Trends in Income Inequality, Volatility, and Mobility Risk

There has been a renewed interest in recent years in income inequality, economic mobility, and income volatility. I define an aggregate measure of income risk as half the squared coefficient of variation of incomes measured over both people and time, which can be decomposed into an inequality component measuring dispersion in mean incomes, a volatility component measuring the average dispersion of fluctuations about person-specific trends, and a mobility component measuring the dispersion of person-specific trends. I apply this decomposition to the Panel Study of Income Dynamics to characterize trends in inequality, volatility, and mobility over the last several decades in the United States. I also examine changes in the regressivity of income growth over time.inequality ; volatility ; instability ; mobility ; progressivity

Regression for nonnegative skewed dependent variables

Several options for estimation and prediction in regressions using nonnegative skewed dependent variables are compared. Often, Poisson regression outperforms competitors, even when its assumptions are violated and the correct model is one that justifies a competitor.

Is the Safety Net Catching Unemployed Families?

Examines changes in benefits and characteristics of unemployed families and those who received unemployment, SNAP, child tax credit, and other public assistance in 2009. Considers factors behind increases in unemployment and SNAP recipients

What Do Nonprofits Maximize? Nonprofit Hospital Service Provision and Market Ownership Mix

Conflicting theories of the nonprofit firm have existed for several decades yet empirical research has not resolved these debates, partly because the theories are not easily testable but also because empirical research generally considers organizations in isolation rather than in markets. Here we examine three types of hospitals – nonprofit, for-profit, and government – and their spillover effects. We look at the effect of for-profit ownership share within markets in two ways, on the provision of medical services and on operating margins at the three types of hospitals. We find that nonprofit hospitals’ medical service provision systematically varies by market mix. We find no significant effect of for-profit market share on the operating margins of nonprofit hospitals. These results fit best with theories in which hospitals maximize their own output.

Risk and Recovery: Understanding the Changing Risks to Family Incomes

Examines the factors that affect the likelihood of families with children to experience sharp income drops and to recover financially, including job loss, separation, and spikes in income before the drop, as well as demographics and original income level

Risk and Recovery: Documenting the Changing Risks to Family Incomes

Based on 1996, 2001, and 2004 data, examines the incidence of incomes of individuals with children falling substantially over a four-month period and the incidence of their recovering to pre-decline levels. Compares data by income quintile

Tracking the Household Income of SSDI and SSI Applicants

Using panel data from the Survey of Income and Program Participation linked to Social Security Administration disability determination records we trace the pattern of household income and the sources of that income from 38 months prior to 39 months following application for Social Security Disability Insurance (SSDI) and Supplemental Security Insurance (SSI). We find that the average applicant’s labor earnings declines dramatically beginning six month before application but the average applicant’s household income drops much less dramatically both in the months just before or just after application and over the next three years, and does so even for those denied benefits. However, we also found substantial heterogeneity in household income outcomes in both the SSDI and SSI applicant population. Our quantile regressions suggest that higher income households experience greater percentage declines in their post-application income. Such results are consistent with the lower replacement rate for higher earners established in the SSDI program and the low absolute level of protection provided to all SSI applicants regardless of income prior to application.

Disability Benefits as Social Insurance: Tradeoffs Between Screening Stringency and Benefit Generosity in Optimal Program Design

The Social Security Disability Insurance (SSDI) system is designed to provide income security to workers in the event that health problems prevent them from working. In order to qualify for benefits, applicants must pass a medical screening that is intended to verify that the individual is truly incapable of work. Past research has shown, however, that the screening procedures used do not function without error. If screening were error-free, it has can be demonstrated that it is socially optimal to distinguish the disabled non-worker from the non-disabled, providing benefits to the disabled. In this paper we first demonstrate that if the errors in the medical screening are too large, it will not be optimal to distinguish the disabled from the non-disabled. Then, we use data on the actual quality of screening to determine first, if segmenting the non-working population is desirable, and second whether the current SSDI system relies too heavily on screening than is justified. Our preliminary conclusion is that while screening is good enough to justify some distinction in benefits, it may not be good enough to justify the size of the benefit offered.

GMM estimation in Mata

A brief introduction to estimating Generalized Method of Moments models in Stata, using the optimize() function in Mata, with applications to nonlinear IV models.

Causal inference for binary regression with observational data

Special problems arise when trying to do causal inference for binary regression with observational data; we will examine some of these problems and critically examine several common and not-so-common solutions.