IDEAS home Printed from https://ideas.repec.org/p/hhs/osloec/2018_005.html
   My bibliography  Save this paper

Estimation of effects of recent macroprudential policies in a sample of advanced open economies

Author

Listed:

Abstract

We analyse a quarterly panel data set consisting of ten advanced open economies that have introduced macroprudential policy measures: caps on loan to value and income (LTV and LTI), and debt service to income (DSTI) requirements in particular, but also risk weights (RW), amortization (Amort) and, less used, countercyclical buffer (CCyB). Estimation of dynamic panel data models, that also include the central bank rate, and controls for common nominal and real trends, gives support to the view that several of the measures may have reduced credit growth when they were introduced.The estimated impact effects are most significant for LTV, LTI and RW. For Amort, the long-run effect on credit growth is significant, and the same is found for RW. The estimation results when house price growth is the dependent variable are in the main consistent with the results for credit growth. The results do not support that CCyB has reduced lending (as a consequence of higher financing costs), and we suggest that the variable is mainly a control in our data set. In that interpretation, it is interesting that the estimated coefficients of the other five instruments are robust with respect to exclusion of CCyB from the empirical models. The results are also robust to controls in the form of impulse indicator saturation (IIS).

Suggested Citation

  • Nymoen, Ragnar & Pedersen, Kari & Sjåberg, Jon Ivar, 2018. "Estimation of effects of recent macroprudential policies in a sample of advanced open economies," Memorandum 5/2018, Oslo University, Department of Economics.
  • Handle: RePEc:hhs:osloec:2018_005
    as

