Skip to main content
SpringerLink
Log in

Do fiscal policies affect the firms’ growth and performance? Urban versus rural area

  • Original Paper
  • Published:
Eurasian Economic Review Aims and scope Submit manuscript

Abstract

In this paper, we investigate the effect of the corporate income tax (CIT) on firm performance in the Dominican Republic (DR) by focusing on both the national and regional levels. The analysis is based on data provided by the local authorities of the DR to the World Bank and comprises administrative CIT declarations by over 18,000 firms distributed across 31 provinces for the period from 2006 to 2015. We use propensity score matching method along with some opportunely selected financial indicators as proxies for firm performance. The overall results show that CIT incentives have a positive effect on growth and on most performance indicators; however, significant differences still arise between regions.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1

Our elaboration based on data provided by the local authorities of the DR to the World Bank

Fig. 2

The 10 regions were based on the classification from the Poverty Rate Index of 2016 provided by the World Bank

Fig. 3
Fig. 4
Fig. 5
Fig. 6

Similar content being viewed by others

Availability of data and material

The authors declare that the data are not available.

Code availability

The authors declare that the codes are not available.

Notes

  1. United Nations Conference on Trade and Development.

  2. See Table 2 for a detailed province specification.

  3. The treatment variable (corporate income tax) is included as a delayed variable at time t- 1.

  4. We also conducted chi-square tests but do not present those results for brevity; they are available upon request.

  5. The estimations are computed using the Psmatch2 -Stata command from Leuven and Sianesi (2003).

  6. The percentage of bias is defined as the difference of sample means in the treated and matched control sub-samples as a percentage of the square root of the sample variances average in both groups (formulae from Rosenbaum and Rubin, 1985). See also pstest command in Stata, Leuven and Sianesi, 2003.

  7. The test results are available upon request.

  8. The analysis is performed using the pstest command by Leuven and Sianesi, (2003).

  9. “The pseudo-R2 indicates how well the regressors X explain the participation probability. After matching there should be no systematic differences in the distribution of covariates between both groups and therefore, the pseudo-R2 should be fairly low” (Caliendo and Kopeinig, 2008, p. 49). See also Sianesi (2004) for a discussion.

  10. See also pstest command in Stata, Leuven and Sianesi, (2003).

References

  • Aharoni, Y. (1996). The Foreign Investment Decision Process (pp. 1–392). Harvard Business School, Boston.

  • Alfonso, O., & Silva, A. (2012). Non-scale endogenous growth effects of subsidies for exporters. Economic Modeling, 29, 1248–1257.

    Article  Google Scholar 

  • Arnold, J., Mattoo, A., & Narciso, G. (2008). Services inputs and firm productivity in Sub-Saharan Africa: Evidence from firm-level data. Journal of African Economies, 17(4), 578–599.

    Article  Google Scholar 

  • Asimakopoulos, I., Samitas, A., & Papadogonas, T. (2009). Firm-specific and economy wide deter- minants of firm profitability: Greek evidence using panel data. Managerial Finance, 35(11), 930–939.

  • Barney, J. (1991). Firm resources and sustained competitive advantage. Journal of Management, 17(1), 99–120.

    Article  Google Scholar 

  • Bernini, C., & Pellegrini, G. (2011). How are growth and productivity in private firms affected by public subsidy? Evidence from a regional policy. Regional Science and Urban Economics, 41, 253–265.

    Article  Google Scholar 

  • Bernstein, J., & Shah, A. (1994). Taxes and production: The case of Pakistan. International Tax and Public Finance, 1, 227–245.

    Article  Google Scholar 

  • Biggs, P. (2007). Tax incentives to attract FDI. In Paper presented at UNCTAD Conference Geneva

  • Boarnet, M. G. (2001). Enterprise zones and job creation: Linking evaluation and practice. Economic Development Quarterly, 15, 242–254.

    Article  Google Scholar 

  • Bondonio, D., & Engberg, J. (2000). Enterprise zones and local employment: Evidence from the states programs. Regional Science and Urban Economics, 30, 519–549.

    Article  Google Scholar 

  • Bondonio, D., & Greenbaum, R. (2007). Do local tax incentives affect economic growth? What mean impacts miss in the analysis of enterprise zone policies. Regional Science and Urban Economics, 37(1), 121–136.

    Article  Google Scholar 

  • Bora, B. (2002). Investment Distortions and the International Policy Architecture. World Trade Organisation, Working Paper, Geneva.

  • Briozzo, A., & Cardone-Riportella, C. (2016). Spanish SMEs subsidized and guaranteed credit during economic crisis: A regional perspective. Regional Studies, 150(3), 496–512.

    Article  Google Scholar 

  • Brodzicki, T., & Golejewska, A. (2019). Firms’ innovation performance and the role of the metropolitan location. Evidence from the European periphery. Entrepreneurship and Regional Development, 31(9–10), 908–929.

