metadata: authors: 0: author: Kaufmann,Daniel
1: author: Kraay,Aart C.
2: author: Mastruzzi,Massimo
count: World
docna: 0: docna: Governance matters V: aggregate and
            individual governance indicators for 1996 - 2005
docty: Policy Research Working Paper
subtopic: Investment and Investment Climate,Judicial System Reform,National Governance,Government Policies,Business Environment,International Terrorism & Counterterrorism,Youth and Governance,Governance Indicators,Armed Conflict
teratopic: Macroeconomics and Economic Growth,Governance,Science and Technology Development
abstracts: cdata!: The authors report on the latest version
            of the worldwide governance indicators, covering 213
            countries and territories and measuring six dimensions of
            governance from 1996 until end-2005: voice and
            accountability, political stability and absence of violence,
            government effectiveness, regulatory quality, rule of law,
            and control of corruption. The latest indicators are based
            on hundreds of variables and reflect the views of thousands
            of citizen and firm survey respondents and experts
            worldwide. Although global averages of governance display no
            marked trends during 1996-2005, nearly one-third of
            countries exhibit significant changes [for better or for
            worse] on at least one dimension of governance. Three new
            features distinguish this update. (1) The authors have moved
            to annual reporting of governance estimates. This update
            includes new governance estimates for 2003 and 2005, as well
            as minor backward revisions to biannual historical data for
            1996-2004. (2) The authors are, for the first time,
            publishing the individual measures of governance from
            virtually every data source underlying the aggregate
            governance indicators. The ready availability of the
            individual data sources underlying the aggregate governance
            indicators is aimed at further enhancing the transparency of
            the methodology and of the resulting aggregate indicators,
            as well as helping data users and policymakers identify
            specific governance challenges in individual countries. (3)
            The authors present new evidence on the reliability of
            expert assessments of governance which, alongside survey
            responses, form part of the aggregate measures of governance.
repnme: repnme: Governance matters V: aggregate and
            individual governance indicators for 1996 - 2005
display_title: Governance matters V: aggregate and
            individual governance indicators for 1996 - 2005
listing_relative_url: /research/2006/09/7088636/governance-matters-v-aggregate-individual-governance-indicators-1996-2005
topicv3: Justice m1326106 840,Investment Climate m1326293 405,Governance Indicators m1327488 834,Terrorism m1327775 2467,Business Environment m1586411 2530
publishtoextweb_dt: 2010-07-01T00:00:00Z
historic_topic: Macroeconomics and Economic Growth,Governance,Science and Technology Development
no_of_pages: 109
author_keys: 0: author_key: 90114
1: author_key: 123715
2: author_key: 554549
model_extractions: # WPS4012

## **Governance Matters V: Aggregate and Individual Governance Indicators for 1996–2005**

**Daniel Kaufmann, Aart Kraay, and Massimo Mastruzzi The World Bank**

**Abstract :** This paper reports on the latest version of the worldwide governance indicators, covering 213 countries and territories and measuring six dimensions of governance since 1996 until end-2005: voice and accountability, political stability and absence of violence, government effectiveness, regulatory quality, rule of law, and control of corruption. The latest indicators are based on hundreds of variables and reflect the views of thousands of citizen and firm survey respondents and experts worldwide. Although global averages of governance display no marked trends during 1996-2005, nearly one-third of countries exhibit significant changes—for better or for worse—on at least one dimension of governance. Three new features distinguish this update. (1) We have moved to reporting estimates of governance on an annual basis. In this update we provide new estimates of governance for 2003 and 2005, as well as minor backward revisions to our biannual historical data for 1996-2004. (2) We are for the first time publishing the individual measures of governance from virtually every data source underlying our aggregate governance indicators. The ready availability of the individual data sources underlying the aggregate governance indicators is aimed at further enhancing the transparency of our methodology and of the resulting aggregate indicators, as well as helping data users and policymakers identify specific governance challenges in individual countries. (3) We present new evidence on the reliability of expert assessments of governance which, alongside survey responses, form part of our aggregate measures of governance. The aggregate and underlying individual governance indicators, a new nontechnical booklet describing the data and analysis, and a number of Web-based tools for analysis of the data are available at <u>www.govindicators.org.</u>

World Bank Policy Research Working Paper 4012, September 2006 _The Policy Research Working Paper Series disseminates the findings of work in progress to encourage the exchange of ideas about development issues. An objective of the series is to get the findings out quickly, even if the presentations are less than fully polished. The papers carry the names of the authors and should be cited accordingly. The findings, interpretations, and conclusions expressed in this paper are entirely those of the authors. They do not necessarily represent the view of the World Bank, its Executive Directors, or the countries they represent. Policy Research Working Papers are available online at http://econ.worldbank.org._

> ______________________________________________________________________ 1818 H Street NW, Washington, D.C. 20433. dkaufmann@worldbank.org, akraay@worldbank.org, <u>mmastruzzi@worldbank.org. The Governance Matters series, as well as its Worldwide Governance Indicators, are</u> the output of a research project on governance indicators initiated in the late 1990’s. The opinions expressed here, as well as the worldwide governance indicators themselves, do not reflect the official views of the World Bank, its Executive Directors, or the countries they represent.   We would like to thank Claudio Raddatz for helpful discussions, and  A. Karatnycky, R. Fullenbaum, S. Sarkis, Jim Langston, S. Hatipoglu, D. Cingranelli, D. Richards, R. Writer, M. Gibney, C. MacCormac, E. Zukov, X. Ye, A. Gelb, G. Turner, M. Walsh, D. West, T. Sysler, B. Broadfoot, M. Lagos, A. Lopes-Claros, R. Coutinho, S. Mannan, and D. Cieslikowsky for providing data and answering our numerous questions. The support and collaboration of the World Economic Forum, the U.S. State Department, and the Netherlands Government is appreciated.
# **1.  Introduction**

This paper presents the latest update of our aggregate governance indicators.<sup>1</sup> The indicators measure six dimensions of governance: voice and accountability, political stability and absence of violence, government effectiveness, regulatory quality, rule of law, and control of corruption. They cover 213 countries and territories for 1996, 1998, 2000, and annually for 2002-2005. The indicators are based on several hundred individual variables measuring perceptions of governance, drawn from 31 separate data sources constructed by 25 different organizations. We assign these individual measures of governance to categories capturing key dimensions of governance, and use an unobserved components model to construct six aggregate governance indicators in each period. We present the point estimates of the dimensions of governance as well as the margins of errors for each country and period.

We begin by describing the data used to construct this round of the governance indicators in Section 2. As discussed in more detail below, we have added one new data source in this round. In the interests of greater comparability over time, we have included it in our past estimates as well, and also dropped a few minor data sources we have used in the past but are no longer regularly available. We have also made minor changes to the scaling of our indicators in earlier years in order to make over-time comparisons of the aggregate indicators more robust to year-to-year changes in the composition of the sample of countries included in the indicators. These revisions have resulted in minor changes to our historical biannual data for 1996-2004, and so the new dataset described here supersedes previous releases. Going forward we plan to continue to update our governance indicators on an annual basis, in order to enable a more timely monitoring of governance worldwide. While we recognize that in many countries year-over-year changes in governance are small, by moving to annual data we aim to assist users to spot and monitor those cases where there are substantial changes in the short term.

> 1 This paper is the fifth in a series of estimates of governance across countries.  Each of these papers has reported on data updates as well as new empirical results using the governance indicators Documentation of the previous rounds of the indicators and analytical findings can be found in Kaufmann, Kraay, and Zoido-Lobatón (1999a,b, 2002), and Kaufmann, Kraay, and Mastruzzi (2004, 2005, 2006).  Kaufmann, Kraay, and Mastruzzi (2004) contains a complete description of the statistical methodology underlying the indicators.

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An important innovation with this round of the governance indicators is that we are now able to fully report data from virtually all of our underlying individual sources (on the web), alongside our aggregate indicators, as we have obtained permission from the institutions generating the data to do so. This new feature will be valuable to users interested in unbundling our aggregate indicators for particular countries in order to better understand the factors contributing to our estimates of levels and changes over time in governance. Moreover, even within each of our aggregate governance indicators, the underlying measures provide a wealth of information on different specific sub-dimensions of governance. By making the underlying data readily available we hope to help users identify -- and act upon -- specific governance challenges identified by these indicators in individual countries.

As in the past, we complement our estimates of governance for each country with estimates of margins of error that indicate the unavoidable uncertainty associated with measuring governance across countries. These margins of error have declined over time with the addition of new data sources to our aggregate indicators, and are substantially smaller than for any of the individual data sources. We continue to encourage users of the governance indicators to take these margins of error into account when making comparisons of governance across countries, and within countries over time. We also encourage other producers of governance indicators to be similarly transparent about the imprecision of all types of measures of governance. Our aggregate indicators are sufficiently informative that many cross-country comparisons of governance can result in statistically -- and practically -- significant differences. In fact, using our 2005 indicators, we show that around 60 percent of all cross-country comparisons reveal strongly significant differences, and we also find that nearly onethird of the countries in our sample experience a significant change in at least one dimension of governance between 1996 and 2005. However, in other cases users will find that confidence intervals for governance based on our reported margins of error will overlap, indicating that comparisons are neither statistically -- nor practically -- significant.

We emphasize, however, that the margins of error we report are not unique to our aggregate indicators, nor are they unique to perceptions-based measures of governance on which we rely: measurement error is pervasive among all indicators of 2
governance and institutional quality, including individual indicators as well as so-called ‘objective’ or fact-based ones -- if these are available at all. Unfortunately, typically little if any effort is placed in estimating, let alone reporting, the substantial margins of error in any other source of governance and/or investment climate indicators – objective or subjective, aggregate or individual. A key advantage of our measures of governance is that we are explicit about the accompanying margins of error, whereas in most other cases they are at best left implicit, and often ignored entirely.

In the third section of this paper we consider in detail a particular critique of expert assessments of governance (which account for 23 of our 31 data sources). Some of these expert assessments are produced by commercial risk rating agencies, others by governments and multilateral organizations, and yet others by nongovernmental organizations. We analyze whether each of these data sources provides independent estimates of governance, and if not, the extent to which one set of expert assessments is influenced by the views of other experts. Here we make three points. First, finding evidence of such correlated perception errors is intrinsically difficult. A high correlation in the rankings of two expert assessments could in principle be due either to highly correlated perceptions errors, or alternatively it could due to the fact that both data sources are actually measuring cross-country differences in governance well. Second, under certain reasonable assumptions that we detail below, we can solve this identification problem and separate out the extent to which expert assessments make correlated errors. When we do this, we find at best very weak evidence of correlated perception errors, suggesting that this critique of expert assessments has little empirical basis. Third, we note that even if expert assessments do contain correlated perception errors, this does not imply that we should discard such data sources entirely. Even with correlated errors, expert assessments do contain information about cross-country differences in governance and this information can usefully add to our aggregate governance indicators.

We conclude the paper by summarizing the key findings in this fifth installment of the Governance Matters series and noting the policy implications of our work.

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# **2.  Description of the 2005 Data Update**

In this section we briefly describe the update of our governance indicators for 2005, as well as some minor backwards revisions to the biannual indicators for 19962004. This year we report data for 2003, in order to create a panel of annual observations covering 2002-2005. We also for the first time will be distributing on the web the bulk of data from the individual indicators of governance that underlie our aggregate indicators. We therefore also describe how this data from the individual indicators can be used to aid in the interpretation of the aggregate indicators.

Our methodology has not changed from past years, and a detailed discussion can be found in Kaufmann, Kraay, and Mastruzzi (2004). As before we construct indicators of six dimensions governance:

1. _Voice and accountability (VA)_ , the extent to which a country’s citizens are able to participate in selecting their government, as well as freedom of expression, freedom of association, and free media

2. _Political stability and absence of violence (PV)_ , perceptions of the likelihood that the government will be destabilized or overthrown by unconstitutional or violent means, including political violence and terrorism 3. _Government effectiveness (GE)_ , 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 4. _Regulatory quality (RQ)_ , the ability of the government to formulate and implement sound policies and regulations that permit and promote private sector development 5. _Rule of law (RL)_ , the extent to which agents have confidence in and abide by the rules of society, and in particular the quality of contract enforcement, the police, and the courts, as well as the likelihood of crime and violence 6. _Control of corruption (CC)_ , the extent to which public power is exercised for private gain, including both petty and grand forms of corruption, as well as “capture” of the state by elites and private interests.

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In brief our methodology consists of identifying many individual sources of data on perceptions of governance that we can assign to these six broad categories. We then use a statistical methodology known as an unobserved components model to construct aggregate indicators from these individual measures. These aggregate indicators are weighted averages of the underlying data, with weights reflecting the precision of the individual data sources. Crucially our methodology also generates margins of error for the estimates of governance for each country, which need to be taken into account when making comparisons of governance across countries and over time. We provide details on this approach in the remainder of this section.

