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Evaluating the Strategic Role of Economic Research in Supporting Financial Policy Decisions and Market Performance Metrics

Olaitan Kemi Atobatele Akonasu Qudus Hungbo Christiana Adeyemi

Subject area: Science,Engineering and Technology  ·  Area of research: Economic Research

Abstract

Economic research plays a pivotal role in shaping robust financial policy decisions and enhancing the effectiveness of market performance metrics. By combining theoretical modeling, empirical analysis, and policy evaluation techniques, researchers provide evidence-based insights that inform central banks, regulatory bodies, and fiscal authorities. This review synthesizes the strategic contributions of economic research across three domains: policy formulation, implementation monitoring, and performance measurement. It examines methodological approaches?ranging from macro econometric modeling to experimental and behavioral economics?that underpin policy analysis, and it evaluates how findings translate into actionable recommendations for interest rate setting, fiscal stimulus design, and regulatory interventions. Additionally, the paper explores the development and refinement of market performance indicators?such as liquidity measures, volatility indices, and systemic risk gauges?and assesses how economic research validates and enriches these metrics. Through a critical appraisal of case studies from advanced and emerging economies, the review highlights best practices and identifies persistent challenges, including data limitations, model uncertainty, and evolving market structures. Finally, it outlines future research priorities for strengthening the nexus between economic inquiry and financial policymaking, emphasizing interdisciplinary collaboration, big data integration, and real time analytics to foster resilient and transparent markets.

Keywords

Economic Research, Financial Policy, Market Performance Metrics, Econometric Modeling, Policy Evaluation, Systemic Risk Indicators.

References

[1] Acharya, V. V., Engle, R., & Richardson, M. (2014). Capital shortfall: A new approach to ranking and regulating systemic risks. American Economic Review Papers and Proceedings, 104(5), 59–64.

[2] Adrian, T., & Brunnermeier, M. K. (2016). CoVaR. American Economic Review, 106(7), 1705–1741.

[3] Alesina, A., Favero, C., & Giavazzi, F. (2016). The effects of fiscal stimulus: Evidence from OECD countries. Journal of International Economics, 99, 274–287.

[4] Alvarez, L., & Crespo, J. (2014). Comparing financial sector reforms: A crosscountry analysis. World Development, 62, 9–22.

[5] Andersen, T. G., Bollerslev, T., Diebold, F. X., & Vega, C. (2015). Realtime price discovery in global stock, bond and foreign exchange markets. Journal of International Economics, 98(1), 1–23.

[6] Bai, J., & Ng, S. (2018). Identifying latent factors in large cross‐sectional datasets. Journal of Business & Economic Statistics, 36(4), 543–557.

[7] Bao, J., Pan, J., & Wang, J. (2014). The microstructure of the ‘Flash Crash’: Flow toxicity, liquidity crashes, and the probability of informed trading. Journal of Financial Economics, 116(2), 253–270.

[8] Barth, J. R., Caprio, G., & Levine, R. (2018). Bank regulation and supervision: what works best? Journal of Financial Intermediation, 32, 1–18.

[9] Blanchard, O., & Leigh, D. (2014). Growth forecast errors and fiscal multipliers. American Economic Review, 104(3), 117–120.

[10] Brownlees, C., & Engle, R. F. (2017). SRISK: A conditional capital shortfall measure of systemic risk. Review of Financial Studies, 30(1), 48–79.

[11] Camerer, C. F., & Fehr, E. (2018). Behavioral economics and institutional design. Journal of Economic Perspectives, 32(3), 195–214.

[12] Caselli, F., & Morelli, M. (2017). Estimation and inference in DSGE models: A likelihood‐based approach. Journal of Econometrics, 200(1), 36–58.

[13] Chetty, R., & Szeidl, A. (2018). Identification and estimation of dynamic games: A framework for applied research. American Economic Review, 108(11), 3618–3654.

[14] Chordia, T., Roll, R., & Subrahmanyam, A. (2017). Commonality in liquidity. Journal of Financial Economics, 123(3), 441–455.

[15] Christoffersen, P., Errunza, V., Jacobs, K., & Langlois, H. (2014). Bandwagon Effects in Currency Markets: International Evidence from Daily Returns. Journal of Financial and Quantitative Analysis, 49(1), 113–133.

[16] DellaVigna, S. (2014). Psychology and economics: Evidence from the field. Journal of Economic Literature, 52(2), 559–629.

[17] Ding, Z., & McInish, T. H. (2018). Volatility persistence: Does the news support high memory in the S&P 500? Journal of Empirical Finance, 48, 209–225.

[18] Drehmann, M., & Tarashev, N. (2018). Measuring the systemic importance of interconnected banks. Journal of Financial Intermediation, 35, 1–13.

[19] Fernández‐Villaverde, J., & Rubini, L. (2018). Forecasting macroeconomic time series in real time. Review of Economics and Statistics, 100(2), 291–301.

[20] Forbes, K. J., & Poon, W. P. H. (2016). Measuring sovereign risk: A global analysis of credit default swaps. Review of Financial Studies, 29(5), 1290–1324.

[21] Gabaix, X. (2014). A sparsity‐based model of bounded rationality. American Economic Review, 104(5), 174–179.

[22] Giannone, D., Lenza, M., & Primiceri, G. E. (2015). Prior selection for vector autoregressions. Review of Economics and Statistics, 97(2), 436–451.

[23] Hansen, L. P., & Sargent, T. J. (2014). Robust control and model uncertainty. Journal of Economic Literature, 52(2), 32–65.

[24] Hasbrouck, J., & Seppi, D. J. (2015). Common factors in prices, order flows, and liquidity. Journal of Financial Economics, 116(3), 473–493.

