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|کد مقاله||سال انتشار||مقاله انگلیسی||ترجمه فارسی||تعداد کلمات|
|11773||2012||12 صفحه PDF||سفارش دهید||محاسبه نشده|
Publisher : Elsevier - Science Direct (الزویر - ساینس دایرکت)
Journal : Energy Economics, Volume 34, Issue 4, July 2012, Pages 930–941
Energy Efficient Technologies (EET) have attracted strong interest because of their role in reducing environmental damage. Their adoption, however, remains rather low, while their impact on productivity is substantial and differentiating with respect to technological characteristics. Energy intensity, being such an obvious characteristic, could be employed to classify EET adopters thus giving rise to two heterogeneous technologies (i.e. those corresponding to firms of low and high energy consumption). Hence, this paper examines the impact of energy intensity on the productivity growth of firms adopting EET in varying time intervals through a metafrontier-based framework, while also decomposing that impact in terms of technical, efficiency and scale-efficiency changes. The analysis is complemented by examining the role of firm-specific characteristics on the productivity growth through linear regression.
نتیجه گیری انگلیسی
In this paper we mainly examined the role of energy intensity on the productivity growth of EET adopters. Given the importance of EET for sustainable development and the technological diversity of EET adopters, our approach aimed at properly encompassing issues related to technological heterogeneity, with energy consumption being such the most critical issue. Hence, we employed a metafrontier-based methodology and the standard decomposition of TFP into technological change, technical efficiency change and scale efficiency change, while also examining the time-varying aspect of EET adoption. Our results with respect to Greek firms established that energy intensity does not affect significantly the TFP growth of EET adopters, thus implying that policy measures encouraging EET adoption should not be more beneficial for heavy energy consumers. Furthermore, we derived expressions for the ‘metafrontier:frontier’ ratio of TFP and its components, which allowed us to investigate whether the observed productivity growth is driven mostly by the restricted technology or the metatechnology. Empirical findings suggest that TFP growth arises mostly from the metatechnology (defined by the entire set of EET adopters), thus illustrating broader knowledge spillovers among most EET adopters, irrespective of their energy intensity. Moreover, we implemented a second step of analysis in order to examine firm-specific factors that moderate EET's impact on productivity; the representative set of variables used essentially complemented the aforementioned findings, while also linking them with related literature. A mixed pattern of the EET adopters' underlying knowledge conditions, encapsulating their absorptive ability as well as their potential for technological leadership, appears to be the main driver of their TFP growth. Moreover, the economic dimensions tagging the EET investment projects appear to be crucial for the EET adopters' TFP growth, whereas the corresponding environmental features of the adopted technologies leave TFP growth unaffected. Along this line, interesting issues of the type “does the pollutant pay for pollution” arise once we co-examine the role of capital subsidies on EET adoption rate and their impact on the adopters' TFP growth. Hence, the approach taken here allows for a thorough examination of productivity issues related to EET by a methodological framework for examining technological and time-based heterogeneity. Given the importance of the topic, this approach could hopefully become valuable in other settings, e.g. for measuring the impact of energy intensity in other countries (or regions) or for disentangling different types of heterogeneity among EET adopters.