Bigerna, Simona and D'Errico, Maria Chiara and Polinori, Paolo (2022): Environmental variables and power firms' productivity: micro panel estimation with time-Invariant variables.
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Abstract
Internal and external institutions play a crucial role in the firms’ decision-making process and their productivity. Along with internal institutional features, such as the corporate ownership structure, external institutions, such as the stringency of market and environmental regulations, shape the framework in which firms operate. This research explores the role of these determinants and their interactions in affecting the productivity changes of the power generating firms in 15 European countries between 2010 and 2016. In a first step, using the firm-level ORBIS dataset, we first the productivity changes over time of power generating companies (NACE Code Rev.2.3511) using the global Malmquist index. Then, in a second step, dynamic panel linear model is applied to investigate how the internal and external institutional variables affect the dynamic of the global Malmquist index. In a preliminary analysis a wide range of tests are performed to detect the presence of outliers, the returns to scale, the correlation among inputs, out- puts and the productivity indexes, the independence between the distribution of the productivity indexes and the second-stage institutional variables. The institutional variables are almost time-invariant, the procedure proposed by Kripfganz and Schwarz (2019) is applied to consistently identify the effects of time invariant variables. This new method provides valuable robustness against wrong assumptions on the exogeneity on the instruments. To capture the interplay among external 54 and internal institutional variables, interaction variables are used. Results highlight the need to fine-tune the environmental regulation with the firm-specific internal features, to avoid hindering firm-level productivity in the power generation sector.
Item Type: | MPRA Paper |
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Commentary on: | Bigerna, Simona and D'Errico, Maria Chiara and Polinori, Paolo (2022): Environmental variables and power firms' productivity: micro panel estimation with time-Invariant variables. |
Original Title: | Environmental variables and power firms' productivity: micro panel estimation with time-Invariant variables |
Language: | English |
Keywords: | Environmental and Market regulation, Time-Invariant Variables, Global Malmquist Index, Electricity Sector |
Subjects: | C - Mathematical and Quantitative Methods > C2 - Single Equation Models ; Single Variables L - Industrial Organization > L5 - Regulation and Industrial Policy L - Industrial Organization > L9 - Industry Studies: Transportation and Utilities O - Economic Development, Innovation, Technological Change, and Growth > O4 - Economic Growth and Aggregate Productivity Q - Agricultural and Natural Resource Economics ; Environmental and Ecological Economics > Q4 - Energy |
Item ID: | 114157 |
Depositing User: | Paolo Polinori |
Date Deposited: | 15 Aug 2022 00:19 |
Last Modified: | 15 Aug 2022 00:19 |
References: | Ackerberg DC, Benkard L, Berry S, Pakes A (2007) Econometric tools for ana- lyzing market outcomes. In Heckman JJ, Leamer EE (ed) Handbook of Econometrics Vol 6, Part A. Horth-Holland, Amsterdam, pp 4171–4276 Ahn, SC, Schmidt P (1995). Efficient estimation of models for dynamic panel data. J Econom 68:5–27. Ajayi V, Weyman-Jones T, Glass A (2017) Cost efficiency and electric- ity market structure: a case study of OECD countries. Energy Econ 65:283–291. Aluchna M, Kaminski B (2017) Ownership structure and company perfor- mance: A panel study from Poland. Baltic J Manag 12:485–502. Ambec S, Lanoie P (2008) Does it pay to be green? A systematic overview. Acad Manag Perspe:45–62. Ambec S, Cohen M, Elgie S, Lanoie P (2013) The Porter hypothesis at 20: can environmental regulation enhance innovation and competitiveness? Rev Environ Econ Policy 7(1):2-22 Arellano M, Bond S (1991) Some Tests of Specification for Panel Data: Monte Carlo Evidence and an Application to Employment Equations. Rev Econ Stud 