We propose a numerical method, based on indirect inference, for checking the identification of a DSGE model. Monte Carlo samples are generated from the model's true structural parameters and a VAR approximation to the reduced form estimated for each sample. We then search for a different set of...

In this paper, we use Monte Carlo methods to study the small sample properties of the classical maximum likelihood (ML) estimator in artificial samples generated by the New-Keynesian open economy DSGE model estimated by Adolfson et al. (2008) with Bayesian techniques. While asymptotic...

In observational studies the overall aim when fitting a model for the propensity score is to reduce bias for an estimator of the causal effect. For this purpose guidelines for covariate selection for propensity score models have been proposed in the causal inference literature. To make the...

The paper discusses the nested logit model for choices between a set of mutually exclusive alternatives (e.g. brand choice, strategy decisions, modes of transportation, etc.). Due to the ability of the nested logit model to allow and account for similarities between pairs of alternatives, the...

Due to its ability to allow and account for similarities between pairs of alternatives, the nested logit model is increasingly used in practical applications. However the fact that there are two different specifications of the nested logit model has not received adequate attention. The utility...

We present a new theory of homogeneous volatility (and variance) estimators for arbitrary stochastic processes. The main tool of our theory is the parsimonious encoding of all the information contained in the OHLC prices for a given time interval by the joint distributions of the high-minusopen,...

Estimation and modelling problems as they arise in many fields often turn out to be intractable by standard numerical methods. One way to deal with such a situation consists in simplifying models and procedures. However, the solutions to these simplified problems might not be satisfying. A...

In this paper, we use Monte Carlo methods to study the small sample properties of the classical maximum likelihood (ML) estimator in artificial samples generated by the New-Keynesian open economy DSGE model estimated by Adolfson et al. (2008) with Bayesian techniques. While asymptotic...

We develop an econometric methodology to infer the path of risk premia from large unbalanced panel of individual stock returns. We estimate the time-varying risk premia implied by conditional linear asset pricing models where the conditioning includes instruments common to all assets and asset...

TSMod is an interactive program which allows the user to estimate a broad range of univariate models. This review describes the possibilities of the package, from a user's perspective and with a secondary focus on the numerical accuracy of the program.