Envy-minimizing unemployment benefits

This paper offers an analysis of the optimality of unemployment benefits based on the concept of no-envy. Using a general equilibrium framework with uncertainty, we derive the conditions for a trade-off between the intensity of envy and the expected percentage of envious persons. If the government's sensitivity to the intensity of envy is not too strong (alongside conditions on households' utilities), the optimal benefit is positive and below the full-insurance level. We also show that, for a low enough sensitivity to the intensity of envy, the optimal replacement ratio decreases with unfavorable changes in the distribution of the technological shock.     

Edgeworth expansions and normalizing transforms for inequality measures

Finite sample distributions of studentized inequality measures differ substantially from their asymptotic normal distribution in terms of location and skewness. We study these aspects formally by deriving the second-order expansion of the first and third cumulant of the studentized inequality measure. We state distribution-free expressions for the bias and skewness coefficients. In the second part we improve over first-order theory by deriving Edgeworth expansions and normalizing transforms. These normalizing transforms are designed to eliminate the second-order term in the distributional expansion of the studentized transform and converge to the Gaussian limit at rate O(n⁻¹)$O\left(n^{-1}\right)$. This leads to improved confidence intervals and applying a subsequent bootstrap leads to a further improvement to order O(n^−3/2)$O\left(n^{-3/2}\right)$. We illustrate our procedure with an application to regional inequality measurement in Côte d’Ivoire.     

Crowding Out Informal Care? Evidence from a Field Experiment in Germany*

This article evaluates the effects of a consumer‐directed home care programme (Personal Budgets) compared with the standard home care programmes of the German long‐term care insurance (LTCI). The evaluation makes use of a random assignment into a treatment group receiving personal budgets and a control group receiving either in‐kind benefits (agency care) or cash payments. Compared with agency care, personal budgets extend the support by independent providers, but leave health outcomes unchanged. Compared with cash payments, personal budgets tend to improve health outcomes, but double LTCI spending due to a strong crowding out of informal care by formal care.     

Estimating willingness to pay for medicare using a dynamic life-cycle model of demand for health insurance

Medicare is the largest health insurance program in the US. This paper uses a dynamic random utility model of demand for health insurance in a life-cycle human capital framework with endogenous production of health to calculate the individual willingness to pay (WTP) for Medicare. The model accounts for the feature that the demand for health insurance is derived through the demand for health, which is jointly determined with the production of health over the life-cycle. The WTP measure incorporates the effects of Medicare insurance on aggregate consumption through effects on medical expenditures and mortality, and consumption utility of health. The model is estimated using panel data from the Health and Retirement Study. The average WTP or change in lifetime expected utility resulting from delaying the age of eligibility to 67 is found to be $ 24,947 in 1991 dollars ($ 39,435 in 2008 dollars). However, there is considerable variation in the WTP, e.g., in 1991 dollars the WTP of individuals who have less than a high school education and are white is $ 28,347 ($ 44,810 in 2008 dollars), while the WTP of those with at least a college degree and who are neither white nor black is $ 15,584 ($ 24,635 in 2008 dollars). More generally, the less educated have a higher WTP to avoid a policy change that delays availability of Medicare benefits. Additional model simulations imply that the primary benefits of Medicare are insurance against medical expenditures with relatively smaller benefits in terms of improved health status and longevity. Medicare also leads to large increases in medical utilization due to deferring of medical care prior to eligibility.     

Testing for stochastic dominance using the weighted McFadden-type statistic

We demonstrate that when testing for stochastic dominance of order three and above, using a weighted version of the Kolmogorov–Smirnov-type statistic proposed by McFadden [1989. In: Fomby, T.B., Seo, T.K. (Eds.), Studies in the Economics of Uncertainty. Springer, New York, pp. 113–134] is necessary for obtaining a non-degenerate asymptotic distribution. Since the asymptotic distribution is complex, we discuss a bootstrap approximation for it in the context of a real application.     

Reliable inference for the Gini index

Although attention has been given to obtaining reliable standard errors for the plug-in estimator of the Gini index, all standard errors suggested until now are either complicated or quite unreliable. An approximation is derived for the estimator by which it is expressed as a sum of IID random variables. This approximation allows us to develop a reliable standard error that is simple to compute. A simple but effective bias correction is also derived. The quality of inference based on the approximation is checked in a number of simulation experiments, and is found to be very good unless the tail of the underlying distribution is heavy. Bootstrap methods are presented which alleviate this problem except in cases in which the variance is very large or fails to exist. Similar methods can be used to find reliable standard errors of other indices which are not simply linear functionals of the distribution function, such as Sen’s poverty index and its modification known as the Sen–Shorrocks–Thon index.     

