The macroeconomic role of the collateral constraint in resource-rich countries

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Abstract

In this paper, we consider DSGE model of a small open economy highly dependent on resource export. The aim of the study is to identify the role of the collateral constraint in the terms-of-trade (TOT) shock transmission. The model contains two non-linear constraints in the form of inequalities: the collateral constraint and the zero lower bound constraint. We have found that if the monetary policy is not inertial, then under a series of unidirectional TOT shocks, the response of the economy is highly skewed with respect to positive and negative shocks. Both inequalities bind and reduce the positive impact of the TOT shock. If the monetary policy is inertial or the central bank reacts poorly to inflation change, then only the collateral constraint binds, and the effect of asymmetry almost disappears

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About the authors

Mikhail Y. Andreyev

Bank of Russia; RANEPA

Email: emm@cemi.rssi.ru

Senior economist; senior researcher

Russian Federation, Moscow

Andrey V. Polbin

Russian Presidential Academy of National Economy and Public Administration (RANEPA), Moscow; Gaidar Institute

Author for correspondence.
Email: emm@cemi.rssi.ru

Head of the Laboratory on economic processes mathematical modeling

Russian Federation

References

  1. Андреев М.Ю., Полбин А.В. (2019). Исследование эффекта финансового акселератора в DSGE модели с описанием производства экспортного продукта // Журнал новой экономической ассоциации. № 4 (44). C 12-49.
  2. Карев М.Г. (2011). Задача выявления предпочтений Банка России. Имитационный подход // Журнал новой экономической ассоциации. № 9. С. 72-97.
  3. Полбин А.В. (2014). Эконометрическая оценка структурной макроэкономической модели российской экономики // Прикладная эконометрика. № 1 (33). С. 3-29.
  4. Aastveit K.A., Anundsen A.K. (2017). Asymmetric effects of monetary policy in regional housing markets. Working Paper 2017/25, Norges Bank.
  5. Andres J., Arce O., Thomas C. (2013). Banking Competition, Collateral Constraints, and Optimal Monetary Policy // Journal of Money, Credit and Banking. Vol. 45(s2). P. 87-125.
  6. Andreyev M., Polbin A. (2021). Optimal simple monetary policy rules for a resource-rich economy and the Zero Lower Bound. Bank of Russia Working Paper Series wps81, Bank of Russia.
  7. Aruoba B., Cuba-Borda P., Schorfheide F. (2018). Macroeconomic Dynamics Near the ZLB: A Tale of Two Countries // Review of Economic Studies. Vol. 85. No. 1. P. 87-118.
  8. Bernanke B.S., Gertler M., Gilchrist S. (1999). The financial accelerator in a quantitative business cycle framework // Handbook of macroeconomics, vol. 1. The Netherlands: North-Holland. P. 1341-1393.
  9. Brzoza-Brzezina M., Kolasa M., Makarski K. (2013). The anatomy of standard DSGE models with financial frictions // Journal of Economic Dynamics and Control. Vol. 37. No. 1. P. 32-51.
  10. Cover J. (1992). Asymmetric effects of positive and negative money supply shocks // Quarterly Journal of Economics. Vol. 107. No. 4. P. 1261–1282.
  11. Davis S., Presno I. (2017). Capital controls and monetary policy autonomy in a small open economy // Journal of Monetary Economics. Vol. 85(C). P. 114-130.
  12. Elliott G., Komunjer I., Timmermann A. (2008). Biases in Macroeconomic Forecasts: Irrationality or Asymmetric Loss? // Journal of the European Economic Association. Vol. 6. No. 1. P. 122-157.
  13. Gertler M., Kiyotaki N., Queralto A. (2012). Financial crises, bank risk exposure and government financial policy // Journal of Monetary Economics. Vol. 59(S). P. 17-34.
  14. Gertler M., Kiyotaki N., Prestipino A. (2020). Credit Booms, Financial Crises, and Macroprudential Policy // Review of Economic Dynamics. Vol. 37. P. 8-33.
  15. Guerrieri L., Iacoviello M. (2015). OccBin: A toolkit for solving dynamic models with occasionally binding constraints easily // Journal of Monetary Economics. Vol. №70(C). P. 22-38.
  16. Guerrieri L., Iacoviello M. (2017). Collateral constraints and macroeconomic asymmetries // Journal of Monetary Economics. Vol. 90(C). P. 28-49.
  17. Hirose Y., Inoue A. (2016). The Zero Lower Bound and Parameter Bias in an Estimated DSGE Model // Journal of Applied Econometrics. Vol. 31. No. 4. P. 630-651.
  18. Iiboshi H., Shintani M., Ueda K. (2020). Estimating a Nonlinear New Keynesian Model with the Zero Lower Bound for Japan. Working Papers e154, Tokyo Center for Economic Research.
  19. Holden T. (2016). Computation of solutions to dynamic models with occasionally binding constraints. EconStor Preprints 130143, ZBW - Leibniz Information Centre for Economics.
  20. Karras G. (1996). Are the output effects of monetary policy asymmetric? Evidence from a sample of European countries // Oxford Bulletin of Economics and Statistics. Vol. 58. P. 267–278.
  21. Kiyotaki N., Moore J. (1997). Credit cycles // Journal of political economy. Vol. 105. No. 2. P. 211-248.
  22. Kocherlakota N. (2000). Creating business cycles through credit constraints // Federal Reserve Bank of Minneapolis. Quarterly Review. No. 24. P. 2-10.
  23. Lepetyuk V., Maliar L., Maliar S. (2020). When the U.S. catches a cold, Canada sneezes: A lower-bound tale told by deep learning // Journal of Economic Dynamics and Control. Vol. 117(C).
  24. Liu Z., Wang P., Zha T. (2013). Land‐Price Dynamics and Macroeconomic Fluctuations // Econometrica. Vol. 81. No. 3. P. 1147-1184.
  25. Liu Z., Miao J., Zha T. (2016). Land prices and unemployment // Journal of Monetary Economics. Vol. 80(C). P. 86-105.

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