Araştırma Makalesi
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The Effects of Power Infrastructure Quality on Manufacturing Industry Performance: A Panel Data Analysis on World Bank Enterprise Surveysand HAMAS

Yıl 2018, Cilt: 18 Sayı: 4, 685 - 698, 23.10.2018

Öz

This study examines how the power infrastructure quality affects manufacturing industry firms’ performance. To this end, panel data analysis is conducted on World Bank Enterprise Surveys, in which data of one hundred and thirty one thousand firms from one hundred and thirty nine countries covering years 2006–2017 is compiled. While performance and infrastructure indicators provided in the surveys for manufacturing industry firms are used as dependent and independent variables, respectively, some of the indicators related with finance, technology and firm characteristics are included to the analyses as explanatory variables. Empirical findings suggest negative and statistically significant effect of poor power infrastructure quality on capacity usage, an indicator of firm performance. Moreover, it is also found that unreliability on power infrastructure quality leads to increase in labor efficiency of the middle scale companies as well as of all the companies in middle-income countries.

Kaynakça

  • Albala-Bertrand, J. M. ve Mamatzakis, E. C. (2004). The impact of public infrastructure on the productivity of the Chilean economy. Review of Development Economics, 8(2), 266-278.
  • Aschauer, D. A. (1989). Is public expenditure productive? Journal of Monetary Economics, 23(2), 177-200.
  • Baltagi, B. (2005). Econometric Analysis of Panel Data, 3rd Edition, John Wiley & Sons.
  • Bartelsman, E. J. ve Doms, M. (2000). Understanding productivity: Lessons from longitudinal microdata. Journal of Economic Literature, 38(3), 569-594.
  • Bartlesman, E. ve Gray, W. B. (1996). The NBER manufacturing productivity database. NBER Technical Working Paper 205.
  • Black, S. E. ve Lynch, L. M. (2001). How to compete: the impact of workplace practices and information technology on productivity. Review of Economics and Statistics, 83(3), 434-445.
  • Bloom, N., Kretschmer, T., ve Van Reenan, J. (2009). Work-life balance, management practices and productivity. Richard B. Freeman ve Kathryn L. Shaw (Ed.), International differences in the business practices and productivity of firms (ss. 15-54). University of Chicago Press.
  • Breusch, T. S., ve Pagan, A. R. (1980). The Lagrange multiplier test and its applications to model specification in econometrics. The Review of Economic Studies, 47(1), 239-253.
  • Duggal, V. G., Saltzman, C., ve Klein, L. R. (1999). Infrastructure and productivity: a nonlinear approach. Journal of Econometrics, 92(1), 47-74.
  • Dunne, T., Foster, L., Haltiwanger, J., ve Troske, K. R. (2004). Wage and productivity dispersion in united states manufacturing: The role of computer investment. Journal of Labor Economics, 22(2), 397429.
  • Fisher-Vanden, K., Mansur, E. T., ve Wang, Q. J. (2015). Electricity shortages and firm productivity: evidence from China’s industrial firms. Journal of Development Economics, 114, 172-188.
  • Fowowe, B. (2017). Access to finance and firm performance: Evidence from African countries. Review of Development Finance, 7(1), 6-17.
  • Goddard, J., Tavakoli, M. ve Wilson J. (2005). Determinants of profitability in European manufacturing and services: Evidence from a dynamic panel model. Applied Financial Economics, 15(18), 1269-1282.
  • Goedhuys, M., Janz, N., ve Mohnen, P. (2008). What drives productivity in Tanzanian manufacturing firms: Technology or business environment? The European Journal of Development Research, 20(2), 199-218.
  • Haider, S., ve Ganaie, A. A. (2017). Does energy efficiency enhance total factor productivity in case of India? OPEC Energy Review, 41(2), 153-163.
  • Hausman, J. A. (1978). Specification tests in econometrics. Econometrica, 46(6), 1251-1271.
  • Hoechle, D. (2007). Robust standard errors for panel regressions with cross-sectional dependence. Stata Journal, 7(3), 281.
  • International Atomic Energy Agency (2008). Energy indicators for sustainable development: Guidelines and methodologies. Vienna (Austria) IAEA
