PMT and Targeting

for the Social Aid Reform in Mauritius

Christophe Muller

Consultant

United Nations Development Programme

October 2010

Acknowledgments

I am grateful to many executives and agents from the Ministry of Social Security, the Central

Statistics Office, the Ministry of Finance and Economic Development and the UNDP for their

support. Special thanks are due to the SRM Team, Mrs I. Jugganaikloo, Mrs. S. Vithilingum,

Mrs. N. Ramjane among others and the UNDP local consultants assisting them, Mr. D. Bundhoo

and Miss M. Rucktooa. Without all these collaborators engaged in this collective work, this

report could not have been produced.

Executive Summary

In this report we discuss the Reform of the Social Aid programme of Mauritius. On the one hand,

we synthetize some of the information produced at the SRM Unit. Statistical tables on current

and future beneficiaries are presented, including some budget tables. On the other hand, we

develop the reflexion on this reform through policy simulations and recommendations.

A few issues need to be dealt with for ensuring the success of the reform:

(1) More rigour is needed in dealing with statistics used to justify the reform.

(2) The ‘additional conditions’ should be considered as a device to protect some losers of the

reform, not as a central policy objective. The focus of the social policy on the poor should not be

lost of sight.

(3) Immediate and massive empowerment of the losers of the reform is impossible for lack of

current capacity at MSI, and probably for a few years. There is no immediate capacity in the

country for dealing with a controled ‘Grand Reform’ of the social system. However, a limited

reform centered on the PMT implementation is still possible.

(4) More information is needed about current or potential beneficiaries in Rodrigues or for

Immediate Payment cases to clarify their participation in the PMT.

The main policy recommendations are as follows:

Decide if the population of the poor is still a priority. Not implementing PMT in order to

overprotect these populations will amount to sacrifice the interest of the poor. Neglecting

them to serve other destitute categories instead would be a major policy change that can

only be decided at the top goverment level.

However, if the priority given to the poor is confirmed, the sooner the PMT can be

implemented, even with imperfections, the better. At the moment the very low coverage of

the poor by social aid (5% for the Regular cases in Mauritius Island) is hurting them.

Delaying PMT implementation implies a continuation of such damage to the poor in

contrast with post-PMT coverage of the poor of 30%.

Apply PMT as soon as possible to Mauritius Island and Regular social aid cases

Improve use of statistical information related to the reform.

Introduce the Additional Conditions designed by the SRM Unit to protect some

beneficiary categories that are bound to lose from the reform.

Collect information to better monitor current and potential beneficiaries for the

‘Immediate Payment’ cases and for Rodrigues.

Make transparent the process of budget allocation for transfers, by subcategories, so that

the PMT threshold can be adjusted.

Associate MSI to the protection of current beneficiaries during the transition period of

PMT implementation. There are many unspent funds of MSI because the empowerment

capacity is no longer in place. These funds could be used to compensate ‘losers’ of the

reform for a limited period.

Group Income Support and Social Aid under the same PMT program.

Monitor the Immediate Payment cases and design selection rules to deal with the most

dramatic situations of these IP cases only. Continue to serve these IP cases, instead of

substituting them with PMT, until more is known about them and it is clear that they can

be discarded.

On the whole, with the additional conditions and possible complement budget from MSI to

compensate losers of the reform, the benefits of moving from the current social aid system to

PMT for the poor very largely offset the inconvenients suffered by a few losers of the reform.

So, we recommend implementing the PMT as soon as possible.

Table of Contents

Executive Summary

1. Introduction 3

2. The Additional Conditions for Accessing Social Aid

3. Who are the Losers?

4. The Immediate Cases and Rodrigues

5. Budget Issues

6. Policy Simulations

7. Policy Conclusions and Recommendations

Appendix A1: References

1. Introduction

The Social Register of Mauritius has been designed as a large database of potential and actual

social programme beneficiaries. It will assist the Ministry of Social Security (from now ‘The

Ministry’ or MSS) in identifying the beneficiaries of each programme and deciding the level of

assistance for each beneficiary. It will also be used to assess social programmes and improve

their performance.

The project of the ‘Social Register for Mauritius’ (SRM) is under the responsibility of the

Ministry. In this project, the Ministry is supported by the Ministry of Finance and Economy and

by the Central Statistics Office (CSO). The United Nations Development Program is providing

technical assistance.

The objectives of the project are:

- Managing the social programmes in an integrated way;

- Enhancing the targeting performance of programmes;

- Designing a unified approach to welfare and targeting criteria;

- Analysing cyclical and structural poverty reduction policies.

The SRM database will be used for a variety of purposes, not only for payment of allowances to

beneficiaries, but also for economic analyses, anti-poverty monitoring, and establishment of

proxy-means transfers schemes that would improve the targeting efficiency of Social Aid and

other social programmes.

Thus, the Mauritian government is taking the lead in modernizing its social system around the

social databases of the country. This is made possible by first emulating statistical and

organisation methods used in industrial economies, such as in European countries with a well-

developed social system, but also by taking advantage of the sophisticated methods that have

been developed for fighting poverty in developing economies.

The SRM will also bear important consequences for assessing the budgetary burden of social

systems and social reforms. Least, but not last, it should allow substantial savings of public funds

by improving the efficiency of social transfers in the country.

In this report we explore ways of improve the reform of social aid programs, which is based on

Proxy-Means Tests that have been proposed for Mauritius Social Aid (Muller, 2010). We are

responding to a government request, under extremely tight deadline. This request emanates from

MSS with the view of protecting some categories of current beneficiaries that would not be

entitled to receive benefits when PMT is implemented.

The requested information had to be provided before September 12, in order to be timely

included in the budget process for the social aid reform. These additional studies are aimed at:

(a) improving the efficiency and accuracy of the PMT so as to take advantage of additional

information;

(b) incorporating further conditions for the inclusion/exclusion of beneficiaries of the PMT.

These conditions should emerge from the long-standing experience of the Ministry of

Social Security in managing its social programs;

(c) studying alternative scenarios of the PMT reform through statistical simulations so as to

provide a range of possibilities to political decision makers;

(d) studying strategies to deal with current Social Aid beneficiaries bound to lose their

benefits under the current system.

(e) exploring the potential for saving funds, thus relating the PMT reform to the elaboration

of the national budget.

These deliveries were conditional on the following items:

- (1) Some of these dimensions of the analysis will be treated immediately in order to reach

the deadline, with just a few immediate simulations, while further analyses, in particular

concerning the budget could be carried out later on.

- (2) The necessary information for these study is rapidly collected from the Ministry early

September. A list of short term information needs was established for this.

- (3) Disturbances are kept at the minimum so that the SRM staff can be fully involved in

urgent tasks with the full support of UNDP local consultants.

In practice, condition (2) was never fully met. Only a limited part of this necessary information

could be gathered in such a short periof by MSS agents and provided just a few days before the

report deadline instead of early September. Moreover, Condition (3) could not be implemented

by administrations, with other tasks massively diverting the time and resources of the SRM team

and UNDP local consultants.

However, considering the major pressure put on MSS agents in this time of reform, these

conditions were probably impossible to reach, despite remarkable efforts by the MSS team and

their local consultants. Although, we could have dismissed the assignment at this stage, we found

it more useful to pursue with the work, with a few immediate simulations on the line of (1),

rather than to stop and wait for favourable study conditions to be established.

Moreover, the current political and administrative context about the reform seems to be volatile.

Obviously, the structural dimensions of the reforms are not yet stabilized. We tried to orient our

work in order to provide some directions of reflection in order to remind fundamental issues and

improve effort coordination.

This document reports the results of our analyses under urgency. Finally, note that all the

statistical results in this document are to be seen as very preliminary, as there was not time to

check them fully under such short notice.

In Section 2, we examine the additional conditions to impose on the selection of beneficiaries for

social aid. In Section 3, we describe the potential losers among social aid beneficiaries following

the PMT implementation. In Section 4, we discuss the Immediate beneficiaries. In Section 5, we

discuss budget issues. In Section 5, we report on policy simulations. Finally, in Section 6, we

propose policy conclusions and recommendations.

Abbreviations:

CSO: Central Statistics Office.

The Ministry or MSS: The Ministry of Social Security.

UNDP: United Nations Development Programme.

SRM: Social Register of Mauritius.

MOFEE: Ministry of Finance and Economic Empowerment.

LCS: Living Conditions Survey.

CS: Complementary Survey.

DCP: Decentralized Cooperation Program.

MSI: The Ministry of Social Integration.

2. The Additional Conditions for Beneficiary Selection

2.1. The issue at hand

MSS already avails of new PMT rules to select beneficiaries and compute amounts of benefits to

each beneficiary. They are ready to be used and presented in Muller (2010).

However, the PMT formulae do not need to be the only information used in deciding of access to

social aid and the amount of benefits transferred. As a matter of fact, it was found desirable to

mobilise the huge experience accumulated in MSS on how to manage social systems in order to

enhance the performance of PMT. In particular, it would be a mistake not to use safe and verified

information that all social officers know to be useful.

In that situation, additional conditions could be incorporated in order to include or exclude

beneficiaries according to some of their observable characteristics, even if these characteristics

are not currently available in the SRM data. In particular:

- More attention could be devoted to the characteristics of the dwelling so that households

living in dire lodging conditions be included, even if their PMT score is too high to have

them directly included. For example, households living in dwellings with roof and walls

made of corrugated tin and wood should be examined in order to assess their conditions.

