Commodity Booms, Productivity, and Misallocation: Evidence from Chile’s Administrative Data
IMF Working Papers, July 31, 2026
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- Commodity Booms, Productivity, and Misallocation: Evidence from Chile’s Administrative Data
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Bibliographic details
- Authors: Pablo Filippi, Ryan Kim, Nan Li, María Jesús Pérez, Younghun Shim
- Published: July 31, 2026
- Series: IMF Working Papers
- DOI: https://doi.org/10.5089/9798229055529.001
Summary
- Study uses administrative microdata from Chile combining firm exports by product and destination, employer-employee records, and firm-to-firm production networks.
- Exploits differential Chinese demand across Chilean commodity products to measure firms’ exposure to the commodity boom and trace effects on productivity and resource allocation.
- Develops a model with heterogeneous export wedges and labor market frictions to assess how commodity booms affect sectoral productivity and input misallocation.
- Calibrated to Chile, the model mechanism explains half of the mining TFP decline from 2005 to 2013.
- Publication details: Pages: 74; Volume: 2026; Issue: 163; Series: Working Paper No. 2026/163; DOI: https://doi.org/10.5089/9798229055529.001; Stock No: WPIEA2026163; ISBN: 9798229055529; ISSN: 1018-5941.
Key findings
- More exposed firms experience larger revenue increases but no differential productivity gains, and they channel revenues into wages and materials.
- Among exposed firms:
- Low-productivity firms expand employment.
- High-productivity firms do not expand employment.
- Employment expansion by low-productivity firms involves hiring workers from more productive employers.
- Domestic suppliers with greater indirect exposure show larger sales and productivity gains.
- Aggregate and firm-level evidence are consistent with a mechanism in which commodity booms can reduce sectoral productivity by exacerbating input misallocation.
- Calibrated quantitative result: the mechanism explains half of the mining total factor productivity (TFP) decline from 2005 to 2013.
Mechanisms identified
- Revenue channel:
- Differential exposure to Chinese demand raises revenues for more exposed firms.
- Revenue increases are not accompanied by corresponding productivity gains.
- Additional revenues are allocated to wages and materials.
- Labor reallocation channel:
- Labor moves from more productive to less productive employers within exposed firms.
- Low-productivity exposed firms expand employment by hiring away workers from higher-productivity firms, reducing effective productivity.
- Input-supplier channel:
- Domestic suppliers with higher indirect exposure to the boom increase sales and experience productivity gains, reflecting networked transmission of demand shocks.
- General equilibrium effect:
- Heterogeneous export wedges combined with labor market frictions generate input misallocation that can lower sectoral productivity during commodity booms.
Model and calibration
- Model features: heterogeneous export wedges; labor market frictions; firm-level heterogeneity; input linkages across firms.
- Calibration to Chilean data yields a quantitative accounting result: the model’s misallocation mechanism accounts for half of the observed mining sector TFP decline over 2005–2013.
Implications for analysis and policy discussion
- Commodity booms can have heterogeneous micro-level effects that do not automatically translate into productivity gains at the firm or sector level.
- Revenue windfalls concentrated in exposed firms may lead to resource reallocation toward less productive uses when labor market frictions and input linkages are present.
- Evaluations of commodity booms should account for indirect exposure through supplier networks and potential adverse reallocation effects on sectoral TFP.
- Policy responses aiming to preserve or enhance sectoral productivity during commodity booms may need to address:
- Labor market frictions that enable inefficient hiring away from higher-productivity firms.
- Input misallocation arising from differential export wedges and network linkages.
Subjects and keywords
- Subject: Commodities, Commodity booms, Exports, International trade, Labor, Labor market frictions, Labor markets, Production, Productivity
- Keywords: commodity boom, Commodity booms, Employment, Exports, Global, IMF working papers, input misallocation, Labor market frictions, Labor markets, Labor reallocation., Micro-level Data, Mining sector, Misallocation, Productivity, productivity gain, sectoral productivity, Total factor productivity, Wages
IMF Working Papers: "Commodity Booms, Productivity, and Misallocation: Evidence from Chile’s Administrative Data", Pablo Filippi, Ryan Kim, Nan Li, María Jesús Pérez, Younghun Shim, July 31, 2026.
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- Working Paper