25 Jahre IWH

Dr. Katja Heinisch

Dr. Katja Heinisch
Aktuelle Position

seit 1/13

Leiterin der Forschungsgruppe Ökonometrische Methoden für wirtschaftliche Prognosen

Leibniz-Institut für Wirtschaftsforschung Halle (IWH)

seit 9/09

Wissenschaftliche Mitarbeiterin der Abteilung Makroökonomik

Leibniz-Institut für Wirtschaftsforschung Halle (IWH)

Forschungsschwerpunkte

  • internationale Makroökonomik
  • angewandte Zeitreihenökonometrie, insb. Kurzfristprognose
  • strukturelle makroökonometrische Modelle

Dr. Katja Heinisch ist seit 2009 wissenschaftliche Mitarbeiterin in der Abteilung Makroökonomik und leitet seit 2013 die Forschungsgruppe "Ökonometrische Methoden für wirtschaftliche Prognosen". Zu ihren Forschungsschwerpunkten zählen insbesondere Kurzfristprognosen und die ökonometrische Modellierung gesamtwirtschaftlicher Zusammenhänge.

Nach ihrem Studium der Volkswirtschaftslehre an der Technischen Universität Chemnitz und der Universität Louis Pasteur Straßburg (Frankreich) war Katja Heinisch als wissenschaftliche Mitarbeiterin am Institut für Empirische Wirtschaftsforschung, Fachgebiet Internationale Wirtschaftspolitik, an der Universität Osnabrück tätig. Während ihrer Dissertationszeit absolvierte Katja Heinisch Forschungsaufenthalte an der Europäischen Zentralbank (EZB) und beim Internationalen Währungsfonds (IWF). Die Promotion erfolgte 2010 an der Universität Osnabrück.

Ihr Kontakt

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

Publikationen

Neueste 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.

Publikation lesen

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.

Publikation lesen

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Konjunktur aktuell: Deutscher Aufschwung schwächt sich ab

Oliver Holtemöller Hans-Ulrich Brautzsch João Carlos Claudio Andrej Drygalla Franziska Exß Katja Heinisch Axel Lindner Oliver Rehbein Birgit Schultz Matthias Wieschemeyer Götz Zeddies Martina Kämpfe Jan-Christopher Scherer

in: Konjunktur aktuell, Nr. 2, 2018

Abstract

Die jüngste Zuspitzung des von der US-Regierung entfachten handelspolitischen Streits bedeutet ein erhebliches Risiko für Welthandel und internationale Konjunktur. Dennoch sind die weltwirtschaftlichen Aussichten weiter recht günstig. Insbesondere für die USA ist wegen der massiven finanzpolitischen Impulse mit kräftigen Zuwachsraten zu rechnen. Allerdings hat sich die Konjunktur im Euroraum seit Jahresanfang deutlich abgeschwächt, und seit Mai dürften Sorgen um den finanzpolitischen Kurs der neuen Regierung in Italien die wirtschaftlichen Erwartungen in Europa zusätzlich drücken.

Publikation lesen

 

Referierte Publikationen

cover_applied-economics-letters.jpg

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.

Publikation lesen

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.

Publikation lesen

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.

Publikation lesen

Arbeitspapiere

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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: IWH-Diskussionspapiere, Nr. 5, 2017
publiziert in: German Economic Review

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 survey 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.

Publikation lesen

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The European Refugee Crisis and the Natural Rate of Output

Katja Heinisch Klaus Wohlrabe

in: IWH-Diskussionspapiere, Nr. 30, 2016
publiziert in: Applied Economics Letters

Abstract

The European Commission follows a harmonized approach for calculating structural (potential) output for EU member states that takes into account labor as an important ingredient. This paper 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 labor 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 modeled adequately compared to results based on the unadjusted European Commission procedure.

Publikation lesen

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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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