A systematic literature review on business cycle approaches: Measurement, nature, duration

Authors

DOI:

https://doi.org/10.24136/oc.2023.028

Keywords:

business cycle, business cycle approach, business cycle model, business cycle measurement, literature review

Abstract

Research background: The business cycle (BC) approaches have found extensive use in economic analysis and forecasting. Especially in the last 40 years, various modern BC models have been proposed and have experienced rapid development. However, there are no recent studies that provide a systematic review of the publications on this topic.

Purpose of the article: This paper aims to comprehensively review publications of BC approaches based on the cause, nature and methods of measurement BC, with the goal of identifying the current research states, research gaps and future trends of BC approaches.

Methods: A systematic literature review of BC approaches is conducted by qualitatively introducing the cause and the nature of BCs and quantitatively analyzing the methods of measurement BCs.  We selected 206 articles related to BC approaches from the WoS Core Collection and Google Scholar database, spanning the years 1946 to 2022, for comprehensive statistical and content analysis. The statistical analysis presents the distribution of publication years, the most popular journals and the highly cited publications. The content analysis classifies the selected publications into 6 categories based on methods of measurement BCs, and the theory, technique and applications of each category are analyzed in detail.

Findings & value added: The analysis results indicate that BC approaches have progressively evolved in sophistication and have found widespread application in decomposing trends within economic time series, quantifying the nature of business cycles, and elucidating the causes and transmission mechanisms underlying them. This review paper provides current states, research challenges and future directions in effectively employing BC approaches for empirical study.

Downloads

Download data is not yet available.

References

Ameer, R. (2014). Financial constraints and corporate investment in Asian countries. Journal of Asian Economics, 33, 44–55.

DOI: https://doi.org/10.1016/j.asieco.2014.05.004
View in Google Scholar

An, S., & Schorfheide, F. (2007). Bayesian analysis of DSGE models. Econometric Reviews, 26(2-4), 113–172.

DOI: https://doi.org/10.1080/07474930701220071
View in Google Scholar

Artis, M., Krolzig, H. M., & Toro, J. (2004). The European business cycle. Oxford Economic Papers-New Series, 56(1), 1–44.

DOI: https://doi.org/10.1093/oep/56.1.1
View in Google Scholar

Artis, M., & Okubo, T. (2011). The intranational business cycle in Japan. Oxford Economic Papers-New Series, 63(1), 111–133.

DOI: https://doi.org/10.1093/oep/gpq022
View in Google Scholar

Backus, D. K., Kehoe, P. J., & Kydland, F. E. (1992). International real business cycles. Journal of Political Economy, 100(4), 745–775.

DOI: https://doi.org/10.1086/261838
View in Google Scholar

Baxter, M., & King, R. G. (1999). Measuring business cycles: Approximate band-pass filters for economic time series. Review of Economics and Statistics, 81(4), 575–593.

DOI: https://doi.org/10.1162/003465399558454
View in Google Scholar

Ben, A. N. (2009). Analysis of shocks affecting Europe: EMU and some Central and Eastern acceding countries. Panoeconomicus, 56(1), 21–38.

DOI: https://doi.org/10.2298/PAN0901021B
View in Google Scholar

Berger, T., & Wortmann, M. (2022). Global vs. group-specific business cycles: The importance of defining the groups. Macroeconomic Dynamics, 26(1), 49–71.

DOI: https://doi.org/10.1017/S1365100520000048
View in Google Scholar

Bernard, H., & Gerlach, S. (1998). Does the term structure predict recessions? The international evidence. International Journal of Finance & Economics, 3(3), 195–215.

DOI: https://doi.org/10.1002/(SICI)1099-1158(199807)3:3<195::AID-IJFE81>3.0.CO;2-M
View in Google Scholar

Beveridge, S., & Nelson, C. R. (1981). A new approach to decomposition of economic time-series into permanent and transitory components with particular attention to measurement of the business-cycle. Journal of Monetary Economics, 7(2), 151–174.

DOI: https://doi.org/10.1016/0304-3932(81)90040-4
View in Google Scholar

Blanchard, O. J., & Quah, D. (1989). The dynamic effects of aggregate demand and supply disturbances. American Economic Review, 79(4), 655–673.

DOI: https://doi.org/10.3386/w2737
View in Google Scholar

Bloom, N., Floetotto, M., Jaimovich, N., Saporta-Eksten, I., & Terry, S. J. (2018). Really uncertain business cycles. Econometrica, 86(3), 1031–1065.

