the role of the state and its governance in the context of a country's economic development presentation

Hulmeetal2015GovernanceasaGlobalDevelopmentGoal.pdf

Home >Political Science homework help >the role of the state and its governance in the context of a country's economic development presentation

Governance as a Global Development Goal? Setting, Measuring and Monitoring the Post- 2015 Development Agenda

David Hulme, Antonio Savoia and Kunal Sen Institute for Development Policy and Management, University of Manchester

Abstract The increasing realisation that governance quality is a fundamental element of long-run development has led to its con- sideration as a desirable development goal in its own right. To contribute to such a process, this article provides a framework to set, measure and monitor governance goals in the post-2015 development agenda. First, we assess whether existing cross-national measures on governance quality can be exploited to measure and monitor aspects of legal, bureaucratic and administrative quality. Such a ‘quick fix’ approach to measuring governance quality is fraught with challenges. The current practice of measurement is still subject to the short country coverage of most available measures, issues of comparability and legitimacy, as well as methodological shortcomings. Second, we argue that, in the long run, measuring and monitoring governance quality may require reconceptualising ‘good governance’ and designing internationally shared measures that are routinely provided by national statistical offices (but, international groups should also continue to make their independent measures). Finally, we consider the different approaches to set- ting governance goals, arguing in favour of a combination of national target setting and minimum standard with con- tinuous improvement.

Policy Implications • Short-term, the task of measuring and monitoring governance goals is quite challenging and one should be mind-

ful that existing indices are subject to short country coverage, issues of comparability and legitimacy, as well as methodological shortcomings. Hence, the interpretation of changes in governance in the future may be challenged both technically and politically.

• Longer-term, since the idea of ‘good governance’ can be highly controversial, one should reflect on which dimen- sions and measures should be included. One approach is to consider the intrinsic value of good governance, which would give precedence to measures capturing state-society relations and accountability. The alternative is consider- ing the instrumental value of governance. In this case, the focus should be on state capacity; and measures of state administrative and legal capability would be a desirable starting point.

• For setting governance goals, we recommend minimum global standards set for fixed dates, but all countries also to pursue improved measures on an annual basis line of argument.

• Policy makers should be aware of the two main tasks involved in this exercise. Short-term, the setting of credible international targets that can contribute to improved governance. Longer-term, the setting in motion of processes that will create governance measurement as a routinised function in all national statistical offices (the creation of a professional cadre, the setting of international standards for example).

Most scholars and policy makers would agree that the design of rules and regulations, the effectiveness of poli- cies and the competence of public bodies play a crucial role in the functioning of economies. In short, gover- nance matters. Since the early 1990s, an increasing amount of research focused on the quality of governance as a determinant of national income levels and economic growth rates. Although its effects on other important development outcomes – such as inequality, health and

education – have received less attention, the current consensus is that ‘good governance’, or perhaps more accurately ‘good enough governance’ (Grindle, 2004), is a prerequisite for development (e.g., Baland, Moene and Robinson, 2010, Cingolani et al., 2013).

The findings of this research have led to increasing recognition of the importance of its role to the point of considering governance a desirable global development goal in its own right (see United Nations, 2013 and

Global Policy Volume 6 . Issue 2 . May 2015 85

R esea

rch A rticle

section 2). This article seeks to contribute to this process by exploring the possibility of setting and monitoring governance goals for the post-2015 development agenda. In order to do so, one must necessarily look also at the possibility of routinely measuring governance goals. Hence, our task requires assessing how, and how well, existing databases and measures capture gover- nance quality: which aspects they measure; what and how robust their methodologies are. We examine the trends for measures of legal, bureaucratic and administra- tive quality, assessing to what extent such measures can be used, in terms of both political acceptability and sta- tistical desirability.

We will argue that the idea of ‘good governance’, as often captured, can be a highly controversial one (for example see Sundaram and Chowdhury, 2012) and risks neglecting the centrality of context to effective institu- tional reform (Andrews, 2013). Hence, existing measures, while offering a quick solution for the post-2015 develop- ment agenda, may not reflect a ‘politically shared’ notion of governance quality. We also argue that we need to think long term: how to develop a professional cadre, setting international standards and getting national sta- tistical offices engaged, so that governance measures become part of a routinised, national statistics activity producing internationally comparable data. This is long term, but it is what the UN has specialised in, and had a lot of success in, since 1950 (Ward, 2004). It would ensure that the post-2030 development agenda has well thought out and high-quality governance measures.

The article proceeds as follows: section 1 provides a background discussion on the approaches and controver- sies of governance quality measurement; section 2 exam- ines the potential of available indicators to capture governance goals, presenting some statistics; sections 3 and 4 discuss the possibility of monitoring and setting governance goals in the post-2015 development agenda; and section 5 concludes.

1. Measuring governance as a development goal

This section provides the background discussion on exist- ing approaches and controversies on measurement and their implications for governance as a development goal. This requires two building blocks. First, we need to define the object of measurement and its dimensions. Second, we must discuss the methodological issues and the properties of governance measures.

Defining what to measure

The concept of governance is commonly viewed as elu- sive or as ambiguous. According to the Oxford English Dictionary, governance is: ‘The manner in which some-

thing is governed or regulated; method of management, system of regulations’. Detailed discussions of its concep- tual underpinnings often conclude that there is no widely accepted definition that can be operationalised (e.g., Bevir, 2011 and Holmberg et al., 2009). The World Bank’s definition of governance as ‘the manner in which power is exercised in the management of a country’s economic and social resources for development’ (World Bank, 1992, p. 1) is used extensively in the literature. In practice, the analysis of governance has fitted a multiplic- ity of dimensions: from the type and quality of political institutions to the set of economic institutions and poli- cies. In particular, political democracy is often considered as part of (good) governance. In democracies, citizens and parties enjoy substantial representation and execu- tive power is subject to checks and balances. Such char- acteristics may often be associated with the attainment of economic and human development goals. However, this article is not concerned with aspects of democracy or political regimes, for two reasons. First, the role of democracy is still controversial as, historically, develop- mental states in Asia existed under authoritarian regimes (e.g., Taiwan and South Korea). Indeed, even authoritarian regimes differ so greatly that thinking that such a cate- gory has analytical utility may be far-fetched. Whether and how political regimes affect the quality of gover- nance remains an open question (e.g., Mulligan et al., 2004; Bardhan, 1999). Second, the analysis of political democracy and political regimes relate to aspects of access to power. It seems conceptually appropriate to keep the issue of access to power separate from the one on the exercise of power (Mazzuca, 2010).1 As Fukuyama (2013) argues, ‘governance is about the performance of agents in carrying out the wishes of principals, and not about the goals that principals set’ (p. 350).

