Meta-analysis of macroeconomic variables on the Capital market with emphasis on the role of the government

Document Type : Research Paper

Authors

1 Ph.D. Student, Department of Accounting, Allameh Tabataba’i University, Tehran, Iran

2 Associate Professor, Department of Accounting, Allameh Tabatabae'i University, Tehran, Iran

3 3. Assistant Professor, Department of Finance and Banking, Allameh Tabataba’i University,

Abstract

The performance of the Capital market is affected by various variables, including macroeconomic variables, and the relationship between macroeconomic variables and the capital market has always been an interesting topic for both researchers and investors, which has led to a large number of research in this field. Despite the extensive research conducted in this regard, there is no complete consensus on the most important variables affecting the Capital market and the role of the government in this regard, and the results presented in different studies are different and sometimes contradictory.
in order to extract a set of variables and integrate them in this study, with a different approach and based on the meta-analysis method using comprehensive software (CMA2), the most important economic variables affecting the Capital market and determining the variables that are most affected by government decisions have been studied, considering the existing literature in this field. For this purpose, based on the search protocol and article selection index, the results of statistical analysis of 61 studies in this field were used.
The review of the selected articles led to the identification of 10 influential economic variables, of which 3 indicators are directly influenced by government decisions and the other indicators are indirectly influenced by government decisions.
Many indicators affecting the capital market, such as interest rates, are directly dependent on government decisions, which itself indicates the importance of the government's role in this market.

