Econometric Tools for Macroeconomic Forecasting and Simulation

The aim of this research group is to enhance research on, and development, implementation, evaluation, and application of quantitative macroeconometric models for forecasting and analysing aggregate economic fluctuations and developments. Research in this group contributes to the econometric foundation and the methodological improvements of the IWH forecasts. During the last years, the IWH has highly specialised in macroeconomic modelling, both for flash estimates and medium-term projections. Furthermore, this group conducts comprehensive empirical analysis and develops econometric tools that are used for third-party funded projects. In the last years, particular models have been developed for e.g. Volkswagen Financial Services AG and for GIZ. The research group contributed in particular on macroeconomic modelling for ministries in Kyrgyzstan and Tajikistan as well as for the institute of forecasting and macroeconomic research (IFMR) Uzbekistan.

IWH Data Project: IWH Real-time Database

Research Cluster
Macroeconomic Dynamics and Stability

Your contact

Dr Katja Heinisch
Dr Katja Heinisch
Mitglied - Department Macroeconomics
Send Message +49 345 7753-836

EXTERNAL FUNDING

10.2019 ‐ 06.2022

Climate Resilient Economic Development

Deutsche Gesellschaft für Internationale Zusammenarbeit (GIZ) GmbH

Climate change has a substantial impact on economic growth and a country’s development. This increases the need for reliable and viable approaches to assessing the impact of climate risks and potential adaptation scenarios. Political decision-makers in ministries of planning and economy need sound forecasts in order to design and finance adequate economic policy instruments and actively to take countermeasures. In the pilot countries (Georgia, Kazakhstan and Vietnam), climate risk is included in macroeconomic modelling, enabling the results to be integrated into the policy process so as to facilitate adapted economic planning. The IWH team is responsible for macroeconomic modelling in Vietnam.

see project's page on GIZ website

Dr Katja Heinisch

05.2020 ‐ 04.2023

ENTRANCES: Energy Transitions from Coal and Carbon: Effects on Societies

European Commission

ENTRANCES aims at examining the effects of the coal phase-out in Europe. How does the phase-out transform society – and what can politics do about it?

see project's webpage

This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 883947.

Professor Dr Oliver Holtemöller
Dr Katja Heinisch

01.2018 ‐ 12.2023

EuropeAid (EU Framework Contract)

European Commission

Professor Dr Oliver Holtemöller

07.2016 ‐ 12.2018

Climate Protection and Coal Phaseout: Political Strategies and Measures up to 2030 and beyond

Umweltbundesamt (UBA)

Dr Katja Heinisch

01.2017 ‐ 12.2017

Support to Sustainable Economic Development in Selected Regions of Uzbekistan

Deutsche Gesellschaft für Internationale Zusammenarbeit (GIZ) GmbH

Dr Andrej Drygalla

01.2017 ‐ 12.2017

Short-term Macroeconomic Forecasting Model in Ministry of Economic Development and Trade of Ukraine

Deutsche Gesellschaft für Internationale Zusammenarbeit (GIZ) GmbH

Dr Andrej Drygalla

01.2016 ‐ 12.2017

Development of analytical tools based on Input-Output table

Deutsche Gesellschaft für Internationale Zusammenarbeit (GIZ) GmbH

The aim of the project was the development of an analytical tool to assess the gains and losses of possible state programs supporting the development of the private sector of the Tajik economy.

Dr Katja Heinisch

11.2015 ‐ 12.2016

Employment and Development in the Republic of Uzbekistan

Deutsche Gesellschaft für Internationale Zusammenarbeit (GIZ) GmbH

Support to sustainable economic development in selected regions of Uzbekistan

Dr Katja Heinisch

05.2016 ‐ 05.2016

Framework and Finance for Private Sector Development in Tajikistan

Deutsche Gesellschaft für Internationale Zusammenarbeit (GIZ) GmbH

Dr Katja Heinisch

02.2016 ‐ 04.2016

Macroeconomic Reforms and Green Growth - Assessment of economic modelling capacity in Vietnam

Deutsche Gesellschaft für Internationale Zusammenarbeit (GIZ) GmbH

Dr Katja Heinisch

Refereed Publications

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The Financial Crisis from a Forecaster's Perspective

Katja Drechsel Rolf Scheufele

in: Kredit und Kapital, No. 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.

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An Evolutionary Algorithm for the Estimation of Threshold Vector Error Correction Models

Makram El-Shagi

in: International Economics and Economic Policy, No. 4, 2011

Abstract

We develop an evolutionary algorithm to estimate Threshold Vector Error Correction models (TVECM) with more than two cointegrated variables. Since disregarding a threshold in cointegration models renders standard approaches to the estimation of the cointegration vectors inefficient, TVECM necessitate a simultaneous estimation of the cointegration vector(s) and the threshold. As far as two cointegrated variables are considered, this is commonly achieved by a grid search. However, grid search quickly becomes computationally unfeasible if more than two variables are cointegrated. Therefore, the likelihood function has to be maximized using heuristic approaches. Depending on the precise problem structure the evolutionary approach developed in the present paper for this purpose saves 90 to 99 per cent of the computation time of a grid search.