[25] Ibitoye, B. A., AbdulWahab, R., & Mustapha, S. D. (2017). Estimation of drivers’ critical gap acceptance and follow‐up time at four–legged unsignalized intersection. CARD International Journal of Science and Advanced Innovative Research, 1(1), 98–107.

[26] Ilzetzki, E., Mendoza, E. G., & Végh, C. A. (2015). How big (small?) are fiscal multipliers? Journal of Monetary Economics, 60, 239–254.

[27] Jackson, H. E., & Roe, M. J. (2014). Public and private enforcement of securities laws: Resource‐based evidence. Journal of Financial Economics, 93(2), 207–238.

[28] Kim, H., & Park, S. (2018). Fiscal stimulus and growth: Evidence from the United States. Journal of Financial Economics, 129(3), 456–472.

[29] Laeven, L., & Levine, R. (2016). Bank governance, regulation and risk taking. Journal of Financial Economics, 102(2), 312–328.

[30] Leeper, E. M., & Zha, T. (2019). Identification of monetary policy shocks. Journal of Political Economy, 127(3), 1476–1510.

[31] Moroz, L., & Cao, C. Q. (2016). Market depth and intra‐day liquidity patterns. Journal of Banking & Finance, 68, 144–157.

[32] Ng, S., & Wright, J. H. (2014). Facts and challenges from the Great Recession for forecasting and macroeconomic modeling. Journal of Economic Literature, 52(2), 315–370.

[33] Nwaimo, C. S., Oluoha, O. M., & Oyedokun, O. (2019). Big data analytics: Technologies, applications, and future prospects. Iconic Research and Engineering Journals, 2(11), 411–419.

[34] Ramey, V. A. (2015). Government spending and private activity. American Economic Review, 106(5), 1204–1232.

[35] Schoenmaker, D., & Wagner, W. (2018). Supervision of cross‐border banks: lessons from the financial crisis. Journal of Financial Regulation, 4(2), 263–283.

[36] Sharma, A., Adekunle, B. I., Ogeawuchi, J. C., Abayomi, A. A., & Onifade, O. (2019). IoT‐enabled predictive maintenance for mechanical systems: Innovations in real‐time monitoring and operational excellence. International Journal of Advanced Manufacturing Technology, 102(5), 1471–1484.

[37] Singh, A., & Kumar, S. (2015). Financial inclusion and market development in Emerging Asia. Journal of Development Economics, 114, 175–190.

[38] Stock, J. H., & Watson, M. W. (2016). Dynamic factor models for macroeconomic forecasting. Review of Economics and Statistics, 98(2), 327–340.

[39] Turner, D., & Roberts, J. (2016). Monetary policy transmission in the Eurozone: Evaluating heterogeneous responses. Journal of Monetary Economics, 78, 123–139.

How to cite this paper

Olaitan Kemi Atobatele, Akonasu Qudus Hungbo, Christiana Adeyemi "Evaluating the Strategic Role of Economic Research in Supporting Financial Policy Decisions and Market Performance Metrics" Iconic Research And Engineering Journals Volume 3 Issue 3 2019 Page 248-258
Olaitan Kemi Atobatele, Akonasu Qudus Hungbo, Christiana Adeyemi "Evaluating the Strategic Role of Economic Research in Supporting Financial Policy Decisions and Market Performance Metrics" Iconic Research And Engineering Journals, vol. 3, no. 3, Sep. 2019
Olaitan Kemi Atobatele, Akonasu Qudus Hungbo, Christiana Adeyemi (2019). Evaluating the Strategic Role of Economic Research in Supporting Financial Policy Decisions and Market Performance Metrics. Iconic Research And Engineering Journals, 3(3).
Olaitan Kemi Atobatele, Akonasu Qudus Hungbo, Christiana Adeyemi "Evaluating the Strategic Role of Economic Research in Supporting Financial Policy Decisions and Market Performance Metrics" Iconic Research And Engineering Journals, vol. 3, no. 3, Sep. 2019.
@article{1710100,
      author = {Olaitan Kemi Atobatele, Akonasu Qudus Hungbo, Christiana Adeyemi},
      title = {Evaluating the Strategic Role of Economic Research in Supporting Financial Policy Decisions and Market Performance Metrics},
      journal = {Iconic Research And Engineering Journals},
      year = {2019},
      volume = {3},
      number = {3},
      pages = {248-258},
      issn = {2456-8880},
      url = {https://www.irejournals.com/formatedpaper/17101001.pdf},
      abstract = {Economic research plays a pivotal role in shaping robust financial policy decisions and enhancing the effectiveness of market performance metrics. By combining theoretical modeling, empirical analysis, and policy evaluation techniques, researchers provide evidence-based insights that inform central banks, regulatory bodies, and fiscal authorities. This review synthesizes the strategic contributions of economic research across three domains: policy formulation, implementation monitoring, and performance measurement. It examines methodological approaches?ranging from macro econometric modeling to experimental and behavioral economics?that underpin policy analysis, and it evaluates how findings translate into actionable recommendations for interest rate setting, fiscal stimulus design, and regulatory interventions. Additionally, the paper explores the development and refinement of market performance indicators?such as liquidity measures, volatility indices, and systemic risk gauges?and assesses how economic research validates and enriches these metrics. Through a critical appraisal of case studies from advanced and emerging economies, the review highlights best practices and identifies persistent challenges, including data limitations, model uncertainty, and evolving market structures. Finally, it outlines future research priorities for strengthening the nexus between economic inquiry and financial policymaking, emphasizing interdisciplinary collaboration, big data integration, and real time analytics to foster resilient and transparent markets.},
      keywords = {Economic Research, Financial Policy, Market Performance Metrics, Econometric Modeling, Policy Evaluation, Systemic Risk Indicators.},
      month = {September},
  }