Agris on-line Papers in Economics and Informatics

Faculty of Economics and Management CULS Prague, Kamýcká 129, 165 00 Praha - Suchdol

The international peer-reviewed scientific journal, ISSN 1804-1930


Dynamic Effects of Public Investment Support in the Food and Beverage Industries

Jindřich Špička

DOI: 10.7160/aol.2018.100108

Agris on-line Papers in Economics and Informatics, No 1 /2018, March

pp. 91-110

Špička, J. (2018) “Dynamic Effects of Public Investment Support in the Food and Beverage Industries", AGRIS on-line Papers in Economics and Informatics, Vol. 10, No. 1, pp. 91-110. ISSN 1804-1930.DOI 10.7160/aol.2018.100108.

Abstract

Impact evaluation of public investment is essential for policy makers to evaluate the effectiveness of public resource allocation and for company management from various industries to determine whether to participate in grant programmes. This article aims to use statistical and econometrical methods (such as propensity score matching, average treatment effect on treated, difference-in-difference approach and pooled regression with time lags) to evaluate the impacts of investment support from the Rural Development Programme, national sources and the Operational Programme Enterprise and Innovation on selected key economic indicators. This representative case study of 412 companies from the Czech food and beverage industry during the period from 2007-2015 noted some interesting findings, many of which go against previous findings. The food and beverage industry is an important beneficiary of public investment subsidies. Investment support increases investment activity and the size of supported companies. This investment support could lead to a crowdingout effect, which has been revealed in recent studies. Simultaneously, investment support changes the capital structure of participants towards higher use of bank loans and positively affects long-term profitability. However, there were not any significant, positive effects on the intensity of the use of fixed assets and labour productivity, which has been a key impact indicator for programme evaluations. However, research revealed positive dynamic effects of investment support on improving resource efficiency.

Keywords

Treatment effects, impact evaluation, lagged effects, food and beverage industry.