Inversely, households living in obviously wealthy estates should not be included,

whatever the result of the PMT formula.

- Outdoor localisation of toilets, or even having no toilets at all, seems to be an obvious

sign that the corresponding households should have to be covered by social aid.

- Absence of any bathing facilities also seems to be a good reason for including households

in social aid, whatever their PMT score.

- A similar criterion concerns households getting their water from river, well or some

public fountain or neighbour. They probably should be included in social aid anyway.

In any case, all the above conditions are mere suggestions that should be assessed by social

officers themselves.

In this section, we shall report proposals of additional conditions emerging from MSS experience

and reflexions.

This is not to imply that the same categories of beneficiaries than the ones currently in use

should be kept. Indeed, the current categories lead to dramatically low coverage of the poor.

However, exceptionally and obviously destitute households in these categories could be

considered for additional investigation of their situation.

We first present the current subprograms in social aid in the following table as described for the

SRM project.

Social Aid and other direct transfers of the MSS National Solidarity Programme1

Programme Objective/Rationale of programme

Type

Mea

ns te

sted

? Current eligibility criteria

Imm

edia

te

Regu

lar

Official

Social Aid in cash Medical

Financial assistance to a person who is temporarily or permanently incapable of supporting himself/herself and his dependents due to:

physical/mental impairment Y Y Y Medical Certificate from Min of Health

Abandoned women abandonment by partner Y Y Y Summon by MSS (but rarely used)

Unmarried mother2 an unmarried mother (not living with a partner, and usually below the age of 18)

Y Y Y Medical Certificate to certify pregnancy

Imprisonment imprisonment of head of household

Y Y Y Certificate from Court; Discharge Certificate from Prisons

Partner dead/missing/disappeared death or disappearance of partner

Y Y Y Death Certificate; Certificate from Police

Sudden loss of employment3 sudden loss of employment for > 6 months

Y Y Y Letter from employer; Registration at Employment Office

Abandoned Child Financial assistance to the guardian of an abandoned child under the age of 15, or 20 if at school or disabled

Y Y N None

BRP-Rental allowance Financial assistance to a recipient of Basic Pension (BRP, BWP, BOP or BIP) living alone and paying rent

Y Y Y Receiving a Basic Pension; Rent book from landlord ; living alone

Carer's allowance Financial assistance to a head of household who has a child under the age of 18 suffering from HIV or severely handicapped, and has multiple congenital deformities

Y Y Y Medical Certificate and statement of emoluments of yearly earnings <= Rs250,000

Ex-Gratia Financial assistance to a head of household who has a child under the age of 18 suffering from a severe disablement

Y Y Y Medical Certificate and statement of emoluments of yearly earnings < =Rs 150,000

Multiple birth Financial assistance to meet expenses in case of multiple births during one confinement

Y Y Y Statement of emoluments of yearly earnings <= Rs150,000

Additional Social Aid Financial assistance to a BRP recipient who has insufficient means to support himself and his dependents (e.g. dependents are attending school/university)

Y Y Y Receiving BRP

Social Aid in kind Spectacles To provide spectacles to any person (or dependent) who is entitled to Social

Aid or a recipient of basic pension who would have qualified for Social AidNA NA Y Medical prescription from

Mins of Health

Dentures To provide financial assistance for the costs of dentures for a BRP recipient who has insufficient means to support his livelihood

Y NA Y Medical prescription from Min of Health

Hearing aid To provide hearing aids to a person who is entitled for Social Aid or to needy persons

NA NA Y Medical prescription from Min of Health

Wheelchair4 To provide wheelchairs to any person who is in need of a wheelchair NA NA N Medical prescription from medical practitioner

Other direct transfers under MSS National Solidarity programme Income support Financial assistance to needy households to purchase rice and flour NA Y Y Recipients of (i) Social

Aid, (ii) UHR, and (iii) basic pension who would qualify for Social Aid; (iv) monthly electricity consumption < 75Kwh

Unemployment Hardship Relief3 Financial assistance to an unemployed head of household whose resources are insufficient to support himself and his dependents

Y Y Y Registration card from Employment Office

Allowance to centenarians One-off gift to any person who has reached the age of 100 NA NA N Birth certificate

Assistance to professional fishermen To compensate fishers who are unable to carry out fishing activities due to bad weather and close season

NA NA N Registered fisher; card stamped every month

Funeral grants One-off financial assistance due to the death of a beneficiary of Social Aid or any of his dependents or a recipient of basic pension who would have qualified for Social Aid

Y NA Y Death certificate; Means test on deceased

Repatriation expenses Financial assistance to Mauritians abroad who have insufficient means to return to Mauritius (beneficiaries have to refund later)

NA NA Y Means test by relevant Mauritian Embassy

Relief to Mauritians abroad Financial assistance to Mauritians abroad who have insufficient means to support themselves

NA NA Y Means test by relevant Mauritian Embassy

Subsidy on SC and HSC exams fees To refund exams fees for SC and HCS students coming from needy households

y NA Y Recipients of (i) Social Aid, (ii) UHR, and (iii) basic pension who would qualify for Social Aid; (iv) monthly income < Rs 8500 if only 1 child is sitting for exams; (v) monthly income < Rs 11,000 if 2 children are sitting for exams

1: Source of info: (i) Legal documents; (ii) Official publications; (iii) brainstorming sessions with some 225 MSS officers; (iv) meetings/working sessions with higher MSS officers2: Very sensitive; need to be treated outside PMT framework

3: Is being replaced by Transitional Unemployment Benefit (TUB)

4: No means test for those in need of a wheelchair

*: Acronym for Empowerment ProgrammesPF: Placement et Formation - eligible for young who are 16 and above; the unemployed; persons without any training/skill; persons who have lost their jobMC: Migration circulaire - provides opportunities to work abroad for a specificied time period, and for selected activities - eligible for those above 21 years and who have been already working

EM: Espace des Metiers - provides services on (i) how to choose an activity, (ii) which training to attend, (iii) how to look for a job, (iv) how to create and run one's own small businessSEP: Special Entrepreneurship Programme - Provides assistance to :(i) creation and development of micro-enterprises in manufacturing, agricultural, agri-business and handicraft, (ii) Socio-

economique empowerment of disbaled personsSFSE: Soutien aux Femmes Sans Emploi: Provides assistance for the setting up of a micro-business; mentoring and follow-up

CSR: Corporate Social Responsibility:CSR Code 201: Unemployment / Retrenchment

CSR Code 203: Support to and integration of people with disabilities CSR Code 206: Gender issues and Women Empowerment; Prevention of violence against women

CSR Code 207: Youth and ChildrenCSR Code 208: Elderly care

CSR Code 302: Non-Communicable diseasesCSR Code 303: Maternal and neo-natal care

CSR Code 602: Promote learning/education (starting from pre-primary up to tertiary/vocational)

2.2. The current eligibility criteria

A good starting point is to know exactly what is done in practice, beyond what has been

published in the law. We asked the SRM team to establish an accurate description of the current

eligibility conditions and how they are practically implemented. The results, although still rough

and incomplete, show the considerable progress in analytical capacity reached by the SRM Unit.

What we are interested here, are the additional conditions formally or informally applied by MSS

agents, notably during the enquiries they routinely carry out in order to check the situation of

applications. Indeed, some of these informal conditions could be made compulsory in order to

improve the selection or rescue of beneficiaries, even under a PMT system. We obtain the

following picture by type of application reason.

(a) Medical:

When a claim for social aid under any application reason, except funeral grant and wheelchair, is

registered at regional office, a visit has to be carried out by MSS agent at the claimant’s

premises. First, they ascertain that the applicant is residing at the given address and they carry

out an enquiry.

If the applicant is living in very poor living condition, described as ‘shabby dwelling

construction material such as corrugated iron sheet/concrete’, this will not affect his means test.

However, if MSS agents find out that the applicant is living in good condition, such as ‘Storyed

house, luxury amenities-refrigerator, televisión with LCD screen, parabol/Canal+, Antenna’, they

will investigate further to check if there are any hidden resources by looking and asking

questions about the beneficiary’s means to afford all these goods. MSS agent can have checks

made at the Registration Office (to verify ownership of land)/Sugar Insurance Fund Board (to

verify whether deriving income from sugar cane cultivation). Note that most variables describing

the above conditions are not available in the CS or HBS dasta, which prevent accurate statistical

analyses of their impact.

MSS agents try to find out if the applicant derives any income from any informal activity. For

example, they check if he has a small business at home like selling ‘dhool puri or roti at home, or

selling home vegetables, or whether the wife is doing some seamstressing work at home. They

also check if the applicant has any child under 20, working and deriving any income. As in the

means test for social aid we take into consideration income derived by child under 20.

During the site visit, the MSS agents also try to find out whether the applicant is owner of any

vehicle. For example, he can be owner of a van or a taxi, a car. He may be working as hawker or

taxi driver. MSS agent can have checks made at the National Transport Authority to verify if he

is owner of a vehicule or holder of a taxi/van/lorry permit to carry out business.

These practices shows the general picture of MSS agents investigating and checking about

applicants whereabouts and situations. We shall not systematically repeat the details of these

activities for all application reasons, although it is easy to understand that the checks done for the

‘Medical’ application reason are also often done for other application reasons.

