Structural fund, endogenous move and commitment

Abstract

In this paper, we extend the study on combined tax and infrastructure competition by endogenizing the timing of decisions made by asymmetric countries. We consider how a structural fund affects the endogenous move decision and show that the poor country prefers to be a follower only when the production function is sufficiently concave. We also analyse the effect of the structural fund on total welfare and design a commitment game to ensure that the socially optimal outcome is achieved.

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Notes

  1. 1.

    In the present paper, we refer to hard and soft infrastructure. Hard infrastructure refers to physical facilities such as transportation and communications networks or electrical power facilities. Soft infrastructure refers to basic institutions that are essential to the functioning of a community, such as health, education, financial and legal systems.

  2. 2.

    The ESIF consists of five main funds working together to support economic development across all the EU countries. These five funds are the European Regional Development Fund, the Cohesion Fund, the European Agricultural Fund for Rural Development, the European Social Fund and the European Maritime and Fisheries Fund.

  3. 3.

    During the period 2014–2020, the Cohesion Fund has assigned EUR 63.4 billion to activities under the trans-European networks (TENs) which includes infrastructure projects under the Connecting Europe Facility. Also encompassed within the Cohesion Fund are investments towards benefiting the environment such as promoting climate change, energy efficiency, the use of renewable energy and strengthening public transport. According to the data from European Commission, Poland, Romania and Czech Republic are the first three countries who receive the most amount of the Cohesion Fund. See https://ec.europa.eu/regional_policy/en/funding/cohesion-fund/ (downloaded July 2, 2020).

  4. 4.

    Source: https://www.europarl.europa.eu/factsheets/en/sheet/96/cohesion-fund, downloaded July 21, 2020.

  5. 5.

    Source: https://cohesiondata.ec.europa.eu/funds/cf, downloaded July 21, 2020.

  6. 6.

    Kempf and Rota-Graziosi (2010) find that leadership by the small region is the risk dominant outcome using the pre-play stage as in Hamilton and Slutsky (1990). However, Hindriks and Nishimura (2015) show that leadership by the large region becomes the risk dominant equilibrium and can even become Pareto superior simply by reversing the form of asymmetry in Kempf and Rota-Graziosi (2010). Ogawa (2013) analyses the role of capital ownership in leadership in tax competition.

  7. 7.

    See Altshuler and Goodspeed (2015) for empirical evidence. Wang (1999) asserts that “it is natural and conceivable that, in a real-world situation of tax-setting, the large region moves first” (p. 974). Baldwin and Krugman (2004) also make the same assumption of the large (core) region’s leadership to show that equilibrium tax rates remain higher in the core region than in the small (periphery). The argument there is that the intuitive leadership by the large region is based on its ability to exploit market power. The large region has greater market power that permits itself to benefit from higher tax rates.

  8. 8.

    Other examples of studies that have used a linear quadratic production function include Bucovetsky (1991, 2009), Peralta and Ypersele (2006) and Itaya et al. (2008).

  9. 9.

    If \(k_{1}=k_{2}=k\), \(g_{1}=g_{2}=g\) and \(S=0\) we have \(F_{2}-F_{1}= \varepsilon k\) and \(\partial F_{2}/\partial k_{2}-\partial F_{1}/\partial k_{1}=\varepsilon\).

  10. 10.

    One interesting implication of this result is that there exists a conflict of interest between the two countries if \(\delta <1\). This opens up the possibility of a conditional transfer where the rich country is trying to induce a certain behaviour by the poor country through the structural fund. This is an interesting possibility but lies outside the scope of this study where we assume that the structural fund is exogenously given.

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Acknowledgements

We appreciate the valuable discussions of this work with the participants of the workshop at Beijing University of Technology (2019). Of course, all eventual mistakes and errors are ours. The project is supported by NSFC (Nos. 71503044 and 71973024), Beijing Social Science Foundation (No. 18YJC017), Huiyuan Excellent Young Scholar (No. 17YQ19) and the Fundamental Research Funds for the Central Universities in UIBE (CXTD11-01).

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Correspondence to Yutao Han.

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Eckel, C., Han, Y., Hynes, K. et al. Structural fund, endogenous move and commitment. Int Tax Public Finance (2021). https://doi.org/10.1007/s10797-020-09641-2

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Keywords

  • Structural fund
  • Endogenous move
  • Commitment
  • Social welfare

JEL Classification

  • H21
  • H73
  • F21
  • C72