download accountability and mdgs

Sakiko Fukuda-Parr

Joshua Greenstein

ACCOUNTABILITY AND MDGs

Methodology for measuring government performance for global goals

SOCIAL AND ECONOMIC POLICY

WORKING PAPER

June 2011

UNICEF POLICY AND PRACTICE

Accountability and MDGs: Methodology for measuring government performance for global goals © United Nations Children’s Fund (UNICEF), New York, 2011 Policy, Advocacy and Knowledge Management, Division of Policy and Practice UNICEF 3 UN Plaza, New York, NY 10017 June 2011 This is a working document. It has been prepared to facilitate the exchange of knowledge and to stimulate discussion. The findings, interpretations and conclusions expressed in this paper are those of the authors and do not necessarily reflect the policies or views of UNICEF. The text has not been edited to official publication standards, and UNICEF accepts no responsibility for errors. The designations in this publication do not imply an opinion on legal status of any country or territory, or of its authorities, or the delimitation of frontiers. The editors of the series are Isabel Ortiz and David Anthony of UNICEF Policy and Practice Division. For more information on the series, or to submit a working paper, please contact [email protected] or [email protected].

Sakiko Fukuda-Parr Professor, Graduate Program in International Affairs The New School Joshua Greenstein Graduate Program in International Affairs The New School

JEL Classification: O11, O21, H5, O23, I3 Keywords: Millennium Development Goals, poverty, human rights based approach, development goals, international policy

Comments may be addressed by email to the authors [email protected] and [email protected], cc: [email protected]

UNICEF SOCIAL AND ECONOMIC POLICY WORKING PAPER

JUNE 2011

Accountability and MDGs

Methodology for measuring government performance for global goals

mailto:[email protected]

ACKNOWLEDGEMENTS The authors acknowledge comments on earlier drafts from many colleagues including Mac Darrow (UN Office of the High Commissioner for Human Rights), Alicia Yamin (Harvard School of Public Health), Malcolm Langford (University of Oslo), Susan Randolph (University of Connecticut), Saranbaatar Bayarmagnai (UN Office of the High Commissioner for Human Rights), David Stewart (Chief Social Policy, UNICEF Uganda), Dan Seymour (Senior Programme Specialist, UNICEF) and comments made at the presentations made in June 2011 at UNICEF seminar and at the New School meeting of the network on quantitative methods in human rights and development. The views, findings and conclusions in this paper remain the responsibility of the authors and do not necessarily reflect the policies or views of UNICEF or of the United Nations.

Table of Contents

Page Executive Summary .......................................................................................................................... i Résumé Analytique ..........................................................................................................................ii Resumen Ejecutivo .......................................................................................................................... iii 1. Introduction ............................................................................................................................ 4

2. Interpreting global goals – planning targets, normative priorities or evaluative benchmarks? ................................................................................................................................... 5

1.1. MDGs as economic planning targets .............................................................................. 5

1.2. MDGs as normative goals ............................................................................................... 7

1.3. MDGs as benchmarks of progress ................................................................................ 10

2. Measuring performance of governments related to normative commitments .................. 10

2.1. Qualitative objectives and compliance measures ........................................................ 10

2.2. Progressive realization .................................................................................................. 11

2.3. Targets vs. benchmarks ................................................................................................ 11

3. Methodologies for Measuring Performance: Consensus approach – ‘Achieving the Goals’ 12

4. Alternative approach – ‘Pace of Progress’ ............................................................................ 14

5. Human Rights, MDGs and international development ........................................................ 18

6. Conclusions: MDGs as benchmarks for Millennium Declaration Commitments ................. 21

Appendix Table 1 Population Below $1 per day, (PPP), Percentage ............................................ 23

Appendix Table 2 Children Under 5 Moderately or Severely Underweight, Percentage ............. 25

Appendix Table 3: Total Net Enrolment Ratio in Primary Education, Both Sexes ........................ 27

Appendix Table 4: Gender Parity Index in Primary Level Enrolment ........................................... 31

Appendix Table 5: Share of Women in Wage Employment in Non-agricultural Sector ............... 36

Appendix Table 6: Children Under 5 Mortality Rate per 1000 Live Births ................................... 39

Appendix Table 7: Children 1 Year Old Immunized against Measles, Percentage ....................... 45

Appendix Table 8: Births Attended by Skilled Health Personnel, Percentage.............................. 51

Appendix Table 9: Proportion of Population Using Improved Drinking Water Sources, Total .... 54

Appendix Table 10: Proportion of the Population Using Improved Sanitation Facilities, Total ... 58

References .................................................................................................................................... 63

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Executive Summary MDGs are global goals and are powerful tools of international policy because they create a framework of accountability by going beyond stating general objectives and set quantitative, time bound targets against which performance can be measured. This paper challenges the methodology conventionally used to monitor MDG implementation that ask whether the 2015 targets are likely to be met by extrapolating trends since 1990 or 2000, then categorizing countries as on or off track. This methodology has three drawbacks: bias against countries with lowest starting points; judging country performance on the basis of targets that cannot be justified as sound economic strategy; and interpretation of MDGs as national planning targets rather than global norms. We argue that MDGs arose from a norm-setting process and should be interpreted as benchmarks for monitoring government performance against normative commitments made to end poverty. We draw on the human rights approach to evaluating government performance in honouring normative commitments and propose an alternative methodology that asks how fast is the country progressing towards the goals. The results of the alternative methodology and criteria lead to findings that diverge in important ways from the conventional methodology. The paper aims to two broader questions: to demonstrate the relevance of human rights concepts to development policy; and to clarify normative development goals as instruments of international policy.

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Résumé Analytique

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Resumen Ejecutivo Los ODMs son metas globales, así como también constituyen herramientas poderosas de política internacional; definen un marco de rendición de cuentas, estableciendo objetivos generales, así como metas cuantitativas y con plazos determinados contra los cuales se puede medir su desempeño. Este estudio cuestiona la metodología convencional utilizada para dar seguimiento a la implementación de los ODMs, la cual se concentra en determinar cuál es la probabilidad de cumplir las metas establecidas para el 2015 extrapolando tendencias desde 1990 o 2000, y luego categorizando a los países dependiendo si están o no en la dirección correcta. Esta metodología tiene tres debilidades: una tendencia que desfavorece a los países con puntos de partida más bajos; el juzgar el desempeño de los países sobre la base de las metas que no pueden ser justificadas bajo una estrategia económica sólida; y el hecho que interpreta a los ODMs como metas nacionales de planificación y no como normas globales. En el estudio argumentamos que los ODMs surgieron de un proceso de definición de normas y deben ser por tanto, interpretadas como puntos de referencia para dar seguimiento al desempeño de los gobiernos con respecto a los compromisos normativos hechos para eliminar la pobreza. Nos basamos en la perspectiva de los derechos humanos para evaluar el desempeño de los gobiernos con respecto a sus compromisos normativos y proponemos una metodología alternativa que pretende determinar qué tan rápido un país está progresando hacia el cumplimiento de las metas. Los resultados de esta metodología y criterios alternativos nos llevan a resultados que divergen de manera importante de aquellos obtenidos con la metodología convencional. Este estudio pretende abordar dos preguntas generales: demostrar la relevancia de los conceptos de derechos humanos en las políticas de desarrollo; y clarificar las metas normativas de desarrollo como instrumentos de política internacional.

1. Introduction The Millennium Development Goals (MDGs) and human rights are linked in a complex relationship, sharing important objectives but differing in important ways and engaging two separate communities of scholars, civil society and policy makers. While MDGs overlap considerably with many elements of economic and social rights, the overlap is not complete. They do not reflect some essential human rights commitments such as reducing inequality and removing discrimination, priority to the poorest of the poor, and the process of peoples’ empowerment1. Nor have they emerged from participatory processes and used as a framework of accountability for human rights obligations2. Some MDG targets are less ambitious than the core minimum human rights norms such as the goal to halve rather than eliminate hunger and extreme poverty. They do not include the full scope of important human rights priorities, for example in neglecting social security, rights of minorities, and a range of political, civil and cultural rights. Nonetheless, as Alston noted in his 2005 article, the MDG and human rights agendas are “both headed for very similar destinations’ (Alston 2005 p.27). MDGs can be instrumental for economic and social rights because they shift ideas about development priorities amongst policy makers and the public at large. Their introduction in 2001 consolidated consensus on the purpose of development as ending poverty and improving the well-being of people. As one of the authors has argued in earlier articles (Fukuda-Parr 2004; Fukuda-Parr 2011), the MDGs mark a departure from the dominant development strategies of the 1980s and 1990s which emphasized macroeconomic stabilization and market liberalization as key objectives and neglected the human dimension. While some human rights activists and scholars rejected the MDGs as a useful initiative for human rights (Alston 2005), they have increasingly begun to engage with them constructively, by developing human rights approaches to their implementation and monitoring. These efforts have focused almost exclusively on the design of the MDGs and approaches to implementation. Surprisingly, monitoring government compliance with MDG commitments has been a neglected issue. For example, the most comprehensive work in this literature, the OHCHR guidelines on the human rights approach to MDGs, Claiming the MDGs, critiques the composition of the MDGs and the process by which they were formulated, and proposes implementation strategies that are consistent with human rights agenda (OHCHR 2008). But these guidelines contain less than one out of a total of sixty pages on accountability mechanisms and do not mention monitoring methods. The purpose of this paper is to demonstrate the relevance of human rights concepts in monitoring MDG implementation, and in developing the correct methodology for judging

1 For excellent summaries of these criticisms, see Alston 2005, OHCHR 2008, and Sumner and Melamed.

2 It could be argued that the MDGs were developed through a participatory process since they are a selection from

the goals that had been adopted by UN development conferences of the 1990s which involved highly participatory processes. However the process of formulating the Millennium Declaration did not involve widespread discussion extending to diverse parts of the world and communities. The civil society networks concerned with development perceive the MDGs as something that they were not involved in creating (Bissio 2003).

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performance of countries in honouring their MDG commitments. The current methodology used by the UN, the World Bank, national governments in their monitoring reports asks ‘will the goals be achieved by 2015’? We argue that this methodology, which we refer to as the ‘Achieving the Goals’ approach, is conceptually inappropriate because it interprets the MDGs as if they were national economic planning targets. The MDGs are global goals, adopted through a norm-setting process, one where world leaders agreed on shared common values and priorities. Drawing on the human rights approach of monitoring normative commitments by criteria of progressive realization, conduct and outcome, we propose an alternative measure which asks ‘how much progress has there been towards meeting the goals’ and which we refer to as ‘Pace of Progress’ approach. The paper first reviews the concept of MDGs to argue that they should be interpreted as benchmarks for monitoring normative commitments, and should not be used as planning targets. The second section argues that the methodology for measuring performance of normative goals should focus on the pace of progress, not on achieved levels. The third section reviews the conventional methodology for measuring performance and proposes an alternative.

2. Interpreting global goals – planning targets, normative priorities or evaluative benchmarks?

Global goals are a policy instrument used since the 1960s by the UN to draw attention to and mobilize action on important but neglected objectives. Global goals could be interpreted in three different ways and used for different purposes.

• As planning targets to frame priorities for policy and for resource allocation, in the context of economic development strategies of governments and donor agencies.

• As normative objectives that define long-term visions in the context of norm setting processes. The numerical targets define the goals more precisely and make objectives actionable, set the level of ambition and call for a scaling-up of effort. Targets create incentives for policy makers and other stakeholders to shift priorities.

• As evaluative benchmarks against which progress can be measured in a monitoring process. Progress data can only be interpreted as adequate or not, successful or not, when compared against expectations.