DOI: https://doi.org/10.3982/ECTA10927
View in Google Scholar

Boldin, M. D. (1994). Dating turning-points in the business-cycle. Journal of Business, 67(1), 97–131.

DOI: https://doi.org/10.1086/296625
View in Google Scholar

Born, B., & Pfeifer, J. (2014). Policy risk and the business cycle. Journal of Monetary Economics, 68, 68–85.

DOI: https://doi.org/10.1016/j.jmoneco.2014.07.012
View in Google Scholar

Buckle, R. A., Kim, K., Kirkham, H., McLellan, N., & Sharma, J. (2007). A structural var business cycle model for a volatile small open economy. Economic Modelling, 24(6), 990–1017.

DOI: https://doi.org/10.1016/j.econmod.2007.04.003
View in Google Scholar

Burns, A. F., & Mitchell, W. C. (1946). Measuring business cycles: National Bureau of economic research.
View in Google Scholar

Camacho, M. (2004). Vector smooth transition regression models for us GDP and the composite index of leading indicators. Journal of Forecasting, 23(3), 173–196.

DOI: https://doi.org/10.1002/for.912
View in Google Scholar

Camacho, M., & Domenech, R. (2012). Mica-bbva: A factor model of economic and financial indicators for short-term GDP forecasting. Series-Journal of the Spanish Economic Association, 3(4), 475–497.

DOI: https://doi.org/10.1007/s13209-011-0078-z
View in Google Scholar

Camacho, M., Perez-Quiros, G., & Poncela, P. (2018). Markov-switching dynamic factor models in real time. International Journal of Forecasting, 34(4), 598–611.

DOI: https://doi.org/10.1016/j.ijforecast.2018.05.002
View in Google Scholar

Canova, F. (1998). Detrending and business cycle facts. Journal of Monetary Economics, 41(3), 475–512.

DOI: https://doi.org/10.1016/S0304-3932(98)00006-3
View in Google Scholar

Canova, F., Ciccarelli, M., & Ortega, E. (2007). Similarities and convergence in g-7 cycles. Journal of Monetary Economics, 54(3), 850–878.

DOI: https://doi.org/10.1016/j.jmoneco.2005.10.022
View in Google Scholar

Caraiani, P. (2012). Stylized facts of business cycles in a transition economy in time and frequency. Economic Modelling, 29(6), 2163–2173.

DOI: https://doi.org/10.1016/j.econmod.2012.06.014
View in Google Scholar

Caraiani, P. (2013). Using complex networks to characterize international business cycles. Plos One, 8(3), e58109.

DOI: https://doi.org/10.1371/journal.pone.0058109
View in Google Scholar

Castro, V. (2013). The duration of business cycle expansions and contractions: Are there change-points in duration dependence? Empirical Economics, 44(2), 511–544.

DOI: https://doi.org/10.1007/s00181-011-0544-2
View in Google Scholar

Chari, V. V., Kehoe, P. J., & McGrattan, E. R. (2007). Business cycle accounting. Econometrica, 75(3), 781–836.

DOI: https://doi.org/10.1111/j.1468-0262.2007.00768.x
View in Google Scholar

Chauvet, M. (1998). An econometric characterization of business cycle dynamics with factor structure and regime switching. International Economic Review, 39(4), 969–996.

DOI: https://doi.org/10.2307/2527348
View in Google Scholar

Chauvet, M., & Piger, J. (2008). A comparison of the real-time performance of business cycle dating methods. Journal of Business & Economic Statistics, 26(1), 42–49.

DOI: https://doi.org/10.1198/073500107000000296
View in Google Scholar

Chauvet, M., & Senyuz, Z. (2016). A dynamic factor model of the yield curve components as a predictor of the economy. International Journal of Forecasting, 32(2), 324–343.

DOI: https://doi.org/10.1016/j.ijforecast.2015.05.007
View in Google Scholar

Christensen, I., & Dib, A. (2008). The financial accelerator in an estimated new Keynesian model. Review of Economic Dynamics, 11(1), 155–178.

DOI: https://doi.org/10.1016/j.red.2007.04.006
View in Google Scholar

Christiano, L. J., Eichenbaum, M., & Evans, C. L. (2005). Nominal rigidities and the dynamic effects of a shock to monetary policy. Journal of Political Economy, 113(1), 1–45.

DOI: https://doi.org/10.1086/426038
View in Google Scholar

Christiano, L. J., & Fitzgerald, T. J. (2003). The band pass filter. International Economic Review, 44(2), 435–465.

