Dynamic Effects of Credit Shocks in a Data-Rich Environment

References

• Aastveit, K. A., Carriero, A., Clark, T., and Marcellino, M. (2017), “Have Standard VARs Remained Stable Since the Crisis?,” Journal of Applied Econometrics, 32, 931–951.
   Web of Science ®Google Scholar
• Abbate, A., Eickmeier, S., Lemke, W., and Marcellino, M. (2016), “The Changing International Transmission of Financial Shocks,” Journal of Money, Credit and Banking, 48, 573–601.
   Web of Science ®Google Scholar
• Amengual, D., and Watson, M. W. (2007), “Consistent Estimation of the Number of Dynamic Factors in a Large N and T Panel,” Journal of Business and Economic Statistics, 25, 91–96.
   Web of Science ®Google Scholar
• Bai, J., and Ng, S. (2002), “Determining the Number of Factors in Approximate Factor Models,” Econometrica, 70, 191–221.
   Web of Science ®Google Scholar
• ———(2006), “Confidence Intervals for Diffusion Index Forecasts and Inference for Factor-augmented Regressions,” Econometrica, 74, 1133–1150.
   Web of Science ®Google Scholar
• ——— (2007), “Determining the Number of Primitive Shocks in Factor Models,” Journal of Business and Economic Statistics, 25, 52–60.
   Web of Science ®Google Scholar
• ——— (2008), “Large Dimensional Factor Analysis,” Foundations and Trends in Econometrics, 3, 89–163.
   Google Scholar
• ——— (2013), “Principal Components Estimation and Identification of the Factors,” Journal of Econometrics, 176, 18–29.
   Web of Science ®Google Scholar
• Banbura, M., Giannone, D., and Reichlin, L. (2010), “Large Bayesian Vector Autoregressions,” Journal of Applied Econometrics, 25, 71–92.
   Web of Science ®Google Scholar
• Bates, B. J., Plagborg-Moller, M., Stock, J. H., and Watson, M. W. (2013), “Consistent Factor Estimation in Dynamic Factor Models with Structural Instability,” Journal of Econometrics, 177, 289–304.
   Web of Science ®Google Scholar
• Bernanke, B. S., Boivin, J., and Eliasz, P. (2005), “Measuring the Effects of Monetary Policy: A Factor-augmented Vector Autoregressive (FAVAR) Approach,” Quarterly Journal of Economics, 120, 387–422.
   Web of Science ®Google Scholar
• Boivin, J., Giannoni, M. P., and Stevanović, D. (2009), “Monetary Transmission in a Small Open Economy: More Data, Fewer Puzzles,” unpublished manuscript, UQAM.
   Google Scholar
• Bernanke, B. S., Gertler, M., and Gilchrist, S. (1999), “The Financial Accelerator in a Quantitative Business Cycle Framework,” in The Handbook of Macroeconomics, eds. J. B. Taylor, and M. Woodford, Amsterdam: Elsevier Science B.V., pp. 1341–1369.
   Google Scholar
• Carriero, A., Clark, T., and Marcellino, M. (2015), “Bayesian VARs: Specification Choices and Forecast Accuracy,” Journal of Applied Econometrics, 30, 46–73.
   Web of Science ®Google Scholar
• Cheng, X., Liao, Z., and Schorfheide, F. (2016), “Shrinkage Estimation of High-Dimensional Factor Models with Structural Instabilities,” Review of Economic Studies, 83, 1511–1543.
   Web of Science ®Google Scholar
• Christiano, L. J., Motto, R., and Rostagno, M. (2014), “Risk Shocks,” American Economic Review, 104, 27–65.
   Web of Science ®Google Scholar
• Del Negro, M., Giannoni, M. P., and Schorfheide, F. (2015), “Inflation in the Great Recession and New Keynesian Models,” American Economic Journal: Macroeconomics, 7, 168–196.
   Web of Science ®Google Scholar
• Del Negro, M., and Schorfheide, F. (2012), “DSGE Model-Based Forecasting,” in Handbook of Economic Forecasting (Vol. 2), eds. G. Elliott, and A. Timmermann, North-Holland: Elsevier, pp. 57–140.
   Google Scholar
• Doz, C., Giannone, D., and Reichlin, L. (2011), “A Two-step Estimator for Large Approximate Dynamic Factor Models Based on Kalman Filtering,” Journal of Econometrics, 164, 188–205.
   Web of Science ®Google Scholar
• Eickmeier, S., and Ng, T. (2015), “How do US Credit Supply Shocks Propagate Internationally? A GVAR Approach,” European Economic Review, 74, 128–145.
   Web of Science ®Google Scholar
• Fisher, J. D. M. (2006), “The Dynamic Effect of Neutral and Investment-Specific Technology Shocks,” Journal of Political Economy, 114, 413–451.
   Web of Science ®Google Scholar
• Forni, M., Giannone, D., Lippi, M., and Reichlin, L. (2009), “Opening The Black Box: Structural Factor Models With Large Cross Sections,” Econometric Theory, 25, 1319–1347.
