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Large Developing Economies
The Rural-Urban Divide, Air Pollution and Climate Policy
May 7th, 2013; Oslo
Email: [email protected]
Characteristics of Rural Energy Use: Insights from India
Page 2
Energy Access– a perception
Defining Access: The Global Understanding Energy poverty is a lack of access to modern energy services. These services are defined
as household access to electricity and clean cooking facilities (e.g. fuels and stoves that do not cause air pollution in houses) (IEA, 2012; ADB, 2011; UNDP/ESMAP, 2010)
Electricity access considered as the existence of a first connection (IEA, 2012)
Clean cooking fuels considered as LPG, Biogas among others (Masera, et. al, 2000; Johnson & Bryden, 2012)
Defining Access: To the household (Pandey, 2002; Rehman, 2010; Pundo & Fraser, 2006)
Reliability
Actual consumption
Do we need to standardize? Access to clean energy fuels is a challenge: Ensuring equity and access are critical
What is transition? (Kojima, et. al, 2010; Pachauri, 2011; Jiang & O’Neill, 2004)
To facilitate a shift to cleaner fuels or a mix of fuels such that the overall benefits of
energy access are greater in terms of additional health and livelihood benefits ?
Page 3
Rethinking Energy Access
Mandla, Madhya Pradesh, India Sonabai’s daily routine – Early morning walk to the forest to collect firewood
Cook at home
Tend to the fields
“Electricity comes for only one hour a day in total….the bulb is always on….It suddenly lights up in the middle of the night or in the day… what is the use….it was better without electricity….We still spend Rs.100 every month on kerosene and now we have to pay another Rs.60 for electricity which is of no use.”
Page 4
Understanding household energy choices
Changes in Income flows
(Occupation and Opportunities)
Value of Labor (Gender roles)
Intervention (Energy or livelihoods)
Development Priorities
(Importance of energy)
Household Energy Basket
Page 5
The Indian context
75.92
12.09 6.11 0.79 2.46 1.53
17.56
64.6
1.38 6.38 0.92
6.55
0 10 20 30 40 50 60 70 80
Fire
woo
d an
d Ch
ips
LPG
Dung
cake
Kero
sene
Oth
ers
No
cook
ing
arra
ngem
ent
Perc
enta
ge H
Hs re
port
ing
prim
ary
cook
ing
fuel
Rural Urban
33.54
65.61
0.28 0.28 4.85
93.83
0.54 0.25 0
10 20 30 40 50 60 70 80 90
100
Kerosene Electricity No lighting arrangement
Others
Perc
enta
ge H
Hs re
port
ing
prim
ary
light
ing
fuel
Rural Urban
Almost 76% rural households are still dependent on traditional biomass fuels for cooking.
Cleaner fuels such as LPG have very little coverage (about 12%) among rural households.
In comparison, almost 65% urban households indicate use of LPG as a cooking fuel.
Only 65% of rural households indicate electricity as their primary source of lighting.
Issues of regularity of supply In urban areas, in comparison,
more than 90% households have access to electricity as a primary source of lighting.
Source: NSSO 66th Round, 2009-10
Page 6
55TH(1999-00), 61ST(2004-05), 66TH (2009-10) ROUNDS
National Sample Survey (NSS) Data Analysis
Page 7
Energy Consumption patterns across rural households in India
Source: NSSO 66th Round, MoSPI, Govt. of India
Page 8
Key Observations for Rural India – Penetration Rates across income classes
Fuel NSSO Round
Low Income (bottom 20%) Med Income High Income
(top 20%)
Cook
ing
FW
55 82-84% 79-81% 46-75%
61 78-81% 79-81% 43-75%
66 85-87% 81-85% 38-75%
LPG
55 0-1% 1-5% 5-29%
61 0-1% 3-9% 9-39%
66 0-2.5% 2.5-11% 12-42%
Ligh
ting
Kerosene
55 65-73% 47-61% 17-45%
61 60-70% 40-59% 13-40%
66 54-61% 23-50% 9-20%
Electricity
55 24-30% 33-50% 57-81%
61 28-35% 40-58% 63-85%
66 37-54% 51-71% 74-90%
Page 9
Energy Usage Patterns Across households for cooking & lighting
- Firewood still remains the major cooking fuel - Switch from firewood to LPG is occurring
only among the higher income classes
- Switch to modern lighting fuels is occurring at lower income classes over time, indicating improved access to modern lighting fuels and a clear transition path
Findings based on three rounds of NSSO data (1999-00, 2004-05, 2009-10): Energy transition to modern fuels for cooking is lagging in comparison to lighting
66 61
55
Page 10
Inequality across income classes
• Inequality in consumption of biomass and petroleum fuels increases with increase in incomes
• Inequality in electricity consumption decreases with increase in incomes
• Higher incomes have wider choices unlike lower income households
• Income – Electricity correlated as electricity access is related to ability to pay and HH economic status
BIOMASS FUELS PETROLEUM FUELS
ELECTRICITY
Page 11
India – Agro-climatic Zones
Page 12
Inequality across regions – Biomass and Petroleum
• For biomass and petroleum products, Zones 1 and 6, that have very low income inequality, have high energy inequality.