# **2.1  Data and Methodology**

As in past years we rely on a large number of individual data sources that provide us with information on perceptions of governance. These data sources consist of surveys of firms and individuals, as well as the assessments of commercial risk rating agencies, non-governmental organizations, and a number of multilateral aid agencies. A full list of these sources is presented in Table 1. For the 2005 round of the data, we rely on a total of 276 individual variables measuring different dimensions of governance. These are taken from 31 different sources, produced by 25 different organizations. Appendices A and B provide a detailed description of each data source, and document how we have assigned individual questions from these data sources to our six aggregate indicators. Almost all of our data sources are available annually, and we use the data only the most recent year in our aggregate indicators. In a few cases, as noted in Appendix B, we use data lagged one or two years if current data are not available.<sup>2</sup> In this round of the governance indicators we have added one new data source, the United States State Department's Trafficking in People Report. It provides country narratives and numerical rankings of countries' policy efforts to prevent trafficking in

> 2 We never use lagged data when current data are available, in order to ensure that our indicators are as timely as possible.  In this respect our approach differs from Transparency International's Corruption Perceptions Index, which in each year uses data from the current and two previous years for some of its sources (GCS, WCY and PRC), although peculiarly it does not follow the same practice for three other annually-available sources (FHT, MIG, and WMO).  As a result the 2005 Corruption Perceptions Index is based on 2005 data from only 10 data sources.  In contrast our Control of Corruption Index is based on 19 data sources, all of which refer to 2005.

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people. Countries are ranked into three tiers, beginning in 2001. We use this tier classification as an ingredient for our Rule of Law indicator, which contains a number of other measures of the prevalence of criminal activity. In addition, a few of the data sources that we have used in the past have either been discontinued, or have not been updated and do not appear likely to be updated in the future on a regular basis. These include the Opacity Factor produced by Price-Waterhouse-Coopers, the USAID/Vanderbilt University Democracy Surveys, the Fundar rankings of budget transparency in Latin America, and the African governance indicators produced by the UN Economic Commission for Africa.<sup>3</sup> To improve the comparability of our estimates of governance over time by having a somewhat more balanced set of sources in each period, we have dropped these measures and recalculated our historical estimates based on this slightly smaller set of data sources. Finally, we have made a number of minor revisions and corrections to the past underlying indicators for 1996-2004. Together these revisions in virtually all cases result in only minor changes in our earlier estimates of governance.<sup>4</sup> Our data sources reflect the perceptions of a very diverse group of respondents. Several are surveys of individuals or domestic firms with first-hand knowledge of the governance situation in the country. These include the World Economic Forum’s Global Competitiveness Report, the Institute for Management Development’s World Competitiveness Yearbook, the World Bank’s business environment surveys, and a 3 In the 2004 update of the governance indicators we relied on data from 37 sources produced by 31 organizations. Our number of organizations falls by six of our deletion of four sources, one of which was produced by two organizations (the Latin America surveys produced by USAID and Vanderbilt University), and also because Global Insight which produced the DRI ratings in 2004 has since also acquired World Markets Online, another of our sources. The number of sources falls by six because (i) we have dropped four sources, (ii) we now count three separate Gallup surveys performed in different years as one source, (iii) we no longer separately count the GCS survey of Africa in 1998 as a separate source but merge it with the GCS for all other countries in that year, and (iv) we add one new source as described in the text, for a net change of six. 4 The correlation between our revised and updated estimates is greater than 0.99 for all but four of the series affected by our backward revisions. Our revised data for GE in 1996 is correlated with the old data at 0.98. In 2004 our main revision was to use the final 2004 CPIA scores, which were unavailable at the time of the release of the 2004 indicators. This had a slightly greater effect on our estimates for PV, RQ, and CC, whose correlations with the old indicators range from 0.96 to 0.97. In only one small territory did our revisions result in a change in an estimate of governance that was statistically significant (in the sense of the 90% confidence intervals for the two estimates not overlapping). This is for the small island state of Tuvalu (which has very few sources) for CC in 2004, where our revisions resulted in a significant improvement for that country.

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variety of global polls of individuals conducted by Gallup, Latinobarometro, and Afrobarometro. We also capture the perceptions of country analysts at the major multilateral development agencies (the European Bank for Reconstruction and Development, the African Development Bank, the Asian Development Bank, and the World Bank), reflecting these individuals’ in-depth experience working on the countries they assess. Other data sources from NGOs (such as Amnesty International, Reporters Without Borders, and Freedom House), as well as commercial risk rating agencies (such as the Economist Intelligence Unit and DRI-McGraw Hill) base their assessments on a global network of correspondents typically living in the country they are rating.

As in our past work, we combine the many individual data sources into six aggregate governance indicators. The premise underlying this statistical approach should not be too controversial – each of the individual data sources we have provides an imperfect signal of some deep underlying notion of governance that is difficult to observe directly. This means that as users of the individual sources, we face a signalextraction problem – how do we isolate the informative signal about governance from each individual data source, and how do we optimally combine the many data sources to get the best possible signal of governance in a country based on all the available data? The statistical procedure we use to perform this aggregation, known as the unobserved components model, is described in detail in our past work (see for example Kaufmann, Kraay and Mastruzzi (2004)). The main advantage of this approach is that the aggregate indicators are more informative about unobserved governance than any individual data source. Moreover, the methodology allows us to be explicit about the precision – or imprecision – of our estimates of governance in each country. As we discuss in more detail throughout the paper, this imprecision is not a consequence of our reliance on subjective or perceptions data on governance – rather imprecision is an issue that should be squarely addressed in all efforts to measure the quality of governance.

An important innovation this year is that we have obtained permission from the majority of our data sources to report the underlying indicators that go into our aggregate indicators. The sources we have made available on our website are noted in Table 1. A number of our data sources, such as Freedom House and the Heritage Foundation have always been publicly available through the publications and/or websites of their 7
respective organizations. Several of our other sources provided by commercial risk rating agencies and commercial survey organizations have only been available for a fee. In the interests of greater transparency, these organizations have kindly agreed to allow us to report their proprietary data in the form in which it enters our governance indicators. As discussed in detail in Appendix A and B, we in some cases use a simple average of multiple questions from the same source as an ingredient in our governance indicators. On our website we report either the individual question, or the average of individual questions, from each source that enters into our governance indicators. All the individual variables have been rescaled to run from zero to one, with higher values indicating better outcomes.

The only data sources we have not been able to obtain permission to publicize fully are the World Bank's Country Policy and Institutional Assessment, and the corresponding internal assessments produced by the African Development Bank and the Asian Development Bank. We do note however that starting in 2002 the World Bank has begun publishing limited information on its CPIA assessments on its external website. For the years 2002-2004 the overall CPIA ratings are reported by quintile for the low-income countries eligible to borrow from the International Development Association (IDA), the soft-loan window of the World Bank. For the data covering 2005, the individual country scores for the IDA allocation factor, a rating that reflects the CPIA as well as other considerations, has now become publicly available. The African Development Bank's CPIA ratings are also publicly available by quintile only since 2004, and the Asian Development Bank has committed to publicly disclosing its ratings starting in 2005.<sup>5</sup> Finally, we have this year slightly altered our presentation of the aggregate indicators in order to make them more comparable over time. In our aggregation procedure, we assume that the distribution of governance across countries follows a normal distribution in each period, with mean zero and standard deviation of one. This is simply a convenient choice of units for governance, and would be entirely innocuous were it not for two considerations. First, as we have discussed in our previous work, it is

> 5 For the African Development Bank see <u>http://www.afdb.org/pls/portal/docs/PAGE/ADB_ADMIN_PG/DOCUMENTS/OPERATIONSINFOR MATION/AFDB_2004_RATINGS_FINAL.PDF, and for the Asian Development Bank see http://www.adb.org/Documents/Reports/ADF/2005-adb-cpa.pdf.</u>

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possible that there are trends in world-wide averages of governance, either improvements or declines. If this is the case, it would inappropriate to rescale the mean of governance to zero in each period as we do. However, as we have documented in the past, and also later in this paper, we do not find much evidence from our underlying individual data sources that there are trends in global averages in governance. As a result, we think the assumption of a constant global average of governance in our aggregate indicators is reasonable.

The second consideration is that the sample of countries covered by our governance indicators has expanded since 1996, and quite considerably for some of our indicators (see Table 2 and the accompanying discussion in the next subsection). If the new countries added each year were broadly representative of the worldwide distribution of governance, this too would pose no special difficulties. However, for some of our indicators, we find that countries added in later years score on average somewhat higher than countries that were continuously in the sample. This in turn means that it would be inappropriate to impose a global average governance score of zero in earlier periods for the smaller set of countries for which data is available, since our earlier estimates did not include the better-than-average performers added later. It also means that some countries in our aggregate indicators in the earlier years showed small declines in some dimensions of governance over time that were driven by the addition of betterperforming countries in later years.

We address this issue with a simple re-scaling of the aggregate governance indicators. We take our 2005 indicators which, depending on the governance component, cover between 203 and 213 countries as representative of the world as a whole, as a benchmark. Consistent with our choice of units for governance, the estimates for 2005 have zero mean and standard deviation of one across countries. We next consider the countries that were added in 2005 relative to 2004. We then adjust the world-wide average score in 2004 so that it would have a mean of zero _had we included the 2005 scores for those countries added in 2005 relative to 2004_ . As a specific example consider Political Stability and Absence of Violence, where between 2004 and 2005 we have added 6 countries, mostly small islands in the Caribbean. Their average score in 2005 is 1.07 which is considerably above the world average of zero. We therefore slightly lower the scores of all of the 207 countries in 2004 by a factor of 0.03 in 9
order to improve the comparability of their scores with 2005.<sup>6</sup> We then continue backwards in time in the same way to adjust the 2003 data. In particular, we look at the entrants to the sample in 2003 relative to 2005, and compute the average score for these countries, using either the 2004 estimates if they are available, or else the 2005 estimates if the country shows up in the sample only in 2005. We then again adjust the 2003 estimates so that a hypothetical sample consisting of the 2003 adjusted scores as well as either the 2004 or 2005 scores of the entrants, whichever is closer to 2003, would have a mean of zero. We continue in this way back to 1996.

Four points are worth noting about this new adjustment.

- Since we adjust the scores for all countries in a given year and indicator by the same amount, this adjustment has no effect on the relative positions of countries on that indicator in that year.  It does however make countries' scores more comparable over time, since the adjustment is designed to remove the effect of adding new countries on the scores of countries already in the sample.

- As a consequence of this adjustment, global averages of the adjusted data show moderate trends over time, mostly improvements.  The most extreme case is that of Political Stability and Absence of Violence where the average across all countries in the sample improves from -0.15 in 1996 to 0 in 2005.  It is important to remember though that this improvement does not reflect an average

6 The adjustment factor for the mean is simply − y T ⋅ (NT − NT−1)/ NT−1 where NT is the number of

> countries with data in period T and y T is the average score of the additional countries in period T.  The higher is the average score of the new entrants and/or the more new entrants there are, the more we lower the mean in the previous period.   This ensures that a hypothetical sample consisting of our year T-1 adjusted scores for all countries combined with the year T scores for the countries added in year T relative to T-1 would have a mean of zero and standard deviation of one. We also adjust the standard deviation of the year T scores to ensure that the standard deviation of this hypothetical sample would be one.  We do this by multiplying the scores (and the standard errors) for each country in 2004 by a factor of

estimates of governance in year T for the new entrants to the sample in period T. The greater is the dispersion in the scores of new entrants, the more we need to reduce the dispersion of scores in the previous years. The adjustments to the standard deviation are in all cases quite small, ranging from 0.96 to 1.08 with a mean adjustment factor of 1 (i.e. no adjustment at all). The adjustments to the means are somewhat higher, particularly in earlier periods where we had smaller samples, and range from -0.20 to 0.01. The interested reader can retrieve all of these adjustment factors simply by calculating the mean and standard deviation of our governance indicators in each period.

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improvement for all countries in the world. Rather it reflects the changing composition of our sample since the new entrants during this period have had above-average performance in this dimension of governance. In fact, there is no evidence of any significant improvement in the world average for the country sample that has been consistently covered over time, as we discuss in more detail below.

- This rescaling of the aggregate indicators is perfectly consistent with the unobserved components model that we use to construct the aggregate indicators in each period.  In particular, rescaling the mean and standard deviation of the aggregate indicators in the way that we do is equivalent to imposing slightly different means and standard deviations of governance as a choice of units in each of the periods.  And as we have argued this changing choice of units is an appropriate way to correct for changes in the composition of countries covered by the indicators over time.

- Finally, for some purposes it is useful to look just at countries' percentile ranks rather than their scores on our governance indicators.  Without similar adjustments these percentile ranks too would not be fully comparable over time as they too would be influenced by new entrants.  Thus, we also perform such adjustment to the percentile ranks, and when we report countries' scores in the form of percentile ranks on our website, we compute the percentile ranks based on a sample consisting of the actual data we have for that indicator and year, combined with imputed data from the nearest year as described above.

# **2.2  Estimates of Governance 1996-2005**

In Appendix C we report the aggregate governance indicators, for all countries, for each of the six indicators. The aggregate indicators, as well as almost all of the underlying indicators, are available at www.govindicators.org. The units in which governance is measured follow a normal distribution with a mean of zero and a standard deviation of one in each period. This implies that virtually all scores lie between -2.5 and 2.5, with higher scores corresponding to better outcomes.<sup>7</sup> This also implies that our aggregate estimates convey no information about trends in global averages of 7 For a handful of cases, individual country ratings can exceed these boundaries when estimates of governance are particularly high or low.

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governance, but they are of course informative about changes in individual countries’ relative positions over time. Below we discuss the information conveyed by some of our individual indicators regarding trends over time in global averages of governance.

