Central Bank Equity as an Instrument of Monetary Policy

Abstract

We examine the use of central bank equity as an unconventional monetary policy tool. In this setting, a central bank employs digital currency to transfer digital cash to each household, thus supporting consumption directly when needed. The asset side of the central bank’s balance sheet remains unchanged, and the creation of new digital cash is offset by a decrease in central bank equity. The central bank thus incurs an immediate loss but does not take on any additional risks for its future income statements. We address several objections to this policy, paying particular attention to the claim that weakening the financial strength of the central bank endangers long-term price stability. Through a meta-analysis of 176 estimates reported previously in the literature, we find that central bank financial strength has not historically correlated with inflation performance.

This is a preview of subscription content, log in to check access.

Fig. 1
Fig. 2

Notes

  1. 1.

    Accounting practices vary across central banks. For example, the US Federal Reserve classifies losses as a “deferred asset” so that capital does not fall (not technically, anyway). Conceptually we see no difference.

  2. 2.

    Since a negative deviation from the interest rate rule is associated with higher inflation, we multiply these estimates by negative one to ensure basic comparability.

  3. 3.

    The partial correlation coefficient is akin to the well-known Pearson correlation coefficient but takes into account the effect of the other variables included in the regression.

  4. 4.

    Publication bias has been identified in empirical economics, for example, by Havranek and Irsova (2011, 2012) and Havranek et al. (2012, 2018a, b, c). No evidence of bias has been found by Havranek and Irsova (2017) and Havranek et al. (2015, 2017).

  5. 5.

    One can argue that Del Negro and Sims (2015) offer a step in this direction. When economic agents find that the financial strength of a central bank is deteriorating, they expect higher inflation. Given these expectations, the central bank must be more hawkish to deliver on its inflation target.

  6. 6.

    Positive results are perfectly plausible when we switch the direction of causality: ceteris paribus, higher inflation can be expected to improve central bank financial strength [at least up to a certain point; see, for example Buiter (2007)]. Nevertheless, the discussion in the literature focuses on the opposite causality direction.

  7. 7.

    All kinds of monetary policy have fiscal effects, so we find it more useful to distinguish between policy tools based on the agency that wields them. In that sense, direct support of consumption is a tool of monetary policy.

  8. 8.

    A lot has been written on related topics. Bacchetta (2018) discusses the rationale behind Swiss Sovereign Money Initiative. Belke and Polleit (2010) examine the importance of fiscal backing for central banks. Berentsen and Schar (2018), BIS (2018), Bordo and Levin (2017), Eichengreen (2019), Fatás and Mauro (2018), Meaning et al. (2018), Berger (2016), and Tolle (2016), among others, analyze the pros and cons of central bank digital currency.

  9. 9.

    Note also that some central banks in small countries (for example, Chile, Israel, and the Czech Republic) have little to no tradition of transferring profits to the government (Bartels et al. 2017). This is because their currency has tended to appreciate, leading to a loss from their portfolio of FX reserves, and so any yearly profits are typically retained to cover past or future losses. The lack of any expectations of transfers to the government increases the independence of central banks and makes the idea of direct support of consumption easier to implement.

  10. 10.

    In principle, the central bank digital currency that we envision would really function as a benefits or food pass card, so no exotic technology is needed—although the central bank would have to communicate with the public and retailers in advance to ensure that the digital currency is well understood and accepted. As with benefits cards, spending the funds stored in such a special digital wallet would transform the funds immediately into bank money. Given the impossibility of transferring funds (other than helicopter drops) to digital wallets, and thus no scope for money laundering, transactions with digital wallets could be kept as close to anonymous as possible by the central bank.

References

  1. Adler, G., P. Castro, and C. Tovar. 2016. Does Central Bank Capital Matter for Monetary Policy? Open Economies Review 27(1): 183–205.

    Google Scholar 

  2. Agarwal, R., and Kimball, M. 2015. Breaking Through the Zero Lower Bound. IMF Working Papers 15/224, International Monetary Fund.

    Google Scholar 

  3. Andrews, I., and Kasy, M. 2019. Identification of and Correction for Publication Bias. American Economic Review (forthcoming).

  4. Bacchetta, P. 2018. The Sovereign Money Initiative in Switzerland: An Economic Assessment. Swiss Journal of Economics and Statistics 154: 3.

    Google Scholar 

  5. Ball, L. 2014. The Case for a Long-Run Inflation Target of Four Percent. IMF Working Papers 14/92, International Monetary Fund.

  6. Bartels, B., Weder di Mauro, B., and Eichengreen, B. 2017. No Smoking Gun: Private Shareholders, Governance Rules and Central Bank Financial Behavior. In Annual Conference 2017: Alternative Structures for Money and Banking, Economic Association.

