Tax Revenue Forecast Errors: Wrong Predictions of the Tax Base or the Elasticity?
(joint with M. Göttert)
In this paper, we disentangle tax revenue forecast errors into influences stemming from wrong macroeconomic assumptions and false predictions of the elasticities linking the tax base to its corresponding tax type. Across six tax types and the overall tax sum for Germany, we find a heterogeneous degree of relative importance of both sources. Whereas wrong macroeconomic assumptions matter most for profit-related taxes and the wage tax, false predictions of the elasticities mainly drive the forecast errors of the energy tax and the sales taxes. For the overall tax sum, more than two-third of the error can be attributed to wrong macroeconomic predictions and approximately one-third to false assumptions on the elasticity. Our results suggest that outsourcing the macroeconomic projections to an independent forecaster and methodological improvements can reduce tax revenue forecast errors.
CESifo Working Paper No. 9148, Submitted
READ-GER: Introducing German Real-time Regional Accounts Data for Revision Analysis and Nowcasting
Accurate real-time macroeconomic data are essential for policy-making and economic nowcasting. In this paper, I introduce a real-time database for German regional economic accounts (READ-GER). The database contains real-time information for nine macroeconomic aggregates and the 16 German states. I conduct both a revision analysis and a nowcasting experiment. Whereas the first estimates show no systematic revision errors by pooling the states together, this procedure suppresses the revision characteristics of single states. For half of the 16 German states I find that the first estimates are no optimal predictions, thus, leaving room for improvements in the future. The real-time nowcasts for real gross domestic product growth based on a mixed-frequency Vector Autoregression are very accurate, beat several benchmark models and are as precise or better as the first official estimates. More regional data would help to further increase the model's nowcast performance and thus its properties for the first estimates from regional accounts.
CESifo Working Paper No. 10315, Supplementary Material, Submitted
Quarterly GDP Estimates for the German States: New Data for Business Cycle Analyses and Long-Run Dynamics
(joint with I. Wikman)
To date, only annual information on economic activity is published for the 16 German States. In this paper, we calculate quarterly regional GDP estimates for the period between 1995 to 2021, thereby improving the regional database in Germany. The new data set will regularly be updated when quarterly economic growth for Germany becomes available. We use the new data for an in-depth business cycle analysis and to estimate long-run growth dynamics. The business cycle analysis reveals large heterogeneities in the duration and amplitudes of state-specific fluctuations as well as in the degrees of cyclical concordance. Long-run trends are found to vary tremendously, with positive developments in economically strong regions and flat or even negative trends for economically much weaker states.
CESifo Working Paper No. 10280, Supplementary Material, Revise and Resubmit: Oxford Bulletin of Economics and Statistics
Forecasting Regional Industrial Production with High-Frequency Electricity Consumption Data
(joint with S. Möhrle)
In this paper, we study the predictive power of electricity consumption data for regional economic activity. Using unique weekly and monthly electricity consumption data for the second-largest German state, the Free State of Bavaria, we conduct a pseudo out-of-sample forecasting experiment for the monthly growth rate of Bavarian industrial production. We find that electricity consumption is the best performing indicator in the nowcasting setup and has higher accuracy than other conventional indicators in a monthly forecasting experiment. Exploiting the high-frequency nature of the data, we find that the weekly electricity consumption indicator also provides good predictions about industrial activity in the current month even with only one week of information. Overall, our results indicate that regional electricity consumption offers a promising avenue to measure and forecast regional economic activity.
CESifo Working Paper No. 9917, Submitted
Economic Forecasting with Spatial Effects: An Assessment for German Districts
In this research project, I will apply panel techniques to forecasting annual GDP growth at the district level in Germany. mimeo
What drives German Trend GDP Growth? A Disaggregated Sectoral View
(joint with L. Zarges)
In this paper, we apply a multivariate unobserved components model estimated by Bayesian methods to industrial data in Germany and ask whether and how structural changes taking place in the last five decades affected trend GDP growth. mimeo
The Slowdown in German Trend GDP Growth: Aggregate or State-Specific Factors?
German trend GDP growth is falling for more than three decades. In this paper, I try to identify whether this decline is driven by aggregate and common factors or by state-specific factors and thus by regional features. mimeo
Forecasting Labor Productivity: A New Measure Based on Business Survey Results
(joint with S. Sauer, K. Wohlrabe and T. Wollmershäuser)
In this paper, we develop a new measure for labor productivity from business survey results and test its properties to forecasting German data. mimeo
From Shopping to Statistics: Tracking and Nowcasting Private Consumption Expenditures in Real-Time
(joint with F. Fourné)
In this paper, we estimate weekly private consumption expenditures based on transaction data in a mixed-frequency environent. mimeo