Data and Code for: Do Tax Incentives Increase Firm Innovation? An RD Design for R&D, Patents, and Spillovers

Principal Investigator(s): View help for Principal Investigator(s) Antoine Dechezlepretre, OECD and CEP; Elias Einio, VATT and CEP; Ralf Martin, Imperial College London and CEP; Kieu-Trang Nguyen, Northwestern University and CEP; John Van Reenen, London School of Economics and MIT

Version: View help for Version V1

Name	File Type	Size	Last Modified
Code			09/20/2024 06:20:PM
Data			09/20/2024 06:20:PM
Databook.xlsx	application/vnd.openxmlformats-officedocument.spreadsheetml.sheet	43.5 KB	09/20/2024 02:20:PM
Replication_log_appendix.log	text/x-log	264.8 KB	09/20/2024 02:20:PM
Replication_log_main.log	text/x-log	154.3 KB	09/20/2024 02:20:PM

Citation:

Dechezlepretre, Antoine, Einio, Elias, Martin, Ralf, Nguyen, Kieu-Trang, and Van Reenen, John. Data and Code for: Do Tax Incentives Increase Firm Innovation? An RD Design for R&D, Patents, and Spillovers: RDTC replication files. Nashville, TN: American Economic Association [publisher], 2024. Ann Arbor, MI: Inter-university Consortium for Political and Social Research [distributor], 2024-09-23. https://doi.org/10.3886/E181362V1-160382

To view the citation for the overall project, see http://doi.org/10.3886/E181362V1.

Project Description

Summary:

We present evidence of the positive causal impacts of research and development (R&D) tax incentives on a firm’s own innovation and that of its technological neighbors (spillovers). Exploiting a change in the assets-based size thresholds that determine eligibility for R&D tax relief, we implement a Regression Discontinuity (RD) Design using administrative data. We find statistically and economically significant effects of tax relief on (quality-adjusted) patenting (and R&D) that persist up to seven years after the change. Moreover, we also find causal evidence of R&D spillovers on the innovation of technologically close peer firms. We can rule out elasticities of patenting with respect to the user cost of R&D of under 2 at the 5% level and show evidence that our large effects are likely because the treated group are more likely to be financially constrained.

Scope of Project

Subject Terms: R&D; Patents; Tax; Innovation; Spillovers; Regression Discontinuity Design

JEL Classification:
      H23 Taxation and Subsidies: Externalities; Redistributive Effects; Environmental Taxes and Subsidies
      H25 Business Taxes and Subsidies including sales and value-added (VAT)
      H32 Fiscal Policies and Behavior of Economic Agents: Firm
      O31 Innovation and Invention: Processes and Incentives
      O32 Management of Technological Innovation and R&D

Universe: UK firms between 2002-2015.

Data Type(s): administrative records data

Methodology

Data Source: Included: Patent data from PATSTAT dataset. Financial data from Bureau Van Dijk's FAME dataset.
Not included: R&D data from HMRC Corporate Tax Returns (CT600) and its extension, the Research and Development Tax Credits (RDTC) dataset.

Unit(s) of Observation: Firm, firm pair.

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Published Versions

V1 [2024-09-23]

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