Energy Markets and Global Economic Conditions
Christiane Baumeister, Dimitris Korobilis, Thomas K. Lee
Review of Economics and Statistics,
im Erscheinen
Abstract
We evaluate alternative indicators of global economic activity and other market funda-mentals in terms of their usefulness for forecasting real oil prices and global petroleum consumption. World industrial production is one of the most useful indicators. However, by combining measures from several different sources we can do even better. Our analysis results in a new index of global economic conditions and measures for assessing future energy demand and oil price pressures. We illustrate their usefulness for quantifying the main factors behind the severe contraction of the global economy and the price risks faced by shale oil producers in early 2020.
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Financial Technologies and the Effectiveness of Monetary Policy Transmission
Iftekhar Hasan, Boreum Kwak, Xiang Li
IWH-Diskussionspapiere,
Nr. 26,
2020
Abstract
This study investigates whether and how financial technologies (FinTech) influence the effectiveness of monetary policy transmission. We examine regional-level FinTech adoption and use an interacted panel vector autoregression model to explore how the effects of monetary policy shocks change with FinTech adoption. The results indicate that FinTech adoption generally enhances monetary policy transmission to real GDP, bank loans, and housing prices, while the evidence of transmission to consumer prices is mixed. A subcategorical analysis shows that the enhanced effectiveness is the most pronounced in the adoption of FinTech payment, compared to that of insurance and credit.
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Exchange Rates and the Information Channel of Monetary Policy
Oliver Holtemöller, Alexander Kriwoluzky, Boreum Kwak
IWH-Diskussionspapiere,
Nr. 17,
2020
Abstract
We disentangle the effects of monetary policy announcements on real economic variables into an interest rate shock component and a central bank information shock component. We identify both components using changes in interest rate futures and in exchange rates around monetary policy announcements. While the volatility of interest rate surprises declines around the Great Recession, the volatility of exchange rate changes increases. Making use of this heteroskedasticity, we estimate that a contractionary interest rate shock appreciates the dollar, increases the excess bond premium, and leads to a decline in prices and output, while a positive information shock appreciates the dollar, decreases prices and the excess bond premium, and increases output.
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Energy Markets and Global Economic Conditions
Christiane Baumeister, Dimitris Korobilis, Thomas K. Lee
Abstract
This paper evaluates alternative indicators of global economic activity and other market fundamentals in terms of their usefulness for forecasting real oil prices and global petroleum consumption. We find that world industrial production is one of the most useful indicators that has been proposed in the literature. However, by combining measures from a number of different sources we can do even better. Our analysis results in a new index of global economic conditions and new measures for assessing future tightness of energy demand and expected oil price pressures.
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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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Nowcasting East German GDP Growth: a MIDAS Approach
João Carlos Claudio, Katja Heinisch, Oliver Holtemöller
Empirical Economics,
im Erscheinen
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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Wage Delegation in the Field
Sabrina Jeworrek, Vanessa Mertins
Journal of Economics & Management Strategy,
Nr. 4,
2019
Abstract
By conducting a natural field experiment, we analyze the managerial policy of delegating the wage choice to employees. We find that this policy enhances performance significantly, which is remarkable since allocated wage premiums of the same size have no effect at all. Observed self‐imposed wage restraints and absence of negative peer effects speak in favor of wage delegation, although the chosen wage premium levels severely dampen its net value. Additional experimental and survey data provide important insights into employees' underlying motivations.
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How Forecast Accuracy Depends on Conditioning Assumptions
Carola Engelke, Katja Heinisch, Christoph Schult
IWH-Diskussionspapiere,
Nr. 18,
2019
Abstract
This paper examines the extent to which errors in economic forecasts are driven by initial assumptions that prove to be incorrect ex post. Therefore, we construct a new data set comprising an unbalanced panel of annual forecasts from different institutions forecasting German GDP and the underlying assumptions. We explicitly control for different forecast horizons to proxy the information available at the release date. Over 75% of squared errors of the GDP forecast comove with the squared errors in their underlying assumptions. The root mean squared forecast error for GDP in our regression sample of 1.52% could be reduced to 1.13% by setting all assumption errors to zero. This implies that the accuracy of the assumptions is of great importance and that forecasters should reveal the framework of their assumptions in order to obtain useful policy recommendations based on economic forecasts.
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Mission, Motivation, and the Active Decision to Work for a Social Cause
Sabrina Jeworrek, Vanessa Mertins
IWH-Diskussionspapiere,
Nr. 10,
2019
Abstract
The mission of a job does not only affect the type of worker attracted to an organisation, but may also provide incentives to an existing workforce. We conducted a natural field experiment with 267 short-time workers and randomly allocated them to either a prosocial or a commercial job. Our data suggest that the mission of a job itself has a performance enhancing motivational impact on particular individuals only, i.e., workers with a prosocial attitude. However, the mission is very important if it has been actively selected. Those workers who have chosen to contribute to a social cause outperform the ones randomly assigned to the same job by about 15 percent. This effect seems to be a universal phenomenon which is not driven by information about the alternative job, the choice itself or a particular subgroup.
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For How Long Do IMF Forecasts of World Economic Growth Stay Up-to-date?
Katja Heinisch, Axel Lindner
Applied Economics Letters,
Nr. 3,
2019
Abstract
This study analyses the performance of the International Monetary Fund (IMF) World Economic Outlook output forecasts for the world and for both the advanced economies and the emerging and developing economies. With a focus on the forecast for the current year and the next year, we examine the durability of IMF forecasts, looking at how much time has to pass so that IMF forecasts can be improved by using leading indicators with monthly updates. Using a real-time data set for GDP and for 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 as soon as the publication of the IMF’s Outlook is only a few months old. In particular, there is an obvious gain using leading indicators from January to March for the forecast of the current year.
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