Table 2 summarizes some of the key features of our governance indicators. In the top panel we show the number of countries included in each of the six indicators and seven periods. In 2005 the Political Stability and Absence of Violence indicator covers the largest set of 213 countries, with the other sources covering between 203 and 210 countries.<sup>8</sup> Over time, there has been a steady increase in the number of sources included in each of our indicators. This increase in the number of data sources is reflected in an increase in the median number of sources available per country, which, depending on the governance component, ranges from four to six in 1996, and from seven to eleven in 2005. Thanks to the increase in sources, the proportion of countries in our sample for which our governance estimates are based on only one source has also declined considerably, to an average of only 7 percent of the sample in 2005.

An important consequence of this expanding data availability is that the margins of error for the governance indicators have declined, as shown in the final panel of Table 2. Depending on the governance component, in 1996 the average (for all countries) of the standard error<sup>9</sup> ranged from 0.28 to 0.40. In 2005 the standard error ranges from 0.17 to 0.21 for five of our six indicators, while for Political Stability it is 0.28. These declines in margins of error illustrate the benefits in terms of precision of constructing composite indicators based on an expanding number of data sources incorporating as much information as possible. Of course, since our aggregate indicators combine information from all of these sources, they have greater precision than any individual underlying data source. Looking across all seven time periods, the median standard

> 8 A few of the entities covered by our indicators are not fully independent states (Puerto Rico, Hong Kong, West Bank/Gaza, Martinique, and French Guyana). A handful of very small independent principalities (Monaco, San Marino, and Andorra) are also included. For stylistic convenience all 215 entities are often referred in this paper as “countries”.

> 9 As described in detail in Kaufmann, Kraay and Mastruzzi (2004), the output of our aggregation procedure is a distribution of possible values of governance for a country, conditional on the observed data for that country.  The mean of this conditional distribution is our estimate of governance, and we refer to the standard deviation of this conditional distribution as the “standard error” of the governance estimate.

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error of the individual data sources for the governance indicators was substantially higher at 0.58, with a 25th percentile of 0.44 and a 75th percentile of 0.85.<sup>10</sup> Despite this increase in precision as a benefit of aggregation relative to individual data sources, and as emphasized in our previous papers, the margins of error for the aggregate governance indicators remain non-trivial. We illustrate this point in Figure 1. In the two panels of Figure 1, we organize countries in ascending order according to their point estimates of governance in 2005 on the horizontal axis, and on the vertical axis we plot the estimate of governance and the associated 90% confidence intervals. These intervals indicate the range in which it is 90 percent likely that the true governance score falls.<sup>11</sup> We do this for two of the six governance indicators, political stability, and control of corruption. The size of these confidence intervals varies across countries, as different countries appear in different numbers of sources with different levels of precision. The resulting confidence intervals are substantial relative to the units in which governance is measured. From Figure 1 it should also be evident that many of the small differences in estimates of governance across countries are not likely to be statistically significant at reasonable confidence levels, since the associated 90 percent confidence intervals are likely to overlap. For many applications, instead of merely observing the point estimates, it is therefore more useful to focus on the _range_ of possible governance values for each country (as summarized in the 90% confidence intervals shown in Figure 1), recognizing that these likely ranges often overlap for countries that are being compared with each other.<sup>12</sup> This is not to say however that the aggregate indicators cannot be used to make cross-country comparisons. To the contrary, there are a great many pairwise country 10 In an earlier paper (Kaufmann, Kraay and Mastruzzi (2004)) we showed how to obtain margins of errors for other objective measures of governance and found that they were as large, or larger than those of our individual subjective measures. This underscores the fact that all efforts to measure governance involve margins of error, often non-trivial.

11 A x% confidence interval for governance can be obtained as the point estimate of governance plus or minus the standard error times the (100-x)/2<sup>th</sup> percentile of the standard normal distribution. For example, the 90% confidence intervals we report throughout the paper are the point estimate plus or minus 1.64 times the standard error.

12 Of course, asking whether 90% confidence intervals overlap or not corresponds to a hypothesis test at a significance level that is more stringent than 10%. The assumptions underlying our statistical model imply that the standard error of the difference between two country scores is the square root of the sum of the squared standard errors of the two sources, which is always smaller than the sum of the two standard errors themselves. It is more convenient -- and more conservative -- for users to simply inspect confidence intervals and see whether they overlap.

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comparisons that do point to statistically significant, and likely also practically meaningful, differences across countries. Our 2005 Control of Corruption indicator for example covers 204 countries, so that it is possible to make 20,706 pairwise comparisons of corruption across countries using this measure. For 64 percent of these comparisons, 90% confidence intervals do not overlap, signaling quite highly statistically significant differences across countries. And if we lower our confidence level to 75 percent, which may be quite adequate for many applications, we find that 74 percent of all pairwise comparisons are statistically significant. The benefit of improved precision of aggregate indicators with increased data availability over time can also be clearly seen from this calculation. Consider our 1996 Control of Corruption indicator, which was based on a median of only four data sources per country, as opposed to a median of eight sources in 2005, implying substantially higher margins of error in 1996. Of the 11,476 possible pairwise comparisons in 1996, only 45 percent are significant at the 90% confidence level, and only 58 percent at the 75 percent confidence interval.

We can also use this calculation to illustrate the benefits of making comparisons based on aggregate indicators that are more informative than individual indicators. Again for Control of Corruption in 2005, consider one of our individual data sources, DRI, which has an estimated standard error of 0.52, corresponding to the median of the standard errors of all of our sources for corruption in 2005. Note that this is of course much higher than the standard error of the typical country in the aggregate indicator in 2005, which is 0.19. Had we based our estimates of governance on just this one data source, only 39 percent of cross-country comparisons would have been significant at the 75 percent level, and only 20 percent at the 90 percent level. Although rarely acknowledged explicitly, all other measures of governance are subject to margins of error as well, which in our past work we have shown to be at least as large as those we calculate for our individual and aggregate indicators. This underscores the need for caution in making cross-country comparisons with any type of governance indicator.

# **2.3  Changes over Time in Governance at the Country Level**

We now turn to the changes over time in our estimates of governance in individual countries. In Kaufmann, Kraay, and Mastruzzi (2005) we provided a detailed analysis of how to perform statistical inference on changes over time in the aggregate 14
governance indicators. Here we simply provide a brief description of changes over time based on the latest update of the indicators. Figure 2 illustrates these changes for two selected governance indicators over the period 2002-2005, Political Stability and Absence of Violence/Terrorism, and Control of Corruption. In both panels, we plot the 2002 score on the horizontal axis, and the 2005 score on the vertical axis. We also plot the 45-degree line, so that countries above this line correspond to improvements in governance, while countries below the line correspond to deteriorations in governance. The first feature of this graph is that most countries are clustered quite close to the 45degree line, indicating that changes in our estimates of governance in most countries are relatively small over the three-year period covered by the graph. A similar pattern emerges for the other four dimensions of governance (not shown in Figure 2), and, not surprisingly the correlation between current and lagged estimates of governance is even higher when we consider shorter time periods than the three-year period shown here.

In Figure 2 we have labeled those countries for which the change in estimated governance over the 2002-2005 period is sufficiently large that the 90% confidence intervals for governance in the two periods do not overlap.<sup>13</sup> Examples of such more substantial changes in governance between 2002 and 2005 include significant declines in Political Stability and Absence of Violence/Terrorism in Thailand, Bolivia and Bangladesh, and improvements in Georgia. For Control of Corruption countries such Turkey and Georgia see significant improvements. Countries such as Kenya, Liberia, Ukraine, and Iraq all improve substantially on Voice and Accountability, while Singapore and Russia register declines.

In Table 3 we provide more detail on all of the large changes in our six governance indicators over the period 2002-2005. The first three columns report the level of governance in the two periods, and the change. The next three columns report on how the underlying data sources move for each case. In the column labeled “Agree” we report the number of sources available in both periods which move in the same direction as the aggregate indicator. The columns labeled “No Change” and “Disagree”

> 13 While this is not a formal test of the statistical significance of changes over time in governance, it is a very simple and transparent rule of thumb for identifying large changes in governance.  In a Kaufmann, Kraay, and Mastruzzi (2005, 2006) we have shown in more detail how to assess the statistical significance of changes in governance, and that this simple rule of thumb turns out to be a fairly good approximation.

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report the number of sources on which that country’s score does not change or moves in the opposite direction to the aggregate indicator. For each country we also summarize the extent to which changes in the individual sources agree with the direction of change in the aggregate indicator by calculating the “Agreement Ratio”, or “Agree” / (“Agree” + “Disagree”).

The agreement ratio is quite high for countries with large changes in governance. Averaging across all countries and indicators, we find an average agreement ratio of 0.8 for the period 2002-2005, as reported in Table 3. This provides some confidence that for countries with large changes in our governance estimates, these changes are most often being driven primarily by changes in underlying sources rather than by the addition or deletion of sources. In fact, for these large changes there are only two cases where the agreement ratio is 50 percent or less. These cases are small Caribbean island economies that had only two data sources in 2002, and the addition of a new data source in 2005 resulted in a substantial change in these countries rankings. As can be seen from Table 3, such cases where the addition of a data source for a country significantly affects a country's score are quite rare.<sup>14</sup> It is also worth noting that the agreement ratios for large changes in governance are substantially higher than the agreement ratios for all changes in governance. This can be seen in Table 4 which computes the same agreement ratio, but for all countries over the period 2002-2005. The agreement ratio averages 62 percent, compared with 80 percent for large changes, suggesting that for the more typical smaller changes in our governance estimates, there is relatively more disagreement across individual sources about the direction of the change than there is for large changes. These examples underscore the importance of carefully examining the factors underlying changes in the aggregate governance indicators in particular countries. In order to facilitate this, on our website users can now retrieve the data from the individual indicators underlying our aggregate indicators and use this to examine trends in the underlying data as well as changes over time in the composition of data sources on which the estimates are based.

> 14 The only other cases for which this occurs are the Solomon Islands and Vanuatu, where the addition of these countries to our data source WMO resulted in a large changes in these countries scores (as can also be seen in Figure 2)

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While the number of countries experiencing highly significant changes in governance over the relatively short period between 2002 and 2005 is small, we do note that over longer periods, a much greater number of countries experience significant changes in governance. Our aggregate indicators now span a 10 year period from 1996-2005. Over the course of this decade, we find that on average, about 8 percent of countries experience changes that are significant at the 90 percent confidence level on each of the six indicators. Looking across all six indicators, 31 percent of countries experience a significant change at 90 percent confidence level in at least one of the six dimensions of governance over this period. We also note that the 90 percent confidence level is quite high, and for some purposes a lower confidence level, say 75 percent, would be appropriate for identifying changes in governance that are likely to be practically important. Not surprisingly this lower confidence level identifies substantially more cases of significant changes: 19 percent of countries experience a significant change on each indicator on average, and fully 60 percent of countries experience a significant change on at least one dimension of governance.

As we have noted above, in some cases the addition of sources over time does have a significant impact on the changes in our aggregate indicators. In our previous paper (Kaufmann, Kraay and Mastruzzi (2005)) we showed however that this was unusual. The same is true for the latest set of changes that we calculate. We can decompose the change over time in the aggregate indicator between 1996 and 2005 for a country into two components: the change based on a common set of sources, and the remainder. We then calculate the share of the variance of changes in the aggregate indicator that is accounted for by changes in the balanced indicator. Averaging across our six indicators we find that 85 percent of the variation in changes in the aggregate indicators can be accounted for by changes in the common set of data sources, suggesting that the inclusion of exclusion of particular sources plays a relatively small role in explaining these changes.

# **2.4  Trends in Global Governance**

We next review the available evidence on trends in global averages of governance over the expanded time period that we now cover. As we have already noted, our aggregate governance indicators are not informative about trends in global 17
averages because we assume that world averages of governance are zero in each period, as a choice of units. While the aggregate indicators are of course informative about the relative performance of individual (or groups of) countries, in order to assess trends in global governance we need to return to our underlying individual data sources.

In Table 5 we summarize trends in world averages in a number of our individual data sources. Most of the sources in this table are polls of experts, with data extending over the whole period 1996-2005. Other than expert polls, only one of them, GCS, is a survey with sufficiently standard format to enable comparisons over this period of time. The first column reports the number of countries covered by the source in each of the periods shown, and the next five columns present the average across all countries of each of the sources in each of the indicated years. The underlying data have been rescaled to run from zero to one, and for each source and governance component, we report the score on the same question or average of questions that we use in the aggregate indicator. The next five columns report the standard deviation across countries for each source. The final columns reports t-statistics associated with a test of the null hypothesis that the world average score is the same in 1996 as in 2005, in 1998 as in 2005, and in 2002 as in 2005.

The picture that emerges from Table 5 is sobering. There is very little evidence of statistically significant improvements in governance worldwide. Over the longest period 1996-2005 the 18 changes reported here are divided exactly in half into 9 improvements and 9 declines in global averages, many of them quite small. There are just six cases of statistically significant changes at the 10 percent level or better (tstatistics greater than 1.64 in absolute value), and these are split between two improvements and four declines. It is not clear how much importance ought to be ascribed to these trends in world averages based on individual indicators. On the one hand, these statistics represent the only information we have on trends over time, and so they should be taken seriously. On the other hand, it is also clear that there is substantial disagreement among sources about even the direction of changes in global averages of governance. For now we cautiously conclude that we certainly do not have any evidence of any significant improvement in governance worldwide until end-2005, and if anything the evidence is suggestive of a possible deterioration - at the very least in dimensions such as regulatory quality, rule of law, and control of corruption.

