The purchasing power parity puzzle relates to the adjustment of real exchange rates. Real exchange rates are extremely volatile, suggesting that temporary shocks emanate from the monetary sector. But the half-life of real exchange rate deviations is extremely large -- 2.5 to 5 years. This...

We estimate a Dynamic Programming model of the decision between continuing schooling or entering the labor market using a panel from the National Longitudinal Survey (NLSY). The model, set in an expected utility framework (with a power utility function), fits data on both schooling attainments...

We estimate a dynamic programming model of schooling decisions in which the degree of risk aversion can be inferred from schooling decisions. In our model, individuals are heterogeneous with respect to school and market abilities but homogeneous with respect to the degree of risk aversion. We...

We estimate a structural dynamic programming model of schooling decisions with unobserved heterogeneity in school ability and market ability on a sample taken from the National Longitudinal Survey of Youth (NLSY). Both the instantaneous utility of attending school and the wage regression...

In this paper, we review the most common specifications of discrete-time stochastic volatility (SV) models and illustrate the major principles of corresponding Markov Chain Monte Carlo (MCMC) based statistical inference. We provide a hands-on ap proach which is easily implemented in empirical...

I perform the joint estimation of a reduced-form dynamic model of the transition from one grade level to the next, and a Mincer wage equation, using panel data taken from the NLSY. A very high degree of flexibility is achieved by approximating the distributions of idiosyncractic grade transition...

In this paper, we develop and apply Bayesian inference for an extended Nelson-Siegel (1987) term structure model capturing interest rate risk. The so-called Stochastic Volatility Nelson-Siegel (SVNS) model allows for stochastic volatility in the underlying yield factors. We propose a Markov...

We introduce a regularization and blocking estimator for well-conditioned high-dimensional daily covariances using high-frequency data. Using the Barndorff-Nielsen, Hansen, Lunde, and Shephard (2008a) kernel estimator, we estimate the covariance matrix block-wise and regularize it. A data-driven...

We model the dynamics of ask and bid curves in a limit order book market using a dynamic semiparametric factor model. The shape of the curves is captured by a factor structure which is estimated nonparametrically. Corresponding factor loadings are assumed to follow multivariate dynamics and are...