Debesh Chakraborty

India's Energy Consumption Changes during 1973/74 to 1991/92

The global energy crisis in the 1970s and early 1980s had adverse economic impacts in all oil-importing countries, including India. The objective of the present paper is to analyze energy consumption changes that have taken place in the Indian economy during 1973174 to 1983184 and 1983184 to 1991192, and the factors responsible for these changes. We develop a structural decomposition analysis in which the energy consumption changes are the result of the following six different factors: technical changes; changes in the final demand structure; changes in the interaction term of technical changes and final demand structure; changes in energy exports; changes in energy imports; changes in energy change in stock. Then, we separate the technical changes and final demand structure again, which identifies explicitly the effects of energy consumption.

A Study on the Indian Information Sector: An Experiment with Input-Output Techniques

It is widely recognized that rapid changes in information technology (IT) are bringing about major structural changes in the economies of the world. Information flexibility, product quality and fast response are the key factors for global competition and IT plays a critical role in these areas. Policy-makers in industrialized and developing countries view IT as a critical infrastructure to enhance their access to global knowledge, markets and capital. These views--of IT as infrastructure and as core capability for development--resonate with Indias aspirations to modernize its infrastructure, transform its industry and join the global economy. Realizing the huge potential of the Indian IT industry, we make an attempt in this paper to study the extent of informatization in the Indian economy during the period 1983-84 to 1989-90 and try to identify the information intensive sectors. This paper also studies the sources of growth of the information sectors of India during 1983-84 to 1989-90 with the help of a structural decomposition analysis (SDA).

ENVIRONMENTAL IMPACTS OF TRADE IN INDIA

Abstract This article aims at contributing to environment trade debate by evaluating the impacts of international trade on emissions of carbon dioxide, sulphur dioxide, and nitrogen oxides for the Indian economy during 90s using Input-Output techniques. The article has constructed an index of pollution terms of trade. Using the Input-Output table of 1991–92 and 1996–97 for India we have computed pollution terms of trade for the content of CO2, SO2, and NO x . Results show that the indices are below 100, indicating that India produces goods that are more environment friendly than goods it imports, thus challenging the pollution haven hypothesis for India. The article has also offered explanations for these results.

Bilateral trade between India and Bangladesh: A general equilibrium approach

Abstract India and Bangladesh have pursued policies of trade liberalization since the early 1990s. However, owing to the differential speeds of opening up, Bangladeshs bilateral trade deficit with India widened substantially over the years. This aggravated the economic and the political tensions between the economies. It has been held that promotion of free trade between the two economies may enhance the trade and hence economic cooperation between them. Against this backdrop the present paper proposes a theoretical framework that provides a general equilibrium determination of the commodity pattern of trade and hence locates the comparative advantages of the economies. The empirical implementation of the model considers trade in 25 sectors comparable in the input–output tables of the economies. The study isolates the gains from free trade accruing to either economy. The paper also explores the pattern of bilateral trade when each economy produces goods by utilizing their own as well as the other countrys technology. The gains from this trading arrangement are also isolated.

Indian Comparative Advantage vis-à-vis Europe as Revealed by Linear Programming of the Two Economies

We develop a customs union model for India and Europe to assess the comparative advantages. The model is Heckscher-Ohlin as regards factor inputs, but Ricardian as regards technology, since the structures of the economies prohibit the ascription of comparative advantages to factor scarcities alone. Moreover, the presence of intermediate products prompts us to revise the standard concept of comparative advantage by the formulation of a foreign earnings program. The solution to the program shows that India is strong in mining, manufacturing and utilities. Specialization in these activities would yield significant eficiency gains. Deregulation of these sectors would make them profitable investment targets, even at European rates of return. Gradual development of other sectors, especially agriculture, involves great opportunity costs.

Energy consumption and prospects for renewable energy technologies in an Indian village.