(b) Abandoned women

The enquiries and investigations on employment, informal activity, living conditions, vehicle

ownership and other details are the same as above. Moreover, delaying tactics are employed to

discourage insincere applicants.

When an application for social aid is registered at MSS office under reason code ‘Abandoned

Woman’ the applicant must produce name and address of her ex –partner, so that the latter can

be summoned at office by MSS agent. Then, face to face interview between the claimant and the

exp-partener is organised in order to confirm abandonment and try to bring reconciliation.

However, most of the time reconciliation fails and the claimant is financially assisted.

Very often these applicants produce false names and addresses or state that they do not know ex-

partner’s address/whereabouts. In that situation, the case is assessed and generally financially

assisted.

When the ex partner is in employment and has acknowledged children, claimant is advised to sue

ex-partner for alimony. However, when legal case is lodged, its outcome is never known by

MSS. The applicant may even be receiving alimony (alimony is considered as an income in the

means test). Sometimes a call from MSS hierarchy is received to expedite matters, before case is

even referred to court (that is, to effect payment). In this situation an improvement would be

obtained by MSS agents sending a list of beneficiaries with their ID numbers to court so that

court informed MSS about the final judgement.

During site visits, MSS agents try to ascertain that applicant is really abandoned and is not living

with another partner. They call at claimant’s premises and ask for the partner instead of claimant.

However, this is only a procedure since MSS agents are not able to prove anything.

( c) Unmarried mother

When a claim for social aid under application reason “unmarried mother” is registered at

regional office, a visit is carried out by MSS agents at the claimant’s premises. They first

ascertain that the applicant is residing at the given address and perform an investigation. As the

claimant is usually under 18 years old, MSS agents try to know with whom she is living. They

check if she is not living with parents, in a home or with relatives.

(d) Imprisonment

First, the same type of investigations as above is implemented. Then, during site visit, MSS

agewnts try to ascertain that the applicant is not living with another partner, as above by asking

for the partner.

( e) Sudden loss of employment

The same investigations as above are carried out.

(f) Abandonned child

When a claim for social aid under application reason ‘abandoned child’ is registered at regional

office, a visit has is carried out by MSS agents at the claimant’s premises. They first ascertain

that the applicant is residing at the given address and then carry out an investigation. They check

about the whereabouts of parents, whether parents are in prison, or if the child is abandoned by

irresponsible parents. They try to find wether the parents are not living under the same roof as

the abandoned child. MSS Agent visit the applicant’s premises to see the living condition of the

child. For example, they search whether there is a bed for that child, a desk where the child can

do his homeworks. They check child’s personal belongings. That way, MSS agents can be sure

that the abandoned child is actually living with the guardian and not with his parents.

(g) Rent Allowance. (Fore beneficiaries of Basic Retirement pension, basic widow’s pension, basic

invalidity’s pension and basic orphan pension)

Same investigations as above are undertaken. Moreover, MSS Agent visits the applicant’s

premises to see whether the applicant is really living alone. They check the number of beds and

whether there is hints at the presence of another person.

(h) Carer’s allowance

The same type of investigaton as above are implemented. However, what is specific to this

applicatin type is the financial assistance to parents who have a child under the age of 18

suffering from HIV or severely handicapped, or has multiple congenital deformities. The carer’s

allowance is paid to the parents to meet additional expenses incurred on behalf of sick child, In

that case, the agents check medical certificates and statements of emoluments of yearly earnings

below RS. 250,000.

(i) Ex-Gratia

The same investigations as above are undertaken. This application type is specific to parents who

have a child under the age of 18 suffereing from severe disability. Then, MSS agents check

medical certificates and statements of emoluments of yearly earnings below RS. 150,000.

(j) Multiple Birth

This scheme corresponds to financial assistance to parents in order to help them meet expenses

during a period of confinement after multiple birth. The same investigations as above are

undertaken. MSS agents check birth certificates of babies and statements of emoluments of

yearly earnings under RS. 150,000.

(k) Additional social aid

This scheme corresponds to financial assistance to a BRP recipient who has insufficient means to

support himself and his dependents. For example, several dependents may be attending school or

university. The same investigations as above are undertaken. However, there are only 18 cases in

this application that should be eliminated.

(l) Social Aid in kind

(m) Income support

(n) Unemployment hardship relief

In all three cases, similar types of investigation as above are undertaken.

(o) Allowance to centenarians

A complete report on the centenarian is done by MSS Agent and it is not means tested. This

report covers family background, number of children, likes and dislikes, eating habits, past

activity. This is only for information, not for selection.

(p) Assistance to professional fishermen

(q) Relief to Mauritian Abroad

(r) Repatriation expenses

In the last three cases, the assessment of applicants for these schemes are not made by MSS.

(s) Funeral grants

There is no visit by MSS Agents. However, MSS agents implement a means test on the

deceased person. They try to find out what was the past activity of deceased – as per statement

given by applicant. No inquirement on applicant means.

(t) Subsidies on HSC and SC Exam fees

These schemes are in the form of refunds for exam fees. The same investigations as above are

undertaken. Moreover, written evidences that the students are sitting for exams are requested and

various means tests are implemented.

2.3. New additional conditions

We now move to additional conditions that were suggested by MSS agents in order to

include/exclude applicants, irrelevantly from the result of the PMT criterion.

The additional conditions are of two type:

- The additional conditions leading to exclude applicants that would be included according to the

pure PMT criterion. They are useful to limit fraud and leakage of benefit funds.

- The additional conditions leading to inclusion of applicants who would be excluded according to

the pure PMT criterion. They are useful to protect very destitute households that have not been

picked up by the PMT formula.

These additional conditions were obtained in several stages. First, the set of current informal

checking practices was clarified and put on paper, as shown in the previous sub-section. Second,

a large ‘brainstorming session’ was organised with many MSS agents from all over the country.

Then, the SRM Unit synthetised and developped these conditions, organising them by

Application Reason. Finally, we undertook many iterations to clarify further these conditions and

extract the usable information from all this research. At various stages there were some feedback

from MSS hierarchy and MSS experts as to the relevance of the proposed condtions. Clearly,

more could be done in this direction of improvement. However, this is already a success that

something was produced at all under such urgency.

Obviously, the work on additional conditions depended on the policy needs perceived by MSs.

The direction of reform followed by MSS seems to be that seriously disadvantaged current

beneficiaries who could not be protected should be redirected to empowerment programs. That

way, there is limited motivation for additional inclusion conditions for middle age or active

persons who are able to work or to study at school. Then, most additional conditions we could

collect and organise in such a short notice have to deal with persons who are young (children,

young mothers..) or rather close to retirement age.

The conditions are described below by application reason, along with some basic example

explaning them. The codes for the activity variable (activ) and the ‘application reason’ variable

(reason) are indicated as they appear in CS files.

1. Medical:Either condition1 or condition2:

a) Condition1: A single, non-headed unemployed male/female, aged between 45 and 59 years old, who is sick and is a beneficiary.

Condition Variables used in CS (Let’s take an individual named Mary.)

Single mari == 8 We are targeting bachelors and spinsters.

Non-headed rel != 1 Mary should not be head. Usually Mary is living with a relative that is well – off.

Unemployed activ == 6|activ == 9|activ==10|active==11 Mary is unable to work due to sickness.

activ == 6 means homemakeractiv == 9 means Not working but looking for workactiv==10 means disabled/invalidactiv==11 means other

Aged 45-59 age >44 & age <60

Any individual below the age of 45 should be empowered to work.After 45, the probability of acquiring a job is difficult.

Sick reason == 5 Mary is certified sick by the MSS medical board.

Beneficiary ismem ==1 Mary is the sole beneficiary.

b) Condition2: An unemployed male/female head, aged between 55 and 59 years old, who is sick and is a beneficiary.

Condition Variables used in CS Let’s take an individual named John.

Head rel == 1 John has a family and he is the bread winner.

Unemployed activ == 6|activ == 8|activ==10|active==11Unemployed John cannot work since he is sick.

activ == 6 means homemakeractiv == 8 means retired activ==10 means disabled/invalidactiv==11 means other

Aged 55-59 age >54 & age <60He cannot be empowered and/or work above the age of 55.

Sick reason == 5 Sick

John is certified sick by the MSS medical board.

Beneficiary ismem ==1 Beneficiary

John and dependants are beneficiaries.

2. Unemployment Hardship ReliefCondition: No additional condition

3. Abandoned women Condition: No additional condition

4. Unmarried motherCondition:

a) Condition: An unmarried mother aged between 11 and 18 years old, who is a beneficiary.

Condition Variables used in CS Why Let’s take an individual named Anna. Unmarried mother reason == 13 We are targeting “fille – mere”Aged 11-18 age>10 & age <19

Any individual between the age 11-18 is considered a child.After 19 they should be empowered to work.

Beneficiary ismem ==1 Anna and child are the beneficiaries.

5. ImprisonmentCondition: No additional condition

6. Additional Social AidCondition: No additional condition

7. Abandoned ChildCondition: No additional condition

8. BRP – Rental AllowanceCondition: No additional condition

9. Carer’s AllowanceCondition: Pmt should not be applied to this reason code. Take all cases.

Indeed, MSS is trying to help non- poor families benefit under this programme.There’s an income ceiling of Rs 250000/yearly.

10. Ex- GratiaCondition: Pmt should not be applied to this reason code. Take all cases.

MSS is trying to help non- poor families benefit under this programme.There’s an income ceiling of Rs 150000/yearly.

