In recent years, one has witnessed a widespread attention on the way monetary policy is conducted and in particular on the role of the so-called monetary policy rules. The conventional approach in the literature consists in estimating reaction functions for a monetary authority (the Federal...

Quantile regression constitutes a natural and flexible framework for the analysis of duration data in general and unemployment duration in particular. Comparison of the quantile regressions for lower and upper tails of the duration distribution shed important insights on the different...

A thorny problem in identifying the determinants of reservation wages and particularly the role of continued joblessness in their evolution is the simultaneity issue. We deploy a natural control function approach to the problem that involves conditioning elapsed duration on completed...

The U.S. labor market has been experiencing unprecedented high average unemployment duration. The shift in the unemployment duration distribution can be traced back to the early nineties. In this paper, censored quantile regression methods are employed to analyze the changes in the US...

In this estimation of models with averaged data, weighted least squares is often used and recommended as a way of improving the efficiency of the estimator. However, if the size of the different groups is not conditionally independent of the regressand, consistent estimation may not be possible...

This paper presents a methodology for detecting asset price booms and busts using non-parametric quantile regressions. The method consists in estimating the distribution of real stock prices as a function of fundamental determinants of stock returns, namely real economic activity and real...

The U.S. labor market has been experiencing unprecedented high average unemployment duration. The shift in the unemployment duration distribution can be traced back to the early nineties. In this study, censored quantile regression methods are employed to analyze the changes in the US...

This paper investigates the consequences of non-stationarity for the principal components analysis and suggests a data transformation that allows obtaining smoother series for the first principal component to be used as a core inflation indicator. The paper also introduces a theoretical model,...