We describe methods of combining administrative and survey data to improve the measurement of income. We begin by decomposing the total survey error in the mean of survey reports of dollars received from a government transfer program. We decompose this error into three parts, generalized...

Aggregate under-reporting of household spending in the Consumer Expenditure Survey (CE) can result from two fundamental types of measurement errors: higher-income households (who presumably spend more than average) are under-represented in the CE estimation sample, or there is systematic...

Previous research on prices of job amenities has suffered from simultaneity bias due to workers' unobserved offer sets, resulting in “wrong-signed” compensating wage differentials. I propose a new estimator for amenity prices that uses only a single imprecise proxy for workers' offer sets to...

Understanding the relationship between disability and employment is critical and has long been the subject of study. However, estimating this relationship is difficult, particularly with survey data, since both disability and employment status are known to be misreported. Here, we use a partial...

The Gini index is the most commonly used measure of income inequality. Like any single summary measure of a set of data it cannot capture all aspects that are of interest to researchers. One of its widely reported flaws is that it is supposed to be overly sensitive to changes in the middle of...

This paper discusses the measurement of ex-ante inequality of opportunity for binary outcome variables. We argue that the use of scale but not translation invariant inequality measures such as the dissimilarity index might be problematic depending on the aim of the study. The main concern is...

This study proposes the mode-based decomposition approach to better examine the change of the more impoverished population's wealth into growth and distribution effects. Given Gibrat’s law, the decomposition first approximates the income distribution to lognormal distribution using the maximum...

In this paper I show that recently proposed methods to quantify the level of inequality of opportunity are likely to be downward biased when the dependent variable is a proxy for an unobserved concept. Using a multidimensional framework of development, such as the capability approach, or a...

In the machine learning community, the Gini index is a very popular score for model selection, and it is also used in actuarial science for evaluating insurance pricing models. The purpose of this tutorial is to discuss the Gini index, both its version in economics and its version in machine...

In explaining wage or income by personal attributes (e.g. educational attainment, age, and ethnicity) in a regression model, many researchers choose to use the log of wage or income as the dependent variable and then to estimate the unknown coefficients by some version of the least-squares...