Hence, this paper adopts a definition of governance that separates the quality of governance from the nature of the political regime in the country in question. Under this definition, governance is the effectiveness of rules, poli- cies and the functioning of public bodies that affect the lives of the members of a community. Even from such a narrow starting point that focuses on the organisation of the state and how effectively it executes policies and programmes, identifying the objects of measurement is not straightforward. Theories of development disagree on which and how many dimensions of governance are crucial to prosperity. The type of governance that pro- motes it may vary according to the proposed mecha- nisms through which institutions and policies affect development outcomes: some emphasise the protection of property rights (see Acemoglu and Robinson, 2012; and Tabellini, 2005); others point to the role of the state involvement in overcoming coordination failures (e.g., Bardhan, 2005); or of protecting specific economic sec- tors, supporting technological innovation, providing infra-

David Hulme, Antonio Savoia and Kunal Sen 86

structure and engaging in human capital formation (e.g., Evans, 1995). Consequently, the concept of governance must be mapped according to the functions one deems key to development.

Based on the existing economics and political science literature, one can differentiate between three conceptu- ally separate dimensions of governance (as being under- stood as the capacity of the state to implement rules and policies effectively), that are seen as being crucial for the achievement of inclusive development. These are:

• Bureaucratic and administrative systems – Whatever we may maintain a state should do to foster development, it needs a bureaucratic apparatus to design and imple- ment policies. This dimension is central to all areas of research on the state and development. Traditionally, state capacity indicators focus on the competence and ability of bureaucracy (e.g., Evans and Rauch, 1999; Rauch and Evans, 2000), and generally include the abil- ity of raising tax and spending the proceeds efficiently on important public goods (Ottervik, 2013).

• Legal infrastructure – The capability of a legal frame- work of enforcing contracts and property rights (i.e., a judicial system for settling disputes, rule of law). The consensus is that, at the very least, the state has to provide such public goods, as they are ill-suited to private provision (Besley and Persson, 2011; Lin and Nugent,1995).

• Transparency and accountability – While there may be disagreement on the appropriate nature of the state in fostering economic development, there seems to be increasing realisation on the importance of trans- parency and accountability in shaping the legitimacy of state institutions and the quality of governance. Here, transparency and accountability is broadly understood to be about the relationship between the citizen and the state and the extent to which the state is answerable for its own actions and inactions (UNDP, 2013). Transparency and accountability are seen as important elements of the effectiveness of states in delivering essential services such as educa- tion, health and infrastructure effectively to the poor (World Bank, 2004; Rakjumar and Swaroop, 2008).

The transparency and accountability component of the ‘good governance’ agenda has been mostly clearly reflected in the post-2015 development goal on gover- nance in the high-level panel (HLP) report (United Nations, 2013). As Table 1 illustrates, all five dimensions of Goal 10: Ensuring Good Governance and Effective Institutions, as formulated in the HLP report, address transparency and accountability, in some degree. It is noteworthy that bureaucratic capacity and legal infra- structure do not seem to figure so clearly in the post-2015 millennium development goals (MDG) goal on governance, when there is a large body of evidence that these dimensions of governance matter more for inclu- sive development (Evans and Rauch, 1999; Besley and Persson, 2011; Savoia and Sen, 2014).

Methodological issues

Empirical research on governance quality has designed numerous and diverse measures: on the protection of property rights; quality and performance of the bureau- cracy; the administration of justice; and micro and mac- roeconomic management.2 This section reviews the methods and findings from such literature.

A popular classification divides governance indicators between objective and subjective measures (e.g., see Wil- liams and Siddiqui, 2008). Examples of measures con- structed from ‘hard’ data often come from the state capacity literature. Proxies can draw on economic vari- ables, such as tax effort (e.g., Hendrix, 2010; Hanson and Sigman, 2013), military expenditure (e.g., Hanson and Sig- man, 2013) or even national income measures (Fearon and Laitin, 2003). Others drew on infrastructure and pub- lic sector variables, such as railroad or road density and census administration (Centeno, 2002; Hanson and Sig- man, 2013) or military personnel (Hendrix, 2010). A sec- ond class of objective measures is rule-based, i.e., constructed by rating the existence and strength of cer- tain formal (de jure) rules. Examples of rule-based mea- sures of governance are those compiled by Global Integrity such as whether a country has regulations requiring an impartial, independent and fairly managed civil service (administrative capacity), laws that require

Table 1. The UN High Level Panel’s illustrative goal for governance

Goal 10: ensure good governance and effective institutions

a) Provide free and universal legal identity, such as birth registrations b) Ensure that people enjoy freedom of speech, association, peaceful protest and access to independent media and information c) Increase public participation in political processes and civic engagement at all levels d) Guarantee the public’s right to information and access to government data e) Reduce bribery and corruption and ensure officials can be held accountable

Source: UN High Level Panel, United Nations (2013, p. 50).

The Post 2015 Development Agenda 87

competitive bidding of major government procurement contracts (legal infrastructure) and in law, citizens can access the asset disclosure records of members of the national legislature (Global Integrity Report, 2011).

Alternatively, subjective measures are perception- based, i.e., ratings rely on perceptions of the de facto functioning of rules, coming from: (1) experts’ opinions, e.g., risk-rating agencies, foreign investors, academics or NGOs; and (2) surveys of national respondents (firms or individual citizens). Surveys have the advantage of cap- turing the views of domestic agents directly involved in the institutions of the country, but are more expensive to administer and less suitable for cross-country compa- rability than expert assessments (Williams and Siddiqui, 2008).

