Do Poverty Reduction Strategy Papers Reduce Poverty and Improve

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Do Poverty Reduction Strategy
Papers reduce poverty and
improve well-being?
Meg Elkins
Simon Feeny
David Prentice
EADI Conference June 2014
Outline
• Background and motivation
• Research questions
• Data
• Methodology – 3 stages
• Results
• Conclusion
2
Background and Motivation
• Poverty Reduction Strategy Papers: (PRSPs): strategic frameworks for lowincome countries to create economic and social policy to reduce multidimensional poverty
• PRSP guiding principles:
• Country-driven and owned; results orientated; comprehensive in scope;
partnership orientated; medium and long-term in focus.
• Collectively, Millennium Development Goals and PRSPs demonstrate the
importance of tackling poverty in its many forms.
• Due to lack of consensus regarding the practicalities of how the MDG targets
would be achieved MDGs were integrated into PRSPs in March 2001.
• Opportunity to reflect on the relative successes of this generation’s policy
tools to inform the next generation of MDGs.
• Provide feedback to the open policy space beyond 2015.
3
Background
• Motivation
• The paper was motivated by a paper by Sumner (2006) questioning the next
plausible contemporary paradigms to emerge in the PRSPs.
• This study extends the literature in the PRSP effectiveness in two ways
• 1) Adopts a multi-dimensional concept of well-being to include MDG
indicators
• 2) Uses heterogeneous and homogeneous PRSP treatment effects –
measures how alignment to the development paradigms further impacts on
MDG indicators
4
Research Questions
1) Do PRSP
adopters achieve
better progress
towards MDG
targets and
poverty reduction
than non-adopting
countries?
2)Does the paradigm
alignment of the
PRSP influence
progress towards
achieving the MDGs?
5
Data
• Panel of 118 countries from 1999-2008 (52 developing countries undertaking
PRSP and 62 control countries) provide the period of treatment
• 7 MDG indicators (WDI): headcount poverty, primary school enrolment, ratio
of girls to boys in the classroom, infant mortality, maternal mortality, HIV
prevalence and access to sanitation
• Control Variables - World bank Governance, GDP per capita (2005), real
GDP, Health expenditure (for the health indicators).
6
Three stage methodology
First stage – devising paradigm alignment
indices
Second stage – determining appropriate
control group . Propensity score matching
Third stage – fixed effects panel –
difference-in-difference estimations
7
Stage 1: Paradigm Alignment Indices
• Scorecards – to assess the degree of alignment to the development
paradigms. For construction see Elkins, 2013; and Elkins and Feeny, 2014
• Washington Consensus: Williamson’s (1990)
• Post-Washington – Rodrik’s interpretation (2005)
• New York Consensus – Millennium Development Project (2005)
• Social Protection Agenda – ADB and Baulch & Wood (2008)
• Index values fall between 0-1
8
Development Paradigms: Washington Consensus –
Williamson (1990)
• Fiscal discipline
• Re-orientation of fiscal expenditures
• Tax reform
• Financial liberalisation/interest rate liberalisation
• Unified and competitive exchange rate
• Trade liberalisation
• Openness to foreign direct investment
• Privatisation
• Deregulation
• Secure property rights
9
Post-Washington Consensus Rodrik (2006)
• Corporate governance
• Anti-corruption measures
• Flexible labour markets
• WTO agreements
• Financial codes and standards
• Prudent capital account opening
• Non-intermediate exchange rate
• Independent central banks
• Social safety nets
• Targeted poverty reduction
10
New York Consensus: UNDPs Millennium Development
Project (2005)
• Infrastructure capacity – capital expenditure
• Rural development- agricultural productivity and management
• Education – provisions
• Health – child and maternal mortality, control for diseases
• Governance – rule of law and anti-corruption measures
• Employment – public works, decent work programmes
• Water and sanitation – infrastructure and management
• Gender equality and empowerment – representation and land entitlement
Environment – biodiversity, urban dwellings, resource protection
• Science and Technology – research and development, higher education
11
Social Protection Agenda
1.
Cash transfers – cash transfers, 1.
cash for work schemes*
Unemployment
insurance*
1.
Labour
market 1.
legislation
to
protect
labour
rights***
Priority or pillar for
social protection in
the PRSP
1.
Cash-in-kind
transfers 1.
agricultural inputs, shelter, nonfood items**
Unconditional
unemployment
payments**
1.
Child
labour 1.
protection – labour
code***
Micro-finance*
1.
Subsidies for housing, energy, 1.
and food**
Educational assistance
1.