References

  1. Abadie, A. (2005) “Semiparametric Difference-in-Differences Estimators”, The Review of Economic Studies, Vol. 72, No. 1, pp. 1–19. ISSN 0034-6527.
  2. Abadie, A. and Imbens, G.W. (2006) “Large Sample Properties of Matching Estimatorsfor Average Treatment Effects”, Econometrica, Vol. 74, No. 1, pp. 235-267. ISSN 0012-9682. DOI 10.1111/j.1468-0262.2006.00655.x.
  3. Allison, P. D. (2009) “Fixed Effects Regression Models“, Quantitative Applications in the SocialSciences, 07-160, SAGE, London, ISBN 978-07-619-2497-5.
  4. Angrist, J. D., Imbens, G. W. and Rubin, D. B. (1996) “Identification of Causal Effects UsingInstrumental Variables”, Journal of the American Statistical Association, Vol. 91, No. 434, p. 444.ISSN 0162-1459. DOI 10.2307/2291629.
  5. Arellano, M. and Bond, S. (1998) “Dynamic Panel Data Estimation Using DPD98 For Gauss:A Guide for Users”, [Online]. Available: ftp://ftp.cemfi.es/pdf/papers/ma/dpd98.pdf[Accessed: 5 Jan. 2018].
  6. Bartova, L. and Hornakova, J. (2016) “Farm Investment Support in the Slovak Republic”, in Smutka,L., Benda, P., Cermakova, H., Domeova, L., Fejfarova, M., Halova, P., Havlicek, Z., Havlikova, M.,Havranek, M., Hlavsa, T., Lorinczova, E., Lostak, M., Mach, J., Maly, M., Moravec, L., Pilar, L.,Prasilova, M., Prochazkova, R., Rojk, S., Rumankova, L., Slaboch, J., Kristkova, Z., Starova, M.,Sanova, P., Simek, P., Tyrychtr, J., Ulman, M., Urbancova, H., Zagata, L. and Zakova Kroupova,Z. (Eds.), Agrarian Perspectives XXV. - Global and European Challenges For Food Production,Agribusiness and the Rural Economy: Proceedings of the 25th International Scientific Conferenceon Agrarian Perspectives, Prague, Czech Republic, September 14-16, Czech University of LifeSciences, Faculty of Economics and Management, Prague, pp. 34–40. ISBN 978-80-213-2670-5.
  7. Bergemann, A., Fitzenberger, B. and Speckesser, S. (2009) “Evaluating the DynamicEmployment Effects of Training Programs in East Germany Using Conditional Difference-in-Differences”, Journal of Applied Econometrics, Vol. 24, No. 5, pp. 797–823. ISSN 0883-7252. DOI 10.1002/jae.1054.
  8. Bernini, C. and Pellegrini, G. (2011) “How Are Growth and Productivity in Private Firms Affectedby Public Subsidy? Evidence from a Regional Policy”, Regional Science and Urban Economics,Vol. 41, No. 3, pp. 253–265. ISSN 0166-0462. DOI 10.1016/j.regsciurbeco.2011.01.005.
  9. Bertrand, M., Duflo, E. and Mullainathan, S. (2004) “How Much Should We Trust Differences-In-Differences Estimates?”, The Quarterly Journal of Economics, Vol. 119, No. 1, pp. 249–275.ISSN 0033-5533. DOI 10.1162/003355304772839588.
  10. Bia, M. and Mattei, A. (2012) “Assessing the Effect of The Amount of Financial Aids to PiedmontFirms Using the Generalized Propensity Score”, Statistical Methods & Applications, Vol. 21, No. 4,pp. 485–516. ISSN 1618-2510. DOI 10.1007/s10260-012-0193-4.
  11. Bozik, M. (2011) “Hodnotenie efektov opatrení podpory investícií Programu rovoje vidieka2007-2013 na úrovni fariem”, Economics in Agriculture, Vol. 11, No. 1, pp. 58–71. ISSN 1338-6336.
  12. Caliendo, M. and Kopeinig, S. (2008) “Some Practical Guidance for the Implementationof Propensity Score Matching”, Journal of Economic Surveys, Vol. 22, No. 1, pp. 31-72.ISSN 0950-0804. DOI 10.1111/j.1467-6419.2007.00527.x.
  13. Cerqua, A. and Pellegrini, G. (2014) “Do Subsidies to Private Capital Boost Firms' Growth?A Multiple Regression Discontinuity Design Approach”, Journal of Public Economics, Vol. 109,No. January 2014, pp. 114-126. ISSN 0047-2727. DOI 10.1016/j.jpubeco.2013.11.005.
  14. Ciaian, P., Kancs, d. and Michalek, J. (2015) “Investment Crowding-Out. Firm-Level Evidencefrom Germany”, LICOS Discussion Paper, No. 370/2015. [Online]. Available: https://ssrn.com/abstract=2634922. DOI 10.2139/ssrn.2634922.
  15. Decramer, S. and Vanormelingen, S. (2016) “The Effectiveness of Investment Subsidies. Evidencefrom a Regression Discontinuity Design”, Small Business Economics, Vol. 47, No. 4, pp. 1007-1032.ISSN 0921-898X. DOI 10.1007/s11187-016-9749-2.
