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Can the Oil Price Stabilisation Fund Reduce the Volatility of Domestic Prices?

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  • The Anh Pham

Abstract

This paper has two primary objectives. First, it contributes to the literature on oil stabilisation funds and price controls by examining how such a fund is used to regulate market prices in the developing country of Vietnam. Second, it employs descriptive statistics and a standard GARCH methodology to investigate whether the fund, which operates as a form of price control, can effectively reduce domestic price volatility. The results show that the oil price stabilisation fund failed to achieve its intended goal. Considering the administrative costs and other negative impacts associated with the fund, a more market‐oriented approach, potentially combined with a price‐elastic tax system, is recommended for determining domestic oil prices.

Suggested Citation

  • The Anh Pham, 2025. "Can the Oil Price Stabilisation Fund Reduce the Volatility of Domestic Prices?," Asia and the Pacific Policy Studies, Wiley Blackwell, vol. 12(3), September.
  • Handle: RePEc:bla:asiaps:v:12:y:2025:i:3:n:e70036
    DOI: 10.1002/app5.70036
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    References listed on IDEAS

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    1. Nomikos, Nikos & Andriosopoulos, Kostas, 2012. "Modelling energy spot prices: Empirical evidence from NYMEX," Energy Economics, Elsevier, vol. 34(4), pages 1153-1169.
    2. Bollerslev, Tim, 1986. "Generalized autoregressive conditional heteroskedasticity," Journal of Econometrics, Elsevier, vol. 31(3), pages 307-327, April.
    3. Christopher J. Neely, 2022. "Why Price Controls Should Stay in the History Books," The Regional Economist, Federal Reserve Bank of St. Louis, March.
    4. Jayne, T.S. & Mason, Nicole M. & Burke, William J. & Ariga, Joshua, "undated". "Agricultural Input Subsidy Programs In Africa: An Assessment Of Recent Evidence," Feed the Future Innovation Lab for Food Security Policy Research Papers 259509, Michigan State University, Department of Agricultural, Food, and Resource Economics, Feed the Future Innovation Lab for Food Security (FSP).
    5. Hiroyuki Taguchi & Javkhlan Ganbayar, 2022. "Natural Resource Funds: Their Objectives and Effectiveness," Sustainability, MDPI, vol. 14(17), pages 1-20, September.
    6. repec:wbk:wbpubs:6610 is not listed on IDEAS
    7. Mariano Tappata, 2009. "Rockets and feathers: Understanding asymmetric pricing," RAND Journal of Economics, RAND Corporation, vol. 40(4), pages 673-687, December.
    8. Mohammadi, Hassan & Su, Lixian, 2010. "International evidence on crude oil price dynamics: Applications of ARIMA-GARCH models," Energy Economics, Elsevier, vol. 32(5), pages 1001-1008, September.
    9. Shi, Xunpeng & Sun, Sizhong, 2017. "Energy price, regulatory price distortion and economic growth: A case study of China," Energy Economics, Elsevier, vol. 63(C), pages 261-271.
    10. Mundaca, Gabriela, 2017. "Energy subsidies, public investment and endogenous growth," Energy Policy, Elsevier, vol. 110(C), pages 693-709.
    11. Di Giacomo, Marina & Piacenza, Massimiliano & Scervini, Francesco & Turati, Gilberto, 2015. "Should we resurrect ‘TIPP flottante’ if oil price booms again? Specific taxes as fuel consumer price stabilizers," Energy Economics, Elsevier, vol. 51(C), pages 544-552.
    12. Tsani, Stella, 2013. "Natural resources, governance and institutional quality: The role of resource funds," Resources Policy, Elsevier, vol. 38(2), pages 181-195.
    13. Engle, Robert F, 1982. "Autoregressive Conditional Heteroscedasticity with Estimates of the Variance of United Kingdom Inflation," Econometrica, Econometric Society, vol. 50(4), pages 987-1007, July.
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