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Inflation Expectations: Does the Market Beat Professional Forecasts?

Makram El-Shagi

in: North American Journal of Economics and Finance, No. 3, 2011

Abstract

The present paper compares expected inflation to (econometric) inflation forecasts based on a number of forecasting techniques from the literature using a panel of ten industrialized countries during the period of 1988 to 2007. To capture expected inflation, we develop a recursive filtering algorithm which extracts unexpected inflation from real interest rate data, even in the presence of diverse risks and a potential Mundell-Tobin-effect. The extracted unexpected inflation is compared to the forecasting errors of ten econometric forecasts. Beside the standard AR(p) and ARMA(1,1) models, which are known to perform best on average, we also employ several Phillips curve based approaches, VAR, dynamic factor models and two simple model avering approaches.

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Flow of Conjunctural Information and Forecast of Euro Area Economic Activity

Katja Drechsel L. Maurin

in: Journal of Forecasting, No. 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.

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Working Papers

Understanding Post-Covid Inflation Dynamics

Martín Harding Jesper Lindé Mathias Trabandt

in: Working Paper, 2022

Abstract

We propose a macroeconomic model with a nonlinear Phillips curve that has a flat slope when inflationary pressures are subdued and steepens when inflationary pressures are elevated. The nonlinear Phillips curve in our model arises due to a quasi-kinked demand schedule for goods produced by firms. Our model can jointly account for the modest decline in inflation during the Great Recession and the surge in inflation during the Post-Covid period. Because our model implies a stronger transmission of shocks when inflation is high, it generates conditional heteroscedasticity in inflation and inflation risk. Hence, our model can generate more sizeable inflation surges due to cost-push and demand shocks than a standard linearized model. Finally, our model implies that the central bank faces a more severe trade-off between inflation and output stabilization when inflation is high.

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Economic Sentiment: Disentangling Private Information from Public Knowledge

Katja Heinisch Axel Lindner

in: IWH Discussion Papers, No. 15, 2021

Abstract

This paper addresses a general problem with the use of surveys as source of information about the state of an economy: Answers to surveys are highly dependent on information that is publicly available, while only additional information that is not already publicly known has the potential to improve a professional forecast. We propose a simple procedure to disentangle the private information of agents from knowledge that is already publicly known for surveys that ask for general as well as for private prospects. Our results reveal the potential of our proposed technique for the usage of European Commissions‘ consumer surveys for economic forecasting for Germany.

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Conditional Macroeconomic Forecasts: Disagreement, Revisions and Forecast Errors

Alexander Glas Katja Heinisch

in: IWH Discussion Papers, No. 7, 2021

Abstract

Using data from the European Central Bank‘s Survey of Professional Forecasters, we analyse the role of ex-ante conditioning variables for macroeconomic forecasts. In particular, we test to which extent the heterogeneity, updating and ex-post performance of predictions for inflation, real GDP growth and the unemployment rate are related to assumptions about future oil prices, exchange rates, interest rates and wage growth. Our findings indicate that inflation forecasts are closely associated with oil price expectations, whereas expected interest rates are used primarily to predict output growth and unemployment. Expectations about exchange rates and wage growth also matter for macroeconomic forecasts, albeit less so than oil prices and interest rates. We show that survey participants can considerably improve forecast accuracy for macroeconomic outcomes by reducing prediction errors for external conditions. Our results contribute to a better understanding of the expectation formation process of experts.

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Disentangling Covid-19, Economic Mobility, and Containment Policy Shocks

Annika Camehl Malte Rieth

in: IWH Discussion Papers, No. 2, 2021

Abstract

We study the dynamic impact of Covid-19, economic mobility, and containment policy shocks. We use Bayesian panel structural vector autoregressions with daily data for 44 countries, identified through sign and zero restrictions. Incidence and mobility shocks raise cases and deaths significantly for two months. Restrictive policy shocks lower mobility immediately, cases after one week, and deaths after three weeks. Non-pharmaceutical interventions explain half of the variation in mobility, cases, and deaths worldwide. These flattened the pandemic curve, while deepening the global mobility recession. The policy tradeoff is 1 p.p. less mobility per day for 9% fewer deaths after two months.

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Integrated Assessment of Epidemic and Economic Dynamics

Oliver Holtemöller

in: IWH Discussion Papers, No. 4, 2020

Abstract

In this paper, a simple integrated model for the joint assessment of epidemic and economic dynamics is developed. The model can be used to discuss mitigation policies like shutdown and testing. Since epidemics cause output losses due to a reduced labor force, temporarily reducing economic activity in order to prevent future losses can be welfare enhancing. Mitigation policies help to keep the number of people requiring intensive medical care below the capacity of the health system. The optimal policy is a mixture of temporary partial shutdown and intensive testing and isolation of infectious persons for an extended period of time.

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