Выпуск №4 2006
СОДЕРЖАНИЕ >> СЕКЦИОННОЕ ЗАСЕДАНИЕ «Наследие Леонтьева и современные экономико-математические методы»

Анализ изменений климата методом "затраты-выпуск"

Input – Output Analysis of Climate Change: Case Study of Efficiency Driven Policy Choice of Indian Response Strategy

Джояшри Рой ( Joyashree Roy), профессор Джадавпурского университета, Индия

Roy Joyashree, Sathaye Jayant, Khaddaria Raman & Das Sarmistha

Introduction

Increasing economic activity with population growth are expected to impose increasing  demand for electricity services in India. The demand can be met by conventional route of capacity addition  and/or  through introduction of electricity efficient technologies. Given the fact that in India approximately 80% of electricity is produced from coal and power sector accounts for major share (Biswas 2006)  in total CO₂ emissions, policy to promote electricity efficient technologies will have high emission mitigation potential. However, mitigation potential cannot be enough incentive for a non-Annex I country like India which prioritise income and employment goals over mitigation goal. In view of the growing concern over climate variability, incentive for choice in favour of ‘technology policy to promote efficiency’ over  ‘capacity addition’ for non annex I countries can only be found  if evidence can be provided to show that former  can address the development goals better or at least as good.

In India government utility companies, with only three major private sector generation and distribution companies, traditionally ran the electric power sector until the mid 1990s. Since then the Indian government has pursued a policy of deregulation by opening it to private sector investment and separating generation from transmission and distribution of electricity. While there were many goals, a primary objective of this policy was to ensure a reliable supply of electricity to consumers at affordable prices. Deregulation was intended to reduce or eliminate the electricity deficit, improve the financial performance of the State Electricity Boards (SEBs), and reduce the government’s outlay for construction of new electricity supply and subsidies.  After more than a full decade of reforms, however, the supply and demand gap of electricity  widened over the years. In 1990-91, the electrical energy deficit was around 7.7%, and by 2001-02 it had remained at about the same level, 7.5%. The peak power deficit was around 18%,but declined to 12.1% by 2001-02 (Ministry of Power, 2003). In part, this persistent deficit was due to the significant slippage in the generation expansion program in the 9^th Plan period. The planned construction was for a capacity of 40.2 GW while only 19.0 GW or less than 50% was built during this period (Planning Commission, 2002). The actual construction of capacity fell well short of the planned capacity in both the public and private sectors. Electricity generation increased faster than GDP until 1991 but has increased at the same rate since then (figure 1). The Government of India has been subsidizing the supply of electricity in the agriculture and domestic sectors and the uncovered subsidy amounted to Rs. 266 billion in 2001-02 or about US $ 5.6 billion (Planning Commission 2002). The 9^th Plan outlay for the power sector in India was 14.49% of the total plan outlay but an even larger proportion (19.26%) of the states’ plan outlay has been for the power sector. Despite a substantial fraction of the government budget being

Figure :1

devoted to the power sector, electricity deficits continue to persist.

The unemployment rate in India decreased from 8.3% in 1983 to 6.0% in 1993-94, but by 1999-00 it had increased to 7.32%. During the 10^th Plan period, 50 million job opportunities would be created through normal growth of the economy and various government programs targeted at job creation. The approach paper of the Tenth Plan suggests ways to provide gainful employment opportunities for the labor force over a five-year period.  Emphasis is given on diminishing the unemployment rate over the 10^th Plan so that by the end of the 11^th Plan this rate will be zero. But it has been estimated, that at a GDP growth rate of 6.5%, at the end of 10^th Plan the percentage of unemployment will grow up to 11% (Planning Commission 2001)).  Therefore to address this situation a higher future GDP growth rate supported by appropriate policies and programs is essential.  The 10^th Plan estimates that GDP growth rate could increase to 8% with such measures, but even at this GDP growth rate, the unemployment rate at the end of Tenth Plan would be 9.79%, or higher than the 9.2% rate at the beginning of the 10^th Plan.  In context of this troubled background of the investment-constrained electric power sector,   projections of a rising unemployment rate, and a high government fiscal deficit, an accelerated program to promote energy efficiency could provide significant benefits besides the  elimination of the electricity deficit. This will succeed in holding the  investment outlays to the electric power sector no more (and potentially even less) than have been planned to date. The tenth five year plan document also emphasizes the need for increasing efficiency in electricity use. A host of possible options have been suggested some of which are : improvement of  efficiency in all segments—generation, transmission and distribution and also power consumption, achievement   through implementation of energy conservation act, 2001, Determination of  minimum power consumption standard, Labeling  for identified appliances, introduction of  norms/ rules and regulations for power intensive industries, formulation  of  energy consumption code, Establishment of  an  energy conservation fund both at the state and the central level, Establishment of Bureau of Energy Efficiency (BEE) in place of Energy Management Centre (EMC), Declaration of  user or a class of user of energy as  designated consumer .

