Equity and Efficiency in Service Delivery: Human Resources

General Budget Support

Annual Review, 2008

Wednesday 26 November

Contents

• What is the context?• How large is the inequity in human

resource distribution? • What are the trends?• How does it affect welfare?• What are the factors that need

addressing?• Way forward and detailed proposed

measures• What can be done in the next year?

Gains in service delivery

• Primary education enrolment up from 59% (2001) to 84% (2007)

• Sharp reductions in infant and under 5 mortality - estimated 41% drop over 8 years

• But problems persist with…unequal distribution of gains across Tanzania

Primary Enrolment Rates, 2001, 2007

0%20%40%60%80%

100%

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3rd

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2001 2007

HBS shows increases in the equality of primary school enrolment…

…but inequality remains. The enrolment rate is 78% in the poorest quintile and

91% for the best off quintile.

We will look at health and education because…

• MKUKUTA priority • Nearly 30% of total budget• Staffing budget for teachers and health

workers is largest part of this• Nearly 350,000 public servants

– 55.9% teachers– 6.8% health workers

We will use public expenditure on wages as proxy for number of workers in next slides

Workers are inequitably distributed in health

sector…

Health Staffing Budget 2008/9 per capita

IFMS MoFEA

Education Staffing Budget 2008/09 per 7-13 aged child

IFMS MoFEA

Top 10 get 8 x more resources than bottom 10

And this is replicated in education

The pattern persists over past decade

-10,00020,00030,00040,00050,00060,00070,000

- 50,000 100,000 150,000

Education spend per child 2007/ 8 - Tsh

Edu

catio

n sp

end

per

child

199

9/00

- Tsh

Login Tanzania

If you received a high level of funding per child in 1999/00 likely to receive

a high level in 2007/08

Poorest areas receive lower levels of funding

5,000

7,000

9,000

11,000

13,000

15,000

17,000

19,000

- 20,000 40,000 60,000 80,000

Education spend per 7-13 - 2001 - Tsh

Poverty - 2

001

It matters for poverty & welfare outcomes

Login Tanzania, 2001 Household Budget Survey and 2002 population census

As can be seen looking at education

010

2030

405060

7080

90100

0 10,000 20,000 30,000 40,000 50,000 60,000 70,000 80,000

Education spend per 7-13 yr old - 2004 - Tsh

Stan

dard

VII

% p

ass r

ate

2004

The more that is spent per child, the greater the likelihood of success

in examinations

Login Tanzania, 2001 and EMIS

How does recruitment and posting happen?

1 LGAs/MDAs submit an establishment request that is approved by PO-PSM

This is based on the number of facilities e.g. each clinic needs a certain number of workers to be fully staffed and other criteria

2 Recruitment drive takes place at LGA/MDA level

Health workers and teachers are supplied by the centre

3 Establishment of new recruits that report to duty in civil service and payroll

And many of those that are recruited (or posted) to under-served areas do not report to duty

E.g.07/08

Ministry of Health: 3,645 workers recruited, only 2,533 reported to duty

In Rukwa: 122 health workers posted , only 31 reported to duty

What about the formula-based block grant allocation system?Introduced in 04 to address inequity in financial resource allocation of the recurrent block grant.Determines the staffing budget allocation based on population needs e.g. number of school going children

but…

Staffing budget can only be disbursed against the actual number of workers in duty

Creating a gap between the number of posts allocated and the number actually filled, despite the available establishments and budgets. This is due to the difficulties in attracting workers to under-served areas.

Let’s show this visually…

LGA = Rungwe(Rank 18)

EDUCATION STAFFING BUDGET

Per 7-13 Year Old

BLUE LINE2008/9

BUDGET

RED LINEFORMULA

Hold harmless would prevent large immediate staffing

cuts & allow gradual smooth transitionHowever, formula cannot be applied because it is hard to attract

& retain staff in underserved LGAs

Rungwe’s staffing budget would fall if formula applied

• It cannot only be about allocating financial resources on an equitable basis

• Need to address the underlying factors that drive the inequity?...

• Attraction and retention of staff

Key factors to address• Difficulties in attracting and retaining

workers to under-served areas

– Continued recruitment in better served areas

– 8000 transferred in just over a year to better served districts

– Administrative procedures – speed, clarity– Roles and responsibilities, coordination –

who does what?– Lack of comprehensive, accessible and

regularly updated data on staffing

Way forward

• In the long term…– infrastructure– amenities– increased numbers of skilled workers

…will make a huge contribution.

• But there are tangible things that can be done in the short-medium term...

Twin-track approach

• Pull factors - targeted incentives in under-served areas

• Push factors - limiting workforce in better served areas

Pull: Provide incentives at central & local levels

• Central: • ‘Attraction’ packages - monetary and non-

monetary• Local: • Empower local government authorities to

create local incentive schemes • Assist in deploying to and within districts• Explore flexible funding for LGAs - existing

or new discretionary funding channels • Learn from others

Push: limit workforce expansion

• Limit recruitment in and transfers to better served district councils– Centrally managed– Short-term– Using an agreed classification

In order to do this what do we need?

• Classification of under-served/better-served in relation to need

• Cross-government review of administrative procedures, roles and responsibilities

• Continued roll-out of the Human Capital Management Information System across government

• Development of Medium-Term Pay Policy

What can be done in the next year?

• Key stakeholders agree on a comprehensive roadmap – Clear time frames, – budgetary implications, – and technical and financial support

required• Classification of under-served/better-

served• Use established inter-ministerial

(education) task force • Medium-Term Pay Policy finalised

Summary• Pull factors - targeted incentives in under-

served areas• Push factors - limiting workforce in better

served areas• Key stakeholders agree on a

comprehensive roadmap • Classification of under-served/better-served• Use established inter-ministerial (education)

task force • Medium-Term Pay Policy finalised