  • International Energy Agency (2014). World Energy Investment Outlook. Paris: IEA
  • International Energy Agency (2016). World Energy Outlook 2016. Paris: IEA
  • Jarmin, R. S. (1999). Evaluating the impact of manufacturing extension on productivity growth. Journal of Policy Analysis and Management, 18 (1), 99-119.
  • Keller, W., ve Yeaple, S. R. (2009). Multinational enterprises, international trade, and productivity growth: Firm-level evidence from the United State. The Review of Economics and Statistics, 91(4), 821-831.
  • Kılıçaslan, Y., Sickles, R. C., Kayış, A. A., ve Gürel, Y. Ü. (2017). Impact of ICT on the productivity of the firm: Evidence from Turkish manufacturing. Journal of Productivity Analysis, 47(3), 277-289.
  • Leiponen, A. (2000). Competencies, Innovation and Profitability of Firms. Economics of Innovation and New Technology, 9(1), 1-24.
  • Mamatzakis, E. C. (2008). Economic performance and public infrastructure: An application to Greek manufacturing. Bulletin of Economic Research, 60(3), 307-326.
  • Medlock, K. B. (2009). Energy demand theory. Hunt, L. C., ve Evans, J. (Ed.), International Handbook on the Economics of Energy (ss. 89-111). UK: Edward Elgar Publishing.
  • Miketa, A. (2001). Analysis of energy intensity developments in manufacturing sectors in industrialized and developing countries. Energy Policy, 29(10), 769-775.
  • Moyo, B. (2013). Power infrastructure quality and manufacturing productivity in Africa: A firm level analysis. Energy Policy, 61, 1063-1070.
  • Mukherjee, K. (2008). Energy use efficiency in the Indian manufacturing sector: An interstate analysis. Energy Policy, 36(2), 662-672.
  • Özmen, E., Şahinöz, S. ve Yalçın, C. (2012). Profitability, Saving and Investment of Non-Financial Firms in Turkey. Working Paper No, 12/14, Turkey: Central Bank of the Republic of Turkey.
  • Paul, S. (2003). Effects of public infrastructure on cost structure and productivity in the private sector. Economic Record, 79(247), 446-461.
  • Pesaran, M.H. (2006). Estimation and inference in large heterogeneous panels with a multifactor error structure. Econometrica, 74(4), 967-1012.
  • Ratnayake, R. (2000). Manufacturing profitability, monopoly power and efficiency in a small economy: implications on competition policies. The Korean Economic Review, 16(1), 149-163.
  • Reddy, B. S. ve Ray, B. K. (2010). Decomposition of energy consumption and energy intensity in Indian manufacturing industries. Energy for Sustainable Development, 14(1), 35-47.
  • Sari, R., Ewing, B. T. ve Soytas, U. (2008). The relationship between disaggregate energy consumption and industrial production in the United States: an ARDL approach. Energy Economics, 30(5), 2302-2313.
  • Sidorkin, O. ve Srholec, M. (2014). Surviving the times of crisis: does innovation make a difference? International Journal of Technological Learning, Innovation and Development, 7(2), 124-146.
  • Solow, R. M. (1957). Technical change and the aggregate production function. The Review of Economics and Statistics, 39(3), 312-320.
  • Soytas, U. ve Sari, R. (2007). The relationship between energy and production: evidence from Turkish manufacturing industry. Energy Economics, 29(6), 1151-1165.
  • Trianni, A., Cagno, E., Worrell, E. ve Pugliese, G. (2013). Empirical investigation of energy efficiency barriers in Italian manufacturing SMEs. Energy, 49, 444-458.
  • UN, United Nations (2015). Transforming our world: The 2030 agenda for sustainable development. A/ RES/70/1, 21 October, 2015 Woolridge, J. (2000). Introductory Econometrics: A Modern Approach. USA: South-Western College Publishing
  • Wan, G. ve Zhang, Y. (2017). The direct and indirect effects of infrastructure on firm productivity: Evidence from Chinese manufacturing. China Economic Review (In press).
  • Worrell, E., Laitner, J. A., Ruth, M. ve Finman, H. (2003). Productivity benefits of industrial energy efficiency measures. Energy, 28(11), 1081-1098.
  • Van Biesebroeck, J. (2005). Firm size matters: Growth and productivity growth in African manufacturing. Economic Development and Cultural Change, 53(3), 545-583.