In this  paper, we examine the cost-effective potential for penetration of selected energy efficiency technologies in India. The objective is to estimate the output and employment implications of removing the electricity deficit through penetration of energy efficient technologies. In  general technical efficiency improvement leads to  cost savings through avoided demand for electricity, which would reduce investment needs for capacity addition. Effective savings in an investment fund may be allocated for overall activity enhancement.  

To assess economy wide impact of penetration of efficient technology we develop an integrated approach and methodology which is explained in section 2, for application of the proposed approach to Indian economy, data source, coverage and construction have been explained in section 3, section 4 presents alternative macro scenarios under alternative policy options, derivation of macro parameters useful for integrated model has been derived in section 5, section 6 presents economy wide impact analysis which is followed by concluding remarks.

Approach and methodology

In order to analyze the impact of accelerated penetration of energy efficiency technologies we construct two electricity capacity expansion scenarios for the five-year period 2004-2008 (this is one year beyond the 2007 end date of the 10^th plan). The first scenario (Supply) is Business as Usual (BAU). This is based on the capacity expansion figures as stated in the 10^th Plan (41110 MW) but adjusted for achievable level ( 19321 MW) derived  from the experience of the 9^th plan in which less than half (47%) of the planned capacity was actually constructed[1]. We consider an average cost of US $ 900/kW for 41,110 MW capacity 10th plan additions. The corresponding total investment for the 10th Plan is Rs. 1,548 billion or US $ 36 billion. A second scenario (Supply and efficiency) is developed for the same period.[2] This scenario includes increased penetration of end-use energy efficiency devices that thus reduce the need (through effective increase in supply of electricity service) for capacity expansion compared to  the first scenario. Since power sector investment is constrained in a developing economy like India, the total investment estimated for a BAU scenario over the five-year period is held at the same level in the second scenario.   However, because efficient technologies require less investment per kWh of electricity service, it is possible to  meet the tenth plan target while holding investment constant. Thus there is no electricity deficit in the second scenario.

The electricity deficit arises due to lack of supply to both productive and consumptive (domestic sector’s share in total electricity consumption in India 20%) sectors. In the productive sector, an electricity deficit implies that other factors of production are present while only electricity supply is inadequate. Increased supply of electricity to this sector should thus stimulate expansion of economic output and employment opportunities. In the consumptive sector, removal of the electricity deficit will increase consumer welfare since consumers will be able to avail themselves of amenities that otherwise are being denied to them. In this analysis, we assume that four of the six energy efficiency measures, target the productive industrial, commercial and agricultural sectors, efficient refrigerators and half of the compact fluorescent lamps (CFLs) target the residential or consumptive sectors.

Efficiency-Employment Integrated Model (EEIM):

The model developed for this analysis here has two components: a spreadsheet model and an input-output model.

Stage I: In order to match the supply and efficiency options, we constructed a spreadsheet model that arithmetically matches annual expansion plans and efficiency options. We assume that the full technical efficiency potential is available for the six technological options that we analyze, and that it can be realized to satisfy capacity as needed within the scenario period.  The spreadsheet model calculates the penetration level of efficient technologies such as to maintain investment at the same level  in both scenarios. Since the primary emphasis in this paper is on investigating the role of energy efficiency, the supply component of the scenario is modeled using a single composite technology that is representative of thermal, hydro, nuclear and other smaller capacity power plants.