1.1. MDGs as economic planning targets The Achieving the Goals methodology implicitly interprets MDGs as hard planning targets. In practice, some national governments have included MDG targets partially into their Poverty Reduction Strategy Papers (PRSPs) while others have kept them out of their planning frameworks (Fukuda-Parr 2008). Moreover, despite efforts by the UN Millennium Project in numerous countries during the mid-2000’s to cost resources required to achieve the MDGs and to shape the PRSP financing requirements (PRSPs) on this basis, no country implemented the

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results. Furthermore, donors do allocate resources with the objective of facilitating MDG achievement (Fukuda-Parr 2008). Interpreted as planning targets, the MDGs have given rise to some sharp criticisms which question whether the MDGs’ global targets applied as national planning goals can be seriously justified as sound economic strategy. Three sets of issues have been raised. First, the MDGs were poorly designed and selected (Easterly 2009; Saith 2006). For example, there are several different ways that these targets could have been defined, by absolute or percentage changes, change targets versus level targets, and by positive or negative indicators, but the choices were not consistent, and the logic behind how each goal was defined is not always clear (Easterly 2009; Saith 2006). Some of these arbitrary choices have resulted in bias against Africa in that African nations are less likely to meet the goals, and so will be dubbed failures (Easterly 2009). Saith (2006) has pointed out numerous flaws in the list of goals, targets and indicators, including definitional issues, lack of adequate data, especially for goals concerning HIV/AIDS and malaria and maternal mortality, and the unwanted incentives that may arise from “institutionalizing” targets, all of which undermine their potential use as programming tools. Another debate revolves around the distortions that they could create as a consequence of policies necessary to achieve the goals. Gupta and others (2005) have argued that this would require huge external resource flows that would destabilize macroeconomic balances such as through the Dutch Disease effects, while other authors have challenged their arguments (McKinley 2005; McKinley and Weeks 2007). Yet others have questioned whether MDGs as a strategy will create growth and development momentum (Roy and Heuty, 2005); whether the constraints on faster progress are institutional and policy-based rather than rooted in a lack of resources (de Renzio, 2005); and if development stagnation can be explained by a theory of “poverty traps” or if a “big push” to escape this trap would be effective (Easterly, 2009). Finally, a fundamental question that is repeatedly raised is whether the goals should be applied to judge performance at the national level, at least without adaptation. Jan Vandemoortele, who co-chaired the group that formulated the MDGs and led the UNDP support team for MDGs implementation, has been the most persistent critic of applying the MDGs to the country level. He argues that the goals were set on the basis of past global, not national trends and argue that goals should not be ‘adopted’ but ‘adapted’ to national contexts and redefined in the form of country specific targets (Vandemoortele 2007). In a marked departure from earlier goal setting efforts (Manning 2009), the texts of the 2000 Millennium Declaration (MD) and the 2001 implementation document the ‘Road Map,’ which introduced the MDGs, do not address how they should be implemented at the country level. The ‘Road Map’ states, “It is crucial that the millennium development goals become national goals and serve to increase the coherence and consistency of national policies and programmes.” (United Nations 2001, para 81) Earlier goal setting efforts were clear in stating

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that UN goals applied at global levels and needed to be adapted for integration into country strategies. For example, the Action Plan from the World Summit for Children is careful to specifically recommend adaptation of the goals to specific national conditions, and to develop national strategies (UNICEF 1999). The 1990 Jomtien Conference on education explicitly suggested that countries may wish to adapt the goals to their circumstances and introduced the goals with a nuanced discussion of the value of targets in mobilizing attention, while also suggesting that the targets needed to be adapted to changing conditions3. Adoption of global goals as national goals without adaptation runs counter to the principle of ‘national ownership’. National planning and programming processes are deeply entrenched institutional mechanisms with established procedures and a history of commitments and achievements. The MDG priorities – education, health, and poverty reduction and so on – have been part of national and local development strategies for decades and the MDGs themselves do not add new ideas. Instead, they introduce new planning targets. But how can national and local authorities take ownership of a ‘one size fits all’ agenda without relating it to this context? By and large, UN operations on the ground accepted adaptation as a reasonable and common sense approach (United Nations n.d.). Without adaptation, many of the MDG targets are biased against countries with the highest level of human poverty. One simple reason is because they have a reverse relationship to the starting point; for example the target to ‘halve’ the income poverty rate can mean cutting a poverty rate of 60% to 30%, or a rate of 10% to 5%. In the poorer countries, some of the goals imply achievement levels far beyond the historical record (Clemens 2007). 4 Further, the less resources and capacities countries have, the steeper the mountain they must climb to achieve the goals5. For the same reason, the universal MDG standards are under-ambitious in some countries; for example, most countries of Latin America and South East Asia had already achieved universal primary enrolment, and civil society activists have dubbed MDGs ‘Minimum Development Goals’ and criticized them for taking the poverty reduction agenda backwards. For all these reasons, the MDGs cannot be uncontroversially endorsed as sound economic policy. It would not be justified to accuse governments of negligence when they fail to integrate them into national planning and policy making. 1.2. MDGs as normative goals

3 Richard Manning, 2009, “Using Indicators to Encourage Development: Lessons from the Millennium Development

Goals”. Danish Institute of International Studies, DIIS Report no 2009/1. p.70. Available at: www.diis.dk/graphics/Publications/Reports2009/DIIS_Report_2009-1_Using_indicators_to_encourage_development.pdf. Last accessed August 29, 2009. 4 For a more detailed analysis of how many of the targets are biased against countries with low starting points, see

Easterly (2009) and Clemens (2007). 5 See more explanation in Vandemoortele 2009 and UNDP Human Development Report 2003.

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MDGs derive from the Millennium Declaration (MD). Like other UN Declarations, the MD is a normative document, setting out a consensus view of what the world should look like in the 21st century, and spelling out long term objectives and pressing priorities needing both individual and collective action of states. But it would be a mistake to conflate the MDGs with the MDs and consider the MDGs themselves to be normative goals. While the MD defined key objectives and included several quantitative targets, the MDGs structured these as operationally monitorable quantitative goals. Packaged with that name, they were introduced in the 2001 ‘Road Map’ document presented by the Secretary General to the General Assembly as the implementation plan for the MD. Moreover, the logic of the MDGs as the implementation plan was not to go back to consensus standards and principles adopted by the UN as reflected in key UN human rights instruments (Fukuda-Parr and Hulme 2011). The MDG construction was carried out by technocrats drawn from among the development economists and statisticians from development agencies (notably World Bank, OECD Development Division, UNDP) and their work was driven by considerations of data availability (Fukuda-Parr and Hulme 2011). Interpreted as normative goals - or as ends rather than the means of public policy agendas - the MDGs have given rise to a multitude of criticisms and controversies. As already mentioned at the outset of this paper, the MDGs are heavily criticized for falling short of human rights priorities contained in human rights instruments. The chief objections include: (i) omission of principles of equality and participation that is a cross cutting principle of all human rights; (ii) scope that does not reflect the full scope of human rights; (ii) targets that are below the level of standards set in human rights law. On the other hand, it is worth noting that the same critics (authors included) endorse the MD as consistent with human rights in the commitment to both values and standards (Saith 2007; Fukuda-Parr 2010; OHCHR 2009). The MD starts with a statement of commitment to equality, solidarity, dignity and freedom, while it categorically defines ending absolute poverty along with peace, democracy and human rights as the principal objectives for the world. The human rights community has not been the only source of criticism of the normative content of MDGs. Without referring to human rights instruments, philosopher Thomas Pogge (2004) has challenged the goal of halving poverty as a regressive step, setting much less ambitious targets than those set at previous global meetings. Others from the broader development community including academics and civil society advocates have also criticized the MDGs for omitting important development objectives. The most frequently criticized omissions are in areas of: (i) equity and inclusion in the benefits of development (Nelson 2007; Fukuda-Parr 2010); (ii) environmental sustainability and equity between generations with focus on the urgent issues of climate change; (iii) gender equality and empowerment of women in all its aspects (Sweetman 2005); (iv) rights of indigenous people (Tauli-Corpuz 2010); (iv) voice of developing countries in global economic policy fora; (v) quantitative goals for donors (UNDP 2003; OHCHR 2008; ); (vi) employment and decent work; and (vii) reproductive health6.

6 Targets for reproductive health and decent work were added in 2005

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The MDGs are also criticized for the process by which they were drawn up, without adequate consultation (Bissio 2003; OHCHR 2008). The MDGs are in fact a selected set of goals that were adopted by several of the UN development conferences held in the 1990s which are noted for having involved extensive consultation across the world involving civil society engagement (United Nations DESA 2007). But the selection of the few goals and targets to be included in the MD, and subsequently in the MDGs, was largely driven by a small group of technocrats in the UN. (Fukuda-Parr and Hulme 2011) For these reasons, the MDGs cannot be defended as a set of normative goals, particularly from the human rights perspective. It is the MD, not the MDGs, that sets normative goals. The confusion arises however because the MD includes quantitative goals and the MDGs reproduce and structure them with monitorable targets and indicators. But these numeric goals are not the full articulation of the norms in their full meaning including ethical values that underline priority social and political objectives for the world. The normative content of the MD is not just in those quantitative targets but the entire document which sets out ending poverty, together with securing peace, democracy and human rights as the normative objectives. The numeric goals are an important part of norms because they help define and communicate complex social objectives. While the concept of poverty is contested and ambiguous, understood in multiple ways7, the quantitative goals communicate these objectives in terms that ordinary people could understand and empathise with, that leaders from around the world could agree on. As Colin Bradford, one of the architects of the International Development Goals which were the antecedents of the MDGs commented, the quantitative goals were set by the OECD DAC because they needed a new rationale for international development aid that would be convincing to the ‘publics and parliaments’ of the rich countries (Fukuda-Parr and Hulme 2011). Goal setting has become popular in UN fora because they make complex normative objectives concrete, and communicate the urgency and magnitude of the challenge. They are effective in mobilizing support for important but neglected causes. As Manning notes8, the value of quantitative targets was clearly explained in the Agenda for Action of Jomtien Conference as it introduced quantitative, time bound global goals: ‘Time-bound targets convey a sense of urgency and serve as a reference against which indices of implementation and accomplishment can be compared... Observable and measurable targets assist in the objective evaluation of progress.’ Moreover, targets are deliberately set at high levels of ambition, to mobilize effort: ‘Targets need not be based solely on current trends and resources. Initial targets can reflect a realistic appraisal of the possibilities presented by the Declaration to mobilize additional 7Poverty is a complex concept that means different things to different people. Even amongst development

economists, there are controversies over its definition and measurement. The income based approach measures poverty on incomes beyond a minimum threshold level of consumption. The capability approach defines poverty as lack of basic capabilities that have multiple dimensions. The participatory approach argues that poverty is a lived experience that can only be pinned down in concrete terms by individuals and communities themselves. The social exclusion approach identifies marginalization from society as a critical aspect of poverty. 8 Manning2009 provides a detailed review of the rationale that drove goal setting and the methodologies used in

the 1990s. see particularly paras 143 - 150

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human, organizational, and financial capacities within a cooperative commitment to human development.’ (Quoted in Manning p.79) While goals help communicate complex social objectives, it would be a mistake to reverse engineer the definition and use the goals to define the social objective. The goals do not define poverty; poverty cannot be reduced to quantitative goals and indicators. Quantitative goals and indicators help observe some aspects of poverty.

1.3. MDGs as benchmarks of progress For all the reasons laid out in the previous sections, the MDGs cannot be defended as planning targets or as normative goals. They are best seen as benchmarks against which progress is made towards the achievement of normative goals. They emerged in 2001 for this purpose and the UN continues to represent them as such. For example, in 2005, then Secretary-General Kofi Anan’s report on the progress of the Millennium Declaration described the MDGs as “globally accepted benchmarks of broader progress.”(United Nations 2005 p.10) However, if they are to be used as benchmarks in monitoring, then country performance needs to be measured by the appropriate metric, and the analysis needs to be framed in a coherent understanding of who is to be held to account for what.

2. Measuring performance of governments related to normative commitments

2.1. Qualitative objectives and compliance measures

To evaluate the performance of governments in implementing such normative commitments is complex. Normative commitments are usually expressed in general terms that are hard to pin down into specific performance measures. Setting quantitative targets – such as MDGs – facilitates the task of monitoring progress. But such global goals set a single standard for the world but do not take account of the fact that countries around the world confront vastly different levels of constraints and possibilities to achieve global goals so performance measures must take account of these differences amongst countries. Consider the example of a normative commitment to achieve full primary school education. The implementation goal set in the MDGs, namely to achieve universal primary education by 2015, poses enormous challenges for countries that currently have a low enrolment rates and have limited resources. Consider Burkina Faso whose primary school enrolment ratio in 2001 was 36% and has a very limited resource base to invest in education, with a GDP per capita of only $1,120 (PPP) and with 61% of the population living on less than $1 a day. Contrast that with, for example, South Africa, where the enrolment ratio was already 89% and the resource base was much higher, with a GDP per capita of $11,290 (PPP), or with Nicaragua where the enrolment rate was 81% and per capita income $2,450. Global goals can be useful in monitoring progress, but when used to define ‘performance’ of national governments, and used to define ‘success or failure’ something more is needed.

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2.2. Progressive realization It is precisely to accommodate the problem of developing a uniform standard to judge performance in a world of diverse national conditions that international human rights law defines obligations of governments to fulfil economic and social rights as obligations of ‘progressive realization’. n Article 2.1 of The International Covenant of Economic, Social, and Cultural Rights (UN 1966)9 states (italics mine):

Each State Party to the present Covenant undertakes to take steps, individually and through international assistance and co-operation, especially economic and technical, to the maximum of its available resources, with a view to achieving progressively the full realization of the rights recognized in the present Covenant, by all appropriate means including particularly the adoption of legislative measures.

These obligations are further defined in the Maastricht Guidelines as “the obligation of conduct requires action reasonably calculated to realize the enjoyment of a particular right… *while] [t]he obligation of result requires States to achieve specific targets to satisfy a detailed substantive standard.” (UN 2000, para. 7). 2.3. Targets vs. benchmarks

MDG performance should then be measured by the pace of progress made towards reaching the goals rather than on the level achieved at the specified point of time. The pace of progress metric speaks directly to the commitments made by governments in adopting the 2000 MD. World leaders made commitments to do their utmost to end poverty, as stated in paras 11 and 12 of chapter IV (italics mine):

11. We will spare no effort to free our fellow men, women and children from the abject and dehumanizing conditions of extreme poverty, to which more than a billion of them are currently subjected. We are committed to making the right to development a reality for everyone and to freeing the entire human race from want. 12. We resolve therefore to create an environment – at the national and global levels alike – which is conducive to development and to the elimination of poverty.

9 United Nations (1966) International Covenant on Economic, Social and Cultural Rights (ICESCR). Adopted 16 Dec.

1966, General Assembly Res. 2200 (XXI), U.N. GAOR, 21st

Sess., Supp. No. 16, U.N. Doc. A/6316 (1966), 993 U.N.T.S. 3 (entered into force 3 Jan. 1976).

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If the measurement focuses on progress, then can we dispense with the targets? Targets are still useful because they provide a reference point against which progress can be measured. Benchmarking has evolved as an important element of human rights monitoring practice. They are used by the Committee on Economic, Social and Cultural Rights as well as by civil society groups in monitoring government performance, and in assessing their compliance with human rights norms and standards. The progress measure would need to consider then not only the rate of progress but the shortfall in reaching the target levels. Evaluating the level of achievement is also relevant and is complementary to monitoring the rate of progress. However, they serve different purposes. The progress measure is the appropriate measure of accountability with respect to government commitments. The level measure can be misleading and unjustified and cannot be used as the primary indicator of the degree to which national governments are in compliance with or in violation of their commitments made in the Millennium Declaration and the MDGs.