  16. Duflo, E., Glennerster, R. and Kremer, M. (2008) “Chapter 61 Using Randomization in DevelopmentEconomics Research: A Toolkit”, in Schultz, T. P. and Strauss, J. (Eds.) "Handbook of developmenteconomics", Handbooks in Economics, Vol. 4, North Holland, Amsterdam, London, pp. 3895–3962.ISSN 0169-7218.
  17. European Commission - Directorate-General for Agriculture and Rural Development (2014)“Investment Support under Rural Development Policy: Contract 30-CE-0609852/00-41”, FinalReport, Publications Office of the European Union, Luxembourg.
  18. European Commission - Directorate-General for Agriculture and Rural Development. (2016)“Guidelines: Assessment of RDP Results: How to Prepare for Reporting on Evaluation in 2017:Annex 11 - Fiches For Answering Common Evaluation Questions For Rural DevelopmentProgrammes 2014-2020”, Brussels.
  19. Freel, M. S. (2000) “Do Small Innovating Firms Outperform Non-Innovators?”, Small BusinessEconomics, Vol. 14, No. 3, pp. 195–210. ISSN 0921-898X. DOI 10.1023/A:1008100206266.
  20. Gilligan, D. O. and Hoddinott, J. (2007) “Is There Persistence in the Impact of EmergencyFood Aid? Evidence on Consumption, Food Security, and Assets in Rural Ethiopia”,American Journal of Agricultural Economics, Vol. 89, No. 2, pp. 225–242. ISSN 0002-9092. DOI 10.1111/j.1467-8276.2007.00992.x.
  21. Greene, W. H. (2012), “Econometric Analysis, Pearson Series in Economics”, 7th ed., Internationaled., Pearson Education, Boston.
  22. Gu, X. S. and Rosenbaum, P. R. (1993) “Comparison of Multivariate Matching Methods. Structures,Distances, and Algorithms”, Journal of Computational and Graphical Statistics, Vol. 2, No. 4,p. 405. ISSN 1061-8600. DOI 10.2307/1390693.
  23. Hahn, J., Todd, P. and Klaauw, W. (2001) “Identification and Estimation of Treatment Effectswith a Regression-Discontinuity Design”, Econometrica, Vol. 69, No. 1, pp. 201-209.ISSN 0012-9682.
  24. Harris, R. and Trainor, M. (2005) “Capital Subsidies and their Impact on Total Factor Productivity.Firm-Level Evidence from Northern Ireland”, Journal of Regional Science, Vol. 45, No. 1, pp. 49-74.ISSN 0022-4146. DOI 10.1111/j.0022-4146.2005.00364.x.
  25. Harrison, R., Jaumandreu, J., Mairesse, J. and Peters, B. (2014) “Does Innovation StimulateEmployment? A Firm-Level Analysis Using Comparable Micro-Data from Four EuropeanCountries”, International Journal of Industrial Organization, Vol. 35, No. July 2014, pp. 29-43.ISSN 0167-7187. DOI 10.1016/j.ijindorg.2014.06.001.
  26. Heckman, J., Ichimura, H., Smith, J. and Todd, P. (1998) “Characterizing Selection Bias UsingExperimental Data”, Econometrica, Vol. 66, No. 5, p. 1017. ISSN 0012-9682. DOI 10.2307/2999630.
  27. Ho, D., Imai, K., King, G. and Stuart, E. (2007) “Matching as Nonparametric Preprocessingfor Reducing Model Dependence in Parametric Causal Inference”, Political Analysis, Vol. 15,No. 3, p. 199-236. ISSN 1047-1987. DOI 10.1093/pan/mpl013.
  28. Khandker, S. R., Koolwal, G. B. and Samad, H. A. (2010) “Handbook on impact Evaluation:Quantitative Methods and Practices”, World Bank, Washington, D.C. ISBN 978-0-81213-8028-4.
  29. Kirchweger, S. and Kantelhardt, J. (2015) “The Dynamic Effects of Government-Supported Farm-Investment Activities on Structural Change in Austrian Agriculture”, Land Use Policy, Vol. 48,No. November 2015, pp. 73-93. ISSN 0264-8377. DOI 10.1016/j.landusepol.2015.05.005.
  30. Kirchweger, S., Kantelhardt, J. and Leisch, F. (2015) “Impacts of The Government-SupportedInvestments on The Economic Farm Performance in Austria”, Agricultural Economics (Zemědělskáekonomika), Vol. 61, No. 8, pp. 343-355. ISSN 0139-570X. DOI 10.17221/250/2014-AGRICECON.
  31. Krejcie, R. V. and Morgan, D. W. (1970) “Determining Sample Size for Research Activities”,Educational and Psychological Measurement, Vol. 30, No. 3, pp. 607-610. ISSN 0013-1644. DOI 10.1177/001316447003000308.
  32. Lee, D. S. and Lemieux, T. (2010) “Regression Discontinuity Designs in Economics”, Journalof Economic Literature, Vol. 48, No. 2, pp. 281–355. ISSN 0022-0515. DOI 10.1257/jel.48.2.281.
  33. Medonos, T., Ratinger, T., Hruska, M. and Spicka, J. (2012) “The Assessment of the Effectsof Investment Support Measures of the Rural Development Programmes: the Caseof the Czech Republic”, Agris on-line Papers in Economics and Informatics, Vol. 4, No. 4, pp. 35-48.ISSN 1804-1930.