Elektrik Altyapı Kalitesinin İmalat Sanayi Performansına Etkileri: Dünya Bankası İşletme Anketleri Üzerine Bir Panel Veri Analizi

Yıl 2018, Cilt: 18 Sayı: 4, 685 - 698, 23.10.2018

Öz

Bu çalışma elektrik altyapı kalitesinin imalat sanayindeki firma performansını nasıl etkilediğini incelemektedir. Bu bağlamda yüz otuz dokuz ülkeden yaklaşık yüz otuz bir bin firmanın 2006–2017 yılları arasındaki verilerinin derlendiği Dünya Bankası İşletme Anketleri kullanılarak panel veri analizi yapılmıştır. Anketlerde imalat sanayi şirketleri için verilen performans ve altyapı göstergeleri sırasıyla bağımlı ve bağımsız değişkenler; finans, teknoloji ve firma özellikleri ile ilgili göstergelerden bazıları ise açıklayıcı değişkenler olarak analizlere dahil edilmiştir. Ampirik bulgular elektrik altyapı kalitesizliğinin firma performansı göstergelerinden kapasite kullanımına negatif ve istatistiksel olarak anlamlı etkilediğini önermektedir. Ayrıca, orta ölçekli şirketlerde ve orta gelir grubu ülkelerindeki tüm şirketlerde elektrik altyapı kalitesine olan güvensizliğin emek verimliliğinde bir artışa sebebiyet verdiği gözlemlenmiştir.

