Assumption Errors and Forecast Accuracy: A Partial Linear Instrumental Variable and Double Machine Learning Approach
Katja Heinisch, Fabio Scaramella, Christoph Schult
IWH Discussion Papers,
Nr. 6,
2025
Abstract
Accurate macroeconomic forecasts are essential for effective policy decisions, yet their precision depends on the accuracy of the underlying assumptions. This paper examines the extent to which assumption errors affect forecast accuracy, introducing the average squared assumption error (ASAE) as a valid instrument to address endogeneity. Using double/debiased machine learning (DML) techniques and partial linear instrumental variable (PLIV) models, we analyze GDP growth forecasts for Germany, conditioning on key exogenous variables such as oil price, exchange rate, and world trade. We find that traditional ordinary least squares (OLS) techniques systematically underestimate the influence of assumption errors, particularly with respect to world trade, while DML effectively mitigates endogeneity, reduces multicollinearity, and captures nonlinearities in the data. However, the effect of oil price assumption errors on GDP forecast errors remains ambiguous. These results underscore the importance of advanced econometric tools to improve the evaluation of macroeconomic forecasts.
Artikel Lesen
Conditional Macroeconomic Survey Forecasts: Revisions and Errors
Alexander Glas, Katja Heinisch
Journal of International Money and Finance,
November
2023
Abstract
Using data from the European Central Bank's Survey of Professional Forecasters and ECB/Eurosystem staff projections, we analyze the role of ex-ante conditioning variables for macroeconomic forecasts. In particular, we test to which extent the updating and ex-post performance of predictions for inflation, real GDP growth and unemployment are related to beliefs about future oil prices, exchange rates, interest rates and wage growth. While oil price and exchange rate predictions are updated more frequently than macroeconomic forecasts, the opposite is true for interest rate and wage growth expectations. Beliefs about future inflation are closely associated with oil price expectations, whereas expected interest rates are related to predictions of output growth and unemployment. Exchange rate predictions also matter for macroeconomic forecasts, albeit less so than the other variables. With regard to forecast errors, wage growth and GDP growth closely comove, but only during the period when interest rates are at the effective zero lower bound.
Artikel Lesen
Department Profiles
Research Profiles of the IWH Departments All doctoral students are allocated to one of the four research departments (Financial Markets – Laws, Regulations and Factor Markets –…
Zur Seite
Projekte
Unsere Projekte 07.2022 ‐ 12.2026 Evaluierung des InvKG und des Bundesprogrammes STARK Bundesministerium für Wirtschaft und Klimaschutz (BMWK) Im Auftrag des Bundesministeriums…
Zur Seite
Department Profiles
Research Profiles of the IWH Departments All doctoral students are allocated to one of the four research departments (Financial Markets – Laws, Regulations and Factor Markets –…
Zur Seite
The IWH Forecasting Dashboard – From Forecasts to Evaluation and Comparison
Katja Heinisch, Christoph Behrens, Jörg Döpke, Alexander Foltas, Ulrich Fritsche, Tim Köhler, Karsten Müller, Johannes Puckelwald, Hannes Reichmayr
IWH Technical Reports,
Nr. 1,
2023
Abstract
The paper describes the “Halle Institute for Economic Research (IWH) Forecasting Dashboard (ForDas)”. This tool aims at providing, on a non-commercial basis, historical and actual macroeconomic forecast data for the Germany economy to researchers and interested audiences. The database renders it possible to directly compare forecast quality across selected institutions and over time. It is partly based on data collected in the DFG-funded project “Macroeconomic Forecasts in Great Crises”.
Artikel Lesen
Conditional Macroeconomic Forecasts: Disagreement, Revisions and Forecast Errors
Alexander Glas, Katja Heinisch
IWH Discussion Papers,
Nr. 7,
2021
Abstract
Using data from the European Central Bank‘s Survey of Professional Forecasters, we analyse the role of ex-ante conditioning variables for macroeconomic forecasts. In particular, we test to which extent the heterogeneity, updating and ex-post performance of predictions for inflation, real GDP growth and the unemployment rate are related to assumptions about future oil prices, exchange rates, interest rates and wage growth. Our findings indicate that inflation forecasts are closely associated with oil price expectations, whereas expected interest rates are used primarily to predict output growth and unemployment. Expectations about exchange rates and wage growth also matter for macroeconomic forecasts, albeit less so than oil prices and interest rates. We show that survey participants can considerably improve forecast accuracy for macroeconomic outcomes by reducing prediction errors for external conditions. Our results contribute to a better understanding of the expectation formation process of experts.
Artikel Lesen
Nowcasting East German GDP Growth: a MIDAS Approach
João Carlos Claudio, Katja Heinisch, Oliver Holtemöller
Empirical Economics,
Nr. 1,
2020
Abstract
Economic forecasts are an important element of rational economic policy both on the federal and on the local or regional level. Solid budgetary plans for government expenditures and revenues rely on efficient macroeconomic projections. However, official data on quarterly regional GDP in Germany are not available, and hence, regional GDP forecasts do not play an important role in public budget planning. We provide a new quarterly time series for East German GDP and develop a forecasting approach for East German GDP that takes data availability in real time and regional economic indicators into account. Overall, we find that mixed-data sampling model forecasts for East German GDP in combination with model averaging outperform regional forecast models that only rely on aggregate national information.
Artikel Lesen
Nowcasting East German GDP Growth: a MIDAS Approach
João Carlos Claudio, Katja Heinisch, Oliver Holtemöller
Abstract
Economic forecasts are an important element of rational economic policy both on the federal and on the local or regional level. Solid budgetary plans for government expenditures and revenues rely on efficient macroeconomic projections. However, official data on quarterly regional GDP in Germany are not available, and hence, regional GDP forecasts do not play an important role in public budget planning. We provide a new quarterly time series for East German GDP and develop a forecasting approach for East German GDP that takes data availability in real time and regional economic indicators into account. Overall, we find that mixed-data sampling model forecasts for East German GDP in combination with model averaging outperform regional forecast models that only rely on aggregate national information.
Artikel Lesen
Regional, Individual and Political Determinants of FOMC Members' Key Macroeconomic Forecasts
Stefan Eichler, Tom Lähner
Journal of Forecasting,
Nr. 1,
2018
Abstract
We study Federal Open Market Committee members' individual forecasts of inflation and unemployment in the period 1992–2004. Our results imply that Governors and Bank presidents forecast differently, with Governors submitting lower inflation and higher unemployment rate forecasts than bank presidents. For Bank presidents we find a regional bias, with higher district unemployment rates being associated with lower inflation and higher unemployment rate forecasts. Bank presidents' regional bias is more pronounced during the year prior to their elections or for nonvoting bank presidents. Career backgrounds or political affiliations also affect individual forecast behavior.
Artikel Lesen
