Fiscal Incentives and Firm Growth

Duke University, Durham NC

Investigators

Abstract

Many countries around the world use tax incentives to influence firm decisions, aiming to promote innovation and productivity as well as to create economic stability. This research exploits a novel data set and provides a new way to precisely measure how firms respond to two different kinds of tax incentives. The investigators analyze the effects of a large fiscal incentive for R&D investment in the form of a corporate income tax cut. The investigators also examine the impact of value-added tax (VAT) reform on firm fixed asset investment and assess its role as a counter-cyclical fiscal stimulus during the financial crisis. The results of this project will give us new evidence on how private enterprises respond to changes in tax policy, and will help us to evaluate the long-run forces that have resulted large changes in challenges to U.S. leadership in global innovation. This research consists of two related projects on fiscal incentives and firm growth. The first project exploits unique features of the Chinese corporate income tax incentives, which generate jumps in firm's payoff function. This project then implements a cross-sectional "bunching" estimator that is novel in the R&D literature. Building on this policy variation and panel data, the investigators use a new estimator of casual effect to further quantify the effects of the tax program on firm productivity and on fiscal costs. The investigators also structurally estimate the model to match the data bunching patterns and the treatment effects. The second project considers changing from production-based VAT to consumption-based VAT, thus allowing the direct deduction of new fixed asset investment from VAT and substantially reducing the user cost of capital. The investigators exploit variations in the timing of the policy roll out in different regions and industries to quantify the response of firm investment to the fiscal stimulus. This project then leverages on the rich heterogeneity of micro-level data to identify how these responses differ across firms.