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GIMME A BREAK! IDENTIFICATION AND ESTIMATION OF THE MACROECONOMIC EFFECTS OF MONETARY POLICY SHOCKS IN THE UNITED STATES

Published online by Cambridge University Press:  23 June 2017

Emanuele Bacchiocchi ,
Efrem Castelnuovo  and
Luca Fanelli
Emanuele Bacchiocchi
Affiliation:
University of Milan
Efrem Castelnuovo*
Affiliation:
University of Melbourne, University of Padova
Luca Fanelli
Affiliation:
University of Bologna
*
Address correspondence to: Efrem Castelnuovo, Melbourne Institute of Economic and Social Research and Department of Economics, Level 5, 111 Barry Street, Faculty of Business and Economics building, 3010 Melbourne, Australia; e-mail: efrem.castelnuovo@unimelb.edu.au.
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Abstract

We employ a non-recursive identification scheme to identify the effects of a monetary policy shock in a Structural Vector Autoregressive (SVAR) model for the US post-WWII quarterly data. The identification of the shock is achieved via heteroskedasticity, and different on-impact macroeconomic responses are allowed for (but not imposed) in each volatility regime. We show that the impulse responses obtained with the suggested non-recursive identification scheme are quite similar to those conditional on a recursive VAR estimated with pre-1984 data. In contrast, recursive vs. non-recursive identification schemes return different short-run responses of output and investment during the Great Moderation. Robustness checks dealing with a different definition of investment, an alternative break-point, and federal funds futures rates as an indicator of the monetary policy stance are documented and discussed.

Keywords

Structural BreakRecursive and Non-Recursive SVARsIdentificationMonetary Policy ShocksImpulse Responses
Type
Articles
Information
Macroeconomic Dynamics , Volume 22 , Issue 6 , September 2018 , pp. 1613 - 1651
Copyright
Copyright © Cambridge University Press 2017 

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Footnotes

We thank William A. Barnett (Editor), an anonymous Associate Editor, and two anonymous referees for insightful comments, and Giovanni Caggiano, Riccardo Lucchetti, Michel Normandin, Giovanni Pellegrino, and Jouko Vilmunen for valuable discussions. We also thank Christopher Crowe for kindly providing us with the new shock series proposed in the Barakchian and Crowe (2013, Journal of Monetary Economics) paper. Participants to presentations held to the Fourth International Conference in memory of Carlo Giannini 2014 (Pavia), the CFE conference 2014 (Pisa), the Society for Computational Economics 2014 (Oslo), the International Association for Applied Econometrics Conference 2015 (Thessaloniki), the Bank of Finland and the University of Padova provided us with useful feedback. Emanuele Bacchiocchi and Luca Fanelli gratefully acknowledge partial financial support from the Italian MIUR Grant PRIN-2010/2011, prot. 2010RHAHPL 003; Luca Fanelli also acknowledges RFO grants from the University of Bologna.

