Showing 1 - 10 of 118
The dissertation aims to develop and apply new empirical methods to analyze and model farm structural change. Changes of the farm structure are not only important for the sector itself but may have broader economic, social and environmental consequences for a region. Understanding this process...
Persistent link: https://www.econbiz.de/10010485311
Persistent link: https://www.econbiz.de/10014419332
We develop a time-varying transition probabilities Markov Switching model in which inflation is characterised by two regimes (high and low inflation). Using Bayesian techniques, we apply the model to the euro area, Germany, the US, the UK and Canada for data from the 1960s up to the present. Our...
Persistent link: https://www.econbiz.de/10011605253
Persistent link: https://www.econbiz.de/10003715380
We propose a new nonlinear classification method based on a Bayesian "sum-of-trees" model, the Bayesian Additive Classification Tree (BACT), which extends the Bayesian Additive Regression Tree (BART) method into the classification context. Like BART, the BACT is a Bayesian nonparametric additive...
Persistent link: https://www.econbiz.de/10003635971
A great proportion of stock dynamics can be explained using publicly available information. The relationship between dynamics and public information may be of nonlinear character. In this paper we offer an approach to stock picking by employing so-called decision trees and applying them to XETRA...
Persistent link: https://www.econbiz.de/10003636039
This paper examines return predictability when the investor is uncertain about the right state variables. A novel feature of the model averaging approach used in this paper is to account for finite-sample bias of the coefficients in the predictive regressions. Drawing on an extensive...
Persistent link: https://www.econbiz.de/10003728591
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...
Persistent link: https://www.econbiz.de/10003770817
Persistent link: https://www.econbiz.de/10003780914
In this paper we consider regression models for count data allowing for overdispersion in a Bayesian framework. We account for unobserved heterogeneity in the data in two ways. On the one hand, we consider more flexible models than a common Poisson model allowing for overdispersion in different...
Persistent link: https://www.econbiz.de/10003310097