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02.10.2019 • 20/2019
Joint Economic Forecast Autumn 2019: Economy Cools Further – Industry in Recession
Berlin, October 2, 2019 – Germany’s leading economics research institutes have revised their economic forecast for Germany significantly downward. Whereas in the spring they still expected gross domestic product (GDP) to grow by 0.8% in 2019, they now expect GDP growth to be only 0.5%. Reasons for the poor performance are the falling worldwide demand for capital goods – in the exporting of which the Germany economy is specialised – as well as political uncertainty and structural changes in the automotive industry. By contrast, monetary policy is shoring up macroeconomic expansion. For the coming year, the economic researchers have also reduced their forecast of GDP growth to 1.1%, having predicted 1.8% in the spring.
Oliver Holtemöller
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Employment Effects of Introducing a Minimum Wage: The Case of Germany
Oliver Holtemöller, Felix Pohle
Abstract
This paper contributes to the empirical literature on the employment effects of minimum wages. We analysed the introduction of a statutory minimum wage in Germany in 2015 exploiting cross-sectional variation of the minimum wage affectedness. We construct two variables that measure the affectedness for approximately 300 state-industry combinations based on aggregate monthly income data. The estimation strategy consists of two steps. We test for (unidentified) structural breaks in a model with cross-section specific trends to control for state-industry specific developments prior to 2015. In a second step, we test whether the trend deviations are correlated with the minimum wage affectedness. To identify the minimum wage effect on employment, we assume that the minimum wage introduction is exogenous. Our results point towards a negative effect on marginal employment and a positive effect on socially insured employment. Furthermore, we analyse if the increase in socially insured employment is systematically related to the reduction of marginal employment but do not detect evidence.
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„Challenges for Forecasting – Structural Breaks, Revisions and Measurement Errors” 16th IWH-CIREQ Macroeconometric Workshop
Matthias Wieschemeyer
Wirtschaft im Wandel,
No. 1,
2016
Abstract
Am 7. und 8. Dezember 2015 fand am Leibniz-Institut für Wirtschaftsforschung Halle (IWH) zum 16. Mal der IWH-CIREQ Macroeconometric Workshop statt. Die in Kooperation mit dem Centre interuniversitaire de recherche en économie quantitative (CIREQ), Montréal, durchgeführte Veranstaltung beschäftigte sich dieses Mal mit zentralen Herausforderungen, denen sich die ökonomische Prognose zu stellen hat: Strukturbrüche in den Daten, statistische Revisionen und Fehler bei der Messung wichtiger Indikatoren.
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Flight Patterns and Yields of European Government Bonds
Gregor von Schweinitz
IWH Discussion Papers,
No. 10,
2013
Abstract
The current European Debt Crisis has led to a reinforced effort to identify the sources of risk and their influence on yields of European Government Bonds. Until now, the potentially nonlinear influence and the theoretical need for interactions reflecting flight-to-quality and flight-to-liquidity has been widely disregarded. I estimate government bond yields of the Euro-12 countries without Luxembourg from May 2003 until December 2011. Using penalized spline regression, I find that the effect of most explanatory variables is highly nonlinear. These nonlinearities, together with flight patterns of flight-to-quality and flight-to-liquidity, can explain the co-movement of bond yields until September 2008 and the huge amount of differentiation during the financial and the European debt crisis without the unnecessary assumption of a structural break. The main effects are credit risk and flight-to-liquidity, while the evidence for the existence of flight-to-quality and liquidity risk (the latter measured by the bid-ask spread and total turnover of bonds) is comparably weak.
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Testing for Structural Breaks at Unknown Time: A Steeplechase
Makram El-Shagi, Sebastian Giesen
Computational Economics,
No. 1,
2013
Abstract
This paper analyzes the role of common data problems when identifying structural breaks in small samples. Most notably, we survey small sample properties of the most commonly applied endogenous break tests developed by Brown et al. (J R Stat Soc B 37:149–163, 1975) and Zeileis (Stat Pap 45(1):123–131, 2004), Nyblom (J Am Stat Assoc 84(405):223–230, 1989) and Hansen (J Policy Model 14(4):517–533, 1992), and Andrews et al. (J Econ 70(1):9–38, 1996). Power and size properties are derived using Monte Carlo simulations. We find that the Nyblom test is on par with the commonly used F type tests in a small sample in terms of power. While the Nyblom test’s power decreases if the structural break occurs close to the margin of the sample, it proves far more robust to nonnormal distributions of the error term that are found to matter strongly in small samples although being irrelevant asymptotically for all tests that are analyzed in this paper.
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Testing for Structural Breaks at Unknown Time: A Steeplechase
Makram El-Shagi, Sebastian Giesen
Abstract
This paper analyzes the role of common data problems when identifying structural breaks in small samples. Most notably, we survey small sample properties of the most commonly applied endogenous break tests developed by Brown, Durbin, and Evans (1975) and Zeileis (2004), Nyblom (1989) and Hansen (1992), and Andrews, Lee, and Ploberger (1996). Power and size properties are derived using Monte Carlo simulations. Results emphasize that mostly the CUSUM type tests are affected by the presence of heteroscedasticity, whereas the individual parameter Nyblom test and AvgLM test are proved to be highly robust. However, each test is significantly affected by leptokurtosis. Contrarily to other tests, where skewness is far more problematic than kurtosis, it has no additional effect for any of the endogenous break tests we analyze. Concerning overall robustness the Nyblom test performs best, while being almost on par to more recently developed tests in terms of power.
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