Keywords

Main Subjects


Abu-Mostafa, Yaser S; and Amir F. Atiya. (1996). Introduction to financial forecasting. Applied Intelligence 6: 205-13. analysis. Studies in Business and Economics, Vol. 12 No. 1, pp. 61-78.
 doi: 10.1515/sbe-2017-0005.
Andrews, I; & Kasy, & M. (2019). Identification of and correction for publication bias. American Economic Review, 109(8), 2766–2794.
Asprem, M. (1989). “Stock prices, asset portfolios and macroeconomic variables in ten European countries”. Journal of Banking and Finance, Vol. 13Nos 4-5, pp. 589-612.
 doi: 0378-4266/10.1016(89).90032-0.
Asravor, R.K. and Fonu, P.D.D. (2021). “Dynamic relation between macroeconomic variable, stock market returns and stock market development in Ghana”. International Journal of Finance and Economics, Vol. 26 No. 2, pp. 2637-2646. doi: 10.1002/ijfe.1925.
Basher, S.A. and Sadorsky, P. (2006). “Oil price risk and emerging stock markets”. Global Finance Journal, Vol. 17No. 2, pp. 224-251. doi: 10.1016/j.gfj.2006.04.001.
Bhuiyan, E.M. and Chowdhury, M. (2020). “Macroeconomic variables and stock market indices: asymmetric dynamics in the US and Canada”. Quarterly Review of Economics and Finance, oard of Trustees of the University of Illinois, Vol. 77, pp. 62-74. doi: 10.1016/j.qref.2019.10.005.
Bilson, C. M; Brailsford, T. J; & Hooper, V. J. (2001). Selecting macroeconomic variables as explanatory factors of emerging stock market returns. Pacific-Basin Finance Journal, 401, (4)9-426.
doi: 10.1016/S5380927X(01)00020-8.
Bodie, Zvi. (1976). Common stocks as a hedge against inflation. The Journal of Finance 31: 459-70. [CrossRef]
Boyd, John H; Jian Hu, and Ravi Jagannathan (2005). The Stock Market’s Reaction to Unemployment News: Why Bad News is Usually Good for Stocks. The Journal of Finance 60: 649-72.
Brodeur, A; Carrell, S; Figlio, D; & Lusher, L. (2023). Unpacking p-hacking and publication bias. American Economic Review, forthcoming.
Brown, A. L; Imai, T; Vieider, F. M; & Camerer, C. F. (2023). Meta-Analysis of empirical estimates of loss aversion. Journal of Economic Literature, forthcoming.
Chen, N.-F; Roll, R; & Ross, S. (1986). Economic forces and the stock market. The Journal of Business, 59(3), 383-403.
doi: 296344/10.1086.
Cheung, Y.-W; & Ng, L. K. (1998). International evidence on the stock market and aggregate economic activity. Journal of Empirical Finance, 5(3), 281-296.
doi: 10.1016/S0927-5398(97)00025-X.
Cohen, J. (1998). Statistical power analysis for the behavioral sciences (second edition). Hillsdale, NJ: Lawrence Erlbaum Associates.
Dahir, A.M; Mahat, F; Ab Razak, N.H. and Bany-Ariffin, A.N. (2018). “Revisiting the dynamic relationship between exchange rates and stock prices in BRICS countries: a wavelet analysis”. Borsa Istanbul Review, Elsevier, Vol. 18 No. 2, pp. 101-113. doi: 10.1016/j.bir.2017.10.001.
Darsono S.N.A.C.; Muttaqin E.I.; Rahmadani R.A.; Ha N.T.T. (2024). “Unveiling the Nexus of Consumer Price Index, Economic Policy Uncertainty, Geopolitical Risks, and Gold Prices on IndonesianSustainableStockMarketPerformance”. Econjournals. Vol. 14No. 6, pp. 128-135. doi: 10.32479/ijefi.16685.
DellaVigna, S; & Linos, E. (2022). RCTs to scale: Comprehensive evidence from two nudge units. Econometrica, 90(1), 81/116.
Dempere, Juan M. (2019). “The impact of the United Arab Emirates' macroeconomic variables on Emirati stock market indexes”. Inderscience Enterprises Ltd. Vol. 2No. 1pp. 330-335.
doi: 10.1504/IJBPM.2019.105249.
Egger M, Meta-Analysis SGD. Potentials and promise. BMJ 1997;315:1371–4.
El Khoury, R. M. (2015). Do macroeconomic factors matter for stock returns? Evidence from the European automotive industry. International Journal of Monetary Economics and Finance, 8(1), 71-84.
doi: 10.1504/IJMEF.
Elliott, G; Kudrin, N; & Wuthrich, K. (2022). Detecting p-hacking. Econometrica, 90(2), 887–906.
Errunza, Vihang, and Ked Hogan. (1998). Macroeconomic Determinants of European Stock Market Volatility. European Financial Management 4: 361-77.
Fama, Eugene F. (1981). Stock Returns, Real Activity, Inflation, and Money. The American Economic Review 71: 545-565. doi: 1331677/10.1080.X.1981.1716264.
Fama, Eugene F. (1990). Returns, Expected Returns and Real Activity. Journal of Finance 45: 1089-108.
Fama, Eugene F. (1995). Random walks in stock market prices. Financial Analysts Journal 71: 75-80.
 doi: 5252/10.1080.X.1995.1716264.
Fama, Eugene F; and G. William Schwert. (1977). Asset returns and inflation. Journal of Financial Economics 5: 115-46.
Ferson, Wayne E; and Campbell R. Harvey. (1991). The Variation of Economic Risk Premiums. Journal of Political Economy 99: 385-415.
Flannery, M; & Protopapadakis, A. (2002). Macroeconomic factors do influence aggregate stock returns. Review of Financial Studies, 15(3), 751-782.
doi: 10.1093/rfs/15.3.751.
Flannery, Mark J; and Aris A. Protopapadakis. (2002). Macroeconomic Factors DO Influence Aggregate Stock Returns. Review of Financial Studies 15: 751.82.
Giri, A.K. and Joshi, P. (2017), “The impact of macroeconomic indicators on Indian stock prices: an empirical
Glass, G.V. (1978), primary, secondary, and meta – analysis of research Educational Researcher, 5: 3-8.
Gong Y.; Bu R.; Chen Q. (2022), “What Affects the Relationship between Oil Prices and the U.S. Stock Market? A Mixed-Data Sampling CopulaApproach?”, Oxford University Press, Vol. 20 No. 2, pp. 253-277.
Hamao, Y. and Mei, J. (2001). “Living with the ‘enemy’: an analysis of foreign investment in the Japanese equity market”. Journal ofInternationalMoney and Finance, Vol. 20 No. 5, pp. 715-735.
 doi: 10.1016/S0261-5606(01)06-7.