    Article  Google Scholar 

  • Bronzini, R., & Di Blasio, G. (2006). Evaluating the impact of investment incentives: The case of Italy’s Law 488/1992. Journal of Urban Economics, 60(2), 327–349.

    Article  Google Scholar 

  • Busso, M. & Kline, P. (2008). Do Local Economic Development Programs Work? Evidence from the Federal Empowerment Zone Program, Economics Department Working Paper, No. 36. Yale University.

  • Caliendo, M., & Kopeinig, S. (2008). Some pratical guidance for the implementation of propensity score matching. Journal of Economic Surveys, 22(1), 31–72.

    Article  Google Scholar 

  • Carlucci, C., Pellegrini, G. (2005). Non parametric analysis of the effects on employment of public subsidies to capital accumulation: the case of law 488/92 in Italy, Presented at the Congress AIEL 2004, Modena.

  • Clarke, G. (2012). Manufacturing Firms in Africa: Some Stylized Facts about Wages and Productivity. In H. T. Dinh & G. R. G. Clarke (Eds.), Performance of Manufacturing Firms in Africa: An Empirical Analysis (pp. 47–83). World Bank.

    Chapter  Google Scholar 

  • Cleeve, E. (2008). How effective are fiscal incentives to attract FDI to Sub-Saharan Africa? The Journal of Developing Areas, 42(1), 135–153.

    Article  Google Scholar 

  • Crespo, G., & Clark, R. A. (2012). Analyzing the determinants of profitablity, part 3: Evidence from European manufacturers. Tax Management Transfer Pricing Report, 21(6), 297310. ISSN: 10632069.

    Google Scholar 

  • Czarnitzk, D., Hanel, P., & Rosa, J. M. (2011). Evaluating the impact of R and D tax credits on innovation: A microeconometric study on Canadian firms. Research Policy, 40(2), 217–229.

    Article  Google Scholar 

  • Daly, M., Gorman, I., Lenjosek, G., MacNevin, A., & Phiriyapreunt, W. (1993). The impact of re- gional investment incentives on employment and productivity. Regional Science and Urban Economics, 23, 559–575.

    Article  Google Scholar 

  • Devereux, M. P., Maffini, G., & Xing, J. (2018). Corporate take incentives and capital structure: New evidence from U.K. firm-level tax returns. Journal of Banking and Finance, 88, 250–266.

    Article  Google Scholar 

  • Duch N., Montolio S., & Mediavilla M. (2007). Evaluation the impact of public subsidies on a firm’s performance: A quasi experimental approach, IEB.

  • Dwenger, N., & Steiner, V. (2014). Financial leverage and corporate taxation: Evidence from German corporate tax return data. International Tax and Public Finance, 21(1), 1–28.

    Article  Google Scholar 

  • Faini, R., & Schiantarelli, F. (1987). Incentives and investment decisions: The effectiveness of regional policy. Oxford Economic Papers, 39, 516–533.

    Article  Google Scholar 

  • Fedderke, J. W., & Teubes, B. G. (2011). Fiscal incentives for research and development. Applied Economics, 43(14), 1787–1800.

    Article  Google Scholar 

  • Fernandez-Serrano, J., Martnez-Romn, J. A., & Romero, I. (1987). The entrepreneur in the regional innovation system. A comparative study for high- and low-income regions. Entrepreneurship and Regional Development, 31(5–6), 337–356.

    Google Scholar 

  • Geroski, P. A., & Mason, R. T. (1987). Dynamic market models in industrial organizations. International Journal of Industrial Organization, 5(1), 113.

    Article  Google Scholar 

  • Goddard, J., Tavakoli, M., & Wilson, J. (2005). Determinants of profitability in European manufacturing and services: Evidence from a dynamic panel model. Applied Financial Economics, 15(18), 1269–1282.

    Article  Google Scholar 

  • Gordon, R. H., & Lee, J. (2001). Do taxes a↵ect corporate debt policy? Evidence from U.S. corporate tax returns data. Journal of Public Economics, 82(2), 195–224.

    Article  Google Scholar 

  • Grant, R. M. (1991). A resource-based perspective of competitive advantage. California Management Review, 33(3), 114135.

    Article  Google Scholar 

  • Hanson, A. (2009). Local employment, poverty, and property value effects of geographically-targeted tax incentives: An instrumental variables approach. Regional Science and Urban Economics, 39, 721–731.

    Article  Google Scholar 

  • Harris, R. (1991). The employment creation effects of factor subsidies: Some estimates for Northern Ireland manufacturing, 1955-1983. Journal of Regional Science, 31, 49–64.

    Article  Google Scholar 

  • Heckman, J., LaLonde, R., & Smith, J. (1999). The economics and econometrics of active labor market programs. In O. Ashenfelter, & D. Card (Eds.), Handbook of Labor Economics (Vol. III, pp. 1865–2097). Elsevier, Amsterdam.

  • Julien, P. A. (2019). The regional variations of entrepreneurial dynamism: A mixed methods study. Entrepreneurship & Regional Development, 31(9–10), 874–907.

