Calibration has become a standard tool of macroeconomics. This paper extends and refines the calibration methodology along several important dimensions. First, accounting for home production is important both in measuring calibration targets and in organizing the data in a model-consistent...

A specification of the steps in designing a computational experiment to address a well-posed quantitative question, emphasizing that the computational experiment is an econometric tool used in the task of deriving the quantitative implications of theory.

This paper develops a method for combining the power of a dynamic, stochastic, general-equilibrium model with the flexibility of a vector autoregressive time-series model to obtain a hybrid that can be taken directly to the data.

The Gaussian log-likelihood can be expressed as the sum over different frequency components. This implies that the likelihood ratio statistic has a similar linear decomposition. Exploiting these observations, the authors devise diagnostic methods that are useful for interpreting...

The mixed logit is a framework for incorporating unobserved heterogeneity in discrete choice models in a general way. These models are difficult to estimate because they result in a complicated incomplete data likelihood. This paper proposes a new approach for estimating mixed logit models. The...

Evolutionary programming is a stochastic optimization procedure that has proved useful in optimizing difficult functions. This paper shows that evolutionary programming can be used to solve the Bellman equation problem with a high degree of accuracy and substantially less CPU time than Bellman...

A presentation of an undetermined coefficients method for obtaining a linear approximation to the solution of a dynamic rational-expectations model. It shows how that solution can be used to compute the model’s implications for impulse response functions and for second moments.

This paper estimates Local Average Treatment Effects (LATEs) of neighborhood quality from the Moving to Opportunity (MTO) housing mobility experiment in a generalized model with multiple treatment levels. We propose a new approach to identifying parameters that exploits the identification of...

The mixed logit is a framework for incorporating unobserved heterogeneity in discrete choice models in a general way. These models are difficult to estimate because they result in a complicated incomplete data likelihood. This paper proposes a new approach for estimating mixed logit models. The...

The estimation of large vector autoregressions with stochastic volatility using standard methods is computationally very demanding. In this paper we propose to model conditional volatilities as driven by a single common unobserved factor. This is justified by the observation that the pattern of...