3. Methodologies for Measuring Performance: Consensus approach – ‘Achieving the Goals’

Since the MDGs were introduced in 2001, a proliferation of annual reports has been published by national governments and UN agencies to monitor progress at global, regional, and national levels. The UN system as a whole prepares an annual report, ‘The Millennium Development Goals Report’ (UN MDG Report), coordinated by the Statistical Division of the UN Department of Economic and Social Affairs with inputs from numerous organizations that ‘presents the most comprehensive global assessment of progress to date’ and is submitted to the annual UN General Assembly for debate on whether progress has been satisfactory (UN 2009). These and other reports prepared by other national and multinational organizations have been regularly disseminated widely for public debate on the progress being made to track progress in ending global poverty. The approach used in these national and international monitoring reports has been to ask ‘will the MDG targets be achieved by 2015?’ The standard method used has been to assess current trends in the indicators in relation to the defined target. The 1990 levels are compared to the most recent levels to determine if improvement has occurred, and extrapolations of 1990 to present trends are used to determine if the world or a specific region or country is likely to meet the mark by 2015. On this basis, performance is evaluated as being ‘on track’ or not. For example, the UN Monitor10 applies this method at the country level to assess performance and classifies countries in four categories: (i) achieved; (ii) on track, very likely to be achieved; (iii) possible to achieve if some changes are made; and (iv) off track.

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The UN’s monitoring information system that tracks progress by country, region and world. www.mdgmonitor.org/country_progress.cfm?c=AFG&cd=4 (accessed Dec 21, 2010)

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This method focuses on the level of achievement. But progress in ending poverty depends on both the absolute level and rate of progress; these monitoring reports ignore the rate of progress. It categorizes country performance as successful when they are ‘on track’ to achieving the goals, and at least by implication, as unsatisfactory when the trend is ‘off track’ or anything less than ‘on track. This method treats the goals as hard planning targets to be implemented that should be the objective of national and global policy efforts. The UN MDG Report (UN 2009) analyses trends from 1990 or in some cases 2000 but does not compare pre-1990 trends with post-1990 trends, or 1990-2000 trends with post-2000 trends. For example, the report notes that total deforestation was lower from 2000-2005 than it was from 1990-2000, but includes only average annual net total net loss for each period, with no indication of the year to year trend during these periods, or whether there was a shift in the annual change beginning in the second period (United Nations 2009, p.43). The report does not acknowledge cases for which the targets are unlikely to be met, but there has nonetheless been progress. For example, the conclusion is that school enrolment rates have been improving but the universal primary education goal for 2015 is unlikely to be met at the current pace of progress. This analysis is based on a comparison between worldwide and regional 1999 and 2006 data (United Nations 2009, p.14). There is no discussion of how this improvement compares to historical trends, or whether the rate of improvement has been changing during the most recent period. The report indicates that the goal is not likely to be met, but not whether the MDG declaration has had a positive effect on enrolment. The numerous other monitoring reports from international agencies and national governments apply the same methodological approach. Other major international institutions use the same approach to measuring progress. The World Bank’s 2011 Global Monitoring Report is structured around whether the goals at the country, regional, or global levels are likely to be achieved by 2015 depending on the distance to the target. Countries are categorized by assessment of whether the country trends are: ‘on target’, ‘close to the target’, or ‘far from the target’ (World Bank 2011). In earlier years, the classification was similar to the UN Monitor: ‘achieved’, ‘on track’ to be achieved, ‘off track’, or ‘seriously off track’. The analysis shows graphically the proportion of countries in these categories, (World Bank 2009, p.17) and the required global trend to meet the target in contrast to the current trend (p.16). It goes on to discuss the possibilities and constraints to goal achievement. While the goal for halving income poverty is considered “in reach” (p.13), and the goals for gender parity in primary and secondary education, and for access to safe water, are ‘on track’, the goals on child mortality are unlikely to be met. By implication, success or failure is judged by the hard line of the level of achievement, in black and white standard. Assessment of country performance is only shaded by the relative distance from that level. No consideration is given to the pace of progress. The Bank report does not ask whether there has been a post-Millennium declaration change in global trends regarding any of these indicators. In an annex entitled “Monitoring the MDGs” the 2009 report contains graphs with trend lines from 1990-2006 for selected indicators alongside its 1990 and 2006 absolute level comparisons. However, even here, the graph is only used to compare the actual trend with the trend line that

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would be required to meet the goal (p.203-209). The focus remains on whether the goal will be met by 2015, and the question of changes in trend in relation to the MDGs remains unasked. The fixation on the goals as economic planning targets is clearly illustrated when, after providing some genuinely disheartening statistics regarding hunger, school enrolment, and other issues, the report makes the seemingly tautological observation that these are “numbers that would be far lower if the world were on track on the MDGs” (p.4). The Asian Development Bank’s (ADB and others) 2007 “The Millennium Development Goals Progress in Asia and the Pacific” follows the same ‘Achieving the Targets’ approach. The report aims at “identifying which countries are on or off track for specific MDG targets” (ADB 2007 p.3) The report divides countries into four categories, “early achiever”-already achieved 2015 target, “on track”-expected to meet target, “off track-slow”-expected to meet the target, but not by the 2015 deadline, and “off track-no progress, regressing.” Country performance is based on the trend since 1990 (p.3). If the goals are to be met, what is necessary “for many countries is to break away from the predicted path.” (p.3) Whether the “early achievers” or “on track” countries have broken away from previous paths during the 1990-2007 period is once again left unexamined. The African Development Bank’s “Assessing Progress in Africa toward the Millennium Development Goals” similarly examines the relative success of the goals almost exclusively by comparing absolute circa 1990 levels with absolute present levels for individual countries. In some cases, 1990-2005/6 trends are the method of choice, but a comparison of pre and post Millennium Declaration trends is not attempted (AfDB 2009).

4. Alternative approach – ‘Pace of Progress’ In another paper (2010) we have proposed a methodology for assessing whether countries made faster progress since their 2000 MD commitments. Our paper presented the results of an empirical analysis of national progress trends since 1990 for MDG 22 indicators for all countries with available data. (For the calculated results of ten major indicators, see appendix.) Our methodology is relatively simple and compares rate of change between the periods before and after the adoption of the MDGs to determine if since the adoption of MDGs, progress to achieving the MDGs has become faster, reflected greater effort on the part of government. The calculations were made using the following formula for each country i, for each indicator x, and each time period post MD (A) and prior to MD (B):

[ ]

[ ]

Where:

( ) ( )

This formula was used to calculate and compare the average rates of change for each period,

15

for each country and indicator, as described above. This formula follows the same approach used by the United Nations Development Programme and the ADB (2007) in their joint report on the MDGs progress in Asia to estimate trends for increasing indicators and extrapolating those trends linearly into the future to assess if the goals are likely to be met. Our calculations show vastly different assessments of country performance when compared with the ‘Achieving the Target’ method. We compared our results with the UN’s MDG monitor which extrapolates current trends to 2015, country by country, to assess the feasibility of achieving the goals and to give a rating between ‘off track’ to ‘achieved,’ as explained earlier. Our calculations assess the annual rate of change since the MD, and whether it has been faster than the historical record. Overall, the best performing countries by the two metrics did not overlap. The results of the ‘Making progress’ metric do not show statistical correlation with the results of the ‘Achieving the Targets’ assessment. Comparisons at the country level show some stark contrasts. We looked for best performing countries which showed faster progress across a number of indicators, which could reflect general commitment to make effort across the 8 goals as shown in table 1. Many of these countries are not succeeding according to the MDG monitor – they do not receive the endorsement of being ‘on track’. To illustrate, consider Ethiopia and Senegal. Both are among the top 15 countries in showing evidence of faster progress post MD on a range of indicators; Ethiopia on 16 out of 22 indicators analysed, and Senegal on 12. While Ethiopia does receive an “on track” score for several of the goals from the UN monitor, and is mentioned positively in relation to some indicators in the Africa Development Report, it is not listed as “on track” for Goal number 1, concerning poverty and extreme hunger. However, four of the sixteen indicators for which we found improved rates for Ethiopia were related to Goal 1. This group includes the indicator of population below $1 a day, arguably the indicator most closely identified with Goal 1. In the case of Senegal, the UN monitor lists it as “on track” for only Goal 4, related to the reduction of child mortality, and there are very few positive mentions of Senegal in the African Development Bank Report studied. We found improvements in a dozen indicators for Senegal, related to almost all of the goals, including some of the most important indicators such as population below $1 a day, total primary school enrolment, and access to improved access to sanitation and water sources. For the goals related to all of these indicators, Senegal is not considered “on track.”

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Table 1. Top Countries by the number of Indicators on which they have evidence of improved rates

Country Region Number of Indicators for which improved rates of change were calculated in second period (22 indicators studied)

Nigeria Sub-Saharan Africa 16

Ethiopia Sub-Saharan Africa 16

Burkina Faso Sub-Saharan Africa 15

Uganda Sub-Saharan Africa 15

Rwanda Sub-Saharan Africa 14

Zambia Sub-Saharan Africa 13

Pakistan South Asia 13

Bangladesh South Asia 13

Madagascar Sub-Saharan Africa 12

Cambodia Southeast Asia 12

China East Asia 12

Central African Republic Sub-Saharan Africa 12

Colombia Latin America and Caribbean

12

Senegal Sub-Saharan Africa 12

Source: Authors’ calculations using data from Millennium Development Goals Indicators Website, UN Statistics Division http://unstats.un.org/unsd/mdg/Data.aspx

We also considered which countries were making fastest improvement post MD commitments across the 22 indicators (see Table 2). For every indicator studied, we calculated the largest improvements in rates between the two periods, and then tallied which countries were among the best improvers for the most indicators. Ethiopia is among the top 15 in 10 indicators and Senegal in 4. Ethiopia is among the top improvers for two indicators related to Goal 1, again including Population below $1 despite, again, not being listed as “on track” for that goal. Senegal is again calculated as a top improver for several indicators related to goals for which it is not considered “on track.” This paradox is not difficult to explain. They have low starting points and have a very long distance to go to achieve the targets set. For example, in 1995, the first year included in our study for Ethiopia, its poverty rate was 60.5% while for Senegal’s earliest data in the sample, 1991, the poverty rate was 65.8%. The two countries have been cutting poverty rates since these dates by an annual average of 2.15 percentage points and 2.3 percentage points, respectively. Yet they will not achieve the goal of cutting this rate by half by 2015 without accelerating further. These countries’ progress is much better than many which are in the ‘on track’ category.

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Table 2: Top countries by number of indicators for which country scores among top 15

biggest improvements from first to second period. Country Region Number of Indicators for which country

has a top 15 biggest improvement from first to second period (22 indicators studied)

Ethiopia Sub-Saharan Africa 10

Rwanda Sub-Saharan Africa 10

Central African Republic Sub-Saharan Africa 9

Burkina Faso Sub-Saharan Africa 8

Zambia Sub-Saharan Africa 8

Cambodia Southeast Asia 6

Tajikistan Central Asia 6

Tanzania Sub-Saharan Africa 6

Lesotho Sub-Saharan Africa 6

Madagascar Sub-Saharan Africa 6

Mozambique Sub-Saharan Africa 5

Malawi Sub-Saharan Africa 5

Congo Sub-Saharan Africa 5

Chad Sub-Saharan Africa 5

Swaziland Sub-Saharan Africa 5

Botswana Sub-Saharan Africa 5

Nigeria Sub-Saharan Africa 5

Iraq West Asia 4

Senegal Sub-Saharan Africa 4

Nepal South Asia 4


Consider now countries which do poorly by the Pace of Progress measure. Some of these are categorized as ‘on track’ and therefore a success in development and poverty reduction, and in compliance with their MD/MDG commitments. To illustrate, consider the record of select countries with respect to reducing child mortality. Comparing the annual rate of reduction in the post MD years compared with the prior decade, Bahrain, Chile, Libya and Mexico did not improve on their progress and in some cases slowed down. Yet they are ‘on track’ to achieving the goals and are considered to be successful in poverty reduction. The conclusion is that they are complying with their commitments. In contrast, Gambia, Lesotho, and Malawi are not likely to achieve the targets, yet have substantially improved their pace of progress. It would be grossly unjustified to label Bahrain, Chile, Mexico and Libya a ‘success’ and honouring their MD/MDG commitments while accusing Gambia, Lesotho, and Malawi of failing to do so.

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Table 3. Different conclusions on under five mortality based on different measurement metrics, some examples

Country Under Five Mortality 1990

Under Five Mortality 2000

Annual Change1990-2000

Under Five Mortality 2007

Annual Change 2000-2007

Post-2000 Change in Speed of Progress

Annual Change, Entire Period

UN MDG Monitor Classification

Libya 41 22 -1.9 18 -0.57 Decline -1.35 “On Track”

Mexico 46 29 -1.7 21 -1.14 Decline -1.47 “Achieved”

Malawi 209 170 -3.9 111 -8.43 Improvement -5.76 “Possible to Achieve with Changes”

Gambia 153 131 -2.2 109 -3.14 Improvement -2.59 “Off Track”

Lesotho 102 107 +0.5 84 -3.29 Improvement -1.06 “Off Track”

Nigeria 230 207 -2.3 189 -2.57 Improvement -2.41 “Off Track”

Togo 150 122 -2.8 100 -3.14 Improvement -2.94 “Off Track”

Tanzania 157 143 -1.4 116 -3.86 Improvement -2.41 “Possible to Achieve with Changes”


What is striking about these results is the favourable performance of the countries in Sub-Saharan Africa. By these metrics, these countries are not failures, unlike by the standard metric, achieving the targets. It should be noted that for many of these indicators, progress may be non-linear. It is possible that as the target levels become closer, progress becomes more difficult. Since our calculations were completed, Hailu and Tsukada (2011) introduced a methodology that is conceptually similar to ours (focusing on rate of progress) but uses a different formula that assumes non-linear rate of progress while our formula assumes linear progress. Their results show similar findings to ours; many countries are likely to ‘fail’ to achieve the targets by 2015 yet are making faster progress.

