Development Targets and Costs

Development Targets and Costs

Based on paper by Luc ChristiaensenChristopher ScottQuentin Wodon

Outline

1. Current practice2. The political economy of target setting3. Approaches to target setting

Historical benchmarking; Macro-simulations;Micro-simulations

4. Approaches to cost estimationAverage costs and efficiency

5. Concluding remarks

1. Are current targets realistic?

A target is a value which a specific indicator should attain by a particular date Current practice

Honduras: cost of reaching PRSP targets and IDG goals together with anticipated wage increase for public employees is high vs HIPC debt relief

Guinea:• Goal: 10 % annual agricultural growth rate by 2010;• Only 5 % of the 3921 recorded 3-year moving averages of ag growth in

all countries worldwide over past 4 decades exceeded 10 % growth rate

Cambodia:• Goal: reduce child undernutrition by 15 % points from 1998 to 2000;• requires annual GDP/cap growth rate of 31 % (2005 as end date)

2. Political economy of target setting

Targets provide incentivesa) Resource mobilization

targets must be realistic

b) Resource allocation and consensus building broad societal support and iterative process required proliferation of targets erodes their effectiveness

Political economy of target setting, cont. 2

c) Performance evaluation: targets introduce accountability• Targets must be attainable and carry broad societal

support• Poor performance by implementing actors must be

distinguishable from the effects of external shocks• Failure to meet targets must entail consequences for the

actors

While targets have in principle positive incentive effects, these do not follow automatically

Political economy of target setting, cont. 3

Experience from BritainWhen the Government set local authorities a target for collecting recyclable waste, it seemed a good idea. Even better, the local authorities persuaded residents to take the trouble to separate the stuff that was worth recycling from all the rest--and met their target. There was only one snag. The target was for collecting recyclable waste, not for recycling it. As a result, some local authorities put the rubbish that had been so carefully separated back in with the rest of their garbage, and incinerated the lot.

Targets must be SMART: Specific, Measurable, Achievable, Relevant and Time-bound

Selected choices in target setting

Targets for inputs, outputs, or for outcomes and impacts?Focus on outcome and impact targets, though input and output targets possible for short runCheck for vertical and horizontal consistency (Uganda)Caution against proliferation of targets

Point targets or target ranges?Given uncertainty surrounding input/output relations:

• target ranges for outcomes/impacts• target points for inputs/outputs

Selected choices in target setting, cont. 2

Aggregate or disaggregate targets?Equity versus efficiency

But: perverse incentives and proliferation of targets

Short-run or long-run targets?Decision rule: marginal cost of, say, poverty reduction equated across time periods

In practice: thought needs to be given to appropriate time path for achieving the target, depending on state of country

3. Approaches to target setting

To facilitate resource allocation and to foster accountability it is key that targets are realistic: they must be technically and fiscally attainableThree methods to gauge technical feasibility

Historical benchmarking

Macro-simulations

Micro-simulations

3.1 Historical benchmarking

Historical evidence and international comparisonNeither time nor skill intensive and data readily available hence, this is a minimum requirementAgricultural growth in Guinea and neighboring countries 1970-2000

3-yr moving avg Guinea Cote d’Ivoire Ghana Mali Senegal

Mean 1987-2000 4.2 3.2 3.0 4.0 1.3Frequency 1970-2000Moving avg. >10 %Moving avg < 0 %

00

06

06

36

28

Proj. growth 2010 (lin. trend)1987-20001970-2000

7.3-

2.82.6

7.83.3

0.44.8

4.81.4

3.2 Macro-simulations

Gauge feasibility of poverty and social development targets by feasibility of implicit economic growth requirementsTwo methods to set targets for poverty

Growth required to reduce poverty by a certain percentage, assuming no change in income distribution

Estimated net elasticity to growth

Liberia: growth & pov. simulations

0.0

10.0

20.0

30.0

40.0

50.0

60.0

70.0

80.0

2007 2008 2009 2010 2011 2012 2013 2014 2015

1% annual growth of the GDP per capita 2% annual growth of the GDP per capita 3% annual growth of the GDP per capita

4% annual growth of the GDP per capita 5% annual growth of the GDP per capita 6% annual growth of the GDP per capita

Macro-simulations, continued

Estimated elasticity of social indicators to GDP/cap growth controlling for time trends and urbanization ; (elasticities can be estimated with world wide panel data (splines, 5 intervals) for GDP/cap and urbanization)Exemples:

Demery and Walton (1999) use an elasticity of under 5 child mortality to GDP/cap growth of –0.4 (SimSIP elasticity varies between zero and –0.47)Alderman et al. (2000) estimate an elasticity of prevalence of child malnutrition to GDP/cap growth of - 0.09 (SimSIP elasticity between zero and –1.1)

Macro-simulations, continued

Other intervening factors may be important results of growth based simulations indicative only

Some tools arguably more sophisticated though also more data and skill intensive; yet literature now exists

