Hostname: page-component-586b7cd67f-tf8b9 Total loading time: 0 Render date: 2024-11-20T18:22:09.896Z Has data issue: false hasContentIssue false
  • English
  • Français

INVESTIGATING THE ROLE OF MONEY IN THE IDENTIFICATION OF MONETARY POLICY BEHAVIOR: A BAYESIAN DSGE PERSPECTIVE

Published online by Cambridge University Press:  24 January 2020

Bing Li ,
Qing Liu  and
Pei Pei
Bing Li*
Affiliation:
Tsinghua University
Qing Liu
Affiliation:
Tsinghua University
Pei Pei
Affiliation:
Central University of Finance and Economics
*
Address correspondence to: Bing Li, Academic Center for Chinese Economic Practice and Thinking, Tsinghua University, Room 128, ShunDe Building, Beijing 100084, China. e-mail: [email protected].
Get access Rights & Permissions [Opens in a new window]

Abstract

This paper estimates an enriched version of the mainstream medium-scale dynamic stochastic general equilibrium model, which features nonseparability between consumption and real money balances in utility and a systematic response of the policy rate to money growth. Estimation results show that money is a significant factor in the monetary policy rule. As a consequence, econometric analysis that omits money from Taylor rules may lead to biased estimates of the model parameters. In contrast to earlier studies that rely on small-scale models, the paper stresses the merits of using a sufficiently rich model. First, it delivers different results, such as the role of nonseparability between consumption and money in utility. Second, the rich dynamics embedded in the model allow us to explore the responses of a larger set of macroeconomic variables, making the model more informative on the effects of shocks and more useful for understanding the sources of business cycles. Third and most importantly, it reveals the possible pitfalls of relying on small-scale models when studying money’s role in business cycles.

Keywords

MoneyMonetary Policy BehaviorDSGE ModelBayesian Methods
Type
Articles
Information
Macroeconomic Dynamics , Volume 25 , Issue 6 , September 2021 , pp. 1495 - 1537
Copyright
© Cambridge University Press 2020

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

Footnotes

We would like to thank the editor, William Barnett, the associate editor, and the two anonymous referees for their helpful comments, which led to significant improvements in the paper. Meanwhile, we wish to thank Chong-En Bai, Alexander Kriwoluzky, Eric Leeper, Johannes Pfeifer, Chris Sims, Ben Zhe Wang, and Tao Zha for their many useful comments and suggestions. We also thank Qingquan Fan, Jinfeng Luo, and Haotian Jia for excellent research assistance. Bing Li acknowledges the support of the National Natural Science Foundation of China (No. 71103103) and Tsinghua University Initiative Scientific Research Program (No. 20151080392). Qing Liu would like to thank the support of the National Natural Science Foundation of China (No. 71773060) and Tsinghua University Initiative Scientific Research Program (No. 2016THZWJC11).