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# **3.  Are Perception Errors Correlated among Expert Assessments of Governance?**

In this section of the paper we consider two common critiques of the expert assessment individual data sources we use as inputs to our aggregate governance indicators. One concern is that the experts producing these assessments share a common set of preconceptions or prejudices about cross-country patterns of governance. If these prejudices are reflected in the assessments that they produce, this will introduces systematic errors into the data. A closely related possibility is that experts base their assessments solely on the assessments of other experts, rather than on their own view of governance in a country.<sup>15</sup> Both of these concerns are potentially serious, because they imply that the errors made by individual sources in their estimates of governance will be correlated across sources. Intuitively this means that our observed data from these various sources will be less informative about governance than if the errors were not correlated. Moreover, these concerns have implications for how we weight different data sources when we construct our aggregate indicators. Recall that our aggregate indicators are weighted averages of the underlying individual indicators. The weights are proportional to our estimates of the precision of each indicator. We in turn infer the precision of each source from its correlation with other sources. In particular, if there are no correlations among the errors made by different sources, then sources that are more highly correlated with each other should be more precise. We thus assign greater weights to sources that tend to be highly correlated with each other.

This neat logic would however break down if we allow for the possibility that the errors made by our different sources might be correlated with each other. This is an issue that has concerned us since we began constructing governance indicators using this methodology. In Kaufmann, Kraay, and Zoido-Lobatón (1999) we showed how the standard errors of our governance estimates would increase if we simply assumed that the errors from different sources were correlated. We now examine in more detail the consequences of (a) shared prejudices, and (b) experts looking at each others' scores,

> 15 We do not discuss further here other potential biases in expert assessments.  In Kaufmann, Kraay, and Mastruzzi (2004) we devise a test for and reject the hypothesis of ideological biases in expert assessments.  In Kaufmann, Kraay, and Mastruzzi (2006) we document the relative unimportance of biases arising from "halo effects".

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for our governance estimates, using two specific examples. These examples suggest to us that while these two possible sources of correlated errors are plausible _a priori_ , quantitatively they do not appear to be too important in terms of their effect on our indicators.

# **3.1  Shared Prejudices**

We first consider the case of shared prejudices. A simple way to capture this possibility is with this small variation on our basic empirical model: where yjk is the governance indicator provided by source k for country j, and gj is the unobserved true level of governance in country j. The only difference from our basic model is that the error term now consists of a weighted average of an idiosyncratic part, εjk, and a component that is common across sources, pj. We interpret the former as source-specific perceptions errors and assume that they are uncorrelated across sources. We interpret the latter as capturing the unobserved common "prejudices" shared by sources. For example, a common criticism is that expert assessments produced by commercial risk rating agencies focus exclusively on the business environment faced by foreign investors. We normalize pj to have mean zero and standard deviation one. To make the problem interesting, we need to assume that pj captures the part of respondents' prejudices that is uncorrelated with actual governance. Accordingly we assume that pj and gj are uncorrelated. Thus for example one can think about pj as capturing the component of the business environment for foreign investors that is uncorrelated with true governance.<sup>16</sup> The new parameter λk captures the weight placed by source k on these prejudices in coming up with its governance score for a country. Finally, we also normalize the variance of the idiosyncratic component of the error term, εjk, to have mean zero and variance one. This means that as we change the 2 parameter λk, the variance of the overall error term remains constant and equal to σk .

> 16 Another interpretation is the possibility of "halo" effects that we have discussed in previous work (Kaufmann, Kraay, and Mastruzzi (2005, 2006)), whereby respondents give good governance scores to rich countries simply because they are rich.  Under this interpretation pj would capture the part of halo effects that is uncorrelated with true governance.

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Note also that when λk=0 we retrieve our original basic model in which we assume that 2 perception errors are independent across sources and have variance equal to σk .

In order to incorporate the effects of shared prejudices on our estimates of governance, we first need to obtain estimates of the parameter λk for each source, i.e. an estimate of the importance of shared prejudices in source k's assessment of governance. Unfortunately we cannot estimate this model in general, because the statistical model in Equation (1) is not identified. Intuitively, the problem is that if we observe a high correlation between two data sources, we have no way of knowing if this is because they both place a high weight on common prejudices, i.e. they both have a high value of λk, or whether instead both sources have a low variance of the error term, 2 i.e. σk is low for the two sources.

In order to make progress we therefore need to impose some identifying assumptions. As an illustration we do this for the case of K=3 data sources which allows us to obtain very intuitive closed-form solutions for all of the relevant parameters as functions of the observed correlations in the data. We impose two key identifying assumptions. The first is that the variance of the overall error term is the same for all 2 2 three sources, i.e. σk =σ for k=1,2,3. This is mostly for convenience because it provides us with a natural benchmark: if shared prejudices play no role, then we would weight the three sources equally in our estimates of governance since the signal-to-noise ratio would be the same in all three.

The second assumption is more important. We assume that two of the three sources share some common prejudices but the third source does not. In particular we assume that λ1=λ2=λ and λ3=0. This assumption is based on the following interpretation of our two main types of data sources: expert assessments, and surveys of firms or individuals. It seems plausible that expert assessments might be prone to some form of "group-think" in which their shared preconceptions of countries affect their estimates of governance. At the same time, such "group-think" is less likely to be present in survey data where respondents are less likely to have access to the ratings provided by commercial risk rating agencies.

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With these identifying assumptions in hand we can now obtain an estimate of the importance of shared perceptions based on the observed correlations in the data. Define R as the average correlation between each of the two expert assessments and the survey, i.e. R=(R13+R23)/2 and define R* as the correlation between the two expert assessments, i.e. R*=R12, where Rjk is the observed correlation between source j and source k. After some algebra (detailed in Appendix D) we can estimate the two key parameters of this extended model as: The intuitions for these two expressions are very straightforward. The higher is R* relative to R, i.e. the higher is the correlation among expert assessments relative to the typical correlation between an expert assessment and the survey, the higher is our estimate of λ. This is because we would attribute the relatively high correlation among expert assessments as reflecting the influence of shared prejudices on their governance ratings. The observed correlation between the expert assessments and the survey, R, provides us with information about the overall noise-to-signal ratio all three sources. The higher are these correlations, the more informative are all three data sources, i.e. the smaller is σ.

How does the presence of shared prejudices unrelated to true governance affect how we should construct our aggregate governance indicators? The simple example we have been discussing provides a useful illustration. If the expert assessments were not influenced by shared prejudices, i.e. if λ=0, then our assumption that the variance of the 2 2 overall error terms is the same, i.e. σk =σ for k=1,2,3 implies that we would weight all three sources equally. In the other extreme case where the error terms of the two expert assessments are perfectly correlated, i.e. if λ=1, then it is possible to show that the optimal estimate of governance would consist of a simple average of the survey and _an average of_ the two expert assessments. In other words, if shared prejudices are not important, then the survey and the two expert assessments should all receive weights of one-third in the estimate of aggregate governance. If on the other hand shared prejudices dominate, then it is optimal to treat the two expert assessments as if they were just one source, and given our assumption of equal variances, to weight this one 22
source equally with the survey. Crucially, however, we note that the possibility of correlated errors among expert assessments does not imply that we should discard these data sources altogether. Rather, it means that we should continue to use them because even in the limiting case of perfectly correlated errors, collectively they still provide some information about unobserved governance.

This re-weighting of the survey is shown graphically in the top panel of Figure 3, which plots the weight of the survey in the aggregate indicator for alternative values of λ. When common prejudices play no role, the weight on the survey is equal to one-third. As we move to the opposite extreme where λ=1, i.e. where the error term is dominated by common prejudices, then the weight on the survey should be 0.5.<sup>17</sup> In Table 6 we provide a sense of how important shared prejudices are quantitatively in our dataset. For our expert assessments we consider our five major data sources provided by commercial risk rating agencies (DRI, EIU, MIG, PRS, and WMO). For our survey we take GCS, which is our only very large cross-country survey of firms. In the top panel we report the two correlations of interest. We first report R* which is the average pairwise correlation between these five expert assessments, for each of our six governance aggregates for the past four years. We also report R, which is the average pairwise correlation of each of these five expert assessments with the survey. In the bottom panel we report the estimates of λ implied by these correlations. The first thing to notice is that for four of our six indicators (PV, GE, RL and CC) R* and R are very similar to each other, and often R*<R implying that the expert assessments are on average actually more correlated with the survey than they are with each other. This pattern of R*<R is inconsistent with shared prejudices, and so for these we have no positive estimate of λ. And in many cases R* is only slightly larger than R, implying very small values of λ.

For two of the six aggregates, VA and RQ, we find that the expert assessments tend to be much more highly correlated with each other than with the survey, implying more substantial estimates of λ. We should however be a bit cautious in taking these

> 17 Clearly the importance of shared prejudices also matters for the precision of our estimates of governance.  In the extreme case where λ=1 the standard error would be the same as if we had only two instead of three sources.

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results at face value. Consider for example VA. The GCS survey questions we use here focus on the extent to which firms are informed by government of regulations, which is a very narrow dimension of accountability, while the expert assessments capture much broader notions of democratic accountability. This may explain the relatively low correlation of the expert assessments with the survey. To see how important this is, we took one specific question from the GCS about firms' perceptions of press freedom, and compared it with two expert assessments of press freedom (RSF, and a specific press freedom rating from FRH). As shown in the row labeled "Press Freedom", we find that the correlation between FRH and RSF is much closer to the average correlation of both of these with the survey, implying a much lower estimate of λ and suggesting a much smaller role for shared prejudices among the expert assessments.<sup>18</sup> Overall this example suggests that the role of shared prejudices in expert assessments in at most minor.

As noted above, in this example finding positive estimates of λ as we have in some cases in Table 6 suggests that it would be appropriate to slightly decrease the weight placed on the expert assessments in our aggregate indicators. We do not make this adjustment to our benchmark governance indicators. This is because our estimate of the role of shared prejudices that we report here is very much in the spirit of an illustrative example, rather than as a definitive analysis. We have made several simplifying assumptions in order to generate these estimates as transparently as possible, and these may or may not be appropriate for our aggregate indicators that rely on our full dataset. However, we do note that a modest reduction in the weight of expert assessments in our aggregate indicators suggested by this example is unlikely to have major systematic effects on our estimates of governance. This is because, as we have mentioned earlier, the expert assessments on which we rely are in most cases quite strongly correlated with other data sources: recall that the average value of the 18 One possible objection to this exercise is that the GCS surveys firms, and it could be that such respondents share a common set of business-oriented prejudices with commercial risk rating agencies. To assess this we would need to have a large cross-country survey of individuals. Unfortunately we have only limited information to address this issue, with two of our regional surveys of individuals, Latinobarometro and Afrobarometer, covering only very small samples of countries. One possibility is to look at the Gallup survey we use that covers a somewhat larger set of 62 countries. In 2004 and 2005 we have survey questions on corruption from this source. These are typically quite highly correlated with expert assessments at about 0.7, while the expert assessments are correlated only slightly more about 0.8 in the same set of countries. This again suggests at most a modest importance of shared prejudices.

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correlation of an expert assessment with the survey in Table 6 is 0.74. This means that even if we moderately shift the weights in our aggregate indicator away from the expert assessments, the resulting aggregate indicator will still be highly correlated with our benchmark assessments that do not allow for shared prejudices.

To investigate this point in more detail, we have recalculated our six governance indicators for all seven periods, weighting all of the components equally, rather than precision-weighting based on the benchmark assumption of uncorrelated errors.<sup>19</sup> This in practice substantially reduces the weights applied to expert assessments from commercial risk rating agencies. The average (across the 42 indicators) correlation between the equally-weighted indicators and our benchmark indicators is 0.99. In only three cases is the correlation less than 0.99, and the minimum correlation is 0.97. This clearly shows that how we weight our underlying data sources does not practically affect our estimates of governance in the vast majority of cases. The main benefit however of weighting sources by their precision is that it yields somewhat smaller standard errors, allowing for more precise inference about cross-country differences and changes over time in governance. On average, the standard error of our equally-weighted indicators is about 10 percent higher than in our benchmark indicators.

# **3.2  Do Sources Update Based on Past Discrepancies?**

We now turn to the possibility that our expert assessments at least in part base their estimates of governance on the assessments of other experts. As noted earlier, we can interpret the previous example as one case of this. Here we consider a different example in which expert assessments update their ratings based on past differences between them. In particular, suppose that we have two expert assessments that produce their estimates of governance as follows: (3)

> 19 In particular, we estimate the parameters of the unobserved components model imposing the restriction that the variance of the error term is the same across sources.  This in turn implies an equal weighting of sources.  See Equations (1)-(3) in Kaufmann, Kraay and Mastruzzi (2004).