References

REFERENCES

Altig, D., Christiano, L. J., Eichenbaum, M., and Linde, J. (2011) Firm-specific capital, nominal rigidities and the business cycle. Review of Economic Dynamics 14 (2), 225–247.Google Scholar
Amisano, G. and Giannini, C. (1997) Topics in Structural VAR Econometrics, 2nd ed. Berlin: Springer.Google Scholar
Bacchiocchi, E. and Fanelli, L. (2012) Identification in Structural Vector Autoregressive Models with Structural Changes, with an Application to U.S. Monetary Policy. Mimeo, Department of Economics, Management and Quantitative Methods, Università degli Studi di Milano.Google Scholar
Bacchiocchi, E. and Fanelli, L. (2015) Identification in structural vector autoregressive models with structural changes with an application to U.S. monetary policy. Oxford Bulletin of Economics and Statistics 77, 761–779.Google Scholar
Bagliano, F. C. and Favero, C. A. (1998) Measuring monetary policy with VAR models: An evaluation. European Economic Review 42, 1069–1112.Google Scholar
Bagliano, F. C. and Favero, C. A. (1999) Information from financial markets and VAR measures of monetary policy. European Economic Review 43 (4–6), 825–837.Google Scholar
Barakchian, S. M. and Crowe, C. (2013) Monetary policy matters: Evidence from new shocks data. Journal of Monetary Economics 60 (8), 950–966.Google Scholar
Barsky, R., House, C., and Kimball, M. (2007) Sticky price models and durable goods. American Economic Review 97, 984–998.Google Scholar
Benati, L. and Surico, P. (2009) VAR analysis and the great moderation. American Economic Review 99 (4), 1636–1652.Google Scholar
Blanchard, O. and Riggi, M. (2013) Why are the 2000s so different from the 1970s? A structural interpretation of changes in the macroeconomic effects of oil prices. Journal of the European Economic Association 11 (5), 1032–1052.Google Scholar
Blanchard, O. and Simon, J. (2001) The long and large decline in U.S. output volatility. Brookings Papers on Economic Activity 1, 135–174.Google Scholar
Boivin, J. and Giannoni, M. (2006) Has monetary policy become more effective?. Review of Economics and Statistics 88 (3), 445–462.Google Scholar
Boivin, J., Kiley, M. T. and Mishkin, F. S. (2010) How has the monetary transmission mechanism evolved over time?. In Friedman, B. M. and Woodford, M. (eds.), Handbook of Monetary Economics, Chapter 8, pp. 369–422. Amsterdam: Elsevier.Google Scholar
Canova, F. (2009) What explains the great moderation in the US? A structural analysis. Journal of the European Economic Association 7 (4), 697–721.Google Scholar
Canova, F. and deAAAANicoló, G. (2002) Monetary disturbances matter for business fluctuations in the G-7. Journal of Monetary Economics 49, 1131–1159.Google Scholar
Canova, F. and Forero, F. J. P. (2015) Estimating overidentified, nonrecursive, time-varying coefficients structural vector autoregressions. Quantitative Economics 6 (2), 359–384.Google Scholar
Canova, F., Gambetti, L., and Pappa, E. (2008) The structural dynamics of US output and inflation: What explains the changes?. Journal of Money, Credit and Banking 40 (23), 369–388.Google Scholar
Canova, F. and Paustian, M. (2011) Business cycle measurement with some theory. Journal of Monetary Economics 58, 345–361.Google Scholar
Castelnuovo, E. (2012) Estimating the evolution of money's role in the U.S. monetary business cycle. Journal of Money, Credit and Banking 44 (1), 23–52.Google Scholar
Castelnuovo, E. (2016) Modest macroeconomic effects of monetary policy shocks during the Great Moderation: An alternative interpretation. Journal of Macroeconomics 47, 300–314.Google Scholar
Castelnuovo, E., Greco, L., and Raggi, D. (2014) Policy rules, regime switches, and trend inflation: An empirical investigation for the U.S. Macroeconomic Dynamics 18, 920–942.Google Scholar
Castelnuovo, E. and Surico, P. (2010) Monetary policy shifts, inflation expectations and the price puzzle. Economic Journal 120 (549), 1262–1283.Google Scholar
Christiano, L., Eichenbaum, M., and Evans, C. (2005) Nominal rigidities and the dynamic effects of a shock to monetary policy. Journal of Political Economy 113 (1), 1–45.Google Scholar
Christiano, L. J., Eichenbaum, M., and Evans, C. (1999) Monetary policy shocks: What have we learned and to what end?. In Taylor, J. B. and Woodford, M. (eds.), Handbook of Macroeconomics, vol. 1, pp. 65–148. Amsterdam: Elsevier Science.Google Scholar