Harnessing renewable energy resources has substantially speeded up the process of rural energy planning in India, where about 80% of the total energy is supplied by noncommercial sources, the share of which is declining. In rural energy planning, with backward agriculture and high poverty levels, the choice of appropriate technology is essential. The present study deals with selecting appropriate alternate energy technologies with priorities to end-use activities in the agriculture and household sectors. The study is based on a field survey and the use of dynamic programming.

Sustainability of marine fishing: a case study of West Bengal.

The marine fishery sector in India is important not only for domestic demand for protein food requirements but also from the imperatives of exports. An increased investment in this sector has taken place during the last few years and the fishing fleet has expanded at a very rapid rate. Presently, however, marine fishers are facing difficulties in fish capture in spite of exerting the same and sometimes more effort. Thus the question of the sustainability of marine fishing arises. The sustainability of marine fishing in the Digha-Shankarpur coastal region has been studied through estimation of the maximum sustainable yield based on a simple bioeconomic model. WLS estimation has been done to remove heteroscedastic disturbances. Estimated results show that actual yields of all varieties are still below maximum sustainable yield (MSY) except prawn, which has reached near optimal levels.

Review of the Case Studies

This chapter reviews a number of case studies across the different states in India. It includes textile, pharmaceuticals, and paints industry from West Bengal; textile and dye industry in Rajasthan and Tamil Nadu; sugar industry in Maharashtra; pulp and paper industry in northern India; and tannery industry in Uttar Pradesh and Tamil Nadu. From these case studies, we find that different industries have adopted different measures depending on their capacity. These case studies provide further insight regarding the implementation of common effluent treatment plant (CETP) and effluent treatment plant (ETP). The findings from the West Bengal studies reveal that measures to control water pollutants by setting up ETP in five industries have been successful. While the experiences from leather industry in North and South India show similar results where both have used CETP to control water pollution, a typical cluster of pulp and paper industry in Northern India shows the feasibility of ETP compared to that of CETP. In general, the performance of CETPs has been found to be very unsatisfactory largely because of poor operation and maintenance.

Experiment with Models: Results and Discussion

This chapter reports the result based on the model calibrated in Chap. 3. It analyzes the results on direct and indirect water pollution requirement, water pollution content of the total final demand of different sectors of India, and effects of pollution abatement costs on output and prices of different goods and services. The results show that the amount of total pollution generation per unit of the product is significantly higher for all industries compared to the direct pollution generation coefficient. Significant numbers of industries (livestock, chemical, beverages, leather, cotton textiles, miscellaneous textile, paper, and milk and milk products) in India are producing water pollution above MINAS by several times. The pollution abatement activities involve costs which, in turn, will affect the price and output of different industries. To analyze the effect of these costs, a clean water sector is added to the economy.

Data Sources and Processing

This chapter provides the data from various sources and discusses the processing of data. The major data required for the work are the input–output table of India, the different types of water pollutants generated by the different industries of India, and the abatement cost for various water-polluting industries. The study has used the input–output table of India for the year 2006–2007 recently prepared by the CSO (Input-output transaction table 2006–2007. Central Statistical Organisation, Ministry of Programme and Implementation, Government of India, 2011). The input–output table of 2006–2007 consists of 130*130 sectors. For our study, the table has been aggregated to 38 sectors. From the publications of the Central Pollution Control Board and various other water pollution information sources, ten types of water pollution parameters are identified which are being discharged by the different industries. These are suspended solids (SS), dissolved solids (DS), chloride, sulfide, zinc, phenol oil and grease, biochemical oxygen demand (BOD), chemical oxygen demand (COD), and other pollutants such as nitrogen, chromium, cyanide, alkalinity, etc. A large number of industries do not conduct systematic record of effluent. However, we are able to collect the pollution data for 31 sectors. We have estimated the abatement cost for the treatment of water pollution for each individual sector. Due to the paucity of the cost data, we could collect the data for 16 sectors. The issue with data limitation is also discussed in this chapter.