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where y1jt and y2jt denote the estimate of governance provided by sources 1 and 2 at time t for country j, and gjt denotes the unobserved true level of governance in country j at time t. The perception errors made by the two sources consist of two parts. First, we assume that each source updates its estimates of governance in period t based on the difference between itself and the other source in the previous period. For example, if source 2 rated country j much higher than source 1 in period t-1, then we assume that in period t source 1 revises its estimate of governance upward, and source 2 revises its estimate of governance downward. The strength of this updating is captured by the parameters λ1 and λ2. The second is an idiosyncratic component which we assume is independent across sources.<sup>20</sup> In order to assess how important this kind of updating is, we need estimates of the λ's. One approach might be to estimate a cross-sectional regression of the assessments of each source on the lagged difference between the two sources. This however is unlikely to lead to consistent estimates of the λ's, since the error term in such a regression, gjt+ε1jt is likely to be correlated with the past discrepancies between sources, y2jt-1-y1jt-1, for two reasons. The first is that unobserved governance gjt might be correlated with the past discrepancies between sources, y2jt-1-y1jt-1. Moreover, if the idiosyncratic component of the error terms is correlated over time, there will by construction be a correlation between ε1jt and y2jt-1-y1jt-1.

A more direct approach is to look at the difference between the two sources, which is: Note that the difference between the two sources will follow an autoregressive process with a negative coefficient on the lagged difference. In particular, if source 1 rates country j higher than source 2 in the previous period, we would expect that in the current

> 20 Note here that we have suppressed differences across sources in the α's and β's which capture differences in scales of measurement across sources.  We do this purely for notational convenience.  In the empirical application we remove the scales from our variables by expressing them as percentile ranks.

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period the difference between the two sources will be smaller, if this kind of updating is important.

Equation (4) suggests two empirical tests. The first is that if this type of updating based on past discrepancies is important, we should expect to see discrepancies decline over time, and as a result, the correlations among sources should be increasing over time.<sup>21</sup> This first implication can readily be checked. The top two panels of Table 7 show the pairwise correlations between our three main commercial risk rating agencies available over the full time span of our governance indicators, for 1996 and 2005. The third panel reports the change over this period in each of the pairwise correlations. These changes over time in correlations are not large, even over the decade-long period covered in the table. The median change is only 0.03, and none of the observed changes would be significant at the 90 percent confidence level. Moreover, overall the changes are quite evenly divided between seven declines and nine increases. This evidence suggests to us that there is no evidence of a systematic increase over time in the correlation among expert assessments. This in turn casts doubt on the hypothesis that these expert assessments update their estimates based on past discrepancies with each other.

Another implication of Equation (4) is that this type of updating would be a force towards creating a negative correlation over time in the pairwise differences in country assessments. We explore the empirical validity of this implication next. The simplest case to consider is when the idiosyncratic error terms in Equation (3) are independent over time. In this case, the autocorrelation over time of the differences in scores between pairs of sources is simply -(λ1+λ2). In this simple case we could just look at the autocorrelation of differences between sources and test whether it is negative. This would then constitute evidence of updating based on past discrepancies. The first three columns of Table 8 report the correlation over time in the pairwise difference in country rankings between 1996 and 2005, for our three main commercial risk rating agencies. The first thing to note is that these correlations are almost always positive, and average around 0.25. This does not appear to be consistent with the updating hypothesis, which

> 21 This will be true as long as the idiosyncratic error terms are not too correlated over time -- as discussed further below.

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would be a force for _negative_ correlations over time in pairwise differences in country rankings.

There is however a complication introduced by the possibility that the idiosyncratic error terms, ε, themselves might be correlated over time. If these error terms are very persistent, then pairwise differences in country rankings would also be very persistent, and this would obscure any negative correlation over time arising from the updating based on past discrepancies. In order to test for the importance of updating, we need to correct for this effect. After some algebra, it is possible to show that the autocorrelation of differences is given by:<sup>22</sup> where ρ is the unobserved correlation over time in the idiosyncratic component of each source's error term, i.e. ρ=CORR(ε1jt, ε1jt-1)= CORR(ε2jt, ε2jt-1). This expression is quite intuitive. As already noted, if ρ=0, the correlation over time of the differences is just -(λ1+λ2). If on the other hand there is on average no updating based on past discrepancies, i.e. λ1+λ2=0, then the correlation of differences over time is just the autocorrelation of the idiosyncratic errors, ρ. Finally, if the error terms are perfectly persistent, ρ=1, then the observed differences in scores would be perfectly correlated as well, regardless of any updating that might be present.

Given the observed correlations over time in differences between sources reported in Table 8, together with assumptions about the autocorrelation of the idiosyncratic errors, ρ, we can use Equation (5) to back out an estimate of λ1+λ2 which summarizes the importance of updating based on lagged discrepancies between sources. We do this in the last two columns of Table 8. The fourth column reports our assumptions on ρ, the correlation over time of the idiosyncratic error terms. These are based on estimates we derived in Kaufmann, Kraay, and Mastruzzi (2005), and average

> 22 To derive this expression first use recursive substitution to write y1jt-y2jt as a moving average of all past differences in the error terms, ε1jt-ε2jt.  Next note that the assumptions in the text imply that E[ε1jt-ε2jt, ε1jt-k-ε2jt-k]=2ρ<sup>k</sup> σ<sup>2</sup> /(1-ρ<sup>2</sup> ).  Finally use this to calculate the autocorrelations of y1jt-y2jt.

28
0.42 across our six indicators, indicating a substantial degree of persistence.<sup>23</sup> The final column reports the estimates of λ1+λ2. Overall these estimates are quite small, averaging only 0.17. While we do not know how to attribute this total over the two sources being considered, absent better information it seems reasonable to divide it equally, implying a value of λ1=λ2=0.085. This in turn implies that on average less than 10 percent of the initial difference between two expert assessments would be eliminated through this process of updating based on past discrepancies. Moreover, it is important to remember that Table 8 refers to correlations calculated over a decade between 1996 and 2005. Thus, our estimates suggest that this process of updating is so gradual that over the course of a decade it results in a reduction of only 10 percent of initial differences between sources. Considering this together with the evidence in Table 7 showing no significant trends in the pairwise correlations among expert assessments, we conclude that the evidence that expert assessments revise their country rankings based on past discrepancies with other assessments is very weak indeed.

We conclude the discussion of interdependence between expert assessments with a final example. Knack (2006) has argued that one of the expert assessments on which we rely, PRS, has in the case of corruption made systematic changes in its methodology in order to ensure that it is more correlated with the Transparency International Corruption Perceptions Index. Since the latter is an amalgam of many different assessments of corruption, including several other expert assessments, Knack (2006) argues that this is an example of one expert assessment basing its views on those of other expert assessments rather than on its own information. In particular, Knack (2006) documents that the correlation of the ICRG corruption rating with the Transparency International measure increases from 0.72 to 0.91 following what he refers to as a "massive recalibration" that occurred in October of 2001.

We do not find this critique of the PRS measure compelling because it does not appear to be systematically true. Several of the many different PRS ratings that we use have indeed had methodological breaks in the past, like the one for corruption that Knack (2006) focuses on. If the objective of such breaks is to generate new ratings that

> 23 These estimates are only suggestive, as they not fully consistent with the statistical model considered here.  In particular, they are based on a model which does not allow for error terms to be correlated across sources.  It is not clear whether this restriction would bias our estimates of ρ up or down.

29
are more correlated those of with other experts, as suggested by Knack (2006), then we should systematically expect increases in correlations with other experts when comparing the period before and after the methodological break. In contrast, we should see no change in the correlation of PRS with other expert assessments for series that did not have methodological breaks.

In Table 9 we examine the 10 governance indicators produced by PRS that we use as an input to our aggregate governance indicators. For each of these series we look at the number of countries whose scores change from month to month on the monthly PRS data. We identify series with methodological breaks by looking for sharp increases in the number of countries whose scores change in a particular month. This method clearly turns up cases of methodological breaks. In the case of corruption, for example, in a typical month only 1.4 percent of countries in the PRS sample change scores relative to the previous month, while in October of 2001 41 percent of the countries in the sample change scores. As shown in Table 9, the main methodological breaks occur in 1997 and in 2001. Importantly for us, not all series have breaks in both periods. In 1997 for example we detect methodological breaks in the PRS series "Democratic Accountability" which we map to VA, and "Bureaucratic Quality" which we map to GE, while the remaining 8 PRS series do not have breaks in 1997. Similarly in 2001 there are five series with breaks and five series without breaks.

In the columns of Table 9 we report the correlations of the PRS series with our two other major expert assessments, DRI and EIU, in the years before and after the break. For corruption, for example, we report the correlation of PRS rating with the corruption ratings provided by DRI and EIU, in 2000 and in 2002. We do this for all 10 PRS indicators, separating those with and without methodological breaks. We then ask whether there is any evidence that the PRS indicators with methodological breaks are more likely to see their correlations with other expert assessments increase than those series without breaks. The answer appears to be no. Consider for example the comparison of correlations with PRS in 2000 and 2002. For the five PRS series with methodological breaks, the median change in the correlation of each of these with DRI and EIU is just 0.01, and in only about half of the cases is the change in correlation positive. The median change in the correlation with DRI and EIU for series without methodological breaks is almost exactly the same, at -0.01. Similarly in 1997, we do not 30
see much in the way of systematic evidence that PRS series with methodological breaks are more likely to become more correlated with other expert assessments. Based on this systematic look at the behavior of the PRS indicators around the time of methodological breaks, we do not find it plausible to argue as does Knack (2006) that PRS has exploited methodological breaks in the past to increase their correlation with the ratings of other expert assessments.

# **4.  Conclusions**

In this paper we have reported on the latest update of our aggregate governance indicators. With this update we have (a) moved to an annual frequency for reporting, (b) for the first time made available virtually all of the individual indicators underlying the aggregate indicators, and (c) provided new evidence on the reliability of expert assessments of governance that form part of our aggregate indicators. It is our hope that more timely annual reporting as well as access to individual indicators will make the aggregate indicators more useful to users in academic and policymaking circles.

We nevertheless emphasize to all users the limitations of these measures of governance, which are shared by virtually all efforts to measure governance across countries and over time. The aggregate indicators we construct are useful for broad cross-country and over time comparisons of governance, but all such comparisons should take appropriate account of the margins of error associated with the governance estimates. These margins of error are not unique to our perceptions-based measures but are present -- if not explicitly acknowledged -- in any effort to measure governance. They naturally reflect the inherent difficulty in measuring something as complicated and multifaceted as governance. However, we have shown the feasibility of using the aggregate indicators to make comparisons of governance across countries and over time, subject to appropriate consideration of margins of error. In fact, for 2005 we have seen that fully 60% of all cross-country comparisons result in highly-significant differences, and that nearly one-third of countries have experienced substantial changes in at least one dimension of governance between 1996 and 2005.

31
We also caution users that the aggregate indicators can in some circumstances be a rather blunt tool for policy advice at the country level. We expect that the provision of the underlying data will help users in identifying -- and acting upon -- more specific aspects of governance that may be problematic in a given country. And we also encourage using these aggregate and individual indicators in conjunction with a wealth of possible more detailed and nuanced sources of country-level data on governance in formulating policy advice.

# **References**

- Kaufmann, Daniel, Aart Kraay and Pablo Zoido-Lobatón (1999a). “Aggregating Governance Indicators.” World Bank Policy Research Working Paper No. 2195, Washington, D.C.

- ——— (1999b). “Governance Matters.” World Bank Policy Research Working Paper No. 2196, Washington, D.C.

- ——— (2002). “Governance Matters II – Updated Indicators for 2000/01.” World Bank Policy Research Working Paper No. 2772, Washington, D.C.

- Kaufmann, Daniel, Aart Kraay and Massimo Mastruzzi (2004).  “Governance Matters III: Governance Indicators for 1996, 1998, 2000, and 2002”.  World Bank Economic Review.  18:253-287.

- Kaufmann, Daniel, Aart Kraay and Massimo Mastruzzi (2005).  “Governance Matters IV: Governance Indicators for 1996-2004.  World Bank Policy Research Working Paper No. 3630.  Washington, D.C.

- Kaufmann, Daniel, Aart Kraay and Massimo Mastruzzi (2006).  “Measuring Governance Using Perceptions Data", in Susan Rose-Ackerman, ed.  Handbook of Economic Corruption.  Edward Elgar.

- Knack, Steven (2006).  "Measuring Corruption in Eastern Europe and Central Asia:  A Critique of the Cross-Country Indicators".  World Bank Policy Research Department Working Paper.