5. Human Rights, MDGs and international development In its 2005 meeting, Social Watch, an international network of citizen’s organizations working on issues of poverty and social justice, adopted a declaration that describes the MDGs as “minimum benchmarks” of Human Rights entitlements, and argues that the MDGs should be “less about meeting targets but more about honouring human rights obligations.” (Social Watch

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2005). Some might argue against this proposition on the grounds that the MDGs fall short of human rights standards and do not reflect core human rights principles. But if the MDGs were merely benchmarks for progress, to be used as tools in analysis of compliance with obligations of progressive realization and duties of conduct, there would be no contradiction between MDGs targets and human rights principles. While the MDGs do not offer a comprehensive set of benchmarks for all rights, they could be useful in efforts to make human rights a reality. They could be accepted as benchmarks for evaluating progress in the fulfilment of some economic and social rights, and can be used for judging country performance against the obligations of progressive realization. While the time bound targets for 2015 might fall short of full realization of rights, the principle of progressive realization recognizes that at any given point of time, full realization would not be achieved, particularly in developing countries. The ‘progressive realization” provision is an important conceptual correction to much of development economics analysis that ignores large variation among countries in starting points and capacity in analysing country performance in development progress and poverty reduction. The use of ‘achieving the target’ is an illustration of this bias in conventional development economics analysis. Countries across the world face hugely different levels of deprivation in the population and capacity. Inherent in the idea of progressive realization is that a government’s ability to achieve realization of rights depends on the level of resources (financial and other) available in the country. The enjoyment of the right to highest attainable standard of health, for example, cannot be achieved overnight, as facilities need to be built, personnel trained, and policy incentives for business and households put in place and so on, so that people have access to healthcare. These arrangements require financial resources which may be beyond what governments and households can mobilize. Consequently, the performance of states with regard to progressively realizing economic and social rights cannot be judged on the basis of outcomes – the level of enjoyment of rights by people -- alone. State accountability must focus on rate of progress in improving that level of enjoyment. Measuring the pace of progress, and examining whether faster progress is being made, would provide good evidence of whether the state is taking such action. Such outcome evidence would be more objective than examining policy since it is difficult to know what would count as good policy since policy impact would depend on the specific social and economic conditions prevailing in a country at a given point of time, and there are no ‘one size fits all’ policy prescriptions that can be objectively justified. What matters is the effectiveness of policy, not taking policy measures which may be poorly designed and ineffective either by deliberate design or by lack of information. Assessing the pace of progress, especially improvement in the pace of progress could therefore serve as a good proxy measure of state effort to monitor compliance with obligations of conduct.

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Table 4. Some possible linkages between the targets and human rights

Goal 1. Eradicate extreme poverty and hunger

Target 1.A. Halve, between 1990 and 2015, the proportion of people whose income is less than $1 a day

Right to adequate standard of living

Target 1.B Achieve full and productive employment and decent work for all, including women and young people

Right to work

Target 1.C Halve, between 1990 and 2015, the proportion of people who suffer from hunger

Right to food

Goal 2. Achieve universal primary education

Target 2.A Ensure that, by 2015, all children everywhere, boys and girls alike, will be able to complete a full course of primary schooling

Right to education

Goal 3. Promote gender equality and empower women

Target 3.A Eliminate gender disparity in primary and secondary education, preferably by 2005, and in all levels of education no later than 2015

Women’s rights to equality

Goal 4. Reduce child mortality

Target 4.A Reduce by two thirds, between 1990 and 2015, the under-five mortality rate

Right to life

Goal 5. Improve maternal health

Target 5.A Reduce by three quarters, between 1990 and 2015, the maternal mortality ratio

Women’s right to life and health

Target 5.B Achieve, by 2015, universal access to reproductive health Women’s right to life and health

Goal 6. Combat HIV/AIDS, malaria and other diseases

Target 6.A Have halted by 2015 and begun to reverse the spread of HIV/AIDS Right to Health

Target 6.B Achieve, by 2010, universal access to treatment for HIV/AIDS for all those who need it

Right to Health

Target 6.C Have halted by 2015 and begun to reverse the incidence of malaria and other major diseases

Right to Health

Goal 7. Ensure environmental sustainability

Target 7.A Integrate the principles of sustainable development into country policies and programmes and reverse the loss of environmental resources

Right to environmental health

Target 7.B Reduce biodiversity loss, achieving, by 2010, a significant reduction in the rate of loss

Right to environmental health

Target 7.C Halve, by 2015, the proportion of people without sustainable access to safe drinking water and basic sanitation

Right to water and sanitation

Target 7.D By 2020 to have achieved a significant improvement in the lives of at least 100 million slum dwellers

Right to adequate housing

Goal 8. Develop a global partnership for development

Targets 8.A-8.D cover aid, trade, debt, landlocked and small island States Right to development. Economic, social and cultural rights

Target 8.E In cooperation with pharmaceutical companies, provide access to affordable essential drugs in developing countries

Right to health

Target 8.F In cooperation with the private sector, make available the benefits of new technologies, especially information and communications

Economic, social and cultural rights

11

Source: Reproduced from OHCHR (2008)

11

Targets 8E and 8Fcould also be related to the right to benefit from scientific progress.

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The MDGs do not reflect the full range of human rights and monitoring their progress does not address the full range of state obligations. These gaps must be addressed by reformulation of the MDGs, not by the methodology of measuring progress. While recognizing these gaps, the MDGs on the current list do overlap with several economic and social rights articulated in the Universal Declaration of Human Rights, the International Covenant on Economic, Social Cultural Rights and other legal instruments (OHCHR 2008) Table 4 above illustrates some of these overlaps as seen by the OHCHR.

6. Conclusions: MDGs as benchmarks for Millennium Declaration Commitments The MDGs are a powerful tool because they go beyond statements of general objectives to making explicit, concrete, time bound, quantitative targets by which progress can be monitored. They make possible the monitoring of government performance against globally agreed standards of poverty reduction. They set up a system for generating objective and empirical evidence for holding states accountable to the commitments made. But to do this requires the right measurement tool. Although the MDGs grew out of a normative process and reflect a global commitment to end poverty, the UN and other agencies monitor them as if they were planning targets, where success or failure depends on achieving the targets by 2015. This is not a justified basis for holding governments to account since they are benchmarks for assessing progress. Governments committed to make effort, and thus to achieve the MDGs progressively, over time. The more appropriate criterion of success or failure is whether adequate progress is being made, and should be measured by the pace of progress. The conventional measure that assesses the level of achievement against the target is still a relevant question. But it should not be used to assess success or failure since it is both conceptually inappropriate and biased against countries with low starting points. The findings of the statistical analysis of performance using the pace of progress method in this paper are quite different from the conventional monitors regarding which countries are ‘succeeding’ and which are ‘failing’. Ironically, the UN does see the MDGs as benchmarks of progress, and its development agencies such as UNICEF and UNDP encourage national adaptation of goals, emphasizing the importance of national ownership as a key factor in successful MDG implementation. Yet, as we have documented, the organization is systematically contradicting itself by judging success or failure by whether each country is achieving the level of goals set globally. While this paper has challenged the conventional methodology used in assessing MDG implementation, it was motivated by two broader purposes. First, we believe that the MDGs can be a powerful tool for promoting the human rights agenda if it is utilized according to human rights norms and principles. Monitoring implementation is an important aspect of that effort. Human rights and development communities can work more effectively together, making use of complementary concepts and efforts to pursue the shared objectives of improving human lives and security, human freedom, and dignity. Secondly, we believe that

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human rights theory and practice can contribute more fundamentally to the practice of development. The concepts and methods of human rights analysis can contribute to strengthening monitoring of MDG implementation. By unpacking the concept of MDGs, this paper challenges the monitoring method being used on the grounds of both normative principles and development economics. By applying the human rights concept of progressive realization, obligations of conduct and result, and benchmarking in monitoring performance, a more appropriate measure of progress can be developed to provide empirical evidence against which government performance can be judged. In this way, this paper aims to illustrate the way that the field of human rights can contribute to policy analysis in the development field.

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Appendix Table 1 Population Below $1 per day, (PPP), Percentage

Country Annual Change, Year 1-2

Annual Change, Year 2-3

Annual Change, entire period

Albania 0.00 0.00 0.00

Argentina 0.79 -1.80 0.19

Azerbaijan -1.55 -1.08 -1.36

Bangladesh -1.13 -1.64 -1.32

Belarus 0.00 0.00 0.00

Bolivia 1.71 -1.07 1.11

Brazil -0.39 -1.30 -0.61

Chile -0.18 0.00 -0.14

China -2.65 -4.17 -2.95

Colombia 0.53 0.20 0.44

Costa Rica -0.28 -1.60 -0.45

Croatia 0.00 0.00 0.00

Dominican Republic 0.14 -0.55 0.03

Ecuador -0.60 -1.45 -0.86

Egypt -0.28 0.00 -0.18

El Salvador 0.20 -1.65 -0.17

Estonia 0.00 0.00 0.00

Ethiopia -0.98 -3.32 -2.15

Georgia 1.77 -0.57 0.99

Guatemala 0.30 -1.30 -0.50

Honduras -1.95 0.03 -1.58

Hungary 0.00 0.00 0.00

Jamaica 0.00 0.00 0.00

Jordan -0.07 0.00 -0.06

Kyrgyzstan 1.71 -6.10 0.29

Latvia 0.00 0.00 0.00

Lithuania -0.17 0.00 -0.14

Madagascar 0.48 -2.13 -0.39

Mali -3.56 -1.96 -2.89

Mexico -0.08 -0.43 -0.18

Mongolia -0.47 2.30 0.36

Morocco 0.38 -0.63 0.00

Nicaragua -1.64 -0.90 -1.39

Pakistan -2.62 -4.43 -3.01

Panama -0.61 -0.33 -0.53

Paraguay 1.03 -2.14 0.04

Peru 0.96 -1.18 0.39

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Philippines -0.79 0.20 -0.58

Poland -0.24 0.00 -0.18

Republic of Moldova

0.01 -4.50 -0.74

Romania 0.09 -0.30 0.00

Russian Federation -0.09 0.00 -0.07

Senegal -2.16 -2.68 -2.31

Slovenia 0.00 0.00 0.00

Thailand -0.35 0.00 -0.29

Turkey -0.01 0.23 0.05

Uganda -1.26 -1.97 -1.42

Ukraine 0.00 0.00 0.00

Uruguay 0.00 0.00 0.00

Venezuela 1.58 -4.97 0.07

Viet Nam -2.62 -4.65 -3.25

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Appendix Table 2 Children Under 5 Moderately or Severely Underweight, Percentage



Annual Change Entire Period

Algeria 0.12 -1.68 -0.39

Azerbaijan -0.66 0.54 -0.06

Bangladesh -2.46 -0.20 -1.41

Belize 0.11 -0.30 -0.01

Benin -1.26 -0.06 -0.66

Bolivia -0.91 -0.32 -0.70

Burkina Faso 0.50 -1.50 -0.07

Cambodia 0.77 -1.92 -0.35

Central African Republic -0.60 0.70 0.11

Chad -3.57 2.15 -0.30

Chile -0.09 0.00 -0.07

China -0.94 -0.30 -0.81

Colombia -0.34 0.06 -0.14

Comoros 0.77 -0.13 0.49

Cuba -1.35 0.02 -0.59

Democratic Republic of the Congo

-0.55 0.05 -0.25

Djibouti -0.42 3.10 0.62

Dominican Republic -0.46 -0.22 -0.39

Egypt -0.14 -0.22 -0.16

El Salvador -0.09 -0.34 -0.17

Ethiopia -0.05 -1.76 -0.71

Gambia -2.30 0.53 -0.60

Ghana -0.53 -1.47 -0.75

Guyana -0.67 -0.20 -0.45

Haiti -0.95 0.82 -0.29

Honduras -0.24 -1.04 -0.58

Iraq 0.44 -1.38 -0.29

Jamaica -0.50 0.20 -0.38

Kenya -0.24 0.33 -0.11

Lao People's Democratic Republic

-0.57 -0.48 -0.53

Lesotho 0.26 0.48 0.33

Madagascar -0.75 2.20 0.23

Malawi -0.53 -0.35 -0.48

Malaysia -1.27 -1.25 -1.27

Mali -1.36 -0.30 -0.83

Mauritania -1.58 -0.16 -0.99

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Mongolia 0.05 -1.28 -0.46

Mozambique -0.41 -1.24 -0.73

Namibia -0.28 -0.50 -0.37

Nepal -0.07 -0.66 -0.34

Nicaragua -0.29 -0.54 -0.38

Niger -0.38 0.40 0.01

Nigeria -0.54 -0.32 -0.48

Occupied Palestinian Territory -0.15 -0.10 -0.13

Paraguay 0.08 -0.10 0.03

Peru -0.46 -0.28 -0.39

Rwanda -0.61 -0.30 -0.48

Senegal 0.14 -1.08 -0.33

Sudan 0.90 -1.62 -0.26

Syrian Arab Republic -0.74 0.47 -0.18

Tunisia -0.94 -0.15 -0.51

Turkey -0.65 -0.22 -0.51

Uganda -0.45 -0.48 -0.46

Uzbekistan -1.82 -0.70 -1.37

Venezuela -0.33 0.20 -0.18

Viet Nam -1.83 -2.73 -2.06

Zambia -0.14 -0.74 -0.32

Zimbabwe 0.19 -0.30 0.10

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Appendix Table 3: Total Net Enrolment Ratio in Primary Education, Both Sexes




