Ökonometrische Methoden für wirtschaftliche Prognosen

Die Forschungsgruppe gehört zum IWH-Forschungscluster Gesamtwirtschaftliche Dynamik und Stabilität. Der Forschungsschwerpunkt der Gruppe liegt in der Entwicklung ökonometrischer Methoden für Kurzfristprognosen (Reduzierte-Form-Modelle), für Regionalisierung und für Langfristprojektionen sowie für strukturelle Prognose- und Simulationsmodelle (DSGE-Modelle). Ferner erstellt sie ökonometrische Hintergrundanalysen für die Prognosetätigkeit der Forschungsgruppe Makroökonomische Analysen und Prognosen. Im Rahmen von Drittmittelprojekten wurden verschiedene makroökonomische Modelle, bspw. für die Volkswagen Financial Services AG oder im Rahmen von GIZ-Projekten für die Wirtschaftsministerien in Kirgistan und Tadschikistan sowie das Institut für makroökonomische Prognosen und Forschung (IFMR) in Usbekistan entwickelt.

IWH-Datenprojekt: IWH Real-time Database

Forschungscluster
Gesamtwirtschaftliche Dynamik und Stabilität

Ihr Kontakt

Dr. Katja Heinisch
Dr. Katja Heinisch
Mitglied - Abteilung Makroökonomik
Nachricht senden +49 345 7753-836

PROJEKTE

11.2015 ‐ 12.2016

Beschäftigung und Entwicklung in der Republik Usbekistan

Deutsche Gesellschaft für Internationale Zusammenarbeit (GIZ) GmbH

Förderung einer nachhaltigen wirtschaftlichen Entwicklung in ausgewählten Regionen Usbekistans

Dr. Katja Heinisch

05.2016 ‐ 05.2016

Rahmenbedingungen und Finanzierungsmöglichkeiten für die Entwicklung des Privatsektors in Tadschikistan

Deutsche Gesellschaft für Internationale Zusammenarbeit (GIZ) GmbH

Dr. Katja Heinisch

07.2016 ‐ 12.2017

Klimaschutz und Kohleausstieg: Politische Strategien und Maßnahmen bis 2030 und darüber hinaus

Umweltbundesamt (UBA)

Dr. Katja Heinisch

02.2016 ‐ 04.2016

Makroökonomische Reformen und umwelt- und sozialverträgliches Wachstum in Vietnam

Deutsche Gesellschaft für Internationale Zusammenarbeit (GIZ) GmbH

Dr. Katja Heinisch

Referierte Publikationen

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For How Long Do IMF Forecasts of World Economic Growth Stay Up-to-date?

Katja Heinisch Axel Lindner

in: Applied Economics Letters, im Erscheinen

Abstract

This study analyses the performance of the International Monetary Fund (IMF) World Economic Outlook output forecasts for the world and for both the advanced economies and the emerging and developing economies. With a focus on the forecast for the current year and the next year, we examine the durability of IMF forecasts, looking at how much time has to pass so that IMF forecasts can be improved by using leading indicators with monthly updates. Using a real-time data set for GDP and for indicators, we find that some simple single-indicator forecasts on the basis of data that are available at higher frequency can significantly outperform the IMF forecasts as soon as the publication of the IMF’s Outlook is only a few months old. In particular, there is an obvious gain using leading indicators from January to March for the forecast of the current year.

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Should Forecasters Use Real-time Data to Evaluate Leading Indicator Models for GDP Prediction? German Evidence

Katja Heinisch Rolf Scheufele

in: German Economic Review, im Erscheinen

Abstract

In this paper, we investigate whether differences exist among forecasts using real‐time or latest‐available data to predict gross domestic product (GDP). We employ mixed‐frequency models and real‐time data to reassess the role of surveys and financial data relative to industrial production and orders in Germany. Although we find evidence that forecast characteristics based on real‐time and final data releases differ, we also observe minimal impacts on the relative forecasting performance of indicator models. However, when obtaining the optimal combination of soft and hard data, the use of final release data may understate the role of survey information.

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On DSGE Models

Lawrence J. Christiano Martin S. Eichenbaum Mathias Trabandt

in: Journal of Economic Perspectives, Nr. 3, 2018

Abstract

The outcome of any important macroeconomic policy change is the net effect of forces operating on different parts of the economy. A central challenge facing policymakers is how to assess the relative strength of those forces. Economists have a range of tools that can be used to make such assessments. Dynamic stochastic general equilibrium (DSGE) models are the leading tool for making such assessments in an open and transparent manner. We review the state of mainstream DSGE models before the financial crisis and the Great Recession. We then describe how DSGE models are estimated and evaluated. We address the question of why DSGE modelers—like most other economists and policymakers—failed to predict the financial crisis and the Great Recession, and how DSGE modelers responded to the financial crisis and its aftermath. We discuss how current DSGE models are actually used by policymakers. We then provide a brief response to some criticisms of DSGE models, with special emphasis on criticism by Joseph Stiglitz, and offer some concluding remarks.

