The synchronisation between financial and business cycles: a cross spectral analysis view
Abstract
Our study bridges the gap between in previous research on the synchronization between financial and business cycles over a long period. Using the data for the UK from 1270 to 2016 we analyze the synchronization between financial and business cycles using spectral Granger causality (Breitung & Candelon, 2006). Our paper brings several important findings to the discussion on the financial and business cycle link. Our paper is the first one (to the best of our knowledge) that use data over a long period spanning several centuries. We use spectral analysis and advanced spectral analysis (SSA) and (MSSA) to study the relationship between financial and business cycles in the long run. Paper results show financial and business cycles series moves along over the medium-term spectrum. We find a strong link between the cyclical component in the output (real GDP series) and the cyclical component in the financial series (housing price, credit).
First published online 26 May 2020
Keyword : financial cycles, business cycles, spectral granger causality, The UK, synchronization
How to Cite
Škare, M., & Porada-Rochoń, M. (2020). The synchronisation between financial and business cycles: a cross spectral analysis view. Technological and Economic Development of Economy, 26(4), 907-919. https://doi.org/10.3846/tede.2020.12567
This work is licensed under a Creative Commons Attribution 4.0 International License.
References
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Allen, M. R., & Smith, L. A. (1996). Monte Carlo SSA: Detecting irregular oscillations in the Presence of Colored Noise. Journal of Climate, 9(12), 3373–3404. https://doi.org/10.1175/1520-0442(1996)009<3373:mcsdio>2.0.co;2
Altar, M., Kubinschi, M., & Barnea, D. (2017). Measuring financial cycle length and assessing synchronization using wavelets. Romanian Journal of Economic Forecasting, 2(3), 18–36.
Andreas, G., & Michael, G. (2015). Monte Carlo Singular Spectrum Analysis (SSA) revisited: Detecting oscillator clusters in multivariate datasets. Journal of Climate, 28(19), 7873–7893. https://doi.org/10.1175/jcli-d-15-0100.1
Antonakakis, N., Breitenlechner, M., & Scharler, J. (2015). Business cycle and financial cycle spillovers in the G7 countries. The Quarterly Review of Economics and Finance, 58, 154–162. https://doi.org/10.1016/j.qref.2015.03.002
Bilan, Y., Brychko, M., Buriak, A., & Vasilyeva, T. (2019). Financial, business and trust cycles: the issues of synchronization. Zbornik radova Ekonomskog fakulteta u Rijeci: časopis za ekonomsku teoriju i praksu, 37(1), 113–138. https://doi.org/10.18045/zbefri.2019.1.113
Bonis, R. D., & Silvestrini, A. (2013). The Italian financial cycle: 18612011. Cliometrica, 8(3), 301–334. https://doi.org/10.1007/s11698-013-0103-5
Borio, C., Furfine, C., & Lowe, P. (2001). Procyclicality of the financial system and financial stability: issues and policy options. In Marrying the macro-and microprudential dimensions of financial stability (Vol. 01, pp. 1–57). Bank for International Settlements. https://econpapers.repec.org/RePEc:bis:bisbpc:01-01
Borio, C., Kennedy, N., & Prowse, S. D. (1994). Exploring aggregate asset price fluctuations across countries: Measurement, determinants and monetary policy implications. (BIS Economic Paper No. 40 (April)).
Borio, C., & Drehmann, M. H. D. (2019). Predicting recessions, financial cycle versus term spread. (BIS working paper No. 818).
Breitung, J., & Candelon, B. (2006). Testing for short- and long-run causality: A frequency-domain approach, Journal of Econometrics, 132(2), 363–378. https://doi.org/10.1016/j.jeconom.2005.02.004
Broadberry, S., Campbell, B. M. S., Klein, A., Overton, M., & van Leeuwen, B. (2015). British economic growth 1270–1870. Cambridge University Press. https://doi.org/10.1017/cbo9781107707603.016
Broomhead, D. S., & King, G. P. (1986a). Extracting qualitative dynamics from experimental data. Physica D: Nonlinear Phenomena, 20(2–3), 217–236. https://doi.org/10.1016/0167-2789(86)90031-x
Broomhead, D. S., & King, G. P. (1986b). On the qualitative analysis of experimental dynamical systems. In S. Sarkar (Eds.), Nonlinear phenomena and chaos (pp. 113–144). Adam Hilger Bristol.