Algeria 0.71 -0.60 0.38

Anguilla -3.40 0.93 -0.80

Argentina 0.02 -0.17 -0.06

Armenia -3.90 2.23 0.18

Aruba -0.60 0.88 0.14

Australia -0.30 0.25 -0.16

Azerbaijan -0.03 1.75 0.41

Bahamas -0.47 1.63 0.06

Bahrain -0.07 0.30 -0.01

Barbados 0.80 0.77 0.79

Belarus 0.61 -0.27 0.39

Belgium 0.18 -0.20 0.09

Belize 0.36 0.05 0.28

Benin 3.24 0.93 2.78

Bhutan 2.85 3.56 3.36

Bolivia 0.22 -0.45 -0.11

Botswana -0.75 -1.10 -0.80

Brazil 0.51 0.50 0.51

British Virgin Islands -0.97 0.67 -0.15

Bulgaria 0.63 0.05 0.48

Burkina Faso 1.06 3.85 1.76

Burundi 0.05 6.88 1.76

Cambodia 1.05 0.54 0.89

Cape Verde 0.26 -2.38 -0.40

Cayman Islands -1.55 -4.17 -3.12

China, Hong Kong Special Administrative Region

0.00 -1.30 -0.65

China, Macao Special Administrative Region

0.50 1.43 0.73

Colombia 2.08 -0.30 1.34

Cook Islands -7.50 -1.43 -2.19

Croatia 0.67 1.48 0.88

Cuba 0.17 -0.17 0.08

Cyprus 0.78 0.18 0.63

Denmark 0.08 -0.98 -0.18

Djibouti 0.27 2.53 0.83

Dominica 0.25 -5.23 -2.10

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Ecuador 0.01 0.00 0.01

Egypt 0.51 0.22 0.44

El Salvador 1.55 -0.10 0.45

Equatorial Guinea -0.60 -5.03 -1.71

Eritrea 2.78 -1.25 1.77

Estonia -0.20 -0.07 -0.17

Ethiopia 1.93 6.68 3.11

Fiji -0.38 -0.20 -0.35

Finland 0.11 -0.77 -0.11

France -0.03 -0.10 -0.04

Gambia 2.17 0.05 1.64

Germany 1.08 0.65 0.97

Ghana 0.68 2.55 1.15

Greece 0.13 0.00 0.10

Grenada 3.70 -5.08 -1.31

Guatemala 2.08 1.25 1.66

Guinea 3.03 2.75 2.96

Honduras 0.14 0.82 0.39

Hungary 0.43 -0.85 0.11

Iceland -0.04 -0.40 -0.13

India 1.20 1.93 1.57

Indonesia 0.18 -0.20 0.08

Iran (Islamic Republic of) -0.44 2.20 0.09

Iraq -0.41 -0.25 -0.39

Ireland 0.36 0.32 0.35

Israel 0.51 -0.22 0.33

Italy -0.03 -0.05 -0.03

Jamaica -0.63 -0.70 -0.65

Japan 0.03 -0.03 0.01

Jordan -0.03 -1.13 -0.31

Kazakhstan 1.01 0.05 0.77

Kenya 2.88 2.88 2.88

Korea, Republic of -0.23 0.50 -0.08

Kuwait 3.44 0.95 2.82

Kyrgyzstan 0.03 -0.07 0.01

Lao People's Democratic Republic 1.63 1.23 1.53

Lebanon 1.53 -0.65 0.98

29




Lesotho 0.50 -1.93 0.01

Lithuania -0.92 -0.20 -0.56

Luxembourg -0.25 0.45 0.10

Madagascar 1.04 5.53 2.16

Malaysia -0.35 0.40 -0.03

Maldives 0.00 -0.20 -0.13

Mali 2.06 2.28 2.11

Malta -0.15 -1.95 -0.41

Marshall Islands 1.80 -6.30 -3.60

Mauritania 2.79 2.50 2.72

Mauritius 0.35 -0.05 0.25

Mexico 0.10 -0.15 0.04

Mongolia -1.05 3.63 0.12

Morocco 2.48 0.55 2.00

Mozambique 1.40 4.78 2.30

Namibia 1.10 0.47 0.79

Nepal 3.00 -0.63 1.19

Netherlands 0.28 -0.03 0.21

New Zealand 0.05 -0.03 0.03

Nicaragua 1.90 1.33 1.76

Niger 1.02 1.80 1.21

Nigeria 0.81 0.90 0.83

Norway -0.02 -0.25 -0.08


Oman 1.00 -1.80 0.30

Pakistan 0.65 2.37 1.68

Panama 0.52 0.00 0.26

Peru -0.07 -0.13 -0.10

Philippines -0.22 -0.50 -0.29

Poland 0.12 -0.63 -0.07

Qatar 0.37 0.40 0.38

Republic of Moldova 0.89 -1.65 0.26

Romania 0.97 0.95 0.96

Rwanda 0.64 4.60 1.63

Saint Lucia 0.06 0.48 0.16

Saint Vincent and the Grenadines 0.47 0.18 0.30

Sao Tome and Principe 2.90 0.02 1.46

Senegal 1.33 2.40 1.60

30




Slovenia -0.23 0.38 -0.08

South Africa 0.24 -0.90 -0.04

Spain 0.33 0.00 0.25

Suriname 0.99 0.05 0.76

Swaziland 0.10 3.08 0.84

Sweden -0.02 -1.38 -0.36

Switzerland 0.05 -0.82 -0.17

Tajikistan 1.66 0.23 1.30

The former Yugoslav Republic of Macedonia

-0.15 -0.85 -0.33

Togo 1.23 0.00 0.92

Tonga 3.95 0.60 1.72

Trinidad and Tobago 0.01 1.48 0.38

Tunisia 0.32 -0.38 0.14

Turkey -0.09 0.75 0.12

Ukraine 0.66 0.25 0.56

United Arab Emirates -0.92 2.60 -0.04

United Kingdom 0.50 -0.38 0.28

United Republic of Tanzania 2.63 4.93 3.09

United States -0.30 -0.15 -0.26

Vanuatu 1.18 -2.23 -0.53

Venezuela 0.37 0.20 0.32

Yemen 1.93 1.75 1.91

Zambia 0.83 4.94 3.40

Zimbabwe -0.27 2.00 0.70

31

Appendix Table 4: Gender Parity Index in Primary Level Enrolment Country Annual Change,

