Financial cycles in the economy and in economic research: a case study in China
This work explores the relationship between financial cycles in the economy and in economic research. To this aim, we take China as an empirical example, and an intuitive bibliometric analysis of selected terms concerning financial cycles in economic research is performed first. Both in the economy and in economic research, we then conduct singular spectrum analysis to further isolate and describe the specific length and amplitude of financial cycles for China based on quarterly time-series data. Finally, according to the estimated cycles that detrended by Hodrick-Prescott filter for financial and bibliometric variables, the Granger causality test scrutinizes the results of the first two steps. Moreover, a time-varying parameter vector autoregression model is estimated to quantitatively investigate the time-varying interaction between financial and bibliometric variables. Our study shows that financial cycles have a strong effect on the developments in the financial-related literature. In particular, the 2008 global financial crisis’s impulse intensity is significantly higher than in other periods. Surprisingly, discussions on financial cycles in the literature also have an impact on financial activities in real life. These findings contribute to nascent work on the patterns in financial cycles, thus providing a new and effective insight on the interpretation of financial activities.
This work is licensed under a Creative Commons Attribution 4.0 International License.
Allen, M., & Smith, L. (1996). Monte Carlo SSA: Detecting irregular oscillations in the Presence of Colored Noise. Journal of Climate, 9. https://doi.org/10.1175/1520-0442(1996)009<3373:MCSDIO>2.0.CO;2
Amiti, M., McGuire, P., & Weinstein, D. E. (2019). International bank flows and the global financial cycle. IMF Economic Review, 67(1), 61–108. https://doi.org/10.1057/s41308-018-0072-6
Beirne, J. (2020). Financial cycles in asset markets and regions. Economic Modelling, 92, 358–374. https://doi.org/10.1016/j.econmod.2020.01.015
Berger, A. N., & Udell, G. F. (1998). The economics of small business finance: The roles of private equity and debt markets in the financial growth cycle. Journal of Banking & Finance, 22(6), 613–673. https://doi.org/10.1016/S0378-4266(98)00038-7
Boisjoly, R. P., Conine, T. E., & McDonald, M. B. (2020). Working capital management: Financial and valuation impacts. Journal of Business Research, 108, 1–8. https://doi.org/10.1016/j.jbusres.2019.09.025
Borio, C. (2014). The financial cycle and macroeconomics: What have we learnt? Journal of Banking & Finance, 45, 182–198. https://doi.org/10.1016/j.jbankfin.2013.07.031
Borio, C. (2017). Secular stagnation or financial cycle drag? Business Economics, 52, 1–12. https://doi.org/10.1057/s11369-017-0035-3
Brem, A., Nylund, P., & Viardot, E. (2020). The impact of the 2008 financial crisis on innovation: A dominant design perspective. Journal of Business Research, 110, 360–369. https://doi.org/10.1016/j.jbusres.2020.01.048
Chen, H., Yang, Y., Yang, Y., Jiang, W., & Zhou, J. (2014). A bibliometric investigation of life cycle assessment research in the web of science databases. The International Journal of Life Cycle Assessment, 19(10), 1674–1685. https://doi.org/10.1007/s11367-014-0777-3
Chen, W., Liu, W., Geng, Y., Brown, M. T., Gao, C., & Wu, R. (2017). Recent progress on emergy research: A bibliometric analysis. Renewable and Sustainable Energy Reviews, 73, 1051–1060. https://doi.org/10.1016/j.rser.2017.02.041
Claessens, S., Kose, M. A., & Terrones, M. E. (2011). Financial cycles: What? How? When? NBER International Seminar on Macroeconomics, 7(1), 303–344.
Costa, D. F., Carvalho, F. D., Moreira, B. C. D., & do Prado, J. W. (2017). Bibliometric analysis on the association between behavioral finance and decision making with cognitive biases such as overconfidence, anchoring effect and confirmation bias. Scientometrics, 111(3), 1775–1799. https://doi.org/10.1007/s11192-017-2371-5
Colebrook, J. M. (1978). Continuous plankton records: Zooplankton and environment, North-East Atlantic and North Sea, 1948–1975. Oceanologica Acta, 1(1), 9–23.