Kaynakça

  • Albala-Bertrand, J. M. ve Mamatzakis, E. C. (2004). The impact of public infrastructure on the productivity of the Chilean economy. Review of Development Economics, 8(2), 266-278.
  • Aschauer, D. A. (1989). Is public expenditure productive? Journal of Monetary Economics, 23(2), 177-200.
  • Baltagi, B. (2005). Econometric Analysis of Panel Data, 3rd Edition, John Wiley & Sons.
  • Bartelsman, E. J. ve Doms, M. (2000). Understanding productivity: Lessons from longitudinal microdata. Journal of Economic Literature, 38(3), 569-594.
  • Bartlesman, E. ve Gray, W. B. (1996). The NBER manufacturing productivity database. NBER Technical Working Paper 205.
  • Black, S. E. ve Lynch, L. M. (2001). How to compete: the impact of workplace practices and information technology on productivity. Review of Economics and Statistics, 83(3), 434-445.
  • Bloom, N., Kretschmer, T., ve Van Reenan, J. (2009). Work-life balance, management practices and productivity. Richard B. Freeman ve Kathryn L. Shaw (Ed.), International differences in the business practices and productivity of firms (ss. 15-54). University of Chicago Press.
  • Breusch, T. S., ve Pagan, A. R. (1980). The Lagrange multiplier test and its applications to model specification in econometrics. The Review of Economic Studies, 47(1), 239-253.
  • Duggal, V. G., Saltzman, C., ve Klein, L. R. (1999). Infrastructure and productivity: a nonlinear approach. Journal of Econometrics, 92(1), 47-74.
  • Dunne, T., Foster, L., Haltiwanger, J., ve Troske, K. R. (2004). Wage and productivity dispersion in united states manufacturing: The role of computer investment. Journal of Labor Economics, 22(2), 397429.
  • Fisher-Vanden, K., Mansur, E. T., ve Wang, Q. J. (2015). Electricity shortages and firm productivity: evidence from China’s industrial firms. Journal of Development Economics, 114, 172-188.
  • Fowowe, B. (2017). Access to finance and firm performance: Evidence from African countries. Review of Development Finance, 7(1), 6-17.
  • Goddard, J., Tavakoli, M. ve Wilson J. (2005). Determinants of profitability in European manufacturing and services: Evidence from a dynamic panel model. Applied Financial Economics, 15(18), 1269-1282.
  • Goedhuys, M., Janz, N., ve Mohnen, P. (2008). What drives productivity in Tanzanian manufacturing firms: Technology or business environment? The European Journal of Development Research, 20(2), 199-218.
  • Haider, S., ve Ganaie, A. A. (2017). Does energy efficiency enhance total factor productivity in case of India? OPEC Energy Review, 41(2), 153-163.
  • Hausman, J. A. (1978). Specification tests in econometrics. Econometrica, 46(6), 1251-1271.
  • Hoechle, D. (2007). Robust standard errors for panel regressions with cross-sectional dependence. Stata Journal, 7(3), 281.
  • International Atomic Energy Agency (2008). Energy indicators for sustainable development: Guidelines and methodologies. Vienna (Austria) IAEA
  • International Energy Agency (2014). World Energy Investment Outlook. Paris: IEA
  • International Energy Agency (2016). World Energy Outlook 2016. Paris: IEA
  • Jarmin, R. S. (1999). Evaluating the impact of manufacturing extension on productivity growth. Journal of Policy Analysis and Management, 18 (1), 99-119.
  • Keller, W., ve Yeaple, S. R. (2009). Multinational enterprises, international trade, and productivity growth: Firm-level evidence from the United State. The Review of Economics and Statistics, 91(4), 821-831.
  • Kılıçaslan, Y., Sickles, R. C., Kayış, A. A., ve Gürel, Y. Ü. (2017). Impact of ICT on the productivity of the firm: Evidence from Turkish manufacturing. Journal of Productivity Analysis, 47(3), 277-289.
  • Leiponen, A. (2000). Competencies, Innovation and Profitability of Firms. Economics of Innovation and New Technology, 9(1), 1-24.
  • Mamatzakis, E. C. (2008). Economic performance and public infrastructure: An application to Greek manufacturing. Bulletin of Economic Research, 60(3), 307-326.
  • Medlock, K. B. (2009). Energy demand theory. Hunt, L. C., ve Evans, J. (Ed.), International Handbook on the Economics of Energy (ss. 89-111). UK: Edward Elgar Publishing.
  • Miketa, A. (2001). Analysis of energy intensity developments in manufacturing sectors in industrialized and developing countries. Energy Policy, 29(10), 769-775.
  • Moyo, B. (2013). Power infrastructure quality and manufacturing productivity in Africa: A firm level analysis. Energy Policy, 61, 1063-1070.
  • Mukherjee, K. (2008). Energy use efficiency in the Indian manufacturing sector: An interstate analysis. Energy Policy, 36(2), 662-672.
  • Özmen, E., Şahinöz, S. ve Yalçın, C. (2012). Profitability, Saving and Investment of Non-Financial Firms in Turkey. Working Paper No, 12/14, Turkey: Central Bank of the Republic of Turkey.
  • Paul, S. (2003). Effects of public infrastructure on cost structure and productivity in the private sector. Economic Record, 79(247), 446-461.
  • Pesaran, M.H. (2006). Estimation and inference in large heterogeneous panels with a multifactor error structure. Econometrica, 74(4), 967-1012.
  • Ratnayake, R. (2000). Manufacturing profitability, monopoly power and efficiency in a small economy: implications on competition policies. The Korean Economic Review, 16(1), 149-163.
  • Reddy, B. S. ve Ray, B. K. (2010). Decomposition of energy consumption and energy intensity in Indian manufacturing industries. Energy for Sustainable Development, 14(1), 35-47.
  • Sari, R., Ewing, B. T. ve Soytas, U. (2008). The relationship between disaggregate energy consumption and industrial production in the United States: an ARDL approach. Energy Economics, 30(5), 2302-2313.
  • Sidorkin, O. ve Srholec, M. (2014). Surviving the times of crisis: does innovation make a difference? International Journal of Technological Learning, Innovation and Development, 7(2), 124-146.
  • Solow, R. M. (1957). Technical change and the aggregate production function. The Review of Economics and Statistics, 39(3), 312-320.
  • Soytas, U. ve Sari, R. (2007). The relationship between energy and production: evidence from Turkish manufacturing industry. Energy Economics, 29(6), 1151-1165.
  • Trianni, A., Cagno, E., Worrell, E. ve Pugliese, G. (2013). Empirical investigation of energy efficiency barriers in Italian manufacturing SMEs. Energy, 49, 444-458.
  • UN, United Nations (2015). Transforming our world: The 2030 agenda for sustainable development. A/ RES/70/1, 21 October, 2015 Woolridge, J. (2000). Introductory Econometrics: A Modern Approach. USA: South-Western College Publishing
  • Wan, G. ve Zhang, Y. (2017). The direct and indirect effects of infrastructure on firm productivity: Evidence from Chinese manufacturing. China Economic Review (In press).
  • Worrell, E., Laitner, J. A., Ruth, M. ve Finman, H. (2003). Productivity benefits of industrial energy efficiency measures. Energy, 28(11), 1081-1098.
  • Van Biesebroeck, J. (2005). Firm size matters: Growth and productivity growth in African manufacturing. Economic Development and Cultural Change, 53(3), 545-583.
Toplam 43 adet kaynakça vardır.