Year 1-2 Annual Change,

Year 2-3 Annual Change, entire

period

Afghanistan 0.0017 0.0150 0.0050

Algeria 0.0067 0.0025 0.0056

Anguilla -0.0100 -0.0067 -0.0083

Argentina 0.0000 -0.0033 -0.0014

Armenia 0.0050 0.0025 0.0033

Aruba -0.0125 0.0075 -0.0025

Australia 0.0008 0.0000 0.0006

Austria -0.0008 0.0000 -0.0006

Azerbaijan -0.0017 0.0050 0.0000

Bahamas -0.0017 -0.0025 -0.0019

Bahrain 0.0008 -0.0033 0.0000

Barbados -0.0008 0.0025 0.0000

Belarus 0.0025 0.0000 0.0019

Belgium -0.0017 0.0025 -0.0006

Belize 0.0017 0.0025 0.0019

Benin 0.0192 0.0300 0.0213

Bermuda 0.0050 -0.0500 -0.0280

Bhutan 0.0233 0.0150 0.0186

Bolivia 0.0025 0.0025 0.0025

Botswana -0.0067 0.0000 -0.0057

Brazil 0.0025 -0.0050 -0.0012

British Virgin Islands -0.0075 0.0050 -0.0013

Brunei Darussalam 0.0058 -0.0050 0.0031

Bulgaria 0.0000 0.0025 0.0006

Burkina Faso 0.0092 0.0225 0.0125

Burundi -0.0025 0.0300 0.0056

Cambodia 0.0083 0.0050 0.0075

Cameroon -0.0008 0.0025 0.0000

Canada 0.0018 -0.0025 0.0007

Cape Verde 0.0008 -0.0025 0.0000

Cayman Islands 0.0050 -0.0300 -0.0160

Central African Republic 0.0042 0.0025 0.0038

Chad 0.0175 0.0100 0.0156

Chile -0.0008 -0.0050 -0.0019

China 0.0058 -0.0025 0.0038


-0.0050 0.0000 -0.0043

32





-0.0025 -0.0025 -0.0025

Colombia -0.0025 0.0000 -0.0019

Comoros 0.0075 0.0300 0.0107

Congo 0.0025 0.0000 0.0019

Cook Islands 0.0075 -0.0025 0.0025

Costa Rica -0.0008 0.0025 0.0000

Cote d'Ivoire 0.0067 0.0000 0.0050

Croatia 0.0025 0.0025 0.0025

Cuba -0.0008 0.0050 0.0006

Cyprus 0.0000 -0.0025 -0.0006

Czech Republic -0.0017 0.0025 -0.0006

Democratic Republic of the Congo 0.0027 0.0060 0.0038

Denmark 0.0000 0.0000 0.0000

Djibouti 0.0050 0.0200 0.0088

Dominica 0.0100 0.0100 0.0100

Dominican Republic 0.0075 -0.0175 -0.0050

Ecuador 0.0008 0.0000 0.0006

Egypt 0.0100 0.0000 0.0075

El Salvador -0.0025 0.0100 0.0006

Equatorial Guinea 0.0008 -0.0050 -0.0006

Eritrea -0.0125 0.0075 -0.0075

Estonia -0.0008 0.0075 0.0013

Ethiopia 0.0058 0.0375 0.0138

Fiji -0.0008 -0.0050 -0.0019

Finland 0.0000 0.0025 0.0006

France 0.0000 0.0000 0.0000

Gambia 0.0242 0.0150 0.0219

Georgia 0.0017 -0.0125 -0.0019

Germany -0.0008 0.0000 -0.0006

Ghana 0.0108 0.0025 0.0088

Greece 0.0000 0.0025 0.0006

Grenada 0.0117 -0.0075 0.0069

Guatemala 0.0033 0.0075 0.0044

Guinea 0.0242 0.0200 0.0231

Guyana -0.0008 0.0000 -0.0006

Honduras -0.0030 -0.0017 -0.0025

Hungary 0.0000 -0.0025 -0.0006

33




Iceland -0.0008 0.0050 0.0006

India 0.0167 -0.0033 0.0127

Indonesia 0.0000 -0.0050 -0.0013

Iran (Islamic Republic of) 0.0058 0.0800 0.0244

Iraq 0.0000 0.0000 0.0000

Ireland -0.0008 0.0025 0.0000

Israel -0.0033 0.0025 -0.0019

Italy -0.0008 0.0000 -0.0006

Jamaica 0.0008 0.0025 0.0013

Japan 0.0000 0.0000 0.0000

Jordan 0.0008 0.0050 0.0019

Kazakhstan 0.0008 0.0000 0.0006

Kenya -0.0017 0.0100 0.0013

Kiribati -0.0075 0.0150 0.0000


Kuwait 0.0050 -0.0075 0.0019

Kyrgyzstan 0.0000 0.0000 0.0000

Lao People's Democratic Republic 0.0067 0.0075 0.0069

Latvia -0.0025 0.0000 -0.0019

Lebanon -0.0008 0.0025 0.0000

Lesotho -0.0175 -0.0033 -0.0147

Libyan Arab Jamahiriya -0.0050 -0.0033 -0.0043

Lithuania 0.0033 0.0000 0.0025

Luxembourg -0.0067 0.0000 -0.0050

Madagascar -0.0017 0.0025 -0.0006

Malawi 0.0118 0.0140 0.0125

Malaysia 0.0008 -0.0033 0.0000

Maldives -0.0075 -0.0025 -0.0050

Mali 0.0133 0.0125 0.0131

Malta 0.0025 -0.0050 0.0014

Marshall Islands -0.0100 0.0075 -0.0013

Mauritania 0.0208 0.0100 0.0181

Mauritius 0.0008 -0.0025 0.0000

Mexico 0.0008 -0.0025 0.0000

Mongolia 0.0000 0.0000 0.0000

Morocco 0.0175 0.0000 0.0131

Mozambique 0.0045 0.0160 0.0081

Namibia -0.0025 -0.0025 -0.0025

34




Nauru -0.0567 0.0100 -0.0186

Nepal 0.0208 0.0275 0.0225

Netherlands -0.0042 0.0000 -0.0031

New Zealand 0.0008 0.0025 0.0013

Nicaragua -0.0058 -0.0025 -0.0050

Niger 0.0083 0.0100 0.0088

Nigeria 0.0025 0.0100 0.0040

Niue -0.0300 0.0025 -0.0083

Norway 0.0000 0.0000 0.0000

Occupied Palestinian Territory -0.0025 0.0000 -0.0013

Oman 0.0058 0.0050 0.0056

Pakistan 0.0133 0.0250 0.0200

Palau -0.0375 0.0600 0.0113

Panama 0.0000 0.0000 0.0000

Papua New Guinea 0.0000 -0.0033 -0.0007

Paraguay 0.0000 0.0000 0.0000

Peru 0.0025 0.0025 0.0025

Philippines 0.0000 -0.0025 -0.0006

Poland 0.0017 0.0000 0.0013

Portugal 0.0000 0.0000 0.0000

Qatar 0.0033 0.0050 0.0038

Republic of Moldova -0.0025 -0.0025 -0.0025

Romania -0.0017 0.0025 -0.0006

Russian Federation 0.0000 0.0000 0.0000

Rwanda 0.0058 0.0050 0.0056

Saint Kitts and Nevis 0.0008 -0.0050 -0.0006

Saint Lucia 0.0017 0.0025 0.0019

Saint Vincent and the Grenadines -0.0017 -0.0050 -0.0025

Samoa -0.0025 0.0025 -0.0013

Sao Tome and Principe -0.0025 0.0100 0.0038

Senegal 0.0158 0.0200 0.0169

Serbia 0.0025 0.0000 0.0013

Seychelles 0.0050 -0.0050 0.0000

Sierra Leone 0.0010 0.0317 0.0125

Slovakia -0.0025 0.0025 0.0000

Slovenia 0.0025 -0.0025 0.0000

Solomon Islands 0.0067 0.0050 0.0064

South Africa -0.0025 0.0025 -0.0013

35




Spain 0.0000 0.0000 0.0000

Sri Lanka 0.0033 0.0000 0.0025

Sudan 0.0075 0.0000 0.0056

Suriname 0.0000 -0.0125 -0.0031

Swaziland -0.0033 -0.0050 -0.0038

Sweden 0.0025 -0.0075 0.0000

Switzerland -0.0008 -0.0025 -0.0013

Syrian Arab Republic 0.0033 0.0050 0.0038

Tajikistan -0.0025 0.0025 -0.0013

Thailand 0.0017 0.0000 0.0013


0.0050 0.0000 0.0025

Togo 0.0142 0.0100 0.0131

Tonga -0.0017 -0.0033 -0.0020

Trinidad and Tobago -0.0017 -0.0025 -0.0019

Tunisia 0.0058 0.0000 0.0044

Turkey 0.0017 0.0025 0.0019

Tuvalu 0.0225 -0.0400 -0.0043

Uganda 0.0117 0.0075 0.0106

Ukraine 0.0000 0.0000 0.0000

United Arab Emirates 0.0008 0.0025 0.0013

United Kingdom -0.0008 0.0025 0.0000

United Republic of Tanzania -0.0017 0.0050 0.0000

United States 0.0017 0.0000 0.0013

Uruguay -0.0008 -0.0025 -0.0013

Uzbekistan 0.0008 -0.0050 -0.0006

Vanuatu 0.0025 -0.0050 0.0006

Venezuela -0.0008 -0.0025 -0.0013

Yemen 0.0325 0.0250 0.0300

Zambia 0.0033 0.0080 0.0062

Zimbabwe 0.0008 0.0033 0.0013

36

Appendix Table 5: Share of Women in Wage Employment in Non-agricultural Sector




Argentina 0.65 -0.17 0.49

Armenia -0.18 -1.00 -0.51

Australia 0.33 -0.53 0.13

Austria 0.35 0.20 0.31

Azerbaijan 0.87 0.40 0.68

Bahamas 0.04 -0.33 -0.05

Bahrain 0.40 -0.75 0.13

Bangladesh 0.12 -0.50 -0.01

Barbados 0.33 -1.20 0.13

Belarus 0.07 -0.07 0.04

Belgium 0.40 0.43 0.41

Belize 0.01 1.20 0.31

Bermuda 0.02 -0.13 -0.01

Botswana 0.56 0.53 0.56

British Virgin Islands 0.06 -0.65 -0.08

Bulgaria 0.10 -0.38 -0.04

Canada 0.18 0.15 0.17

Cayman Islands 0.35 -1.23 -0.04

Chile 0.13 0.25 0.16


0.43 0.38 0.42


0.48 -0.23 0.32

Colombia 0.54 -0.07 0.39

Costa Rica 0.18 0.40 0.23

Croatia 0.16 0.00 0.12

Cuba 0.14 0.23 0.17

Cyprus 1.00 -0.05 0.65

Czech Republic -0.32 -0.13 -0.28

Denmark 0.02 0.18 0.05


Ecuador 0.23 -0.17 0.16

Egypt -0.05 -0.60 -0.15

El Salvador 0.18 0.23 0.19

Estonia -0.06 0.20 0.00

Finland 0.00 0.10 0.02

France 0.26 0.30 0.27

37




French Polynesia -0.01 0.13 0.03

Georgia -0.10 -0.05 -0.08

Germany 0.31 0.13 0.26

Gibraltar 0.55 -0.15 0.38

Greece 0.37 0.48 0.39

Greenland -0.07 -0.05 -0.07

Guam -0.57 0.15 -0.16

Guatemala 0.40 0.33 0.39

Honduras 0.39 -1.05 0.01

Hungary -0.01 -0.28 -0.08

Iceland -0.01 -0.63 -0.16

India 0.38 0.25 0.36

Indonesia 0.02 0.28 0.08


Ireland 0.44 0.20 0.38

Israel 0.45 0.03 0.35

Italy 0.41 0.45 0.42

Jamaica 0.01 -0.17 -0.03

Japan 0.22 0.20 0.21

Jordan 0.08 0.85 0.19

Korea, Republic of 0.24 0.23 0.24

Kyrgyzstan -0.17 0.88 0.21

Latvia 0.14 -0.32 0.01

Liechtenstein 0.07 0.25 0.14

Lithuania -0.17 -0.08 -0.15


Malaysia 0.22 0.28 0.23

Maldives 2.48 -1.77 0.89

Malta 0.51 0.63 0.55

Mauritius 0.13 -0.30 0.03

Mexico 0.02 0.65 0.18

Mongolia 0.08 0.50 0.20

Morocco -0.10 0.25 -0.02

Netherlands 0.62 0.40 0.56

New Zealand 0.28 0.28 0.28

Nigeria 0.15 0.15 0.15

Norway 0.16 0.03 0.13

Occupied Palestinian Territory 0.21 0.05 0.15

38




Pakistan 0.45 -0.10 0.32

Panama -0.12 -0.23 -0.14

Paraguay -0.16 0.33 -0.05

Peru 0.48 -0.03 0.36

Philippines 0.07 0.27 0.12

Poland 0.09 -0.25 -0.01

Portugal 0.34 0.18 0.30

Puerto Rico -0.49 0.35 -0.29

Qatar 0.08 0.33 0.19

Republic of Moldova 0.43 0.00 0.21

Romania 0.26 0.20 0.25

Russian Federation -0.02 0.00 -0.01

San Marino 0.12 -0.95 -0.14

Saudi Arabia -0.30 0.16 -0.01

Singapore 0.09 0.40 0.17

Slovakia 0.27 -0.45 0.10

Slovenia -0.03 -0.15 -0.06

South Africa 0.17 0.10 0.13

Spain 0.65 0.75 0.67

Sri Lanka -0.08 0.25 0.01

Sweden 0.03 -0.20 -0.02

Switzerland 0.27 -0.03 0.20

Tajikistan 0.11 -1.33 -0.28

Thailand 0.20 0.13 0.18


0.45 -0.43 0.24


Turkey 0.30 0.18 0.27

Turks and Caicos Islands -1.60 0.40 -0.60

Ukraine 0.20 0.08 0.16

United Kingdom 0.35 -0.05 0.26

United States 0.08 -0.08 0.05

Uruguay 0.45 -0.65 0.19

Venezuela 0.55 -0.25 0.36

39

Appendix Table 6: Children Under 5 Mortality Rate per 1000 Live Births Country Annual Change,