DOI: https://doi.org/10.1111/1468-2354.t01-1-00076
View in Google Scholar

Christiano, L. J., Motto, R., & Rostagno, M. (2014). Risk shocks. American Economic Review, 104(1), 27–65.

DOI: https://doi.org/10.1257/aer.104.1.27
View in Google Scholar

Clements, M. P., & Krolzig, H. M. (2003). Business cycle asymmetries: Characterization and testing based on Markov-switching autoregressions. Journal of Business & Economic Statistics, 21(1), 196–211.

DOI: https://doi.org/10.1198/073500102288618892
View in Google Scholar

Cologni, A., & Manera, M. (2008). Oil prices, inflation and interest rates in a structural cointegrated var model for the G-7 countries. Energy Economics, 30(3), 856–888.

DOI: https://doi.org/10.1016/j.eneco.2006.11.001
View in Google Scholar

Cologni, A., & Manera, M. (2009). The asymmetric effects of oil shocks on output growth: A Markov-switching analysis for the G-7 countries. Economic Modelling, 26(1), 1–29.

DOI: https://doi.org/10.1016/j.econmod.2008.05.006
View in Google Scholar

Cooley, T. F., & Dwyer, M. (1998). Business cycle analysis without much theory - A look at structural vars. Journal of Econometrics, 83(1-2), 57–88.

DOI: https://doi.org/10.1016/S0304-4076(97)00065-1
View in Google Scholar

Costa, L., Guedes de Oliveira, F., Leitão, A., & Paredes, J. (2020). Business cycles and trends in Germany and Portugal: Macroeconomic policy implications in the euro area. European Planning Studies, 29(4), 654–680.

DOI: https://doi.org/10.1080/09654313.2020.1766424
View in Google Scholar

Crucini, M. J., Kose, M. A., & Otrok, C. (2011). What are the driving forces of international business cycles? Review of Economic Dynamics, 14(1), 156–175.

DOI: https://doi.org/10.1016/j.red.2010.09.001
View in Google Scholar

Davig, T., & Hall, A. S. (2019). Recession forecasting using Bayesian classification. International Journal of Forecasting, 35(3), 848–867.

DOI: https://doi.org/10.1016/j.ijforecast.2018.08.005
View in Google Scholar

Dees, S., Di Mauro, F., Pesaran, M. H., & Smith, L. V. (2007). Exploring the international linkages of the euro area: A global var analysis. Journal of Applied Econometrics, 22(1), 1–38.

DOI: https://doi.org/10.1002/jae.932
View in Google Scholar

Diebold, F. X., & Rudebusch, G. D. (1996). Measuring business cycles: A modern perspective. Review of Economics and Statistics, 78(1), 67–77.

DOI: https://doi.org/10.2307/2109848
View in Google Scholar

Drake, L., & Mills, T. C. (2010). Trends and cycles in euro area real GDP. Applied Economics, 42(11), 1397–1401.

DOI: https://doi.org/10.1080/00036840701721372
View in Google Scholar

Eo, Y., & Kim, C. J. (2016). Markov-switching models with evolving regime-specific parameters: Are postwar booms or recessions all alike? Review of Economics and Statistics, 98(5), 940–949.

DOI: https://doi.org/10.1162/REST_a_00561
View in Google Scholar

Estrella, A., & Mishkin, F. S. (1998). Predicting us recessions: Financial variables as leading indicators. Review of Economics and Statistics, 80(1), 45–61.

DOI: https://doi.org/10.1162/003465398557320
View in Google Scholar

Filardo, A. J. (1994). Business-cycle phases and their transitional dynamics. Journal of Business & Economic Statistics, 12(3), 299–308.

DOI: https://doi.org/10.1080/07350015.1994.10524545
View in Google Scholar

Fiorito, R., & Kollintzas, T. (1994). Stylized facts of business cycles in the G7 from a real business cycles perspective. European Economic Review, 38(2), 235–269.

DOI: https://doi.org/10.1016/0014-2921(94)90057-4
View in Google Scholar

Forinirni, M., Gambetti, L., Lippi, M., & Sala, L. (2017). Noisy news in business cycles. American Economic Journal-Macroeconomics, 9(4), 122–152.

DOI: https://doi.org/10.1257/mac.20150359
View in Google Scholar

Forni, M., Gambetti, L., & Sala, L. (2014). No news in business cycles. Economic Journal, 124(581), 1168–1191.