References

REFERENCES

Andrés, J., López-Salido, J. D. and Nelson, E. (2009) Money and the natural rate of interest: Structural estimates for the United States and the euro area. Journal of Economic Dynamics and Control 33, 758–776.CrossRefGoogle Scholar
Andrés, J., López-Salido, J. D. and Vallés, J. (2006) Money in an estimated business cycle model of the euro area. The Economic Journal 116, 457–477.CrossRefGoogle Scholar
Arestis, P., Chortareas, G. and Tsoukalas, J. D. (2010) Money and information in a new neoclassical synthesis framework. The Economic Journal 120, 101–128.CrossRefGoogle Scholar
Barnett, W. A. (2012) Getting it Wrong: How Faulty Monetary Statistics Undermine the Fed, the Financial System, and the Economy. Cambridge, MA: MIT Press.Google Scholar
Barnett, W. A., Liu, J., Mattson, R. S. and van den Noort, J. (2013) The new CFS Divisia monetary aggregates: Design, construction, and data sources. Open Economies Review 24, 101–124.CrossRefGoogle Scholar
Belongia, M. T. and Ireland, P. N. (2015) Interest rates and money in the measurement of monetary policy. Journal of Business & Economic Statistics 33(2), 255–269.CrossRefGoogle Scholar
Bernanke, B. S. (2006) Monetary aggregates and monetary policy at the Federal Reserve: A historical perspective. Speech delivered at the Fourth ECB Central Banking Conference on The Role of Money: Money and Monetary Policy in the Twenty-First Century, ECB, Frankfurt.Google Scholar
Bhattarai, S., Lee, J. W. and Park, W. Y. (2016) Policy regimes, policy shifts, and U.S. business cycles. The Review of Economics and Statistics 98(5), 968–983.CrossRefGoogle Scholar
Canova, F. and Menz, T. (2011) Does money matter in shaping domestic business cycles? An international investigation. Journal of Money, Credit and Banking 43(4), 577–607.CrossRefGoogle 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.CrossRefGoogle Scholar
Chib, S. and Jeliazkov, I. (2001) Marginal likelihood from the Metropolis-Hastings output. Journal of the American Statistical Association 96(453), 270–281.CrossRefGoogle Scholar
Chib, S. and Ramamurthy, S. (2010) Tailored randomized block MCMC methods with applications to DSGE models. Journal of Econometrics 155, 19–38.CrossRefGoogle Scholar
Chib, S. and Tan, F. (2017) Marginal Likelihood in High-Dimensional DSGE Models. Manuscript, Saint Louis University.Google Scholar
Clarida, R., Galí, J. and Gertler, M. (2000) Monetary policy rules and macroeconomic stability: Evidence and some theory. The Quarterly Journal of Economics 115(1), 147–180.CrossRefGoogle Scholar
Coibion, O. and Gorodnichenko, Y. (2011) Monetary policy, trend inflation, and the Great Moderation: An alternative interpretation. American Economic Review 101(1), 341–370.CrossRefGoogle 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(1), 168–196.Google Scholar
Fernández-Villaverde, J. (2010) The econometrics of DSGE models. SERIES 1, 3–49.CrossRefGoogle Scholar
Fratto, C. and Uhlig, H. (2014) Accounting for Post-crisis Inflation and Employment: A Retro Analysis. NBER Working Paper No. 20707.CrossRefGoogle Scholar
Gordon, D. B. and Leeper, E. M. (1994) The dynamic impacts of monetary policy: an exercise in tentative identification. Journal of Political Economy 102(6), 1228–1247.CrossRefGoogle Scholar
Geweke, J. (1999) Using simulation methods for Bayesian econometric models: Inference, development and communication. Econometric Reviews 18(1), 1–73.CrossRefGoogle Scholar
Guerron-Quintana, P. A. (2010) What you match does matter: The effects of data on DSGE estimation. Journal of Applied Econometrics 25, 774–804.CrossRefGoogle Scholar
Ireland, P. N. (2004) Money’s role in the monetary business cycle. Journal of Money, Credit and Banking 36(6), 969–983.CrossRefGoogle Scholar
Ireland, P. N. (2007) Changes in the Federal Reserve’s inflation target: Causes and consequences. Journal of Money, Credit and Banking 39(8), 1851–1882.CrossRefGoogle Scholar
Justiniano, A., Primiceri, G. E. and Tambalotti, A. (2010) Investment shocks and business cycles. Journal of Monetary Economics 57, 132–145.CrossRefGoogle Scholar
Justiniano, A., Primiceri, G. E. and Tambalotti, A. (2011) Investment shocks and the relative price of investment. Review of Economic Dynamics 14, 102–121.CrossRefGoogle Scholar
