We survey and apply several techniques from the statistical and computer science literature to the problem of demand estimation. We derive novel asymptotic properties for several of these models. To improve out-of-sample prediction accuracy and obtain parametric rates of convergence, we propose...

The solar industry in the US typically uses a credit score such as the FICO score as an indicator of consumer utility payment performance and credit worthiness to approve customers for new solar installations. Using data on over 800,000 utility payment performance and over 5,000 demographic...

This paper focuses on the specification and stability of a dynamic, stochastic, general equilibrium model of the American business cycle with sticky prices. Maximum likelihood estimates reveal that the data prefer a version of the model in which adjustment costs apply to the price level but not...

The conventional wisdom in macroeconomic modeling is to attribute business cycle fluctuations to innovations in the level of the fundamentals. Though volatility shocks could be important too, their propagating mechanism is still not well understood partly because modeling the latent volatilities...

This paper makes the following original contributions to the literature. (1) We develop a simpler analytical characterization and numerical algorithm for Bayesian inference in structural vector autoregressions that can be used for models that are overidentified, just-identified, or...

The outcome of any important macroeconomic policy change is the net effect of forces operating on different parts of the economy. A central challenge facing policy makers is how to assess the relative strength of those forces. Dynamic Stochastic General Equilibrium (DSGE) models are the leading...

This paper uses contemporaneous monetary data to carry out econometric tests of the "equilibrium" approach to modeling the relation between monetary disturbances and macroeconomic fluctuations. The theoretical analysis introduces into an equilibrium macroeconomic model the availability of...

Quantile regression(QR) fits a linear model for conditional quantiles, just as ordinary least squares (OLS) fits a linear model for conditional means. An attractive feature of OLS is that it gives the minimum mean square error linear approximation to the conditional expectation function even...

This paper studies quantitative implications of model economies that exhibit multiple equilibria. The goal is to assess two interrelated issues. First, do economies with multiple equilibria have falsifiable predictions? Second, is identification possible in economies that exhibit multiple...

The paper discusses how current inflation targeting should be modeled, and argues that it is better represented as a commitment to a targeting rule (a rule specifying operational objectives for monetary policy or a condition for the target variables), than as a commitment to a simple instrument...