DOI: https://doi.org/10.1111/ecoj.12111
View in Google Scholar

Forni, M., & Lippi, M. (2001). The generalized dynamic factor model: Representation theory. Econometric Theory, 17(6), 1113–1141.

DOI: https://doi.org/10.1017/S0266466601176048
View in Google Scholar

Friedman, M., & Schwartz, A. J. (2008). A monetary history of the United States, 1867-1960 (Vol. 16): Princeton University Press.

DOI: https://doi.org/10.1515/9781400829330
View in Google Scholar

Gadea, M. D., Gomez-Loscos, A., & Montanes, A. (2012). Cycles inside cycles: Spanish regional aggregation. Series-Journal of the Spanish Economic Association, 3(4), 423–456.

DOI: https://doi.org/10.1007/s13209-011-0068-1
View in Google Scholar

Goldfeld, S. M., & Quandt, R. E. (1973). A Markov model for switching regressions. Journal of Econometrics, 1(1), 3–15.

DOI: https://doi.org/10.1016/0304-4076(73)90002-X
View in Google Scholar

Goodwin, T. H. (1993). Business-cycle analysis with a markov-switching model. Journal of Business & Economic Statistics, 11(3), 331–339. doi: 10.2307/1391958.

DOI: https://doi.org/10.1080/07350015.1993.10509961
View in Google Scholar

Gossel, S. J., & Biekpe, N. (2012). South Africa's post-liberalised capital flows and business cycle fluctuations. South African Journal of Economics, 80(4), 510–525.

DOI: https://doi.org/10.1111/j.1813-6982.2012.01331.x
View in Google Scholar

Gregory, A. W., Head, A. C., & Raynauld, J. (1997). Measuring world business cycles. International Economic Review, 38(3), 677–701.

DOI: https://doi.org/10.2307/2527287
View in Google Scholar

Guerin, P., & Marcellino, M. (2013). Markov-switching midas models. Journal of Business & Economic Statistics, 31(1), 45–56.

DOI: https://doi.org/10.1080/07350015.2012.727721
View in Google Scholar

Hamilton, J. D. (1989). A new approach to the economic-analysis of nonstationary time-series and the business-cycle. Econometrica, 57(2), 357–384.

DOI: https://doi.org/10.2307/1912559
View in Google Scholar

Hamilton, J. D. (2018). Why you should never use the Hodrick-Prescott filter. Review of Economics and Statistics, 100(5), 831–843.

DOI: https://doi.org/10.1162/rest_a_00706
View in Google Scholar

Hamilton, J. D., & Susmel, R. (1994). Autoregressive conditional heteroskedasticity and changes in regime. Journal of Econometrics, 64(1-2), 307–333.

DOI: https://doi.org/10.1016/0304-4076(94)90067-1
View in Google Scholar

Hao, L. L., & Ng, E. C. Y. (2011). Predicting Canadian recessions using dynamic probit modelling approaches. Canadian Journal of Economics-Revue Canadienne D Economique, 44(4), 1297–1330.

DOI: https://doi.org/10.1111/j.1540-5982.2011.01675.x
View in Google Scholar

Harding, D., & Pagan, A. (2002). Dissecting the cycle: A methodological investigation. Journal of Monetary Economics, 49(2), 365–381.

DOI: https://doi.org/10.1016/S0304-3932(01)00108-8
View in Google Scholar

Harvey, A. C. (1985). Trends and cycles in macroeconomic time-series. Journal of Business & Economic Statistics, 3(3), 216–227.

DOI: https://doi.org/10.1080/07350015.1985.10509453
View in Google Scholar

He, D., & Liao, W. (2012). Asian business cycle synchronization. Pacific Economic Review, 17(1), 106–135.

DOI: https://doi.org/10.1111/j.1468-0106.2011.00574.x
View in Google Scholar

He, Q., Chong, T. T. L., & Shi, K. (2009). What accounts for Chinese business cycle? China Economic Review, 20(4), 650–661.

DOI: https://doi.org/10.1016/j.chieco.2009.05.008
View in Google Scholar

Hodrick, R. J., & Prescott, E. C. (1997). Postwar us business cycles: An empirical investigation. Journal of Money Credit and Banking, 29(1), 1–16.

DOI: https://doi.org/10.2307/2953682
View in Google Scholar

Iacobucci, A., & Noullez, A. (2005). A frequency selective filter for short-length time series. Computational Economics, 25(1-2), 75–102.