11. Multiple BirthCondition: No additional condition

12. Sudden Loss of EmploymentCondition: No additional condition

13. Partner dead/missing/disappearCondition: No additional condition

A few remarks are worth adding to these conditions.

(a) Ex gratia or Carer’s allowance:

Any regular beneficiary of social aid having a child under 18 medically certified

sick/handicapped would most probably qualify to receive Ex gratia or carer’s allowance

as the case may be. In its endeavour to help more families, Government has introduced

new eligibility criteria.

The ceiling of yearly earnings ≤ Rs250,000 (Carer’s allowance) & ≤ Rs150,000 (Ex-

gratia), to help non-poor families benefit from these assistances.

However, there is no yearly revision of these ceilings, which means that authorities

want to limit the number of non-poor families. This is a point that has to be taken into

consideration when the new rules are to be proposed.

(b) Medical

It seems important to distinguish between mild and severe cases when deciding to

exclude applicants under the reason medical. This could be done by MSS medical

board.

These cases would have to be given financial assistance temporarily for the period of

incapacity that is stated on the medical certificate. In practice, they often end up as

permanent beneficiaries. Then, MSS medical board should be able to eliminate some

cases by checking the duration of the illness.

The two additional conditions for ‘Medical’ that have been proposed correstpond to

unemployed adults who could not be empowered considering their age. These persons

may be suffering from chronic illness. Then, it is reasonable to keep them under social

aid, even if they do not pass PMT.

Note that beneficiaries who would be benefiting from severe illness would qualify for

basic invalidity pension instead of social aid. Therefore, there is no danger of excluding

them while applying PMT to social aid.

( c) Unmarried mothers

In principle, all beneficiaries under this application reason should be aged less than 18

years. In practice, there are beneficiaries aged from 11 to 54 years under this reason.

1

3. Who are the losers?

3.1. Frequency table for eligible and ineligible cases

The following tables inform on numbers and percentages of eligible and ineligible

beneficiaries (respectively households and individuals) under the modified PMT rule

incorporating the new additional rules.

Obviously, there are four important application reasons: Medical, Abandoned Women,

Abandoned Child and Carer’s allowance. The seeach for additional conditions

concentrated on these cases, although it was realised that Abandoned Women could

easily follow various empowerment programs. On the other hand, the application

reasons Ex-Gratia and Carer’s Allowance seems serious enough to justify systematic

preservation of these beneficiaries.

The chosen additional conditions are influential for the selected application reasons, as

show the comparaison of Tables 1 and 2. However, on the whole the impact on the total

number of beneficiaries is rather minor.

2

Table 1 - Distribution of beneficiaries, households and individuals by application reason and sub-categories under PMT, CS 2008

Social Aid

Complementary Survey 2008Beneficiaries Households

Not eligible1 Eligible1 Total Not

eligible1 Eligible1 Total eligibleNo. % No. % No. No. % No. % No. No.

Application Reason

Medical2

48455,2

2 013 44,8 4 497

2 481

55,2

2 013 44,8 4 494 6 567

PMT only 894 19,9 894 19,9

Unemployed single non-head aged 45 -59 yrs 170 3,8 170 3,8

Unemployed head aged 55 -59 yrs 949 21,1 949 21,1

Unemploy.Hardship Relief 6482,1 14 17,9 78 64

82,1 14 17,9 78 232

Abandoned women1

72045,9

2 026 54,1 3 746

1 720

45,9

2 026 54,1 3 746 5 372

Unmarried mother 8035,6 145 64,4 225 79

35,3 145 64,7 224 293

PMT only 122 54,2 122 54,5 Teenagers aged 11- 18 yrs 23 10,2 23 10,3

Imprisonment 18460,3 121 39,7 305 176

60,5 115 39,5 291 650

Additional Social Aid 1477,8 4 22,2 18 14

77,8 4 22,2 18 42

Abandoned Child 61955,0 506 45,0 1 125 506

61,6 316 38,4 822 1 700

BRP-Rental allowance 16543,4 215 56,6 380 165

43,4 215 56,6 380 165

Carer's allowance2 0 0,02

410100,

0 2 410 0 0,02

350100,

0 2 350 0

Ex-Gratia2 0 0,0 155100,

0 155 0 0,0 154100,

0 154 0

Multiple birth 12755,7 101 44,3 228 69

57,5 51 42,5 120 324

Sudden loss of employment 583,3 1 16,7 6 5

83,3 1 16,7 6 22

Partner dead/missing/disap 7753,5 67 46,5 144 77

53,5 67 46,5 144 223

Total Social Aid5

53941,6

7 778 58,4 13 317

5 356

41,8

7 471 58,2 12 827

15 590

3

Note 1 & 2: Eligibility assessment based on CS data using PMT + subprograms on Medical & Unmarried mother, except for Carer's Allowance and Ex-Gratia where all beneficiaries have been included.

4

Table 2 - Distribution of beneficiaries, households and individuals by application reason under PMT, CS 2008

Social Aid

Complementary Survey 2008Beneficiaries Households

Not eligible1 Eligible1 Total Not

eligible1 Eligible1 Total Not eligible

No. % No. % No. No. % No. % No. No.

Application Reason

Medical 3603 80,1 894 19,9 4 497 3600 80,1 894 19,9 4494 8 935

Unemploy.Hardship Relief 64 82,1 14 18,0 78 64 82,1 14 18,0 78 232

Abandoned women 1 720 45,9 2 026 54,1 3 746 1 720 45,9 2 026 54,1 3746 5 372

Unmarried mother 103 45,8 122 54,2 225 102 45,5 122 54,5 224 388

Imprisonment 184 60,3 121 39,7 305 176 60,5 115 39,5 291 650

Additional Social Aid 14 77,8 4 22,2 18 14 77,8 4 22,2 18 42

Abandoned Child 619 55,0 506 45,0 1 125 506 61,6 316 38,4 822 1 700

BRP-Rental allowance 165 43,4 215 56,6 380 165 43,4 215 56,6 380 165

Carer's allowance 1 632 67,7 778 32,3 2 410 1 597 68,0 753 32,0 2350 6 339

Ex-Gratia 101 65,2 54 34,8 155 100 64,9 54 35,1 154 386

Multiple birth 127 55,7 101 44,3 228 69 57,5 51 42,5 120 324

Sudden loss of employment 5 83,3 1 16,7 6 5 83,3 1 16,7 6 22

Partner dead/missing/disap 77 53,5 67 46,5 144 77 53,5 67 46,5 144 223

Total Social Aid 8414 63,2 4 903 36,8 13 317 8195 63,9 4632 36,1 12827 24 778

Note 1 : Eligibility and Non-eligibility under PMT only

5

Table 3 - Distribution of beneficiaries, households and individuals with disability and by application reason , CS 2008

Social AidComplementary Survey 2008

Beneficiaries Households Not Eligible Eligible Total Not Eligible Eligible Total

No. % No. % No. No. % No.Application Reason Medical 2420 55,08 1974 44,92 4394 2204 55,77 1 748 44,2 3952 2959

Unemploy.Hardship Relief 12 85,71 2 14,29 14 9 90 1 10,0 10 Abandoned women 312 55,71 248 44,29 560 387 54,13 328 45,9 715 Unmarried mother 5 35,71 9 64,29 14 13 36,11 23 63,9 36 Imprisonment 17 73,91 6 26,09 23 13 56,52 10 43,5 23 Additional Social Aid 6 66,67 3 33,33 9 7 70 3 30,0 10 Abandoned Child 12 48 13 52 25 128 61,84 79 38,2 207

BRP-Rental allowance 91 43,75 117 56,25 208 91 43,75 117 56,3 208 Carer's allowance 0 0 2350 100 2350 0 0 263 100,0 263 Ex-Gratia 0 0 151 100 151 0 0 16 100,0 16 Multiple birth 1 100 0 0 1 3 50 3 50,0 6

Sudden loss of employment 1 100 0 0 1 1 100 0 0,0 1

Partner dead/missing/disap 12 46,15 14 53,85 26 14 51,85 13 48,2 27Total Social Aid 2889 37,15 4887 62,85 7776 2870 52,43 2 604 47,6 5474 4126

6

3.2. Other considerations

Note that additional conditions designed in order to rescue severe cases that could be

empowered cover only a minority of the concerned individuals. They are still useful as

show the following figures.

Under the reason ‘Medical’, with PMT 894 current beneficiaries remain eligible.

Adding the new conditions would allow the Ministry to rescue 1119 other beneficiaries.

This is not negligible, although it remains a small correction as compared to the total

number of beneficiaries under social aid.

Under the reason ‘Unmarried mothers’, only 122 current beneficiaries are eligible under

PMT. 23 other beneficiaries can be rescued with the additional conditions.

Under the reason ‘Carer’s Allowance’, 778 are eligible under PMT. 1632 other

beneficiaries can be rescued by applying the additional conditions.

Finally, under the reason ‘Ex Gratia’, 54 beneficiaries remain eligible under PMT, while

101 other ones can be rescued by applying the proposed additional conditions.

Another important element to realize is that many Medical cases can be kept by

invoking the level of disability of the beneficiary. In that case, the beneficiaries could be

redirected towards social programs better specialised in the treatment of disabilities than

7

social aid. The following table shows the number of cases with one or several

disabilities in the current files of SRM at MSS. Obviously there are many of them,

while it is unclear how severe these disabilities are. As mentioned before, individual

with severe disabilities should not be under social aid but another scheme.

