Papua New Guinea: Systematic analysis of domestic production and world market shocks
Askar Mukashov,
Paul A. Dorosh,
Emily Schmidt and
James Thurlow
No 18, Papua New Guinea project notes from International Food Policy Research Institute (IFPRI)
Abstract:
Using an economy-wide, multi-sectoral model, this study explores potential vulnerability of Papua New Guinea (PNG) to economic shocks and identifies factors that contribute most to economic uncertainty. Economic scenarios were developed using historical data on volatile domestic sectors (e.g., primary agriculture and hydropower electricity generation) and world prices of goods and services in which PNG trades. The Computable General Equilibrium (CGE) model of PNG was used to simulate a range of potential economic outcomes under these scenarios. In addition, data mining and machine learning methods were applied to quantify the contribution of each shock to the uncertainty of economic outcomes. Key findings suggest that Papua New Guinea’s economy is predominantly exposed to external risks, with world prices and foreign capital volatility together accounting for approximately two-thirds of the potential variation in GDP and three-fourths of the potential variation in private consumption, poverty, and undernourishment (domestic production volatility contributes the remaining one-third and one-fourth, respectively). The current structure of the PNG economy underpins these results. While agriculture is the most uncertain sector, it is relatively less important compared to the overall economy; export earnings from energy and metals, as well as volatile foreign exchange capital inflows, play a much more significant role in the country’s current economic risks. Understanding how potential shocks might impact various segments of the PNG economy and population is a critical first step in facilitating discussions on relevant risk mitigation strategies, such as increasing sectoral productivity or diversifying production away from high-risk sectors.
Keywords: computable general equilibrium models; domestic production; machine learning; shock; vulnerability; world markets; Papua New Guinea; Oceania (search for similar items in EconPapers)
Date: 2025-03
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https://hdl.handle.net/10568/173653
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Persistent link: https://EconPapers.repec.org/RePEc:fpr:pngprn:173653
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