How can we understand the impact of energy subsidies and their reform on households?

People’s ability to afford electricity to light their homes or power their household appliances, pay for gas to cook or heat their homes, or buy fuel to run their businesses has been a concern for many poor and vulnerable households. In recent years, even middle-income households in developing and developed countries alike started feeling such pressures. It’s no surprise, then, that various media outlets have been reporting extensively on how energy affordability concerns affect daily lives of households and small business owners, such as this New York Times story about those in Ecuador, Nigeria and the Philippines (similar stories are here, here, here, here, here and here).

Governments have deployed various tools to address these concerns. These included broad-based energy subsidies, often through keeping the price of commodities low for all consumers—such as when gasoline is sold at prices well below what it costs to produce and deliver it.  

While they may help keep energy prices low, broad-based energy subsidies come with significant costs for the economy, society, and the environment. On top of the resulting fiscal cost, economic inefficiency, and environmental damage, untargeted universal subsidies are also an inefficient and ineffective way of supporting the poor. They often benefit better-off households that consume more energy, instead of channeling support to the those who need it the most. In other words, despite all the government spending to finance them—money that could have gone to poverty reduction, job creation, human development, or infrastructure investments—those subsidies don’t always fully and exclusively benefit the poor. To make matters worse, sometimes, governments aren’t completely clear on whom the existing subsidies benefit.  

Nonetheless, universal subsidies still deliver some benefit to the poor, and their sudden and wholesale removal can negatively impact lower-income households as well.

All of this makes one thing clear: it is critical to understand whom existing energy subsidies benefit, and how different households stand to be affected by different options for reforming them. 

This is where distributional analysis comes in, as a critical tool to assess the incidence of existing subsidies and identify potential impacts of reforms for households across the income distribution. Sound distributional analyses can help governments identify ways to strengthen energy subsidy reform design options to mitigate the most critical impacts of reform  through better-targeted support, and help address political economy constraints.

To better understand how this can be done, a new ESMAP Technical Report reviews main approaches and methodologies for distributional analysis and explores how they were deployed in real-world energy subsidy reform efforts to help governments analyze available options and inform reform designs.   

Real-world reform experiences in Guinea, Indonesia, Ukraine, and Uzbekistan illustrate how different approaches were deployed in diverse country contexts, to help governments assess potential impacts of reforms on poverty, affordability, and inequality. In each country, standard approaches were tailored to country settings, and further refined during implementation. Some highlights are below.

• In Ukraine, a standard distributional analysis drew on extensive data for a comprehensive assessment of potential reform options. It found that, prior to reform, poorer households spent a higher proportion of their income on energy bills compared to the rest of the population, while existing subsidies disproportionately benefited wealthier households with higher energy consumption. As a result of the reform, which recognized and sought to address the distributional impacts, the targeting of government support was improved, and became gradually more progressive, with a larger share of benefits going to the poorest income quintile. The reform also helped reduce energy expenditures for low-income households and limited the increase in poverty rates.
• In Indonesia, distributional analysis of electricity and fuel subsidies was undertaken as part of broader fiscal analysis using the Commitment to Equity (CEQ) framework. This approach was useful in highlighting the fiscal magnitude and distributional impact of energy subsidies relative to other, more effective, social programs.
• In Uzbekistan, in early 2010s, at a time when there were greater data constraints (which have since been addressed through extensive government effort) quantitative approaches were complemented by qualitative analyses, involving stakeholder surveys, focus group discussions, and in-depth interviews. This allowed the analysis to reveal insights that would otherwise not have been captured through quantitative data and helped inform the government’s reform efforts.
• In Guinea, distributional implications of different electricity tariff increase scenarios had to be analyzed amid substantial data availability constraints, and the modeling approach had to be adapted to the context, with transparent assumptions.

Country and sector context, reform objectives, and systemic factors play a critical role in determining the feasibility and usefulness of various approaches to distributional analysis.  Each analytical approach has different strengths, weaknesses, and resource requirements, and that even when a methodology is well developed, the quality of the analysis is strongly dependent on the data available and the underlying assumptions. The work may not always be straightforward, and teams may have to be creative in combining various sources of information and methods available to overcome data constraints. In this context, transparency about data sources, assumptions and methodological limitations is critical.

As governments contemplate how to reform harmful energy subsidies, well-designed and context-appropriate distributional analysis can strengthen reform design, especially when initiated at an early stage.  The relevance and usefulness of these analyses can be enhanced through choosing context-appropriate methodologies, focusing on data availability and quality, allowing greater transparency, and ensuring the availability of the right skillsets.

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