Distribution of beneficiaries, households and individuals by disability

Number of disabilities

Complementary Survey 2008

Beneficiaries Households Individuals

No. % No. % No. %

1 7776 58,4 5474 42,7 11031 26,3

2 2796 21,0 1790 14,0 3782 9,0

3 1711 12,8 1106 8,6 2326 5,6

Out of 13,317 beneficiaries, 7776 beneficiaries (58.4 %) have one disability, 2796 (21.0 %) have two disabilities and 1711 (12.8 %) have three disabilities.

Out of 12,827 households, 5474 household heads (42.7 %) have one disability, 1790 (14.0 %) have two disabilities and 1106 (8.6 %) have three disabilities.

Out of 41,865 individuals, 11031 individuals (26.3 %) have one disability, 3782 (9.0 %) have two disabilities and 2326 (5.6 %) have three disabilities.

The following table, calculated using HBS data, shows that it is illusory to think that we

should be able to identify a large proportion of households with disabled people by just

monitoring the household medical expenses. Indeed, many of them do not spend

anything on health, or have just very small health expenses.

8

Number of disabled/invalid households & individuals by expenditure on health,

HBS 2006/07

Health expenditure (Rs) Households (No) Individuals (No)

No expenditure 61 194

Less than 500 28 115

501 - 1000 10 35

1001 - 1500 8 25

1501 - 2500 4 14

2501 - 4000 1 9

4001 - 6000 2 4

6001 - 8000 0 3

8001 - 10000 0 1

above 10000 0 1

Total 114 401

Looking at the individuals working in the Formal Sector or in the Informal Sector could

be useful in future selection rules, as shows the next table. Typically, the poor are

believed to belong more to the Informal Sector than to the Formal Sector. Then, our

combined PMT with additional conditions would raise the proportion of beneficiaries

coming from the Informal Sector.

Sector of Individuals - Complementary Survey 2008

9

employmentNot eligible Eligible Total

No. % No. % No. %

Formal 2 015 72,4 768 27,6 2 043 100,0

Informal 3 187 63,1 1 867 36,9 5 054 100,0

10

4. The Immediate Cases and Rodrigues

In this section, we deal with groups of beneficiaries for which we have only the slimmer

information. Immediate cases on the one hand, Rodrigues beneficiaries on the other

hand, may be especially important as it is possible that they include some of the most

dramatic situations. Indeed, Rodrigues is the district with higher poverty level, and

immediate payments are often motivated by social emergencies.

4.1. The ‘Immediate’ Cases

The ‘Immediate’ cases under the reason ‘medical’ occur in the following case. A

claimant is employed in the formal sector or the informal sector and is temporarily

incapable of supporting himself/herself and his/her dependents due to temporary

sickness or temporary disability certified by a medical certificate from Ministry of

Health. Then, he/she is assisted by an IP voucher (immediate payment). In Social Aid

Regulation no provision has been made concerning the period during which payment

can be made by IP. However, some of the claimants suffering from temporary sickness

end up as regular cases.

When a claimant is severely ill, he/she is advised to apply for Basic Invalidity Pension

(BIP). Pending determination of his/her claim for BIP, he/she may be paid by IP if

he/she gets through the means test.

11

The situation is still further complicated by the fact that a ‘Immediate Payment’ is not

done only to ‘Immediate Cases’. As a matter of fact, there exist ad hoc cases where

immediate payment is performed. None of these payment, nor any of the immediate

cases, can be studied from the CS data that covers only Regular cases. Finally, a given

person may benefit from more than one immediate payment. So, breaking down the IP

cases by ‘Application reason’ for beneficiaries is not easy.

Immediate payment cases correspond to the 12 application reasons of Social Aid in

about 4/5 of cases. These 80% can be broken down into: 50% for Medical, 30% for

Abandoned Women and 20% for other miscellaneous reasons. However, in 1/5 of the

cases, the immediate payments respond to ad hoc situations (fire victimes, money for

dentures, flood victims, released prisoners). Moreover, this rough division of cases can

vary across years, notably due to the occurrence of natural hazards such as floods.

So, the first thing to do is to try to assess how many immediate cases there are, and the

corresponding number of households, individuals and beneficiaries.

The budget spent on IP for the last financial years are:

(i) 2005/06: Rs 45, 746, 507

(ii) 2006/07: Rs 106, 395, 086

(iii) 2007/08: Rs 62, 998, 688

(iv) 2008/09: Rs 42,588,513

12

It seems that the reason why the budget for 2006/07 is exceptionally higher than the

other years is because it includes Exams Fees. However, such discrepancy does not give

confidence in the social accounts.

In principle, it is impossible to relate the number of beneficiaries to these budgets since

the MSS does not have data on the number of IP beneficiaries. Indeed, there may be

several payments for some IP beneficiaries.

Moreover, the amount payable depends on the reason and the number of days. For

example, for flood it is a one off payment, for medical the number of days payable is

different for different individuals according to the medical certificate, there can be more

than one IP for the same beneficiary within the same month, etc.

However, it is posible to attempt to breakdown the 2008/09 budget by application

reason based on the broad parameters obtained from SRM expert experience. The

remaining reasons 20% can be Split up by using the % breakdown in the CS data and

applying appropriate adjustment so as the total equals the 2008/09 budget. The 2008/09

budget since it is the closest to the CS period.

These very rough estimates have been obtained by starting from the budget breakdown

and converting them into number of beneficiaries. Based on MSS knowledge, the

number of beneficiaries is assumed to be equal to the number of IP, except for Medical.

For Medical, we relied on expert opinions from SRM Unit experts.

13

Then, the numbers of households are extrapolated using the same

beneficiaries/households ratio by Application Reason than for Regular cases in the CS.

Finally, the number of individuals by Application Reason is obtained by using the same

ration individuals/households as in the CS data.

Then, the number of cases paid can be extrapolated, tentatively, by dividing each budget

all by the mean benefit recorded in the CS. The results are shown in the next tables.

They indicate that a large number of persons, perhaps often in dire emergency

situations, benefit from the Immediate Payments. Therefore, there should be taken more

seriously as mere details around a core of Regular cases who are the object of most of

the analyses.

The emergency nature of the IP mechanisms may be a critical social response that it

would be bold to discard without further analyses confirming that such a decisión would

not generate important damage for destitute populations.

In these conditions the reform could focus mostly on the substitution of the current

Regular cases with a PMT system, and complement it with Immediate Payments in a

form adjusted to whatever new information can be obtained about these.

Note that with the new PMT system, there will be no risk of IP cases to become

permanent. This element should generate some saving of social funds as compared to

the current system in which many IP beneficiary settle permanent assistence for life.

14

Immediate Payment 2008/09 budget - Rough breakdown estimates by Application Reason

Application Reason 2008/09 budget breakdown (Rs)

No of cases

PAID1

Medical 17,035,405 9,898

Abandoned women 10,221,243 5,939

Unemployment Hardship Relief 55,620 32

Unmarried mother 248,200 144

Imprisonment 395,625 230

Additional Social Aid 12,927 8

Abandoned Child 1,102,900 641

BRP-Rental allowance 352,041 205

Carer's allowance 4,025,179 2,339

Ex-Gratia 155,537 90

Multiple birth 277,501 161

Sudden loss of employment 8,585 5

Partner dead/missing/disappeared 180,046 105

TOTAL 34,070,810 19,795

OTHERS (FIRE, FLOOD, DENTURES, PRISONERS) 8,517,703 4,949

GRAND TOTAL IMMEDIATE PAYMENT 2008/09 42,588,513 24,744

Footnote 1: Figures refer to the number of Immediate Payments (NOT to the number of beneficiaries). That is a particular beneficiary can obtain more than 1 Immediate Payment.

15

Immediate Payment 2008/09 budget - Rough breakdown estimates by Application Reason

Application Reason

2008/09 budget

breakdown (Rs)

No of cases PAID

No. of Beneficiaries

No. of Household

s

Medical 17,035,405 9,898 8,244 7,941

Abandoned women 10,221,243 5,939 5,939 5,720

Unemployment Hardship Relief 55,620 32 32 31

Unmarried mother 248,200 144 144 139

Imprisonment 395,625 230 230 221

Additional Social Aid 12,927 8 8 7

Abandoned Child 1,102,900 641 641 617

BRP-Rental allowance 352,041 205 205 197

Carer's allowance 4,025,179 2,339 2,339 2,253

Ex-Gratia 155,537 90 90 87

Multiple birth 277,501 161 161 155

Sudden loss of employment 8,585 5 5 5

Partner dead/missing/disappeared 180,046 105 105 101

TOTAL 34,070,810 19,795 18,142 17,474

16

4.2. Rodrigues

Let us now turn to the case of Rodrigues, for which there is no data in the CS dtabase.

Again, the same rough approximation as before can be generated to assess the number

of individual concerned.

Budget 2011 for Regular cases has been obtained from MOFEE. Budget for Immediate

cases was 1.7 Million Rupees for 2009/09, it has been approximated to 2 Million

Rupees for 2011.

The following table shows rough breakdown estimates by Application Reason. Again,

some estimates of the number of indivudal and households are bsed on the ratios found

in CS data for Mauritius.

These estimates indicate a clear dominance of Abandonned Woman cases, whereas

Medical cases seems to be almost inexistent. Obviously, these tentative statistical results

seem to be too suspect to want to base any policy on them without further investigation.

