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Optimal policies for managing oil revenue stabilization funds: An illustration using Saudi Arabia

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  • AlKathiri, Nader
  • Atalla, Tarek N.
  • Murphy, Frederic
  • Pierru, Axel

Abstract

We develop an analytical approach that offers insights into how governments can better manage an oil-revenue stabilization fund. The model maximizes the expected intertemporal utility of households and consists of decisions that are a function of the fund level and oil revenue. We apply our approach to Saudi data, noting that the government deposits and reserve at the Saudi Arabian Monetary Agency have historically served as a buffer to decouple the Saudi government budget from oil revenue fluctuations. Results from our model match intuition: the larger the fund, the smaller the additions during periods of high revenues and the bigger the withdrawals during periods of low revenues. We also show that the fund can be partitioned into tranches with different asset durations rather than being solely invested in short-term assets. Our results indicate that the boundary between an oil-revenue stabilization fund and a sovereign wealth fund is not a bright line.

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  • AlKathiri, Nader & Atalla, Tarek N. & Murphy, Frederic & Pierru, Axel, 2020. "Optimal policies for managing oil revenue stabilization funds: An illustration using Saudi Arabia," Resources Policy, Elsevier, vol. 67(C).
    • Handle: RePEc:eee:jrpoli:v:67:y:2020:i:c:s0301420719304258
    DOI: 10.1016/j.resourpol.2020.101686
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    More about this item

    Keywords

    Oil; Stabilization fund; Welfare; Regime switching; Sovereign wealth fund; Dynamic programming;
    All these keywords.

    JEL classification:

    • Q43 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Energy and the Macroeconomy
    • E21 - Macroeconomics and Monetary Economics - - Consumption, Saving, Production, Employment, and Investment - - - Consumption; Saving; Wealth
    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis

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