Papua New Guinea: Systematic analysis of domestic production and world market shocks

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., prima...

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Main Authors: Mukashov, Askar, Dorosh, Paul A., Schmidt, Emily, Thurlow, James
Format: Brief
Language:Inglés
Published: International Food Policy Research Institute 2025
Subjects:
Online Access:https://hdl.handle.net/10568/173653
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author Mukashov, Askar
Dorosh, Paul A.
Schmidt, Emily
Thurlow, James
author_browse Dorosh, Paul A.
Mukashov, Askar
Schmidt, Emily
Thurlow, James
author_facet Mukashov, Askar
Dorosh, Paul A.
Schmidt, Emily
Thurlow, James
author_sort Mukashov, Askar
collection Repository of Agricultural Research Outputs (CGSpace)
description 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.
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spelling CGSpace1736532026-01-06T20:10:13Z Papua New Guinea: Systematic analysis of domestic production and world market shocks Mukashov, Askar Dorosh, Paul A. Schmidt, Emily Thurlow, James computable general equilibrium models domestic production machine learning shock vulnerability world markets agricultural production 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. 2025-03 2025-03-17T15:47:31Z 2025-03-17T15:47:31Z Brief https://hdl.handle.net/10568/173653 en Open Access application/pdf International Food Policy Research Institute Mukashov, Askar; Dorosh, Paul A.; Schmidt, Emily; and Thurlow, James. 2025. Papua New Guinea: Systematic analysis of domestic production and world market shocks. Papua New Guinea Project Note 18. Washington, DC: International Food Policy Research Institute. https://hdl.handle.net/10568/173653
spellingShingle computable general equilibrium models
domestic production
machine learning
shock
vulnerability
world markets
agricultural production
Mukashov, Askar
Dorosh, Paul A.
Schmidt, Emily
Thurlow, James
Papua New Guinea: Systematic analysis of domestic production and world market shocks
title Papua New Guinea: Systematic analysis of domestic production and world market shocks
title_full Papua New Guinea: Systematic analysis of domestic production and world market shocks
title_fullStr Papua New Guinea: Systematic analysis of domestic production and world market shocks
title_full_unstemmed Papua New Guinea: Systematic analysis of domestic production and world market shocks
title_short Papua New Guinea: Systematic analysis of domestic production and world market shocks
title_sort papua new guinea systematic analysis of domestic production and world market shocks
topic computable general equilibrium models
domestic production
machine learning
shock
vulnerability
world markets
agricultural production
url https://hdl.handle.net/10568/173653
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