Therefore, what is needed is to collect the missing information in Rodrigues.

Alternatively, the same policy than in Mauritius could be purseued blindly, hoping that

what has worked well for Mauritius would also work reasonably well for Rodrigues.

17

Rodrigues Social Aid 2011 Budget - Rough breakdown estimates by Application Reason

Regular cases Immediate cases

Application Reason2011 budget breakdown

(Rs)1Benefic.2 Hholds3 Indiv3

Approx 2011

Budget breakdown

(Rs)

Benefic.4

Medical 713,465 26 25 82 33,184 13

Abandoned women 22,721,123 828 798 2,600 1,056,796 423

Unemployment Hardship Relief 6,860,243 250 241 785 319,081 128

Unmarried mother 686,024 25 24 79 31,908 13

Imprisonment 27,441 1 1 3 1,276 1

Additional Social Aid 0 0 0 0 0 0

Abandoned Child 7,628,590 278 268 873 354,818 142

BRP-Rental allowance 0 0 0 0 0 0

Carer's allowance 3,430,121 125 120 393 159,541 64

Ex-Gratia 631,142 23 22 72 29,355 12

Multiple birth 164,646 6 6 19 7,658 3

Sudden loss of employment 0 0 0 0 0 0

Partner dead/missing/disappeared 137,205 5 5 16 6,382 3

TOTAL 43,000,000 1,567 1,509 4,920 2,000,000 800

1: Same budget of Rs Mn 43 in 2010 is planned for 20112: Last data available - 20093: Rough breakdown using information from CS data4: Data for year 2008/09 used for breakdown

18

5. Budget Issues

A major piece of information for the specification of the transfer scheme is the available

budget. However, it is important to understand that the approach we proposed for the

PMT adjusted with additional conditions can be fitted to any budget. This is because the

optimal transfer formulae we proposed are defined in terms of a threshold that can be

recalculated for any new budget situation. However, we need a precise budget estimate.

In a previous report, we suggested that MSS regularly establishes a set of accounting

tables about how social aid budget is spent, say every few months.

At the occasion of this urgent response to policy demands, the SRM Unit was prompted

to produce budget tables to clarify further the implementation of the reform. Some

interesting tables were produced that are shown below.

However, there are still some interrogations about the available budget. In particular,

there is a large MSI budget in principle available for empowerment actions. But clearly,

MSI’s capacity to carry out these actions efficiently is not likely to be established before

a long time. In these conditions, it would be natural that MSI could participate to the

funding of the reform in the meantime.

On the other hand, when using CS data, which only covers regular cases for Mauritius,

we have estimated the sum of amounts paid for social aid at 197 millions of Rupees

corresponding the time of the CS collection. In our current simulations, we therefore

19

used again 193 millions of Rupees as the budget to fund PMT transfers instead of

regular social aid transfers in Mauritius (193 instead of 197 because of convenient

rounding in the software program). However, when correcting for the missed

households during the matching of LCS and CS data, we obtain 271 millions.

Finally, the total of amounts paid recorded in the CS file is equal to 291 millions of

Rupees. The latter two amounts are close enough to make the simulations credible.

At some stage, MSS plan was that those who are eligible under PMT adjusted with

additional conditions would be MSS clients, whereas those who are not eligible would

be empowered by MSI. However, the latter, hopefully, will continue to receive cash

transfers for about a year. In that case, MSS would like to have the breakdown estimates

for the 2010 budget for these same categories.

As before, budget breakdown by categories of eligibility status by application reason

can be extrapolated from the amounts paid in CS data.

20

The following table shows the budget for the social safety net.The Social Safety net is a

sub-programme in the budget which deals with Social Benefits. As mentioned before,

the social benefits by Application Reasons are broken down using the percentages

obtained from the CS data.

PBB Budget Estimates - Social Safety Net (Item 50201) Source: Programmme-Based Budget reports

Item 2008/09 EstimatesTOTAL - SOCIAL SAFETY NET (ITEM 50201 IN PBB) 809 695 000 Compensation of Employees 52 630 000 Personal Emoluments 42 620 000 Other Staff Costs 10 010 000 Goods and Services 32 540 000 Utilities (electricity, phone, water, etc.) 2 360 000 Rent 4 570 000 Office equipment and furniture 120 000 Office expenses (postage, cleaning, etc.) 1 355 000 Maintenance (building, equipment, etc.) 1 310 000 Security 250 000 Publications/Stationery 950 000 Fees (to Mauritius Post Ltd) 100 000 Studies and Surveys 20 000 000 Other Goods and Services (e.g. uniforms) 1 525 000 Social Benefits 670 925 000 Social Assistance in Cash 659 925 000 Social Aid 100,00 % 373 300 000 of which: Medical 33,39 % 124 631 794 Unemployment Hardship Relief 0,32 % 1 189 970 Abandoned women 27,56 % 102 880 599 Unmarried mother 1,42 % 5 310 197 Imprisonment 2,27 % 8 464 306 Additional Social Aid 0,07 % 276 574 Abandoned Child 6,32 % 23 596 327 BRP-Rental allowance 2,02 % 7 531 851 Carer's allowance 23,07 % 86 117 883

21

Ex-Gratia 0,89 % 3 327 689 Multiple birth 1,59 % 5 937 085 Sudden loss of employment 0,05 % 183 684

Partner dead/missing/disappeared 1,03 % 3 852 042

Assistance to fishermen 60 000 000 Income Support 130 000 000 Funeral grants 10 900 000 Subsidy on SC and HSC exams fees 85 700 000 Family Allowance 25 000 Social Assistance in Kind 11 000 000 Other Expense (transfers to Non-Profit institutions) 50 100 000 Acquisition of Non-Financial Assets 3 500 000 Non-Residential buildings 0 Transport Equipment 3 500 000

The next table shows the amount paid from CS Social Aid - per month. (CS data updated @ April 2010)Calcs to estimate % by reason. This is used to distribute S.Aid Budget from PBB reports over the Application Reasons (UHR has also been included within Social Aid)

Total %

Medical 8 141 487 33,39Unemployment Hardship Relief 77 734 0,32Abandoned women 6 720 605 27,56Unmarried mother 346 885 1,42Imprisonment 552 925 2,27Additional Social Aid 18 067 0,07Abandoned Child 1 541 414 6,32BRP-Rental allowance 492 013 2,02Carer's allowance 5 625 592 23,07Ex-Gratia 217 379 0,89Multiple birth 387 836 1,59Sudden loss of employment 11 999 0,05Partner dead/missing/disappeared 251 632 1,03Total 24 385 568 100,00

22

Social Benefits: Cash Transfers - 2010 Budget Estimates (Rs Mn)(Breakdown of Social Aid by Application Reasons using Complementary Survey data)

Social Benefits details

Beneficiaries - Complementary Survey 2008 2010 estimates (Rs Mn) for beneficiaries who are:Not eligible1 Eligible1 Total

No. % No. % No. % Not eligible4

Social Aid Medical 2 484 55,2 2 013 44,8 4 497 100,0 72,5 Unemployment Hardship Relief 64 82,1 14 17,9 78 100,0 1,0 Abandoned women 1 720 45,9 2 026 54,1 3 746 100,0 46,2 Unmarried mother 80 35,6 145 64,4 225 100,0 2,0 Imprisonment 184 60,3 121 39,7 305 100,0 5,1 Additional Social Aid 14 77,8 4 22,2 18 100,0 0,2 Abandoned Child 619 55,0 506 45,0 1 125 100,0 12,1 BRP-Rental allowance 165 43,4 215 56,6 380 100,0 3,5 Carer's allowance2 0 0,0 2 410 100,0 2 410 100,0 0,0 Ex-Gratia2 0 0,0 155 100,0 155 100,0 0,0 Multiple birth 127 55,7 101 44,3 228 100,0 3,4 Sudden loss of employment 5 83,3 1 16,7 6 100,0 0,1 Partner dead/missing/disappeared 77 53,5 67 46,5 144 100,0 2,1Total Social Aid 5 539 41,6 7 778 58,4 13 317 100,0 148,3

Other cash transfers 3 Assistance to fishermen Income Support Funeral Grants SC and HSC exams fees Total 2010 estimates (Social Benefits) 148,3

1 & 2: Eligibility assessment based on CS data using PMT + additional rules, except for Carer's Allowance and Ex-Gratia where all beneficiaries have been included.

3: Data on Other Cash Transfers is not available in the CS data.