Scholarships *
Health/sickness
insurance*
Non-contributory
pension schemes**
1.
Minimum
Wage***
employment
promotion,
matching people to
jobs*
1.
Fee waivers
services.**
Contributory
schemes**
1.
Disaster relief programmes – 1.
funds for emergency relief or
post-emergency transitions.**
Disability pensions*
1.
Targeted conditional cash- 1.
transfers for service delivery **
Maternity allowances*
1.
Programmes for vulnerable 1.
groups: the elderly, disabled
widows and, orphans.*
Industrial
payments*
1.
Programmes for the internally 1.
displaced:
migrants
and
refugees**
Family payments**
1.
for
essential 1.
1.
pensions
injury
12
Stage 2: Propensity Score Matching
• To construct an appropriate control group the study uses propensity score
matching techniques
• Matches on the probability of PRSP treatment based on similar country
characteristics
• Matched on the infant mortality – large sample size and consistency across
all MDG variables
• Matched on cross section data averaged between 1996-1999 – ie pretreatment characteristics to determine the likelihood of treatment.
• The following variables related to infant mortality: External debt to GNI, GDP
per capita, Governance, % health expenditure to GDP, and Ethnicity
• 52 PRSP treatment countries matched with 62 control countries
13
Stage 3: Difference-in-difference estimation
• D-I-D used in combination with PSM is a relatively new programme
evaluation technique
• Regressions estimations D-I-D controls for any pre-existing constant
difference in the outcomes
• Countries adopt PRSPs in different years –therefore the indicator is only
switched on when ‘treatment’ is in effect
• Use PRSP dummies to capture country and fixed effects – prior and post
policy changes.
14
Model Specification
1) Base regression specification
Yit  0  1PRSPit  3 X it  1   t   it
(1)
Evaluates MDG progress from the PRSP treatment
Uses PRSP treatment dummy to determine treatment effect
2) Alternate specification with alignment indices
Yit = 0 +1PRSPit + 2PRSP*PAISit + 3Xit + i +t +it
(2)
Uses interaction term between the treatment dummy and alignment
scores
15
Average Treatment effect
• Average treatment effect estimates the potential unobserved outcome
4
ATE  1 PRSP    J PAIS J PRSP
J 1
(3)
16
Results
Head-Count Head-Count Primary
Poverty
Poverty
School
Enrolment
PRSP treatment
Ratio of
Female to
Male in PS
-3.947***
2.498***
1.870***
(-3.62)
-3.62
-6.04
Interact WC
Interact PWC
Interact NYC
Interact SPI
Average Treatment
Effect
Observations
R-squared
Number of Countries
Primary
School
Enrolment
357
0.468
91
Ratio of
Female to
Male in PS
10.292*
3.226
5.126***
-1.92
-1
-3.41
-9.573
-17.945***
-6.882***
(-1.51)
(-4.82)
(-3.89)
-3.867
9.737***
3.106***
-3.867
9.737***
3.106***
(-0.88)
-4.29
-2.91
(-2.10)
(-2.56)
(-4.70)
-1.371
2.336
1.896
357
0.489
91
784
0.277
105
784
0.322
105
1,009
0.284
110
1,009
0.311
110
17
Results continued
PRSP treatment
Infant
Infant
Mortality Mortality
Maternal
Mortality
-3.132***
-5.805
-0.186***
0.674***
(-8.143)
(-0.35)
(-3.69)
-2.64
Interact WC
Interact PWC
Interact NYC
Interact SPI
Average Treatment
Effect
Observations
1,120
R-squared
0.639
Number of Countries 112
Maternal
Mortality
HIV
HIV
Access to Access to
Prevalence Prevalence Sanitation Sanitation
2.012
-180.321*
0.179
3.157**
-1.039
(-1.73)
-0.75
-2.49
-1.163
288.031***
0.381
-3.129**
(-0.531)
-4.12
-1.42
(-2.18)
-3.067**
47.787
-0.453**
-1.992**
(-2.212)
-0.99
(-2.55)
(-2.19)
1.457
-90.572
0.243
2.026**
-1.082
71.832
-1.47
-2.33
-2.0345
-1.43
-0.118
1.724
1,120
0.645
112
266
0.307
105
266
0.391
105
910
0.111
91
910
0.125
91
1,089
0.43
110
1,089
0.441
110
18
Discussion
• Results find that PRSP adopters did achieve statistically significant
improvements in all categories but maternal mortality – although data was
weakest for this indicator
• Heterogeneous effects as estimated by average treatment effects reported
marginally smaller results for headcount poverty, primary school enrolment,
ratio of girls to boys in the classroom, infant mortality, maternal mortality and
HIV prevalence. The ATE for sanitation was larger.