Cortés-Sánchez, J. D. (2019). Innovation in Latin America through the lens of bibliometrics: Crammed and fading away. Scientometrics, 121, 869–895. https://doi.org/10.1007/s11192-019-03201-0
Demetrescu, C., Finocchi, I., Ribichini, A., & Schaerf, M. (2020). On bibliometrics in academic promotions: A case study in computer science and engineering in Italy. Scientometrics. https://doi.org/10.1007/s11192-020-03548-9
Drehmann, M., Borio, C., & Tsatsaronis, K. (2012). Characterising the financial cycle: Don’t lose sight of the medium term! (BIS Working Papers No. 380, pp. 1–38).
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.
Elliott, G., Stock, J., & Rothenberg, T. (1996). Efficient tests for an autoregressive unit root. Econometrica, 64, 813–836. https://doi.org/10.2307/2171846
Elsner, J. B. (2002). Analysis of time series structure: SSA and related techniques. Journal of the American Statistical Association, 97(460), 1207–1208. https://doi.org/10.1198/jasa.2002.s239
Farrell, G., & Kemp, E. (2020). Measuring the financial cycle in South Africa. South African Journal of Economics. https://doi.org/10.1111/saje.12246
Fidrmuc, J., & Korhonen, I. (2010). The impact of the global financial crisis on business cycles in Asian emerging economies. Journal of Asian Economics, 21(3), 293–303. https://doi.org/10.1016/j.asieco.2009.07.007
Geiger, N. (2014). The rise of behavioural economics: A quantitative assessment. In 18th Annual ESHET Conference on “Liberalisms: perspectives and debates in the history of economic thought” (pp. 29–31).
Geiger, N., & Kufenko, V. (2016). Business cycles in the economy and in economics: an econometric analysis. Scientometrics, 107(1), 43–69. https://doi.org/10.1007/s11192-016-1866-9
Geweke, J. F. (1991). Evaluating the accuracy of sampling-based approaches to the calculation of posterior moments (Staff Report 148). Federal Reserve Bank of Minneapolis. https://ideas.repec.org/p/fip/fedmsr/148.html
Ghil, M., Allen, M., Dettinger, M., Ide, K., Kondrashov, D., Mann, M., Saunders, A., Tian, Y., & Varadi, F. (2001). Advanced spectral methods for climatic time series. Reviews of Geophysics, 40.
Granger, C. (1980). Testing for causality: A personal viewpoint. Journal of Economic Dynamics and Control, 2, 329–352. https://doi.org/10.1016/0165-1889(80)90069-X
Granger, C. W. J. (1969). Investigating causal relations by econometric models and cross-spectral methods. Econometrica, 37(3), 424–438. https://doi.org/10.2307/1912791
Groth, A., & Ghil, M. (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
Hodrick, R. J., & Prescott, E. C. (1997). Postwar U.S. business cycles: An empirical investigation. Journal of Money, Credit and Banking, 29(1), 1–16.
Iacobucci, A. (2005). Spectral analysis for economic time series. Lecture Notes in Economics & Mathematical Systems, 551, 203–219. https://doi.org/10.1007/3-540-28444-3_12
Inekwe, J. N., & Valenzuela, M. R. (2020). Financial integration and banking crisis. A critical analysis of restrictions on capital flows. World Economy, 43(2), 506–527. https://doi.org/10.1111/twec.12855
Jetter, M., & Kristoffersen, I. (2018). Financial shocks and the erosion of interpersonal trust: Evidence from longitudinal data. Journal of Economic Psychology, 67, 162–176. https://doi.org/10.1016/j.joep.2018.07.001
Jordà, Ò., Schularick, M., & Taylor, A. M. (2013). When credit bites back. Journal of Money, Credit and Banking, 45(s2), 3–28. https://doi.org/10.1111/jmcb.12069
Juselius, M., Borio, C., Disyatat, P., & Drehmann, M. (2016). Monetary policy, the financial cycle, and ultra-low interest rates. International Journal of Central Banking, 13, 55–89.