Investment is held constant in the two scenarios, but the distribution of investment is different, which leads to a relatively small difference between the macroeconomic impacts of the two scenarios.  The more significant macroeconomic impact arises due to the fact that in the second scenario (Supply with efficiency) there is no electricity deficit which permits the economy  to function at its full potential. Avoided  use of electricity due to the energy efficiency devices,  result in monetary savings to consumers. These savings are assumed to be  reinvested or spent on other economic activities to generate additional employment and income in the economy.

Stage II: Several authors have investigated the use of input-output multipliers to estimate regional and national economic output (Hsu 1989, Roy and Mukhopadhyay 1999, Mukhopadhyay 2001) and employment impacts of energy strategies (Sathaye and Ruderman, 1980, Sathaye and Ruderman, 1984, Laitner, Bernow, and DeCicco, 1998, Das S, 2006). Following these approaches, in order to estimate these impacts, we constructed an input-output table at the 8-sector level for 1993-94 (latest I-O table available officially) and matched the employment statistics at this level of detail for the national Indian economy. Macro parameters like output and employment multipliers were then estimated.

Stage III : Parameter estimates of employment and output multipliers from stage II are combined with estimates derived from stage I on BAU capacity addition , and net surplus reinvestment fund generated through avoided electricity use through efficiency improvement.

Data

Scenario analysis using EEIM requires cost, capacity, and energy data on power plants, energy efficiency technologies, economy-wide employment and output, and an input output table for the Indian economy. We describe the data sources for these inputs below. The data on 9^th Plan actual, and 9^th and 10^th Plan planned, capacity and energy generated were obtained from the Planning Commission (Planning Commission, 2002). The data on electricity peak capacity and energy deficit are from the 2002-03 annual report of the Ministry of Power. The composite construction cost data for electric power plants is based on investment cost information from Mathur et al. (2003). Coal and natural gas power plant cost is estimated at Rs. 30,000 per kW, large and small hydro is Rs. 60,000 and Rs. 74,000 per kW respectively, wind power is Rs. 40,000 and nuclear power is Rs. 90,000 per kW. The contribution of PV, advanced coal and other technologies is small or negligible in the capacity expansion scenario.

The electricity peak deficit in 2002 was 12.1% and energy deficit was 9.1%. We assume a conservative projected peak deficit of 10% and an energy deficit of 6%. This implies that the Electricity Act 2003 and the Energy Conservation Act 2001 would have their intended effect of reducing the capacity and energy deficit.

Based on generation and capacity data for 1999, we estimate the plant capacity factor to be 56%. Again due to the reforms being pursued in the power sector this figure is expected to increase, and we estimate that this will gradually increase to 65% by 2008, the last year of our scenario period.

Data on electricity efficiency technologies are obtained from a report by Deneb Consultants (2002). The devices for which data are available are (1) variable speed drives in industry, (2) rectification of agricultural pump sets, (3) motor rewinding and downsizing, (4) high efficiency agricultural pump sets, (5) improved high efficiency refrigerators, and (6) CFLs and electronic ballasts. A  report to USAID, Delhi, cited the potential for the use of these devices in the Indian economy, and that potential clearly exceeds the 13.2 GW deficit identified in the BAU Scenario. This report also provides data on the cost of the six technologies, and their annual hours of operation in specified sectors and applications. This information was used to estimate the electricity avoided by the use of the above six technologies.  To estimate the monetary savings from the avoided purchase of electricity in the Supply with Efficiency Scenario, we need data on electricity prices. These price data were estimated by sector (Planning Commission, 2002), and are agriculture – 1 cent/kWh, industry – 8 cents per kWh, residential 4 cents/ kWh, and commercial at 9 cents per kWh. We assume that refrigerators save consumptive electricity in the residential sector, and that half the CFLs and electronic ballasts are in the productive commercial sector, and the other half in the consumptive residential sector.

For the purpose of calculating the input-output multipliers we use data from the input-output transactions table (IOTT), and match the sectors with those for which employment data are available from the reports of the National Sample  Survey Organisation (NSSO). Population growth rates from census tables were also used for this purpose. We have referred to NSS rounds titled as " Employment and Unemployment in India" for calculating the employment figures per 1000 distribution of usually employed persons by eight sectors classified as  Agriculture,  Mining& Quarrying,  Manufacturing,  Electricity gas & water, Construction, Trade, Transport and Services.