Year 2-3 Annual Change, entire

period

Afghanistan -0.30 0.00 -0.18

Albania -2.20 -1.29 -1.82

Algeria -2.50 -1.00 -1.88

Andorra -0.20 -0.14 -0.18

Angola -6.70 -4.71 -5.88

Antigua and Barbuda -1.20 -0.57 -0.83

Argentina -0.80 -0.71 -0.76

Armenia -2.00 -1.71 -1.88

Australia -0.30 0.00 -0.18

Austria -0.30 -0.29 -0.29

Azerbaijan -2.90 -4.29 -3.47

Bahamas -1.00 -0.86 -0.94

Bahrain -0.70 -0.29 -0.53

Bangladesh -6.00 -4.29 -5.29

Barbados -0.40 -0.14 -0.29

Belarus -0.60 -0.71 -0.65

Belgium -0.40 -0.14 -0.29

Belize -1.40 -0.57 -1.06

Benin -4.00 -3.00 -3.59

Bhutan -4.20 -3.14 -3.76

Bolivia -4.10 -3.86 -4.00

Bosnia and Herzegovina -0.50 -0.43 -0.47

Botswana 3.00 -6.71 -1.00

Brazil -2.60 -1.43 -2.12

Brunei Darussalam -0.20 0.00 -0.12

Bulgaria -0.10 -0.71 -0.35

Burkina Faso -1.60 0.14 -0.88

Burundi -0.50 -0.57 -0.53

Cambodia -1.20 -2.29 -1.65

Cameroon 1.20 -0.43 0.53

Canada -0.20 0.00 -0.12

Cape Verde -1.80 -1.43 -1.65

Central African Republic 1.50 -2.00 0.06

Chad 0.40 0.57 0.47

Chile -1.00 -0.29 -0.71

China -0.80 -2.14 -1.35

40




Colombia -0.90 -0.86 -0.88

Comoros -3.60 -2.57 -3.18

Congo 1.20 1.29 1.24

Cook Islands -0.80 -0.86 -0.82

Costa Rica -0.40 -0.43 -0.41

Cote d'Ivoire -1.50 -1.29 -1.41

Croatia -0.50 -0.29 -0.41

Cuba -0.50 -0.14 -0.35

Cyprus -0.40 -0.29 -0.35

Czech Republic -0.60 -0.29 -0.47

Democratic Republic of the Congo -2.10 -2.57 -2.29

Denmark -0.30 -0.29 -0.29

Djibouti -2.80 -2.86 -2.82

Dominica -0.20 -0.71 -0.41

Dominican Republic -2.90 0.14 -1.65

Ecuador -2.50 -1.43 -2.06

Egypt -4.20 -2.14 -3.35

El Salvador -2.50 -1.57 -2.12

Equatorial Guinea -3.00 -2.57 -2.82

Eritrea -5.00 -3.86 -4.53

Estonia -0.70 -0.71 -0.71

Ethiopia -5.30 -4.57 -5.00

Fiji -0.40 0.00 -0.24

Finland -0.30 0.00 -0.18

France -0.40 -0.14 -0.29

Gabon -0.10 0.00 -0.06

Gambia -2.20 -3.14 -2.59

Georgia -1.20 -0.71 -1.00

Germany -0.40 -0.14 -0.29

Ghana -0.80 0.43 -0.29

Greece -0.40 -0.43 -0.41

Grenada -1.10 -1.00 -1.06

Guatemala -2.90 -2.00 -2.53

Guinea -4.60 -5.00 -4.76

Guinea-Bissau -2.20 -2.86 -2.47

Guyana -1.80 -1.43 -1.65

Haiti -4.30 -4.71 -4.47

Honduras -1.90 -2.14 -2.00

41




Hungary -0.70 -0.43 -0.59

Iceland -0.30 -0.14 -0.24

India -2.60 -2.71 -2.65

Indonesia -4.30 -2.43 -3.53

Iran (Islamic Republic of) -2.80 -1.57 -2.29

Iraq -0.50 -0.57 -0.53

Ireland -0.20 -0.43 -0.29

Israel -0.50 -0.29 -0.41

Italy -0.40 -0.29 -0.35

Jamaica -0.10 -0.14 -0.12

Japan -0.10 -0.14 -0.12

Jordan -1.00 -0.86 -0.94

Kazakhstan -1.60 -1.71 -1.65

Kenya 2.00 0.57 1.41

Kiribati -1.80 -1.00 -1.47

Korea, Democratic People's Republic of

0.00 0.00 0.00


Kuwait -0.20 -0.29 -0.24

Kyrgyzstan -2.40 -1.71 -2.12

Lao People's Democratic Republic -6.20 -4.43 -5.47

Latvia -0.20 -0.86 -0.47

Lebanon -0.50 -0.43 -0.47

Lesotho 0.50 -3.29 -1.06

Liberia -4.10 -4.43 -4.24

Libyan Arab Jamahiriya -1.90 -0.57 -1.35

Liechtenstein -0.40 -0.43 -0.41

Lithuania -0.50 -0.43 -0.47

Luxembourg -0.40 -0.29 -0.35

Madagascar -3.10 -3.57 -3.29

Malawi -3.90 -8.43 -5.76

Malaysia -0.80 -0.43 -0.65

Maldives -5.60 -3.57 -4.76

Mali -3.30 -3.00 -3.18

Malta -0.40 -0.29 -0.35

Marshall Islands -2.40 -2.00 -2.24

Mauritania -0.80 -0.43 -0.65

Mauritius -0.50 -0.57 -0.53

42




Mexico -1.70 -1.14 -1.47

Micronesia, Federated States of -1.10 -1.00 -1.06

Monaco -0.30 -0.29 -0.29

Mongolia -3.50 -2.86 -3.24

Montenegro -0.20 -0.57 -0.35

Morocco -3.50 -2.86 -3.24

Mozambique -1.70 -2.29 -1.94

Myanmar -2.00 -1.00 -1.59

Namibia 1.20 -4.43 -1.12

Nauru 0.00 0.00 0.00

Nepal -5.70 -4.29 -5.12

Netherlands -0.20 -0.14 -0.18

New Zealand -0.40 -0.14 -0.29

Nicaragua -2.50 -1.14 -1.94

Niger -7.40 -7.71 -7.53

Nigeria -2.30 -2.57 -2.41

Norway -0.40 -0.14 -0.29


Oman -1.70 -0.43 -1.18

Pakistan -2.60 -2.29 -2.47

Palau -0.70 -0.57 -0.65

Panama -0.80 -0.43 -0.65

Papua New Guinea -1.80 -1.57 -1.71

Paraguay -0.80 -0.57 -0.71

Peru -3.80 -2.86 -3.41

Philippines -2.50 -1.29 -2.00

Poland -0.70 -0.43 -0.59

Portugal -0.80 -0.43 -0.65

Qatar -0.70 -0.57 -0.65


Romania -0.90 -1.14 -1.00

Russian Federation -0.30 -1.29 -0.71

Rwanda 1.50 -9.29 -2.94

Saint Kitts and Nevis -1.10 -1.00 -1.06

Saint Lucia -0.50 0.29 -0.18

Saint Vincent and the Grenadines 0.20 -0.71 -0.18

Samoa -1.60 -1.00 -1.35

San Marino -0.60 -0.43 -0.53

43




Sao Tome and Principe -0.10 -0.14 -0.12

Saudi Arabia -1.50 -0.57 -1.12

Senegal -1.60 -2.71 -2.06

Serbia -0.60 -0.71 -0.67

Seychelles -0.40 -0.29 -0.35

Sierra Leone -1.60 -1.71 -1.65

Singapore -0.40 -0.14 -0.29

Slovakia -0.50 -0.29 -0.41

Slovenia -0.60 -0.14 -0.41

Solomon Islands -3.30 -2.57 -3.00

Somalia -3.90 -3.14 -3.59

South Africa 1.00 -2.14 -0.29

Spain -0.40 -0.14 -0.29

Sri Lanka -0.90 -0.29 -0.65

Sudan -1.00 -0.86 -0.94

Suriname -1.30 -1.29 -1.29

Swaziland 3.70 -6.00 -0.29

Sweden -0.30 -0.14 -0.24

Switzerland -0.20 -0.14 -0.18

Syrian Arab Republic -1.50 -0.71 -1.18

Tajikistan -2.30 -3.86 -2.94

Thailand -1.80 -0.86 -1.41


-2.20 0.14 -1.24

Timor-Leste -5.50 -4.57 -5.12

Togo -2.80 -3.14 -2.94

Tonga -0.60 -0.43 -0.53


Tunisia -2.10 -1.43 -1.82

Turkey -3.80 -3.00 -3.47

Turkmenistan -2.80 -3.00 -2.88

Tuvalu -1.10 -0.71 -0.94

Uganda -2.60 -2.71 -2.65

Ukraine -0.20 -0.43 -0.29

United Arab Emirates -0.50 -0.29 -0.41

United Kingdom -0.20 -0.14 -0.18

United Republic of Tanzania -1.40 -3.86 -2.41

United States -0.30 0.00 -0.18

44




Uruguay -0.80 -0.43 -0.65

Uzbekistan -1.20 -3.00 -1.94

Vanuatu -1.40 -2.00 -1.65

Venezuela -0.80 -0.71 -0.76

Viet Nam -2.60 -2.14 -2.41

Yemen -2.90 -3.57 -3.18

Zambia 1.50 -1.14 0.41

Zimbabwe 2.70 -4.57 -0.29

45

Appendix Table 7: Children 1 Year Old Immunized against Measles, Percentage Country Annual Change,


Year 2-3 Annual Change Entire

Period

Afghanistan 2.31 5.00 2.94

Albania 0.38 1.00 0.53

Algeria 0.08 2.00 0.53

Andorra 1.00 -0.50 0.40

Angola 1.85 6.50 2.94

Antigua and Barbuda 0.77 0.00 0.59

Argentina 0.31 0.50 0.35

Armenia 0.09 -0.50 -0.07

Australia 0.62 0.00 0.47

Austria 1.46 0.00 1.12

Azerbaijan 2.91 -0.25 2.07

Bahamas 0.31 1.50 0.59

Bahrain 0.92 0.00 0.71

Bangladesh 0.85 3.00 1.35

Barbados 0.23 -3.75 -0.71

Belarus 0.45 0.00 0.33

Belgium -0.23 2.50 0.41

Belize 0.77 0.00 0.59

Benin -1.08 -1.00 -1.06

Bhutan -0.38 1.75 0.12

Bolivia 2.08 0.25 1.65

Bosnia and Herzegovina 2.91 3.00 2.93

Botswana 0.23 0.00 0.18

Brazil 1.62 0.00 1.24

Brunei Darussalam 0.00 -0.50 -0.12

Bulgaria -0.23 0.00 -0.18

Burkina Faso -0.23 4.50 0.88

Burundi 0.08 0.00 0.06

Cambodia 2.38 3.50 2.65

Cameroon 0.38 3.25 1.06

Canada 0.46 -0.25 0.29

Cape Verde -0.85 1.50 -0.29

Central African Republic -2.54 3.25 -1.18

Chad -0.69 0.00 -0.53

Chile -0.08 -1.25 -0.35

China -1.00 2.25 -0.24

Colombia 0.77 0.75 0.76

46




Comoros -1.85 0.50 -1.29

Congo -1.92 4.25 -0.47

Cook Islands 2.46 -0.25 1.82

Costa Rica -0.08 0.25 0.00

Cote d'Ivoire 1.85 -3.25 0.65

Croatia 0.45 0.25 0.40

Cuba 0.38 0.00 0.29

Cyprus 0.69 0.25 0.59

Czech Republic 0.10 -0.50 -0.07

Democratic Republic of the Congo 1.23 6.25 2.41

Denmark 0.92 -1.75 0.29

Djibouti -1.46 2.00 -0.65

Dominica 0.85 -0.75 0.47

Dominican Republic -0.92 3.00 0.00

Ecuador 3.00 0.00 2.29

Egypt 0.92 -0.25 0.65

El Salvador -0.62 2.00 0.00

Equatorial Guinea -2.85 0.00 -2.18

Eritrea 5.60 1.25 4.36

Estonia 2.10 0.25 1.57

Ethiopia 1.31 2.50 1.59

Fiji 0.54 -2.50 -0.18

Finland 0.00 0.25 0.06

France 1.15 0.25 0.94

Gabon -1.62 0.00 -1.24

Gambia 0.31 -1.25 -0.06

Georgia 5.82 4.25 5.40

Germany 1.46 0.00 1.12

Ghana 1.46 3.75 2.00

Greece 0.92 0.00 0.71

Grenada 1.08 -0.25 0.76

Guatemala 2.00 -0.25 1.47

Guinea 1.00 5.75 2.12

Guinea-Bissau 1.62 0.50 1.35

Guyana 1.23 1.75 1.35

Haiti 2.00 0.25 1.59

Honduras 0.38 -1.50 -0.06

Hungary 0.00 0.00 0.00

47




Iceland -0.46 0.50 -0.24

India 0.23 2.00 0.65

Indonesia 1.23 1.50 1.29

Iran (Islamic Republic of) 1.08 -0.50 0.71

Iraq 0.08 -1.75 -0.35

Ireland 0.00 2.25 0.53

Israel 0.31 0.50 0.35

Italy 3.08 1.00 2.59

Jamaica 0.38 -0.75 0.12

Japan 2.00 -0.25 1.47

Jordan 0.69 -0.25 0.47

Kazakhstan 0.91 0.00 0.67

Kenya -0.46 2.00 0.12

Kiribati -0.23 5.25 1.06


-0.23 1.00 0.06

Korea, Republic of 0.23 -1.00 -0.06

Kuwait 2.38 0.50 1.94

Kyrgyzstan 0.45 0.00 0.33

Lao People's Democratic Republic 0.77 -0.50 0.47

Latvia 0.36 -0.50 0.13

Lebanon -0.62 0.00 -0.47

Lesotho 0.38 0.00 0.29

Liberia 0.33 10.50 6.14

Libyan Arab Jamahiriya 0.46 0.75 0.53

Lithuania 0.82 -0.25 0.53

Luxembourg 0.85 1.25 0.94


Malawi -0.31 1.50 0.12

Malaysia 1.85 -1.00 1.18

Maldives 0.00 0.25 0.06

Mali 1.31 2.00 1.47

Malta 0.77 -2.75 -0.06

Marshall Islands 2.92 1.00 2.47

Mauritania 2.54 -1.00 1.71

Mauritius 1.38 1.00 1.29

Mexico 1.62 0.00 1.24

Micronesia, Federated States of 0.77 0.25 0.65

48




Monaco 0.00 0.00 0.00

Mongolia 0.46 0.00 0.35

Morocco 0.85 1.25 0.94


Myanmar 0.62 1.25 0.76

Namibia -0.50 -0.25 -0.44

Nauru -7.67 11.50 0.00

Nepal 1.38 1.50 1.41

Netherlands 0.08 0.25 0.12

New Zealand -0.46 -1.25 -0.65

Nicaragua 0.85 1.50 1.00

Niger 1.31 1.25 1.29

Nigeria -0.69 4.25 0.47

Norway -0.08 1.50 0.29

Oman 0.00 -0.25 -0.06

Oman -1.00 3.25 0.00

Pakistan 0.85 4.75 1.76

Palau 0.08 -2.00 -0.41

Panama 0.77 1.50 0.94

Papua New Guinea -0.31 -1.25 -0.53

Paraguay 1.69 -2.75 0.65

Peru 2.38 1.00 2.06


Poland 0.15 0.25 0.18

Portugal 0.85 -0.25 0.59

Qatar 1.08 -0.25 0.76

Republic of Moldova 0.36 0.00 0.27

Romania 0.38 0.00 0.29


Rwanda 0.54 2.25 0.94

Saint Kitts and Nevis -0.08 0.25 0.00

Saint Lucia 0.62 1.00 0.71

Saint Vincent and the Grenadines -0.15 1.25 0.18

Samoa 0.77 -9.00 -1.53

San Marino -0.67 0.25 -0.44

Sao Tome and Principe 1.23 -0.25 0.88

Saudi Arabia 0.62 0.00 0.47

Senegal 0.69 6.00 1.94

49




Serbia and Montenegro 0.45 4.50 1.08

Seychelles 1.00 0.00 0.76

Sierra Leone 2.75 -1.50 0.63

Singapore 0.69 0.50 0.65

Slovakia 0.22 0.00 0.15

Slovenia -0.27 2.25 0.40

Solomon Islands 0.00 2.00 0.47

Somalia 0.77 -1.50 0.24


Spain -0.08 -0.25 -0.12

Sri Lanka 1.46 -0.25 1.06

Sudan 0.62 3.50 1.29

Suriname 0.31 4.00 1.18

Swaziland -1.08 5.00 0.35

Sweden -0.08 0.25 0.00

Switzerland -0.62 1.00 -0.24


Tajikistan 1.73 -0.50 1.13

Thailand 1.23 0.00 0.94


-0.20 0.00 -0.14

Togo -0.38 3.00 0.41

Tonga 1.00 0.00 0.76


Tunisia -0.23 2.00 0.29

Turkey -0.23 5.25 1.06

Turkmenistan 1.91 0.50 1.53

Tuvalu 0.00 0.00 0.00

Uganda 0.92 1.00 0.94

Ukraine 0.82 -0.25 0.53

United Arab Emirates 1.08 -0.50 0.71

United Kingdom -0.54 1.50 -0.06

United Republic of Tanzania 1.31 -1.75 0.59

United States 0.23 0.00 0.18

Uruguay -0.15 0.25 -0.06

Uzbekistan 1.36 0.00 1.00

Vanuatu -1.38 4.25 -0.06

Venezuela 1.69 -7.00 -0.35

50




Viet Nam 0.38 -2.50 -0.29

Yemen -0.23 2.00 0.29

Zambia -0.46 0.25 -0.29

Zimbabwe -1.31 -1.00 -1.24

51

Appendix Table 8: Births Attended by Skilled Health Personnel, Percentage Country Annual Change,


