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

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

Katja Heinisch Rolf Scheufele

in: Empirical Economics , im Erscheinen

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

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The European Refugee Crisis and the Natural Rate of Output

Katja Heinisch Klaus Wohlrabe

in: Applied Economics Letters , im Erscheinen

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

The Performance of Short-term Forecasts of the German Economy before and during the 2008/2009 Recession

Katja Drechsel Rolf Scheufele

in: International Journal of Forecasting , Nr. 2, 2012

Abstract

The paper analyzes the forecasting performance of leading indicators for industrial production in Germany. We focus on single and pooled leading indicator models both before and during the financial crisis. Pairwise and joint significant tests are used to evaluate single indicator models as well as forecast combination methods. In addition, we investigate the stability of forecasting models during the most recent financial crisis.

Publikation lesen

The Financial Crisis from a Forecaster's Perspective

Katja Drechsel Rolf Scheufele

in: Kredit und Kapital , Nr. 1, 2012

Abstract

This paper analyses the recession in 2008/2009 in Germany. This recession is very different from previous recessions in particular regarding their causes and magnitude. We show to what extent forecasters and forecasts based on leading indicators fail to detect the timing and the magnitude of the recession. This study shows that large forecast errors for both expert forecasts and forecasts based on leading indicators resulted during this recession which implies that the recession was very difficult to forecast. However, some leading indicators (survey data, risk spreads, stock prices) have indicated an economic downturn and hence, beat univariate time series models. Although the combination of individual forecasts provides an improvement compared to the benchmark model, the combined forecasts are worse than several individual models. A comparison of expert forecasts withthe best forecasts based on leading indicators shows only minor deviations. Overall, the range for an improvement of expert forecasts in the crisis compared to indicator forecasts is small.

Publikation lesen

Flow of Conjunctural Information and Forecast of Euro Area Economic Activity

Katja Drechsel L. Maurin

in: Journal of Forecasting , Nr. 3, 2011

Abstract

Combining forecasts, we analyse the role of information flow in computing short-term forecasts up to one quarter ahead for the euro area GDP and its main components. A dataset of 114 monthly indicators is set up and simple bridge equations are estimated. The individual forecasts are then pooled, using different weighting schemes. To take into consideration the release calendar of each indicator, six forecasts are compiled successively during the quarter. We found that the sequencing of information determines the weight allocated to each block of indicators, especially when the first month of hard data becomes available. This conclusion extends the findings of the recent literature. Moreover, when combining forecasts, two weighting schemes are found to outperform the equal weighting scheme in almost all cases. Compared to an AR forecast, these improve by more than 40% the forecast performance for GDP in the current and next quarter.

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

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

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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