4: The breakdown of the Social Aid budget into categories of [Eligibility x Application Reason] is based on the amount of benefits paid to beneficiaries, as recorded in the CS data

23

Reformed Social Aid: Cash Transfers - 2010 Budget Estimates (Rs Mn)Budget estimates for Social Aid allowance and Income Support for beneficiaries of Social Aid: Breakdown by Application Reasons

Application Reason

2010 estimates (Rs Mn) for Social Aid allowance

2010 estimates (Rs Mn) for Income Support for beneficiaries of Social

Aid

2010 estimates (Rs Mn) for Social Aid allowance + Income Support:

Not eligible1 Eligible1 Total Not

eligible3 Eligible3 Total eligible

Medical 72,5 57,7 130,2 7,6 6,2 13,7 Unemployment Hardship Relief 1,0 0,3 1,2 0,7 0,1 0,8 Abandoned women 46,2 61,3 107,5 8,3 9,8 18,1 Unmarried mother 2,0 3,6 5,5 0,3 0,6 0,9 Imprisonment 5,1 3,7 8,8 0,8 0,5 1,3 Additional Social Aid 0,2 0,1 0,3 0,1 0,0 0,1 Abandoned Child 12,1 12,5 24,7 1,2 1,0 2,1 BRP-Rental allowance 3,5 4,4 7,9 0,1 0,1 0,2 Carer's allowance2 0,0 90,0 90,0 0,0 0,0 0,0 Ex-Gratia2 0,0 3,5 3,5 0,0 0,0 0,0 Multiple birth 3,4 2,8 6,2 0,0 0,0 0,0 Sudden loss of employment 0,1 0,0 0,2 0,0 0,0 0,0 Partner dead/missing/disappeared 2,1 2,0 4,0 0,3 0,3 0,6Total Social Aid 148,3 241,7 390,0 19,4 18,6 38,0

1 & 2: Eligibility assessment based on CS data using PMT + additional rules, except for Carer's Allowance and Ex-Gratia where all beneficiaries have been included.

3: Breakdown of Income Support by Application Reason based on CS data and expenditure data for financial year 2008-09

Even if these tentative budget information do not inform on the budget available for the

reform, they may be useful to determine the amount necessary to sustain PMT non-

eligible current beneficiaries that would still be kept on social aid by MSS.

These tables have now to be refined tso as we can distinguish the Regular from the

Immediate cases.

24

6. Policy Simulations

6.1. The problem

We want to use additional information in order to improve the efficiency of PMT. Many

varaibles have been deemed to be useful for this aim. However, they are neither

available in the CS data, nor in the HBS data. So, we turned our attention to the LCS dta

to attempt to mobilise a few additional variables in order to enhance the prediction of

living standards.

These variables are: characteristics of the toilet, characteristics of the kitchen, presence

of an ill person in the household, urban/rural location, various equipment such a tv,

stereo, vcr, refrigerator, washing machine, fixe and mobile phones, etc.

6.2. The predictive equations

The predictive equations are used to predict household living standards from a small set

of easy-to-observe characteristics. The new equations are estimated using LCS data

(with 1125 households) instead of using HBS data (based on 6720 households).

In Muller (2005) and Muller and Bibi (2010), develop a new methodology to target

efficiently direct transfers against poverty. The principle is to estimate ‘focused’ transfer

schemes that highly improve anti-poverty targeting performances. With the new

25

estimation method, post-transfer poverty can be substantially reduced. For Mauritius,

we have benefited from the experience accumulated in Tunisia, and proposed PMT that

lead to reduced severity of poverty when using the social aid budget of Regular cases

for Mauritius..

In our approach, focusing on the poor means that the living standard predictions are

calculated by defining the quantile regression in terms of living standard levels

representative of the poor. Precisely, we use the quantile regression centered in the

quantile of living standard corresponding to the poverty line.

The estimated PMT score is:

Score = p_y = 7.15 + 0 .018 age of head - 0 .00020 age_sq - 0.16 gender of head

+ 0.153 rooms - 0.00431 room_sq - 0 .121 babies - 0.138 young children

- 0 .142 teenagers - 0.0957 young adults - 0 .0659 adults - 0.174 elderlies

- 0.1008281 district of Pamplemousses - 0.1090934 district of Riv. du Rempart

-0.2054286 district of Flacq - 0.111349 district of Grand Port - 0.0512721 district of

Savanne -0.0390504 district of Plaines Wilhems -0.1222938 district of Moka

-0.0741835 district of Black River - 0.5114234 Island of Rodrigues + 0 .284 detached

building + 0.272 semi-detached building + 0.205 subdivided building

where

age head=age of head

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age_sq= (age of head) 2

gender of head= sex of head which is unity if sex = male, 2 otherwise

rooms = Number of rooms within the household

room_sq = (Number of rooms within the household) 2

babies = number of babies aged 0 to 3 years old

young children = number of children aged 4 to 10 years old

teenagers = number of teenagers aged 11 to 16 years old

young adults = number of adults aged 17 to 21 years old

adults = number of adults aged 22 to 60 years old

elderlies= number of elderly above 60 years old

6.3. Optimal transfers from using predicted living standards

For minimizing a FGT poverty measure (Foster et al., 1984) sensitive to poverty severity

(α >1), the solution can be stated explicity. It is optimal to start allocating the anti-

poverty budget to the poorest of the poor, and then ‘sweeping up’ the income

distribution. In that case, the transfer formula can be written as:

ti = ymax – yi if yi < ymax

ti = 0 otherwise,

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where ymax is the highest cut-off income allowed by the budget. As the anti-poverty

budget rises, ymax increases up to the poverty line, z.

This formula shows explicitly that the transfer rule can be adjusted to any budget chosen

by the government.

In practice, rather than estimating expected poverty, the unobserved living standards can

be replaced by their predictions based on observed variables.

We follow a two-step procedure. First, the predictions of yi conditional on Xi (the

vector of income correlates for household i is parametrically estimated by using quantile

regressions centered at the poverty line. Then, if the budget allows it, each predicted

poor individual receives the difference between its predicted income and the poverty

line.

The calculated transfer is: ymax minus the predicted income, for each household

predicted poor; and zero for households predicted non-poor. So, the calculation of the

transfers in the simulations requires determining the cut-off income, ymax. This is done

by estimating the total amount of potential transfers, while raising or lowering ymax until

it corresponds to the available budget. With the social aid budget spend for regular

households in Mauritius island in the CS data and the short score we obtain ymax = 76 %

of the general poverty line.

Let us now adjust this reasoning for dealing with living standards instead of merely

incomes. As a matter of fact, on the observed sample the PMT score exactly coincide

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with the predicted living standard, denoted p_y. Then, the considered household is

selected for social aid support if and only if p_y < ymax.

Then, the predicted optimal transfer is equal to

(y max - p_y) * (general equivalence scale).

The correction by the equivalence scale is what allows us to account for differences in

household composition among beneficiaries.

We do not restrict our attention to optimal transfers. Indeed, the optimality of such

transfer formula would be completely ensured only if living standard predictions were

perfect. This situation cannot be reached with limited data. Then, we also consider

uniform transfers where individuals identified as poor from their predicted living

standard all receive the same transfer amount.

In that case, the households are still selected for social aid by using the same rule:

p_y < ymax

and they receive each:

(total transfer budget) /

(number of households such that p_y < ymax)

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The studied scenario corresponds to:

(1) Taking away social aid from observed regular beneficiaries in Mauritius, as

detected by matching them with LCS;

(2) Giving PMT transfers to all households selected by using the above PMT

formula in Mauritius Island.

Note that we do not consider any change in transfers for Rodrigues as the corresponding

households do not appear in the data.

At that stage, several modifications were done as compared to past simulations:

(a) Using the LCS dta instead of the BS data

(b) Adding a few other variables in the score estimation

(c) Adding the additional consitions to the eligibility criteria.

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Let us remind some of the results obtained with the PMT, even before investigating the

new variables.

The coverage of the poor households can be reached with the PMT system (25.5 % of

poor households for general poverty, 28.1 % of poor households for nutritional poverty)

than with the current social aid program for regular cases in Mauritius (5.1 % for

general poverty, 3.2 % for nutritional poverty).

When considering targeting indicators at the individual level. Namely, 30.9 % of the

general poor are potentially covered by the new PMT system, and 35.9% of the

nutritional poor.

The current Social Aid program of regular cases in Mauritius island leads to spend 91%

of the budget on individuals who are non-poor in the general sense, and 97 % on

individuals who are non-poor in the nutritional sense. In contrast, the proposed focused

PMT scheme allows us to reduce the Leakage to 71.9 % of households and 72.1 % of

individuals when considering general poverty; and 86.9 % of households and 83.9 % of

individuals when considering nutritional poverty.

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With the focused PMT, the reduction in poverty severity is of 17 % (from 0.449 to

0.374), with the same budget.

Using the PMT score with uniform transfers and a selection threshold at the nutritional

poverty line produces a 4 % fall of the head-count index associated with a 8 % fall of

poverty severity.

From there, we added the new variables to the score and we incorporated the additional

conditions. This yielded a large set of new simulations (not shown to save on time).

Unfortunately, these new simulations provided rather disappointing results. They do not

allow us to improve the performance of the PMT in terms of poverty reduction, and

even sometimes raise poverty levels. More work could be done in this direction, though,

as only a few days were available to push these simulations.

There are several reasons why the new simulation did not provide much improvements.

First, the only data usable with the new variables is the LCS data that is characterised by

a small simple size and an unbalanced simple scheme. These data do not allow to

generate as strong predictions as the HBS data which was used to specify the initial

PMT formulae. Indeed, the (quantile) regressions are less accurately estimated than

from HBS data, notably because of the much smaller simple size. This yields less

accurate predicted living standards than for the initial PMT, even when using more

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variables. Therefore, the estimated performance of the new PMT is in fact less

satisfactory for the anti-poverty policy.

Second, the introduction of additional conditions to protect some of the loserrs of the

reform seems to have caused some confusión as to the aim of a social aid system.

The impact of the additional conditions weakens the efficiency of the PMT, although

rather marginally as only a few current beneficiaries can be rescued by these conditions.

