By Ali Enami (PhD Candidate, Department of Economics, Tulane University), Nora Lustig (Samuel Z. Stone Professor of Latin American Economics, Tulane University; director of the Commitment to Equity institute; nonresident fellow of Center for Global Development and Inter-American Dialogue), and Alireza Taqdiri.
http://d.repec.org/n?u=RePEc:tul:ceqwps:48&r=ara
Policy Brief
In December 2010, Iran’s government replaced its energy and bread subsidies with a lump-sum cash transfer known as the Targeted Subsidy Program (TSP) (Guillaume et. al. 2011). The transfer was set at about $40 (current 2011 dollars) per person per month for all Iranians, including children of any age. The government justified this reform on two main grounds: the high fiscal burden of the energy subsidies, which amounted to 20% of GDP in 2010 (or $70 billion US dollars), and the fact that fiscal resources disproportionately were benefitting the non-poor (Guillaume et. al. 2011; Salehi-Isfahani et al. 2015). In this paper, we examine the components of Iran’s fiscal system in general and TSP in particular in order to evaluate the impact and effectiveness of each component in reducing inequality and poverty. We pay a special attention to TSP, because of its important role in reducing inequality and poverty, and through simulation we show how it could have a greater impact if it is targeted better toward the lower deciles of income distribution.
Fiscal incidence analyses usually rely on estimating the effect of taxes and transfers on various indicators of inequality and poverty. What is generally missing in these studies is to put these estimation in a proper context. Given the size of taxes raised and transfers, is a 0.02 Gini points reduction in inequality or 5% percentage points reduction in poverty headcount ratio big or small? The simple solution, which is to divide these values by the size of the corresponding tax or transfer is not correct. Many inequality and poverty indicators do not have a linear relationship with the size of programs and, therefore, big programs appear to have a lower “bang for the buck” than they actually have. Therefore, in our study not only we measure the impact of various components of Iran’s fiscal system on inequality and poverty, but also we use a proper set of effectiveness indicators to determine how successful various taxes and transfers are in achieving their maximum potential.
To measure the contribution of taxes and transfers to fiscally-induced changes in inequality and poverty, we use the marginal contribution approach (Lambert, 2001; Enami, Lustig, and Aranda, forthcoming). By this method, the contribution of a tax or a transfer to a change in inequality is measured by comparing the existing fiscal system to a counter-factual that excludes the tax (or transfer) of interest. For example, the marginal contribution of direct taxes to reducing inequality is measured by comparing the Gini of the system with direct taxes to the Gini of the same system without direct taxes. One also can think of this counter-factual as having the tax or transfer replaced with an alternative tax or transfer of the same size but with no effect on inequality or poverty. This approach is superior to using progressivity indicators (such as the Kakwani index) for determining whether a tax (or transfer) is inequality-increasing (or decreasing). That is because standard progressivity indicators can yield the wrong prediction, in terms of the impact of a particular intervention, when the number of fiscal instruments is greater than one. When a fiscal system is composed of multiple taxes and transfers (strictly, more than one), a progressive tax (or transfer) can actually increase inequality and a regressive tax (transfer) can reduce inequality.
To measure the effectiveness of taxes and transfers in reducing inequality and poverty, we follow Fellman et al. (1999) and Enami (forthcoming(b)), and define effectiveness by comparing how close the actual marginal contribution of a tax (transfer) comes to achieving its optimal effect. The optimal effect is obtained as follows: a given amount of taxes (or transfers) can be collected (allocated) in such a way as to maximize the impact on inequality (or poverty) reduction. In the case of the Gini coefficient, for example, the maximum effect comes from collecting taxes from the richest individual until his/her income becomes equal to that of the second richest; then taxing both of them until their income becomes equal to that of the third richest person. This process continues until all of the required tax is collected. This procedure maximizes the reduction in Gini while keeping the size of the collected tax constant. An “optimal” transfer would follow a similar procedure, but would start with the poorest individual and move him/her up the income distribution.
In our analysis, we use the Iranian Household Expenditure and Income Survey for 2011/12 (1390 Iranian calendar). We find that the combined effect of direct and indirect taxes, cash transfers, and indirect subsidies is a decline of 0.0854 points in the Gini coefficient and 10.5 percentage points in the poverty headcount ratio. Transfers are relatively more effective in reducing inequality than taxes. For example, direct transfers together realize about 40% of their potential to reduce inequality while direct taxes together only realize about 20% of their potential. Direct and indirect taxes are especially effective in raising revenue without causing poverty to rise, a desirable property of fiscal systems. While transfers are not targeted toward the poor, they reduce poverty significantly. The main driver is the Targeted Subsidy Program (TSP), a universal cash transfer program implemented in 2010 to compensate individuals for the elimination of energy subsidies. In spite of its large poverty reducing impact, the effectiveness of TSP is rather low because of its universality. We show through simulations that given the amount spent on TSP, the poverty reducing impact could be enhanced, almost two times, if resources were more targeted to the bottom deciles while keeping the program budgetary neutral.
References
Lambert, Peter. 2001.“The distribution and redistribution of income”. Manchester University Press.
Enami Ali, Nora Lustig and Rodrigo Aranda Balcazar. Forthcoming. “Analytic Foundations: Measuring the Redistributive Impact of Taxes and Transfers”. A chapter in N. Lustig (Ed.) “Commitment to Equity Handbook. A Guide to Estimating the Impact of Fiscal Policy on Inequality and Poverty”. Brookings Institution Press and CEQ Institute of Tulane University.
Enami Ali. Forthcoming (b). “Measuring the Effectiveness of Taxes and Transfers in Fighting Poverty and Inequality in Iran”. A chapter in N. Lustig (Ed.) “Commitment to Equity Handbook. A Guide to Estimating the Impact of Fiscal Policy on Inequality and Poverty”. Brookings Institution Press and CEQ Institute of Tulane University.
Fellman, Johan, Markus Jäntti, and Peter J. Lambert. 1999. “Optimal Tax-Transfer Systems and Redistributive Policy.” Scandinavian Journal of Economics 101, no. 1. pp. 114-126.
Guillaume, Dominique M., Mohammad Reza Farzin, and Roman Zytek. 2011. “Iran: The chronicles of the subsidy reform”. International Monetary Fund.
Salehi-Isfahani, Djavad, Bryce Wilson Stucki, and Joshua Deutschmann. 2015.“The Reform of Energy Subsidies in Iran: The Role of Cash Transfers.” Emerging Markets Finance and Trade 51, no. 6: 1144-1162.
Acknowledgment:
This paper was produced under the research program on fiscal incidence in low and middle income countries of the Commitment to Equity (CEQ) Institute at Tulane University (www.commitmentoequity.org) and the Economics Research Forum (ERF). An earlier version of this work was partly published as ERF Working Paper Number 1020 (http://erf.org.eg/publications/role-fiscal-policy-fighting-poverty-reducing-inequality-iran-application-commitment-equity-ceq-framework/) and partly published as CEQ Working Paper Number 58 (http://www.commitmentoequity.org/publications-iran/). The authors are very grateful to ERF for its financial and intellectual support. The contents and recommendations do not necessarily reflect ERF’s views and any remaining errors are the sole responsibility of the authors.
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