• New York Consensus found statistically significant improvements for primary
school enrolment, ratio of girls to boys in the classroom, infant mortality, and
HIV prevalence
• Alignment to the SPI was significant for headcount poverty and for access to
sanitation.
19
Conclusion
• Evidence from this study suggest that PRSP recipients more effective
at achieving MDG outcomes than the comparison group of countries
• Inclusion of the paradigm alignment indices tries to address the issue
of causation by including policy choices made within each PRSP.
• Results are encouraging for the international community with PRSP
treatment and alignment to the NYC achieve even higher results for
all MDG indicators except maternal mortality and access to
sanitation.
• These results evidence how the ambitious targets of the MDGs used
in combination with the practicalities of the PRSR are able to deliver
the intended objective of multi-dimensional poverty reduction.
• Augurs well for setting and embedding ambitious targets in the next
generation of MDGs
20
Conclusion
MDG Indicator
GOAL 1
Head Count Poverty
$1.25
GOAL 2
PS enrolment
GOAL 3
Ratio of male to
female in PS
GOAL 4
Infant Mortality
GOAL 5
Maternal mortality
GOAL 6
HIV/Aids
GOAL 7
Improved access to
sanitation
NYC
SPI
-
-
-
+
-
-
+
-
-
+
-
+
-
-
+
+
PRSP
treatment
Without
paradigm
index
-
PRSP
with
paradi
gm
index
+
+
+
+
-
+
WC
PWC
+
+
-
+
-
-
+
21
Thank you!
• Meg Elkins
• RMIT University – Melbourne Australia
• Meg.elkins@rmit.edu.au
22
MDG progress indicator and PRSP treatment – OLS
MDG progress and PRSP treatment
Model 1
VARIABLES
PRSP treatment
MDG adjusted progress indicator
Ethnic
Average governance
Average GDP per capita
Average health expenditure
Average WC
Average PWC
Average NYC
Average SPI
Constant
Observations
R-squared
F
t-statistics in parentheses
*** p<0.01, ** p<0.05, * p<0.1
-0.022
(-1.51)
0.172*
(1.92)
-0.009
(-1.07)
-0.000**
(-2.34)
0.011
(0.91)
0.571**
(2.54)
-0.203
(-0.83)
0.440**
(2.44)
0.332**
(2.02)
0.200
(1.33)
115
0.796
45.49
23
Treated Countries
Control Countries
Armenia
Azerbaijan
Bangladesh
Benin
Bhutan
Bolivia
Bosnia and Herzegovina
Burkina Faso
Burundi
Cambodia
Cameroon
Cape Verde
Central African Republic
Lesotho
Liberia
Madagascar
Malawi
Maldives
Mali
Mauritania
Moldova
Mongolia
Mozambique
Nepal
Nicaragua
Niger
Nigeria
Algeria
Angola
Argentina
Belarus
Belize
Botswana
Brazil
Bulgaria
Chile
China
Colombia
Comoros
Costa Rica
Dominican Republic
Malaysia
Mauritius
Mexico
Morocco
Panama
Papua New Guinea
Paraguay
Peru
Philippines
Russian Federation
Samoa
Seychelles
Solomon Islands
South Africa
Chad
Congo, Rep.
Cote d'Ivoire
Pakistan
Rwanda
Senegal
Ecuador
Egypt, Arab Rep.
El Salvador
St. Kitts and Nevis
St. Lucia
St. Vincent and the Grenadines
Djibouti
Serbia- Montenegro
Eritrea
Sudan
Dominica
Ethiopia
Gambia, The
Georgia
Ghana
Guinea
Guinea-Bissau
Guyana
Honduras
Kenya
Kyrgyz Republic
Lao PDR
Sierra Leone
Sri Lanka
Tajikistan
Tanzania
Uganda
Uzbekistan
Vietnam
Yemen, Rep.
Zambia
Fiji
Gabon
Grenada
Guatemala
India
Indonesia
Iran, Islamic Rep.
Jamaica
Jordan
Kazakhstan
Latvia
Lebanon
Lithuania
Macedonia, FYR
62 control countries
Swaziland
Syrian Arab Republic
Thailand
Togo
Tonga
Tunisia
Turkey
Turkmenistan
Ukraine
Uruguay
Vanuatu
Venezuela,
Zimbabwe
Albania
54 treated countries
24
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