58(2):277-297 Arocena P, Price CW (2002) Generating efficiency: economic and environmen- tal regulation of public and private electricity generators in Spain. Int J Ind Organ 20(1):41-69 Atkinson SE, Primont D (2002) Stochastic estimation of firm technology, inefficiency, and productivity growth using shadow cost and distance functions. J Econometrics 108(2):203–225. Bahçe S, Taymaz E (2008) The impact of electricity market liberalization in Turkey: “Free consumer” and distributional monopoly cases. Energy Econ 30:1603–1624 Banker RD, Natarajan R (2011) Statistical tests based on DEA efficiency scores. In: Cooper WW, Seiford LM, Zhu J (ed). Handbook on data envelopment analysis, Springer Nature, Switzerland AG, pp. 273-295 Baumol WJ, Oates WE (1988) The Theory of Environmental Policy. Cam- bridge University Press, New York. Beladi H, Chao C (2006) Does privatization improve the environment? Econ Lett 93:343—347 Benedsen M, Nielsen KM (2010) Incentive and entrenchment effects in European ownership. J Bank Finance 34:2212–2229 Bifulco R, Bretschneider S (2001) Estimating school efficiency: A comparison of methods using simulated data. Eco Educ Rev 20(5):417–429. Blundell R, Bond S (1998) Initial conditions and moment restrictions in dynamic panel data models. J Econom 87(1):115-143 Blundell R, Bond SR, Windmeijer F (2001) Estimation in dynamic panel data models: Improving on the performance of the standard gmm estimator. In Baltagi BH, Fomby TF, Hill RC (ed) Nonstationary Panels, Panel Cointegration, and Dynamic Panels (Advances in Econometrics, Vol. 15), Emerald Group Publishing Limited, Bingley, pp. 53-91. https://doi.org/ 10.1016/S0731-9053(00)15003-0 Claessens S, Djankov S, Fan JPH, Lang LHP (2002) Disentangling the incentive and entrenchment effects of large shareholdings. J Finance 57:2741–2771. Daraio C, Simar L, Wilson PW (2018) Central limit theorems for condi- tional efficiency measures and tests of the ‘separability’ condition in non-parametric, two-stage models of production. Econom J 21(2):170- 191 Earnhart D, Lizal L (2006) Effects of ownership and financial performance on corporate environmental performance. J Comparative Econ 34(1):111– 129 Erdogdu E (2011) What happened to efficiency in electricity industries after reforms? Energy Policy 39(10):6551–6560 Fowlie M (2010) Emissions trading, electricity restructuring, and investment in pollution abatement. Am Econ Rev 100(3):837–69 Henisz WJ 2000 The institutional environment for economic growth. Econ Politics 12(1):1-31 Hsiao C, Pesaran MH, Tahmiscioglu AK (2002) Maximum likelihood esti- mation of fixed effects dynamic panel data models covering short time periods. J Econom 109:107–150 Jaffe AB, Newell RG, Stavins RN(2002) Environmental policy and technolog- ical change. Environ Resource Econ 22(1-2):41-70 Johnstone N, Managi S, Rodríguez MC, Haščič I, Fujii H, Souchier M (2017) Environmental policy design, innovation and efficiency gains in electricity generation. Energy Econ 63:106-115 Joskow PL (2008) Lessons learned from the electricity market liberalization. The Energy J 29(SI 2): 9-42 Kneip A., Simar L, Wilson PW (2016) Testing hypothesis in nonparametric models of production. J Bus Econ Stat 34:435-456. Knittel CR, Metaxoglou K, Trindade A (2019) Environmental implications of market structure: Shale gas and electricity markets. Int J Ind Organ 63:511-550 Kozluk T, Zipperer V (2015) Environmental policies and productivity growth. OECD Journal: Econ Stud:155–185 Kripfganz S, Schwarz C (2019) Estimation of linear dynamic panel data models with time-invariant regressors. J Appl Econom 34(4):526-546 Kumbhakar SC, Lovell CAK (2000) Stochastic frontier analysis. Cambridge University Press, Cambridge La Porta,R, Lopez-de-Silanes F, Shleifer A, Vishny RW (1998) Law and finance. J Political Econ 106(6):1113–1155 Levinson A, Taylor MS (2008) Unmasking the pollution haven effect. Inter Econ Review 49: 223-254. https://doi.org/10.1111/j.1468-2354 .2008.00478.x Lin B, Chen X (2020) Environmental regulation and energy-environmental per- formance—Empirical evidence from China’s non-ferrous metals industry. J Environ Manag 269, Article 110722 Mahdiloo M, Ngwenyama O, Scheepers R, Tamaddoni