32
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**Figure 2:  Changes Over Time in Governance Indicators 2002-2005**

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**Figure 3:  Reweighting Survey Due to Shared Prejudices**

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# **Table 1:  Sources of Governance Data**

||||||Country|Represe||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
|Source|Publication|Code|Type|Public|Coverage|-ntative<br>|199|6<br>1998<br>2|000|2002|2003<br>|200|4<br>2005|
|African Development Bank|Country Policy & Institutional Assessments|ADB|Poll|No|50||||x|x|x|x|x|
|Afrobarometer|Afrobarometer Survey|AFR|Survey|Yes|18||||x|x|x|x|x|
|Asian Development Bank|Country Policy & Institutional Assessments|ASD|Poll|Partial|26||||x|x|x|x|x|
|Bertelsmann Foundation|Bertelsmann Transformation Index|BTI|Poll|Yes|119|||||||x|x|
|Brown University's Center for Public Policy|Global E-Governance|EGV|Poll|Yes|192|x||||x|x|x|x|
|Business Environment Risk Intelligence|Business Risk Service|BRI|Poll|Yes|50||x|x|x|x|x|x|x|
|Business Environment Risk Intelligence|Qualitative Risk Measure|QLM|Poll|Yes|115|x|x|x|x|x|x|x|x|
|Columbia University|State Capacity Project|CDU|Poll|Yes|108|x|||x|x|x|x||
|Economist Intelligence Unit|Country Risk Service|EIU|Poll|Yes|120|x|x|x|x|x|x|x|x|
|European Bank for Reconstruction & Development|Transition Report|EBR|Poll|Yes|27||x|x|x|x|x|x|x|
|Freedom House|Countries at the Crossroads|CCR|Poll|Yes|30|||||||x|x|
|Freedom House|Nations in Transition|FHT|Poll|Yes|27||x|x|x|x|x|x|x|
|Freedom House|Freedom in the World|FRH|Poll|Yes|192|x|x|x|x|x|x|x|x|
|Gallup International|Voice of the People Survey|GAL|Survey|Yes|69|||||x|x|x|x|
|Global Insight|Global Risk Service|DRI|Poll|Yes|111|x|x|x|x|x|x|x|x|
|Global Insight|Business Conditions and Risk|WMO|Poll|Yes|202|x||||x|x|x|x|
|Heritage Foundation|Economic Freedom Index|HER|Poll|Yes|161|x|x|x|x|x|x|x|x|
|IJET Travel Intelligence|Country Security Risk Assessment|IJT|Poll|Yes|167|x||||||x|x|
|Institute for Management and Development|World Competitiveness Yearbook|WCY|Survey|Yes|49||x|x|x|x|x|x|x|
|International Research & Exchanges Board|Media Sustainability Index|MSI|Poll|Yes|19|||||x|x|x|x|
|Latinobarometro|Latinobarometro Surveys|LBO|Survey|Yes|18||x|x|x|x|x|x|x|
|Merchant International Group|Grey Area Dynamics|MIG|Poll|Yes|159|x||||x|x|x|x|
|Political & Economic Risk Consultancy|Corruption Survey|PRC|Survey|Yes|10|||x|x|x|x|x|x|
|Political Risk Services|International Country Risk Guide|PRS|Poll|Yes|140|x|x|x|x|x|x|x|x|
|Reporters Without Borders|Reporters Without Borders|RSF|Poll|Yes|165|x||||x|x|x|x|
|State Department|Trafficking in People Report|TPR|Poll|Yes|149|x|||x|x|x|x|x|
|State Department / Amnesty International|Human Rights Dataset|HUM|Poll|Yes|192|x|x|x|x|x|x|x|x|
|World Bank|Business Enterprise Environment Survey|BPS|Survey|Yes|27||||x|x|x|x|x|
|World Bank|World Business Environment Survey|WBS|Survey|Yes|80|x||x|x|||||
|World Bank|Country Policy & Institutional Assessments|PIA|Poll|Partial|136||x|x|x|x|x|x|x|
|World Economic Forum|Global Competitiveness Report|GCS|Survey|Yes|117|x|x|x|x|x|x|x|x|

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# **Table 2:  Summary Statistics on Governance Indicators**

||**Voice and**<br>**Accountability**|**Political**<br>**Stability**|**Government**<br>**Effectiveness**|**Regulatory**<br>**Quality**|**Rule of Law**|**Control of**<br>**Corruption**|**Overall**|
|---|---|---|---|---|---|---|---|
|**Number of Co**|**untries**|||||||
|1996|193|179|181|183|168|152|176|
|1998|192|166|184|185|186|184|183|
|2000|192|166|187|188|188|187|185|
|2002|199|186|202|197|197|197|196|
|2003|201|186|202|197|197|197|197|
|2004|207|207|208|204|208|204|206|
|2005|208|213|210|203|208|204|208|
|**Median Numbe**|**r of Sources Pe**|**r Country**||||||
|1996|4|4|4|4|6|4|4|
|1998|4|4|4|4|7|5|5|
|2000|5|6|6|5|9|7|6|
|2002|7|7|8|7|11|8|8|
|2003|7|7|8|7|11|8|8|
|2004|8|8|9|8|12|8|9|
|2005|8|7|9|8|11|8|9|
|**Proportion of**|**Countries with O**|**nly One Data**|**Source**|||||
|1996|15|18|22|15|7|18|16|
|1998|14|10|19|13|11|18|14|
|2000|14|6|7|7|5|7|8|
|2002|10|10|5|7|7|8|8|
|2003|10|9|5|7|7|7|7|
|2004|6|6|8|8|8|8|7|
|2005|6|7|9|8|8|7|7|
|**Average Stand**|**ard Error**|||||||
|1996|0.28|0.40|0.30|0.37|0.28|0.34|0.33|
|1998|0.26|0.32|0.36|0.41|0.27|0.29|0.32|
|2000|0.26|0.34|0.27|0.40|0.23|0.26|0.29|
|2002|0.22|0.27|0.23|0.23|0.19|0.21|0.23|
|2003|0.19|0.28|0.23|0.21|0.18|0.20|0.22|
|2004|0.18|0.26|0.23|0.22|0.19|0.21|0.21|
|2005|0.17|0.28|0.20|0.20|0.19|0.19|0.21|

37
# **Table 3:  Large Changes in Governance, 2002-2005**

||**Gove**<br>**2005**|**rnance**<br>**2002**|**Score**<br>**Change**|**Agree**|**No**<br>**change**|**Dis-**<br>**agree**|**Agree/**<br>**(agree+**<br>**Disagree)**|**Sources**<br>**Added**|**Sources**<br>**Subtracted**|
|---|---|---|---|---|---|---|---|---|---|
|**Voice & Accountability**||||||||||
|UNITED ARAB EMIRATES|-1.08|-0.49|-0.59|4|1|1|0.80|2|0|
|RUSSIA|-0.85|-0.45|-0.40|8|0|3|0.73|2|1|
|SINGAPORE|-0.29|0.50|-0.79|4|1|2|0.67|3|0|
|IRAQ|-1.47|-2.15|0.69|6|0|0|1.00|1|0|
|KENYA|-0.12|-0.69|0.57|5|1|1|0.83|3|1|
|LIBERIA|-0.92|-1.57|0.65|5|0|0|1.00|1|1|
|UKRAINE|-0.26|-0.68|0.43|6|2|1|0.86|2|1|
|SERBIA AND MONTENEGRO|0.12|-0.30|0.42|7|1|0|1.00|3|0|
|**Political Stability**||||||||||
|BANGLADESH|-1.65|-0.73|-0.92|4|0|3|0.57|1|1|
|BOLIVIA|-1.15|-0.21|-0.95|5|0|2|0.71|0|0|
|IRAQ|-2.82|-1.80|-1.01|4|1|1|0.80|1|0|
|TOGO|-1.22|0.03|-1.24|3|0|0|1.00|2|0|
|THAILAND|-0.55|0.31|-0.86|7|0|2|0.78|1|1|
|ANGOLA|-0.82|-1.66|0.84|6|0|0|1.00|1|1|
|GEORGIA|-0.80|-1.83|1.03|2|1|1|0.67|2|1|
|**Government Effectiveness**||||||||||
|ZIMBABWE|-1.42|-0.81|-0.61|6|0|3|0.67|2|0|
|* ST. KITTS AND NEVIS|1.00|-0.27|1.28|0|0|2|0.00|1|0|
|* ST. VINCENT AND THE GRENADINES|1.07|-0.20|1.27|1|0|1|0.50|1|0|
|SLOVAK REPUBLIC|0.95|0.46|0.49|9|1|0|1.00|2|0|
|**Regulatory Quality**||||||||||
|VENEZUELA|-1.15|-0.57|-0.58|6|1|2|0.75|1|0|
|* VANUATU|0.05|-1.23|1.29|2|0|0|1.00|1|0|
|IRAQ|-1.61|-2.30|0.69|4|0|1|0.80|0|0|
|**Control of Corruption**||||||||||
|GEORGIA|-0.57|-1.07|0.50|5|0|2|0.71|2|1|
|TURKEY|0.08|-0.45|0.52|8|2|1|0.89|2|1|
|* SOLOMON ISLANDS|0.02|-1.35|1.37|2|0|0|1.00|1|0|
|* VANUATU<br>* 2005 estimates based on fewer than thre|0.26<br>e data s|-0.81<br>ources.|1.07|1|1|0|1.00|1|0|

38
# **Table 4:  Agreement Ratio for Changes in Governance, 2002-2005**

||||**ALL CHANGE**|**S**|**Agree / (Agree +**|
|---|---|---|---|---|---|
||**Sample**|**Agree**|**No Change**|**Disagree**|**Disagree)**|
|**Voice and Accountability**|199|2.28|1.32|1.35|0.63|
|**Political Stability**|186|2.17|0.73|1.25|0.63|
|**Government Effectiveness**|196|2.56|1.30|1.74|0.60|
|**Regulatory Quality**|196|2.54|0.97|1.54|0.62|
|**Rule of Law**|196|2.62|3.22|1.53|0.63|
|**Control of Corruption**|196|2.18|2.17|1.16|0.65|
|**Average**|**195**|**2.4**|**1.6**|**1.4**|**0.63**|
|||**SIGNIFIC**|**ANT CHANG**|**ES (90%)**|**Agree / (Agree +**|
|||**Agree**|**No Change**|**Disagree**|**Disagree)**|
||**Sample**|||||
|**Voice and Accountability**|8|5.6|0.8|1.0|0.88|
|**Political Stability**|7|4.4|0.3|1.3|0.94|
|**Government Effectiveness**|4|4.0|0.3|1.5|0.94|
|**Regulatory Quality**|3|4.0|0.3|1.0|0.92|
|**Rule of Law**|0|..|..|..|..|
|**Control of Corruption**|4|4.0|0.8|0.8|0.84|
|**Average**|**4**|**4.4**|**0.5**|**1.1**|**0.91**|

39
# **Table 5:  Global Trends in Governance 1996-2005 for Selected Sources**

||||**Wor**|**[Quas**<br>**ld Aver**|**i Bala**<br>**age**|**nced Sa**|**mple]* ***<br>**Std.**|*** *****<br>**Dev. Ac**|**ross C**|**ountries**||**tttiti**|**tttiti**|**tttiti**|
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
||**Sample**|**1996**|**1998**|**2000**|**2002**|**2005**|**1996**|**1998**|**2000**|**2002**|**2005**|**-sasc**<br>**1996-2005**|**-sasc**<br>**1998-2005**|**-sasc**<br>**2002-2005**|
|**Voice and Accountability**|||||||||||||||
|EIU|115|0.41|0.42|0.42|0.46|0.45|_0.30_|_0.32_|_0.31_|_0.28_|_0.28_|1.15|0.89|-0.19|
|FRH|190|0.552|0.565|0.569|0.582|0.59|_0.31_|_0.31_|_0.30_|_0.30_|_0.30_|1.33|0.90|0.38|
|GCS (Press Freedom / Parliament) **|97|..|..|..|0.57|0.55|_.._|_.._|_.._|_0.15_|_0.15_|..|..|-0.81|
|PRS *|140|0.63|0.63|0.63|0.63|0.67|_0.25_|_0.27_|_0.27_|_0.26_|_0.26_|1.26|1.34|1.18|
|WMO|186|..|..|..|0.55|0.57|_.._|_.._|_.._|_0.26_|_0.25_|..|..|0.53|
|**Political Stability**|||||||||||||||
|EIU|115|0.54|0.51|0.56|0.54|0.56|_0.29_|_0.30_|_0.30_|_0.28_|_0.27_|0.53|1.33|0.43|
|GCS (cost of terrorism) **|97|..|..|..|0.66|0.67|_.._|_.._|_.._|_0.17_|_0.14_|..|..|0.44|
|PRS *|140|0.70|0.76|0.78|0.75|0.74|_0.13_|_0.14_|_0.11_|_0.12_|_0.11_|2.54|-1.79|-0.94|
|WMO|186|..|..|..|0.67|0.67|_.._|_.._|_.._|_0.24_|_0.22_|..|..|0.10|
|**Government Effectiveness**|||||||||||||||
|EIU|115|0.39|0.45|0.44|0.38|0.37|_0.30_|_0.24_|_0.24_|_0.29_|_0.31_|-0.46|-2.33|-0.40|
|GCS (infrastructure quality) **|97|0.49|0.52|0.54|0.53|0.50|0.22|0.21|0.25|0.24|0.23|0.55|-0.53|-0.80|
|PRS *|140|0.58|0.51|0.54|0.54|0.53|_0.24_|_0.21_|_0.29_|_0.29_|_0.28_|-1.47|0.80|-0.24|
|WMO|186|..|..|..|0.56|0.57|_.._|_.._|_.._|_0.23_|_0.23_|..|..|0.36|
|**Regulatory Quality**|||||||||||||||
|EIU|115|0.42|..|..|0.51|0.54|_0.25_|_.._|_.._|_0.25_|_0.24_|3.77|..|1.08|
|GCS (burden of regulations) **|97|0.44|0.48|0.42|0.30|0.34|0.15|0.15|0.12|0.13|0.11|-5.17|-7.59|2.60|
|HERITAGE ***|155|0.50|0.48|0.49|0.50|0.51|_0.30_|_0.31_|_0.31_|_0.29_|_0.18_|0.39|0.94|0.23|
|WMO|186|..|..|..|0.58|0.59|_.._|_.._|_.._|_0.25_|_0.25_|..|..|0.35|
|**Rule of Law**|||||||||||||||
|EIU|115|0.47|0.50|0.48|0.52|0.51|_0.27_|_0.30_|_0.30_|_0.26_|_0.26_|0.96|0.36|-0.38|
|GCS (cost of organized crime / quality of|||||||||||||||
|<br>police / independent judiciary) **|97|..|0.65|0.62|0.56|0.55|_.._|_0.21_|_0.23_|_0.21_|_0.19_|..|-3.45|-0.43|
|HERITAGE ***|155|0.50|0.48|0.46|0.44|0.44|_0.30_|_0.31_|_0.31_|_0.29_|_0.28_|-1.87|-1.12|-0.18|
|PRS *|140|0.72|0.62|0.65|0.62|0.64|_0.23_|_0.26_|_0.23_|_0.24_|_0.21_|-3.31|0.50|0.75|
|QLM|115|0.45|0.45|0.46|0.46|0.44|_0.29_|_0.29_|_0.30_|_0.30_|_0.30_|-0.07|-0.23|-0.34|
|WMO|186|..|..|..|0.58|0.59|_.._|_.._|_.._|_0.23_|_0.23_|..|..|0.38|
|**Control of Corruption**|||||||||||||||
|EIU|115|0.35|0.34|0.33|0.35|0.33|_0.31_|_0.32_|_0.31_|_0.32_|_0.35_|-0.29|-0.23|-0.33|
|GCS (bribe frequency)**|97|..|0.66|0.69|0.64|0.63|_.._|_0.29_|_0.25_|_0.22_|_0.18_|..|-0.86|-0.35|
|PRS *|140|0.59|0.51|0.47|0.41|0.41|_0.21_|_0.21_|_0.21_|_0.19_|_0.20_|-7.08|-3.85|0.33|
|QLM|115|0.39|0.40|0.40|0.40|0.38|_0.29_|_0.29_|_0.29_|_0.29_|_0.29_|-0.35|-0.54|-0.51|
|WMO|186||||052|053||||_027_|_026_|||032|
|* PRS Country coverage in 1996: 130, all<br>** GCS Country coverage in 1996: 58; in 1<br>*** Heritage Country coverage in 1996: 13|other peri<br>998: 59; i<br>7; all othe|..<br>ods 140<br>n 2000:<br>r periods|..<br>.<br>75; 20<br>155.|..<br>02:80; 2|.<br>003-20|.<br>05: 97.|_.._|_.._|_.._|_._|_._|..|..|.|

