This paper studies a discrete-time utility maximization problem of an infinitely-lived quasi-geometric consumer whose labor income is subject to uninsurable idiosyncratic productivity shocks. We restrict attention to a first-order Markov recursive solution. We show that under the assumption of...

This paper studies the business cycle dynamics of the income and wealth distributions in the context of the neoclassical growth model where agents are heterogeneous in initial wealth and non-acquired skills. Our economy admits a representative consumer which enables us to characterize the...

GARCH models are commonly used as latent processes in econometrics, financial economics and macroeconomics. Yet no exact likelihood analysis of these models has been provided so far. In this paper we outline the issues and suggest a Markov chain Monte Carlo algorithm which allows the calculation...

We construct a general-equilibrium version of Krusell, Ohanian, Ríos-Rulland Violante’s (2000) model with capital-skill complementarity. To account forgrowth patterns observed in the data, we assume several sources of growthsimultaneously, specifically, exogenous growth of skilled and...

This paper examines the stochastic volatility model suggested by Heston (1993). We employ a time-series approach to estimate the model and we discuss the potential effects of time-varying skewness and kurtosis on the performance of the model. In particular, it is found that the model tends to...

This paper studies how the EU Eastern enlargement can affect the economies of the old and the new EU members and the non-acceded countries in the context of a multi-country neoclassical growth model where Foreign Direct Investment (FDI) is subject to border costs. We assume that in the moment of...

This paper proposes a GARCH-type model allowing for time-varying volatility, skewness and kurtosis. The model is estimated assuming a Gram-Charlier series expansion of the normal density function for the error term, which is easier to estimate than the non-central t distribution proposed by...

We develop numerically stable and accurate stochastic simulation approaches for solving dynamic economic models. First, instead of standard least-squares methods, we examine a variety of alternatives, including least-squares methods using singular value decomposition and Tikhonov regularization,...

We study the processes for the conditional mean and variance given a specification of the process for the observed time series. We derive general results for the conditional mean of univariate and vector linear processes, and then apply it to various models of interest. We also consider the...

We investigate several important inference issues for factor models with dynamic heteroskedasticity in the common factors. First, we show that such models are identified if we take into account the time-variation in the variances of the factors. Our results also apply to dynamic versions of the...