Which types of measures have the most desirable properties? Methodologically, proxies from hard data are free from the political or ideological bias that experts’ assessments may have. Perhaps the main limitation of such proxies is that they may be outcomes of gover- nance, rather than an assessment of its quality (and may change as a result of changes in factors other than reforms in the governance apparatus, e.g., such proxies may reflect the role of national culture and values). Simi- larly, the advantage of rule-based indicators is that they are not affected by observer’s bias. In addition, such measures have the advantage of synthesising many and diverse formal institutional and policy elements into a single aggregate governance index. However, they could well be vulnerable to gaps between the essence of rules and codes and how they function on the ground (e.g., bribes can be codified as illegal, but no agency actually enforces this law). Therefore, rule-based measures may exhibit ‘systemic isomorphic mimicry’ – where countries adopt the outward forms (such as appearances and structures) of functional states and organisations else- where to camouflage a persistent lack of function (Pritch- ett et al., 2013). Thus, while Ghana, Uganda, India and Venezuela receive the same score from the Global Integ- rity Report 2011 in terms of the existence of procedures on the meritocratic recruitment and promotion of civil servants, the same report finds that in practice, civil ser- vants in Ghana and Uganda are twice as likely to be appointed and evaluated according to professional crite- ria, when compared to India and Venezuela. This sug- gests that de facto measures, which are sensitive to any institutional and policy change: both formal and informal, may be preferred to rule-based or de jure measures of governance.

Apart from being prone to observer’s bias, an addi- tional limitation of subjective indicators is that they can- not indicate which specific policy intervention is actually responsible for observed changes in governance quality.3

There is no compelling reason to believe that, for instance, a policy intervention aimed at improving the

rule of law affects other aspects of the institutional envi- ronment, such as the recruitment of bureaucrats. This may or may not happen, depending on the actual policy and the degree to which this is implemented. Yet, the correlations among popular perception-based measures show that different dimensions of governance are signifi- cantly and positively correlated among themselves (see Hulme et al., 2014), suggesting that policy interventions in one area might be perceived as improving the general governance environment. Hence, perception-based indi- ces might have limited power in distinguishing different attributes of governance. However, such regularities could alternatively suggest that there are significant com- plementarities among dimensions of governance (as argued in Besley and Persson, 2011), in which case sub- jective measures would correctly record a simultaneous change in all the components.

Despite these potential limitations, there is scope for using subjective assessments: having a wider range of measures increases the number of dimensions that pol- icy makers can monitor. But one must carefully choose the appropriate measure or combination of measures, if the issue of governance under scrutiny demands. To this aim, Table 2 summarises types and properties of gover- nance measures. Moreover, even when they purportedly capture similar aspects, governance measures should not be necessarily considered interchangeable. As the concept of governance quality remains ambiguous, similar measures may express distinct aspects of governance.

Having provided an overview of the methodological issues, we finish the section with some remarks on the construction of a composite index, which would aggre- gate the dimensions of interest. A synthetic index, while not always desirable for academic research, would be quite useful to policy makers. But this begs the question of how many dimensions should be part of a composite index. Even if one could reach a consensus on which governance dimensions should be included, we would still be left with the task of elaborating an appropriate formula to combine the would-be components. For example, should it be additive or multiplicative? This can only be decided on the basis of further theoretical foun- dations on what constitutes governance for develop- ment.4 Meanwhile, policy makers wishing to draw on existing data may wish to use disaggregated measures, although it can be argued that using such ‘dashboards’ may encourage idiosyncratic choices and weaken the accumulation of knowledge about governance and its effects. From this, it follows that a useful property of any aggregate governance index is to make its components available. On the other hand, if one believes that there could be complementarities among different elements of governance, further discussion on a composite measure combining different aspects would have greater scope.

David Hulme, Antonio Savoia and Kunal Sen 88

2. Governance indicators for the post-2015 development agenda

What are the available measures that could be poten- tially used for the post-2015 development agenda? Mea- suring governance quality has gradually become an industry that sees NGOs, research organisations and com- mercial providers operating in this field. Reviews and guides on governance measurement (e.g., Teorell et al., 2013; Foresti et al., 2014), provide a broader overview of the available databases and measures. This section assesses a selection of representative indicators on the areas of governance identified above (but the list could be longer, such is the size of the governance rating industry). To see how governance quality has evolved, we also illustrate their trends over time.

Table 3 gives a snapshot comparison of selected gov- ernance indicators on the three dimensions of gover- nance discussed earlier – administrative capacity, legal capacity and transparency and accountability. Three facts stand out: (1) the current practice of measuring gover- nance quality seems to privilege methodologies based on a subjective approach; (2) policy makers interested in the areas of legal capacity, transparency and accountabil- ity and bureaucratic and administrative quality can choose from a variety of indicators; (3) efforts to provide comparable governance measures often face the con- straint of limited country coverage.

To give an illustration of the temporal evolution, we examine two databases that – measuring legal and administrative quality – allow observing governance over the longest period: the Quality of Government (QoG) index assembled by Teorell et al. (2013) and the Quality of Legal Structure and Security of Property Rights (QoLSSPR) index (Gwartney et al., 2013). In both cases, the ratings come from subjective assessments of foreign investors and business experts.5

The QoG index is calculated as the average of rule of law, corruption in government, and bureaucratic quality

indices from various editions of the International Country Risk Guide (ICRG, 2012). It spans from 1984 to 2010 and is rescaled to lie between 0 and 10. This index seems to capture some of the dimensions of governance quality that are implicit in the governance goal in the HLP report, particularly in its rule of law and anticorruption dimensions. However, the fact that it is expressing the views of the business community does raise concerns over its representativeness and legitimacy.

The QoLSSPR index is, instead, a proxy for legal capac- ity. A component of the Fraser Institute Index of Economic Freedom, such variable is continuous and ranges between 0 and 10, with a higher score corresponding to higher quality (see Gwartney et al., 2013). It has been recorded every five years from 1970 until 2000 (and every year from 2001 on). Unfortunately, it samples fewer countries than the ICRG database and it has been assembled over the years from different sources. Like the QoG, the QoLSSPR is also constructed from commercial ratings pro- duced by the business community (including the ICRG, the Business Environment Risk Intelligence and the Glo- bal Competitiveness Report), raising the same concerns over its representativeness and legitimacy.

Table 4 shows the trends in advanced, developing and transition economies over 2000–2010. The first stylised fact is the gap in governance quality between advanced economies and the rest remains wide and stable. A sec- ond stylised fact is that both measures show that advanced economies remain a more homogenous group than developing and transition economies.

