دانلود مقاله ISI انگلیسی شماره 11371
ترجمه فارسی عنوان مقاله

رشد بهره وری در کشورهای عضو سازمان همکاری و توسعه:  مقایسه با شاخصهای ملکوئیست

عنوان انگلیسی
Productivity growth in OECD countries: A comparison with Malmquist indices
کد مقاله سال انتشار تعداد صفحات مقاله انگلیسی
11371 2005 20 صفحه PDF
منبع

Publisher : Elsevier - Science Direct (الزویر - ساینس دایرکت)

Journal : Journal of Comparative Economics, Volume 33, Issue 2, June 2005, Pages 401–420

ترجمه کلمات کلیدی
شاخص بهره وری ملکوئیست - کشورهای عضو سازمان همکاری و توسعه
کلمات کلیدی انگلیسی
Malmquist productivity index,OECD countries
پیش نمایش مقاله
پیش نمایش مقاله  رشد بهره وری در کشورهای عضو سازمان همکاری و توسعه:  مقایسه با شاخصهای ملکوئیست

چکیده انگلیسی

We utilize two alternative indices to measure productivity growth for all but two OECD countries. First, we employ a Malmquist productivity index without considering the existence of hazardous by-products of production processes. To address the shortfalls of this index, we construct an alternative Malmquist–Luenberger productivity index and find that the Malmquist index underestimates the productivity growth. Finally, we investigate the effects of an international protocol on reducing global emissions and country-specific effects on Malmquist–Luenberger productivity measures. Journal of Comparative Economics33 (2) (2005) 401–420.

مقدمه انگلیسی

Increased awareness of environmental quality has prompted policymakers to adopt precise measures of the environmental impacts of policy choices and consider these when formulating economic policy. As environmental issues are becoming more important and treated as international matters, countries are required to measure, document, and publish accurate information on their impact on a set of economic indicators ranging from national accounts to social indicators. As an initial step, an assessment that internalizes negative externalities in production processes is essential. However, traditional measures of productivity growth, e.g., Törnquist and Fischer indices, concentrate only on the production of desirable outputs and fail to consider environmentally hazardous by-products of production processes. Hence, this approach yields biased measures of productivity growth. To measure productivity growth that accounts for undesirable outputs, one possible approach is to modify traditional indices so as to incorporate negative externalities. However, this methodology requires price information for both desirable and undesirable outputs as well as inputs. In this case, shadow prices for each of various inputs, outputs, and pollutants can be computed by the methods found in Pittman (1983) and Färe et al. (1993). Alternatively, Färe et al., 1989 and Färe et al., 1994a propose a tool to measure productivity that requires information on quantities only. Their non-parametric Malmquist measure relies on constructing a best practice frontier over the whole sample and computing the distance of individual observations from the frontier. This Malmquist index,1 hereafter referred to as the M index, can be partitioned exhaustively into useful component measures. In particular, it can be decomposed into technical change and efficiency change components. However, the M index must be modified to incorporate negative externalities if environmental issues are to be considered. In their seminal work, Chung et al. (1997) propose a modified version of the M index to measure productivity growth in the presence of the joint production of both desirable and undesirable outputs, namely the Malmquist–Luenberger productivity index; hereafter referred to as the ML index. This index considers the reduction of undesirable outputs as well as the increase in desirable outputs; it also possesses all the desirable properties of the M index. In contrast to the extensive literature on the M index, only a limited number of empirical studies employ the ML index to measure productivity growth. Using micro-level panel data, Färe et al. (2001) employ the ML index to account for both marketed output and the output of pollution abatement activities of US state manufacturing sectors from 1974 to 1986. Weber and Domazlicky (2001) apply the same methodology to state manufacturing data and the aggregated emissions from the US Environmental Protection Agency's Toxic Release Inventory from 1988 to 1994. As industrial activity reaches as levels that lead to irreversible environmental damage, governments and international bodies try to enforce regulations to control the resulting pollution. Policies that improve environmental management not only slow the rate of natural resource depletion, but also advance sustainable growth. These standard-setting approaches are referred to as the precautionary principle in Article 3 of United Nations Framework Convention on Climate Change, hereafter referred to as UNFCCC, which aims to reduce global emissions. UNFCCC was negotiated at the Earth Summit in Rio de Janeiro in 1992. The main objective of the convention was to stabilize greenhouse gas concentrations in the atmosphere at desirable levels, but to do so with economic development in a sustainable manner. Along with several mandates, including the Luxembourg Decision of 1990, Rio Summit of 1992, and Berlin Mandate of 1995, UNFCCC has played a key role in establishing a final international agreement, i.e., the Kyoto Protocol of 1997. This protocol is designed to give countries the opportunity to meet the mandated emission targets at low economic cost. Even though the Kyoto Protocol received a worldwide support with 84 signatories, only 64 countries have ratified it as of September 2004. The USA, which accounts for approximately one-third of emissions of highly industrialized Annex 1 countries and one-quarter of all global emissions, has refused to ratify the protocol. In addition, two contributors to global emissions, Japan and France, have also refused to ratify the Kyoto Protocol. The lack of participation of these three countries renders the Kyoto Protocol ineffective and makes UNFCCC the primary effective international protocol to date. However, although UNFCCC contains various regulation plans, the mandates are not binding in many aspects. Using recent macro-level data, our paper contributes to the previous literature by computing and comparing two district indices of productivity growth for each of the OECD countries and by constructing a reliable framework to assess the underlying source of productivity growth. We first compute an M index to measure the productivity growth of OECD countries and then compute an ML index to incorporate negative externalities. In the absence of information on prices, non-parametric production frontier techniques and distance functions are essential tools for the computation of both indices. These two measures of productivity growth also provide useful information for OECD countries engaged in international protocols, i.e., UNFCCC and the Kyoto Protocol. For example, the precautionary approach of UNFCCC mandates a production plan that is least detrimental to environmental quality. Hence, among the many combinations of inputs, outputs, and pollution emissions, the production plan that maximizes the desirable outputs while simultaneously minimizing undesirable outputs is preferable. To test whether the ML index is a useful measure of compliance with this requirement, we investigate the effects of country-specific variables and a variable to capture the effect of UNFCCC on the ML index. Our results indicate that the M index underestimates productivity growth and that a threshold level of GDP per capita and industrialization exists for OECD countries, above which an upward trend in productivity growth is observed. Moreover, the UNFCCC variable has a significant and positive effect on the productivity growth measures. The organization of this paper is as follows. Section 2 presents the trends in emissions for OECD countries, the construction of the indices, and discusses the data sources. Section 3 presents the comparison of the indices. Section 4 discusses the policy implications within a panel data estimation framework. Finally, Section 5 concludes with a summary of the results. We relegate the development of the analytical framework to Appendix A.