Does income inequality lead to banking crises in developing countries? Empirical evidence from cross-country panel data

This study empirically examines whether increasing income inequality results in banking crises using panel data for 68 countries covering the years 1973 to 2010. The results show that developing countries with high inequality tend to have higher levels of domestic credit and that domestic credit booms increase the probability of banking crises. We also find that developing economies display direct channels from inequality to banking crises without an association with credit booms. We find no consistent evidence that income inequality contributes to banking crises in advanced economies. In developing countries, the probability of banking crises increases dramatically as income inequality levels increase: The probability of a systemic banking crisis within three years is 9.5% when the Gini is as low as 0.2 in developing countries and increases to 57.4% when the Gini is 0.4. These results are robust to several specifications.     

An econometric method of correcting for unit nonresponse bias in surveys

Past approaches to correcting for unit nonresponse in sample surveys by re-weighting the data assume that the problem is ignorable within arbitrary subgroups of the population. Theory and evidence suggest that this assumption is unlikely to hold, and that household characteristics such as income systematically affect survey compliance. We show that this leaves a bias in the re-weighted data and we propose a method of correcting for this bias. The geographic structure of nonresponse rates allows us to identify a micro compliance function, which is then used to re-weight the unit-record data. An example is given for the US Current Population Surveys, 1998–2004. We find, and correct for, a strong household income effect on response probabilities.     

Learning and the value of information: Evidence from health plan report cards

This paper develops a framework to analyze the value of information in the context of health plan choice. We use a Bayesian learning model to estimate the impact and value of information using data from a large employer, which started distributing health plan ratings to its employees in 1997. We estimate the parameters of the model with simulated maximum likelihood, and use the estimates to quantify the value of the report card information. We model both continuous specifications with Gaussian priors and signals, and discrete specifications with Beta priors and Binomial signals. We find that the release of information had a statistically significant effect on health plan choices. Consumers were willing to pay about $330 per year per below expected performance rating avoided, and the average value of the report card per employee was about $20 per year. We find large variation in valuations across different performance domains, but no significant evidence of heterogeneity based on observable employee characteristics or unobservable dimensions.     

Estimation of collective household models with Engel curves

The structural consumer demand methods used to estimate the parameters of collective household models are typically either very restrictive and easy to implement or very general and difficult to estimate. In this paper, we provide a middle ground. We adapt the very general framework of [Browning, M., Chiappori, P.A., Lewbel, A., 2004. Estimating Consumption Economies of Scale, Adult Equivalence Scales, and Household Bargaining Power, Boston College Working Papers in Economics 588] by adding a simple restriction that recasts the empirical model from a highly nonlinear demand system with price variation to a slightly nonlinear Engel curve system. Our restriction has an interpretation in terms of the behaviour of household scale economies and is testable. Our method identifies the levels of (not just changes in) household resource shares, and a variant of equivalence scales called indifference scales. We apply our methodology to Canadian expenditure data.     

Nonparametric estimation and inference about the overlap of two distributions

This paper develops methodology for nonparametric estimation of a measure of the overlap of two distributions based on kernel estimation techniques. This quantity has been proposed as a measure of economic polarization between two groups, Anderson (2004) and Anderson et al. (2010). In ecology it has been used to measure the overlap of species. We give the asymptotic distribution theory of our estimator, which in some cases of practical relevance is nonstandard due to a boundary value problem. We also propose a method for conducting inference based on estimation of unknown quantities in the limiting distribution and show that our method yields consistent inference in all cases we consider. We investigate the finite sample properties of our methods by simulation methods. We give an application to the study of polarization within China in recent years using household survey data from two provinces taken in 1987 and 2001. We find a big increase in polarization between 1987 and 2001 according to monetary outcomes but less change in terms of living space.     

An analysis of the effect of noise in a heterogeneous agent financial market model

Heterogeneous agent models (HAMs) in finance and economics are often characterised by high dimensional nonlinear stochastic differential or difference systems. Because of the complexity of the interaction between the nonlinearities and noise, a commonly used, often called indirect, approach to the study of HAMs combines theoretical analysis of the underlying deterministic skeleton with numerical analysis of the stochastic model. However, it is well known that this indirect approach may not properly characterise the nature of the stochastic model. This paper aims to tackle this issue by developing a direct and analytical approach to the analysis of a stochastic model of speculative price dynamics involving two types of agents, fundamentalists and chartists, and the market price equilibria of which can be characterised by the stationary measures of a stochastic dynamical system. Using the stochastic method of averaging and stochastic bifurcation theory, we show that the stochastic model displays behaviour consistent with that of the underlying deterministic model when the time lag in the formation of price trends used by the chartists is far away from zero. However, when this lag approaches zero, such consistency breaks down.     

Long-term earnings and employment effects of housing voucher receipt

Using a propensity score matching approach coupled with difference-in-differences regression analysis, we estimate the effect of housing voucher receipt on the employment and earnings of a large longitudinal sample of low-income families for 6 years following voucher receipt. Our results indicate that voucher receipt has little effect on employment, but a negative effect on earnings. The negative earnings effect is largest in the years immediately following initial receipt, and fades out over time. In addition, we find that the pattern of recipient earnings responses to voucher receipt differs substantially across demographic subgroups. Several robustness tests are run to support the reliability of our findings. We discuss the implications of our findings for research and policy.