However, clearly with just a few percent of the poor covered by the current system,

preserving some of the ineligible current beneficiaries is always going to degrade the

performance of the system in terms of povery alleviation. Now, there may be other

motivations to keep some of these beneficiaries, for example dealing with gender issues

or health problems for non-poor households. This was not initially the approach of the

government who wanted to center the social policy on the poor.

Third, these estimation results do not mean that introducing new variants in the PMT is

not a good idea. It is just that we do not have the data to estímate accurately enough the

coefficients of these variables in the score. To progress from this, CSO should include

these variables in the next HBS. Then, new PMT socre including these variables could

be reestimated from these new data. In any case, it will be useful to update the PMT

formula when the new HBS data is available.

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6. Policy Conclusions and Recommendations

6.1. The Issues

A few central issues remain within the social and administrative system which would

need to be tackled in order to make the reform successful.

First, grossly wrong statistics or figures are routinely used in various documents about

the reform. This is contradicting the strategy of capacity building in management and

analysis of social statistics at MSS, which is a central objective of the SRM project.

Beyond, the lack of knowledge and experience of survey statistics techniques, this

denotes that the basic documents in the country about social aid, targeting and poverty

analysis have often not even been read by the authors of these documents. I cannot see

how any credible policy can be produced without a basic effort of acquiring core

information. There is nothing wrong is not knowing well how to compute statistics as

long as these wrong figures are not used. It is so simple to use correct and published

figures instead.

Note that many statistical reports have been produced by the SRM project. In these

report, almost all the useful statistical results are present. Moreover, deontology requires

citing the sources of the used statistics. Too often, ‘cooked out’ figures distort the

Mauritius reality (as grossly wrong coverage of the poor by social aid for example).

This lack of control of statistics in the reform documents has several damaging

consequences we would like to avoid. On the one hand, it makes the public and the

knowledgeable experts doubt about the seriousness of the reform. On the other hand,

wrong statistics may lead to wrong policy conclusions such as ‘almost no households

34

will be excluded’, which are not only ludicrous but may harm the population in the end.

So, more rigour is needed in the use of statistics for the reform.

Second, the additional conditions proposed by the SRM Unit from a synthesis of

internal MSS expertise are useful, while they have only limited impact. It is doubtful if

they will sufficiently provide sufficient protections to the losers of the reforms in

situations where the empowerment system is not fully operational.

But is the aim of the reform to protect losers at all cost? Ultimately, this question is

related to the policy trade-off between serving the poor or other social categories of

destitute households. If the view of the government is still to reorient the social system

in the direction of the poor, these additional conditions are not as important as if new

policy targets are decided.

Third, at the core of some current reform proposal is the illusion that it would be

possible to immediately ‘empower’ the PMT-excluded social aid beneficiaries, and

therefore make the suppression of their benefits harmless. However, my perception of

the situation after several years of work on social systems in Mauritius is that the

current empowerment system at MSI and eslsewhere is far from ready to deal with

losers of the reform. In fact, I doubt that a comprehensive and functioning

empowerment system can be put in place before a few years of capacity building

efforts. This opinion is consistent with a recent UNDP report (Sibandan, 2010), which is

crystal clear about the glaring gaps in the current empowerment system.

35

The truth is that there is no immediate capacity in the country for dealing with a

controled ‘Grand Reform’ of the social system. However, a limited reform centered on

the PMT implementation is still possible.

The fact that the empowerment system is not ready makes the chosen additional

conditions less relevant, as these conditions are based on the assumption that mostly

persons who cannot be empowered should be of concern. However, these conditions can

still be used on the ground that excluded beneficiaries could be promised to benefit from

empowerment programmes in the future when these are ready. In that sense, the

compensation to losers is delayed in time, while not inexistent.

Fourth, at the moment, there is not enough safe information available on some

categories of current or potential beneficiaries to be able to monitor their situation well.

This is the case for the ‘Immediate Payment’ beneficiaries and for Rodrigues island.

These cases are important enough to justify further investigation.

Fifth, despite the efforts devoted by the SRM Unit and other national administration

offices to clarify these questions, the information on budget structures and the

corresponding projections still seems to be on shaky bases. As mentioned in a previous

report, some further efforts from MSE and MOFEE are necessary to reach more control

in this area.

An improvement would be to make transparent the principles for deciding of the level

of the global transfer budget. Then, it would also be useful to routinely establish social

budgets at a very disaggregated level. For example, one would like to know the amount

of transfers by sub-programmes (the ‘application reasons’ in CS data), with the

36

breakdown between immediate and regular cases, and separating the islands of

Mauritius and Rodrigues.

Finally, it would be worthwhile to explore the interconnection of MSS and MSI budget

in the perspective of MSI of financing some transitory assistance in the form of cash

transfers for current MSS beneficiaries who are going to lose their benefits with the

PMT implementation.

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6.2. Recommendations

(d) Statistics

Make available all relevant statistical documents to the experts and staff involved in the

reform and ask them to read them carefully.

Control important indicator estimates. Avoid claiming policy conclusions from badly

understood statistics.

Cite sources of information and/or estimation methodology for statistics. Any figure

without citing the source is to be considered as suspect.

(e) Additional conditions

Systematize and improve the informal checks already carried out for current MSS

programs in the case of the new PMT-based social aid. The results of the checks can be

used for excluding applicants but also to temporary rescue current beneficiaries from

being excluded from the new program.

Keep on social aid all current beneficiaries of carer’s allowance and ex-Gratia.

Introduce Medical reports from MSS medical board to limit frauds further.

38

Use the proposed Additional conditions for the Medical and Carer’s allowance

applications.

( c) Information Needs

Collect more information on current and potential beneficiaries for the ‘Immediate

Payment’ cases and for Rodrigues.

Add questions about a few correlates of living standards in the next CS and HBS

questionnaires.

Produce budget breakdown separating Immediate and Regular cases. Clarify the

mechanisms producing the budget for transfers over a few years.

(d) Budget

Associate MSI to the protection of current beneficiaries during the transition period of

PMT implementation. There are many unspent funds of MSI because the empowerment

capacity is no longer in place. These funds could be used to compensate ‘losers’ of the

reform for a limited period.

Once the definite budget is known for Regular cases in Mauritius, an adjusted threshold

can be estimated for the PMT corresponding to the cases, under additional conditions.

Thus, there is some flexibility in the calculus of transfer benedit that can be adjusted to

the finally decided annual budget.

39

(e) Grouping programs

Group Income Support and Social Aid under the same PMT program.

Eliminate the sub-programmes ‘Additional Social Aid’ and ‘Sudden Loss of

Unemployment’ that have very few ineligible beneficiaries under PMT.

(f) Deal with Immediate Payment Cases

Monitor the Immediate Payment cases and design selection rules to deal with the most

dramatic situations only.

Continue to deal these IP cases, instead of substituting them with PMT, until more is

known about them and it is clear that they can be discarded.

(g) Focus to the poor

Decide if the population of the poor is still a priority. It is legitímate to be concerned

about other target population than the poor and deal with gender issues and health

problems. However, not implementing PMT in order to overprotect these populations

will amount to sacrifice the interest of the poor, which is the main target population.

40

Abandoning them to serve other destitute categories instead would be a major policy

change that can only be decided at the top goverment level.

However, if the priority given to the poor is confirmed, the sooner the PMT can be

implemented, even with imperfections, the better. At the moment the very low coverage

of the poor by social aid (5% for the Regular cases in Mauritius Island) is hurting them.

Delaying PMT implementation implies a continuation of such damage to the poor since

post-PMT coverage of the poor is about 30%.

On the whole, with the additional conditions and possible complement budget from MSI

to compensate losers of the reform, the benefits of moving from the current social aid

system to PMT for the poor very largely offset the inconvenients suffered by a few

losers of the reform. So, we recommend implementing the PMT as soon as possible.

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6.3. Policy Options

Option 1: Just apply PMT to Mauritius such as described in Muller (2010). After further

analyses, what was first proposed appears as quite robust to our attempts of

improvement. No much more can be done at the moment in termes of statistical

efficiency with the current available information. Keep IP cases.

Option 2: Apply PMT to Mauritius with the additional conditions proposed in Section 2.

Keep IP cases.

Option 3: Apply PMT and keep completely the category Medical along with additional

conditions. Then, the budget differential would come from the unspend funds from

MSI. Keep IP cases.

Option 4: Apply PMT universally including Rodrigues and IP cases. Use additional

conditions

Option 5: Do nothing.

Appendices

A1: References:

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Foster, J., J. Greer, and Thorbecke, E. (1984), “A Class of Decomposable Poverty Measures,” Econometrica, vol. 52: 761-765.

Muller, C. (2005), "Optimising Anti-Poverty Transfers with Quantile Regressions," Applied and Computational Mathematics, Vol. 4, No. 2.

Muller, C. (2009a), “A Nutritional Poverty Profile in Mauritius 2006-07,” UNDP

Mauritius, Port-Louis, January.

Muller, C. (2009b), “Living Condition Survey in Mauritius: General Poverty Profile,”

UNDP Mauritius, Port-Louis, October.

Muller, C. (2010), Targeting Indicators of Social Aid in Mauritius,” UNDP Mauritius, Port-Louis, June 2010.

Muller, C. And S. Bibi (2010), “Refining Targeting against Poverty: Evidence from Tunisia”, Forthcoming Oxford Bulletin of Economics and Statistics.

Sibandan, B., “Aide Ménoire Mauritius scoping mission, main findings and recommendations,”UNDP, Mauritius, October 2010

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