Governance quality appears to be a slow-changing phenomenon and it should also be analysed over a longer period. Figure 1 below provides further details of the QoG and QoLSSPR by disaggregating the developing countries group by region. The end of the Cold War was accompanied by sharp improvements in governance quality, suggesting that it has been a positive shock.6

QoG shows a spike for all groups of countries in the mid- 1990s, where all regions of the developing world seem

Table 2. Classification and properties of governance measures

Type of measure based on:

Objective Subjective

Proxies from hard data De jure rules De facto rules

Advantages Not affected by observer’s bias.

(1) Not affected by observer’s bias;

Capture formal and informal rules.

(2) can isolate specific governance dimensions.

Limitations (1) express outcomes of governance;

May not capture the functioning of informal mechanisms.

(1) Affected by observer’s bias;

(2) do not address specific governance aspects.

(2) unable to isolate specific governance dimensions.

The Post 2015 Development Agenda 89

Table 3. Governance quality, comparing selected indicators

Index and source Methodology Coverage Data

Bureaucratic and administrative quality Bureaucratic quality, ICRG (2012)

Subjective. Experts’ assessments which indicate autonomy from political pressure and strength and expertise to govern without drastic changes in policy or interruptions in government services and also the existence of an established mechanism for recruiting and training.

145 countries Panel, 1984–2011

Government effectiveness, WGIs (World Bank, 2011)

Subjective. Expert assessments and surveys. It captures perceptions of the quality of public services, the quality of the civil service and the degree of its independence from political pressures, the quality of policy formulation and implementation, and the credibility of the government’s commitment to such policies. Aggregating components from various sources. Continuous, original scale: -2.5 to 2.5.

202 countries Panel, 1996–2011

Bureaucratic compensation, career opportunities and meritocratic recruitment – Evans and Rauch’s (1999, 2000)

Subjective. Experts’ survey (academics and non) answering questionnaires on ‘Career Opportunities’, ‘Bureaucratic compensation’ and ‘Meritocratic recruitment’. The three measures are equal-weight indices of a subset of questions eliciting evaluations on recent history (roughly 1970–1990 period), ranging all from 0 to 1.

35 less developed economies

Cross-section, 1970–1990

Quality of public administration – Country Policy and Institutional Assessments (World Bank, 2002)

Subjective. Expert assessment of the extent to which civilian central government staffs (including teachers, health workers, and police) are structured to design and implement government policy and deliver services effectively.

77 less developed economies

Panel, 2005–2011

Legal capacity Steering capability, BTI, Bertelsmann Foundation (2011)

Subjective. Expert assessment evaluating to what extent the political leadership sets and maintains strategic priorities; how effective the government is in implementing reform policy; how flexible and innovative the political leadership is; and if the political leadership learns from past errors.

119 less developed economies

Cross-section, 2006

Quality of Legal System and Property rights, Fraser Institute

Subjective assessment combining survey and exerts’ opinions, ranging between 1 and 10; a higher score corresponds to a stronger protection of private property rights.

139 countries Panel, 1970–2008

Rule of law, WGI (World Bank, 2011)

Subjective. Expert assessments and surveys. Aggregating components from various sources. Continuous, original scale: -2.5 to 2.5. It captures perceptions of the extent to which agents have confidence in and abide by the rules of society, and in particular the quality of contract enforcement, property rights, the police, and the courts, as well as the likelihood of crime and violence.

202 countries Panel, 1996–2010

Rule of law, ICRG (2012) Subjective. It reflects the degree to which the citizens of a country are willing to accept the established institutions to make and implement laws and adjudicate disputes, its scores evaluate soundness of political institutions, the strength of the court system, and the provisions for an orderly succession of power, as opposed to a tradition depending on physical force or illegal means to settle claims.

145 countries Panel, 1984–2011

Transparency and accountability Right to Information, and Freedom of the Media, Global Integrity (2011)

Both objective and subjective. Expert assessment and surveys of whether laws exists on the books, on whether citizens have the legal right to information, and whether the freedom of the media is guaranteed, and whether in practice, this is the case. From a scale of 0 to 100.

31 countries Panel, 2006–2011

Open Budget Survey, International Budget Partnership (2012)

Subjective, expert assessment of the degree to which country budgets are transparent, and the extent of civil society and citizen budget monitoring

100 countries Panel, 2008, 2010, 2012

Source: authors’ compilation.

David Hulme, Antonio Savoia and Kunal Sen 90

to move closer to the advanced economies. But the sub- sequent worsening slows this process, although some convergence seems to have occurred. The QoLSSPR pre- sents a similar evolution across regions. The group of countries that has improved governance quality most compared to its initial level is the MENA region (followed by Latin America), in terms of the QoLSSPR, and Asia (fol- lowed by Latin America), in terms of the QoG. Note also that in both cases the transition economies have experi- enced a significant decrease in governance quality after the end of the Cold War.

Apart from providing some stylised facts, the evidence in this section illustrates the difficulties faced by policy makers wishing to monitor governance for the post-2015 development agenda. Figure 1 reveals that changes in the quality of governance and legal structure and prop- erty rights are relatively slow. Changes in governance quality originate from institutional changes. These are

long-run phenomena that are best monitored with rela- tively low frequency data. Attempts to measure such variables on an annual basis may be as likely to change because of measurement error as much as substantive change. This suggests that monitoring of such indicators might be best framed as every five years (and not annu- ally) or as a three-year rolling average.

Finally, if 2005 is selected as the ‘start’ of the monitor- ing period for achieving post-2015 goals (as was the case with the MDGs with a 1990 ‘start’ for goals set in 2000), then the only available database that can provide mea- sures for all the UN’s 193 member countries, and for three governance dimensions identified here, is the World Governance Indicators (World Bank, 2011). How- ever, among the limitations of such database, one would still have to address concerns of comparability over time (see Arndt and Oman, 2006), as the secondary data sets they draw from have changed over time. Data from com-

Table 4. Governance quality the world around 2000–2010

Panel (a): Quality of legal structure and security of property rights index

Year 2000 2005 2010

Whole sample Mean 5.83 5.85 5.60 CV 0.33 0.30 0.29 N 123 139 142

Advanced economies Mean 8.34 8.17 7.64 CV 0.14 0.11 0.12 N 30 30 30

Developing economies Mean 4.87 5.05 4.84 CV 0.27 0.28 0.27 N 78 86 87

Transition economies Mean 5.82 5.73 5.69 CV 0.14 0.17 0.12 N 15 23 25

Panel (b): Quality of Government index

Whole sample Mean 5.65 5.28 5.37 CV 0.36 0.39 0.38 N 140 140 139

Advanced economies Mean 8.55 8.42 8.44 CV 0.14 0.14 0.13 N 30 30 30

Developing economies Mean 4.67 4.24 4.37 CV 0.29 0.30 0.28 N 87 87 87

Transition economies Mean 5.45 5.05 5.06 CV 0.29 0.22 0.23 N 23 23 22

Notes: data is from Qwartney et al. (2013) and Teorell et al. (2013). Higher values indicate greater governance quality. The statistics reported are the simple average (Mean), the coefficient of variation (CV) and the sample size (N). The trends are very similar also when the same statistics are calculated keeping the sample size equal to the one in the initial year and constant over time. Countries’ classi- fication follows the IMF system: based on per capita income level, export diversification and degree of integration into the global financial system (http://www.imf.org/external/pubs/ft/weo/2011/01/weodata/groups.htm, accessed on 25/6/2013).