  7. Belke, A. 2018. Helicopter Money: Should Central Banks Rain Money from the Sky? Intereconomics: Review of International Trade and Development 53(1): 34–40.

    Google Scholar 

  8. Belke, A., and T. Polleit. 2010. How Much Fiscal Backing Must the ECB Have? The Euro Area is Not the Philippines. Économie Internationale 124: 5–30.

    Google Scholar 

  9. Benecka, S., Holub, T., Kadlcakova, N., and Kubicova, I. 2012. Does Central Bank Financial Strength Matter for Inflation? An Empirical Analysis. CNB Working Papers 2012/03, Czech National Bank, Research Department.

  10. Berentsen, A., and Schar, F. 2018. The Case for Central Bank Electronic Money and the Non-case for Central Bank Cryptocurrencies. In Federal Reserve Bank of St. Louis Review, Second Quarter 2018, 100(2), pp. 97–106.

    Google Scholar 

  11. Berger, R. 2016. Think Act—The Rise of Cryptofinance in Central Banking. Munich: Roland Berger.

    Google Scholar 

  12. Bernanke, B. 2016. What Tools Does the Fed Have Left? Part 3: Helicopter Money. Brookings Institution 11: 1–14.

    Google Scholar 

  13. BIS. 2018. Cryptocurrencies: Looking Beyond the Hype. Annual Report, Bank for International Settlements, Basel.

  14. Blinder, A. 2010. How Central Should the Central Bank Be? Journal of Economic Literature 48(1): 123–133.

    Google Scholar 

  15. Bordo, M., and Levin, A. 2017. Central Bank Digital Currency and the Future of Monetary Policy. NBER Working Paper 23711.

  16. Braun, B. 2016. Speaking to the People? Money, Trust, and Central Bank Legitimacy in the Age of Quantitative Easing. Review of International Political Economy 23(6): 1064–1092.

    Google Scholar 

  17. Buiter, W. 2007. Seigniorage. Economics, 10, October.

  18. Buiter, W. 2014. The Simple Analytics of Helicopter Money: Why It Works—Always. Economics, vol. 8, August.

  19. Caselli, F. 2017. Did the Exchange Rate Floor Prevent Deflation in the Czech Republic?. IMF Working Paper 17/206.

    Google Scholar 

  20. Cohen, J. 1988. Statistical Power Analysis in the Behavioral Sciences. Hillsdale: Erlbaum.

    Google Scholar 

  21. Del Negro, M., and C. Sims. 2015. When Does a Central Bank’s Balance Sheet Require Fiscal Support? Journal of Monetary Economics 73: 1–19.

    Google Scholar 

  22. DeLong, J. B. 2016. Why Do We Talk About Helicopter Money? In Grasping Reality with Both Hands, August 25, 2016.

  23. Diercks, A. 2017. The Reader’s Guide to Optimal Monetary Policy. In Bank of Governors of the Federal Reserve System, Mimeo.

  24. Doucouliagos, C. 2011. How Large is Large? Preliminary and relative guidelines for interpreting partial correlations in economics. Economics Series 5, Deakin University.

  25. Doucouliagos, C., and T. Stanley. 2013. Are All Economic Facts Greatly Exaggerated? Theory Competition and Selectivity. Journal of Economic Surveys 27(2): 316–339.

    Google Scholar 

  26. Egger, M., G. Davey Smith, M. Schneider, and C. Minder. 1997. Bias in Meta-analysis Detected by a Simple, Graphical Test. British Medical Journal 315(7109): 629–634.

    Google Scholar 

  27. Eichengreen, B. 2019. From Commodity to Fiat and Now to Crypto: What Does History Tell Us? NBER Working Paper 25426.

  28. English, W., Erceg, C., and Lopez-Salido, J. D. 2017. Money-Financed Fiscal Programs: A Cautionary Tale. In Finance and Economics Discussion Series 2017-060, Board of Governors of the Federal Reserve System.

  29. Fatás, A., and Weder Di Mauro, B. 2018. Cryptocurrencies’ Challenge to Central Banks. VoxEU, 14 May.

  30. Friedman, M. 1969. The Optimum Quantity of Money and Other Essays. Chicago: Aldine Publishing Company.

    Google Scholar 

  31. Furukawa, C. 2019. Publication Bias Under Aggregation Frictions: Theory, Evidence, and a New Correction Method. MIT, Working Paper.

  32. Gabaix, X. 2017. A Behavioral New Keynesian Model. NBER Working Papers 22954, National Bureau of Economic Research, Inc. Updated February, 2017.

  33. Galí, J. 2017. The Effects of a Money-Financed Fiscal Stimulus. Economics Working Papers 1441, Department of Economics and Business, Universitat Pompeu Fabra.