• Zone 6 includes the rich states of Punjab, Haryana and Delhi. These states have high income and as a result the inequality in energy consumption is probably due to availability of more choices
• Zone 1 includes the mountain states of Kashmir and Himachal Pradesh. Here, inequality could be due to substitution from other forms of fuel (this requires further study)
Page 13
Inequality across regions - Electricity
• Conforming to previous results regarding electricity, regions with lower income inequality have lower electricity inequality.
• Possible cause would be lack of substitutes for electricity, ability to pay and/or willingness to pay for electricity
Page 14
NSS data – Key Findings
Transitions in cooking fuel choices is a major challenge
If income is a prime determinant, expected causation would be that energy inequality would have a direct correlation to income inequality – NSS data indicates significant deviations from this hypothesis
Traditional notion of access to electricity vis-à-vis field experience – Access differs across income groups and regions
Different bandwidths exist across income classes and within/across regions for transitions
Responsiveness of livelihood interventions will differ across regions and income groups – approach should be acceptable within a particular socio-cultural construct
Use of natural resources is defined locally – differential impacts of prices across regions and income classes – While biomass resource price is determined locally (distance and availability),
price of cleaner fuels determined by state/regional boundaries
Page 15
TERI-NFA SUPPORTED BY THE NORWEGIAN MINISTRY OF FOREIGN AFFAIRS
Analyzing Rural Energy Transitions and Inequities in India
Page 16
Project Objectives
To analyze rural energy inequalities and transitions
How transitions to clean energy can be enabled in rural India?
Calculate inequality measures in energy consumption patterns in rural India Reasons for differing energy consumption patterns Drivers of transition to clean energy: relationships between socio-economic
parameters, household fuel choice and energy demand Barriers and effectiveness of interventions Gender implications
Page 17
MANDLA, RAISEN, RATLAM, & BETUL DISTRICTS OF MADHYA PRADESH
PILOT SURVEY ANALYSIS
Page 18
Pilot Survey – Madhya Pradesh
Madhya Pradesh comprises of 50 districts that are grouped into 10 divisions. A primary survey was conducted in four districts of four divisions of Madhya Pradesh.
– Bhopal Division: Raisen district
– Jabalpur Division: Mandla district
– Narmadapuram Division: Betul district
– Ujjain Division: Ratlam district
Data was collected for 200 households on various indicators ranging from primary cooking fuel, primary activity for men and women, education level of household.
Two Blocks from each district were covered and two villages from each block were surveyed to maintain a good sample of the households.
The data collected at the household and village level was based on interviews with the village residents with the help of a pre-designed questionnaire.
Page 19
Pilot Sites
Page 20
Logit Model (1) – With electricity access
Primary cooking fuel Robust Coef. Std.Err. z P>|z| [95% Conf. Interval]
socialstatus -0.1432212 0.801239 -0.18 0.858 -1.713621 1.427178
Primary livelihood activity (Men) 2.018577 0.885418 2.28 0.023** 0.2831907 3.753964
mpceclass 0.8372557 0.413984 2.02 0.043* 0.0258613 1.64865
logedumale 2.393379 2.112356 1.13 0.257 -1.746763 6.533521
logedufemale 1.726696 0.973183 1.77 0.076 -0.180708 3.634099
timelive -3.242136 1.241909 -2.61 0.009*** -5.676233 -0.808039
loghhsize 2.145111 2.08919 1.03 0.305 -1.949626 6.239848
logpLPG -156.4151 35.97687 -4.35 0.000*** -226.9285 -85.90176
logpsko 62.84464 56.72915 1.11 0.268 -48.34246 174.0317
logpfw 15.45975 37.37725 0.41 0.679 -57.79832 88.71782
logland 2.163311 0.964814 2.24 0.025** 0.2723105 4.054312
elecaccess 7.249156 2.177322 3.33 0.001*** 2.981684 11.51663
_cons 760.6622 . . . . .
