This study uses a Bayesian VAR to demonstrate that the recent house price boom in Germany can be explained by falling interest rates and that higher interest rates are likely suciffient to stop the increase of German house prices. The latter suggests a potential drawback of the current monetary...

Correlation models, such as Constant Conditional Correlation (CCC) GARCH model or Dynamic Conditional Correlation (DCC) GARCH model, play a crucial role in forecasting Value-at-Risk (VaR) or Expected Shortfall (ES). The additional inclusion of constant correlation tests into correlation models...

We propose a prior for VAR models that exploits the panel structure of macroeconomic time series while also providing shrinkage towards zero to address overfitting concerns. The prior is flexible as it detects shared dynamics of individual variables across endogenously determined groups of...

This study considers Bayesian variable selection in the Phillips curve context by using the Bernoulli approach of Korobilis (2013a). The Bernoulli model, however, is unable to account for model change over time, which is important if the set of relevant predictors changes over time. To tackle...

We conduct a framed field experiment in Indonesian fishing communities, with an eye towards evaluating the potential of Territorial Use Rights for Fisheries (TURFs) to preserve coral reef fisheries. Conducted in three culturally distinctive sites, the study assembles groups of five fishers who...

As of late 2008, the steady decline of U.S. crude oil production over the last decades was reversed by the increased adoption of the hydraulic fracturing ("fracking") technology. Adapting the supply-side model proposed by Kaufmann et al. (2004) to assess OPEC's ability to influence real oil...

At the onset of the United Nations' decade of ecosystem restoration, lessons from well-designed impact evaluations on land restoration programs are crucial for improving policymaking. This study presents findings from a systematic review of research on the socioeconomic impact of such...

For spatial data with a sufficiently long time dimension, the concept of global cointegration has been recently included in the econometrics research agenda. Global cointegration arises when non-stationary time series are cointegrated both within and between spatial units. In this paper, we...

For spatial data with a sufficiently long time dimension, the concept of global cointegration has been recently included in the econometrics research agenda. Global cointegration arises when non-stationary time series are cointegrated both within and between spatial units. In this paper, we...

In this study we introduce a new indicator for private consumption based on search query time series provided by Google Trends. The indicator is based on factors extracted from consumption-related search categories of the Google Trends application Insights for Search. The forecasting performance...