Must be used with caution as results are not indicative of policy actions needed

3.3 Micro-simulations

Country-specific nature of relationship between development outcomes and their determinants lost in macro approach regression analysis and micro-simulations based on household dataApplication to child malnutrition in Ethiopia:

15 years of 2.5 % growth of income/adult equivalent and bringing at least one female adult/household up to level of primary school level reduce prevalence of child stunting by 9 to 29 percent, far removed from international goal of halving child stunting by 2015If combined with nutrition education programs reduction by up to 42 %

Increasingly possible, as more and more household data sets are becoming available, yet technically difficult

4. The cost of reaching a target

Targets must be technically AND fiscally attainableEffect of (public and private) expenditures on development outcomes depends on:

amount spent on these objectives effectiveness of money spent

Fiscal sustainability of targets can be gauged byGovernment’s capacity for increasing public spendingGovernment’s scope for enhancing efficiency of its spending

4.1 Costs and fiscal sustainability

Need for detailed sectoral informationSimSIP simulator for estimating costs of reaching education targetsEducation example: average costing method Need for assumptions on:

Demographics: number of children of various age groups joining education system

Costs and fiscal sustainability, cont.2

Data on Cost parameters:

• Supply-side costs: teacher wage, teacher-student ratio, administrative costs

• Demand side costs: stipend value, coverage• Investment costs: cost per classroom, teacher training

Delivery system: • length of schooling cycle, repetition, promotion, and drop out rates by

cycle or by grade, distribution of age at entry for each cycle

Targets for • Changes in distribution of age at entry• Changes in repetition, promotion and drop out rates

Costs and fiscal sustainability, cont.3

Logic of education costing• Detailed cohort analysis depending on efficiency

parameters (promotion, repetition, drop out, …)• Parametrize software to reproduce initial conditions

– budget spending by cyle– teacher salaries, share of administrative budget– number of children enrolled by cycle– net & gross enrollment rates, with targets– realistic other parameters (cost of new schools/classrooms)

• Change efficiency parameters and demographics over time, and track various costs as they evolve

– Number students number teachers/classrooms costs

Costs and fiscal sustainability, cont.3

Selected parameters for Liberia – primary level(all parameters must be checked)

• Net enrollment (CWIQ 2007): 37.3% (low probably due to conflict – older children enrolling in last few years)

• Gross enrollment (CWIQ 2007): 86.3%• Budget: +/- US$ 4 million• Number of teachers: 26,755 cost/teacher• Number of students: 894,316 pupil/teacher ratio 33• Share of public sector: 67% (incl. community)• New entrants every year: +/-110,000, to increase in future• Admin cost: 15% (assumption)

Costs and fiscal sustainability, cont.3

Selected parameters for Liberia – secondary level(all parameters must be checked)

• Net enrollment (CWIQ 2007): 15.2% (low probably due to conflict – older children enrolling in last few years)

• Gross enrollment (CWIQ 2007): 51.3%• Budget: +/- US$ 1.5 million (need to check)• Number of teachers: 8756 cost/teacher• Number of students: 150,914 pupil/teacher ratio 17• Share of public sector: 46% (incl. community)• New entrants: depends on primary schooling parameters• Admin costs: 15% (assumption)

Example of simulation (VERY prelim.)

Note: 2003 in simulator represents 2006 in reality; Assumes no increases in real wage for teachers; Secondary spending expected to increase faster; Possibility to estimate needed investment costs; overall costs probably underestimated/need to get correct data

Recurrent Costs

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1.00

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8.00

2003 2006 2009 2012 2015 2018Time (year)

4.2 Efficiency considerations

Outcomes can be increased throughExpansion of inputs keeping efficiency constant Increase in efficiency keeping inputs constant

Given limited tax base, room for expansion of social expenditures often narrowMurray et al. (1994): typical country in Sub Saharan Africa could improve health outcomes by 40 % simply by reallocating resources to most cost-effective intervention mix

Measuring efficiency

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100

0 20 40 60 80 100

input

ou

tpu

t

oa

b

Best performance frontier

E=a/(a+b)

Measuring efficiency, examples

Efficiency of national health systems (WHO)Output: disability adjusted life expectancy

Inputs: real total (private and public) health expenditures/capita and average years of schooling

E>0.7 (good): Costa Rica, Sri Lanka, Bangladesh (good)

0.7<E<0.5 (mediocre): Gambia, Viet Nam

E<0.5 (poor): most African countries, e.g. E for Guinea and Kenya respectively 0.47 and 0.32

Concluding remarks & discussion points

In principle, targets powerful tools to foster accountability and facilitate consensus building;

Targets must be carefully designed and evaluated; they must be SMART

Chapter focused on feasibility aspect, though also need for more hard rules on other aspects of target design

Remarks & discussion points, cont. 2

Set of readily applicable tools to assess technical and fiscal feasibility of development targets

Each tool has its limitation need for joint applicationTools must be used with care; they are indicative of feasibility of targets, but not of policies neededTools only useful in practice if readily available

• Need for continuous updating of elasticities = public good• Encourage policy simulations based on household data• Research on efficiency of expenditures on social outcomes