Ayrıntılar

Birincil Dil Türkçe
Bölüm Araştırma Makalesi
Yazarlar

İstemi Berk 0000-0003-3507-2293

Yayımlanma Tarihi 23 Ekim 2018
Kabul Tarihi 10 Temmuz 2018
Yayımlandığı Sayı Yıl 2018 Cilt: 18 Sayı: 4

Kaynak Göster

APA Berk, İ. (2018). Elektrik Altyapı Kalitesinin İmalat Sanayi Performansına Etkileri: Dünya Bankası İşletme Anketleri Üzerine Bir Panel Veri Analizi. Ege Academic Review, 18(4), 685-698.
AMA Berk İ. Elektrik Altyapı Kalitesinin İmalat Sanayi Performansına Etkileri: Dünya Bankası İşletme Anketleri Üzerine Bir Panel Veri Analizi. eab. Ekim 2018;18(4):685-698.
Chicago Berk, İstemi. “Elektrik Altyapı Kalitesinin İmalat Sanayi Performansına Etkileri: Dünya Bankası İşletme Anketleri Üzerine Bir Panel Veri Analizi”. Ege Academic Review 18, sy. 4 (Ekim 2018): 685-98.
EndNote Berk İ (01 Ekim 2018) Elektrik Altyapı Kalitesinin İmalat Sanayi Performansına Etkileri: Dünya Bankası İşletme Anketleri Üzerine Bir Panel Veri Analizi. Ege Academic Review 18 4 685–698.
IEEE İ. Berk, “Elektrik Altyapı Kalitesinin İmalat Sanayi Performansına Etkileri: Dünya Bankası İşletme Anketleri Üzerine Bir Panel Veri Analizi”, eab, c. 18, sy. 4, ss. 685–698, 2018.
ISNAD Berk, İstemi. “Elektrik Altyapı Kalitesinin İmalat Sanayi Performansına Etkileri: Dünya Bankası İşletme Anketleri Üzerine Bir Panel Veri Analizi”. Ege Academic Review 18/4 (Ekim 2018), 685-698.
JAMA Berk İ. Elektrik Altyapı Kalitesinin İmalat Sanayi Performansına Etkileri: Dünya Bankası İşletme Anketleri Üzerine Bir Panel Veri Analizi. eab. 2018;18:685–698.
MLA Berk, İstemi. “Elektrik Altyapı Kalitesinin İmalat Sanayi Performansına Etkileri: Dünya Bankası İşletme Anketleri Üzerine Bir Panel Veri Analizi”. Ege Academic Review, c. 18, sy. 4, 2018, ss. 685-98.
Vancouver Berk İ. Elektrik Altyapı Kalitesinin İmalat Sanayi Performansına Etkileri: Dünya Bankası İşletme Anketleri Üzerine Bir Panel Veri Analizi. eab. 2018;18(4):685-98.