Burns, A. F., & Mitchell, W. C. (1946). Measuring business cycles. NBER Books. https://academic.microsoft.com/paper/2109083778
Claessens, S., Kose, M. A., & Terrones, M. E. (2012). How do business and financial cycles interact?. Journal of International Economics, 87(1), 178–190. https://doi.org/10.1016/j.jinteco.2011.11.008
Clark, G. (2010). The macroeconomic aggregates for England 1209–2008. In A. Field (Ed.), Research in economic history (pp. 51–140). Emerald Group Publishing Limited. https://doi.org/10.1108/s0363-3268(2010)0000027004
Coussin, M. (2019). Financial cycle discrepancy in the euro area (Master thesis 2). Universite de Paris 1 Panthenon Sorbonne, France.
Drehman, M., Borio, C., & Tsatsaronis, K. (2012). Characterizing the financial cycle: Don’t lose sight of the medium term!. Bank of International Settlement. https://web.archive.org
Drehmann, M., Borio, C., & Tsatsaronis, K. (2013). Can we identify the financial cycle?. The Role of Central Banks in Financial Stability How Has It Changed? Studies in International Economics 30, 131–156. https://doi.org/10.1142/9789814449922_0007
Fisher, I. (1933). The debt-deflation theory of great depressions. Econometrica, 1(4), 337. https://doi.org/10.2307/1907327
Floris, T. (1981). Detecting strange attractors in turbulence. In Lecture Notes in Mathematics (pp. 366– 381). Springer Berlin Heidelberg. https://doi.org/10.1007/bfb0091924
Galati, G., Hindrayanto, I., Koopman, S. J., & Vlekke, M. (2016). Measuring financial cycles in a modelbased analysis: Empirical evidence for the United States and the euro area. Economics Letters, 145, 83–87. https://doi.org/10.1016/j.econlet.2016.05.034
Ginevičius, R., Dudzevičiūtė, G., Schieg, M., & Peleckis, K. (2019). The inter-linkages between financial and economic development in the European Union Countries, Economic Research-Ekonomska Istraživanja, 32(1), 3309–3326. https://doi.org/10.1080/1331677X.2019.1663436
Gonzalez, R. B., Lima, J., & Marinho, L. (2015). Business and financial cycles: An estimation of cycles’ length focusing on Macroprudential Policy (Working paper 385, pp. 1–48). Banco central Du Brasil.
Groth, A., & Ghil, M. (2011). Multivariate singular spectrum analysis and the road to phase synchronization. Physical Review E, 84(3). https://doi.org/10.1103/physreve.84.036206
Gupta, R., Marco Lau, C. K., Plakandaras, V., & Wong, W. K. (2019). The role of housing sentiment in forecasting U.S. home sales growth: evidence from a Bayesian compressed vector autoregressive model, Economic Research-Ekonomska Istraživanja, 32(1), 2554–2567. https://doi.org/10.1080/1331677X.2019.1650657
Harding, D., & Pagan, A. (2016). The econometric analysis of recurrent events in macroeconomics and finance. Economics Books (1 ed.). Princeton University Press. https://doi.org/10.23943/princeton/9780691167084.001.0001
Hiebert, P., Jaccard, I., & Schüler, Y. (2018). Contrasting financial and business cycles: Stylized facts and candidate explanations. Journal of Financial Stability, 38, 72–80. https://doi.org/10.1016/j.jfs.2018.06.002
Hudson, H. R. (1957). A model of the trade cycle*. Economic Record, 33(66), 378–389. https://doi.org/10.1111/j.1475-4932.1957.tb01306.x
Iacobucci, A. (2005). Spectral analysis for economic time series. In Lecture Notes in Economics and Mathematical Systems (pp. 203–219). Springer-Verlag. https://doi.org/10.1007/3-540-28444-3_12
Jordà, Ò., Schularick, M., & Taylor, A. M. (2017). Macrofinancial history and the new business cycle facts. In M. Eichenbaum & J. A. Parke (Eds.), NBER Macroeconomics Annual 2016, Volume 31, (pp. 213–263). University of Chicago Press. https://doi.org/10.1086/690241
Kaldor, N. (1940). A model of the trade cycle. The Economic Journal, 50(197), 78. https://doi.org/10.2307/2225740
Keynes, J. M. (1936). The general theory of employment, interest and money. Macmillan.
