The paper illustrates how one may assess our comprehensive uncertainty about the various relations in the entire chain from human activity to climate change. Using a modified version of the RICE model of the global economy and climate, we perform Monte Carlo simulations, where full sets of...

Many applications in financial economics use data series with different starting or ending dates. This paper describes estimation methods, based on the generalized method of moments (GMM), which make use of all available data for each moment condition. We introduce two asymptotically equivalent...

Standard practice for the estimation of dynamic stochastic general equilibrium (DSGE) models maintains the assumption that economic variables are properly measured by a single indicator, and that all relevant information for the estimation is summarized by a small number of data series. However,...

We analyze the initial conditions bias in the estimation of brand choice models with structural state dependence. Using a combination of Monte Carlo simulations and empirical case studies of shopping panels, we show that popular, simple solutions that mis-specify the initial conditions are...

Estimation of discontinuities is pervasive in applied economics: from the study of sheepskin effects to prospect theory and “bunching” of reported income on tax returns, models that predict discontinuities in outcomes are uniquely attractive for empirical testing. However, existing empirical...

This study uses Monte Carlo simulations to examine the ability of the two-stage least-squares (2SLS) estimator and two-stage residual inclusion (2SRI) estimators with varying forms of residuals to estimate the local average and population average treatment effect parameters in models with binary...

This paper studies identification and inference for the effect of a mis-classified, binary, endogenous regressor when a discrete-valued instrumental variable is available. We begin by showing that the only existing point identification result for this model is incorrect. We go on to derive the...

Small sample properties of parameter estimates and test statistics in the vector autoregressive dividend ratio model (Campbell and Shiller [1988 a,b]) are derived by stochastic simulation. The data generating processes are co integrated vector autoregressive models, estimated subject to...

We develop and implement a technique for closed-form maximum likelihood estimation (MLE) of multifactor affine yield models. We derive closed-form approximations to likelihoods for nine Dai and Singleton (2000) affine models. Simulations show our technique very accurately approximates true (but...

Recent work on robust estimation has led to many procedures, which are easy to formulate and straightforward to program but difficult to study analytically. In such circumstances experimental sampling is quite attractive, but the variety and complexity of both estimators and sampling situations...