A key input to quantitative evaluations of transport infrastructure projects is their impact on transport costs. We propose a new method of estimating this impact relying on widely accessible customs data: by using the route choice of exporters. We combine our method with a spatial equilibrium model to study the effects of the massive expressway construction in China between 1999 and 2010. We find transport costs are 20% lower on expressways than on regular roads. The expressways construction increases aggregate exports by 10% and domestic trade by 14%. It generates 5.1% welfare gains, implying a 150% net return to investment.

We examine whether local political corruption affects managers' discretionary disclosures of non-GAAP earnings. Using United States Department of Justice data on the number of corruption convictions of government officials, we find that firms headquartered in more corrupt districts (1) are less likely to report non-GAAP earnings, (2) have less aggressive non-GAAP earnings disclosures, and (3) experience a significant decline in the exclusion magnitudes of non-GAAP earnings. These results are more pronounced for firms with concentrated operations in their headquarter states and are robust to controlling for demographic characteristics, employing alternative corruption and non-GAAP measures, using the instrumental variable approach, and conducting a difference-in-difference analysis based on firms' relocation. Finally, we show that as local political corruption increases, managers exclude lower levels of both recurring and non-recurring items when calculating non-GAAP earnings. Overall, the results suggest that managing non-GAAP reporting is one channel through which firms could deter rent-seeking by corrupt officials.

Using influenza epidemic data, we examine how constraints on corporate information production affect disclosure policies. We find that firms in areas with higher flu activity are less likely to issue short‐run earnings forecasts and more likely to issue long‐run earnings forecasts. These results are more pronounced when the information production process is more complex, when managers face a greater reputational loss for issuing low‐quality short‐run forecasts, and when firms’ costs of switching the forecast horizon are lower. Further analysis implies that the effect of flu activity on these forecast issuance decisions is not driven by firm performance or information uncertainty. Our results suggest that managers do not simply avoid issuing forecasts in response to information production constraints. Instead, they shift the forecast horizon from short‐run to long‐run, appearing to balance the costs of issuing low‐quality forecasts with those of not issuing forecasts at all.

This study examines the impact of local corruption on firms' narrative research and development (R&D) disclosures in the United States. We find that firms in more corrupt areas include fewer R&D sentences in their 10-K filings, and these sentences contain less numerical and forward-looking information. Our results hold across various measures of local corruption and R&D disclosures and remain robust after controlling for firms' R&D activities, implementing fixed effects, using difference-in-differences tests, and applying instrumental variable analysis. Additionally, the effects are more pronounced for firms with concentrated operations in their headquarters states and for firms whose R&D disclosures closely relate to future earnings. However, they are less pronounced for firms with CEOs politically aligned with the state's incumbent party and when the benefit of resolving market dispersion from firms' R&D disclosure is high. Overall, our findings indicate that local corruption adversely affects firms' narrative R&D disclosures.