  34. Haldane, A. 2017. A Little More Conversation: A Little Less Action. In Speech at the Federal Reserve Bank of San Francisco, March 31, 2017.

  35. Hall, R., and Reis, R. 2015. Maintaining Central-Bank Financial Stability Under New-Style Central Banking. NBER Working Papers 21173.

  36. Hampl, M. 2018. A Digital Currency Useful for Central Banks?. In Speech at the 7th BBVA Seminar for Public Sector Investors and Issuers, Bilbao, February 27, 2018.

  37. Hausman, J. 2001. Mismeasured Variables in Econometric Analysis: Problems from the Right and Problems from the Left. Journal of Economic Perspectives 15(4): 57–67.

    Google Scholar 

  38. Havranek, T. 2015. Measuring Intertemporal Substitution: The Importance of Method Choices and Selective Reporting. Journal of the European Economic Association 13(6): 1180–1204.

    Google Scholar 

  39. Havranek, T., R. Horvath, Z. Irsova, and M. Rusnak. 2015. Cross-Country Heterogeneity in Intertemporal Substitution. Journal of International Economics 96(1): 100–118.

    Google Scholar 

  40. Havranek, T., D. Herman, and Z. Irsova. 2018a. Does Daylight Saving Save Electricity? A Meta-analysis. Energy Journal 39(2): 35–61.

    Google Scholar 

  41. Havranek, T., and Z. Irsova. 2011. Estimating Vertical Spillovers from FDI: Why Results Vary and What the True Effect Is. Journal of International Economics 85(2): 234–244.

    Google Scholar 

  42. Havranek, T., and Z. Irsova. 2012. Survey Article: Publication Bias in the Literature on Foreign Direct Investment Spillovers. Journal of Development Studies 48(10): 1375–1396.

    Google Scholar 

  43. Havranek, T., and Z. Irsova. 2017. Do Borders Really Slash Trade? A Meta-analysis. IMF Economic Review 65(2): 365–396.

    Google Scholar 

  44. Havranek, T., Z. Irsova, and K. Janda. 2012. Demand for Gasoline is More Price-Inelastic than Commonly Thought. Energy Economics 34(1): 201–207.

    Google Scholar 

  45. Havranek, T., Z. Irsova, and T. Vlach. 2018b. Measuring the Income Elasticity of Water Demand: The Importance of Publication and Endogeneity Biases. Land Economics 94(2): 259–283.

    Google Scholar 

  46. Havranek, T., Z. Irsova, and O. Zeynalova. 2018c. Tuition Fees and University Enrollment: A Meta-Regression Analysis. Oxford Bulletin of Economics and Statistics 80(6): 1145–1184.

    Google Scholar 

  47. Havranek, T., M. Rusnak, and A. Sokolova. 2017. Habit Formation in Consumption: A Meta-analysis. European Economic Review 95(1): 142–167.

    Google Scholar 

  48. Holston, K., T. Laubach, and J. Williams. 2017. Measuring the Natural Rate of Interest: International Trends and Determinants. Journal of International Economics 108(1): 59–75.

    Google Scholar 

  49. Ioannidis, J., T. Stanley, and C. Doucouliagos. 2017. The Power of Bias in Economics Research. Economic Journal 605: 236–265.

    Google Scholar 

  50. Ize, A. 2007. Spending Seigniorage: Do Central Banks Have a Governance Problem? IMF Staff Papers 4(3): 563–589.

    Google Scholar 

  51. Kiley, M., and J. Roberts. 2017. Monetary Policy in a Low Interest Rate World, 317–396. Fall: Brookings Papers on Economic Activity.

    Google Scholar 

  52. Klueh, U., and Stella, P. 2008. Central Bank Financial Strength and Policy Performance: An Econometric Evaluation. IMF Working Papers 08/176, International Monetary Fund.

  53. Lee, Y., and Y. Yoon. 2016. Central Bank Losses and Monetary Policy Implementation (in Korean). Economic Analysis Quarterly (Bank of Korea) 22(4): 109–147.

    Google Scholar 

  54. Lonergan, E. 2016. Helicopter Money is Different. Philosophy of Money, May 24, 2016.

  55. Mayer, T. 2016. From Zirp, Nirp, QE, and Helicopter Money to a Better Monetary System. Flossbach von Storch Research Institute, Economic Policy Note 16/3/2016.

  56. Meaning, J., Dyson, B., Barker, J., and Clayton, E. 2018. Broadening Narrow Money: Monetary Policy with a Central Bank Digital Currency. Staff Working Paper No. 724, London: Bank of England (May).

  57. Parker, J., N. Souleles, D. Johnson, and R. McClelland. 2013. Consumer Spending and the Economic Stimulus Payments of 2008. American Economic Review 103(6): 2530–2553.

