Total Factor Productivity in OECD Countries: A Panel Data Application with Stochastic Frontier Approach

Year 2021, Volume: 23 Issue: 3, 1108 - 1147, 31.12.2021

Nadide Yiğiteli , Fahriye Öztürk

https://doi.org/10.26745/ahbvuibfd.875248

Cited By: 1

Abstract

Productivity, the fundamental element of sustainable growth, is the term that expresses the level of efficient and effective use of labor, capital and other production factors. This term is an indicator of the ability of economic units to transform their input into output. Considering large and increasing differences between countries in terms of per capita income and factor accumulations that cannot fully explain these differences, productivity growth plays a dominant role for sustainable economic growth. In this study, the total factor productivity (TFP) growth and its components were calculated with a panel data set that includes 28 OECD countries for the period 1970-2017 by using a stochastic frontier analysis. It was determined that the average annual increase of TFP was 0.13% during the analysis period. The annual average productivity declined in the years of the 1970s and the early 1980s. It also decreased in 2008 and 2009 when the global crisis was experienced. The deepest decline was seen in 2009 with 2.25%. The growth in TFP is mainly dependent on technological progress rather than improvements in technical efficiency and scale efficiency. Another finding of the study is that countries with higher per capita income are also dominant in technological progress.

Keywords

Stochastic Frontier Analysis, Total Factor Productivity, Efficiency, Productivity, Economic Growth

OECD Ülkelerinde Toplam Faktör Verimliliği: Stokastik Sınır Yaklaşımı ile Bir Panel Veri Uygulaması

Abstract

Sürdürülebilir büyümenin temel unsuru olan verimlilik, en yalın haliyle, emek, sermaye ve diğer üretim faktörlerinin ne düzeyde etkin ve etkili kullanıldığını ifade eden bir kavramdır. Bu kavram, ekonomik birimlerin girdilerini çıktıya dönüştürme kabiliyetinin bir göstergesidir. Kişi başı gelir düzeyi açısından ülkeler arasında büyük ve artan farklılıkların olduğu ve faktör birikimlerinin bu farklılıkları tam olarak açıklayamadığı dikkate alındığında, sürdürülebilir ekonomik büyüme için verimlilik artışı başat bir rol oynamaktadır. Çalışmada, toplam faktör verimliliği (TFV) büyümesi ve bileşenleri, 1970-2017 dönemine ilişkin olarak 28 OECD ülkesini içeren panel veri seti ve stokastik sınır analizi (SSA) yaklaşımıyla hesaplanmıştır. TFV’de, analiz döneminde panel geneli için yıllık ortama %0,13 oranında artış meydana geldiği tespit edilmiştir. 1970’li ve 1980’li yılların başı ile küresel krizin yaşandığı 2008 ve 2009 yıllarında yıllık ortalama verimlilik düşüşü yaşandığı, en derin düşüşün ise %2,25 ile 2009 yılında ortaya çıktığı görülmektedir. TFV'deki büyümenin, teknik etkinlik ve ölçek etkinliğindeki iyileşmelerden çok, büyük ölçüde teknolojik ilerlemeye bağlı olduğu; yüksek kişi başı gelir düzeyine sahip ülkelerin de bu noktada hakim konumda olduğu çalışmada tespit edilen diğer bulgulardandır.

Keywords

Stokastik Sınır Analizi, Toplam Faktör Verimliliği, Etkinlik, Verimlilik, Ekonomik Büyüme

