Self-assessed health status conditioned by several objective measures of health and socio-demographic characteristics are used to measure health inequality. We compare the quality of health and health inequality among different racial/ethnic groups as well as across 17 regions in New York State....

Following recent econometric developments, we use self-assessed general health on a Likert scale conditioned by several objective determinants to measure health disparity between non-Hispanic Whites and minority groups in the United States. A statistical decomposition analysis is conducted to...

Following recent econometric developments, we use self-assessed general health on a Likert scale conditioned by several objective determinants to measure health disparity between non-Hispanic Whites and minority groups in the United States. A statistical decomposition analysis is conducted to...

We study the role of the well-known monthly diffusion indices produced by the Institute or Supply Management in nowcasting current quarter US GDP growth. We investigate their marginal impact on these nowcasts when large unbalanced (jagged edge) macroeconomic data sets are used in real time to...

We develop a monthly output index of the U.S. Transportation sector over 1980:1-2002:4 covering air, rail, water, truck, transit and pipeline activities. Separate indexes for freight and passenger are also constructed. Our total transportation output index matches very well with the annual...

Using a Factor Structural Vector Autoregressive (FSVAR) model and monthly GDP growth forecasts during 1995-2003, we find that Indian economy responds largely to domestic and Asian common shocks, and much less to shocks the from the West. However, when we exclude the Asian crisis period from our...

With the proliferation of quality multi-dimensional surveys, it becomes increasingly important for researchers to employ an econometric framework in which these data can be properly analyzed and put to their maximum use. In this chapter we have summarized such a framework developed in Davies and...

We develop a Markov Chain Monte Carlo (MCMC) algorithm for estimating nested logit models in a Bayesian framework. Appropriate "heating target" and reparameterization techniques are adopted for fast mixing. For illustrative purposes, we have implemented the algorithm on two real-life examples...