Koopman, S. J., & Lucas, A. (2005). Business and default cycles for credit risk. Journal of Applied Econometrics, 20(2), 311–323. https://doi.org/10.1002/jae.833
El-Baz, O. (2018). The synchronization of financial and business cycles in Saudi Arabia. Scholedge International Journal of Management & Development, 5(4), 32–47. https://doi.org/10.19085/journal.sijmd050401
Michael, G. (2002). Advanced spectral methods for climatic time series. Reviews of Geophysics, 40(1). https://doi.org/10.1029/2000rg000092
Minsky, H. (1986). Stabilizingan unstable economy. Yale University Press.
Minsky, H. P. (1964). Longer waves in financial relations: Financial factors in the more severe depressions. The American Economic Review, 54(3), 324–335.
Pontines, V. (2017). The financial cycles in four East Asian economies. Economic Modelling, 65, 51–66. https://doi.org/10.1016/j.econmod.2017.05.005
Porada-Rochoń, M., & Škare, M. (2020). Generalized financial cycle theory from the Minsky’s Perspective: UK 1270–2016, Journal of Business Economics and Management (forthcoming).
Rashid, A., Fayyaz, M., & Karim, M. (2019). Investor sentiment, momentum, and stock returns: an examination for direct and indirect effects, Economic Research-Ekonomska Istraživanja, 32(1), 2638–2656. https://doi.org/10.1080/1331677X.2019.1650652
Ricardo, M. (1981). On the dimension of the compact invariant sets of certain non-linear maps. In Lecture Notes in Mathematics (pp. 230–242). Springer Berlin Heidelberg. https://doi.org/10.1007/bfb0091916
Rünstler, G., & Vlekke, M. (2016). Business, housing and credit cycles (ECB Working Paper Series, No. 1915).
Ryland, T., & Dimsdale, N. (2017). A millenium of UK data. Bank of England OBRA dataset. http://www.bankofengland.co.uk/research/Pages/onebank/threecenturies.aspx
Scharnagl, M., & Mandler, M. (2019). Real and financial cycles in Euro area economies: Results from wavelet analysis. Jahrbücher Für Nationalökonomie Und Statistik, 239(5–6), 895–916. https://doi.org/10.1515/jbnst-2019-0035
Schüler, Y. S., Hiebert, P., & Peltonen, T. A. (2014). Characterizing financial cycles across Europe: one size does not fit all. https://doi.org/10.2139/ssrn.2539717
Skare, M., & Porada-Rochon, M. (2019a). Tracking financial cycles in ten transitional economies 2005– 2018 using singular spectrum analysis (SSA) techniques. Equilibrium. Quarterly Journal of Economics and Economic Policy, 14(1), 7–29. https://doi.org/10.24136/eq.2019.001
Skare, M., & Porada-Rochoń, M. (2019b). Multi-channel Singular-Spectrum Analysis (MSSA) of financial cycles in ten developed economies 1970–2018. Journal of Business Research, 112, 567–575. https://doi.org/10.1016/j.jbusres.2019.10.047
Strohsal, T., Proaño, C. R., & Wolters, J. (2018). Assessing the cross-country interaction of financial cycles: evidence from a multivariate spectral analysis of the USA and the UK. Empirical Economics, 57(2), 385–398. https://doi.org/10.1007/s00181-018-1471-2
Strohsal, T., Proaño, Ch. R., & Wolters, J. (2019). Characterizing the financial cycle: Evidence from a frequency domain analysis. Journal of Banking and Finance, 106, 568–591. https://doi.org/10.1016/j.jbankfin.2019.06.010
Tastan, H. (2016). COSPECTDENS: Stata module to compute cross spectra. Statistical Software Components S458168. Boston College Department of Economics, revised 31 May 2016.