Estimated Coefficients
Number of Observations = 185 Pseudo R2 = 0.6750 Log pseudolikelihood = -14.4382 AIC*n = 54.877 BIC' = 2.666 Hosmer-Lemeshow chi2(8) = 0.36 Area under ROC curve = 0.9851 Correctly classified = 96.76%
Page 21
Logit Model (1) - Results
The results show that primary occupation of men, MPCE class, timelive, log of price of LPG, land ownership and electricity access is found to be significant. These variables influence households decision over cooking fuel.
Odds ratio can be interpreted as the probability of going higher up the energy ladder to the probability of not going. For a unit change in primary livelihood activity for men, the odds of choosing cleaner cooking fuels
are expected to change by a factor of 7.52, ceteris paribus. It can also be interpreted as, for every unit increase in primary livelihood activity for men, the odds of choosing a cleaner cooking fuel is expected to increase by about 652% [100*(7.52 – 1)], ceteris paribus.
The signs for ‘price of firewood’ and ‘price of LPG’ are opposite – indicating substitutes
Page 22
Logit Model (2) – without electricity access
Primary cooking fuel Robust Coef. Std. Err. z P>|z| [95% Conf. Interval]
socialstatus 0.4367723 0.450506 0.97 0.332 -0.4462 1.319748
Primary livelihood activity (Men)
0.8744928 0.476518 1.84 0.066 -0.05947 1.808451
mpceclass 0.3709437 0.252937 1.47 0.142 -0.1248 0.866691
logedumale 2.8849850 1.803539 1.60 0.110 -0.64989 6.419856
logedufemale 0.7711796 0.664561 1.16 0.246 -0.53134 2.073694
timelive -1.4702760 0.583332 -2.52 0.012** -2.61359 -0.32697
loghhsize -0.2291600 1.319293 -0.17 0.862 -2.81493 2.356608
logpLPG -103.02280 12.38131 -8.32 0.000*** -127.29 -78.7559
logpsko 36.704110 19.78822 1.85 0.064 -2.08008 75.48831
logpfw -0.9883915 13.12615 -0.08 0.940 -26.7152 24.73838
logland 1.5319420 0.548026 2.80 0.005*** 0.457831 2.606052
_cons 531.87870 . . . . .
Estimated Coefficients
Number of Observations = 185 Pseudo R2 = 0.4874 Log pseudolikelihood = -22.775 AIC*n = 69.551 BIC' = 14.120 Hosmer-Lemeshow chi2(8) = 2.11 Area under ROC curve = 0.9456 Correctly classified = 95.14%
Page 23
Logit Model (2) - Results
‘Elecaccess’ defined as ‘receiving satisfactory electricity supply between 6PM - 9PM for at least 20 days in a month’
Without ‘elecaccess’, the model’s robustness changes
Dropping ‘elecaccess’ has resulted in indirect income variables being insignificant
Thus, productive use of electricity has significant impacts on household energy choices
Page 24
Inequality across Income groups – Biomass and Petroleum
GINI = 0.44
Trends similar to NSSO
Page 25
Beyond existing data
Secondary data indicates significant gaps in explanations for energy consumption patterns and energy inequalities across regions
Considerable variations (in traditions and norms, livelihood sources, market responsiveness) exist across regions
Income is not the only factor in determining household fuel choices Socio-cultural factors need to be accounted for – Cultures have evolved as a response to natural environment which varies across agro-climatic zones – Differing food habits, cooking habits – leading to differing energy use patterns
Variations exist both within and across regions – thus a particular state
cannot be representative of a region
Facilitate more action-oriented approaches with better impacts
Page 26
Primary Household Survey
Page 27
Survey Plan
Selected States
Maharashtra
Karnataka
Goa
Madhya Pradesh
Odisha
Rajasthan
Himachal Pradesh
Selected States
Page 28
Enabling transitions…Bridging the divide
Understanding of key barriers and drivers
Relevance to Policy
Towards an integrated approach
Page 29
Case Study 1: Goa
Background: – Forest-dwelling community
– Nearest road access about 10 kms.
