Charting the Course: Total Factor Productivity Trends in Croatia Post-pre-bankruptcy Act
Abstract
The synthetic control method (SCM) is a valuable tool for unbiased pre-bankruptcy reform analysis in economic policy evaluations. This study utilizes SCM to assess the impact of the Financial Operations and Pre-Bankruptcy Settlement Act (AFOPBS) on Croatia's total factor productivity (TFP). Control units and weights were meticulously chosen to construct a synthetic control for Croatia, creating a counterfactual scenario for the reform's absence. The policy's impact was quantified by comparing TFP growth post-policy between Croatia and its synthetic control. Placebo tests confirmed the results' significance, and further validation was achieved through panel difference-in-differences analysis (PDID). Our findings show that the pre-bankruptcy reform in late 2012 effectively reduced the gap between Croatia and its synthetic control throughout the post-treatment years. However, it had two short-term adverse impacts and a subsequent recovery-like phase. These effects were statistically significant and confirmed by cross-validation. In conclusion, Croatia's pre-bankruptcy reform significantly influenced TFP volatility, highlighting SCM's effectiveness in evaluating economic policies, especially those crucial for economic growth
Povzetek
Metoda sintetične kontrole (SCM) je dragoceno orodje za nepristransko analizo reforme pred stečajem pri vrednotenju ekonomskih politik. Ta študija uporablja SCM za oceno vpliva Zakona o finančnem poslovanju in predstečajni poravnavi (AFOPBS) na skupno faktorsko produktivnost (TFP) na Hrvaškem. Kontrolne enote in uteži so bile skrbno izbrane za oblikovanje sintetične kontrole za Hrvaško, s čimer je bil ustvarjen nasprotni scenarij za odsotnost reforme. Vpliv politike je bil količinsko opredeljen s primerjavo rasti skupne faktorske produktivnosti po uvedbi politike med Hrvaško in njeno sintetično kontrolo. Placebo testi so potrdili pomembnost rezultatov, nadaljnja potrditev pa je bila dosežena s panelno analizo razlik v razlikah (PDID). Naše ugotovitve kažejo, da je reforma pred stečajem konec leta 2012 učinkovito zmanjšala razliko med Hrvaško in njeno sintetično kontrolo v vseh letih po izvedbi ukrepa. Vendar je imela dva kratkoročna negativna učinka in poznejšo fazo, podobno okrevanju. Ti učinki so bili statistično značilni in potrjeni z navzkrižnim preverjanjem. Zaključimo lahko, da je hrvaška reforma pred stečajem pomembno vplivala na nestanovitnost skupne faktorske produktivnosti, kar poudarja učinkovitost SCM pri ocenjevanju gospodarskih politik, zlasti tistih, ki so ključne za gospodarsko rast
Downloads
References
Aspects, J. Econ. Lit., 59(2), 391–425. DOI: 10.1257/jel.20191450.
Abadie, A., Gardeazabal, J. (2003). The economic costs of conflict: A case study of the Basque
Country, Am. Econ. Rev., 93, 113–132. DOI: 10.2139/ssrn.293120.
Abadie, A., Diamond, A., Hainmueller, A. J. (2010). Synthetic control methods for
comparative case studies: Estimating the effect of California’s tobacco control program, J.
Am. Stat. Assoc., 105, 493–505. DOI: 10.1198/jasa.2009.ap08746.
Abadie, A., Diamond, A., Hainmueller, J. (2015). Comparative Politics and the Synthetic
Control Method. Am. J. Pol. Sci., 59, 495–510. DOI: 10.2139/ssrn.1950298.
Acemoglu, D., Guerrieri, V. (2008). Capital Deepening and Non-Balanced Economic Growth,
Journal of Political Economy, 116, 467–498. DOI: 10.1086/589523.
Albalate, D., Bel, G., Mazaira-Font, F. A. (2021). Decoupling synthetic control methods to
ensure stability, accuracy, and meaningfulness, SERIEs, 12(1), 549–584. DOI: 10.1007/s13209-021-00242-8.
Aleksanyan, L., Huiban, J. P. (2016). Economic and financial determinants of firm bankruptcy:
evidence from the French food industry, Review of Agricultural, Food and Environmental Studies, 97(2), 89-108. DOI: 10.1007/s41130-2016.
Barro, R. J. (1999). Determinants of Economic Growth: A Cross-Country Empirical Study,
American Political Science Association, 76(6), 1-55. DOI: 10.2307/2585721.
Bodul, D., Vuković, A. (2015). Još jedna reforma stečajnog zakonodavstva – funkcionalizacija
stečajno-pravne zaštite ili placebo efekt?, Zbornik Pravnog fakulteta Sveučilišta u Rijeci, 36(1), 181-212.
Cespedes, J., Thakor, R. T., Yang, K. (2022). The Ex Ante Effect of Bankruptcy Law:
Evidence from Chapter 12, 1-30. DOI: 10.2139/ssrn.4236600.
Cosci, S., and Meliciani, V. (2002). Multiple banking relationships: Evidence from the Italian
experience. Manchester School, 70(0), 37–54. DOI: 10.1111/1467-9957.70.s1.3.
Di Martino, P., Latham, M., Vasta, M. (2020). Bankruptcy Laws Around Europe (1850–2015):
Institutional Change and Institutional Features, Enterprise & Society, 21(4), 1-55. DOI: 10.1017/eso.2019.46.
Dvouletý, O., Srhoj, S., Pantea, S. (2021). Public SME grants and firm performance in
European Union: A systematic review of empirical evidence, Small Business Economics, 57, 243–263. DOI: 10.1007/s11187-019-00306-x.