Lee, C.-C., Chen, M.-P., & Ning, S.-L. (2017). Why did some firms perform better in the global financial crisis? Economic Research-Ekonomska Istrazivanja, 30(1), 1339–1366. https://doi.org/10.1080/1331677X.2017.1355258
Martínez-García, E., & Grossman, V. (2020). Explosive dynamics in house prices? An exploration of financial market spillovers in housing markets around the world. Journal of International Money and Finance, 101, 102103. https://doi.org/10.1016/j.jimonfin.2019.102103
Mizen, P., & Tsoukas, S. (2012). The response of the external finance premium in Asian corporate bond markets to financial characteristics, financial constraints and two financial crises. Journal of Banking & Finance, 36(11), 3048–3059. https://doi.org/10.1016/j.jbankfin.2012.07.005
Morana, C. (2017). The U.S. dollar/Euro exchange rate: Structural modeling and forecasting during the recent financial crises. Journal of Forecasting, 36(8), 919–935. https://doi.org/10.1002/for.2430
Mourao, P. R., & Martinho, V. D. (2020). Forest entrepreneurship: A bibliometric analysis and a discussion about the co-authorship networks of an emerging scientific field. Journal of Cleaner Production, 256, 120413. https://doi.org/10.1016/j.jclepro.2020.120413
Muhammad, A., Ali, M. A. H., & Shanono, I. H. (2020). ANSYS-A bibliometric study. Materials Today: Proceedings, 26(2), 1005–1009. https://doi.org/10.1016/j.matpr.2020.01.192
Nakajima, J. (2011). Time-varying parameter VAR model with stochastic volatility: An overview of methodology and empirical applications. Monetary and Economic Studies, 29, 107–142.
Nielsen, B. (2001). Order determination in general vector autoregressions. IMS Lecture Notes-Monograph Series, 52.
Ouyang, A. Y., & Guo, S. (2019). Macro-prudential policies, the global financial cycle and the real exchange rate. Journal of International Money and Finance, 96, 147–167. https://doi.org/10.1016/j.jimonfin.2019.05.009
Ozili, P. K. (2018). Impact of digital finance on financial inclusion and stability. Borsa Istanbul Review, 18(4), 329–340. https://doi.org/10.1016/j.bir.2017.12.003
Pagan, A., & Robinson, T. (2014). Methods for assessing the impact of financial effects on business cycles in macroeconometric models. Journal of Macroeconomics, 41, 94–106. https://doi.org/10.1016/j.jmacro.2014.04.002
Pinheiro, T., Rivadeneyra, F., & Teignier, M. (2017). Financial development, credit, and business cycles. Journal of Money Credit and Banking, 49(7), 1653–1665. https://doi.org/10.1111/jmcb.12427
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
Pragidis, I. C., Tsintzos, P., & Plakandaras, B. (2018). Asymmetric effects of government spending shocks during the financial cycle. Economic Modelling, 68, 372–387. https://doi.org/10.1016/j.econmod.2017.08.005
Primiceri, G. E. (2005). Time varying structural vector autoregressions and monetary policy. The Review of Economic Studies, 72(3), 821–852. https://doi.org/10.1111/j.1467-937X.2005.00353.x
Qin, Y., Wang, X. X., Xu, Z. S., & Škare, M. (2021). The impact of poverty cycles on economic research: evidence from econometric analysis. Economic Research-Ekonomska Istraživanja, 34(1), 152–171. https://doi.org/10.1080/1331677X.2020.1780144
Qin, Y., Xu, Z. S., Wang, X. X., & Škare, M. (2020). Are family firms in the eyes of economic policy? International Entrepreneurship and Management Journal. https://doi.org/10.1007/s11365-020-00699-2
Rey, H. (2013). Dilemma not trilemma: the global cycle and monetary policy independence. Proceedings – Economic Policy Symposium – Jackson Hole, 1–2.
