The Time is Ripe for Means-Testing

Mauritius has relatively low levels of absolute and relative poverty: less than 1% of the population lives with less than $2 a day and around 8% of the population earns below half of median-income (compared to 17% in the United States). Several explanations: (1) the ‘rising tide did raise most boats’ (Mauritius has been among the top 10 fastest growing nations in the world in the last 30 years), (2) a generous welfare state, by the standards of middle income countries (for example, it is estimated that, if the current universal state retirement pension scheme were to be removed, relative poverty would rise from 8% to 14%) and (3) Asian-style family structures which ‘insure’ individual members against income shocks. The Mauritian welfare state has traditionally been universal in its nature: education and health (a copy of the NHS) are free to all, the state retirement pension is non-contributory and there are direct subsidies on basic commodities such as flour, rice and gas. Right now, there is a heated debate in the country about whether the state transfers should be more targeted towards, well, those who really deserve them, i.e. the poor or they should stay universal. Current empirical evidence elsewhere in the world is at best mixed, but for a country like Mauritius, the balance seems to be tilting in favour of means-testing.

According to Amartya Sen, targeting/means-testing have the following clear-enough benefit: “the more accurate a subsidy is in reaching the poor, the less the wastage, and the less it costs to achieve the desired objective. It is a matter of cost-effectiveness in securing a particular benefit.” But, he adds, this elementary vision of targeting must be weighted against some of the costs:

1. inaccurate specification of who are in fact poor and/or information manipulation (i.e. the rich passing as poor, especially in economies with big informal sectors)

2. poorly designed programs that do not reach the target group even if it is known accurately

3. poor governance/corruption in the implementation of schemes so that the costs exceed the benefits.

4. Incentive distortion, i.e. the prospect of losing a subsidy if one were to earn too much can discourage economic activity.

5. Stigma of being on benefits

Some of these factors should not be underestimated. In a 2005 report on poverty-reduction strategies in India, Thailand, Indonesia, the Philippines and China, the Asian Development Bank had this to say:

Experiences in the five case-study countries suggest that errors have been very significant, leakage rates have been high and many of the poor have not been covered, with the implication that in some cases these programs have had only a minor impact on poverty reduction.

In India, State governments had the responsibility for identifying the poor,
although the process was slow and incomplete and even where surveys were
undertaken identification cards were not provided to a significant number of poor families.

In Indonesia there have been many allegations of corruption and malpractice… For example, the employment creation programs through labor-intensive infrastructure schemes, which were one of the key planks of the response to the impact of the Financial Crisis, were alleged to have been associated with considerable malpractice by local officials as expenditures designed to cover wages were diverted to materials and equipment, which could be sold locally.

Apart from motives of corruption, the natural objectives of public officials can also create targeting errors. This appears to have been particularly important in the poor country employment creation and subsidized loan programs in China, where because of the financial constraints they faced, local officials had incentives to divert funds to projects capable of generating revenue rather than funding those projects with the greatest direct poverty impact. Similarly, with microcredit schemes in China and elsewhere, the officials of the implementing banks were under pressure to lend to the more credit-worthy customers, who would not be the poorest households.

Brazil has shown, however, how a carefully thought-through programme of targeted poverty-reduction, called Bolsa Familia (Family Fund) can succeed. Dubbed by the Economist magazine as the “anti-poverty scheme invented in Latin America which is winning converts worldwide“, the program attempts to reduce short-term poverty by direct cash transfers and fight long-term poverty through cash transfers made conditional on poor families sending their children to school. Here is how it works:

Where a family earns less than 120 reais ($6 per head per month, mothers are paid a benefit of up to 95 reais on condition that their children go to school and take part in government vaccination programmes. Municipal governments do much of the collection of data on eligibility and compliance, but payments are made by the federal government.

The Bolsa Familia, which reduced poverty by 28% between 2003-2006, has been copied in many parts of Latin America, in New York City, Cairo, Easter Europe, etc. Despite the possibilities of fraud and leakages, most of the money from the Scheme does seem to go to the right people: 70% ends up in the pockets of the poorest 20% of families, according to World Bank findings.

Mauritius, is a small economy, with a sophisticated administrative apparatus and a ratio informal sector to formal sector much smaller than countries like Brazil (and the informal sector in Mauritius is shrinking thanks to productivity growth, structural changes and recently improved tax compliance and collection schemes). The conditions are therefore present for means-testing to be successfully implemented in the allocation of the basic state pension (which in, its current form, gives a meagre $80 a month to all residents in Mauritius over the age of 60, regardless of income), and in the subsidization of basic commodities.

The issue, it seems, is not whether targeting or means-testing work or not. It is how to make them work by targeting the right people and give them the right incentives.