Positive assortative matching implies that high productivity workers and firms match together. However, there is almost no evidence of a positive correlation between the worker and firm contributions in two-way fixed-effects wage equations. This could be the result of a bias caused by standard...

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...

We study the impact of the arrival of macroeconomic news on the informational and noise-driven components in high-frequency quote processes and their conditional variances. Bid and ask returns are decomposed into a common ("efficient return") factor and two market-side-specific components...

We study the impact of the arrival of macroeconomic news on the informational and noise-driven components in high-frequency quote processes and their conditional variances. Bid and ask returns are decomposed into a common ("efficient return") factor and two market-side-specific components...

Positive assortative matching implies that high productivity workers and firms match together. However, there is almost no evidence of a positive correlation between the worker and firm contributions in two-way fixed-effects wage equations. This could be the result of a bias caused by standard...

This paper examines the impact of innovations and wages on the demand for heterogeneous labour. Based on matched data from the IAB-establishment panel survey and the files of the employment statistics register for the year 1995, input shares derived from a generalised Leontief cost function are...

This paper investigates the use of price intensities to estimate volatilities based on high-frequency data. We interpret the conditional probability for the occurrence of a price event within a certain time horizon as a risk measure which allows us to obtain an estimator of the conditional...

When making decisions, agents tend to make use of decisions others have made in similar situations. Ignoring this behavior in empirical models can be interpreted as a problem of omitted variables and may seriously bias parameter estimates and harm inference. We suggest a possibility of...