A (2018) Managing emissions allowances of electricity producers to maximize CO2 abate- ment: DEA models for analyzing emissions and allocating emissions allowances. Int J Prod Econ 205:244-255 Mayston DJ (2017) Data envelopment analysis, endogeneity and the quality frontier for public services. Ann Oper Res 250(1):185-203 Montgomery D (1972) Markets in Licenses and Efficient Pollution Control Programs. J Econ Theory 5:395-418 Nakano M, Managi S (2008) Regulatory reforms and productivity: an empirical analysis of the Japanese electricity industry. Energy Policy 36(1):201–209 Nickell S (1981) Biases in dynamic models with fixed effects. Econom 49:1417–1426. OECD, (2005). OECD SME and Entrepreneurship Outlook: 2005. OECD Paris. Pastor JT, Knox Lovell CA (2005) A global Malmquist productivity index. Econ Lett 88(2):266-271 Peyrache A, Coelli T (2009) Testing procedures for detection of linear dependencies in efficiency models. Eur J Oper Res 198(2):647-654 Pollit M (2008) The arguments for and against ownership unbundling of energy transmission networks. Energy Policy 36(2):704–713 Reinhardt FL (2000) Down to earth: Applying business principles to environ- mental management. Harvard Business School Press, Boston Requate T, Unold W (2003) Environmental policy incentives to adopt advanced abatement technology: Will the true ranking please stand up? Eur Econ Rev 47(1):125–146 Shleifer A, Vishny RW (2002) The grabbing hand: Government pathologies and their cures. Harvard University Press, Cambridge Sickles RC, Good DH, Getachew L (2002) Specification of distance func- tions using semi-and nonparametric methods with an application to the dynamic performance of eastern and western European air carriers. J Product Anal 17(1-2):133–155 Simar L, Wilson PW (2000) Statistical inference in nonparametric frontier models: The state of the art. J Product Anal 13:49–78 Simar L, Wilson PW (2002) Non-parametric tests of returns to scale. Eur J Oper Res 139(1):115–132 Simar L, Wilson PW (2020) Hypothesis testing in nonparametric models of production using multiple sample splits. J Product Anal 53:287–303. Song M, Zhu S, Wang J, Zhao J (2020) Share green growth: Regional evaluation of green output performance in China. Int J Prod Econ 219:152-163 Steiner F (2001) Regulation, Industry Structure, and Performance in the Electricity Supply Industry. OECD Econ Stud 32(1):143-182 Triebs TP, Pollitt MG (2019) Objectives and incentives: Evidence from the privatization of Great Britain’s power plants. Int J Ind Organ 65:1-29. Vickers J, Yarrow G (1998) Privatisation: An Economic Analysis. MIT Press, Cambridge Vollebergh HRJ, Van der Werf E (2014) The role of standards in eco- innovation: Lessons for policymakers. Rev Environ Econ Policy 8(2):230- 248 Wang LFS, Wang Y, Zhao L (2009) Privatization and the environment in amixed duopoly with pollution abatement. Econ Bullettin 29(4):3112- 3119 Wang K, Shailer G (2015) Ownership concentration and firm performance in emerging markets: A meta-analysis. J Economic Surv 29(2):199-229 Wang K, Wei YM, Huang Z (2018) Environmental efficiency and abatement efficiency measurements of China's thermal power industry: A data envel- opment analysis based materials balance approach. Eur J Oper Res 269(1):35-50. Wilson PW (1993). Detecting outliers in deterministic nonparametric frontier models with multiple outputs. J Bus Econ Stat 11(3): 319-323. Windmeijer F (2005) A finite sample correction for the variance of linear efficient two-step GMM estimators. Journal of Econometrics 126:25-51. Wooldridge JM (2009) On estimating firm-level production functions using proxy variables to control for unobservables. Econ Lett 104(3):112-114 Zhang Y, Parker D, Kirkpatrick C (2008) Electricity sector reform in develop- ing countries: an econometric assessment of the effects of privatization, competition and regulation. J Regul Econ 33:159-178 Zhang F (2013) How Fit are Feed-in Tariff Policies? Evidence from the Euro- pean Wind Market. Policy Res Working Papers - World Bank Group. https://elibrary.worldbank.org/doi/pdf/10.1596/1813-9450-6376 |
URI: | https://mpra.ub.uni-muenchen.de/id/eprint/114157 |
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