The European Commission’s growth forecasts play a crucial role in shaping policies and provide a benchmark for many (national) forecasters. The annual forecasts are built on quarterly estimates, which do not receive much attention and are hardly known. Therefore, this paper provides a comprehensive analysis of multi-period ahead quarterly GDP growth forecasts for the European Union (EU), euro area, and several EU member states with respect to first-release and current-release data. Forecast revisions and forecast errors are analyzed, and the results show that the forecasts are not systematically biased. However, GDP forecasts for several member states tend to be overestimated at short-time horizons. Furthermore, the final forecast revision in the current quarter is generally downward biased for almost all countries. Overall, the differences in mean forecast errors are minor when using real-time data or pseudo-real-time data and these differences do not significantly impact the overall assessment of the forecasts’ quality. Additionally, the forecast performance varies across countries, with smaller countries and Central and Eastern European countries (CEECs) experiencing larger forecast errors. The paper provides evidence that there is still potential for improvement in forecasting techniques both for nowcasts but also forecasts up to eight quarters ahead. In the latter case, the performance of the mean forecast tends to be superior for many countries.

This paper investigates forecast aggregation via the random subspace regressions method (RSM) and explores the potential link between RSM and the Shapley value decomposition (SVD) using the US GDP growth rates. This technique combination enables handling high-dimensional data and reveals the relative importance of each individual forecast. First, it is possible to enhance forecasting performance in certain practical instances by randomly selecting smaller subsets of individual forecasts and obtaining a new set of predictions based on a regression-based weighting scheme. The optimal value of selected individual forecasts is also empirically studied. Then, a connection between RSM and SVD is proposed, enabling the examination of each individual forecast’s contribution to the final prediction, even when there is a large number of forecasts. This approach is model-agnostic (can be applied to any set of predictions) and facilitates understanding of how the aggregated prediction is obtained based on individual forecasts, which is crucial for decision-makers.

We study how connections to German federal parliamentarians affect firm dynamics by constructing a novel dataset linking politicians and election candidates to the universe of firms. To identify the causal effect of access to political power, we exploit (i) new appointments to the company leadership team and (ii) discontinuities around the marginal seat of party election lists. Our results reveal that connections lead to reductions in firm exits, gradual increases in employment growth without improvements in productivity. Adding information on credit ratings, subsidies and procurement contracts allows us to distinguish between mechanisms driving the effects over the politician’s career. 

Using the near-universe of Danish owner-occupied residential houses, we show that an exogenous increase in wealth significantly increases the likelihood to switch to green heating. We estimate an elasticity of one at the median of the wealth distribution, i.e., a 10% increase in wealth increase raises green heating adoption by 10%. Effects are heterogeneous along the wealth distribution: all else equal, a redistribution of wealth from rich households to poor households can significantly increase green heating adoption. We further explore potential channels of our findings (pro-social preferences, financial constraints, and luxury goods interpretation). Our results emphasize the role of economic growth for the green transition.

How do firms invest when financial constraints are relaxed? We document that firms affected by a large positive credit supply shock predominantly increase borrowing for transaction-based purposes. These treated firms have larger asset and employment growth rates; however, growth entirely stems from the increased takeover activity. Announcement returns indicate a low quality of the credit-supply-induced takeover activity. These results offer the possibility that credit-driven growth can simply reflect redistribution, rather than net gains in assets or employment.