The synthetic control method is widely used in comparative case studies to adjust for differences in pre-treatment characteristics. A major attraction of the method is that it limits extrapolation bias that can occur when untreated units with different pre-treatment characteristics are combined...

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...

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...

Field experiments conducted with the village, city, state, region, or even country as the unit of randomization are becoming commonplace in the social sciences. While convenient, subsequent data analysis may be complicated by the constraint on the number of clusters in treatment and control....

This paper gives an alternative derivation of a Monte Carlo method that has been used to study robust estimators. Extensions of the technique to the regression case are also considered and some computational points are briefly mentioned

Recent work by Said and Dickey (1984 ,1985) , Phillips (1987), and Phillips and Perron(1988) examines tests for unit roots in the autoregressive part of mixed autoregressive-integrated-moving average (ARIHA) models (tests for stationarity). Monte Carlo experiments show that these unit root tests...

We give some Monte Carlo results on the performance of two robust alternatives to least squares regression estimation - least absolute residuals and the one-step "sine" estimator. We show how to scale the residuals for the sine estimator to achieve constant efficiency at the Gaussian across...

We develop a sequential Monte Carlo (SMC) algorithm for estimating Bayesian dynamic stochastic general equilibrium (DSGE) models, wherein a particle approximation to the posterior is built iteratively through tempering the likelihood. Using three examples consisting of an artificial state-space...

We propose a portmanteau test for serial correlation of the error term in a fixed effects model. The test is derived as a conditional Lagrange multiplier test, but it also has a straightforward Wald test interpretation. In Monte Carlo experiments, the test displays good size and power properties

Many dynamic problems in economics are characterized by large state spaces which make both computing and estimating the model infeasible. We introduce a method for approximating the value function of high-dimensional dynamic models based on sieves and establish results for the: (a) consistency,...