In this study, FAVAR method is tried to be explained by comparing with VAR, and a literature search is being conducted in this subject.
📌 3 Key Takeaways
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Objective & Hypothesis:In the Vector Autoregressive (VAR) models, which are widely used in economic studies and developed by Sims (1980), impulse response functions can only be obtained from variables included only because of the infrequent use of information sets, and the dimensions of structural shocks can not be measured precisely.
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Key Findings & Data:FAVAR (Factor Augmented Vector Autoregression) method was developed by Bernanke, Boivin and Eliasz (2005) and this method can use large data sets.
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Conclusion & Impact:In this study, FAVAR method is tried to be explained by comparing with VAR, and a literature search is being conducted in this subject.
In the Vector Autoregressive (VAR) models, which are widely used in economic studies and developed by Sims (1980), impulse response functions can only be obtained from variables included only because of the infrequent use of information sets, and the dimensions of structural shocks can not be measured precisely. It is also not possible that for some variables to be represented by a single time series. The VAR estimation is insufficient for parsing operations involving large data sets. FAVAR (Factor Augmented Vector Autoregression) method was developed by Bernanke, Boivin and Eliasz (2005) and this method can use large data sets. In this study, FAVAR method is tried to be explained by comparing with VAR, and a literature search is being conducted in this subject.
AHMADI, A.P., RITSCHL, A.: 2009 “Depression Econometrics: A FAVAR Model of Monetary Policy During the Great Depression”, London School Of Economics, Economic History Working Papers, No. 130/09 BAI, J., KUNPENG, LI., LU, L.: 2014 “Estimation and Inference of FAVAR Models”, MPRA Paper No. 60960, Online: http://mpra.ub.uni-muenchen.de/60960/
BAGZIBAGLI, K.: 2012 “Monetary Transmission Mechanism and Time Variation in the Euro Area”, Department of Economics Discussion Paper, 12-12.
University of Birmingham BELKE, A., REES, A.: 2014 “Globalization and Monetary Policy – A FAVAR analysis for the G7 and the eurozone”, The North American Journal of Economics and Finance, 29, 306-321.
BANERJEE, A., MARCELLİNO, M., MASTEN, I.:(2015) “An Overview of the Factor-augmented Error-Correction Model”, University of Birmingham Department of Economics Discussion Paper, 15-03
BERNANKE, B., BOIVIN, J.: 2003“Monetary Policy in a Data-Rich Environment”, Journal of Monetary Economics, 50:3, 525-546.
BERNANKE, B., BOIVIN, J., ELIASZ, P.: 2005 “Measuring the Effects of Monetary Policy: A Factor-Augmented Vector Autoregressive (FAVAR) Approach.”, Quarterly Journal of Economics, 120(1), 387-422.
BLAES, B.: 2009 “Money and monetary policy transmission in the euro area evidence from FAVAR and VAR approaches”, Discussion Paper, Dt. Bundesbank Frankfurt. BLAES, B.: 2009 “Money and monetary policy transmission in the euro area evidence from FAVAR and VAR approaches”, Discussion Paper, Dt. Bundesbank Frankfurt. BOIVIN, J., GIANNONI, M., MIHOV, I.: 2007 “Sticky prices and monetary policy: Evidence from disaggregated U.S. data”, NBER Working Paper, 12824