The Post 2015 Development Agenda 91

mercial organisations is only available on approximately 140 of the UN’s 193 member countries. Moreover, the possibility of reconstructing the data for missing coun- tries is quite limited, if not impossible, for measures adopting a subjective approach.

3. Monitoring governance: which way? Options and choices

This section first reflects on the challenges facing mea- suring and monitoring governance: finding a ‘politically acceptable’ dimension(s) of governance, which is consis- tent across countries and over time. The second task of this section is to set the scene for the long term, i.e., developing the capabilities for comparative and routin- ised production of governance measure in UN member countries.

Thinking short term

The post-2015 development agenda, following the results-based management principles that underlay the MDGs, seeks to have ‘SMART’ goals and targets – specific, measurable, attainable (but stretching), relevant and time-bound (Hulme, 2010). For the contemporary timeta- ble (i.e., 2015), which requires a baseline without having the time to develop new sources, monitoring governance must therefore rely on one or more existing measures and databases. Apart from the methodological and data quality problems discussed earlier, this approach presents a number of further challenges.

First, most governance databases do not include a sig- nificant number of developing countries. Apart from the Worldwide Governance Indicators (WGIs), a significant number of available governance measures, especially those produced by political risk consultancies for a clien-

tele of foreign investors (e.g., the ICRG), are not comprehensive. Apart from coverage problems, using commercial organisations data may also raise issues of legitimacy, as they reflect solely the views of the busi- ness community.

Second, as Kauffmann and Kraay (2008) have stressed, governance measures can be subject to measurement error as the ‘true’ concept of governance one would like to measure is difficult to define. Therefore assessing spe- cific governance aspects in different countries could face problems of comparability across countries and over time. Even the most trusted measures are not immune to this. However, future empirical analysis could explicitly examine this problem, so shedding further light on the degree to which measurement error and conceptualisa- tion may shape changes in a measure.7

Third, one should reflect on which governance dimen- sions and measures should be included. There are two ways to approach this issue. One could argue that good governance has an intrinsic value in itself, similar to goal 2 in the post-2015 goals proposed by the HLP, which is on the empowerment of girls and women. Such an approach takes the Universal Declaration of Human Rights as the basis for good governance, which as the HLP report notes, ‘sets out the fundamental freedoms and human rights that form the foundations of human devel- opment’ (United Nations, 2013, p. 30). Or one could argue that good governance has instrumental value, and that improvement in governance quality has tangible effects on both material and nonmaterial dimensions of eco- nomic development. For the former, measures of gover- nance that capture the nature of state–society relations, or of the degree of state legitimacy and accountability, would take precedence in the development of indicators for the post-2015 goals. For the latter, a good starting point is to base such a choice on the empirical literature

Figure 1. Governance quality time paths by level of development.

David Hulme, Antonio Savoia and Kunal Sen 92

using governance measures to estimate their effects on development outcomes. Findings from econometric analyses at cross-country level in this area are mainly aimed at explaining economic growth and national income levels, focusing on the contracting and legal envi- ronment, suggest that protection of private property rights is positively and robustly associated with national income levels. However, even if most would agree that property rights institutions are crucial to get incentives right, protecting private property rights represents a polit- ical challenge. This literature is not clear on whose prop- erty rights one should protect (e.g., peasants or landlords, capitalists or workers, foreign or domestic investors, etc.).8

Moreover, other important development outcomes, such as inequality, health, education and poverty, have received scant attention so far within this line of research.

Further recent research highlighting the instrumental value of governance, building on the well-established liter- ature on developmental states (e.g., Evans, 1995; Evans and Rauch, 1999; and the collection of articles in Lange and Rueschemeyer, 2005), increasingly recognises the importance of state capacity as a fundamental ingredient for economic development. Approaching governance from this angle would suggest that the focus in the post-2015 goals should be on indicators that capture the administra- tive and legal capabilities of states. However, this still poses a significant measurement challenge, as there is no universally accepted measure of state administrative and legal capabilities. Existing measures such as the WGIs, the ICRG measure of bureaucratic quality or the Evans-Rauch measure (which captures the Weberian properties of the bureaucracy) have both strengths and weaknesses. The WGIs are noncomparable over time as recalled in the pre- vious section (as well as not being very clear whose opin- ions they represent). The ICRG and the Evans-Rauch measures are perception-based and depend on the opin- ions of a limited set of experts. As Fukuyama (2013) has argued, the Evans-Rauch measure is the closest to what we understand by state capacity – ‘the government’s abil- ity to make and enforce rules, and to deliver services’ (Fukuyama 2013, p. 387). Under this definition, governance is about ‘the performance of agents in carrying out the wishes of principals, and not about the goals that princi- pals set’ (Fukuyama 2013, p. 387). While the Evans-Rauch measure may be the most desirable from a theoretical standpoint (if we agree with Fukuyama’s definition), it is handicapped by the lack of time-series data, and the very limited coverage of countries (30 countries). One impor- tant issue here for further discussion is that if indeed we were to base a measure of governance on the Evans-Rauch approach, how would we go about conducting the expert surveys which form the basis of the measure, and how can we make sure that most, if not all, developing countries are covered by this measure?

Thinking long term: towards 2030

The idea of setting governance goals for the post-2015 development agenda, and subsequently monitoring them has important implications for the long-term devel- opment of comparative governance measures that are recognised as authoritative by all (or at least the vast majority) of UN member states. Including governance goals in the post-2015 development agenda has poten- tial advantages for the evolution and institutionalisation of governance statistics; but, it also has dangers.

