The effect of regulatory scrutiny asymmetric cost pass-through in power wholesale and its end

We find an asymmetric pass-through of European Emission Allowance (EUA) prices to wholesale electricity prices in Germany and show that this asymmetry has disappeared in response to a report on investigations by the competition authority. The asymmetric pricing pattern, however, was not detected at the time of the report, nor had it been part of the investigations. Our results therefore provide evidence of the deterring effect of regulatory monitoring on firms which exhibit non-competitive pricing behavior. We do not find any asymmetric pass-through of EUA prices in recent years. Several robustness checks support our results

Do residential property companies systematically adjust their capital structure? : The case of Germany

This paper analyzes whether predominantly non-listed corporations in the residential property industry systematically adjust their capital structure to changing financing requirements. Since previous research almost exclusively focused on listed companies, little is known about the considerations that drive the choice of capital structure of nonlisted companies. We therefore adopt established testing approaches for the pecking order theory and the trade-off theory from the finance literature, which we then apply to a sample of 1,300 German residential property companies. These companies are characterized by various legal forms and large differences in size. We find that capital structure adjustment behavior differs largely among property companies of different legal forms. While housing cooperatives behave in line with the trade-off theory, the behavior of stock companies and corporations with limited liability is more in line with the pecking order theory

Three Essays on the Econometrics of Survey Expectations Data

This dissertation consists of three essays that have a common focus on the econometrics of survey expectations data. Such data play a crucial role in economics. First, as most decisions depend on expectations, these data facilitate a better understanding of economic dynamics. Second, survey data provide information that is otherwise unavailable, e.g. the economic expectations of professional forecasters or firms' hiring, investment and production activities. This thesis contributes to the relevant literature by considering novel aspects in the measurement of expectations, and by proposing a new approach to exploit survey expectations data in forecasting

Combining survey forecasts and time series models : the case of the Euribor

This paper reinterprets Maganelli’s (2009) idea of “Forecasting with Judgment” to obtain a dynamic algorithm for combining survey expectations data and time series models for macroeconomic forecasting. Existing combination approaches typically obtain combined forecasts by linearly weighting individual forecasts. The approach presented here instead uses survey forecasts in the estimation stage of a time series model. Thus an estimate of the model parameters is obtained that reflects two sources of information: a history of realizations of the variables that are involved in the time series model and survey expectations on the future course of the variable that is to be forecast. The idea at the estimation stage is to shrink parameter estimates towards values that are compatible (in an appropriate sense) with the survey forecasts that have been observed. It is exemplified how this approach can be applied to different autoregressive time series models. In an empirical application, the approach is used to forecast the three-month Euribor at a six-month horizon

Combining Survey Forecasts and Time Series Models: The Case of the Euribor

This paper reinterprets Maganelli’s (2009) idea of “Forecasting with Judgment” to obtain a dynamic algorithm for combining survey expectations data and time series models for macroeconomic forecasting. Existing combination approaches typically obtain combined forecasts by linearly weighting individual forecasts. The approach presented here instead uses survey forecasts in the estimation stage of a time series model. Thus an estimate of the model parameters is obtained that reflects two sources of information: a history of realizations of the variables that are involved in the time series model and survey expectations on the future course of the variable that is to be forecast. The idea at the estimation stage is to shrink parameter estimates towards values that are compatible (in an appropriate sense) with the survey forecasts that have been observed. It is exemplified how this approach can be applied to different autoregressive time series models. In an empirical application, the approach is used to forecast the three-month Euribor at a six-month horizon.Tendency survey; forecast combination