Rozite, K., Bezemer, D. J., & Jacobs, J. P. A. M. (2019). Towards a financial cycle for the U.S., 1973–2014. The North American Journal of Economics and Finance, 50, 101023. https://doi.org/10.1016/j.najef.2019.101023
Schularick, M., & Taylor, A. (2009). Credit booms gone bust: Monetary policy, leverage cycles, and financial crises, 1870–2008. American Economic Review, 102, 1029–1061. https://doi.org/10.1257/aer.102.2.1029
Schüler, Y. S., Hiebert, P. P., & Peltonen, T. A. (2020). Financial cycles: Characterisation and real-time measurement. Journal of International Money and Finance, 100, 102082. https://doi.org/10.1016/j.jimonfin.2019.102082
Shen, C.-H., Shi, J.-G., & Wu, M.-W. (2019). Is finance a veil? Lead-and-lag relationship between financial and business cycles: The case of China. European Financial Management, 25(4), 978–1012. https://doi.org/10.1111/eufm.12193
Sims, C. A. (1980). Macroeconomics and Reality. Econometrica, 48(1), 1–48. https://doi.org/10.2307/1912017
Škare, M., & Porada-Rochon, M. (2019). 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
Škare, M., & Porada-Rochoń, M. (2020). Multi-channel singular-spectrum analysis of financial cycles in ten developed economies for 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. (2019a). Assessing the cross-country interaction of financial cycles: Evidence from a multivariate spectral analysis of the USA and the U.K. Empirical Economics, 57(2), 385–398. https://doi.org/10.1007/s00181-018-1471-2
Strohsal, T., Proaño, C. R., & Wolters, J. (2019b). Characterizing the financial cycle: Evidence from a frequency domain analysis. Journal of Banking & Finance, 106, 568–591. https://doi.org/10.1016/j.jbankfin.2019.06.010
Tunger, D., & Eulerich, M. (2018). Bibliometric analysis of corporate governance research in Germanspeaking countries: Applying bibliometrics to business research using a custom-made database. Scientometrics, 117(3), 2041–2059. https://doi.org/10.1007/s11192-018-2919-z
Tandon, A., Kaur, P., Mäntymäki, M., & Dhir, A. (2021). Blockchain applications in management: A bibliometric analysis and literature review. Technological Forecasting and Social Change, 166, 120649. https://doi.org/10.1016/j.techfore.2021.120649
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), 95–126. https://doi.org/10.1016/0167-2789(92)90103-T
Wang, X. X., Xu, Z. S., Su, S. F., & Zhou, W. (2021). A comprehensive bibliometric analysis of uncertain group decision making from 1980 to 2019. Information Sciences, 547, 328–353. https://doi.org/10.1016/j.ins.2020.08.036
Wen, F., Zhang, M., Deng, M., Zhao, Y., & Ouyang, J. (2019). Exploring the dynamic effects of financial factors on oil prices based on a TVP-VAR model. Physica A: Statistical Mechanics and its Applications, 532, 121881. https://doi.org/10.1016/j.physa.2019.121881
Yu, D. J., Xu, Z. S., & Saparauskas, J. (2019). The evolution of “Technological and Economic Development of Economy”: A bibliometric analysis. Technological and Economic Development of Economy, 25(3), 369–385. https://doi.org/10.3846/tede.2019.10193
Yamani, E. (2019). Diversification role of currency momentum for carry trade: Evidence from financial crises. Journal of Multinational Financial Management, 49, 1–19. https://doi.org/10.1016/j.mulfin.2019.02.004
Yan, C., & Huang, K. X. D. (2020). Financial cycle and business cycle: An empirical analysis based on the data from the U.S. Economic Modelling, 93, 693–701. https://doi.org/10.1016/j.econmod.2020.01.018
Yépez, C. A. (2018). Financial intermediation and real estate prices impact on business cycles: A Bayesian analysis. The North American Journal of Economics and Finance, 45, 138–160. https://doi.org/10.1016/j.najef.2018.02.006
Zouri, S. (2020). Business cycles, bilateral trade and financial integration: Evidence from economic community of West African states (ECOWAS). International Economics, 163, 25–43. https://doi.org/10.1016/j.inteco.2020.04.001