Tsai, I. C. (2019). European house price deviation: infectivity and the momentum effect, Economic Research-Ekonomska Istraživanja, 32(1), 1521–1541. https://doi.org/10.1080/1331677X.2019.1636698
Vautard, R., & Ghil, M. (1989). Singular spectrum analysis in nonlinear dynamics, with applications to paleoclimatic time series. Physica D: Nonlinear Phenomena, 35(3), 395–424. https://doi.org/10.1016/0167-2789(89)90077-8
Vautard, R., Yiou, P., & Ghil, M. (1992). Singular-spectrum analysis: A toolkit for short noisy chaotic signals. Physica D: Nonlinear Phenomena, 58(1–4), 95–126. https://doi.org/10.1016/0167-2789(92)90103-t
Vasicek, B., & Monteiro, D. (2018). Financial cycle in the euro area. Quarterly Report on EU data, 17(2).
Aikman, D., Haldane, A. G., & Nelson, B. D. (2015). Curbing the credit cycle. The Economic Journal, 125(585), 1072–1109. https://doi.org/10.1111/ecoj.12113
Allen, M. R., & Smith, L. A. (1996). Monte Carlo SSA: Detecting irregular oscillations in the Presence of Colored Noise. Journal of Climate, 9(12), 3373–3404. https://doi.org/10.1175/1520-0442(1996)009<3373:mcsdio>2.0.co;2
Altar, M., Kubinschi, M., & Barnea, D. (2017). Measuring financial cycle length and assessing synchronization using wavelets. Romanian Journal of Economic Forecasting, 2(3), 18–36.
Andreas, G., & Michael, G. (2015). Monte Carlo Singular Spectrum Analysis (SSA) revisited: Detecting oscillator clusters in multivariate datasets. Journal of Climate, 28(19), 7873–7893. https://doi.org/10.1175/jcli-d-15-0100.1
Antonakakis, N., Breitenlechner, M., & Scharler, J. (2015). Business cycle and financial cycle spillovers in the G7 countries. The Quarterly Review of Economics and Finance, 58, 154–162. https://doi.org/10.1016/j.qref.2015.03.002
Bilan, Y., Brychko, M., Buriak, A., & Vasilyeva, T. (2019). Financial, business and trust cycles: the issues of synchronization. Zbornik radova Ekonomskog fakulteta u Rijeci: časopis za ekonomsku teoriju i praksu, 37(1), 113–138. https://doi.org/10.18045/zbefri.2019.1.113
Bonis, R. D., & Silvestrini, A. (2013). The Italian financial cycle: 18612011. Cliometrica, 8(3), 301–334. https://doi.org/10.1007/s11698-013-0103-5
Borio, C., Furfine, C., & Lowe, P. (2001). Procyclicality of the financial system and financial stability: issues and policy options. In Marrying the macro-and microprudential dimensions of financial stability (Vol. 01, pp. 1–57). Bank for International Settlements. https://econpapers.repec.org/RePEc:bis:bisbpc:01-01
Borio, C., Kennedy, N., & Prowse, S. D. (1994). Exploring aggregate asset price fluctuations across countries: Measurement, determinants and monetary policy implications. (BIS Economic Paper No. 40 (April)).
Borio, C., & Drehmann, M. H. D. (2019). Predicting recessions, financial cycle versus term spread. (BIS working paper No. 818).
Breitung, J., & Candelon, B. (2006). Testing for short- and long-run causality: A frequency-domain approach, Journal of Econometrics, 132(2), 363–378. https://doi.org/10.1016/j.jeconom.2005.02.004
Broadberry, S., Campbell, B. M. S., Klein, A., Overton, M., & van Leeuwen, B. (2015). British economic growth 1270–1870. Cambridge University Press. https://doi.org/10.1017/cbo9781107707603.016
Broomhead, D. S., & King, G. P. (1986a). Extracting qualitative dynamics from experimental data. Physica D: Nonlinear Phenomena, 20(2–3), 217–236. https://doi.org/10.1016/0167-2789(86)90031-x
Broomhead, D. S., & King, G. P. (1986b). On the qualitative analysis of experimental dynamical systems. In S. Sarkar (Eds.), Nonlinear phenomena and chaos (pp. 113–144). Adam Hilger Bristol.
Burns, A. F., & Mitchell, W. C. (1946). Measuring business cycles. NBER Books. https://academic.microsoft.com/paper/2109083778
Claessens, S., Kose, M. A., & Terrones, M. E. (2012). How do business and financial cycles interact?. Journal of International Economics, 87(1), 178–190. https://doi.org/10.1016/j.jinteco.2011.11.008
Clark, G. (2010). The macroeconomic aggregates for England 1209–2008. In A. Field (Ed.), Research in economic history (pp. 51–140). Emerald Group Publishing Limited. https://doi.org/10.1108/s0363-3268(2010)0000027004
Coussin, M. (2019). Financial cycle discrepancy in the euro area (Master thesis 2). Universite de Paris 1 Panthenon Sorbonne, France.
