The Macroeconomic Risks of Undesirably Low Inflation
Jonas Arias, Christopher J. Erceg, Mathias Trabandt
European Economic Review,
2016
Abstract
This paper investigates the macroeconomic risks associated with undesirably low inflation using a medium-sized New Keynesian model. We consider different causes of persistently low inflation, including a downward shift in long-run inflation expectations, a fall in nominal wage growth, and a favorable supply-side shock. We show that the macroeconomic effects of persistently low inflation depend crucially on its underlying cause, as well as on the extent to which monetary policy is constrained by the zero lower bound. Finally, we discuss policy options to mitigate these effects.
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Effects of Incorrect Specification on the Finite Sample Properties of Full and Limited Information Estimators in DSGE Models
Sebastian Giesen, Rolf Scheufele
Journal of Macroeconomics,
June
2016
Abstract
In this paper we analyze the small sample properties of full information and limited information estimators in a potentially misspecified DSGE model. Therefore, we conduct a simulation study based on a standard New Keynesian model including price and wage rigidities. We then study the effects of omitted variable problems on the structural parameter estimates of the model. We find that FIML performs superior when the model is correctly specified. In cases where some of the model characteristics are omitted, the performance of FIML is highly unreliable, whereas GMM estimates remain approximately unbiased and significance tests are mostly reliable.
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Unemployment and Business Cycles
Lawrence J. Christiano, Martin S. Eichenbaum, Mathias Trabandt
Econometrica,
No. 4,
2016
Abstract
We develop and estimate a general equilibrium search and matching model that accounts for key business cycle properties of macroeconomic aggregates, including labor market variables. In sharp contrast to leading New Keynesian models, we do not impose wage inertia. Instead we derive wage inertia from our specification of how firms and workers negotiate wages. Our model outperforms a variant of the standard New Keynesian Calvo sticky wage model. According to our estimated model, there is a critical interaction between the degree of price stickiness, monetary policy, and the duration of an increase in unemployment benefits.
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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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Global Food Prices and Business Cycle Dynamics in an Emerging Market Economy
Oliver Holtemöller, Sushanta Mallick
Abstract
This paper investigates a perception in the political debates as to what extent poor countries are affected by price movements in the global commodity markets. To test this perception, we use the case of India to establish in a standard SVAR model that global food prices influence aggregate prices and food prices in India. To further analyze these empirical results, we specify a small open economy New-Keynesian model including oil and food prices and estimate it using observed data over the period from 1996Q2 to 2013Q2 by applying Bayesian estimation techniques. The results suggest that big part of the variation in inflation in India is due to cost-push shocks and, mainly during the years 2008 and 2010, also to global food price shocks, after having controlled for exogenous rainfall shocks. We conclude that the inflationary supply shocks (cost-push, oil price, domestic food price and global food price shocks) are important contributors to inflation in India. Since the monetary authority responds to these supply shocks with a higher interest rate which tends to slow growth, this raises concerns about how such output losses can be prevented by reducing exposure to commodity price shocks and thereby achieve higher growth.
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Monetary Policy and the Transaction Role of Money in the US
Alexander Kriwoluzky, Christian A. Stoltenberg
Economic Journal,
No. 587,
2015
Abstract
The declining importance of money in transactions can explain the well-known fact that US interest rate policy was passive in the pre-Volcker period and active after 1982. We generalise a standard cashless new Keynesian model (Woodford, 2003) by incorporating an explicit transaction role for money. In the pre-Volcker period, we estimate that money did play an important role and determinacy required a passive interest rate policy. However, after 1982, money no longer played an important role in facilitating transactions. Correspondingly, the conventional view prevails and an active policy ensured equilibrium determinacy.
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Understanding the Great Recession
Mathias Trabandt, Lawrence J. Christiano, Martin S. Eichenbaum
American Economic Journal: Macroeconomics,
No. 1,
2015
Abstract
We argue that the vast bulk of movements in aggregate real economic activity during the Great Recession were due to financial frictions. We reach this conclusion by looking through the lens of an estimated New Keynesian model in which firms face moderate degrees of price rigidities, no nominal rigidities in wages, and a binding zero lower bound constraint on the nominal interest rate. Our model does a good job of accounting for the joint behavior of labor and goods markets, as well as inflation, during the Great Recession. According to the model the observed fall in total factor productivity and the rise in the cost of working capital played critical roles in accounting for the small drop in inflation that occurred during the Great Recession.
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15th IWH-CIREQ Macroeconometric Workshop: “Identification and Causality“
Matthias Wieschemeyer
Wirtschaft im Wandel,
No. 6,
2014
Abstract
Am 1. und 2. Dezember 2014 fand am IWH in Zusammenarbeit mit dem Centre interuniversitaire de recherche en économie quantitative (CIREQ), Montréal, und der Martin-Luther Universität Halle-Wittenberg (MLU) der 15. IWH-CIREQ Macroeconometric Workshop statt. Wissenschaftlerinnen und Wissenschaftler aus dem In- und Ausland folgten auch in diesem Jahr der Einladung, ihre neuesten Forschungsarbeiten auf dem Gebiet der angewandten Makroökonometrie vorzustellen.
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14th IWH-CIREQ Macroeconometric Workshop: “Forecasting and Big Data“
Katja Drechsel
Wirtschaft im Wandel,
No. 1,
2014
Abstract
Am 2. und 3. Dezember 2013 fand am IWH in Zusammenarbeit mit dem Centre interuniversitaire de recherche en économie quantitative (CIREQ), Montréal, und der Martin-Luther-Universität Halle-Wittenberg der 14. IWH-CIREQ Macroeconometric Workshop statt. Im Rahmen des Workshops stellten Wissenschaftler und Wissenschaftlerinnen europäischer Universiäten und internationaler Organisationen, wie z. B. der Europäischen Zentralbank und der Europäischen Kommission sowie der spanischen, kanadischen und japanischen Zentralbanken, ihre neuesten Forschungsergebnisse im Bereich makroökonometrischer Modellierung und Prognose unter Berücksichtigung großer und komplexer Datenbanken vor. Auch wurden weitere makroökonomische Themen wie beispielsweise die Wirkung geldpolitischer Schocks oder Wechselkurs-Volatilitäten diskutiert.
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Effects of Incorrect Specification on the Finite Sample Properties of Full and Limited Information Estimators in DSGE Models
Sebastian Giesen, Rolf Scheufele
Abstract
In this paper we analyze the small sample properties of full information and limited information estimators in a potentially misspecified DSGE model. Therefore, we conduct a simulation study based on a standard New Keynesian model including price and wage rigidities. We then study the effects of omitted variable problems on the structural parameters estimates of the model. We find that FIML performs superior when the model is correctly specified. In cases where some of the model characteristics are omitted, the performance of FIML is highly unreliable, whereas GMM estimates remain approximately unbiased and significance tests are mostly reliable.
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