The concepts used and the adjustments made for arriving at the employment figures for these eight sectors are in line with the famework of the NSSO. The usual status of employment refers to the status of activity in which a person spends relatively longer time of the preceding 365 days from the date of survey is considered as the principal usual status activity of the person. Accordingly, a person is considered 'working or employed' if he/she was engaged for a relatively longer time during the past year in any one or more work related activities (economic activities). The person is considered as 'seeking or available' for work or 'unemployed' if the person was not working but was either seeking or available for work for a relatively longer time during the past year. If the person was engaged in any non-economic activities for a relatively longer time of the reference year he/she is considered as 'out of labor force'. The specific activity category is determined on the basis of time-spent criterion i.e. the activity on which major time was spent being assigned as the usual status activity.

A person is categorized as 'worker' or ' employed ' on the basis of the 'principal status worker' or 'principal status employed'. A person categorized as a non-worker (i.e. unemployed or out of labor force) who pursued some economic activity in a subsidiary capacity is called a 'subsidiary status employed'. These two groups together constitute 'all workers' according to the usual status classification.  This is the conceptual framework, which has been followed by the National Sample Survey (NSS). Essentially what we understand by workers or employed persons is known as 'principal status worker' or 'principal status employed' persons. This is estimated  for a particular sector using the per 1000 distribution of usually employed persons by industry section,  labor force participation rates (LFPR) by sex and by using the following relation.

(1)           Total workers in i^th sector=

where, = number of persons rural male engaged in  i^th sector out of 1000 persons rural-males who are in turn denoted by .

Similarly we have , and as principal-status employed in agriculture classified as rural-females, urban-males and urban-females respectively.

Also ,and stand for total number of ps rural-females, ps urban-males, ps urban-females.

However values for ,, and are not available directly. Instead we have a distribution of ps workers per 1000 people classified according to rural urban and according to sex.

Let ,,and  denote number of rural-males, rural females, urban-males and urban-females respectively. From table 5.1 of the NSS  round 50 we have the following ratios

,,and   .

Population figures on rural-males, rural-females, urban-males and urban-females from the census reports will give us the required figures.

Note: The NSSO survey being a quinquennial survey, data are available at an interval of five years. On the other hand the broad population figures required from the census reports are available at 10 year intervals. Hence, in order to have annual employment figures for various sectors we interpolate in order to arrive at yearly data.

The inter-industry or commodity x commodity matrix of 93-94 is used which is  115x115 matrix. For our purpose the 115 sectors have been aggregated into the sectors enumerated above. In order to make the multipliers comparable, the inter-industry matrices for these years have been deflated at 1981-82 prices using appropriate price indices to get constant values.

Scenarios

As outlined in the approach, we constructed two scenarios, the BAU scenario followed a modified 10^th Plan schedule for power plant construction, and the second one, Supply with Efficiency Scenario (SES) focused on an accelerated penetration of energy efficiency technologies. Business as Usual (BAU) or Supply with Deficit Scenario, SDS, (Scenario 1): The capacity and generation for the first scenario (BAU Scenario) is shown in Table 1. Columns 1 and 2 show the actual capacity and the 9^th Plan additions from 1996 to 2001. The total 9^th Plan planned capacity was 40,245 MW and this is shown in the last row in Column 2. Column 3 shows our estimate of the capacity additions during the 10^th Plan. This estimate assumes that the 9^th Plan experience of slightly less than half the planned capacity being constructed is repeated during the 10^th Plan. Column 5 shows the electricity capacity deficits reported by the Ministry of Power for the period 1996-2002. Beyond 2002, we assume conservatively that with inadequate construction of power plant capacity the annual deficit will prevail at about 10%. Column 6 in Table 1 shows the corresponding nationwide annual capacity deficit.

Column 7 in Table 1 shows the investment needed to support the construction of the projected capacity additions.  At a unit cost of $900 / kW, the total investment amounts to $120.2 billion.