Drehman, M., Borio, C., & Tsatsaronis, K. (2012). Characterizing the financial cycle: Don’t lose sight of the medium term!. Bank of International Settlement. https://web.archive.org
Drehmann, M., Borio, C., & Tsatsaronis, K. (2013). Can we identify the financial cycle?. The Role of Central Banks in Financial Stability How Has It Changed? Studies in International Economics 30, 131–156. https://doi.org/10.1142/9789814449922_0007
Fisher, I. (1933). The debt-deflation theory of great depressions. Econometrica, 1(4), 337. https://doi.org/10.2307/1907327
Floris, T. (1981). Detecting strange attractors in turbulence. In Lecture Notes in Mathematics (pp. 366– 381). Springer Berlin Heidelberg. https://doi.org/10.1007/bfb0091924
Galati, G., Hindrayanto, I., Koopman, S. J., & Vlekke, M. (2016). Measuring financial cycles in a modelbased analysis: Empirical evidence for the United States and the euro area. Economics Letters, 145, 83–87. https://doi.org/10.1016/j.econlet.2016.05.034
Ginevičius, R., Dudzevičiūtė, G., Schieg, M., & Peleckis, K. (2019). The inter-linkages between financial and economic development in the European Union Countries, Economic Research-Ekonomska Istraživanja, 32(1), 3309–3326. https://doi.org/10.1080/1331677X.2019.1663436
Gonzalez, R. B., Lima, J., & Marinho, L. (2015). Business and financial cycles: An estimation of cycles’ length focusing on Macroprudential Policy (Working paper 385, pp. 1–48). Banco central Du Brasil.
Groth, A., & Ghil, M. (2011). Multivariate singular spectrum analysis and the road to phase synchronization. Physical Review E, 84(3). https://doi.org/10.1103/physreve.84.036206
Gupta, R., Marco Lau, C. K., Plakandaras, V., & Wong, W. K. (2019). The role of housing sentiment in forecasting U.S. home sales growth: evidence from a Bayesian compressed vector autoregressive model, Economic Research-Ekonomska Istraživanja, 32(1), 2554–2567. https://doi.org/10.1080/1331677X.2019.1650657
Harding, D., & Pagan, A. (2016). The econometric analysis of recurrent events in macroeconomics and finance. Economics Books (1 ed.). Princeton University Press. https://doi.org/10.23943/princeton/9780691167084.001.0001
Hiebert, P., Jaccard, I., & Schüler, Y. (2018). Contrasting financial and business cycles: Stylized facts and candidate explanations. Journal of Financial Stability, 38, 72–80. https://doi.org/10.1016/j.jfs.2018.06.002
Hudson, H. R. (1957). A model of the trade cycle*. Economic Record, 33(66), 378–389. https://doi.org/10.1111/j.1475-4932.1957.tb01306.x
Iacobucci, A. (2005). Spectral analysis for economic time series. In Lecture Notes in Economics and Mathematical Systems (pp. 203–219). Springer-Verlag. https://doi.org/10.1007/3-540-28444-3_12
Jordà, Ò., Schularick, M., & Taylor, A. M. (2017). Macrofinancial history and the new business cycle facts. In M. Eichenbaum & J. A. Parke (Eds.), NBER Macroeconomics Annual 2016, Volume 31, (pp. 213–263). University of Chicago Press. https://doi.org/10.1086/690241
Kaldor, N. (1940). A model of the trade cycle. The Economic Journal, 50(197), 78. https://doi.org/10.2307/2225740
Keynes, J. M. (1936). The general theory of employment, interest and money. Macmillan.
Koopman, S. J., & Lucas, A. (2005). Business and default cycles for credit risk. Journal of Applied Econometrics, 20(2), 311–323. https://doi.org/10.1002/jae.833
El-Baz, O. (2018). The synchronization of financial and business cycles in Saudi Arabia. Scholedge International Journal of Management & Development, 5(4), 32–47. https://doi.org/10.19085/journal.sijmd050401
Michael, G. (2002). Advanced spectral methods for climatic time series. Reviews of Geophysics, 40(1). https://doi.org/10.1029/2000rg000092
Minsky, H. (1986). Stabilizingan unstable economy. Yale University Press.
