Macroeconomic Forecasting in Great Crises

Prof. Dr. Jörg Döpke, Merseburg (Principal Investigator)

Prof. Dr. Ulrich Fritsche, Hamburg (Principal Investigator)

Prof. Dr. Christian Pierdzioch, Hamburg (Principal Investigator)

Christoph Behrens, Hamburg

Karsten Müller, Merseburg

Johannes Puckelwald, Hamburg

 

The discussion of the quality and the role of forecasts of social and economic events is a classic topic of theoretical and empirical research in the economic and social sciences, tracing back at least to the contributions of Morgenstern (1928), Wagemann (1929), and Löwe (1929). In recent years, the evaluation of the quality and role of forecasts has itself become the subject of research in the history of economic thought (Antholz, 2006). Moreover, there is a broad interest in the topic of economic and social forecasting not only in the scientific community but also in politics and in the general public. This interest is not surprising given that, unlike earlier crises, the recent financial and economic crisis has led not only to short-lived financial market jitters but, even by historical standards, to a significant downswing in economic activity, a drop in international trade, and a dramatic increase in unemployment in a lot of countries. Therefore the period staring in 2008 has become known as the Great Recession.

The Great Recession also impinged back on the economics profession. Economists became under external pressure as journalist have written books to explain why economists will “also miss the coming crises” (Nienhaus, 2009), but even scholars from within the profession discuss ”the guilt of the economists” (Riedel, 2013). Within the economics profession, a sharp disagreement on possible consequences of this debate emerged. Statements ranged from ”no one saw it coming” (see the examples quoted in Bezemer (2011)) to “the crisis was predictable and predicted (...)”, and so-called “heterodox” economists, who felt marginalized in the economics profession thought that their time had come and claimed that they had foreseen the crisis (see Gaffney (2011) and the sources quoted therein). But also ”mainstream” economists have started to discuss what presumably went wrong and what could be changed to improve the state of the art of economic modeling in general and of economic forecasting in particular. The financial and economic crisis has triggered a broad strand of publications which seeks to extend the dominant DSGE-paradigm in business-cycle analysis to include, for example, certain important facets of real-world financial markets (see De Paoli et al. (2014) and Brunnermeier et al. (2012) and the literature cited therein for an overview of this literature). While some authors argue that no entirely new paradigm in macroeconomic modeling is needed (Buch and Holtemöller, 2014) other authors argue that the economics profession should build macroeconomic models from other micro-foundations (Stiglitz, 2011, 2014) or concentrate on their “roots” (Gordon, 2009).

To sum up, the outburst of interest in economic forecasting following the Great Recession makes it necessary to rethink the role of forecasts and economic experts for society. The research project will take some steps in this direction. We will concentrate on three topics: How should the quality of forecasts be judged? What are the incentive structures for a strategic forecast behavior? What is the role of economic forecasts for the development of economics and the economic profession?

 

Publications

Pierdzioch, C./Reid, M.B./Gupta, R. (2016): Inflation Forecasts and Forecaster Herding: Evidence from South African Survey Data. Journal of Behavioral and Experimental Economics 62: 42−50.

Pierdzioch, C./Reid, M.B./Gupta, R. (2016): Forecasting the South African Inflation Rate: On Asymmetric Loss and Forecast Rationality. Economic Systems (2016) 40: 82−92.

Fritsche, Ulrich/Pierdzioch, Christian (2017): Animal spirits, the stock market, and the unemployment rate: Some evidence for German data, in: Economics Bulletin 37, 1, pp. 204-213

Döpke, Jörg/Fritsche, Ulrich/Pierdzioch, Christian (2017): Predicting recessions with boosted regression trees, in: International Journal of Forecasting 33, S. 745-759

Behrens, C./Pierdzioch, C/M. Risse (2018): A Bayesian Analysis of the Efficiency of Growth and Inflation Forecasts for Germany. Arbeitspapier.

Behrens, C./Pierdzioch, C./Risse, M. (2018): A Test of the Joint Efficiency of Macroeconomic Forecasts Using Multivariate Random Forests. Journal of Forecasting 37: 560−572.

Bonato, M./Demirer, R./Pierdzioch, C./Gupta, R. (2018): Gold Futures Returns and Realized Moments: A Forecasting Experiment Using a Quantile-Boosting Approach. Resources Policy 57: 196−212.

Behrens, C./Pierdzioch, C./Risse, M. (2018): Testing the Optimality of Inflation Forecasts Under Flexible Loss with Random Forests. Economic Modelling 72: 270−277.

Pierdzioch, C./Reid, M.B./Gupta, R. (2018): On the Directional Accuracy of Inflation Forecasts: Evidence from South African Survey Data. Journal of Applied Statistics 45: 884−900.

Döpke, Jörg/Fritsche, Ulrich/Waldhof, Gabi (2019): Theories, Techniques and the Formation of German Business Cycle Forecasts: Evidence from a Survey of Professional Forecasters, in: Journal of Economics and Statistics, 239, 2 (2019), pp. 203-241.

Behrens, Christoph (2019): Evaluating the Joint Efficiency of German Trade Forecasts. A nonparametric multivariate approach. Working Papers of the Priority Programme 1859 “Experience and Expectation. Historical Foundations of Economic Behaviour” No 9 (March), Berlin

Rohloff, S. (2019): Commodity prices and the AUD-Yen exchange rate: A real-time forecasting analysis. Applied Economics 51: 1360-1382.

Pierdzioch, Christian/Gupta, Rangan/Nyakabawo, Wendy/Risse, Marian: On REIT Returns and (Un-)Expected Inflation: Empirical Evidence Based on Bayesian Additive Regression Trees, in: Finance Research Letters 30: 160-169.

Fritsche, Ulrich / Köster, Roman /Lenel, Laetitia (eds.), Futures Past. Economic Forcasting in the 20th and 21st Century, Berlin et al.: Peter Lang 2020.

Döpke, Jörg / Fritsche Ulrich / Waldhof, Gabi: Never Change a Losing Horse? On Adaptions in German Forecasting after the Great Financial Crisis, in: Fritsche, Ulrich / Köster, Roman /Lenel, Laetitia (eds.), Futures Past. Economic Forcasting in the 20th and 21st Century, Berlin et al.: Peter Lang 2020, pp. 191-218.

Pierdzioch, Christian/Risse, Marian (2020): Forecasting Precious Metal Returns With Multivariate Random Forests, in: Empirical Economics 58/3:1167-1184.

Behrens, Christopher: A Nonparametric Evaluation of the Optimality of German Export and Import Growth Forecasts under Flexible Loss, in: Economies 7/3 (2019), 93.

Behrens, Christopher: Evaluating the joint efficiency of German trade forecasts - a nonparametric multivariate approach, in: Applied Economics 52/34 (2020), pp. 3732-3747

Behrens, Christoph (2020): German Trade Forecasts since 1970 - An Evaluation Using the Panel Dimension. Working Papers of the Priority Programme 1859 “Experience and Expectation. Historical Foundations of Economic Behaviour” No 26 (October), Berlin.

Fritsche, Ulrich and Spoerer, Mark. "Introduction: Digital History" Jahrbuch für Wirtschaftsgeschichte / Economic History Yearbook, vol. 64, no. 1, 2023, pp. 1-7. https://doi.org/10.1515/jbwg-2023-0001.