Why is Unemployment so Countercyclical?
Lawrence J. Christiano, Martin S. Eichenbaum, Mathias Trabandt
Abstract
We argue that wage inertia plays a pivotal role in allowing empirically plausible variants of the standard search and matching model to account for the large countercyclical response of unemployment to shocks.
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Nowcasting East German GDP Growth: a MIDAS Approach
João Carlos Claudio, Katja Heinisch, Oliver Holtemöller
Abstract
Economic forecasts are an important element of rational economic policy both on the federal and on the local or regional level. Solid budgetary plans for government expenditures and revenues rely on efficient macroeconomic projections. However, official data on quarterly regional GDP in Germany are not available, and hence, regional GDP forecasts do not play an important role in public budget planning. We provide a new quarterly time series for East German GDP and develop a forecasting approach for East German GDP that takes data availability in real time and regional economic indicators into account. Overall, we find that mixed-data sampling model forecasts for East German GDP in combination with model averaging outperform regional forecast models that only rely on aggregate national information.
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Does Machine Learning Help us Predict Banking Crises?
Johannes Beutel, Sophia List, Gregor von Schweinitz
Journal of Financial Stability,
December
2019
Abstract
This paper compares the out-of-sample predictive performance of different early warning models for systemic banking crises using a sample of advanced economies covering the past 45 years. We compare a benchmark logit approach to several machine learning approaches recently proposed in the literature. We find that while machine learning methods often attain a very high in-sample fit, they are outperformed by the logit approach in recursive out-of-sample evaluations. This result is robust to the choice of performance metric, crisis definition, preference parameter, and sample length, as well as to using different sets of variables and data transformations. Thus, our paper suggests that further enhancements to machine learning early warning models are needed before they are able to offer a substantial value-added for predicting systemic banking crises. Conventional logit models appear to use the available information already fairly efficiently, and would for instance have been able to predict the 2007/2008 financial crisis out-of-sample for many countries. In line with economic intuition, these models identify credit expansions, asset price booms and external imbalances as key predictors of systemic banking crises.
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Trade, Misallocation, and Capital Market Integration
Laszlo Tetenyi
IWH-CompNet Discussion Papers,
No. 8,
2019
Abstract
I study how cross-country capital market integration affects the gains from trade in a model with financial frictions and heterogeneous, forward-looking firms. The model predicts that misallocation among exporters increases as trade barriers fall, even as misallocation decreases in the aggregate. The reason is that financially constrained productive exporters increase their production only marginally, while unproductive exporters survive for longer and increase their size. Allowing capital inflows magnifies misallocation, because unproductive firms expand even more, leading to a decline in aggregate productivity. Nevertheless, under integrated capital markets, access to cheaper capital dominates the adverse effect on productivity, leading to higher output, consumption and welfare than under closed capital markets. Applied to the period of European integration between 1992 and 2008, I find that underdeveloped sectors experiencing higher export exposure had more misallocation of capital and a higher share of unproductive firms, thus the data is consistent with the model’s predictions. A key implication of the model is that TFP is a poor proxy for consumption growth after trade liberalisation.
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Total Factor Productivity and the Terms of Trade
Jan Teresinski
IWH-CompNet Discussion Papers,
No. 6,
2019
Abstract
In this paper we analyse how the terms of trade (TOT) – the ratio of export prices to import prices – affect total factor productivity (TFP). We provide empirical macroeconomic evidence for the European Union countries based on the times series SVAR analysis and microeconomic evidence based on industry level data from the Competitiveness Research Network (CompNet) database which shows that the terms of trade improvements are associated with a slowdown in the total factor productivity growth. Next, we build a theoretical model which combines open economy framework with the endogenous growth theory. In the model the terms of trade improvements increase demand for labour employed in exportable goods production at the expense of technology production (research and development – R&D) which leads to a shift of resources from knowledge development towards physical exportable goods. This reallocation has a negative impact on the TFP growth. Under a plausible calibration the model is able to replicate the observed empirical pattern.
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Thou Shalt not Bear False Witness Against Your Customers: Cultural Norms and the Volkswagen Scandal
Iftekhar Hasan, Felix Noth, Lena Tonzer
Abstract
This paper investigates whether cultural norms shaped by religion drive consumer decisions after a corporate scandal. We exploit the unexpected notice of violation by the US Environmental Protection Agency in September 2015, accusing the car producer Volkswagen (VW) to have used software to manipulate car emission values during test phases. Using a difference-in-difference model, we show that new registrations of VW (diesel) cars decline significantly in German counties with a high share of Protestants following the VW scandal. Our results suggest that the enforcement culture rooted in Protestantism affects consumer decisions and penalises corporate fraud.
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Should Forecasters Use Real‐time Data to Evaluate Leading Indicator Models for GDP Prediction? German Evidence
Katja Heinisch, Rolf Scheufele
German Economic Review,
No. 4,
2019
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.
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19.09.2019 • 19/2019
Long-term effects of privatisation in eastern Germany: award-winning US economist begins large-scale research project at the IWH
It is one of the most prestigious awards in the German scientific community: the Max Planck-Humboldt Research Award 2019 endowed with €1.5 million goes to Ufuk Akcigit, Professor of Economics at the University of Chicago. At the Halle Institute for Economic Research (IWH), Akcigit aims to use innovative methods to investigate why the economy in eastern Germany is still lagging behind that in western Germany – and what role the privatisation process 30 years ago played in this.
Reint E. Gropp
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The Impact of Innovation and Innovation Subsidies on Economic Development in German Regions
Uwe Cantner, Eva Dettmann, Alexander Giebler, Jutta Günther, Maria Kristalova
Regional Studies,
No. 9,
2019
Abstract
Public innovation subsidies in a regional environment are expected to unfold a positive economic impact over time. The focus of this paper is on an assessment of the long-run impact of innovation and innovation subsidies in German regions. This is scrutinized by an estimation approach combining panel model and time-series characteristics and using regional data for the years 1980–2014. The results show that innovation and innovation subsidies in the long run have a positive impact on the economic development of regions in Germany. This supports a long-term strategy for regional and innovation policy.
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Pricing Sin Stocks: Ethical Preference vs. Risk Aversion
Stefano Colonnello, Giuliano Curatola, Alessandro Gioffré
European Economic Review,
2019
Abstract
We develop an ethical preference-based model that reproduces the average return and volatility spread between sin and non-sin stocks. Our investors do not necessarily boycott sin companies. Rather, they are open to invest in any company while trading off dividends against ethicalness. When dividends and ethicalness are complementary goods and investors are sufficiently risk averse, the model predicts that the dividend share of sin companies exhibits a positive relation with the future return and volatility spreads. An empirical analysis supports the model’s predictions. Taken together, our results point to the importance of ethical preferences for investors’ portfolio choices and asset prices.
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