MODELLING OF DISTRIBUTIONAL IMPACTS OF ENERGY SUBSIDY REFORMS: AN ILLUSTRATION WITH INDONESIA

Christina Timiliotis, Junior Policy AnalystOECD Trade and Agriculture Directorate

APEC Fossil Fuel Subsidy Reform Capacity Building Workshop, 14-15 December, Honolulu

• Redistribution schemes can play a crucial role to make the subsidy reforms acceptable and equitable

• The sole analysis of macroeconomic and environmental impacts is insufficient when considering energy subsidy reforms

• What are the distributional consequences of a fossil-fuel subsidies phase out and which compensatory measure minimizes inequality and poverty?

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Motivation

Macro model Microsimulation models

The analytical framework

Economy -wide effects

• Market prices• Wages and rents• Taxes and transfers

Household-level effects

• Income• Expenditures• Demand adjustment

Fossil fuel consumption subsidy phase out

Economic Efficiency

Environmental effectiveness

Distributional effect

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The energy consumption subsidy phase out scenarios

Linear phase out of energy consumption subsidies in Indonesia from2012 to 2020

• Electricity, gasoline, diesel, kerosene, LPG • For firms and households

3 different redistribution schemes:Cash transfer: all the households receive identical paymentFood subsidies: food & agricultural products are subsidizedLabour support: households receive payments proportional to theirlabour income

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Macroeconomic impact

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Limited gains on GDP due to modest share of energy consumption in total household consumption

Distributional impact

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Net real return rates by income sources in various scenarios in 2020

Cash transfer requirements to compensate households

What fraction needs to be redistributed to keep constant the real income of households until to a given decile?

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Strong emissions reduction: ~8% for GHG for all scenarios

GHG impact

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• Cash transfer scheme represented is stylized and tends to abstract from the institutional context

• Modelling framework is limited with in terms of redistribution mechanisms (e.g. provision of public services)

• Underlying assumption of the approach are equal commodity prices for all households

• Representation of households’ sources of revenue remains very simplified

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Shortcomings

• Based on our simulations: cash transfers are the best way to make a phase out more efficient and equitable

• However, it is necessary to consider the feasibility of such mechanism

• Alternatively, cash transfers might be limited and targeted to more specific households

Conclusions

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THANK YOU

For further information: Christina.timiliotis@oecd.org

Please find the link to the paper here: http://www.oecd.org/officialdocuments/publicdisplaydocume

ntpdf/?cote=ENV/WKP(2015)7&docLanguage=En

APPENDIX

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Transfers: the revenues generated by the phase out can be redistributed to the households based on eligibility criteria.

Households may be impacted differently by an energy consumption subsidy reform

Expenditures: consumer prices change and the impacts on household groups depend their consumption structure and on how they behave

Income: the policy can affect wage rates as well as non-wage factor income and the impact on households’ income depend on their sources of income

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Microsimulation models, based on household budget surveys, are often needed for quantifying the differences in impacts between household groups

Combining micro and macro approaches

But for a energy subsidy phase out has economy-wide effects, and a microsimulation model has to be linked with a macroeconomic model• The effects on the phase on final prices and households’ income

depend on the whole structure of the economy

• Redistribution schemes cannot be featured without representing how governments’ budget adjusts to the policy

• Distributional, environmental, economic effects interplay

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The decomposition algorithm at iterationk and period t

CGE model with 1 representative

household

Microsimulation model:1-Household-level revenues computation2-Household-level optimal consumptionand savings

Final good prices

Total households’ consumptions and

savings

Production factors’ prices

Recalibration of the representative

household’s utility function

calibrated representative household’s utility function

iteration k+1

iteration k

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• Low budget shares of energy• Increasing share of food consumption• The share of formal labour in revenue decrease with income

Elements on households heterogeneity

0%10%20%30%40%50%60%70%80%90%

100%

1 2 3 4 5 6 7 8 9 10deciles

Labour (formal) Labour (informal)Capital LandNatural resource Transfers

0%10%20%30%40%50%60%70%80%90%

100%

1 2 3 4 5 6 7 8 9 10deciles

Electricity Gasoline and DieselKerosene and LPG Transportation servicesAgricultural products Food productsManufactured goods Services

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Based on the IFLS4 household budget survey data, >10000 Indonesianhousehold groups are explicitly represented in the multi-period,multi-region CGE model

For the models’ base year, household-specific parameter arecalibrated on the HS data

• Parameters of the extended linear demand system

• Endowments in production factors

The baseline projection is generated assuming that the households’preferences and endowment parameters are static: no structuralchange

Resolution of the integrated model using a decomposition algorithm(Rutherford et al. 2006)

Representative households groups for Indonesia in ENV-Linkages

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Remarks on the imputation process

• Gasoline and diesel expenditures are not explicitly represented in the HS.They are proxied based on information about expenditures for transportationand vehicle ownership

• Profits from own business assigned to labour and capital revenue categoriesusing values shares from the corresponding sector in the CGE.

The process for reconciling the HS and the CGE data ensures:

• Micro-macro accounting consistency: for each expenditure and incomecategory, the total over households adds-up to the CGE base-year value

• Balance budget for individual households: for each household, the totaldisposable income is equal to the sum of expenditures and savings

• “Steady state savings”: for all the households, the ratio between savings andcapital revenues is the same. This requirement is used because of the multi-period setting in order to avoid a massive reallocation of capital incomebetween the households in the baseline scenario

Imputation and reconciliation of survey data with the CGE

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Driving mechanisms of distributional impacts in the cash transfer scenario

The redistribution scheme makes the reform progressive• The direct effect through final price changes is slightly regressive

• The cash transfers effect is very progressive and dominates theregressive effects of final price changes

-5-3-113579

111315

1 11 21 31 41 51 61 71 81 91income centile groups

Total effect

Final price effect

Transfer effect

Source: ENV-Linkages

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Driving mechanisms of distributional impacts in the labour support scenario

The effect through labour income is regressive as labourincome from formal activities represents a lower proportion of total income for higher-income than for lower-income households

-5-4-3-2-1012345

1 11 21 31 41 51 61 71 81 91income centile groups

Total effect Final price effect Labour income effect

Source: ENV-Linkages

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Conclusions (1/2)

The energy consumption subsidy phase out contributes to emissions reduction: ~8% for GHG and ~12% for CO2, if excluding emission from tropical forest fires

Positive impacts on GDP (+0.4 to +.7% in 2020 w.r.t. baseline)

Direct price effect of subsidy removal is regressive but the compensation schemes can make the reform progressive

Cash transfers are the best policies in terms of GDP growth, and inequality reduction

Impacts of the redistribution schemes • Cash transfers: very progressive• Food subsidies: slightly progressive• Labour support: regressive

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