Minsky, H. P. (1964). Longer waves in financial relations: Financial factors in the more severe depressions. The American Economic Review, 54(3), 324–335.
Pontines, V. (2017). The financial cycles in four East Asian economies. Economic Modelling, 65, 51–66. https://doi.org/10.1016/j.econmod.2017.05.005
Porada-Rochoń, M., & Škare, M. (2020). Generalized financial cycle theory from the Minsky’s Perspective: UK 1270–2016, Journal of Business Economics and Management (forthcoming).
Rashid, A., Fayyaz, M., & Karim, M. (2019). Investor sentiment, momentum, and stock returns: an examination for direct and indirect effects, Economic Research-Ekonomska Istraživanja, 32(1), 2638–2656. https://doi.org/10.1080/1331677X.2019.1650652
Ricardo, M. (1981). On the dimension of the compact invariant sets of certain non-linear maps. In Lecture Notes in Mathematics (pp. 230–242). Springer Berlin Heidelberg. https://doi.org/10.1007/bfb0091916
Rünstler, G., & Vlekke, M. (2016). Business, housing and credit cycles (ECB Working Paper Series, No. 1915).
Ryland, T., & Dimsdale, N. (2017). A millenium of UK data. Bank of England OBRA dataset. http://www.bankofengland.co.uk/research/Pages/onebank/threecenturies.aspx
Scharnagl, M., & Mandler, M. (2019). Real and financial cycles in Euro area economies: Results from wavelet analysis. Jahrbücher Für Nationalökonomie Und Statistik, 239(5–6), 895–916. https://doi.org/10.1515/jbnst-2019-0035
Schüler, Y. S., Hiebert, P., & Peltonen, T. A. (2014). Characterizing financial cycles across Europe: one size does not fit all. https://doi.org/10.2139/ssrn.2539717
Skare, M., & Porada-Rochon, M. (2019a). Tracking financial cycles in ten transitional economies 2005– 2018 using singular spectrum analysis (SSA) techniques. Equilibrium. Quarterly Journal of Economics and Economic Policy, 14(1), 7–29. https://doi.org/10.24136/eq.2019.001
Skare, M., & Porada-Rochoń, M. (2019b). Multi-channel Singular-Spectrum Analysis (MSSA) of financial cycles in ten developed economies 1970–2018. Journal of Business Research, 112, 567–575. https://doi.org/10.1016/j.jbusres.2019.10.047
Strohsal, T., Proaño, C. R., & Wolters, J. (2018). Assessing the cross-country interaction of financial cycles: evidence from a multivariate spectral analysis of the USA and the UK. Empirical Economics, 57(2), 385–398. https://doi.org/10.1007/s00181-018-1471-2
Strohsal, T., Proaño, Ch. R., & Wolters, J. (2019). Characterizing the financial cycle: Evidence from a frequency domain analysis. Journal of Banking and Finance, 106, 568–591. https://doi.org/10.1016/j.jbankfin.2019.06.010
Tastan, H. (2016). COSPECTDENS: Stata module to compute cross spectra. Statistical Software Components S458168. Boston College Department of Economics, revised 31 May 2016.
Tsai, I. C. (2019). European house price deviation: infectivity and the momentum effect, Economic Research-Ekonomska Istraživanja, 32(1), 1521–1541. https://doi.org/10.1080/1331677X.2019.1636698
Vautard, R., & Ghil, M. (1989). Singular spectrum analysis in nonlinear dynamics, with applications to paleoclimatic time series. Physica D: Nonlinear Phenomena, 35(3), 395–424. https://doi.org/10.1016/0167-2789(89)90077-8
Vautard, R., Yiou, P., & Ghil, M. (1992). Singular-spectrum analysis: A toolkit for short noisy chaotic signals. Physica D: Nonlinear Phenomena, 58(1–4), 95–126. https://doi.org/10.1016/0167-2789(92)90103-t
Vasicek, B., & Monteiro, D. (2018). Financial cycle in the euro area. Quarterly Report on EU data, 17(2).