We employ CPS data to analyze the sources of hourly real wage changes in the United States for 1976 to 2016 at various quantiles of the wage distribution. We account for the selection bias from the annual hours of work decision by developing and implementing an estimator for nonseparable...