While recurring and regular variations of weather conditions are implicitly addressed by standard seasonal adjustment procedures of economic time series, extraordinary weather outcomes are not. We analyze their impact on German total industrial and construction-sector production and find modest...

The detection of business-cycle turning points is usually performed with non-linear discrete-regime models such as binary dependent variable (e.g., probit or logit) or Markov-switching methods. The probit model has the drawback that the continuous underlying target variable is discretized, with...

While recurring and regular variations of weather conditions are implicitly addressed by standard seasonal adjustment procedures of economic time series, extraordinary weather outcomes are not. We propose a way of measuring aggregate abnormal weather conditions based on available local...

For the timely detection of business-cycle turning points we suggest to use mediumsized linear systems (subset VARs with automated zero restrictions) to forecast the relevant underlying variables, and to derive the probability of the turning point from the forecast density as the probability...