40
**Table 6:  Shared Prejudices in Expert Assessments**

|**_Correlations Among_**|**_Experts_**|**_(R*) and C_**<br>|**_orrelation_**<br>|**_s with Surv_**<br>|**_ey (R)_**<br>|
|---|---|---|---|---|---|
|||**2002**|**2003**|**2004**|**2005**|
|Voice and Accountability|R*|0.85|0.85|0.86|0.84|
||R|0.66|0.65|0.61|0.74|
|Political Stability|R*|0.74|0.78|0.79|0.76|
||R|0.73|0.76|0.78|0.80|
|Government Effectiveness|R*|0.74|0.78|0.79|0.76|
||R|0.73|0.76|0.78|0.80|
|Regulatory Quality|R*|0.68|0.72|0.73|0.72|
||R|0.52|0.61|0.64|0.60|
|Rule of Law|R*|0.75|0.78|0.80|0.78|
||R|0.79|0.78|0.80|0.81|
|Control of Corruption|R*|0.77|0.80|0.82|0.80|
||R|0.79|0.83|0.83|0.82|
|Press Freedom|R*|0.79|0.83|0.82|0.83|
||R|0.80|0.79|0.79|0.77|
||**_Implie_**|**_d Estimate_**|**_s of_**λ|||
|||**2002**|**2003**|**2004**|**2005**|
|Voice and Accountability||0.57|0.56|0.64|0.40|
|Political Stability||0.03|0.09|0.05|..|
|Government Effectiveness||0.03|0.09|0.05|..|
|Regulatory Quality||0.32|0.28|0.26|0.30|
|Rule of Law||..|..|..|..|
|Control of Corruption||..|..|..|..|
|Press Freedom||..|0.17|0.16|0.28|

Note: ".." indicates that estimates of R* and R are not consistent with a positive value of λ 41
# **Table 7:  Trends in Correlations Among Expert Assessments**

||**dri-eiu**|**1996**<br>**dri-prs**|**eiu-prs**||
|---|---|---|---|---|
|Voice and Accountability|..|..|0.82||
|Political Stability|0.71|0.59|0.66||
|Government Effectiveness|0.81|0.67|0.79||
|Regulatory Quality|0.70|0.56|0.55||
|Rule of Law|0.82|0.72|0.72||
|Control of Corruption|0.83|0.65|0.75||
|||**2005**|||
||**dri-eiu**|**dri-prs**|**eiu-prs**||
|Voice and Accountability|..|..|0.80||
|Political Stability|0.81|0.62|0.54||
|Government Effectiveness|0.74|0.62|0.84||
|Regulatory Quality|0.64|0.79|0.78||
|Rule of Law|0.84|0.70|0.77||
|Control of Corruption|0.81|0.70|0.84||
|||**Change**|||
||**dri-eiu**|**dri-prs**|**eiu-prs**||
|Voice and Accountability|..|..|-0.02||
|Political Stability|0.10|0.03|-0.12||
|Government Effectiveness|-0.07|-0.06|0.05||
|Regulatory Quality|-0.06|0.23|0.23||
|Rule of Law|0.02|-0.02|0.05||
|Control of Corruption|-0.03|0.06|0.09||
||**Sum**<br>|**mary of Cha**<br>|**nges**<br>||
||**dri-eiu**|**dri-prs**|**eiu-prs**|**overall**|
|Median Change|-0.03|0.03|0.05|0.03|
|Changes<0|3|2|2|7|
|Changes>0|2|3|4|9|

Note: Sample size = 103 for VA and 87 for remaining indicators. This implies standard errors for changes of 0.14 and 0.15.

42
# **Table 8:  Serial Correlation of Pair-wise Differences in Country Rankings**

||**Diffe**<br>**(Correlatio**|**rence in R**<br>**n of 1996**|**anks**<br>**with 2005)**||||
|---|---|---|---|---|---|---|
||**dri-eiu**|**dri-prs**|**eiu-prs**|**average R**|**Average**ρ|**Implied (**λ**1+**λ**2)**|
|Voice and Accountability|||0.32|0.32|0.51|0.21|
|Political Stability|0.15|0.42|0.52|0.36|0.40|0.04|
|Government Effectiveness|0.21|0.23|0.09|0.18|0.35|0.18|
|Regulatory Quality|0.28|0.10|-0.06|0.11|0.33|0.23|
|Rule of Law|0.35|0.58|0.31|0.41|0.54|0.16|
|Control of Corruption|0.19|0.34|0.10|0.21|0.38|0.18|
|Average|0.24|0.33|0.21|0.27|0.42|0.17|

43
# **Table 9:  Methodological Breaks in PRS Indicators**

||**1996**|**1996**|**1998**|**1998**|**Change**|**Change**||
|---|---|---|---|---|---|---|---|
||**DRI**|**EIU**|**DRI**|**EIU**|**DRI**|**EIU**||
|**_Series With Breaks in 1997_**||||||||
|Democratic Accountability (VA)|..|0.83|..|0.75|..|-0.08||
|Bureaucratic Quality (GE)|0.67|0.79|0.68|0.62|0.01|-0.18||
|_Median Change_|||||||-0.08|
|_Fraction Increase_|||||||0.33|
|**_Series Without Breaks in 1997_**||||||||
|Military in Politics (VA)||0.72||0.73|..|0.02||
|Internal Conflict (PV)|0.62|0.60|0.74|0.77|0.12|0.17||
|External Conflict (PV)|0.33|0.43|0.51|0.51|0.19|0.08||
|Ethnic Tensions (PV)|0.50|0.56|0.61|0.66|0.11|0.10||
|Government Stability (PV)|0.04|0.14|0.02|0.10|-0.02|-0.04||
|Investment Profile (RQ)|0.56|..|0.54|..|-0.02|..||
|Law and Order (RL)|0.72|0.71|0.74|0.77|0.03|0.05||
|Corruption (CC)|0.64|0.75|0.69|0.68|0.04|-0.07||
|_Median Change_|||||||0.05|
|_Fraction Increase_|||||||0.71|
||**2000**|**2000**|**2002**|**2002**|**Change**|**Change**||
||**DRI**|**EIU**|**DRI**|**EIU**|**DRI**|**EIU**||
|**_Series With Breaks in 2001_**||||||||
|Internal Conflict (PV)|0.68|0.78|0.76|0.75|0.08|-0.03||
|External Conflict (PV)|0.50|0.51|0.44|0.48|-0.06|-0.03||
|Government Stability (PV)|0.09|0.19|0.19|0.20|0.10|0.01||
|Investment Profile (RQ)|0.55||0.68||0.13|||
|Corruption (CC)|0.75|0.75|0.74|0.84|-0.02|0.09||
|_Median Change_|||||||0.01|
|_Fraction Increase_|||||||0.56|
|**_Series Without Breaks in 2001_**||||||||
|Military in Politics (VA)||0.71||0.70||-0.01||
|Democratic Accountability (VA)||0.75||0.79||0.05||
|Ethnic Tensions (PV)|0.46|0.52|0.37|0.44|-0.09|-0.08||
|Bureaucratic Quality (GE)|0.75|0.82|0.73|0.86|-0.02|0.04||
|Law and Order (RL)|0.74|0.70|0.71|0.70|-0.03|0.00||
|_Median Change_|||||||-0.01|
|_Fraction Increase_<br>Note: Break in series identified by fraction of<br>Series identified as having breaks have 40 pe<br>Series identified as having no breaks have les<br>Correlations based on common sample of 97|countries that cha<br>rcent or more of c<br>s than 18 percent<br>countries|nge from mont<br>ountries chang<br>of countries c|h to month in<br>e in a single<br>hange in a sin|PRS<br>month<br>gle month.|||0.38|

44
**Governance Matters V: Appendices** Daniel Kaufmann, Aart Kraay, and Massimo Mastruzzi

# **Appendix A:  Sources for Governance Indicators**

|A1.|African Development Bank (ADB)...................................................... 47|
|---|---|
|A2.|Afro-barometer (AFR) .................................................................... 48|
|A3.|Asian Development Bank (ASD)......................................................<br>49|
|A4.|Bertelsmann Foundation (BTI) .......................................................... 50|
|A5.|Business Environment & Enterprise Performance Survey (BEEPS) ............... 51|
|A6.|Business Environment Risk Intelligence (BRI, QLM) .................................52|
|A7.|Columbia University’s State Capacity Survey (CUD) ............................... 54|
|A8.|Country Policy & Institutional Assessment (CPIA) ................................... 55|
|A9.|Economist Intelligence Unit (EIU) ........................................................ 56|
|A10.|European Bank for Reconstruction and Development (EBR) ............... ........ 57|
|A11.|Freedom House (CCR, FRH, FNT)........................................................ 58|
|A12.|Gallup International (GAL).............................................................. 61|
|A13.|Global E-Government Index (EGV)..................................................... 62|
|A14.|Global Insight's Global Risk Service (DRI) .......................................... 63|
|A15.|Global Insight's Business Conditions and Risk Indicators (WMO).................. 65|
|A16.|Heritage Foundation (HER)......................... ...................................... 67|
|A17.|IJET Country Security Ratings (IJT) .................................................... 68|
|A18.|Institute for Management Development (WCY) ........................................ 69|
|A19.|Media Sustainability Index (MSI)........................................................ 70|
|A20.|Latino-Barometro (LOB)............................................................................... 71|
|A21.|Merchant International Group (MIG)............................................................ 72|
|A22.|Political Economic Risk Consultancy (PRC)........................................... 73|
|A23.|Political Risk Services (PRS).............................................................. 74|
|A24.|Reporters without Borders (RSF)........................................................... 76|
|A25.|State Department’s Trafficking in people Report (TPR).............................. 77|
|A26.|State Department / Amnesty International (HUM)..................................... 78|
|A27.|World Business Environment Survey (WBS, WDR).................................. 79|
|A28.|World Economic Forum (GCS, GCSA) ................................................. 81|

# **Appendix B:  Components of Aggregate Governance Indicators**

|B1.|Voice and Accountability.................................................................. 83|
|---|---|
|B2.|Political Stability and Lack of Violence................................................. 84|
|B3.|Government Effectiveness................................................................ 85|
|B4.|Regulatory Quality.......................................................................... 86|
|B5.|Rule of Law.................................................................................. 88|
|B6.|Control of Corruption...................................................................... 89|

# **Appendix C:  Governance Indicators over Time**

|C1.|Voice and Accountability.................................................................. 90|
|---|---|
|C2.|Political Stability and Lack of Violence.................................................. 93|
|C3.|Government Effectiveness................................................................. 96|
|C4.|Regulatory Quality.......................................................................... 99|
|C5.|Rule of Law.................................................................................. 102|
|C6.|Control of Corruption....................................................................... 105|
|**Appe**|**ndix D:**........................................................................................ 108|

45
# **TABLE A1.  African Development Bank (ADB)**

## **A1: African Development Bank (ADB)**

http://www.afdb.org/ The African Development Bank (ADB) is a major development bank in Africa. Established in 1963 in order to promote economic and social development, the Bank has grown into a $33 billion, multinational development bank, with 52 African countries and 24 other shareholders.