    Download full text from publisher

    File URL: https://www.sv.uio.no/econ/english/research/unpublished-works/working-papers/pdf-files/2018/memo0518.pdf
    File Function: Full text
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Hendry, David F., 2018. "Deciding between alternative approaches in macroeconomics," International Journal of Forecasting, Elsevier, vol. 34(1), pages 119-135.
    2. Kuttner, Kenneth N. & Shim, Ilhyock, 2016. "Can non-interest rate policies stabilize housing markets? Evidence from a panel of 57 economies," Journal of Financial Stability, Elsevier, vol. 26(C), pages 31-44.
    3. Hendry, David F. & Johansen, Søren, 2015. "Model Discovery And Trygve Haavelmo’S Legacy," Econometric Theory, Cambridge University Press, vol. 31(1), pages 93-114, February.
    4. Maurice J. G. Bun & Frank Windmeijer, 2010. "The weak instrument problem of the system GMM estimator in dynamic panel data models," Econometrics Journal, Royal Economic Society, vol. 13(1), pages 95-126, February.
    5. Cerutti, Eugenio & Claessens, Stijn & Laeven, Luc, 2017. "The use and effectiveness of macroprudential policies: New evidence," Journal of Financial Stability, Elsevier, vol. 28(C), pages 203-224.
    6. Ragnar Nymoen & Victoria Sparrman, 2015. "Equilibrium Unemployment Dynamics in a Panel of OECD Countries," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 77(2), pages 164-190, April.
    7. Jennifer L. Castle & Xiaochuan Qin & W. Robert Reed, 2013. "Using Model Selection Algorithms To Obtain Reliable Coefficient Estimates," Journal of Economic Surveys, Wiley Blackwell, vol. 27(2), pages 269-296, April.
    8. Arellano, Manuel, 2003. "Panel Data Econometrics," OUP Catalogue, Oxford University Press, number 9780199245291.
    9. Carlos Santos & David Hendry & Soren Johansen, 2008. "Automatic selection of indicators in a fully saturated regression," Computational Statistics, Springer, vol. 23(2), pages 317-335, April.
    10. Manuel Arellano & Stephen Bond, 1991. "Some Tests of Specification for Panel Data: Monte Carlo Evidence and an Application to Employment Equations," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 58(2), pages 277-297.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Vítor Martins & Alessandro Turrini & Bořek Vašíček & Madalina Zamfir, 2021. "Euro Area Housing Markets: Trends, Challenges and Policy Responses," European Economy - Discussion Papers 147, Directorate General Economic and Financial Affairs (DG ECFIN), European Commission.
    2. Lo Duca, Marco & Hallissey, Niamh & Jurca, Pavol & Kouratzoglou, Charalampos & Lima, Diana & Pirovano, Mara & Prapiestis, Algirdas & Saldías, Martín & Tereanu, Eugen & Bartal, Mehdi & Giedraitė, Edita, 2023. "The more the merrier? Macroprudential instrument interactions and effective policy implementation," Occasional Paper Series 310, European Central Bank.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Ragnar Nymoen & Kari Pedersen & Jon Ivar Sjåberg, 2019. "Estimation of Effects of Recent Macroprudential Policies in a Sample of Advanced Open Economies," IJFS, MDPI, vol. 7(2), pages 1-20, May.
    2. Belkhir, Mohamed & Naceur, Sami Ben & Candelon, Bertrand & Wijnandts, Jean-Charles, 2022. "Macroprudential policies, economic growth and banking crises," Emerging Markets Review, Elsevier, vol. 53(C).
    3. Felix Pretis, 2022. "Does a Carbon Tax Reduce CO2 Emissions? Evidence from British Columbia," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 83(1), pages 115-144, September.
    4. Akinci, Ozge & Olmstead-Rumsey, Jane, 2018. "How effective are macroprudential policies? An empirical investigation," Journal of Financial Intermediation, Elsevier, vol. 33(C), pages 33-57.
    5. Maurice J.G. Bun & Sarafidis, V., 2013. "Dynamic Panel Data Models," UvA-Econometrics Working Papers 13-01, Universiteit van Amsterdam, Dept. of Econometrics.
    6. Ferdi Celikay, 2020. "Dimensions of tax burden: a review on OECD countries," Journal of Economics, Finance and Administrative Science, Emerald Group Publishing Limited, vol. 25(49), pages 27-43, March.
    7. Raksmey, Uch & Lin, Ching-Yang & Kakinaka, Makoto, 2022. "Macroprudential regulation and financial inclusion: Any difference between developed and developing countries?," Research in International Business and Finance, Elsevier, vol. 63(C).
    8. Fatma Pinar Erdem Kucukbicakci & Etkin Ozen & Ibrahim Unalmis, 2020. "Are Macroprudential Policies Effective Tools to Reduce Credit Growth in Emerging Markets?," World Journal of Applied Economics, WERI-World Economic Research Institute, vol. 6(1), pages 73-89, June.
    9. Kuttner, Kenneth N. & Shim, Ilhyock, 2016. "Can non-interest rate policies stabilize housing markets? Evidence from a panel of 57 economies," Journal of Financial Stability, Elsevier, vol. 26(C), pages 31-44.
    10. Lena Gerling, 2018. "Rebellious Youth: Evidence on the Link between Youth Bulges, Institutional Bottlenecks, and Conflict," CESifo Economic Studies, CESifo Group, vol. 64(4), pages 577-616.
    11. Zhong, Changbiao & Xie, Lijuan & Shi, Yu & Xu, Xiangyun, 2023. "Macro-prudential policy, its alignment with monetary policy and house price growth: A cross-country study," The Quarterly Review of Economics and Finance, Elsevier, vol. 90(C), pages 51-62.
    12. de Moraes, Claudio Oliveira & de Mendonça, Helder Ferreira, 2019. "Bank’s risk measures and monetary policy: Evidence from a large emerging economy," The North American Journal of Economics and Finance, Elsevier, vol. 49(C), pages 121-132.
    13. Marcin Czaplicki, 2022. "Measuring the restrictiveness of (macro)prudential policy: the case of bank capital regulation in Poland," Journal of Banking Regulation, Palgrave Macmillan, vol. 23(3), pages 322-338, September.
    14. Hayakawa, Kazuhiko, 2019. "Alternative over-identifying restriction test in the GMM estimation of panel data models," Econometrics and Statistics, Elsevier, vol. 10(C), pages 71-95.
    15. Angelica Gonzalez, 2007. "Angelica Gonzalez," Edinburgh School of Economics Discussion Paper Series 168, Edinburgh School of Economics, University of Edinburgh.
    16. Sebastian Kripfganz & Claudia Schwarz, 2019. "Estimation of linear dynamic panel data models with time‐invariant regressors," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 34(4), pages 526-546, June.
    17. Chokri Zehri & Zagros Madjd‐Sadjadi, 2024. "Capital flow management and monetary policy to control credit growth," Economics and Politics, Wiley Blackwell, vol. 36(2), pages 637-676, July.
    18. Castle, Jennifer L. & Doornik, Jurgen A. & Hendry, David F., 2023. "Robust Discovery of Regression Models," Econometrics and Statistics, Elsevier, vol. 26(C), pages 31-51.
    19. De Wachter, Stefan & Tzavalis, Elias, 2012. "Detection of structural breaks in linear dynamic panel data models," Computational Statistics & Data Analysis, Elsevier, vol. 56(11), pages 3020-3034.
    20. Gadatsch, Niklas & Mann, Lukas & Schnabel, Isabel, 2018. "A new IV approach for estimating the efficacy of macroprudential measures," Economics Letters, Elsevier, vol. 168(C), pages 107-109.

    More about this item

    Keywords

    Macroprudential policy measures; house prices; credit growth; open economics; macro panel; impulse indicator saturation; robust estimation;
    All these keywords.

    JEL classification:

    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models
    • C44 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Operations Research; Statistical Decision Theory
    • C58 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Financial Econometrics
    • G28 - Financial Economics - - Financial Institutions and Services - - - Government Policy and Regulation
    • G38 - Financial Economics - - Corporate Finance and Governance - - - Government Policy and Regulation

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:hhs:osloec:2018_005. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Mari Strønstad Øverås (email available below). General contact details of provider: https://edirc.repec.org/data/souiono.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.