Ferranti, D., Baumol, W., Malach, M., Pablos-Mendez, A., Tabish, H. and Wu, L. (2012). The Cost
Disease: Why Computers Get Cheaper but Healthcare Doesn't. New Haven, CT: Yale University Press. DOI: 10.12987/9780300188486.
Gonçalves, D., Martins, A. (2016). The Determinants of TFP Growth in the Portuguese
Manufacturing Sector, Boletin Mensan de Economia Portugesa, 9, 47-55.
Groningen Growth and Development Centre (GGDC). (2021). Penn World Table 10.0. Retrieved
from URL: https://www.rug.nl/ggdc/productivity/pwt/pwt-releases/pwt100.
Hiroki, T., Iwatsubo, K., Watkins, C. (2022). Does Firm-Level Productivity Predict Stock
Returns? Pacific-Basin Finance Journal, 72, 1-45. DOI: 10.1016/j.pacfin.2022.101710.
Hurst, E., Pugsley, B. W. (2011). What do Small Businesses Do? Brookings Papers on Economic
Activity, 43(2), 73-142. DOI: 10.1353/eca.2011.0017.
Jensen, M. C. (1986). Agency Costs of Free Cash Flow, Corporate Finance, and Takeovers, The
American Economic Review, 76(2), 323-329.
Köke, J. (2001). Control Transfers in Corporate Germany: Their Frequency, Causes, and
Consequences, EFA 2001 Barcelona Meetings, p. 00-67.
Kreif, N., Grieve, R., Hangartner, D., Turner, A. J., Nikolova, S., Sutton, M. (2016).
Examination of the synthetic control method for evaluating health policies with multiple treated units, Health Econ, 25(12), 1514-1528. DOI: 10.1002/hec.3258.
Lim, Y., Hahn, C. H. (2009). Bankruptcy Policy Reform and Total Factor Productivity
Dynamics in Korea: Evidence from Microdata. In Ito, T., Rose, A. K., eds. Growth and Productivity in East Asia, NBER-East Asia Seminar on Economics, University of Chicago Press, 13: 10-33.
Lin, B., Chen, X. (2018). Is the implementation of the increasing block electricity prices policy
really effective? Evidence-based on the analysis of synthetic control method, Energy,
163(3), 734–750. DOI: 10.1016/j.energy.2018.08.178.
Miao, L., Zhuo, Y., Wang, H., Lyu, B. (2022). Non-Financial Enterprise
Financialization, Product Market Competition, and Total Factor Productivity of Enterprises, SAGE Open, 12(2), 1-15. DOI: 10.1177/21582440221089956.
Misra, B. S. (2019). Determinants of total factor productivity in Indian states, Indian Growth and
Development Review, 13(1), 259–82. DOI: org/10.1108/igdr-01-2019-0008.
Neira, J. (2017). Bankruptcy and Cross-Country Differences in Productivity. Journal of Economic
Behavior & Organization, 157, 1-47. DOI: 10.1016/j.jebo.2017.
Qi, X., Han, Y. (2021). Energy quota trading can achieve energy savings and emission
reduction: Evidence from China’s pilots, Environ. Sci. Pollut. Res., 28(1), 1-28. DOI: 10.1007/s11356-021-14409-0.
Sadeghi, A., Kibler, E. (2022). Do bankruptcy laws matter for entrepreneurship? A Synthetic
Control Method analysis of bankruptcy reform in Finland, Journal of Business Venturing Insights, 18(2), 1-9. DOI: 10.1016/j.jbvi.2022.
Sampaio, B. (2014). Identifying peer states for transportation policy analysis with an application
to New York’s handheld cell phone ban, Transp. A Transp. Sci., 10, 1–14. DOI: 10.1080/18128602.2012.688073.
Schweiger, H. (2011). The impact of state aid for restructuring on the allocation of resources,
EBRD Working Paper No. 127, 1-40. Available at SSRN: https://ssrn.com/abstract=2180457 or http://dx.doi.org/10.2139/ssrn.2180457.
Shao, W., Sun, Y., Bai, X., Naeem, M. A., Taghizadeh-Hesary, F. (2022). Zombie enterprises,
crowding out effect, and total factor productivity: Empirical evidence from Chinese manufacturing listed companies, International Journal of Finance & Economics, 28(4), 4512-4531. DOI: 10.1002/ijfe.
Tamayo, C. (2017). Bankruptcy choice with endogenous financial constraints, Review of Economic
Dynamics, 26, 225-242. DOI: 10.1016/j.red.2017.06.004.
Tomura, Hajime. (2007). Firms Dynamics, Bankruptcy Laws, and Total Factor Productivity, Bank
of Canada Working Paper, 17, 1-10. DOI: 10.34989/swp-2007-17.
Vollrath, D. (2019). Fully Grown: Why a Stagnant Economy Is a Sign of Success. The University of
Chicago Press, Chicago, and London. DOI: 10.7208/Chicago/9780226666143.001.0001.
World Bank. (2023). World Development Indicators. Retrieved from URL: https://datatopics.worldbank.org/world-development-indicators/.
Xia, H., Wu, S. (2021). Effect of the International Tourism Island Policy on Hainan Farmers’
Income and the Urban-rural Income gap: An analysis based on the GPCA and SCM Models. J. Adv. Comput. Intell. Intell. Inform., 25(5), 592–600. DOI: 10.20965/jaciii.2021.p0592.
Yamaguchi, K. (2022). The productivity impact of the government-led bailout of Japan Airlines,
Asian Transport Studies, 8, 1-9. ISSN 2185-5560. DOI: 10.1016/j.eastsj.2022.