  34. Michalek, J. (2012) “Counterfactual impact evaluation of EU rural development programmes:Propensity score matching methodology applied to selected EU Member States, Volume 1: A microlevelapproach”, EUR (Luxembourg. Online), Vol. 25421, Publications Office; FAO, Luxembourg,Rome.
  35. Ministry of Agriculture, MoA (2008) “Rural Development Programme of the Czech Republicfor 2007 – 2013”, Prague, Ministry of Agriculture.
  36. Ministry of Industry and Trade, MoIT. (2007) “Operational Programme Enterprise and Innovation”,Prague, Ministry of Industry and Trade.
  37. Naglova, Z., Spicka, J. and Gurtler, M. (2016) “Evaluation of Effects of Investment Supportin the Czech Dairy Industry”, Acta Universitatis Agriculturae et Silviculturae MendelianaeBrunensis, Vol. 64, No. 4, pp. 1345-1351. ISSN 1211-8516. DOI 10.11118/actaun201664041345.
  38. Petrick, M. and Zier, P. (2011) “Regional Employment Impacts of Common Agricultural PolicyMeasures in Eastern Germany. A Difference-in-Differences Approach”, Agricultural Economics,Vol. 42, No. 2, pp. 183-193. ISSN 0169-5150. DOI 10.1111/j.1574-0862.2010.00509.x.
  39. Pufahl, A. and Weiss, C. R. (2009) “Evaluating the effects of farm programmes. Resultsfrom propensity score matching”, European Review of Agricultural Economics, Vol. 36, No. 1,pp. 79-101. ISSN 0165-1587. DOI 10.1093/erae/jbp001.
  40. Ratinger, T., Medonos, T. and Hruska, M. (2013) “An Assessment of the Differentiated Effectsof the Investment Support to Agricultural Modernisation: the Case of the Czech Republic”, Agrison-line Papers in Economics and Informatics, Vol. 5, No. 4, pp. 153–164. ISSN 1804-1930.
  41. Ravallion, M. (2005) “Evaluating Anti-Poverty Programs”, The World Bank.
  42. Rezbova, H. and Skubna, O. (2013) “Analysis of the Impact of Subsidies on Economic Performanceof Agricultural Enterprises in the Czech Republic”, in Smutka, L. and Zagata, L. (Eds.), AgrarianPerspectives XXII. - Development Trends In Agribusiness: Proceedings of the 22th InternationalScientific Conference on Agrarian Perspectives, Prague, Czech Republic, September 17 – 18,Czech University of Life Sciences, Faculty of Economics and Management, Prague, pp. 78–85.ISBN 978-80-213-2419-0.
  43. Rosenbaum, P. R. (1989) “Optimal Matching for Observational Studies”, Journal of the AmericanStatistical Association, Vol. 84, No. 408, p. 1024. ISSN 0162-1459. DOI 10.2307/2290079.
  44. Rosenbaum, P. R. and Rubin, D. B. (1985) “Constructing a Control Group Using MultivariateMatched Sampling Methods That Incorporate the Propensity Score”, The American Statistician,Vol. 39, No. 1, p. 33. ISSN 0003-1305. DOI 10.2307/2683903.
  45. Rudinskaya, T. (2017) “Heterogeneity and Efficiency of Food Processing Companies in the CzechRepublic”, Agricultural Economics (Zemedelska ekonomika), Vol. 63, No. 9, pp. 411-420.ISSN 0139-570X. DOI 10.17221/1/2016-AGRICECON.
  46. Smith, J. A. and Todd, P. E. (2005) “Does Matching Overcome LaLonde's Critique of NonexperimentalEstimators?”, Journal of Econometrics, Vol. 125, No. 1-2, pp. 305–353. ISSN 0304-4076. DOI 10.1016/j.jeconom.2004.04.011.
  47. Spicka, J., Naglova, Z. and Gurtler, M. (2017) “Effects of The Investment Support in the CzechMeat Processing Industry”, Agricultural Economics (Zemedelska ekonomika), Vol. 63, No. 8,pp. 356-369. ISSN 0139-570X. DOI 10.17221/367/2015-AGRICECON.
  48. Spicka, J., Smutka, L. and Selby, R. (2016) “Recent Areas of Innovation Activities in the CzechDairy Industry”, Agricultural Economics (Zemedelska ekonomika), Vol. 61, No. No. 6, pp. 249-264.ISSN 0139-570X. DOI 10.17221/128/2014-AGRICECON.
  49. Svejnar, J. (1995) “The Czech Republic and Economic Transition in Eastern Europe”, San Diego,California, Academic Press, ISBN 0-12-678180-X.
  50. van der Klaauw, W. (2002) “Estimating the Effect of Financial Aid Offers on College Enrollment.A Regression-Discontinuity Approach”, International Economic Review, Vol. 43, No. 4,pp. 1249-1287. ISSN 0020-6598. DOI 10.1111/1468-2354.t01-1-00055.
  51. Wooldridge, J. M. (2016) “Introductory Econometrics: A Modern Approach“, 6th edition, CengageLearning, Boston, MA.

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