SUMMARY In this paper, we estimate a copula‐based bivariate dynamic hurdle model of prescription drug and nondrug expenditures to test the cost‐offset hypothesis, which posits that increased expenditures on prescription drugs are offset by reductions in other nondrug expenditures. We apply...

We develop a model specification and estimation framework that is applicable to many microeconometric models which fall into a treatment-outcome framework. We apply our methodology to examine the causal effect of man-aged care on the utilization of health care services. Specifically, we jointly...

We describe specification and estimation of a multinomial treatment effects negative binomial regression model. A latent factor structure is used to accommodate selection into treatment, and a simulated likelihood method is used for estimation. We describe its implementation via the mtreatnb...

This paper presents a new multivariate copula-based modeling approach for analyzing cost-offsets between drug and nondrug expenditures. Estimates are based on panel data from the Medical Expenditure Panel Survey (MEPS) with quarterly measures of medical expenditures. The approach allows for...

This paper presents a new multivariate copula-based modeling approach for analyzing cost-offsets between drug and nondrug expenditures. Estimates are based on panel data from the Medical Expenditure Panel Survey (MEPS) with quarterly measures of medical expenditures. The approach allows for...

The aim of this paper is to measure the returns to migration using non-experimental data taking both observed and unobserved characteristics into account. A significant challenge related to migration research and the issues of unobserved heterogeneity is that the standard 2stage least squares...

We investigate characteristics of cross‐market correlations using daily data from U.S. stock, bond, money, and currency futures markets using a new multivariate GARCH model that permits direct hypothesis testing on conditional correlations. We find evidence that arrival of information in a...

This paper develops and implements a GMM estimator for latent class models suitable for count data. The estimator uses conditional moment restrictions derived from standard count models. Both the efficient and consistent variants are considered. The implementation of optimal GMM based on...

In this study, we examine the effect of SNAP on health quite generally, examining self-assessed health (SAH), healthy time, and basic health utilization measures as outcomes. Our approach is to model outcomes and participation simultaneously, using exogenous variation in state eligibility to...