نتیجه گیری انگلیسی

The OECD has a long-standing program to improve resource efficiency, to address the environmental impact of growth, and to consider issues related to technological change. Efficient use of resources encourages growth and sustainable development in OECD countries. However, measures that internalize negative externalities in production processes are required to provide an accurate assessment of environmental problems. Following Färe et al. (1994b) and Chung et al. (1997), we measure productivity growth of the OECD countries using two indices, namely the Malmquist (M) index and the Malmquist–Luenberger (ML) index. We find that the M index, which does not account for negative externalities, measures higher productivity growth than the ML index during the periods in which undesirable outputs trend upwards. Alternatively, during time periods exhibiting a downward trend in pollutants, the ML index is larger than the M index. Therefore, we conclude that the M index is not well-suited to measure productivity in the presence of negative externalities. Although the ranking of countries differs according to which emissions are included, Ireland and Norway are the best performers for all four ML indices computed. In addition, the technical change component dominates the efficiency change component in these ML indices. The ML indices measure average productivity growth of at least about 10% for the OECD countries from 1985 to 1998, with the index that includes nitrogen oxide and organic water pollutant emissions, indicating a 20% productivity growth. Compared with the conventional M index, the ML indices record at least 7% higher productivity growth for OECD countries. Finally, we investigate the determinants of the variation in productivity growth across these countries, paying attention to the potential role played by the UNFCCC protocol on emissions. We find that the dummy variable representing the ratification of this agreement has a significant, positive effect on the ML index. Furthermore, we establish threshold levels of GDP per capita and industrialization for the OECD countries above which productivity growth trends upward.