DOI: https://doi.org/10.1007/s10614-005-6276-7
View in Google Scholar

Ince, O., & Papell, D. H. (2013). The (un)reliability of real-time output gap estimates with revised data. Economic Modelling, 33, 713–721.

DOI: https://doi.org/10.1016/j.econmod.2013.05.023
View in Google Scholar

Jakimowicz, A., & Rzeczkowski, D. (2019). Firm ownership and size versus innovation activities over the business cycle: Near-zero inertia as a sign of the transition from the fifth to the sixth Kondratieff wave. Oeconomia Copernicana, 10(4), 689–741.

DOI: https://doi.org/10.24136/oc.2019.033
View in Google Scholar

Jiang, D., & Weder, M. (2021). American business cycles 1889–1913: An accounting approach. Journal of Macroeconomics, 67, 103285.

DOI: https://doi.org/10.1016/j.jmacro.2020.103285
View in Google Scholar

Justiniano, A., Primiceri, G. E., & Tambalotti, A. (2010). Investment shocks and business cycles. Journal of Monetary Economics, 57(2), 132–145.

DOI: https://doi.org/10.1016/j.jmoneco.2009.12.008
View in Google Scholar

Kabundi, A., & Loots, E. (2007). Co-movement between South Africa and the southern African development community: An empirical analysis. Economic Modelling, 24(5), 737–748.

DOI: https://doi.org/10.1016/j.econmod.2007.02.001
View in Google Scholar

Kauppi, H., & Saikkonen, P. (2008). Predicting U.S recessions with dynamic binary response models. Review of Economics and Statistics, 90(4), 777–791.

DOI: https://doi.org/10.1162/rest.90.4.777
View in Google Scholar

Kehoe, P. J., Midrigan, V., & Pastorino, E. (2018). Evolution of modern business cycle models: Accounting for the great recession. Journal of Economic Perspectives, 32(3), 141–166.

DOI: https://doi.org/10.1257/jep.32.3.141
View in Google Scholar

Keynes, J. M. (1937). The general theory of employment. Quarterly Journal of Economics, 51, 209–223.

DOI: https://doi.org/10.2307/1882087
View in Google Scholar

Kim, C. J. (1994). Dynamic linear-models with markov-switching. Journal of Econometrics, 60(1-2), 1–22.

DOI: https://doi.org/10.1016/0304-4076(94)90036-1
View in Google Scholar

Kim, C. J., & Nelson, C. R. (1998). Business cycle turning points, a new coincident index, and tests of duration dependence based on a dynamic factor model with regime switching. Review of Economics and Statistics, 80(2), 188–201.

DOI: https://doi.org/10.1162/003465398557447
View in Google Scholar

Kim, C. J., & Nelson, C. R. (1999). Has the us economy become more stable? A Bayesian approach based on a markov-switching model of the business cycle. Review of Economics and Statistics, 81(4), 608–616.

DOI: https://doi.org/10.1162/003465399558472
View in Google Scholar

Kim, I. M., & Loungani, P. (1992). The role of energy in real business-cycle models. Journal of Monetary Economics, 29(2), 173–189.

DOI: https://doi.org/10.1016/0304-3932(92)90011-P
View in Google Scholar

King, R. G., Plosser, C. I., & Rebelo, S. T. (1988). Production, growth, and business cycles: I. The basic neoclassical model. Journal of Monetary Economics, 21(2-3), 195–232.

DOI: https://doi.org/10.1016/0304-3932(88)90030-X
View in Google Scholar

King, R. G., & Rebelo, S. T. (1993). Low-frequency filtering and real business cycles. Journal of Economic Dynamics & Control, 17(1-2), 207–231.

DOI: https://doi.org/10.1016/S0165-1889(06)80010-2
View in Google Scholar

Klarl, T. (2020). The response of CO2 emissions to the business cycle: New evidence for the us. Energy Economics, 85, 104560.

DOI: https://doi.org/10.1016/j.eneco.2019.104560
View in Google Scholar

Kobayashi, K., & Inaba, M. (2006). Business cycle accounting for the Japanese economy. Japan and the World Economy, 18(4), 418–440.

DOI: https://doi.org/10.1016/j.japwor.2006.04.003
View in Google Scholar

Konstantakopoulou, I., & Tsionas, E. G. (2014). Half a century of empirical evidence of business cycles in OECD countries. Journal of Policy Modeling, 36(2), 389–409.

DOI: https://doi.org/10.1016/j.jpolmod.2014.01.006
View in Google Scholar

Koopmans, T. C. (1947). Measurement without theory. Review of Economic Statistics, 29(3), 161–172.

