Taxation, corruption, and growth
GAICIL Insights
The tax debate usually asks how much to take.1 This paper asks who is spending it, and how honestly. Taxation, corruption, and growth, by Philippe Aghion, Ufuk Akcigit, Julia Cagé and William R. Kerr, builds an endogenous growth model capturing both faces of taxation: it finances the public infrastructure entrepreneurs rely on, and it discourages entrepreneurial effort. Political corruption governs how efficiently tax revenue becomes infrastructure. The model predicts an inverted-U relationship between taxation and growth, with corruption reducing the optimal level of taxation.
The evidence supports the predictions. Using the Longitudinal Business Database of the US Census Bureau, the authors find the marginal effect of taxation on growth significantly positive for a state at the 10th or 25th percentile of corruption, and much lower for a state at the 90th percentile. Higher local corruption weakens taxation's positive effect on growth, innovation and entry, apparently through entrepreneurial channels. The same tax rate can build infrastructure in one state and leak away in another.
Progress toward causality comes from Granger-style tests and from periphery counties where effective tax policy is largely driven by bordering states. In calibration, the calibrated taxation rate of 37% is fairly close to the model's estimated welfare-maximizing rate of 42%. Reducing corruption offers the largest potential welfare gain, through its impact on the uses of tax revenue. Cleaning up spending beats fine-tuning rates.
The core insight: taxation's effect depends on how revenues are used. Where revenue translates efficiently into infrastructure, taxation supports growth by providing public goods entrepreneurs need. Where corruption diverts revenue, taxation mainly discourages effort. Governance quality decides whether taxes help or hurt growth. The left-right argument about tax levels misses the variable that matters most.
AI depends heavily on public infrastructure: research funding, education, data infrastructure and digital networks, all financed by taxation. The growth effects of such spending depend on how efficiently it is managed. Efficient, accountable governments can use tax revenue to build infrastructure supporting AI entrepreneurship. An AI budget passing through a leaky government delivers far less than its headline.
Corruption lowering the optimal tax level carries a governance lesson. Where institutions are inefficient, the case for higher taxes to fund public investment weakens. Better governance raises the returns to public investment, letting taxation support growth. For countries building AI capabilities, strengthening institutions may matter as much as spending more. Integrity is a productivity input.
The authors note that tax policy analysis often omits innovation and growth as leading criteria. Debates over income tax progressivity and corporate rates frequently focus on revenue and distribution. This paper links the revenue side of the public ledger to the spending side and to spending effectiveness. In an AI era where innovation drives growth, that link is essential.
Entrepreneurs sit at the center. They respond to taxation's disincentives and to infrastructure's benefits. AI entrepreneurship is a major source of innovation, and tax and spending policies supporting entrepreneurs can foster AI-driven growth.
The paper calls itself a first step in a broader agenda on factoring growth and innovation into optimal tax design. That agenda grows more important as governments consider how to tax and support AI. Research linking taxation, spending and innovation can inform those choices.
At bottom, taxation, governance and growth are interconnected. Taxes can support growth when revenue finances useful infrastructure efficiently, and corruption undermines the relationship. As governments design policies for the AI economy, they should treat innovation and growth as central criteria and invest in governance ensuring public funds support the entrepreneurs driving progress.
AI industrial strategies might start here: before announcing a bigger AI fund, audit the pipe it will flow through. On this evidence, reducing corruption may be a major lever for innovation-led growth.
Introduction
We build an endogenous growth model to analyze the relationships between taxation, corruption, and economic growth. Entrepreneurs lie at the center of the model and face disincentive effects from taxation but acquire positive benefits from public infrastructure. Political corruption governs the efficiency with which tax revenues are translated into infrastructure. The model predicts an inverted-U relationship between taxation and growth, with corruption reducing the optimal taxation level. We find evidence consistent with these predictions and the entrepreneurial channel using data from the Longitudinal Business Database of the US Census Bureau. The marginal effect of taxation for growth for a state at the 10th or 25th percentile of corruption is significantly positive; on the other hand, the marginal effects of taxation for growth for a state at the 90th percentile of corruption are much lower across the board. We make progress towards causality through Granger-style tests and by considering periphery counties where effective tax policy is largely driven by bordering states. Finally, we calibrate our model and find that the calibrated taxation rate of 37% is fairly close to the model׳s estimated welfare maximizing taxation rate of 42%. Reducing corruption provides the largest potential impact for welfare gain through its impact on the uses of tax revenues.
Takeaway
In this paper we have analyzed the effect of taxation and corruption on growth, innovation, and entry. First, we have built an endogenous growth model with quality-improving innovations that lead to the new product lines, and then calibrated this model to assess the welfare effects of the interaction between taxation and corruption. Then, using cross-state and then crosscounty panel data from the Longitudinal Business Database (LBD) of the US Census Bureau, we have obtained evidence that is consistent with the theoretical prediction that the effect of taxation on growth and innovation should be increasing and concave, and that higher local corruption should weaken the positive effect of taxation on growth, innovation, and entry. Evidence also suggests this effect operates through entrepreneurial channels consistent with the model’s structure. This paper is a very first step in a broader research agenda on how to factor in growth and innovation considerations in optimal tax design. In particular, there are large debates in the US Congress and among European countries on how progressive the income tax should be and on the desirable corporate tax rate. However, analyses of these issues often do not feature innovation and growth as leading criteria in the design of a desirable tax system. We believe it very important to begin linking the growth and revenue sides of the public ledger to the spending side and the overall effectiveness on how public funds are spent.1
This paper makes several forays into theoretical and empirical dimensions, and we believe we are just scratching the surface of what could be exciting and important research aimed at better linking public finance conditions to entrepreneurship, innovation, and growth.
This model does not allow entrants and incumbents to engage in different types of innovation or to have different step sizes to their innovations (e.g., Akcigit and Kerr 2010). Building these differences into the model would have a larger impact on this part of the calibration and the comparison of entrants and incumbents than on other parts of the model.
Notes
- Philippe Aghion et al., Taxation, corruption, and growth, 86 Eur. Econ. Rev. 24 (2016), https://doi.org/10.1016/j.euroecorev.2016.01.012. Takeaway source: Conclusion, reproduced from a free author or repository copy (working-paper version). ↩
Cite as: Philippe Aghion et al., Taxation, corruption, and growth, 86 Eur. Econ. Rev. 24 (2016), https://doi.org/10.1016/j.euroecorev.2016.01.012
Header image: Ballot Box, North Lyme CT.jpg by John Phelan, CC BY 4.0, via Wikimedia Commons.