Hamilton, James D; and Raul Susmel. (1994). Autoregressive conditional heteroskedasticity and changes in regime. Journal of Econometrics 64: 307-33.
Havranek, T; Irsova, Z; Laslopova, L; & Zeynalova, O. (2024). Publication and attenuation biases in measuring skill substitution. The Review of Economics and Statistics, forthcoming.
Higgins JP, Thomas J, Chandler J, Cumpston M, li T, et al. Cochrane handbook for systematic reviews of interventions version 6.2 (updated February 2021). Wiley; 2021. Available from:
https://www.training.cochrane.org/handbook. Accessed 30 Sept 2021
Higgins J, Thomas J, Chandler J, et al. (2023). Cochrane handbook for systematic reviews of interventions version 6.4. In: Cochrane. 2023. Available:
 https://training.cochrane.org/handbook.
Hiransha, M; E. A. Gopalakrishnan, Vijay Krishna Menon, and Soman Kp.  (2018). NSE stock market prediction using deep-learning models. Procedia Computer Science  132: 1351-62..
ong-term stock market movements? A comparison of the US and Japan. Applied Financial Economics 19: 111-19.
 doi: 8777/10.1080.X.2020.1716264.
IngrId Majerová, ToMáš Pražák (2020). The impacT of crises on The relaTionship beTween sTock market development and macroeconomic variables: evidence from hong kong and Singapore. Forum Scientiae Oeconomia. Volume 8. No. 4.
 doi: 1331677/10.1080.X.2020.1716264.
Irsova, Z; Doucouliagos, H; Havranek, T; & Stanley, T. (2023). “Meta-analysis of social science research: A practitioner’s guide”. Journal of Economic Surveys published by John Wiley & Sons Ltd. J Econ Surv. 2024; 38: 1547–1566.
 doi: 1331677/10.1080.X.2020.1716264.
Jain, A. and Biswal, P.C. (2016). “Dynamic linkages among oil price, gold price, exchange rate, and stock market in India”, Resources Policy, Elsevier, Vol. 49, pp. 179-185.
 doi: 10.1016/j.resourpol.2016.06.001.
Liow, K.H; Ibrahim, M.F. and Huang, Q. (2006). “Macroeconomic risk influences on the property stock
Mahedi Masuduzzaman. (2012). Impact of the Macroeconomic Variables onthe Stock Market Returns: The Case of Germany and the United Kingdom. Global Journal of Management and Business Research 12: 23-34.
doi: 1331677/10.1080.X.2012.1716264.
McQueen, Grant, and V. Vance Roley. (1993). Stock Prices, News, and Business Conditions. Review of Financial Studies 6: 683-707.
Megaravalli, A.V. and Sampagnaro, G. (2018). “Macroeconomic indicators and their impact on stock markets in ASIAN 3: a pooled mean group approach”. Cogent Economics and Finance, Cogent, Vol. 6 No. 1, pp. 1-14.
doi: .23322039.2017.1432450/10.1080.
Modigliani, Franco, and Richard A. Cohn. (1979). Inflation, Rational Valuation and the Market. Financial Analysts Journal 35: 24-44.
Mukherjee, T.K. and Naka, A. (1995). “Dynamic relations between macroeconomic variables and the Japanese stock market: an application of a vector error correction model”. Journal of Financial Research, Vol. 18 No. 2,
pp. 223-237.
doi: 10.1111/j.1475-6803.1995.tb00563.x.
Nasseh, A. and Strauss, J. (2000). “Stock prices and domestic and international macroeconomic activity: a cointegration approach”. The Quarterly Review of Economics and Finance, Vol. 40No. 2,
pp. 229-245.
doi: 10.1016/s1062-9769(99)00054-x.
Ouchchikh R.; Belghouat K.; Ait Bari A. (2025). “A wavelet analysis of monetary policy transmission channels in Morocco”. African Journal of Economic and Management Studies.
Pearce, Douglas K; and V. Vance Roley. (1983). The Reaction of Stock Prices to Unanticipated Changes in Money: A Note. The Journal of Finance 38: 33-1323.
doi: 985677/10.1080.X.1999.1716264.
Pearce, Douglas K; and V. Vance Roley. (1985). Stock Prices and Economic News. Journal of Business 58:49-67.
 doi: 1331677/10.1080.X.2020.1716264.
Rapach, David E; Mark E. Wohar, and Jesper Rangvid. (2005). Macro variables and international stock return predictability. International Journal of Forecasting 21: 137-66.
doi: 8977/10.1080.X.2005.1716264.
Ratanapakorn, Orawan, and Subhash C. Sharma. (2007). Dynamic analysis between the US stock returns and the macroeconomic variables. Applied Financial Economics 17: 369-77. doi: 3561677/10.1080.X.2007.1711764.
Sanusi K.A.; Kapingura F.M. (2022). “On the relationship between oil price, exchange rate and stock market performance in South Africa: Further evidence from time-varying and regime switching approaches”. Cogent OA, Vol. 10, No.1.
 doi: 23322039.2022.2106629/10.1080.
Sarika Keswani, Veerma Puri & Rimjhim Jha (2024). Relationship among macroeconomic factors and stock prices: cointegration approach from the Indian stock market, Cogent Economics & Finance, 12:1, 2355017.
 doi: 23322039.20242355017/10.1080.
Singh, G. (2016). “The impact of macroeconomic fundamentals on stock prices revised: a study of Indian stock market”. Journal of International Economics, Vol. 7 No. 1, pp. 76-91.
Sterne JAC, Egger M, Smith GD. (2001). Systematic reviews in health care: Investigating and dealing with publication and other biases in meta-analysis. BMJ; 323:101–5.
doi: 231877/10.1080.X.2000.1716264.
Uwubanmwen, A. and Eghosa, I.L. (2015), “Inflation rate and stock returns: evidence from the Nigerian stock market”, Inflation Rate and Stock Returns: Evidence from the Nigerian Stock Market, Vol.6, No. 11, pp. 155-167.
Wang, R. and Li, L. (2020). “Dynamic relationship between the stock market and macroeconomy in China (1995-2018): new evidence from the continuous wavelet analysis”, Economic Research-Ekonomska Istrazivanja, Routledge, Vol. 33No. 1, pp. 521-539.
 doi: 1331677/10.1080.X.2020.1716264.
Zhong, Xiao, and David Enke. (2017). Forecasting daily stock market return using dimensionality reduction. Expert Systems with Applications 67: 126-39.
doi: 1315477/10.1080.X.2020.1716264.