  • Keefe, O. ’S. (2004). Job creation in California’s enterprise zones: A comparison using a propensity score matching model. Journal of Urban Economics, 55, 131–150.

    Article  Google Scholar 

  • Lee, J. (1996). Government interventions and productivity growth. Journal of Economic Growth, 1(3), 391–414.

    Article  Google Scholar 

  • Leuven, E., & Sianesi, B. (2003). PSMATCH2: Stata Module to Perform Full Mahalanobis and Propensity Score Matching, Common Support Graphing, and Covariate Imbalance Testing,Software, http://ideas.repec.org/c/boc/bocode/s432001.html.

  • Mayende, S. (2013). The effects of tax incentives on firm performance: Evidence from Uganda. Journal of Politics and Law, 6(4), 95–107.

    Article  Google Scholar 

  • Morisset, J., & Pirnia, N. (2000). How Tax Policy and Incentives Affect Foreign Direct Investment : A Review, Policy Research Working Paper, No. 2509. World Bank, Washington, DC. © World Bank. pp. 1–30. https://openknowledge.worldbank.org/handle/10986/19742. License: CC BY 3.0 IGO

  • Peteraf, M. A. (1993). The cornerstones of competitive advantage: A resource-based view. Strategic Management Journal, 14(3), 179–191.

    Article  Google Scholar 

  • Porter, M. (1979). The structure within industries and companies perform. Economics and Statistics, 61(2), 214–227.

    Article  Google Scholar 

  • Rajagopal, D., & Shah, A. (1992). Tax incentive market power and corporate Investment. A rational expectation model applied to Pakistani and Turkish Industries, Policy Research Working Paper Series 908, The World Bank.

  • Rapuluchukwu, E. U., Belmondo, T.V., & Ibukun, B. (2016). Incentives and Firms Productivity: Exploring Multidimensional Fiscal Incentives in a Developing Country, OCP Policy Center, Research paper.

  • Rosembaum, P. R. (1985). Constructing a control group using multivariate matched sampling methods that incorporate the propensity score. The American Statistican, 39, 33–38.

    Google Scholar 

  • Rosembaum, P. R., & Rubin, D. B. (1983). The central role of the propensity score in observational studies for causal effects. Biometrika, 70(1), 41–55.

    Article  Google Scholar 

  • Rubin, D. (1977). Assignment to treatment group on the basis of a covariate. Journal of Educational and Behavioral Statistics, 2(1), 1–26.

    Article  Google Scholar 

  • Sianesi, B. (2004). An evaluation of the active labour market programmes in Sweden. The Review of Economics and Statistics, 86(1), 133–155.

    Article  Google Scholar 

  • Squires, G., & Hall, S. (2013). esson (un)learning in spatially targeted fiscal incentive policy: Enterprise Zones (England) and Empowerment Zones (United States). Land Use Policy, 33, 81–89.

    Article  Google Scholar 

  • UNCTAD. (2004). Incentives. UNCTAD.

    Google Scholar 

  • UNCTAD. (2015). Broadening the sources of growth in Africa: The role of investment. UNCTAD.

    Google Scholar 

  • World Bank. (2017). Dominican republic gearing up for a more efficient tax system: an assessment of tax efficiency, a cost-benefit analysis of tax expenditures, and an exploration of labor informality and its tax implications. World Bank, Washington, DC. © World Bank. https://openknowledge.worldbank.org/handle/10986/29394. License: CC BY 3.0 IGO.

  • Zeli, A., & Mariani, P. (2009). Productivity and profitability analysis of large Italian companies: 1998-2002. International Review of Economics, 56(2), 175–188.

    Article  Google Scholar 

Download references

Funding

This research received no external funding.

Author information

Authors and Affiliations

  1. Department of Economics and Statistics, University of Salerno, Fisciano, SA, Italy

    Alessandra Amendola & Marinella Boccia

  2. World Bank, Washington, USA

    Gianluca Mele

  3. Department of Management and Innovation Systems, DISA-MIS, University of Salerno, Fisciano, SA, Italy

    Luca Sensini

Authors
  1. Alessandra Amendola
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Marinella Boccia
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Gianluca Mele
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Luca Sensini
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Marinella Boccia.

Ethics declarations

Conflict of interest

The authors declare no conflict of interest.

Ethical approval

This article does not contain any studies with human participants or animals performed by any of the authors.

Consent to participate

The authors declare their consent to participate.

Consent for publication

The authors declare their consent for publication.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Appendix

Appendix

See Table 11.

Table 11 Number of Treated and Non-Treated Units by Region
Full size table

Rights and permissions

Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Amendola, A., Boccia, M., Mele, G. et al. Do fiscal policies affect the firms’ growth and performance? Urban versus rural area. Eurasian Econ Rev 13, 1–33 (2023). https://doi.org/10.1007/s40822-022-00223-7

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s40822-022-00223-7

Keywords

JEL Classification

Search

Navigation