DOI: https://doi.org/10.2307/1928627
View in Google Scholar

Korobilis, D., & Pettenuzzo, D. (2019). Adaptive, hierarchical priors for high-dimensional vector autoregressions. Journal of Econometrics, 212(1), 241–271.

DOI: https://doi.org/10.1016/j.jeconom.2019.04.029
View in Google Scholar

Kydland, F. E., & Prescott, E. C. (1982). Time to build and aggregate fluctuations. Econometrica, 50(6), 1345–1370.

DOI: https://doi.org/10.2307/1913386
View in Google Scholar

Kydland, F. E., & Prescott, E. C. (1990). Business cycles: Real facts and a monetary myth. Federal Reserve Bank of Minneapolis Quarterly Review, 14(2), 3–18. doi: 10.21034/qr.1421.

DOI: https://doi.org/10.21034/qr.1421
View in Google Scholar

Lam, P. S. (1990). The Hamilton model with a general autoregressive component - estimation and comparison with other models of economic time-series. Journal of Monetary Economics, 26(3), 409–432.

DOI: https://doi.org/10.1016/0304-3932(90)90005-O
View in Google Scholar

Leiva-Leon, D. (2017). Measuring business cycles intra-synchronization in us: A regime-switching interdependence framework. Oxford Bulletin of Economics and Statistics, 79(4), 513–545.

DOI: https://doi.org/10.1111/obes.12157
View in Google Scholar

Liberati, A., Altman, D. G., Tetzlaff, J., Mulrow, C., Gotzsche, P. C., Ioannidis, J. P. A., Clarke, M., Devereaux,P. J., Kleijnen, J., & Moher, D. (2009). The Prisma statement for reporting systematic reviews and meta-analyses of studies that evaluate health care interventions: Explanation and elaboration. Plos Medicine, 6(7), e1000100. doi: 10.1371/journal.pmed.1000100.

DOI: https://doi.org/10.1371/journal.pmed.1000100
View in Google Scholar

Long, J. B., & Plosser, C. I. (1983). Real business cycles. Journal of Political Economy, 91(1), 39–69.

DOI: https://doi.org/10.1086/261128
View in Google Scholar

Lucas, J., & Robert, E. (1972). Expectations and the neutrality of money. Journal of Economic Theory, 4(2), 103–124. doi: 10.1016/0022-0531(72)90142-1.

DOI: https://doi.org/10.1016/0022-0531(72)90142-1
View in Google Scholar

Lucas, R. E. (1977). Understanding business cycles. Carnegie-Rochester Conference Series on Public Policy, 5, 7–29.

DOI: https://doi.org/10.1016/0167-2231(77)90002-1
View in Google Scholar

Lv, S., Xu, Z., Fan, X., Qin, Y., & Skare, M. (2023). The mean reversion/persistence of financial cycles: Empirical evidence for 24 countries worldwide. Equilibrium. Quarterly Journal of Economics and Economic Policy, 18(1), 11–47.

DOI: https://doi.org/10.24136/eq.2023.001
View in Google Scholar

Massmann, M., Mitchell, J., & Weale, M. (2003). Business cycles and turning points: A survey of statistical techniques. National Institute Economic Review, 183, 90–106.

DOI: https://doi.org/10.1177/0027950103183001465
View in Google Scholar

Merola, R. (2015). The role of financial frictions during the crisis: An estimated dsge model. Economic Modelling, 48, 70–82.

DOI: https://doi.org/10.1016/j.econmod.2014.10.037
View in Google Scholar

Morley, J., & Piger, J. (2012). The asymmetric business cycle. Review of Economics and Statistics, 94(1), 208–221.

DOI: https://doi.org/10.1162/REST_a_00169
View in Google Scholar

Murray, C. J. (2003). Cyclical properties of Baxter-king filtered time. Review of Economics and Statistics, 85(2), 472–476.

DOI: https://doi.org/10.1162/003465303765299945
View in Google Scholar

Neumeyer, P. A., & Perri, F. (2005). Business cycles in emerging economies: The role of interest rates. Journal of Monetary Economics, 52(2), 345–380.

DOI: https://doi.org/10.1016/j.jmoneco.2004.04.011
View in Google Scholar

Nyberg, H. (2018). Forecasting us interest rates and business cycle with a nonlinear regime switching var model. Journal of Forecasting, 37(1), 1–15.

