GHG Emissions and Economic Growth

Historically, the developed countries have been the chief contributors to global warming. But, lately, onus for the perpetuation and aggravation of the climate change problem is being increasingly shifted to the developing counties. Fast economic growth in these emerging countries makes them potential energy guzzlers and, thereby, large emitters of greenhouse gases (GHG). India is a prominent member of this club of emerging countries, and, in fact is, in absolute terms, the fifth largest GHG emitter in the world. Internationally, therefore, India is expected to reduce its energy-related GHG emissions. In any case, India being a primarily agricultural country, its vulnerability to climate change is disproportionate to its culpability. Balancing GHG emissions and economic growth is therefore not only an international obligation but also a daunting national challenge for India. In response to this challenge, India’s efforts are underway and the results so far are mixed – i.e., there are both successes and failures. In this context, this chapter reviews the climate change literature with a view to assess the past and the extant climate change mitigation policies in India and identify gaps in research geared towards guiding policymakers. In an attempt to partially fill this gap, the chapter sets three key objectives for the study : (i) to develop a database and a methodology to examine the impact of economic growth on GHG emissions, (ii) to delineate the factors governing the sectoral emission intensities, and, (iii) to formulate a climate-focused computable general equilibrium (CGE)model which can analyse \the efficacy of market-based policy instruments for climate change mitigation.

Social accounting matrix (SAM) is a technique related to national income accounting, providing a conceptual basis for examining both growth and distributional issues within a single analytical framework in an economy. It can be seen as a means of presenting in a single matrix the interaction between production, income, consumption, and capital accumulation. In this describe the concept and, we describe the concept and methodology for construction of a SAM for India. The novelty of this SAM is a detailed account of disaggregated energy sectors, electricity sectors, energy intensive sectors, and biomass as an alternative source of fuel. Further, this is one of the latest SAMs for India with such a high level of disaggregation.

The accounting for pollution-related activities within a social accounting matrix (SAM) framework is useful for analysis of environment-related issues. In this chapter, we describe the methodology one uses for accounting the same in a SAM framework. In other words, how to construct an environmentally extended SAM (ESAM), is spelt out in detail here. We have used this methodology to convert our constructed SAM into an ESAM. Basically, the ESAM presented in this chapter provides an integrated account for both economic transactions in monetary unit and flow of environmental substances in physical unit. Such integrated account in a consistent framework helps us to understand and quantify the linkages between economic activities and the flow of environmental substances.

In general, direct pollution effect is only a small part of the total effect of pollution when production/consumption activities take place in an economy. To estimate the same, we have to undertake multiplier analysis. In this chapter, we have followed the social accounting matrix (SAM) multiplier method to estimate empirically the multiplier impact of economic activity on greenhouse gas (GHG) emissions in India. To be specific, this chapter explains the linkage of output growth with energy demand and GHG emissions. Finally, the issue of green employment opportunity has been analyzed with the help of SAM multiplier.

This chapter describes the historical trend of greenhouse gas (GHG) emissions and analyzes the factors influencing this historical trend. Since every economy passes through various structural change processes over time, their implications must be assessed for future policy implementation. Therefore, in this chapter, we have described the methodology of input-output (IO) structure decomposition analysis to assess and determine the factors for historical GHG emissions trend in the Indian economy.

The input–output model and social accounting matrix (SAM) models have been widely used in building multisectoral, economy-wide models for development planning and policy analysis (Miller and Blair, Input-Output Analysis: Foundations and Extensions, 1985). Models of this type assume an economy that is linear in costs with exogenous demands and fixed prices. These models might be appropriate for short-run policy analysis, but their assumptions do not appear to apply to most real-world economies, which are either pure market economies or market-based economies with an overarching governmental presence. Even in the latter type of mixed economies, for example, India, a great deal of economic activity is not under direct control of the government, but is governed by price signals of the market. In such a decentralized system, myriad intersectoral and intrasectoral substitutions, mostly nonlinear, take place in production, consumption, and distribution in response to price changes. Moreover, there are important feedbacks arising out of interactions among the various commodity and factor markets. A computable general equilibrium (CGE) model is especially designed to capture these essential features of the market. CGE analysis, in comparison to other available techniques, thus captures a wider set of economic impacts from a shock or the implementation of a policy reform, typically, by building and then comparing alternative policy scenarios. Therefore, in this study, we have used a CGE model to evaluate the greenhouse gas (GHG) emissions abatement policies. This model is a single-country model interacting with the rest-of-the-world (ROW). We use this to address the primary concern of our policy makers to formulate national climate change mitigation policies which protect national interest without harming global concerns on climate-related issues.

Typically, a computable general equilibrium (CGE) model is employed to develop, first and foremost, what could be called the “no-policy” or “benchmark” scenario, but is conventionally alluded to as the baseline or business-as-usual (BAU) scenario, or simply reference scenario. Subsequently, it is usually run to generate counterfactual policy scenarios, which are then compared with respect to the reference scenario to derive policy lessons. In accordance with this convention in CGE analysis, we have developed a reference scenario, without any market-based instrument for climate change mitigation, and two carbon tax scenarios in which producers are fiscally incentivised to switch to cleaner sources of energy.

Between the developed and developing countries, it is the latter which are more vulnerable to climate change even though the developed countries have been the primary contributors to greenhouse gas (GHG) emissions till date. Further, it is ironical that the ones who are the most vulnerable to climate change are the least capable to mitigate it while those who are responsible for causing it in the first place are most unwilling to do their part in resolving it. There is therefore much consensus in the climate change literature on problem statement, but none in finding solutions. Given that the developing countries have to fend for themselves in combating climate change, this concluding chapter summarizes the broad policy lessons of this study.