On the positive side, the inclusion of governance goals (or targets or indicators) would increase the pressure on governments, bureaucracies, professionals/researchers and civil society to collect relevant data and improve the quality of such data. Arguably, the greater availability of such data would lead to a greater focus on improving governance.

On the negative side, the rapid selection of a measure(s) to meet the 2015 deadline might:

• Lead to the selection of a sub-optimal measure from ‘what is available’. This would mean that the interpre- tation of changes in governance in the future would be challenged both technically (the measure is flawed) and politically (the measure is ideologically biased against some countries).

• Damage the long-term evolution of a professional cadre of ‘governance statisticians’; of widely accepted standards and measures for governance; and, the insti- tutionalisation of governance measures as a routine part of national and international data collection and analysis.

In an ideal world, those engaged in setting the post- 2015 development agenda would carefully assess the trade-offs of focusing on the short-term task of identify- ing measures for 2015 against the long-term task of insti- tutionalising top quality governance statistics across the world. In the world we live in, leaders in this field may need to focus on developing ‘the best measures we can for 2015’ while setting in motion processes that will pro- mote the institutionalisation of governance statistics longer term. One ‘governance target’ would be that by 2020 all UN member states could produce a basic set of governance statistics that meet an international stan- dard.9 One of the great successes of the UN system – but a ‘quiet success’ – has been its contribution to the evolution of globally accepted statistical measures, qual- ity standards, statistical professionals and national statisti- cal capacities (Ward, 2004). The quality of these national measures could be partly assessed by independent ana- lysts comparing what national statistical measures with the independent measures produced by international groups.

The Post 2015 Development Agenda 93

4. Approaches to setting governance goals

Finally, mention must be made about the different ways in which governance goals/targets/indicators could be set and the relative strengths and weaknesses of these approaches. The MDGs used a number of different types of target.10

1. Percentage reductions/improvements in outcomes – Most common were percentage reductions in bad outcomes (e.g., halving income poverty, reducing child mortality by two-thirds) partially based on stretching (i.e., accelerating) the pre-existing rate of improvement in such indicators. For governance mea- sures, for which there is such limited data on histori- cal rates of change, this approach has limited relevance.

2. Universal outcome achievement – Also common was the universal achievement of some targets by 2015 (e.g., universal primary education, elimination of gender dis- parities in education, full employment, universal access to reproductive health). For governance measures, con- ceptualising universal achievements is highly problem- atic: what would ‘universal accountability’ or ‘total transparency’ or ‘full property rights’ actually mean?

3. Absolute outcome achievement – Less common, and rather strange because of its arbitrariness, was the setting of absolute global targets (e.g., significantly improving the lives of 100 million slum dwellers). Given the existing dissatisfaction with these MDG measures, there seems to be little point in pursuing such an approach, as the justification of such tar- gets would have no (or very limited) technical basis.

4. Process-based targets – There were also a number of ‘process-based’ targets for issues that were hard to quantify and/or were politically controversial. These did not set outcome targets but called for improved national and/or global processes (e.g., the integration of sustainable development principles into national poli- cies, the development of a fairer global trading and financial system, action to address the needs of the least developed countries). Such an approach might be possible for some governance targets but, learning from the MDG experience, actual targets and completion dates would need to be specified if they are to encour- age countries (or the international community) to accel- erate progress in improving important processes. For governance targets, one could also identify at

least two other approaches to setting targets. 5. Minimum standard with continuous improvement –

That a universal minimum standard be achieved by a set date but that all countries should be continuously improving on their achievement (so that all countries achieve the minimum target but no country can

‘relax’ simply because that minimum standard has been achieved). As an example, by 2030 all countries achieve a target of 80 per cent of social transfer recip- ients reporting ‘no corruption’ when accessing trans- fers and, for all countries that have achieved this target, continued reductions in reports of corruption on an annual basis.

6. National target-setting – That all countries agree to a goal but that some form of inclusive, national deci- sion-making process sets the actual target (so that tar- gets are not ‘imposed from above’). For example, a UN target that all countries are to reduce recipient reported levels of social transfer corruption on an annual basis but the specific rate of reduction (5 per cent or 10 per cent per annum) is to be determined independently by each national legislature based on a national debate on what is desirable and feasible in that specific context.

Careful consideration will need to be given to the issue of what approaches to goals and target setting are best for governance. Given that many governance goals and targets are about improving processes, approaches (4), (5) and (6) are the logical preference. In particular, combinations of approaches (5) and (6) are particularly attractive as they could permit the setting of global mini- mum targets at the UN integrated with democratically set national targets. National targets would set either ‘faster’ achievement of the UN global targets or set the rate at which higher levels of target achievement are to be attained). However, given the MDG goal 8 experience, such approaches would have to avoid weak specification that permits them to be side-lined by member states.

5. Conclusions

This paper has offered an overview of the strengths and limitations in current empirical research on governance quality and their implications for measuring, setting and monitoring governance goals and targets in the post- 2015 development agenda. Of particular significance are ongoing debates about whether good governance is good for development and/or, whether good enough governance is the best to which nations can aspire.

It will be important for those engaged in improving governance to think both short term and long term about setting, measuring and monitoring governance goals/targets. We have argued that, in the short term, existing measures on governance quality used in cross- national research can be exploited by policy makers shaping the post-2015 development agenda to capture aspects of legal, bureaucratic and administrative capacity. We have utilised them to provide stylised facts on its evolution. However, such an approach is subject to a number of challenges, e.g., country coverage, data

David Hulme, Antonio Savoia and Kunal Sen 94

comparability and the ideological base of the concepts of governance measured. As a consequence, setting and monitoring governance goals should be seen as planning for the long run. Longer term, policy makers need to think about how the selection of goals/targets for the post-2015 development agenda can go beyond rapidly creating goal 10 of the HLP’s Illustrative Goals and foster the institutionalisation (measures, methods, standards, training, professional accreditation) of high quality gover- nance statistics at both national and international levels. The post-2015 development agenda is only one early step along the path to establishing measures of gover- nance as a routine statistical artefact, as has happened with the economic and social statistics that we take for granted today.

Notes 1. A similar argument can be made for not including the achieve-

ment of human rights as a core component of good gover- nance. While successful institutionalisation and legalisation of human rights are important as ends in themselves in the devel- opment process, these can be seen as neither necessary nor suf- ficient in the delivery of development goods (Nelson, 2007).