Clarida, R., Galí, J., and Gertler, M. (2000) Monetary policy rules and macroeconomic stability: Evidence and some theory. Quarterly Journal of Economics 115, 147–180.Google Scholar
Cogley, T. and Sargent, T. (2005a) Drifts and volatilities: Monetary policies and outcomes in the post war U.S.. Review of Economic Dynamics 8, 262–302.Google Scholar
Cogley, T. and Sargent, T. (2005b) The conquest of U.S. inflation: Learning and robustness to model uncertainty. Review of Economic Dynamics 8, 528–563.Google Scholar
Coibion, O. (2012) Are the effects of monetary policy shocks big or small?. American Economic Journal: Macroeconomics 4 (2), 1–32.Google Scholar
Coibion, O. and Gorodnichenko, Y. (2011) Monetary policy, trend inflation and the great moderation: An alternative interpretation. American Economic Review 101, 341–370.Google Scholar
DelAAAANegro, M. and Schorfheide, F. (2004) Priors for general equilibrium models for VARs. International Economic Review 45, 643–673.Google Scholar
DelAAAANegro, M., Schorfheide, F., Smets, F., and Wouters, R. (2007) On the fit of new-Keynesian models. Journal of Business and Economic Statistics 25 (2), 124–162.Google Scholar
Eichenbaum, M. (1992) Comment on “Interpreting the macroeconomic time series facts: The effects of monetary policy” by C.A. Sims. European Economic Review 36 (5), 1001–1011.Google Scholar
Erceg, C. and Levin, A. (2006) Optimal monetary policy with durable consumption goods. Journal of Monetary Economics 53, 1341–1359.Google Scholar
Estrella, A. (2015) The price puzzle and VAR identification. Macroeconomic Dynamics 19, 1880–1887.Google Scholar
Faust, J. (1998) The robustness of identified VAR conclusions about money. Carnegie Rochester Conference Series on Public Policy 49, 207–244.Google Scholar
Faust, J., Swanson, E. T., and Wright, J. H. (2004) Identifying VARs based on high frequency futures data. Journal of Monetary Economics 51, 1107–1131.Google Scholar
Fry, R. and Pagan, A. (2011) Sign restrictions in structural vector autoregressions: A critical review. Journal of Economic Literature 49 (4), 938–960.Google Scholar
Galí, J. (2008) Monetary Policy, Inflation and the Business Cycle. Princeton, NJ: Princeton University Press.Google Scholar
Gertler, M. and Karadi, P. (2014) Monetary Policy Surprises, Credit Costs and Economic Activity. NBER working paper no. 20224.Google Scholar
Groshenny, N. (2013) Monetary policy, inflation and unemployment: In defense of the federal reserve. Macroeconomic Dynamics 17, 1311–1329.Google Scholar
Hanson, M. (2004) The “Price Puzzle” reconsidered. Journal of Monetary Economics 51, 1385–1413.Google Scholar
Herwartz, H. and Lütkepohl, H. (2014) Structural vector autoregressions with Markov switching: Combining conventional with Statistical identification of shocks. Journal of Econometrics 183, 104–116.Google Scholar
Justiniano, A. and Primiceri, G. (2008) The time-varying volatility of macroeconomic fluctuations. American Economic Review 98 (3), 604–641.Google Scholar
Justiniano, A., Primiceri, G., and Tambalotti, A. (2011) Investment shocks and the relative price of investment. Review of Economic Dynamics 14 (1), 101–121.Google Scholar
Justiniano, A., Primiceri, G. E., and Tambalotti, A. (2010) Investment shocks and business cycles. Journal of Monetary Economics 57 (2), 132–145.Google Scholar
Kilian, L. (1998) Small-sample confidence intervals for impulse response functions. Review of Economics and Statistics 80, 218–230.Google Scholar
Kim, C. and Nelson, C. (1999) Has the U.S. economy become more stable? A Bayesian approach based on a Markov-switching model of the business cycle. Review of Economics and Statistics 81, 608–616.Google Scholar
Kliem, M. and Kriwoluzky, A. (2013) Reconciling narrative monetary policy disturbances with structural VAR model shocks?. Economics Letters 121 (2), 247–251.Google Scholar
Kuttner, K. (2001) Monetary policy Surprises and interest rates: Evidence from the fed funds futures market. Journal of Monetary Economics 47 (3), 523–544.Google Scholar
Lanne, M. and Lütkepohl, H. (2008) Identifying monetary policy shocks via changes in volatility. Journal of Money, Credit and Banking 40, 1131–1149.Google Scholar
Lanne, M. and Lütkepohl, H. (2010) Structural vector autoregressions with non-normal residuals. Journal of Business and Economic Statistics 28, 159–168.Google Scholar
Lanne, M. L., Lütkepohl, H., and Maciejowska, K. (2010) Structural vector autoregressions with Markov switching. Journal of Economic Dynamics and Control 34, 21–131.Google Scholar
