Dr Katja Heinisch

Dr Katja Heinisch
Current Position

since 1/13

Head of the Research Group Econometric Tools for Macroeconomic Forecasting

Halle Institute for Economic Research (IWH) – Member of the Leibniz Association

since 9/09

Economist in the Department of Macroeconomics

Halle Institute for Economic Research (IWH) – Member of the Leibniz Association

Research Interests

  • international macroeconomics
  • applied time series econometrics and short-term forecasting
  • macroeconometric modeling

Katja Heinisch joined the Department of Macroeconomics in September 2009. Her research focuses on short-term forecasting and macroeconometric modelling.

Katja Heinisch earned a diploma from Chemnitz University of Technology and University of Strasbourg. She received her PhD from Osnabrück University. Katja Heinisch gained international research experience while working at the European Central Bank (ECB) and the International Monetary Fund (IMF).

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Dr Katja Heinisch
Dr Katja Heinisch
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Publications

Recent Publications

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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, No. 3, 2019

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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Mittelfristprojektion des IWH: Wirtschaftsentwicklung und Öffentliche Finanzen 2018 bis 2025

Andrej Drygalla Katja Heinisch Oliver Holtemöller Axel Lindner Matthias Wieschemeyer Götz Zeddies

in: Konjunktur aktuell, No. 4, 2018

Abstract

In Deutschland wird die Anzahl der Erwerbspersonen mittelfristig aufgrund der Alterung der Bevölkerung sinken und damit auch das Wirtschaftswachstum niedriger ausfallen als in den vergangenen Jahren. Gleichzeitig hat die Bundesregierung eine Reihe von zusätzlichen Staatsausgaben beschlossen. Auf der Grundlage einer gesamtwirtschaftlichen Projektion mit dem IWH-Deutschlandmodell lässt sich aber zeigen, dass es bis zum Jahr 2025 kaum zu Haushaltsdefiziten kommt, auch wenn sämtliche im Koalitionsvertrag enthaltenen finanzpolitischen Maßnahmen umgesetzt werden. Selbst wenn sich die makroökonomischen Rahmenbedingungen verschlechtern, etwa wegen eines deutlichen Zinsanstiegs oder eines Einbruchs der ausländischen Nachfrage, würde der Finanzierungssaldo zwar negativ, die zu erwartenden Defizite lägen aber dennoch wohl unter 0,5% in Relation zum Bruttoinlandspro-dukt. Ein Einbruch der ausländischen Nachfrage würde die Produktion zwar stärker dämpfen als ein Zinsschock, die Effekte auf den gesamtstaatlichen Finanzierungssaldo wären aber vergleichbar. Denn ein Zinsschock belastet eher die Binnennachfrage, von deren Rückgang die staatlichen Einnahmen stärker betroffen sind als von einem Rückgang der Exporte. Für die kommenden Jahre dürfte der deutsche Staatshaushalt damit recht robust sein; dabei ist aber zu beachten, dass etwa die aus dem Rentenpaket resultierenden Mehrausgaben erst nach dem Jahr 2025 deutlich zu Buche schlagen.

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IWH-Flash-Indikator IV. Quartal 2018 und I. Quartal 2019

Katja Heinisch

in: One-off Publications, No. 4, 2018

Abstract

Die deutsche Wirtschaft hat im dritten Quartal 2018 einen deutlichen Dämpfer erhalten. Sie schrumpfte um 0,2%, nachdem sie in den vergangenen drei Jahren kontinuierlich expandiert hatte. Der aktuelle IWH-Flash-Indikator deutet darauf hin, dass die wirtschaftliche Aktivität im vierten Quartal 2018 und ersten Quartal 2019 mit jeweils 0,2% langsam wieder Fahrt aufnehmen wird.

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Refereed Publications

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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, forthcoming

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

Katja Heinisch Axel Lindner

in: Applied Economics Letters, No. 3, 2019

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

Katja Heinisch Rolf Scheufele

in: Empirical Economics, No. 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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Working Papers

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Outperforming IMF Forecasts by the Use of Leading Indicators

Katja Drechsel Sebastian Giesen Axel Lindner

in: IWH Discussion Papers, No. 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.

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Should We Trust in Leading Indicators? Evidence from the Recent Recession

Katja Drechsel Rolf Scheufele

in: IWH Discussion Papers, No. 10, 2010

Abstract

The paper analyzes leading indicators for GDP and industrial production in Germany. We focus on the performance of single and pooled leading indicators during the pre-crisis and crisis period using various weighting schemes. Pairwise and joint significant tests are used to evaluate single indicator as well as forecast combination methods. In addition, we use an end-of-sample instability test to investigate the stability of forecasting models during the recent financial crisis. We find in general that only a small number of single indicator models were performing well before the crisis. Pooling can substantially increase the reliability of leading indicator forecasts. During the crisis the relative performance of many leading indicator models increased. At short horizons, survey indicators perform best, while at longer horizons financial indicators, such as term spreads and risk spreads, improve relative to the benchmark.

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Flow of conjunctural information and forecast of euro area economic activity

Katja Drechsel L. Maurin

in: ECB Working Paper, no. 925, 2008

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