Year 2-3 Annual Change Entire

Period

Algeria 1.89 -0.18 1.30

Angola 4.44 0.43 2.25

Antigua and Barbuda 0.00 -0.02 -0.01

Argentina 0.26 0.23 0.26

Azerbaijan -0.02 -3.90 -1.48

Bahamas 0.00 0.00 0.00


Barbados 0.00 0.00 0.00

Benin 1.14 2.44 1.79

Bolivia 2.18 -0.20 1.33

Bosnia and Herzegovina 0.23 -0.08 0.15

Bulgaria 0.01 0.07 0.02

Burkina Faso -0.37 5.23 0.92

Cambodia -1.10 2.40 1.40

Cameroon -0.43 0.50 -0.06

Central African Republic -0.36 1.55 0.68

Chad 0.43 -0.48 -0.09

Chile 0.05 0.00 0.03

China 0.15 0.63 0.24

Colombia -0.73 2.00 0.18

Costa Rica 0.00 0.17 0.04

Cote d'Ivoire 2.90 -1.00 0.95

Croatia 0.01 0.00 0.01

Cuba 0.01 0.00 0.01

Czech Republic -0.01 0.00 -0.01


Egypt 2.74 1.90 2.49

Estonia 0.06 0.03 0.06

Gambia 1.06 0.35 0.79

Georgia 0.18 -0.35 0.11

Ghana 0.33 0.87 0.45

Guinea 2.27 -8.75 0.58


Guyana -0.17 -3.57 -1.30

Haiti 0.64 -3.97 -1.87

Honduras 0.98 2.24 1.43

Hungary 0.02 0.03 0.02

52




India 1.19 0.68 0.95

Indonesia 1.97 1.68 1.90


Jamaica 0.46 -0.07 0.26

Jordan 1.03 -0.10 0.69


-0.13 0.10 -0.06

Latvia -0.08 0.33 0.00

Lesotho -0.16 -1.10 -0.50

Lithuania 0.00 0.00 0.00

Madagascar -1.35 1.28 -0.48

Malawi 0.57 -1.73 -0.09

Malaysia 0.35 0.30 0.35

Maldives -2.81 4.57 -0.60

Mali 0.12 1.68 0.90


Mongolia 0.68 0.73 0.70

Namibia 0.91 0.98 0.94

Nepal 0.35 1.56 0.75

Nicaragua 0.74 1.36 0.98

Niger 0.10 2.87 1.29

Occupied Palestinian Territory 0.63 0.25 0.40

Oman 0.72 0.57 0.64

Pakistan 0.47 2.26 1.25

Panama 0.67 -0.50 0.40

Peru 0.85 1.95 1.32

Romania -0.11 -0.07 -0.10


Rwanda 0.69 2.60 1.64

Saint Kitts and Nevis 0.00 0.12 0.09

Saint Lucia -0.18 0.50 0.05

Saint Vincent and the Grenadines 0.35 0.00 0.12

Senegal 1.20 -2.03 0.39

Slovakia -0.05 0.02 -0.03

Slovenia 0.02 0.00 0.02

Somalia -3.13 2.05 -0.17

Sri Lanka 0.27 0.36 0.31

Sudan 0.08 -6.30 -2.47

53




Suriname -2.63 0.88 -0.52

Swaziland 2.25 -1.00 1.00

Tajikistan -1.98 2.46 0.49


0.77 0.03 0.63

Togo 2.06 0.40 1.44

Trinidad and Tobago -1.00 0.30 -0.13

Turkmenistan 0.35 0.38 0.37

Uganda 0.17 0.62 0.36

Ukraine 0.00 -0.30 -0.11

Uzbekistan -0.48 0.72 0.24

Viet Nam 1.58 0.68 1.18

Yemen 0.87 2.97 1.57

Zambia -0.71 0.62 -0.27

54

Appendix Table 9: Proportion of the Population using Improved Drinking Water Sources, Total



Annual Change entire Period

Afghanistan 0 0.17 0.09

Albania 0.2 0.00 0.09

Algeria -0.5 -0.67 -0.56

Angola 0.5 1.17 0.75

Argentina 0.2 0.00 0.13

Armenia 0.4 0.83 0.64

Azerbaijan 0.8 0.33 0.63


Benin 0.1 0.17 0.13

Bolivia 1 0.67 0.88

Bosnia and Herzegovina 0 0.33 0.13

Botswana 0.2 0.17 0.19

Brazil 0.6 0.33 0.50

British Virgin Islands 0 0.00 0.00

Bulgaria 0 0.00 0.00


Burundi 0.1 0.00 0.06

Cambodia 3.8 4.50 4.18

Cameroon 1.4 1.17 1.31


Chad 2 2.33 2.18

Chile 0.2 0.33 0.25

China 1.3 1.33 1.31

Colombia 0.2 0.33 0.25

Comoros -0.5 -0.50 -0.50

Cook Islands 0.1 0.00 0.06

Costa Rica 0.2 0.17 0.18

Cote d'Ivoire 0.8 1.00 0.88

Croatia 0 0.00 0.00

Cuba 0 0.00 0.00


0.2 0.17 0.19

Djibouti 0.7 1.50 1.00

Dominican Republic 0.8 0.50 0.69

Ecuador 1.5 1.17 1.38

Egypt 0.3 0.17 0.25

55




El Salvador 1 0.83 0.94

Equatorial Guinea 0 0.00 0.00

Eritrea 1.1 1.00 1.06

Ethiopia 1.6 2.17 1.81

Fiji -0.1 0.00 -0.06

Gabon 0.4 0.33 0.36

Gambia 0.2 0.00 0.09

Georgia 1.1 2.00 1.44

Ghana 1.6 1.33 1.50

Greece 0.3 0.17 0.25

Guatemala 1.2 0.83 1.06

Guinea 1.6 1.50 1.56

Guinea-Bissau 0 -0.17 -0.09

Guyana 0.2 0.67 0.45

Haiti 0.4 0.33 0.38

Honduras 0.8 0.67 0.75

Hungary 0.3 0.17 0.25

India 1.1 1.17 1.13

Indonesia 0.5 0.50 0.50

Iraq -0.3 -0.50 -0.38

Jamaica 0.1 0.00 0.06

Jordan 0 0.17 0.06

Kazakhstan 0 0.00 0.00

Kenya 1 1.00 1.00

Kiribati 1.4 0.50 1.06

Kyrgyzstan 1 1.17 1.09


1 2.33 1.73

Latvia 0 0.00 0.00

Lesotho 0 0.17 0.09

Liberia 0.6 0.17 0.44


Malawi 2.2 2.17 2.19

Malaysia 0 0.17 0.06

Maldives -0.9 -0.67 -0.81

Mali 1.8 1.50 1.69


Mexico 0.5 0.33 0.44

56




Micronesia, Federated States of 0.4 0.33 0.38

Mongolia 0.4 0.67 0.50

Morocco 0.5 0.50 0.50


Myanmar 1.4 1.50 1.44

Namibia 2.4 2.00 2.25

Nepal 1.1 1.00 1.06

Nicaragua 0.7 0.33 0.56

Niger 0 0.17 0.06

Nigeria -0.1 -0.33 -0.19

Northern Mariana Islands 0 0.00 0.00


Pakistan 0.2 0.33 0.25

Palau 0 -0.17 -0.06

Panama 0 0.00 0.00

Papua New Guinea 0 0.17 0.06

Paraguay 1.7 1.33 1.56

Peru 0.6 0.50 0.56


Portugal 0.3 0.00 0.19


Romania 0.9 0.50 0.75


Rwanda 0 0.00 0.00

Saint Kitts and Nevis 0 0.00 0.00

Saint Lucia 0 0.00 0.00

Samoa -0.2 -0.17 -0.19


Senegal 0.5 0.83 0.63

Sierra Leone 0 -0.67 -0.36


Somalia 0.4 1.00 0.73


Sri Lanka 1 0.83 0.94

Sudan 0.5 0.17 0.38

Suriname 0 0.17 0.09

Swaziland 0 0.17 0.09


57





Thailand 0.2 0.17 0.19

Togo 0.6 0.67 0.63


Tunisia 0.8 0.67 0.75

Turkey 0.8 0.67 0.75

Tuvalu 0.3 0.00 0.19

Uganda 1.3 1.33 1.31

Ukraine 0 0.00 0.00

United Republic of Tanzania 0.4 0.33 0.38

United States 0 0.00 0.00

Uzbekistan -0.1 -0.17 -0.13

Viet Nam 2.5 2.50 2.50

Yemen -0.4 -0.67 -0.55

Zambia 0.4 0.67 0.50

Zimbabwe 0.2 0.17 0.19

58

Appendix Table 10: Proportion of the Population Using Improved Sanitation Facilities, Total



Annual Change entire Period

Afghanistan -0.4 0.00 -0.18

Albania 0.6 1.33 1.00

Algeria 0.4 0.33 0.38

Angola 1.4 1.67 1.50

Argentina 0.8 0.33 0.63

Armenia 0 0.33 0.18

Australia 0 0.00 0.00

Austria 0 0.00 0.00

Azerbaijan 0 0.00 0.00

Bahamas 0 0.00 0.00


Barbados 0 -0.17 -0.06

Belarus 9 0.17 4.18

Benin 1.2 1.00 1.13

Bolivia 0.6 0.67 0.63

Bosnia and Herzegovina 0 -0.17 -0.09

Botswana 0.7 0.33 0.56

Brazil 0.3 0.50 0.38

British Virgin Islands 0 0.00 0.00

Bulgaria 0 0.00 0.00


Burundi -0.2 -0.17 -0.19

Cambodia 1.6 2.00 1.82

Cameroon 0.8 0.67 0.75

Canada 0 0.00 0.00


Chad 0.2 0.33 0.25

Chile 0.7 0.50 0.63

China 1.1 1.00 1.06

Colombia 0.6 0.67 0.63

Comoros 1.1 1.00 1.06

Cook Islands 0.4 0.00 0.25

Costa Rica 0.2 0.00 0.13

Cote d'Ivoire 0.2 0.33 0.25

Croatia 0 0.00 0.00

Cuba 0 0.00 0.00

59




Cyprus 0 0.00 0.00

Czech Republic -0.1 0.00 -0.06


1 1.00 1.00

Denmark 0 0.00 0.00

Dominican Republic 0.6 0.83 0.69

Ecuador 0.9 0.67 0.81

Egypt 1.1 0.83 1.00

El Salvador 0.9 0.67 0.81

Equatorial Guinea 0 0.00 0.00

Eritrea 0.1 0.17 0.13

Estonia 0 0.00 0.00

Ethiopia 0.3 0.67 0.44

Fiji 0.2 0.17 0.19

Finland 0 0.00 0.00

French Polynesia 0 0.00 0.00

Gabon 0.2 0.00 0.09

Gambia 0.4 0.50 0.45

Georgia -0.1 0.00 -0.06

Germany 0 0.00 0.00

Ghana 0.3 0.17 0.25

Greece 0.1 0.00 0.06

Grenada 0 0.00 0.00

Guam 0 0.00 0.00

Guatemala 1 0.67 0.88

Guinea 0.3 0.50 0.38


Guyana 0 -0.17 -0.09

Haiti -0.5 -0.83 -0.63

Honduras 1.3 1.33 1.31

Hungary 0 0.00 0.00

Iceland 0 0.00 0.00

India 0.9 0.83 0.88

Indonesia 0.1 0.00 0.06

Iraq 0.2 0.67 0.45

Jamaica 0 0.00 0.00

Japan 0 0.00 0.00

Jordan -1 -0.83 -0.91

60




Kazakhstan 0 0.00 0.00

Kenya 0.2 0.17 0.19

Kiribati 0.8 0.50 0.69

Kyrgyzstan 0.2 0.00 0.09


1.8 4.33 3.18

Lesotho 0.2 0.33 0.27

Liberia -0.8 0.00 -0.50

Libyan Arab Jamahiriya 0 0.00 0.00

Luxembourg 0 0.00 0.00


Malawi 0.9 0.83 0.88

Maldives 0.2 0.17 0.18

Mali 0.7 0.50 0.63


Mauritius 0 0.00 0.00

Mexico 2 0.83 1.56

Micronesia, Federated States of -0.3 -0.17 -0.25

Mongolia 0.2 0.33 0.27

Montserrat 0 0.00 0.00

Morocco 1.3 1.17 1.25

Mozambique 1 0.67 0.82

Myanmar 3.6 3.83 3.69

Namibia 0.6 0.50 0.56

Nepal 1.1 1.17 1.13

Netherlands 0 0.00 0.00

Nicaragua 0.4 0.33 0.38

Niger 0.2 0.33 0.25

Nigeria 0.2 0.33 0.25

Niue 0 0.00 0.00

Northern Mariana Islands 0.8 0.33 0.63

Occupied Palestinian Territory 0 0.00 0.00

Pakistan 1.5 1.67 1.56

Palau 0.4 0.33 0.38

Panama 1.2 0.83 1.00

Papua New Guinea 0 0.17 0.06

Paraguay 0.7 0.50 0.63

Peru 1 1.17 1.06

61





Portugal 0.5 0.33 0.44

Qatar 0 0.00 0.00

Republic of Moldova 0 0.17 0.09

Romania 0.1 -0.17 0.00

Russian Federation 0 0.00 0.00

Rwanda 1.5 1.33 1.44

Saint Kitts and Nevis 0 0.00 0.00

Samoa 0.2 0.00 0.13


Senegal 0.1 0.17 0.13

Sierra Leone 0 -0.17 -0.09

Slovakia 0 0.00 0.00


Somalia 0 0.33 0.18


Spain 0 0.00 0.00

Sri Lanka 1 0.83 0.94

Sudan 0.1 0.17 0.13

Suriname 0 -0.17 -0.09

Swaziland 0 0.00 0.00

Sweden 0 0.00 0.00

Switzerland 0 0.00 0.00



Thailand 1.5 0.50 1.13

Togo -0.1 0.00 -0.06

Tonga 0 0.00 0.00

Trinidad and Tobago -0.1 0.00 -0.06

Tunisia 0.7 0.67 0.69

Turkey 0.2 0.17 0.19

Tuvalu 0.8 0.50 0.69

Uganda 0.3 0.17 0.25

Ukraine 0 -0.50 -0.19

United Arab Emirates 0 0.00 0.00

United Republic of Tanzania -0.1 -0.17 -0.13

United States 0 0.00 0.00

Uruguay 0 0.00 0.00

62




Uzbekistan 0.1 0.33 0.19

Viet Nam 2.2 2.33 2.25

Yemen 1.1 1.17 1.13

Zambia 0.7 0.50 0.63

Zimbabwe 0.1 0.17 0.13

References African Development Bank, United Nations Economic Commission for Africa and African Union Commission.

(2009). Assessing Progress in Africa Towards the Millenium Development Goals MDG Report 2009. United Nations Economic Commission for Africa, African Union Commission, African Development Bank.

Alston, Philip (2005) ‘Ships passing in the night: the current state of the human rights and development debate seen through the lens of the Millennium Development Goals’, Human Rights Quarterly 7.3 p.755

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