We propose autocorrelation-robust asymptotic variances of the Brier score and Brier skill score, which are generally applicable in circumstances with weak serial correlation. An empirical application in macroeconomics underscores the importance of taking care of serial correlation. We find that...

The performance in finite samples is examined of inference obtained by variants of the Arellano-Bond and the Blundell-Bond GMM estimation techniques for single dynamic panel data models with possibly endogenous regressors and cross-sectional heteroskedasticity. By simulation the effects are...

Established tests for proper calibration of multivariate density forecasts based on Rosenblatt probability integral transforms can be manipulated by changing the order of variables in the forecasting model. We derive order invariant tests. The new tests are applicable to densities of arbitrary...

This paper introduces a new test of the predictive performance and market timing for categorical forecasts based on contingency tables when the user has non-categorical loss functions. For example, a user might be interested in the return of an underlying variable instead of just the direction....

Regression model error assumptions are essential to estimator properties. Least squares model parameters are consistent and efficient when the underlying error terms are normally distributed but yield inefficient estimators when errors are not normally distributed. Partially adaptive and...

We study how individual inventors respond to incentives to work on "clean" electricity technologies. Using natural gas price variation, we estimate output and entry elasticities of inventors and measure the medium-term impacts of a price increase mirroring the social cost of carbon. We find that...

This paper investigates how access to finance and skilled workforce endowments affect the propensity of European small and medium sized enterprises (SMEs) to adopt different types of resource efficiency measures (REMs), possibly simultaneously. For this purpose, a Multinomial Logit model is...

The oil and gas industry’s early 2000’s fracking and horizontal drilling revolution realigned the industry and larger economies. This study uses New Growth Theory to evaluate innovation across an industry with various integrated but distinct upstream, midstream, and downstream units. Two...

This paper investigates static and dynamic connectedness between the first and second moments of fossil and renewable energy stock indices in the last decade at the daily frequency. For this purpose the Diebold and Yilmaz (2014) methodology is applied; in addition, endogenous break tests are...

We analyse the drivers of European Power Exchange (EPEX) retail electricity prices between 2012 and early 2022 using machine learning. The agnostic random forest approach that we use is able to reduce in-sample root mean square errors (RMSEs) by around 50% when compared to a standard linear...