DOI: https://doi.org/10.1002/for.2458
View in Google Scholar

Ocal, N., & Osborn, D. R. (2000). Business cycle non-linearities in uk consumption and production. Journal of Applied Econometrics, 15(1), 27–43.

DOI: https://doi.org/10.1002/(SICI)1099-1255(200001/02)15:1<27::AID-JAE552>3.0.CO;2-F
View in Google Scholar

Owyang, M. T., Piger, J., & Wall, H. J. (2005). Business cycle phases in us states. Review of Economics and Statistics, 87(4), 604–616.

DOI: https://doi.org/10.1162/003465305775098198
View in Google Scholar

Owyang, M. T., Rapach, D. E., & Wall, H. J. (2009). States and the business cycle. Journal of Urban Economics, 65(2), 181–194.

DOI: https://doi.org/10.1016/j.jue.2008.11.001
View in Google Scholar

Padilla, A., & Quintero Otero, J. D. (2022). Regional business cycles in emerging economies: A review of the literature. International Journal of Emerging Markets. Advance online publication.

DOI: https://doi.org/10.1108/IJOEM-09-2021-1484
View in Google Scholar

Page, M. J., McKenzie, J. E., Bossuyt, P. M., Boutron, I., Hoffmann, T. C., Mulrow, C. D., Shamseer, L., Tetzlaff, J.M., Akl, E. A., Brennan, S. E., Chou, R., Glanville, J., Grimshaw, J. M., Hróbjartsson, A., Lalu, M. M. , Li, T., Loder, E. W. , Mayo-Wilson, E., McDonald, S., McGuinness, L. A. , Stewart, L. A., Thomas, J., Tricco, A. C., Welch, V. A. , Whiting, P., & Moher, D. (2021). The Prisma 2020 statement: An updated guideline for reporting systematic reviews. Int J Surg, 88, 105906.

DOI: https://doi.org/10.31222/osf.io/v7gm2
View in Google Scholar

Pandey, R., Patnaik, I., & Shah, A. (2017). Dating business cycles in India. Indian Growth and Development Review, 10(1), 32–61.

DOI: https://doi.org/10.1108/IGDR-02-2017-0013
View in Google Scholar

Pesaran, M. H., & Potter, S. M. (1997). A floor and ceiling model of us output. Journal of Economic Dynamics & Control, 21(4-5), 661–695.

DOI: https://doi.org/10.1016/S0165-1889(96)00002-4
View in Google Scholar

Pichler, P. (2011). Solving the multi-country real business cycle model using a monomial rule Galerkin method. Journal of Economic Dynamics & Control, 35(2), 240–251.

DOI: https://doi.org/10.1016/j.jedc.2010.09.009
View in Google Scholar

Proano, C. R. (2017). Detecting and predicting economic accelerations, recessions, and normal growth periods in real-time. Journal of Forecasting, 36(1), 26–42.

DOI: https://doi.org/10.1002/for.2412
View in Google Scholar

Ramajo, J., Marquez, M. A., & Hewings, G. J. D. (2017). Spatiotemporal analysis of regional systems: A multiregional spatial vector autoregressive model for Spain. International Regional Science Review, 40(1), 75–96.

DOI: https://doi.org/10.1177/0160017615571586
View in Google Scholar

Ravn, M. O., & Uhlig, H. (2002). On adjusting the Hodrick-Prescott filter for the frequency of observations. Review of Economics and Statistics, 84(2), 371–376.

DOI: https://doi.org/10.1162/003465302317411604
View in Google Scholar

Restrepo-Ochoa, S. I., & Vazquez, J. (2004). Cyclical features of the Ozawa-lucas endogenous growth model. Economic Modelling, 21(2), 285–322.

DOI: https://doi.org/10.1016/S0264-9993(03)00016-6
View in Google Scholar

Sarantis, N. (1999). Modeling non-linearities in real effective exchange rates. Journal of International Money and Finance, 18(1), 27–45.

DOI: https://doi.org/10.1016/S0261-5606(98)00045-X
View in Google Scholar

Sargent, T. J., & Sims, C. A. (1977). Business cycle modeling without pretending to have too much a priori economic theory. New methods in business cycle research, 1, 145–168.
View in Google Scholar

Schirwitz, B. (2009). A comprehensive German business cycle chronology. Empirical Economics, 37(2), 287–301.

DOI: https://doi.org/10.1007/s00181-008-0233-y
View in Google Scholar

Siliverstovs, B. (2019). Assessing nowcast accuracy of us GDP growth in real time: The role of booms and busts. Empirical Economics, 58(1), 7–27.