   Web of Science ®Google Scholar
• Gambetti, L., and Musso, A. (2012), “Loan Supply Shocks and the Business Cycle,” ECB Working Paper No. 1469, ECB.
   Google Scholar
• Gertler, M., and Lown, C. S. (1999), “The Information in the High-Yield Bond Spread for the Business Cycle: Evidence and Some Implications,” Oxford Review of Economic Policy, 15, 132–150.
   Web of Science ®Google Scholar
• Giannone, D., Lenza, M., and Primiceri, G. (2015), “Prior Selection for Vector Autoregressions,” Review of Economics and Statistics, 97, 436–451.
   Web of Science ®Google Scholar
• Gilchrist, S., Ortiz, A., and Zakrajšek, E. (2009), “Credit Risk and the Macroeconomy: Evidence From an Estimated DSGE Model,” Mimeo, Boston University.
   Google Scholar
• Gilchrist, S., Yankov, V., and Zakrajšek, E. (2009), “Credit Market Shocks and Economic Fluctuations: Evidence From Corporate Bond and Stock Markets,” Journal of Monetary Economics, 56, 471–493.
   Web of Science ®Google Scholar
• Gilchrist, S., and Zakrajšek, E. (2012), “Credit Spreads and Business Cycle Fluctuations,” American Economic Review, 102, 471–493.
   Web of Science ®Google Scholar
• Greenwood, J., Hercowitz, Z., and Krusell, P. (1997), “Long Run Implications of Investment-Specific Technological Change,” American Economic Review, 87, 342–362.
   Web of Science ®Google Scholar
• Hallin, M., and Liska, R. (2007), “Determining the Number of Factors in the General Dynamic Factor Model,” Journal of the American Statistical Association, 102, 603–617.
   Web of Science ®Google Scholar
• Helbling, T., Huidrom, R., Kose, M. A., and Otrok, C. (2011), “Do Credit Shocks Matter? A Global Perspective,” European Economic Review, 55, 340–353.
   Web of Science ®Google Scholar
• Justiniano, A., Primiceri, G. E., and Tambalotti, A. (2010), “Investment Shocks and Business Cycles,” Journal of Monetary Economics, 57, 132–145.
   Web of Science ®Google Scholar
• ——— (2011), “Investment Shocks and the Relative Price of Investment,” Review of Economic Dynamics, 14, 102–121.
   Web of Science ®Google Scholar
• Koop, G. (2013), “Forecasting with Medium and Large Bayesian VARs,” Journal of Applied Econometrics, 28, 177–203.
   Web of Science ®Google Scholar
• Mueller, P. (2007), “Credit Spreads and Real Activity,” Columbia Business School, Mimeo, unpublished.
   Google Scholar
• Onatski, A. (2010), “Determining the Number of Factors from Empirical Distribution of Eigenvalues,” Review of Economics and Statistics, 92, 1004–1016.
   Web of Science ®Google Scholar
• Peersman, G. (2012), “Bank Lending Shocks and the Euro Area Business Cycle,” Mimeo, Ghent University.
   Google Scholar
• Prieto, E., Eickmeier, S., and Marcellino, M. (2016), “Time Variation in Macro-Financial Linkages,” Journal of Applied Econometrics, 31, 1215–1233.
   Web of Science ®Google Scholar
• Sims, C. A. (1992), “Interpreting the Macroeconomic Time Series Facts: The Effects of Monetary Policy,” European Economic Review, 36, 975–1000.
   Web of Science ®Google Scholar
• Stevanovic, D. (2015), “Factor-Augmented Autoregressive Distributed Lag Models with Macroeconomic Applications,” CIRANO Working Papers 2015s–33, CIRANO.
   Google Scholar
• Stock, J. H., and Watson, M. W. (1989), “New Indexes of Coincident and Leading Economic Indicators,” NBER Macroeconomics Annual, 351–393.
   Web of Science ®Google Scholar
• ——— (2002a), “Forecasting Using Principal Components from a Large Number of Predictors,” Journal of the American Statistical Association, 97, 1167–1179.
   Web of Science ®Google Scholar
• ——— (2002b), “Macroeconomic Forecasting Using Diffusion Indexes,” Journal of Business and Economic Statistics, 20, 147–162.
   Web of Science ®Google Scholar
• ——— (2003), “Forecasting Output and Inflation: The Role of Asset Prices,” Journal of Economic Literature, 41, 788–829.
   Web of Science ®Google Scholar
• ——— (2012), “Disentangling the Channels of the 2007-2009 Recession,” Brookings Papers on Economic Activity, Spring, 81–135.
   Google Scholar
• ——— (2016), “Dynamic Factor Models, Factor-Augmented Vector Autoregressions, and Structural Vector Autoregressions in Macroeconomics,” in Handbook of Macroeconomics, 2, 415–525.
   Google Scholar
• Swanson, E. T., and Williams, J. C. (2014), “Measuring the Effect of the Zero Lower Bound on Medium- and Longer-Term Interest Rates,” American Economic Review, 104, 3154–3185.
   Web of Science ®Google Scholar