Section 1502 of the Dodd–Frank Act requires SEC‐registered issuers to conduct supply chain due diligence and submit conflict minerals disclosures (CMDs) that indicate whether their products contain tantalum, tin, tungsten, or gold (3TG) sourced from the Democratic Republic of the Congo (DRC) or its neighboring countries (“covered countries”). Consistent with the reputational cost hypothesis, we find that heightened public attention to CMDs increases responsible sourcing. After Section 1502 takes effect, we find higher demand for 3TG products processed in certified smelters, decreased conflicts in covered countries’ mining regions relative to other regions, and reduced sensitivity of conflict risk to conflict minerals’ price spikes. Finally, we find that conflicts decrease in Eastern DRC territories with prevalent 3T (tantalum, tin, and tungsten) mines but increase in territories with prevalent gold mines. Overall, our findings highlight the real effects of enhanced supply chain transparency regulation.

Analyzing account-level data from an account aggregator, we find that households increase consumption when they receive expected tax refunds, as if they face liquidity constraints. However, these same households smooth consumption when making payments in other years, primarily by transferring funds among liquid accounts. Even households carrying credit card debt smooth consumption when making payments, and even highly liquid households spend out of refunds. This behavior is inconsistent with pure liquidity constraints or hand-to-mouth behavior and is most consistent with a mental accounting life-cycle model.

For years, online retailers have maintained a price advantage over brick‐and‐mortar retailers by not collecting sales tax at the time of sale. Recently, several states have required that online retailer Amazon collect sales tax during checkout. Using transaction‐level data, we document that households living in these states reduced their Amazon purchases by 9.4% following the implementation of the sales tax laws, implying elasticities of –1.2 to –1.4. The effect is stronger for large purchases, where purchases declined by 29.1%, corresponding to an elasticity of –3.9. Studying competitors in the electronics field, we find some evidence of substitution toward competing retailers.