Optimizing Local Content Requirements Under Technology Gaps
Abstract
Problem definition: We study how the government of a developing country optimizes its local content requirement (LCR) policy to maximize social welfare in a setting where foreign original equipment manufacturers (OEMs) produce and sell multicomponent products in the developing country. The foreign OEMs’ local sourcing of components is more costly than global sourcing because of technology gaps between local and global suppliers. Academic/practical relevance: We characterize and compare the optimal product-level and component-level LCR policies imposed on multicomponent products. Component-level LCR and its relationship with product-level LCR, although relevant to trade policy making, have not been studied in prior research. Methodology: We use stylized modeling with a Stackelberg game, welfare optimization, and Cournot competition. Results: The optimal component-level LCR for low-gap (or high-gap) components is higher (or lower) than the optimal product-level LCR, although the two policies achieve the same maximum social welfare. The optimal LCR is monotone increasing in the market size of the final product but decreasing in the corporate tax rate. The optimal LCR is decreasing in the number of competing foreign OEMs but increasing in the number of competing local OEMs. Managerial implications: (1) From a welfare standpoint, imposing an LCR at the component level may be unnecessary. However, when replacing a product-level LCR policy with a component-level one, governments should increase (or decrease) the LCR for low-gap (or high-gap) components. (2) Governments should consider raising LCRs when their domestic markets grow. (3) When more foreign OEMs operate in a developing country, its government should consider lowering LCRs. (4) The emergence of local OEMs should give governments an incentive to raise LCRs. (5) The carrot-and-stick approach makes sense when implementing LCR policies—the LCR should be set low (or high) when the corporate tax rate is high (or low).
https://kenaninstitute.unc.edu/publication/optimizing-local-content-requirements-under-technology-gaps/