Table 1: Energy Supply with Deficit Scenario -- Annual Capacity and Deficit

Year (Col. 1)	Actual and Projected Capacity (MW) (Col. 2)	9th Plan: Actual Capacity Additions (MW) (Col. 3)	10th Plan: Estimated Capacity Additions (MW) (Col. 4)	Actual and Projected Capacity Deficit (%) (Col. 5)	Actual and Projected Capacity Deficit (MW) (Col. 6)	Investment for Projected Capacity @ $ 900 / kW (Million US $) (Col. 7)
1996	84,912			18	15,284
1997	89,090	4,178		11.3	9977
1998	93,253	4,163		13.9	12851
1999	97,854	4,601		12.4	12035
2000	101,660	3,806		13.0	13164
2001	103,410	4,806		11.8	12202
2002	106,822		2450	12.2	12915
2003	110,331		3183	11.0	11995
2004	114,299		3653	10.0	11270	3288,
2005	117,640		3436	10.0	11613	3092
2006	121,917		4348	10.0	12048	3913
2007	126,675		4868	10.0	12535	4382
2008*	132,443		6247	10.0	13159	5622
Total		21,554	22552			20,197
Planned Additional Capacity		40,245	41,110

Note:10^th Plan period ranges from 2002-2007. Planned additional capacity of 44,245 MW is for 2002-07. The year 2008 is added to round off the modeling of the last year of capacity additions.

Table 2 shows the electricity deficit that corresponds to the capacity information reported in Table 1. Plant load factors (capacity factors) nationally have been around 60% until 2001, although there is some evidence that these are improving (Economic Survey, 2004-05). We follow a conservative approach to avoid over estimation and assume that  load factors will be 0.65 by 2008. Using the data on capacity in place from Column 2, Table 1, and the plant load factors, we estimate the electricity generation values shown in Column 3 in Table 2 for the period 1996 to 2008.The Ministry of Power reports the national electricity deficit to have been 9.1 % in 2002. We use a conservative figure of 6% for the projected period to 2008, and use it to estimate the projected electricity deficit from 2003 to 2008.

Table 2: Supply with Deficit Scenario

Year (Col. 1)	Actual and Projected Load Factors (Col. 2)	Actual and Projected Generation (TWh) (Col. 3)	Actual and Projected Electricity Deficit (%) (Col. 4)	Actual and Projected Electricity Deficit (TWh) (Col. 5)
1996	0.53	396	11.5	46.
1997	0.54	422	8.1	34
1998	0.55	449	5.9	26
1999	0.56	481	6.2	30
2000	0.57	509	7.8	40
2001	0.58	526	7.5	39
2002	0.59	553	9.1	50
2003	0.60	581	6.0	35
2004	0.61	612	6.0	37
2005	0.62	640	6.0	38
2006	0.63	674	6.0	40
2007	0.64	711	6.0	43
2008	0.65	755	6.0	45

Supply with Efficiency Scenario, SES, (Scenario 2): In this scenario, our goal is to reduce or eliminate the electric capacity and energy deficit through increased penetration of energy efficiency measures. Detailed analyses of the potential for electricity efficiency measures and their cost are not available in a consistent format. A 1991 study reports this information (Nadel et al. 1991), and a more recent analysis provides similar information, which shows a very large potential for six common end-uses and for commercially available energy efficiency measures that are also cost-effective (Deneb Consultants, 2002). The report also provides estimates of the investment requirements of these measures.  Data on estimated costs, and hours of operation of these six measures are shown in Table 3.

The Supply with Efficiency Scenario is constructed such that the total investment in the two scenarios remains unchanged. In the Supply with Deficit Scenario (SSS), $19.9 billion is invested at an average cost of $900 per kW. In the SES scenario, since the investment for the six options ranges from $100 to $300 per kW, it is possible to construct a scenario in which both new supply and efficiency play a role without increasing investment. Table 3 shows the capacity savings from each energy efficiency measure, the total capacity savings, and the required capacity addition from new electricity supply while holding the total investment from 2004-08 to $19.9 billion. The total capacity savings over the five-year period 2004-08 amount to 16.7 GW, while the corresponding total generation capacity addition over this period amounts to 15.5 GW. The supply and efficiency capacity available by 2008 in this scenario is thus 35.4 GW compared to a supply capacity of 22.1 GW in Scenario 1, which is accompanied by a deficit of 13.2 GW.

Table 3: Supply with Efficiency Scenario - 2: Characteristics of Efficiency measures, and

Efficiency Savings and Supply Capacity

Energy Efficiency Measure (Col. 1)

Investment ($/kW) (Col. 2)

Daily Use (Hours/day) (Col. 3)