References

• Abramovitz, M. (1956). “Resource and output trends in the United States since 1870”. The American Economic Review, 46(2), 5-23.
• Aguiar, D., Costa, L., & Silva, E. (2017). "An attempt to explain differences in economic growth: A stochastic frontier approach". Bulletin of Economic Research, 4, E42-E65.
• Ahmadzai, H. (2017). "Crop diversification and technical efficiency in Afghanistan: Stochastic frontier analysis". CREDIT Research Paper, 17(04).
• Arcelus, F. J., & Arocena, P. (2000). "Convergence and productive effciency in fourteen OECD countries: A non-parametric frontier approach". International Journal of Production Economics, 66(2), 105-117.
• Archibugil, D. &Michie, J. (1998). “Technical change, growth snd trade: New departures in institutional economics”. Journal of Economic Surveys, 12(3), 313-332.
• Barro, R. J. & Lee, J. W. (2013). “A new data set of educational attainment in the world, 1950–2010". Journal of Development Economics, 104, 184-198. Web: http://www.barrolee.com/ Updated: 2018.
• Battese, G. E., & Coelli, T. J. (1988). "Prediction of firm-level technical efficiencies with a generalized frontier production function and panel data". Journal of Econometrics, 38(3), 387-399.
• Battese, G. E., & Coelli, T. J. (1992). "Frontier production functions, technical efficiency and panel data: With application to paddy farmers in India". Journal of Productivity Analysis, 3(1), 153-169.
• Batttese, G. E., & Coelli, T. J. (1995). "A model for technical inefficiency effects in a stochastic frontier production function for panel data". Empirical Economics, 20(2), 325-332.
• Belotti, F., Daidone, S., Ilardi, G., & Atella, V. (2013). "Stochastic frontier analysis using Stata". The Stata Journal, 13(4), 719-758.
• Bocutoğlu, E. (2012). Karşılaştırmalı makro iktisat: Teoriler ve politikalar. Trabzon: Murathan Yayınevi.
• Bos, J., Economidou, C., Koetter, M., & Kolari, J. (2010). "Do all countries grow alike?" Journal of Development Economics, 91(1), 113-127.
• Caselli, F. (2005). "Accounting for cross-country income differences". Handbook of Economic Growth, 1, 679-741.
• Cohen, D., Leker, L. & Soto, M. (2014). International educational attainment database. Web: (http://www. parisschoolofeconomics. eu/en/cohen-daniel/international-educational-attainment-database/).
• Desli, E., C. Ray, S., & Kumbhakar, S. (2003). A dynamic stochastic frontier production model with time-varying efficiency". Applied Economics Letters, 10(10), 623-626.
• Du, K. (2017). Translog: Stata module to create new variables for a translog function, statistical software components S458318, Boston College Department of Economics. Link: https://ideas.repec.org/c/boc/bocode/s458318.html
• Easterly, W., & Levine, R. (2001). "What have we learned from a decade of empirical research on growth? It's not factor accumulation: Stylized facts and growth models". The World Bank Economic Review, 15(2), 177-219.
• Färe, R., Grosskopf, S., Norris, M., & Zhongyang, Z. (1994). "Productivity growth, technical progress, and efficiency change in industrialized countries". The American Economic Review, 84, 66-83.
• Forstner, H., & Isaksson, A. (2002). "Productivity, technology, and efficiency: An analysis of the world technology frontier; when memory is infinite". Statistics and Information Networks Branch of UNIDO.
• Fuente-Mella, H. d., Vallina-Hernandez, A. M., & Fuentes-Solís, R. (2020). "Stochastic analysis of the economic growth of OECD countries". Economic Research-Ekonomska Istraživanja, 33(1), 2189-2202.
• Golany, B., & Thore, S. (1997). "The economic and social performance of nations: Efficiency and returns to scale". Socio-Economic Planning Sciences, 31(3), 191-294.
• Greene, W. (2005a). "Fixed and random effects in stochastic frontier models". Journal of Productivity Analysis, 23(1), 7-32.
• Greene, W. (2005b). "Reconsidering heterogeneity in panel data estimators of the stochastic frontier model". Journal of Econometrics, 126(2). 269-303.
• Hagemann, H. (2009). "Solow's 1956 contribution in the context of the Harrod-Domar model". History of Political Economy, 41(1). 67-87.
• Hall, R. E., & Jones, C. I. (1999). "Why do some countries produce so much more output per worker than others?". The Quarterly Journal of Economics, 114(1), 83-116.
• Harrod, R. F. (1939). "An essay in dynamic theory". The Economic Journal, 49(193), 14-33.
• Harrod, R. F. (1948). Towards a dynamic economics: some recent developments of economic theory and their application to policy. London: MacMillan and Company,
• Heshmati, A., & Rashidghalam, M. (2020). "Estimation of technical change and TFP growth based on observable technology shifters". Journal of Productivity Analysis, 53, 21-36.
• Hoover, H. C., & L. H. Hoover (1912), Georgius Agricola de re metallica: Translated from the Latin edition of 1556, Reprinted 1950. New York: Dover.
• Hou, Z., Roseta-Palma, C., & Ramalho, J. J. (2020). "Directed technological change, energy and more: A modern story". Environment and Development Economics, 25(6). 611-633.
• Human Capital in PWT 9.0. (n.d.). [ebook] Penn World Table. Available at: http://www.rug.nl/ggdc/docs/human_capital_in_pwt_90.pdf [Erişim: 10/10/2020].