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Bottom-up or Direct? Forecasting German GDP in a Data-rich Environment

Katja Heinisch Rolf Scheufele

in: Empirical Economics, Nr. 2, 2018

Abstract

In this paper, we investigate whether there are benefits in disaggregating GDP into its components when nowcasting GDP. To answer this question, we conduct a realistic out-of-sample experiment that deals with the most prominent problems in short-term forecasting: mixed frequencies, ragged-edge data, asynchronous data releases and a large set of potential information. We compare a direct leading indicator-based GDP forecast with two bottom-up procedures—that is, forecasting GDP components from the production side or from the demand side. Generally, we find that the direct forecast performs relatively well. Among the disaggregated procedures, the production side seems to be better suited than the demand side to form a disaggregated GDP nowcast.

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The European Refugee Crisis and the Natural Rate of Output

Katja Heinisch Klaus Wohlrabe

in: Applied Economics Letters, Nr. 16, 2017

Abstract

The European Commission follows a harmonized approach for calculating structural (potential) output for EU member states that takes into account labour as an important ingredient. This article shows how the recent huge migrants’ inflow to Europe affects trend output. Due to the fact that the immigrants immediately increase the working population but effectively do not enter the labour market, we illustrate that the potential output is potentially upward biased without any corrections. Taking Germany as an example, we find that the average medium-term potential growth rate is lower if the migration flow is modelled adequately compared to results based on the unadjusted European Commission procedure.

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Arbeitspapiere

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Expectation Formation, Financial Frictions, and Forecasting Performance of Dynamic Stochastic General Equilibrium Models

Oliver Holtemöller Christoph Schult

in: IWH-Diskussionspapiere, Nr. 15, 2018

Abstract

In this paper, we document the forecasting performance of estimated basic dynamic stochastic general equilibrium (DSGE) models and compare this to extended versions which consider alternative expectation formation assumptions and financial frictions. We also show how standard model features, such as price and wage rigidities, contribute to forecasting performance. It turns out that neither alternative expectation formation behaviour nor financial frictions can systematically increase the forecasting performance of basic DSGE models. Financial frictions improve forecasts only during periods of financial crises. However, traditional price and wage rigidities systematically help to increase the forecasting performance.

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The Effects of Fiscal Policy in an Estimated DSGE Model – The Case of the German Stimulus Packages During the Great Recession

Andrej Drygalla Oliver Holtemöller Konstantin Kiesel

in: IWH-Diskussionspapiere, Nr. 34, 2017

Abstract

In this paper, we analyse the effects of the stimulus packages adopted by the German government during the Great Recession. We employ a standard medium-scale dynamic stochastic general equilibrium (DSGE) model extended by non-optimising households and a detailed fiscal sector. In particular, the dynamics of spending and revenue variables are modeled as feedback rules with respect to the cyclical component of output. Based on the estimated rules, fiscal shocks are identified. According to the results, fiscal policy, in particular public consumption, investment, transfers and changes in labour tax rates including social security contributions prevented a sharper and prolonged decline of German output at the beginning of the Great Recession, suggesting a timely response of fiscal policy. The overall effects, however, are small when compared to other domestic and international shocks that contributed to the economic downturn. Our overall findings are not sensitive to the allowance of fiscal foresight.

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Progressive Tax-like Effects of Inflation: Fact or Myth? The U.S. Post-war Experience

Matthias Wieschemeyer Bernd Süssmuth

in: IWH-Diskussionspapiere, Nr. 33, 2017

Abstract

Inflation and earnings growth can push some tax payers into higher brackets in the absence of inflation-indexed schedules. Moreover, inflation may affect the composition of individuals’ income sources. As a result, depending on the relative tax burden of labour and capital, inflation may decrease or increase the difference between before-tax and after-tax income. However, whether some and if so which percentiles of the income distribution net benefit from inflation via taxation is a widely unexplored question. We make use of a novel dataset on U.S. pre-tax and post-tax income distribution series provided by Pike ty et al. (2018) for the years 1962 to 2014 to answer this question. To this end, we estimate local projections to quantify dynamic effects. We find that inflation shocks increase progressivity of taxation not only contemporaneously but also with some repercussion of several years after the shock. While particularly the bottom two quintiles gain in share, it is not the top but the fourth quintile that lastingly loses.

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Outperforming IMF Forecasts by the Use of Leading Indicators

Katja Drechsel Sebastian Giesen Axel Lindner

in: IWH-Diskussionspapiere, Nr. 4, 2014

Abstract

This study analyzes the performance of the IMF World Economic Outlook forecasts for world output and the aggregates of both the advanced economies and the emerging and developing economies. With a focus on the forecast for the current and the next year, we examine whether IMF forecasts can be improved by using leading indicators with monthly updates. Using a real-time dataset for GDP and for the indicators we find that some simple single-indicator forecasts on the basis of data that are available at higher frequency can significantly outperform the IMF forecasts if the publication of the Outlook is only a few months old.

Publikation lesen

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A Federal Long-run Projection Model for Germany

Oliver Holtemöller Maike Irrek Birgit Schultz

in: IWH-Diskussionspapiere, Nr. 11, 2012

Abstract

Many economic decisions implicitly or explicitly rely on a projection of the medium- or long-term economic development of a country or region. In this paper, we provide a federal long-run projection model for Germany and the German states. The model fea-tures a top-down approach and, as major contribution, uses error correction models to estimate the regional economic development dependent on the national projection. For the medium- and long-term projection of economic activity, we apply a production function approach. We provide a detailed robustness analysis by systematically varying assumptions of the model. Additionally, we explore the effects of different demographic trends on economic development.

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