This paper uses data available from the National Opinion Research Center's (NORC) survey on religious attitudes and powerful statistical methods to evaluate the effect of prayer on the attitude of God toward human beings. -- Kernel estimator ; unobserved variables

This paper summarizes our recent research on evaluating the distributional consequences of social programs. This research advances the economic policy evaluation literature beyond estimating assorted mean impacts to estimate distributions of outcomes generated by different policies and determine...

This paper examines the performance of the JTPA performance system, a widely emulated model for inducing efficiency in government organizations. We present a model of how performance incentives may distort bureaucratic decisions. We define cream skimming within the model. Two major empirical...

This paper has been accepted for publication in the 'Review of Economics and Statistics'.We propose a dynamic factor model for mixed-measurement and mixed-frequency panel data. In this framework time series observations may come from a range of families of parametric distributions, may be...

We introduce a new efficient importance sampler for nonlinear non-Gaussian state space models. We propose a general and efficient likelihood evaluation method for this class of models via the combination of numerical and Monte Carlo integration methods. Our methodology explores the idea that...

We propose a new model for dynamic volatilities and correlations of skewed and heavy-tailed data. Our model endows the Generalized Hyperbolic distribution with time-varying parameters driven by the score of the observation density function. The key novelty in our approach is the fact that the...

We study the performance of alternative methods for calculating in-sample confidence and out of-sample forecast bands for time-varying parameters. The in-sample bands reflect parameter uncertainty only. The out-of-sample bands reflect both parameter uncertainty and innovation uncertainty. The...

We introduce a dynamic Skellam model that measures stochastic volatility from high-frequency tick-by-tick discrete stock price changes. The likelihood function for our model is analytically intractable and requires Monte Carlo integration methods for its numerical evaluation. The proposed...

We introduce a new model for time-varying spatial dependence. The model extends the well-known static spatial lag model. All parameters can be estimated conveniently by maximum likelihood. We establish the theoretical properties of the model and show that the maximum likelihood estimator for the...