2. In economics, thorough surveys on measuring governance are Williams and Siddiqui (2008) and Kauffman and Kraay (2008). Within the public administration scholarship, an effective review of the debate on public sector performance is Van de Walle (2009).

3. Political scientists have produced powerful critiques, lamenting the lack of conceptual clarity and the uncertainty of ratings (Kurtz and Schrank, 2007; Hanson and Sigman, 2013).

4. Recent work by political scientists, such as Hanson and Sigman (2013), use factor analytic methods such as Bayesian latent vari- able analysis to construct composite measures of governance and state capacity from different dimensions of governance. However, as Goertz (2006) notes, the relationship between the indicators of governance used in the factor analytic methods and the concept of governance as broadly understood is often tenuous.

5. See Hulme et al. (2014) for more statistical evidence. 6. The apparent improvement in governance quality measures in

this period needs further investigation and is the subject of a separate paper – see Savoia and Sen (2013). At least in part, this could be because western countries stopped allocating foreign aid to ‘bad’ regimes (for example, Banda in Malawi and Mobutu in the Congo were aid recipients during the Cold War to ensure they did not support the Soviet Union even though donors knew that they were badly governing their respective states).

7. An additional factor limiting both policy and academic research is the short time coverage of existing databases. Unfortunately, no measures have substantial time-series variation. But gover- nance phenomena are persistent and trends should be studied over the long run (see Savoia and Sen, 2014). There is a lot to gain from bringing temporal depth to governance measures in the future. Monitoring and policy design could be better informed by understanding the historical evolution of gover- nance phenomena. Academic research could offer better sup- port to policy makers, if it will be able to draw on time-series variation when the tracing the effects and origins of good governance.

8. See Chang (2011) and Lawson-Remer (2012) for a critical per- spective on institutions and growth.

9. The issue of exactly ‘what’ data national statistical agencies should collect, the methods to be used and ‘how’ international standards could be agreed merits detailed thought but we are not able to cover it in this article. The recent Strategy for the Harmonisation of Statistics in Africa report covers such issues for nongovernance measures (African Union, n.d.).

10. In addition to setting targets the MDGs also informally utilised a comparative performance approach to target achievement. By listing countries that were ‘on’ and ‘off’ track for target achieve- ment a ‘league table’ element was brought into play.

References

Acemoglu, D. and Robinson, J. (2012) Why Nations Fail: The Origins of Power, Prosperity and Poverty. London: Profile Books.

African Union (n.d.) Strategies for the Harmonisation of Statistics in Africa. Addis Ababa, Ethiopia: African union, Statistics Division.

Andrews, M. (2013) The Limits of Institutional Reform in Development. Cambridge: Cambridge University Press.

Arndt, C. and Oman, C. (2006) Uses and Abuses of Governance Indicators. Paris: OECD Development Centre Studies.

Baland, J. -M., Moene, K. O. and Robinson, J. A. (2010) ‘Governance and Development’, in Handbook of Development Economics. Amsterdam: Elsevier, volume 5, pp. 4597–4656.

Bardhan, P. (1999) ‘Democracy and Development: a Complex Relationship’, in I. Shapiro and C. Hacker (eds.), Democracy’s Values. Cambridge: Cambridge University Press.

Bardhan, P. (2005) ‘Institutions Matter, but which ones?‘ Economics of Transition, 13 (3), pp. 499–532.

Bertelsmann Foundation (2011) Bertelsmann Transformation Index [online]. Available from: http://www.bertelsmann-trans formation-index.de/en/bti/ [Accessed 13 June 2013].

Besley, T. and Persson, T. (2011) Pillars of Prosperity: The Political Economics of Development Clusters. Princeton, NJ: Princeton University Press.

Bevir, M. (ed.) (2011) The Sage Handbook of Governance. London: Sage.

Centeno, M. A. (2002) Blood and Debt: War and the Nation-State in Latin America. University Park: Penn State Press.

Chang, H-J. (2011) ‘Institutions and economic development: theory, policy and history’, Journal of Institutional Economics, 7(4), pp. 473–498.

Cingolani, L., Thomsson, K. and de Crombrugghe, D. (2013) ‘Minding Weber More Than Ever? The Impacts of State Capacity and Bureaucratic Autonomy On Development Goals’, UNU-MERIT, Maastricht Working Paper No. 52.

Evans, P. (1995) Embedded autonomy: states and industrial transformation. Princeton, NJ: Princeton University Press.

Evans, P. B. and Rauch, J. E. (1999) Bureaucracy and growth: a cross- national analysis of the effects of ‘Weberian’ state structures on economic growth. American Sociological Review, 64 (5), pp. 748–765.

Fearon, J. D. and Laitin, D. D. (2003) ‘Ethnicity, insurgency, and civil war’, American Political Science Review, 97 (1), pp. 75–90.

Foresti, M., Wild, L., Takeuchi, L. R. and Norton, A. (2014) Governance Targets and Indicators for Post 2015: An Initial Assessment, Working Paper. London: Overseas Development Institute.

Fukuyama, F. (2013) ‘What is Governance?‘ Governance, 26(3), pp. 347–368.

Goertz, G. (2006) Social Science Concepts: An User’s Guide, Princeton, NJ: Princeton University Press.

The Post 2015 Development Agenda 95

Global Integrity (2011) Global Integrity Report [online]. Available from: https://www.globalintegrity.org/downloads/ [Accessed 13 June 2013].

Grindle, M. S. (2004) ‘Good Enough Governance: Poverty Reduction and Reform in Developing Countries’, Governance, 17, pp. 525–548.

Gwartney, J. G., Lawson, R. and Hall, J. (2013) Economic Freedom of the World: 2013 Annual Report. Vancouver: Fraser Institute [online]. Available from: www.freetheworld.com [Accessed 13 June 2013].

Hanson, J. and Sigman, R. (2013) ‘Leviathan’s Latent Dimensions: Measuring State Capacity for Comparative Political Research.’ Paper presented at the World Bank Political Economy Brown Bag Lunch Series, March 21.

Hendrix, C. S. (2010) ‘Measuring state capacity: Theoretical and empirical implications for the study of civil conflict’, Journal of Peace Research, Washington, 47(3), pp. 273–285.

