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

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

flash2018q1-2018q2.jpg

IWH-Flash-Indikator I. Quartal und II. Quartal 2018

Katja Heinisch

in: Einzelveröffentlichungen , Nr. 1, 2018

Abstract

Die deutsche Wirtschaft hat ihr hohes Expansionstempo auch zuletzt weiter halten können. Das Bruttoinlandsprodukt (BIP) stieg im vierten Quartal 2017 – wie vom IWH-Flash-Indikator im November 2017 angezeigt – mit 0,6% fast genauso schnell wie im Vorquartal. Der IWH-Flash-Indikator deutet darauf hin, dass das Expansionstempo im ersten Quartal 2018 noch einmal leicht zulegen wird, im zweiten Quartal 2018 dann jedoch etwas nachlässt. Das Bruttoinlandsprodukt dürfte damit im ersten Quartal 2018 um 0,7% und im zweiten Quartal 2018 um 0,4% steigen.

Publikation lesen

 

Referierte Publikationen

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

cover_applied-economics-letters.jpg

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.

Publikation lesen

Arbeitspapiere

cover_DP_2017-5.jpg

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

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

cover_DP_2016-30.jpg

The European Refugee Crisis and the Natural Rate of Output

Katja Heinisch Klaus Wohlrabe

in: IWH-Diskussionspapiere , Nr. 30, 2016

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

Cover_IWH-Discussion-Papers_2016.jpg

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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