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Granger Causality And Cointegration In Romania’S Inflationary Dynamics €“ An Empirical Study

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  • Mester Ioana Teodora

    ()

  • Simut Ramona

    ()

Abstract

One of the most difficult issues that monetary authorities in many developing economies have to deal with is the management of a stable price environment. Inflation can create uncertainty, a low level of investment, and raise costs in general, thus lowering rates of growth. As a result, there exists a widespread need for understanding inflationary dynamics in any country of interest, especially in developing countries, subject to more significant and volatile price changes. This paper develops a VEC model for the Romanian economy, using CPI index and other macroeconomic data, in order to capture the transmission mechanism of inflation.

Suggested Citation

  • Mester Ioana Teodora & Simut Ramona, 2010. "Granger Causality And Cointegration In Romania’S Inflationary Dynamics €“ An Empirical Study," Annals of Faculty of Economics, University of Oradea, Faculty of Economics, vol. 1(1), pages 272-278, July.
  • Handle: RePEc:ora:journl:v:1:y:2010:i:1:p:272-278
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    File URL: http://anale.steconomiceuoradea.ro/volume/2010/n1/042.pdf
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    References listed on IDEAS

    as
    1. Pesaran, M. Hashem & Smith, Ron, 1995. "Estimating long-run relationships from dynamic heterogeneous panels," Journal of Econometrics, Elsevier, vol. 68(1), pages 79-113, July.
    2. Budina, Nina & Maliszewski, Wojciech & de Menil, Georges & Turlea, Geomina, 2006. "Money, inflation and output in Romania, 1992-2000," Journal of International Money and Finance, Elsevier, vol. 25(2), pages 330-347, March.
    Full references (including those not matched with items on IDEAS)

    More about this item

    Keywords

    inflation forecasting; monetary policy; developing countries; Romania; VAR model;

    JEL classification:

    • E52 - Macroeconomics and Monetary Economics - - Monetary Policy, Central Banking, and the Supply of Money and Credit - - - Monetary Policy
    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models

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