    Google Scholar 

  58. Perera, A., D. Ralston, and J. Wickramanayake. 2013. Central Bank Financial Strength and Inflation: Is There a Robust Link? Journal of Financial Stability 9(3): 399–414.

    Google Scholar 

  59. Pinter, J. 2017. Central Bank Financial Strength and Inflation: An Empirical Reassessment Considering the Key Role of the Fiscal Support. Documents de Travail du Centre d’Economie de la Sorbonne 17055, Université Panthéon-Sorbonne (Paris 1).

  60. Rachel, L., and T. Smith. 2017. Are Low Real Interest Rates Here to Stay? International Journal of Central Banking 13(3): 1–42.

    Google Scholar 

  61. Reifschneider, D. 2016. Gauging the Ability of the FOMC to Respond to Future Recessions. Finance and Economics Discussion Series 2016-068, Board of Governors of the Federal Reserve System.

  62. Rodnyansky, A., and O. Darmouni. 2017. The Effects of Quantitative Easing on Bank Lending Behavior. Review of Financial Studies 30(11): 3858–3887.

    Google Scholar 

  63. Rogoff, K. 2017. Dealing with Monetary Paralysis at the Zero Bound. Journal of Economic Perspectives 31(3): 47–66.

    Google Scholar 

  64. Rossouw, J. 2016. Private Shareholding and Public Interest: An Analysis of an Eclectic Group of Central Banks. South African Journal of Economic and Management Sciences 19(1): 150–159.

    Google Scholar 

  65. Rossouw, J. 2018. An Institutional Comparison of Private Shareholding in the Central Banks of South Africa and Turkey. ERSA Working Papers 724, Economic Research Southern Africa.

  66. Stanley, T. 2001. Wheat from Chaff: Meta-analysis as Quantitative Literature Review. Journal of Economic Perspectives 15(3): 131–150.

    Google Scholar 

  67. Stanley, T. 2005. Beyond Publication Bias. Journal of Economic Surveys 19(3): 309–345.

    Google Scholar 

  68. Stanley, T. 2008. Meta-Regression Methods for Detecting and Estimating Empirical Effects in the Presence of Publication Selection. Oxford Bulletin of Economics and Statistics 70(1): 103–127.

    Google Scholar 

  69. Stanley, T., and C. Doucouliagos. 2010. Picture This: A Simple Graph That Reveals Much Ado About Research. Journal of Economic Surveys 24(1): 170–191.

    Google Scholar 

  70. Stanley, T., and C. Doucouliagos. 2014. Meta-Regression Approximations to Reduce Publication Selection Bias. Research Synthesis Methods 5(1): 60–78.

    Google Scholar 

  71. Stella, P. 2003. Why Central Banks Need Financial Strength. Central Banking Journal 14: 23–29.

    Google Scholar 

  72. Stella, P. 2011. Central Bank Financial Strength and Macroeconomic Policy Performance. In The Capital Needs of Central Banks, ed. S. Milton and P. Sinclair, 47–68. New York, NY: Routledge.

    Google Scholar 

  73. Tolle, M. 2016. Central Bank Digital Currency: The End of Monetary Policy as We Know It?. Bank Underground (25 July).

  74. Turner, A. 2015. The Case for Monetary Finance—An Essentially Political Issue. In IMF Jacques Polak Research Conference, November 5, 2015.

  75. van Rooij, M., and de Haan, J. 2016. Will Helicopter Money be Spent? New evidence. DNB Working Papers 538, Netherlands Central Bank, Research Department.

Download references

Acknowledgements

This research was conducted when Hampl was Vice-Governor of the Czech National Bank, and both authors gratefully acknowledge the support from the Bank (though the views expressed here are not necessarily those of the Bank). Havranek also acknowledges support from the Czech Science Foundation (Project 18-02513S) and Charles University (Project Primus/17/HUM/16). We thank Volha Audzei, Vit Barta, Vojtech Benda, Oldrich Dedek, Michal Franta, Tomas Holub, Nikolaos Kyriazis, Jiri Schwarz, and participants of a Czech National Bank seminar for useful comments, and a referee of Comparative Economic Studies for an exceptionally detailed report.

Author information

Affiliations

Authors

Corresponding author

Correspondence to Tomas Havranek.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Hampl, M., Havranek, T. Central Bank Equity as an Instrument of Monetary Policy. Comp Econ Stud 62, 49–68 (2020). https://doi.org/10.1057/s41294-019-00092-1

Download citation

Keywords

  • Central bank equity
  • Inflation
  • Seigniorage
  • Monetary policy
  • Helicopter money
  • Central bank digital currency

JEL Classification

  • E42
  • E52
  • E58