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For valuable comments and suggestions, we would like to thank Benedict Clements, David Coady, Irineu de Carvalho Filho, Julio Escolano, Chris Lane, Edouard Martin, Pierre Nguimkeu, Jean Noah Ndela Ntsama, Sanjaya Panth, Nathan Porter, Martha Ruiz Arranz, Philippe Wingender, Daria Zakharova, and participants in the departmental seminar in the IMF’s Fiscal Affairs Department and in the Discussion Forum in the Middle-East and Central Asia Department at the IMF. The usual disclaimer applies.
See also IEA and others (2010), a joint report on the scope of energy subsidies (with suggestions to phasing them out) for the 2010 G-20 Summit Meeting in Toronto.
Pre-tax energy subsidies are generally higher among net oil exporters. They absorbed around 22 percent of government revenues in the MENA region in 2011 (see Regional Economic Outlook, Middle-East and Central Asia, IMF (2013b)).
In a review of the evidence on the welfare impact of energy subsidy reform across twenty countries from Africa, Asia, the Middle East, and Latin America, Arze del Granado, Coady, and Gillingham (2012) finds that the top income quintile captures six times more in subsidies than the bottom, in absolute terms. These distributional effects vary substantially across products with the subsidies on gasoline being the most regressive. Also, a study by the International Energy Agency (see IEA (2011)) finds that the poorest 20 percent of households receive only about one-tenth of natural gas and electricity subsidies.
Notwithstanding the recent sharp drop in international oil prices, they are still at about their pre-crisis level (see appendix, Figure 3), and crude oil futures show some signs of pick-up in the near term.
IMF (2014) provides empirical evidence that public support for redistributive policies has grown in recent decades, partly due to rising inequality. Energy subsidies, however, disproportionately benefit upper-income groups and would not reduce inequality, which adds to the puzzle.
Economic agents may also favor energy subsidies over public social spending that potentially guarantee higher future earnings to their children if their degree of altruism or their discount factor are low enough, or if the perceived return to education/health is highly uncertain. This is more likely to be the case among lower-income groups, generally credit-constrained.
The rich favor the high energy subsidies equilibrium because it implies large private savings on their energy bill (using public resources) and therefore more (private) resources left for non-energy consumption.
Pani and Perroni (2014) propose a political economy model whereby energy subsidy reform is hard to achieve because of a commitment problem: the adoption of energy-saving techniques weakened the motives to reduce energy subsidies as initially announced.
Baqir (2002) also finds that democratization is a significant predictor of government spending on education and health in a large panel of countries.
Ellis (2010) offers a review of models and empirical studies on the effects of fossil-fuel subsidy reform.
Throughout the paper, the subscript r denotes rich agents (or members of the elite) and p denotes poor agents (part of the middle-class).
It is important to stress that our results do not depend heavily on the specification of the utility function—the adopted functional forms aim at developing the main intuitions of the model, through the lense of close-form solutions. For instance, we briefly discuss below the implications of adopting a functional form that is non-separable in c and k.
The model assumes that the share of the energy good (and of the non-energy good) is the same in the consumption basket of the rich and the poor. It is straightforward to solve the model with different consumption shares across the two groups of agents.
This is equivalent to assuming that the quality of domestic institutions is exogenous. In reality, however, public social spending would improve the human capital of the poor and perhaps their participation to the electoral process in a democracy. Our model is quasi-static in that sense.
The timing of the game may be thought of as reflecting the fact that the middle-class forms the majority of the population, prompting the elite to internalize their “move” (see backward induction below). This timing is common in the political economy literature (see, e.g., the seminal paper by Acemoglu and Robinson (2001), and Acemoglu (2014, Chap. 13)).
The amount of energy subsidy is a combination of the subsidy rate and the amount of energy that agents consume in equilibrium.
International agencies such as the IEA, the IMF, and the World Bank have raised this concern over energy subsidies—not sending the right price signal to consumers may lead to an inefficiently high level of energy consumption and hence higher CO2 emission.
The model may also be set-up in a way that ζ captures the probability that the politician will actually deliver on the public good’s promise.
Note that the non-energy good, n, does not enter the common pool budget constraint, given that it is entirely paid for by agents privately.
Equation (7) suggests that this condition holds as long as the entire pool of common resources is not devoted to energy subsidies in equilibrium (which is highly likely).
Given that pre-tax subsidies are positively defined by definition,
We consider averages over sub-periods rather than yearly time series for robustness. In fact, changes in subsidies and social spending from one year to another could be arbitrary. The 2006–07 cut-off is chosen to reflect the dynamics in energy prices, but the point made here holds for alternative cut-off dates (and hence sub-periods).
MENA countries, Indonesia, and Moldova are represented on the figure with their flags.
It is worth emphasizing the necessity to control for the government size in the model. In fact, all categories of spending may also go down regardless what happens to energy subsidies (e.g., if tax revenues fall). We therefore control for the government size (spending-to-GDP, excluding subsidies) to make sure we isolate the marginal effect of subsidies on public social spending. We focus on social spending for political economy reasons, as highlighted in the introduction.
All the variables are averages over the sample period (2000–11).
We are grateful to David Coady for bringing this useful interpretation to our attention.
To anticipate a bit on our estimation results, the extent of energy subsidies in neighbor countries alone accounts for one quarter of the total variation in energy subsidies across countries and for up to half of the variation among the net oil exporters.
The database is available at: http://cepii.fr/CEPII/fr/bdd_modele/presentation.asp?id=6.
The government size and tax revenues could not be included simultaneously in the regressions, due to their high correlation.