DOI: https://doi.org/10.1007/s00181-019-01704-6
View in Google Scholar

Simkins, S. (1995). Forecasting with vector autoregressive (var) models subject to business cycle restrictions. International Journal of Forecasting, 11(4), 569–583.

DOI: https://doi.org/10.1016/0169-2070(95)00616-8
View in Google Scholar

Simkins, S. P. (1994). Do real business-cycle models really exhibit business-cycle behavior. Journal of Monetary Economics, 33(2), 381–404.

DOI: https://doi.org/10.1016/0304-3932(94)90007-8
View in Google Scholar

Sims, C. A. (1980). Macroeconomics and reality. Econometrica, 48(1), 1–48.

DOI: https://doi.org/10.2307/1912017
View in Google Scholar

Skalin, J., & Terasvirta, T. (1999). Another look at Swedish business cycles, 1861-1988. Journal of Applied Econometrics, 14(4), 359–378.

DOI: https://doi.org/10.1002/(SICI)1099-1255(199907/08)14:4<359::AID-JAE517>3.0.CO;2-1
View in Google Scholar

Smets, F., & Wouters, R. (2003). An estimated dynamic stochastic general equilibrium model of the Euro area. Journal of the European Economic Association, 1(5), 1123–1175.

DOI: https://doi.org/10.1162/154247603770383415
View in Google Scholar

Smets, F., & Wouters, R. (2007). Shocks and frictions in us business cycles: A Bayesian DSGE approach. American Economic Review, 97(3), 586–606.

DOI: https://doi.org/10.1257/aer.97.3.586
View in Google Scholar

Solow, R. M. (1956). A contribution to the theory of economic-growth. Quarterly Journal of Economics, 70(1), 65–94.

DOI: https://doi.org/10.2307/1884513
View in Google Scholar

Stanisic, N. (2013). Convergence between the business cycles of Central and Eastern European countries and the euro area. Baltic Journal of Economics, 13(1), 63–74.

DOI: https://doi.org/10.1080/1406099X.2013.10840526
View in Google Scholar

Stock, J. H., & Watson, M. W. (1989). New indexes of coincident and leading economic indicators. NBER Macroeconomics Annual, 4, 351–394.

DOI: https://doi.org/10.1086/654119
View in Google Scholar

Terasvirta, T., & Anderson, H. M. (1992). Characterizing nonlinearities in business cycles using smooth transition autoregressive models. Journal of Applied Econometrics, 7, S119–S136.

DOI: https://doi.org/10.1002/jae.3950070509
View in Google Scholar

Tian, R., & Shen, G. (2019). Predictive power of Markovian models: Evidence from us recession forecasting. Journal of Forecasting, 38(6), 525–551.

DOI: https://doi.org/10.1002/for.2579
View in Google Scholar

Van Dijk, D., & Franses, P. H. (1999). Modeling multiple regimes in the business cycle. Macroeconomic Dynamics, 3(3), 311–340.

DOI: https://doi.org/10.1017/S136510059901202X
View in Google Scholar

Wang, X., Xu, Z., Wang, X., & Skare, M. (2022). A review of inflation from 1906 to 2022: A comprehensive analysis of inflation studies from a global perspective. Oeconomia Copernicana, 13(3), 595–631.

DOI: https://doi.org/10.24136/oc.2022.018
View in Google Scholar

Watson, M. W. (1993). Measures of fit for calibrated models. Journal of Political Economy, 101(6), 1011–1041.

DOI: https://doi.org/10.1086/261913
View in Google Scholar

Yogo, M. (2008). Measuring business cycles: A wavelet analysis of economic time series. Economics Letters, 100(2), 208–212.

DOI: https://doi.org/10.1016/j.econlet.2008.01.008
View in Google Scholar

Zhang, L. (2017). Modeling the Phillips curve in China: A nonlinear perspective. Macroeconomic Dynamics, 21(2), 439–461.

DOI: https://doi.org/10.1017/S1365100515000577
View in Google Scholar

Downloads

Published

2023-09-30

How to Cite

Pu, Z., Fan, X., Xu, Z., & Skare, M. (2023). A systematic literature review on business cycle approaches: Measurement, nature, duration. Oeconomia Copernicana, 14(3), 935–976. https://doi.org/10.24136/oc.2023.028

Issue

Section

Articles

Similar Articles

1 2 3 4 5 6 7 8 9 10 > >> 

You may also start an advanced similarity search for this article.