Kass, R. E. and Rafterty, A. E. (1995) Bayes factors. Journal of the American Statistical Association 90(430), 773–795.CrossRefGoogle Scholar
Kriwoluzky, A. and Stoltenberg, C. A. (2015) Monetary policy and the transaction role of money in the US. The Economic Journal 125(587), 1452–1473.CrossRefGoogle Scholar
Leeper, E. M. and Roush, J. E. (2003) Putting ‘M’ back in monetary policy. Journal of Money, Credit and Banking 35(6), 1217–1256.CrossRefGoogle Scholar
Leeper, E. M., Traum, N. and Walker, T. B. (2017) Clearing up the fiscal multiplier morass. American Economic Review 107(8), 2409–2454.CrossRefGoogle Scholar
Leeper, E. M. and Zha, T. (2001) Assessing simple policy rules: A view from a complete macroeconomic model. Federal Reserve Bank of Atlanta Economic Review (Q4) 86(4), 13–36.Google Scholar
Leeper, E. M. and Zha, T. (2003) Modest policy interventions. Journal of Monetary Economics 50, 1673–1700.CrossRefGoogle Scholar
Liu, Z., Waggoner, D. F. and Zha, T. (2011) Sources of macroeconomic fluctuations: A regime-switching DSGE approach. Quantitative Economics 2, 251–301.CrossRefGoogle Scholar
Lubik, T. A. and Schorfheide, F. (2004) Testing for indeterminacy: An application to U.S. monetary policy. American Economic Review 94(1), 190–217.CrossRefGoogle Scholar
Mouabbi, S. and Sahuc, J.-G. (2019) Evaluating the macroeconomic effects of the ECB’s unconventional monetary policies. Journal of Money, Credit and Banking 51(4), 831–858.CrossRefGoogle Scholar
Poilly, C. (2010) Does money matter for the identification of monetary policy shocks: A DSGE perspective. Journal of Economic Dynamics and Control 34, 2159–2178.CrossRefGoogle Scholar
Poole, W. (1970) Optimal choice of monetary policy instruments in a simple stochastic macro model. Quarterly Journal of Economics 84(2), 197–216.CrossRefGoogle Scholar
Schorfheide, F. (2005) Learning and monetary policy shifts. Review of Economic Dynamics 8, 392–419.CrossRefGoogle Scholar
Sims, C. A. (2003) Probability Models for Monetary Policy Decisions. Technical Report, Princeton University.Google Scholar
Sims, C. A. and Zha, T. (2006a) Were there regime switches in U.S. monetary policy? American Economic Review 96(1), 54–81.CrossRefGoogle Scholar
Sims, C. A. and Zha, T. (2006b) Does monetary policy generate recessions? Macroeconomic Dynamics 10, 231–272.CrossRefGoogle Scholar
Smets, F. (2003) Discussion of “Putting ‘M’ back in monetary policy” by Eric Leeper and Jennifer Roush. Journal of Money, Credit, and Banking 35(6) Part 2, 1257–1264.Google Scholar
Smets, F. and Wouters, R. (2003) An estimated dynamic stochastic general equilibrium model of the euro area. Journal of the European Economic Association 1(5), 1123–1175.CrossRefGoogle Scholar
Smets, F. and Wouters, R. (2007) Shocks and frictions in US business cycles: A Bayesian DSGE approach. American Economic Review 97(3), 586–606.CrossRefGoogle Scholar
Smith, A. L. (2016) When does the cost channel pose a challenge to inflation targeting central banks? European Economic Review 89, 471–494.CrossRefGoogle Scholar
Taylor, J. B. (1993) Discretion versus policy rules in practice. Carnegie-Rochester Conference Series on Public Policy 39, 195–214.CrossRefGoogle Scholar
Taylor, J. B. (1999) A historical analysis of monetary policy rules. In: Taylor, J. B. (ed.), Monetary Policy Rules, pp. 319–348. Chicago: University of Chicago Press.CrossRefGoogle Scholar
Traum, N. and Yang, S.-C. S. (2015) When does government debt crowd out investment? Journal of Applied Econometrics 30(1), 24–45.CrossRefGoogle Scholar
Woodford, M. (2003) Interest and Prices: Foundation of a Theory of Monetary Policy. Princeton, NJ: Princeton University Press.Google Scholar
Wu, J. C. and Xia, F. D. (2016) Measuring the macroeconomic impact of monetary policy at the zero lower bound. Journal of Money, Credit and Banking 48(2–3), 253–291.CrossRefGoogle Scholar
Wu, J. C. and Zhang, J. (2017) A Shadow Rate New Keynesian Model. Chicago Booth Research Paper No. 16-18.Google Scholar
Supplementary material: PDF

Li et al. supplementary material

Online Appendix

Download Li et al. supplementary material(PDF)
PDF 294.6 KB