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Evaluating inflation targeting based on the distribution of inflation and inflation volatility

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  • Ginindza, Mzwandile
  • Maasoumi, Esfandiar

Abstract

In this paper the Financial Development Index (FDI) is used to rank 57 of the world's leading financial systems. Its calculation is based on the following 7 economic pillars: (1) Institutional environment, (2) Business environment, (3) Financial stability, (4) Banking financial services, (5) Non-banking financial services, (6) Financial markets, and (7) Financial access. Pillar (4) is constructed from bond markets, stock markets, foreign exchange markets, and derivative markets. Pillar (5) includes a country's IPO activity, namely the IPO market share, IPO proceeds amount, and IPOs share of world IPOs. The stock market index provides a short-term account of financial activities, whereas the FDI provides a long-term broader account of the financial structure and health of an economy. As the performance and success of a given monetary policy would less likely be judged on short-term dynamics, it seems sensible to use the annual FDI as one of several economic and country attributes in a policy evaluation of Inflation Targeting. The paper offers a potential outcomes analysis of the impact of inflation targeting on inflation and inflation volatility, and focuses on advanced economies that adopt “inflation targeting” as a formal monetary policy. In order to deal with the counterfactual question, namely what would be the inflation rate for an adopting country had it not adopted this policy, the paper offers a new matching technique that subsumes the traditional propensity scores methods as a special case. The paper has different proposals for assessing “matching” based on the whole distribution of any “scores”. Additionally, the paper goes beyond the Average Treatment Effect (ATE) and examines the entire distribution of inflation and its “variability”. It is found that the adoption of inflation targeting has helped lower inflation (not just the mean) for the targeting countries. However, it is shown that exact numerical quantification of this policy effect is as highly subjective as choosing ideal social welfare functions. The paper also finds no evidence of a larger gain for “late adopters” of inflation targeting. As for inflation variability, there is some robust evidence of small and often statistically insignificant reduction in variability due to targeting.

Suggested Citation

  • Ginindza, Mzwandile & Maasoumi, Esfandiar, 2013. "Evaluating inflation targeting based on the distribution of inflation and inflation volatility," The North American Journal of Economics and Finance, Elsevier, vol. 26(C), pages 497-518.
  • Handle: RePEc:eee:ecofin:v:26:y:2013:i:c:p:497-518
    DOI: 10.1016/j.najef.2013.02.018
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    References listed on IDEAS

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    1. Maasoumi, Esfandiar & Eren, Ozkan, 2006. "The Information Basis of Matching with Propensity Score," Departmental Working Papers 0606, Southern Methodist University, Department of Economics.
    2. Laurence M. Ball & Niamh Sheridan, 2004. "Does Inflation Targeting Matter?," NBER Chapters, in: The Inflation-Targeting Debate, pages 249-282, National Bureau of Economic Research, Inc.
    3. Klaus Schmidt-Hebbel & Matías Tapia, 2002. "Monetary Policy Implementation and Results in Twenty Inflation-Targeting Countries," Working Papers Central Bank of Chile 166, Central Bank of Chile.
    4. Lin, Shu & Ye, Haichun, 2007. "Does inflation targeting really make a difference? Evaluating the treatment effect of inflation targeting in seven industrial countries," Journal of Monetary Economics, Elsevier, vol. 54(8), pages 2521-2533, November.
    5. Rajeev H. Dehejia & Sadek Wahba, 2002. "Propensity Score-Matching Methods For Nonexperimental Causal Studies," The Review of Economics and Statistics, MIT Press, vol. 84(1), pages 151-161, February.
    6. Quah, Danny, 1997. "Empirics for Growth and Distribution: Stratification, Polarization, and Convergence Clubs," CEPR Discussion Papers 1586, C.E.P.R. Discussion Papers.
    7. Lim, G.C. & Maasoumi, Esfandiar & Martin, Vance L., 2006. "A reexamination of the equity-premium puzzle: A robust non-parametric approach," The North American Journal of Economics and Finance, Elsevier, vol. 17(2), pages 173-189, August.
    8. Marco Vega & Diego Winkelried, 2005. "Inflation Targeting and Inflation Behavior: A Successful Story?," International Journal of Central Banking, International Journal of Central Banking, vol. 1(3), December.
    9. von Furstenberg, George M. & Fratianni, Michele, 1996. "Indicators of financial development," The North American Journal of Economics and Finance, Elsevier, vol. 7(1), pages 19-29.
    10. C. W. Granger & E. Maasoumi & J. Racine, 2004. "A Dependence Metric for Possibly Nonlinear Processes," Journal of Time Series Analysis, Wiley Blackwell, vol. 25(5), pages 649-669, September.
    11. Quah, Danny T, 1997. "Empirics for Growth and Distribution: Stratification, Polarization, and Convergence Clubs," Journal of Economic Growth, Springer, vol. 2(1), pages 27-59, March.
    12. Maasoumi, Esfandiar, 1986. "The Measurement and Decomposition of Multi-dimensional Inequality," Econometrica, Econometric Society, vol. 54(4), pages 991-997, July.
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    Cited by:

    1. Chia-Lin Chang & Allen, David & McAleer, Michael, 2013. "Recent developments in financial economics and econometrics: An overview," The North American Journal of Economics and Finance, Elsevier, vol. 26(C), pages 217-226.
    2. Maasoumi, Esfandiar & Racine, Jeffrey S., 2016. "A solution to aggregation and an application to multidimensional ‘well-being’ frontiers," Journal of Econometrics, Elsevier, vol. 191(2), pages 374-383.

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