– No electricity lines
Intervention: – Govt. installed solar-wind hybrid
system to generate electricity for the village
– Meters installed in all houses – pay for use
Current Status:
- System stopped working after 6 months
- No training provided to the locals on O&M
- Reverse transition from electricity to kerosene and biomass
Nadke village, Canacona taluk, Goa
Page 30
Case Study 2: Maharashtra
Background: – Forest-dwelling community; Mainly daily
wage earners – Nearest road access about 8 kms. – No electricity lines
Intervention: – Reliance Industries installed solar home
systems in every house as part of CSR project for 5 year duration
– Systems are not functioning properly now (4th year); in spite of O&M training , costs too high
Pachghar village, Thane District, Maharashtra
Current Status: ˗ Returning back to a situation of no electricity
˗ Too poor to afford kerosene, hence, use candles as and when possible
˗ Reverse transition from electricity to candles/no lighting
Page 31
Case Study 3: Karnataka
Shapur village, Bidar District, Karnataka Background:
– Forest-dwelling community; Mainly daily wage earners
– Nearest road access about 10 kms.
– No LPG connections due to land-holding issues and general access issues
Intervention: – No interventions
Current Status: - Restricted access to forests under FRA -
households buy firewood at Rs.400/quintal/month
- Local innovation is the key – initiative by the District Forest Department
- Use of locally grown Glyceria plant to meet biomass needs thus reducing pressure on forests
Page 32
Key Insights so far… (1/3)
Income measures may not be most relevant for targeting in interventions:
Inverse relation between income inequality and energy inequality
Econometric models vis-à-vis qualitative factors
Designing clean energy interventions in rural India requires evidence-base of other social and cultural factors
Financing mechanisms and delivery models need to be supplemented by technical support:
According to the pilot survey, most households indicate that financial assistance is not given to households for meeting specific requirements related to clean energy
Financing mechanism targeted at enabling energy transitions should consider the possibility of staggered payments
Page 33
Key Insights so far… (2/3)
Information, Education and Communication (IEC) activities for clean energy options needs further strengthening
Integrating energy efficiency into mainstream school curriculum (ex. Mandla and Raisen, Madhya Pradesh, India)
There is need to strengthen awareness and education related policies and activities around clean cookstoves as the perceived environmental and health benefits of improved cookstoves are not deemed significant enough to outweigh the financial costs involved
Entrepreneur-led models could help in the revival of biogas programmes
Land availability is a significant concern for individual biogas plants
Success of community plants is questionable due to variable levels of social capital and trust regarding land as a common pool resource
Biogas programmes could be revived through entrepreneur-led models for biogas
Page 34
Key Insights so far… (3/3)
Demonstration projects may lead to greater uptake
Bandwagon effects are visible in villages of Mandla and Betul
Demonstration projects may lead to greater uptake and acceptability of a particular technology
Page 35
Bridging the Gap – On-ground Policy Scenario
URBAN RURAL
Ministry of Urban Development: Jawaharlal Nehru National Urban
Renewal Mission
Mission for Basic Services to the Urban Poor
Ministry of Rural Development: National Rural Livelihood Mission; Mahtama Gandhi National Rural Employment Guarantee Scheme
Ministry of New and Renewable Energy:
National Program for Improved Cookstoves; National Biogas & Manure Management Program;
Enabling rural poor to increase household income through sustainable livelihood enhancements Ministry of Housing and Urban
Poverty Alleviation: Swarna Jayanti Shahari Rozgar
Yojana
Providing gainful employment to the
urban unemployed and under-employed poor
Public Distribution System
(Fair Price Shops)
Ministry of Power: Rajiv Gandhi Grameen Vidyutikaran
Yojana
Page 36
What we need to know…
What framework can help us in assessing energy transitions at the household level?
How should more state specific or regional energy policy interventions (both government as well as non-government) be designed?
What is the baseline electrical energy needed by a rural household given its geographical, socio-economic and cultural context? Given the constraints, how should its delivery be prioritized?
How can energy access interventions be integrated with other development interventions so as to make them locally appropriate?
How can new metrics and field insights related to energy access help facilitate informed decision making?