Lubik, T. and Schorfheide, F. (2004) Testing for indeterminacy: An application to U.S. monetary policy. American Economic Review 94 (1), 190–217.Google Scholar
Lütkepohl, H. (2013) Identifying structural vector autoregressions via changes in volatility. Advances in Econometrics, 32, 169–203.Google Scholar
Lütkepohl, H. and Netŝunajev, A. (2014a) Disentangling demand and supply Shocks in the crude oil market: How to check sign restrictions in structural VARs. Journal of Applied Econometrics 29, 479–496.Google Scholar
Lütkepohl, H. and Netŝunajev, A. (2014b) Structural Vector Autoregressions with Smooth Transition in Variances: The Interaction between U.S. Monetary Policy and the Stock Market. Research discussion paper no. 1388, DIW Berlin.Google Scholar
Lütkepohl, H. and Reimers, H. (1992) Impulse response analysis of cointegrated systems with an application to German money demand. Journal of Economic Dynamics and Control 16, 53–78.Google Scholar
Lütkepohl, H. and Velinov, A. (2016) Structural vector autoregressions: Checking identifying long-run restrictions via heteroskedasticity. Journal of Economic Surveys 30 (2), 377–392.Google Scholar
McConnell, M. and Perez-Quiros, G. (2000) Output fluctuations in the United States: What has changed since the early 1980s?. American Economic Review 90, 1464–1476.Google Scholar
Monacelli, T. (2009) New-Keynesian models, durable goods, and collateral constraints. Journal of Monetary Economics 56 (2), 242–254.Google Scholar
Normandin, M. and Phaneuf, L. (2004) Monetary policy shocks: Testing identification conditions under time-varying conditional volatility. Journal of Monetary Economics 51, 1217–1243.Google Scholar
Phillips, P. (1998) Impulse response and forecast error variance asymptotics in nonstationary VARs. Journal of Econometrics 83, 21–56.Google Scholar
Primiceri, G. (2005) Time-varying structural vector autoregressions and monetary policy. Review of Economic Studies 72, 821–852.Google Scholar
Rigobon, R. (2003) Identification through heteroskedasticity. Review of Economics and Statistics 85, 777–792.Google Scholar
Rigobon, R. and Sack, B. (2003) Measuring the reaction of monetary policy to the stock market. Quarterly Journal of Economics 118, 639–669.Google Scholar
Rigobon, R. and Sack, B. (2004) The impact of monetary policy on asset prices. Journal of Monetary Economics 51, 1553–1575.Google Scholar
Romer, C. and Romer, D. (2004) A new measure of monetary policy shocks: Derivation and implications. American Economic Review 94 (4), 1055–1084.Google Scholar
Rotemberg, J. and Woodford, M. (1997) An Optimization-Based Econometric Framework for the Evaluation of Monetary Policy. Discussion paper, NBER Macroeconomics Annual.Google Scholar
Rubio-Ramírez, J. F., Waggoner, D. F., and Zha, T. (2010) Structural vector autoregressions: Theory of identification and algorithms for inference. Review of Economic Studies 77, 665–696.Google Scholar
Rudebusch, G. D. (1998) Do measures of monetary policy in a VAR make Sense?. International Economic Review 39 (4), 907–931.Google Scholar
Sims, C. (1980) Macroeconomics and reality. Econometrica 48 (1), 1–48.Google Scholar
Sims, C. and Zha, T. (2006) Were there regime switches in U.S. monetary policy?. American Economic Review 96 (1), 54–81.Google Scholar
Smets, F. and Wouters, R. (2007) Shocks and frictions in US business cycle: A Bayesian DSGE approach. American Economic Review 97 (3), 586–606.Google Scholar
Stock, J. H. and Watson, M. W. (2002) Has the business cycle changed and why?. In Gertler, M. and Rogoff, K. (eds.), NBER Macroeconomic Annual. Cambridge, MA: MIT Press.Google Scholar
Stock, J. H. and Watson, M. W. (2012) Disentangling the channels of the 2007–2009 recession. Brookings Papers on Economic Activities Spring, 81–135.Google Scholar
Svensson, L. (1997) Inflation forecast targeting: Implementing and monitoring inflation targets. European Economic Review 41, 1111–1146.Google Scholar
Söderström, U. (2001) Predicting monetary policy with federal funds futures prices. Journal of Futures Markets 214, 377–391.Google Scholar
Uhlig, H. (2005) What are the effects of monetary policy? Results from an agnostic identification procedure. Journal of Monetary Economics 52, 381–419.Google Scholar
Vlaar, P. (2004) On the asymptotic distribution of impulse response functions with long-run restrictions. Econometric Theory 20, 891–903.Google Scholar