• Jondrow, J., Lovell, C. K., Materov, I. S., & Schmidt, P. (1982). "On the estimation of technical ınefficiency in the stochastic frontier production function model". Journal Of Econometrics, 19(2-3), 233-238.
• Jones, C. (2001). İktisadi büyümeye giriş. (Çev: Ateş, Ş. &Tuncer, İ.). İstanbul: Literatür Yayıncılık.
• Kalirajan, K. P., & Shand, R. T. (1999). "Frontier production functions and technical efficiency measures". Journal of Economic Surveys, 13(2), 149-172.
• Keynes, J. (1936). The general theory of employment, interest and money. Ed: Macmillan London.
• Kim, D. S. (1999). A standardization technique to reduce the problem of multicollinearity in polynomial regression analysis. Link: http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.573.1999&rep=rep1&type= df
• Kim, S., Park, D., & Park, J.-H. (2010). "Productivity growth across the world, 1991-2003". Asian Development Bank Economics Working Paper Series(212).
• Koop, G., Osıewalskı, J., & Steel, M. F. (2000). "A stochastic frontier analysis of output level and growth in Poland and western economies". Economics of Planning, 33(3), 185-202.
• Kök, R. (1991). Endüstriyel verimlilik ve etkinlik-bir uygulama. Yayınlanmamış Doktora Tezi. Atatürk Üniversitesi, Sosyal Bilimler Enstitüsü, Erzurum.
• Kök, R., & Deliktaş , E. (2003). Endüstri İktisadında verimlilik ölçme ve strateji geliştirme teknikleri. İzmir: DEÜ İİBF Yayınları, Yayın Karar No:25-8/1.
• Kumbhakar, S. C. (1990). "Production frontiers, panel data, and time-varying technical inefficiency". Journal of Econometrics, 46(1-2), 201-211.
• Kumbhakar, S. C., & Heshmati, A. (1995). "Efficiency measurement in Swedish dairy farms: an application of rotating panel data, 1976–88. American Journal of Agricultural Economics, 77(3), 660-674.
• Kumbhakar, S. C., Lien, G., & Hardaker, J. B. (2014). "Technical efficiency in competing panel data models: a study of Norwegian grain farming". Journal of Productivity Analysis, 41(2), 321-337.
• Kumbhakar, S., & Lovell, C. (2000). Stochastic frontier analysis. New York: Cambridge University Press.
• Kumbhakar, S. C., Wang, H.-J., & Horncastle, A. P. (2015). A practitioner's guide to stochastic frontier analysis using Stata. New York: Cambridge University Press.
• Kumbhakar, S. C., & Wang, H. J. (2005). "Estimation of growth convergence using a stochastic production frontier approach". Economics Letters, 88(3), 300-305.
• Mahadevan, R. (2004). The Economics of productivity in Asia and Australia. Massachusetts: Edward Elgar Publishing.
• Mankiw, N. G., Phelps, E. S., & Romer, P. M. (1995). "The growth of nations". Brookings Papers on Economic Activity, 1. 275-326.
• Marx, K. (2018). Kapital cilt III: Ekonomi politiğin eleştirisi. (Çev. Selik, M. & Satlıgan, N.), İstanbul: Yordam Kitap.
• Önder, A., Deliktaş, E., & Lenger, A. (2003). "Efficiency in the manufacturing industry of selected provinces in Turkey: A stochastic frontier analysis". Emerging Markets Finance and Trade, 39(2), 98-113.
• Pablo-Romero, M. D. P., & Gómez-Calero, M. D. L. P. (2013). “A Translog production function for the Spanish provinces: Impact of the human and physical capital in economic growth”. Economic Modelling, 32, 77-87.
• Pires , J., & Garcia, F. (2012). "Productivity of nations: A stochastic frontier approach to TFP Decomposition". Economics Research International(Article ID 584869), 1-20.
• Psacharopoulos, G. (1994). "Returns to investment in education: A global update". World Development, 22(9), 1325-1343.
• Rao, D.S.P. & Coelli, T.J. (1998). "A cross-country analysis of GDP growth catch-up and convergence in productivity and inequality”, Centre for Efficiency and Productivity Analysis (CEPA). Working Paper No. 5/98, University of New England, Australia.
• Reyna, O. (2007). Panel data analysis fixed and random effects using Stata (v. 4.2). Princeton University, 9.
• Ricardo, D. 1951. On the principles of political economy and taxation, Sraffa, P. (ed.), Cambridge, Cambridge University Press.
• Schumpeter, J. (1934). The theory of economic development (trans. R. Opie). Cambridge, MA: Harvard University Press.
• Schumpeter, J. (1950). Capitalism, socialism and democracy (3rd edn b.). New York: HarperPerennial.
• Smith, A.,1976. The wealth of nations. Chicago: The University of Chicago Press,
• Solow, R. M. (1956). "A contribution to the theory of economic growth". The Quarterly Journal of Economics, 70(1), 65-94.
• Solow, R. M. (1957). "Technical change and the aggregate production function". Review of Economics and Statistics, 39(3). 312-320.
• Sweezy, P. (1970). Kapitalizm nereye gidiyor?. (Çev. Kafaoğlu, A. B). İstanbul: Ağaoğlu Yayınevi. Şanlı, D. (2016). "Nitelik uyarlanmış beşeri sermaye endeksi 1976-2013". Bulletin of Economic Theory and Analysis, 1(1), 13-49.
• Wang, H.-J. (2002), “Heteroscedasticity and non-monotonic efficiency effects of a stochastic frontier model,” Journal of Productivity Analysis, 18, 241–53.
• Wang, H.-J., & Ho, C.-W. (2010). "Estimating fixed-effect panel stochastic frontier models by model transformation". Journal of Econometrics, 157(2), 286-296.
• Wooldridge, J. M. (2003). Introductory econometrics-A modern approach. Ohio: Thomson. Mason.