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Business Income Tax from Profit-Seeking Enterprises and Spatial Autocorrelation: Do Local Economic Characteristics Matter?

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  • Hao-Chen Huang

    (Department of Public Finance and Taxation, National Kaohsiung University of Science and Technology, Kaohsiung 824303, Taiwan)

  • Chin-Fu Hung

    (Ph.D. Program in Business Intelligence School, National Kaohsiung University of Science and Technology, Kaohsiung 824303, Taiwan)

  • Chi-Lu Peng

    (Department of Public Finance and Taxation, National Kaohsiung University of Science and Technology, Kaohsiung 824303, Taiwan)

  • Ting-Hsiu Liao

    (Graduate Institute of Tourism Management, National Kaohsiung University of Hospitality and Tourism, Kaohsiung 81271, Taiwan)

Abstract

We seek to explore whether local economic characteristics affect the collection of profit-seeking enterprise (PSE) income tax in Taiwan, by adopting panel data from 2001 to 2020 collected in its counties and cities. The results of this analysis of spatial econometric modeling indicate that the increase in sales of profit-seeking enterprises (SPSE) has a positive and significant direct effect on the collection of PSE income tax in this county and city. In terms of spatial spillover effects, when the number of profit-seeking enterprises (NPSE) in neighboring regions increases and the percentage of employees working in industrial sectors (PEI) increases, they will then impact the increase in PSE income tax collection in any particular county and city. We find that the amount of PSE income tax collection relates to the agglomeration economy. The findings of this study may be provided as a reference for local governments to conduct administrative construction on the formulation of PSE income tax collection.

Suggested Citation

  • Hao-Chen Huang & Chin-Fu Hung & Chi-Lu Peng & Ting-Hsiu Liao, 2022. "Business Income Tax from Profit-Seeking Enterprises and Spatial Autocorrelation: Do Local Economic Characteristics Matter?," Land, MDPI, vol. 11(9), pages 1-18, September.
    • Handle: RePEc:gam:jlands:v:11:y:2022:i:9:p:1533-:d:911908
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    1. Quentin Frère & Matthieu Leprince & Sonia Paty, 2014. "The Impact of Intermunicipal Cooperation on Local Public Spending," Urban Studies, Urban Studies Journal Limited, vol. 51(8), pages 1741-1760, June.
    2. Schmidheiny, Kurt, 2006. "Income segregation and local progressive taxation: Empirical evidence from Switzerland," Journal of Public Economics, Elsevier, vol. 90(3), pages 429-458, February.
    3. Liao, Wen-Chi & Wang, Xizhu, 2012. "Hedonic house prices and spatial quantile regression," Journal of Housing Economics, Elsevier, vol. 21(1), pages 16-27.
    4. Harris, Richard D. F. & Tzavalis, Elias, 1999. "Inference for unit roots in dynamic panels where the time dimension is fixed," Journal of Econometrics, Elsevier, vol. 91(2), pages 201-226, August.
    5. Kameda, Taisuke & Namba, Ryoichi & Tsuruga, Takayuki, 2021. "Decomposing local fiscal multipliers: Evidence from Japan," Japan and the World Economy, Elsevier, vol. 57(C).
    6. Simon Loretz & Padraig Moore, 2013. "Corporate tax competition between firms," International Tax and Public Finance, Springer;International Institute of Public Finance, vol. 20(5), pages 725-752, October.
    7. Alexander Klemm & Stefan Parys, 2012. "Empirical evidence on the effects of tax incentives," International Tax and Public Finance, Springer;International Institute of Public Finance, vol. 19(3), pages 393-423, June.
    8. Xiao Cheng & Yanping Pu, 2017. "Effective Tax Rates, Spatial Spillover, and Economic Growth in China: An Empirical Study Based on the Spatial Durbin Model," Annals of Economics and Finance, Society for AEF, vol. 18(1), pages 73-97, May.
    9. Pereira, Alfredo Marvao & Roca-Sagales, Oriol, 2003. "Spillover effects of public capital formation: evidence from the Spanish regions," Journal of Urban Economics, Elsevier, vol. 53(2), pages 238-256, March.
    10. Yawei Qi & Wenxiang Peng & Neal N. Xiong, 2020. "The Effects of Fiscal and Tax Incentives on Regional Innovation Capability: Text Extraction Based on Python," Mathematics, MDPI, vol. 8(7), pages 1-19, July.
    11. Min Hwang & John M. Quigley, 2006. "Economic Fundamentals In Local Housing Markets: Evidence From U.S. Metropolitan Regions," Journal of Regional Science, Wiley Blackwell, vol. 46(3), pages 425-453, August.
    12. Jeffrey P. Cohen & Catherine J. Morrison Paul, 2004. "Public Infrastructure Investment, Interstate Spatial Spillovers, and Manufacturing Costs," The Review of Economics and Statistics, MIT Press, vol. 86(2), pages 551-560, May.
    13. Yong Tu & Hua Sun & Shi-Ming Yu, 2007. "Spatial Autocorrelations and Urban Housing Market Segmentation," The Journal of Real Estate Finance and Economics, Springer, vol. 34(3), pages 385-406, April.
    14. Jaakko Simonen & Rauli Svento & Artti Juutinen, 2015. "Specialization and diversity as drivers of economic growth: Evidence from High-Tech industries," Papers in Regional Science, Wiley Blackwell, vol. 94(2), pages 229-247, June.
    15. Fan, Songmei & Yan, Jingjing & Sha, Jinghua, 2017. "Innovation and economic growth in the mining industry: Evidence from China's listed companies," Resources Policy, Elsevier, vol. 54(C), pages 25-42.
    16. Sotiris Karkalakos & Christos Kotsogiannis, 2007. "A spatial analysis of provincial corporate income tax responses: evidence from Canada," Canadian Journal of Economics/Revue canadienne d'économique, John Wiley & Sons, vol. 40(3), pages 782-811, August.
    17. Zhao, Jingfeng & Tang, Jianmin, 2018. "Industrial structure change and economic growth: A China-Russia comparison," China Economic Review, Elsevier, vol. 47(C), pages 219-233.
    18. Ismaëlh Cissé & Jean Dubé & Cédric Brunelle, 2020. "New business location: how local characteristics influence individual location decision?," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 64(1), pages 185-214, February.
    19. Lu, Chien-Lin & Liao, Wen-Chi & Peng, Chien-Wen, 2020. "Developers’ perspectives on timing to build: Evidence from microdata of land acquisition and development," Journal of Housing Economics, Elsevier, vol. 49(C).
    20. Levin, Andrew & Lin, Chien-Fu & James Chu, Chia-Shang, 2002. "Unit root tests in panel data: asymptotic and finite-sample properties," Journal of Econometrics, Elsevier, vol. 108(1), pages 1-24, May.
    21. Sergio Rey & Brett Montouri, 1999. "US Regional Income Convergence: A Spatial Econometric Perspective," Regional Studies, Taylor & Francis Journals, vol. 33(2), pages 143-156.
    22. Elhorst, J. Paul & Emili, Silvia, 2022. "A spatial econometric multivariate model of Okun's law," Regional Science and Urban Economics, Elsevier, vol. 93(C).
    23. Fernando A. López & Pedro J. Martínez-Ortiz & Juan-Gabriel Cegarra-Navarro, 2017. "Spatial spillovers in public expenditure on a municipal level in Spain," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 58(1), pages 39-65, January.
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