The Two-Country CGE for Malaysia and Indonesia for Energy Subsidy Removal Yanfei Li Energy Economist, Economic Research Institute for ASEAN and East Asia.

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The Two-Country CGE for Malaysia and Indonesia for Energy Subsidy Removal Yanfei Li Energy Economist, Economic Research Institute for ASEAN and East Asia 16 Feb 2016 IAEE Asia 2016, Perth

Background: Indonesia Energy subsidy in Indonesia started in 1967 The distributional effects have been unequal and favored the rich who are more capable to consume more The energy subsidies appeared to drive for more inefficient use of fuels and electricity, and distort the market signals for energy-related investments On the government side, they became a fiscal burden and limits the fiscal policies’ capability to stimulate economic growth

Background: Malaysia Malaysia also provides subsidies on petroleum fuels and electricity. Specially, the subsidies on electricity has two channels. One is through subsidizing the natural gas supplied to TNB (one half of the company’s power generation capacity is natural gas-fired), the Malaysian national power corporation. The other is through special rebates given to low income households. Energy subsidies are found to cause more serious problems in Malaysia than in Indonesia. Specially, such subsidies in Malaysia were believed to incentivize the use of outdated and dirtier technologies with negative environmental impacts

Literature on Indonesia’s Energy Subsidies The impacts of Indonesia’s energy subsidy removal have been studied by a few studies which arrived at controversial conclusions. Hope and Sigh (1995), IEA (1999) and Mourougane (2010) estimated that GDP could be stimulated rather than depressed. Clement et al. (2007) estimated that there would be 2% real output loss in the case of Indonesia. The study by Widodo et al. (2012), using a Social Accounting Matrix method, shows a negative impact of subsidy removal on GDP. However, with reallocation of the subsidy to targeted sectors could offset the negative impacts to a large extent.

Literature on Malaysia’s Energy Subsidies The Malaysia government is considering the so-called rationalization of subsidies, implying liberalization of pricing to reflect the cost of supply while keeping the subsidies to targeted social groups. The impacts of Malaysia’s energy subsidy removal has been studied by Hamid and Rashid (2012), using a CGE model with the I-O table partitioned into energy and non-energy blocks. – This study shows a painful process of subsidy removal to the economy, including declining wages and rising costs of production factors which could substitute for reduced use of fuels. – However, the authors emphasize that such is healthy to long-term economic growth path of Malaysia and boost the competitiveness of Malaysia Industries.

Research Questions Indonesia and Malaysia are well linked in economics. – For Indonesia, Malaysia is the 7 th biggest export market – For Malaysia, Indonesia is the 9 th biggest market for its exports – They share a lot in terms of culture, language, as well as economic structure – To ask how energy subsidies on both sides have affected each other Both countries are embarking on massive reduction of energy subsidies – To see what would be the cross-border impacts of such actions – To see the difference in timing of action from either of the two countries If Malaysia cut energy subsidies first, what the impacts on Indonesia would be, and vice versa. To identify the most vulnerable sectors to subsidy removal To see how the reallocation of the fund of energy subsidies as public transfer for investment and consumption in different sectors would affect real output and welfare 6

Methodologies A two-country CGE model – Econometric sub-models will be built – Simulations to show not only the impacts of energy subsidy reduction, but also the impacts of different sequence in doing so by the two countries. To extend Hosoe et al. (2004) by incorporating energy sectors as well as energy products as factor inputs and commodities for consumption. – The model is static and nonlinear – It serves as a tool for short-term impact analysis – In the future, the framework could be extended into dynamic models Results to be compared to single country models from other ERIA projects 7

The Data Structure I

The Data Structure II

Non-energy Sector

Resources Sector

Electricity Production

Refineries

Integrating the Energy Sector in the CGE Model Domestic production - Composite factor aggregation function: F includes capital, labor, electricity, and other energy Intermediate demand function: Composite factor demand function: Factor demand function:

Electricity Generation Technologies: coal-fired, gas-fired, oil-fired, hydro, biomass, geothermal, solar PV, wind Electricity producing technologies are characterised by different cost structures and conversion efficiencies. Generation costs are conceived in three categories: i) investment costs, ii) operating and maintenance costs and iii) fuel costs. A cost minimization method is adopted to produce the desired amount of electricity A 8% transmission and distribution system losses is assumed.

Electricity Generation Function and Demand for Fuel Mix Linear cost of electricity generation leads to corner solution – dispatch by merit order

Scenarios for Subsidy Removal Simultaneous subsidy removal by the two countries Indonesia removes subsidies Malaysia removes subsidies Partial / selected removal Subsidies for targeted social groups only

Expected Policy Implications To identify policies that are needed to ensure net welfare gain for the economy in implementing energy subsidy reduction To suggest policies that could reduce energy subsidies while minimize the negative impacts on its own economy as well as possible leakages to trade partners To identify policies that are needed to minimize the negative impacts on specific sectors and social groups To suggest policies that are needed to optimally reallocate the funds for energy subsidies to various sectors and social groups To identify how to synchronize policies for removing energy subsidies to minimize negative impacts and to maximize possible gains 18