Holmberg, S., Rothstein, B. and Nasiritousi, N. (2009) ‘Quality of Government: What You get’, Annual Review of Political Science, 12, pp. 135–161.

Hulme, D. (2010) Global Poverty: How Global Governance is Failing the Poor. London: Routledge.

Hulme, D., Savoia, A. and Sen, K. (2014) ‘Governance as a global development goal? Setting, measuring and monitoring the Post 2015 Development Agenda’, ESID Working Paper No. 32. Manchester: University of Manchester [online]. Available from: http://www. effective-states.org/working-paper-32/ [Accessed 13 June 2014].

ICRG (2012). ‘International Country Risk Guide Researchers Dataset, Table 3B’. The Political Risk Services Group, third edition, Syracuse, NY: International Country Risk Guide.

Kauffman, D. and Kraay, A. (2008) ‘Governance Indicators: Where Are We, Where Should We be Going?‘ World Bank Research Observer, 23 (1), pp. 1–30.

Kurtz M.J., Schrank A. (2007) ‘Growth and Governance: Models, Measures, and Mechanisms.’, Journal of Politics, 69, 2 (May), pp. 538–554.

Lange, M. and Rueschemeyer, D. (eds) (2005) States and Development: Historical Antecedents of Stagnation and Advance. London: Palgrave Macmillan Press.

Lawson-Remer, T. (2012) ‘Property Insecurity’, Brooklyn Journal of International Law, 38 (1), pp. 145–188.

Lin, Y. L. and Nugent, J. (1995) ‘Institutions and Economic Development’, in J. Behrman and T. N. Srinivasan (eds), Handbook of Development Economics, vol. III. Amsterdam: Elsevier Science.

Mazzuca, S. L. (2010) ‘Access to Power Versus Exercise of Power Reconceptualizing the Quality of Democracy in Latin America’, Studies in Comparative International Development, 45, pp. 334–357.

Mulligan Casey, B., Gil, R. and Sala-i-Martin, X. (2004) ‘Do Democracies Have Different Public Policies than Nondemocracies?’, Journal of Economic Perspectives, 18 (1), pp. 51–74.

Nelson, P. (2007) ‘Human Rights, the Millennium Development Goals, and the Future of Development Cooperation’, World Development, 35 (12), pp. 2014–2055.

Ottervik, M. (2013) ‘Conceptualizing and Measuring State Capacity: Testing the Validity of Tax Compliance as a Measure of State Capacity’, Quality of Government Institute Working Paper no. 20 Gothenburg.

Pritchett, L., Woolcock, M. and Andrews, M. (2013) ‘Looking Like a State: Techniques for Persistent Failure in State Capability for Implementation’, Journal of Development Studies, 49 (1), pp. 1–18.

Rajkumar, A. S. and Swaroop, V. (2008) ‘Public Spending and Outcomes: Does Governance Matter?‘ Journal of Development Economics, 86 (1), pp. 96–111.

Rauch, J. E and Evans, P. (2000) ‘Bureaucratic Structure and Bureaucratic Performance in Less Developed countries’, Journal of Public Economics, 75 (1), pp. 49–71.

Rodrik, D., Subramanian, A. and Trebbi, F. (2004) Institutions rule: the primacy of institutions over geography and integration in economic development. Journal of Economic Growth, 9 (2), pp. 131–165.

Savoia, A. and Sen, K. (2013) ‘Do We See Convergence in Institutions: A Cross-Country Analysis’, Development Economics and Public Policy Working Paper Series No. 33, Manchester: University of Manchester.

Savoia, A. and Sen, K. (2014) ‘Measurement, Evolution, Determinants and Consequences of State Capacity: a Review of Recent Research’, Journal of Economic Surveys, forthcoming.

Sundaram, J. K. and Chowdhury, A. (2012) Is Good Governance Good for Development? London: Bloomsbury Academic.

Tabellini, G. (2005) ‘The Role of the State in Economic Development’, Kyklos, 58(2), pp. 283–303.

Teorell, J., Charron, N., Dahlberg, S., Holmberg, S., Rothstein, B. and Sundin, P. et al. (2013) The Quality of Government Dataset, version 15 May 13. University of Gothenburg: The Quality of Government Institute [online]. Available from: http://www.qog. pol.gu.se [Accessed 13 June 2013].

UNDP (2013) Reflections on social accountability: Catalyzing democratic governance to accelerate progress towards the Millennium Development Goals, New York: UNDP, July. Available at:http://www. undp.org/content/dam/undp/documents/partners/civil_society/ publications/2013_UNDP_Reflections-on-Social-Accountability_EN. pdf [Accessed 13 June 2013].

United Nations (2013) Report of the High-Level Panel on Post2015 MDGs. New York, NY: UN.

Van de Walle, S. (2009) ‘International comparisons of public sector performance: how to move ahead?‘ Public Management Review, 11 (1), pp, 39–56.

Ward, M. (2004) Quantifying the World: UN Ideas and Statistics. Bloomington: Indiana University Press.

Williams, A. and Siddiqui, A. (2008) ‘The Use (and Abuse) of Governance Indicators in Economics: a Review’, Economics of Governance, , 9 (2), pp, 131–175.

World Bank (1992) Governance and Development. Washington, DC: World Bank.

World Bank (2002) ‘Country policy and institutional assessment 2002 assessment questionnaire’ [online]. Available from: http:// siteresources.worldbank.org/IDA/Resources/CPIA2002.pdf [Accessed 13 June 2013].

World Bank (2011) Worldwide Governance Indicators (WGI) project [online]. Available from: http://info.worldbank.org/governance/ wgi/index.asp [Accessed 13 June 2013].

Author Information David Hulme, Professor of Development Studies at the Institute for Development Policy and Management (IDPM), University of Man- chester, and Director of the Brooks World Poverty Institute (BWPI) and the Effective States and Inclusive Development Research Centre (ESID).

Antonio Savoia, Lecturer in Development Economics at the Univer- sity of Manchester and researcher at the Effective States and Inclu- sive Development Research Centre (ESID).

Kunal Sen, Professor of Development Economics at the Institute for Development Policy and Management (IDPM), University of Man- chester, research director of the Effective States and Inclusive Devel- opment Research Centre (ESID) and Professorial Fellow of the Brooks World Poverty Institute.

David Hulme, Antonio Savoia and Kunal Sen 96