The African Development Bank develops its own "Country Policy and Institutional Assessments" for its own client sample. Similarly to the World Bank's CPIA, the ADB Indicators annually assess the quality of African Development Bank borrowers’ policy and institutional performance in areas relevant to economic growth and poverty reduction. Data is publicly disclosed only on a limited basis.

In the table below we list the variables included in each of the governance indicators. We use data from 2000, and from 2002-2005.

|**Table A1: Africa Developme**|**nt Bank(50 African**|**coun**|**tries)**|||||
|---|---|---|---|---|---|---|---|
||2005|2004|2003|2002|2000|1998|1996|
|**Voice and Accountability**||||||||
|NA|..|..|..|..|..|..|..|
|**Political Stability**||||||||
|NA|..|..|..|..|..|..|..|
|**Government Effectiveness**||||||||
|Policies to improve efficiency of public sector|X|X|X|X|X|..|..|
|Budget Management|X|X|X|X|X|..|..|
|Efficiency of Public Expenditures|X|X|X|X|X|..|..|
|Management of public debt|X|X|X|X|X|..|..|
|**Regulatory Quality**||||||||
|Trade policy|X|X|X|X|X|..|..|
|Competitive environment|X|X|X|X|X|..|..|
|Labor Market Policies|X|X|X|X|X|..|..|
|**Rule of Law**||||||||
|Property rights|X|X|X|X|X|..|..|
|**Control of Corruption**||||||||
|Anti-corruption policies|..|X|X|X|X|..|..|
|Transparency / corruption|X|X|X|X|X|..|..|

46
# **TABLE A2.  Afrobarometer (AFR)**

## **A2: Afrobarometer (AFR)**

http://www.afrobarometer.org The Afrobarometer is a joint enterprise of Michigan State University (MSU), the Institute for Democracy in South Africa (IDASA) and the Centre for Democracy and Development (CDD, Ghana). The Afrobarometer Series, launched in October 1999, reports the results of national sample surveys on the attitudes of citizens in selected African countries towards democracy, markets and other aspects of development. The objective of the Afrobarometer is to collect, analyze and disseminate cross-national, time-series attitudinal data for up to a dozen new democracies on the African continent.

In the table below we list the variables included in each of the governance indicators. We use data from the 2000, 2002 and 2005 Surveys. 2003 and 2004 data were drawn from 2002 survey.

|**Table A2: Afrobarometer(18 African**|**count**|**ries)**||||||
|---|---|---|---|---|---|---|---|
||2005|2004|2003|2002|2000|1998|1996|
|**Voice and Accountability**||||||||
|How much do you trust the parliament?|..|X|X|X|..|..|..|
|Overall, how satisfied are you with the way democracy works in your<br>country?|..|X|X|X|X|..|..|
|Free elections|X|..|..|..|..|..|..|
|**Political Stability**||||||||
|NA|..|..|..|..|..|..|..|
|**Government Effectiveness**||||||||
|What proportion of the country's problems do you think the government<br>can solve?|..|X|X|X|..|..|..|
|Based on your experiences, how easy or difficult is it to obtain<br>household services (like piped water, electricity or telephone)?|X|X|X|X|..|..|..|
|Based on your experiences, how easy or difficult is it to obtain an<br>identity document (such as birth certificate, driver's license or passport)?|X|X|X|X|..|..|..|
|Government handling of health services|X|..|..|..|..|..|..|
|Government handling of education system|X|..|..|..|..|..|..|
|**Regulatory Quality**||||||||
|NA|..|..|..|..|..|..|..|
|**Rule of Law**||||||||
|Over the past year, how often have you or anyone in your family feared<br>crime in your own home?|..|X|X|X|..|..|..|
|Over the past year, how often have you or anyone in your family had<br>something stolen from your house?|..|X|X|X|..|..|..|
|Over the past year, how often have you or anyone in your family been<br>physically attacked?|..|X|X|X|..|..|..|
|How much do you trust the courts of law?|..|X|X|X|..|..|..|
|How much do you trust the police?|..|X|X|X|X|..|..|
|Based on your experiences, how easy or difficult is it to obtain help from<br>the police when you need it?|X|X|X|X|..|..|..|
|**Control of Corruption**||||||||
|How well would you say the current government is handling the fight of<br>corruption in the government?|..|X|X|X|..|..|..|
|How many elected leaders (parliamentarians) do you think are involved<br>in corruption?|X|X|X|X|..|..|..|
|<br>How many judges and magistrates do you think are involved in|X|X|X|X|..|..|..|
|How many government officials do you think are involved in corruption?|X|X|X|X|X|..|..|
|How many border/tax officials do you think are involved in corruption?|X|X|X|X|..|..|..|

47
# **TABLE A3.  Asian Development Bank (ASD)**

## **A3: Asian Development Bank (ASD)**

http://www.adb.org/ The Asian Development Bank is a multilateral development finance institution dedicated to reducing poverty in Asia and the Pacific. Established in 1966, the ADB - headquartered in Manila and with 26 offices worldwide - is currently owned by 63 member countries, mostly from the region.

The Asian Development Bank develops its own "Country Policy and Institutional Assessments" for its own Client sample. Similarly to the World Bank's CPIA, the ASD Indicators annually assess the quality of Asian Development Bank borrowers’ policy and institutional performance in areas relevant to economic growth and poverty reduction. Data is publicly disclosed only on a limited basis.

In the table below we list the variables included in each of the governance indicators. We use data from 2000, and from 2002-2005.

|**Table A3: Asian Developm**|2005<br>**ent Bank(26 Asian**|2004<br>**count**|2003<br>**ries)**|2002|2000|1998|1996|
|---|---|---|---|---|---|---|---|
|**Voice and Accountability**||||||||
|NA|..|..|..|..|..|..|..|
|**Political Stability**||||||||
|NA|..|..|..|..|..|..|..|
|**Government Effectiveness**||||||||
|Competence of civil service|X|X|X|X|X|..|..|
|Budget Management|X|X|X|X|X|..|..|
|Efficiency of Public Expenditures|X|X|X|X|X|..|..|
|Management of public debt|X|X|X|X|X|..|..|
|**Regulatory Quality**||||||||
|Trade policy|X|X|X|X|X|..|..|
|Competitive environment|X|X|X|X|X|..|..|
|Factor and products markets|..|X|X|X|X|..|..|
|**Rule of Law**||||||||
|Property rights|X|X|X|X|X|..|..|
|**Control of Corruption**||||||||
|Anticorruption and Accounting Institutions|X|X|X|X|X|..|..|

48
# **TABLE A4:  Bertelsmann Transformation Index (BTI)**

## **A4: Bertelsmann Tranformation Index (BTI)**

http://www.bertelsmann-transformation-index.de/atlas.0.html?&L=1 Founded by Reinhard Mohn in 1977 and headquartered in Berlin, the **Bertelsmann Foundation** is a non-profit organization dedicated to identifying social problems and challenges early on in order to develop and implement model solutions.

Starting in 2004, the Foundation began publishing the **Bertelsmann Transformation Index** (BTI), a global ranking that analyzes and evaluates development and transformation processes in 116 countries. The Bertelsmann Transformation Index provides the international public and political actors with a comprehensive view of the status of democracy and a market economy as well as the quality of political management in each of these countries.

The goal of a consolidated market-based democracy constitutes the BTI’s normative framework. The BTI analyzes the status of both democratization and market liberalization as it evaluates actors’ performance in managing these changes. The quantitative data collected for the Bertelsmann Transformation Index 2003 is outlined in two parallel indices: the **Status Index** and the **Management Index.** The Status Index (SI) shows the development achieved by 116 states on their way toward democracy and a market economy. States with functioning democratic and market-based structures receive the highest scores. The Management Index (MI) reveals the extent to which governments and political actors have been consistent and determined in their pursuit of a market-based democracy. Those states showing progress in the last five years and in which transformation has resulted from astute management receive the highest scores.

In the table below we list the variables included in each of the governance indicators. We use data from 2004, drawing 5 variables from the Management Index and 6 variables from the Status Index.

|**Table A4: Bertelsman Transform**|2005<br>**ation Index(119 develo**|2004<br>**ping c**|2003<br>**ountr**|2002<br>**ies)**|2000|1998|1996|
|---|---|---|---|---|---|---|---|
|**Voice and Accountability**||||||||
|Political Participation (SI)|X|X|..|..|..|..|..|
|Institutional Stability (SI)|X|X|..|..|..|..|..|
|Political and Social Integration (SI)|X|X|..|..|..|..|..|
|**Political Stability**||||||||
|NA|..|..|..|..|..|..|..|
|**Government Effectiveness**||||||||
|Consensus Building (MI)|X|X|..|..|..|..|..|
|Governance Capability (MI)|X|X|..|..|..|..|..|
|Effective Use of Resources (MI)|X|X|..|..|..|..|..|
|**Regulatory Quality**||||||||
|Price Stability (SI)|X|X|..|..|..|..|..|
|Competition (SI)|X|X|..|..|..|..|..|
|**Rule of Law**||||||||
|Rule of Law (SI)|X|X|..|..|..|..|..|
|Private Property (SI)|X|X|..|..|..|..|..|
|**Control of Corruption**||||||||
|NA|..|..|..|..|..|..|..|

49
# **TABLE A5.  Business Environment and Enterprise Performance Survey (BEEPS)**

## **A5: Business Environment and Enterprise Performance Survey (BEEPS)**

http://www.worldbank.org/eca/governance The Business Environment and Enterprise Performance Survey (BEEPS) was developed jointly by the World Bank and the European Bank for Reconstruction and Development. In its first round conducted in 1999-2000, it surveyed over 4,000 firms in 22 transition countries that examined a wide range of interactions between firms and the state. In its second round conducted in 2002, the survey covered over 2,100 firms in 27 countries. In its second round conducted in 2005, the survey covered almost 10,000 firms in 27 countries.

In the table below we list the variables included in each of the governance indicators. We use data from 2005/6, 2002/3 and 1999/2000 surveys. 2003 and 2004 data were drawn from the 2002 survey.

|**Table A5: Business Environment and Enterprise Performance Survey **|**(27 Tra**|**nsition**|**Eco**|**nomie**|**s)**|||
|---|---|---|---|---|---|---|---|
||2005|2004|2003|2002|2000|1998|1996|
|**Voice and Accountability**||||||||
|NA|..|..|..|..|..|..|..|
|**Political Stability and Lack of Violence**<br>||||||||
|NA|..|..|..|..|..|..|..|
|**Government Effectiveness**||||||||
|How problematic are telecommunications for the growth of your business|X|X|X|X|..|..|..|
|How problematic is electricity for the growth of your business.|X|X|X|X|..|..|..|
|How problematic is transportation for the growth of your business.|X|X|X|X|..|..|..|
|**Regulatory Quality**||||||||
|Information on the laws and regulations is easy to obtain|X|X|X|X|..|..|..|
|Interpretations of the laws and regulations are consistent and predictable|..|X|X|X|..|..|..|
|Unpredictability of changes of regulations|X|X|X|X|..|..|..|
|How problematic are labor regulations for the growth of your business.|X|X|X|X|..|..|..|
|How problematic are tax regulations for the growth of your business.|X|X|X|X|..|..|..|
|How problematic are custom and trade regulations for the growth of your business.|X|X|X|X|..|..|..|
|**Rule of Law**||||||||
|How often is following characteristic associated with the court system: Fair|X|X|X|X|..|..|..|
|How often is following characteristic associated with the court system: affordable|X|X|X|X|..|..|..|
|How often is following characteristic associated with the court system: enforceable|X|X|X|X|..|..|..|
|How often is following characteristic associated with the court system: Honesty|X|X|X|X|..|..|..|
|How often is following characteristic associated with the court system: Quickness|X|X|X|X|..|..|..|
|Are property rights adequately protected|X|X|X|X|..|..|..|
|How problematic is organized crime for the growth of your business.|X|X|X|X|..|..|..|
|How problematic is judiciary for the growth of your business.|X|X|X|X|..|..|..|
|How problematic is street crime for the growth of your business.|X|X|X|X|..|..|..|
|**Control of Corruption**||||||||
|How common is for firms to have to pay irregular additional payments to get things done|X|X|X|X|..|..|..|
|Percentage of total annual sales do firms pay in unofficial payments to public officials|X|X|X|X|..|..|..|
|How often do firms make extra payments to influence the content of new legislation|X|X|X|X|..|..|..|
|Extent to which firms' payments to public officials impose costs on other firms|X|X|X|X|X|..|..|
|How problematic is corruption for the growth of your business.|X|X|X|X|..|..|..|

50
# **TABLE A6:  Business Environment Risk Intelligence (BRI, QLM)**

## **A6: Business Environment Risk Intelligence (BRI)**

http://www.beri.com BERI S.A. is a private source of analysis and forecasts of the business environment in developed and developing countries. The firm was founded in 1966 and is headquartered in Geneva, Switzerland.

BERI has two services that include variables of interest for the purpose of this paper: The Business Risk Service, and the FORELEND or Lender Risk Rating. Both services are supervised by Dr. F.T. Haner, founder and senior editor. A number of analysts review various data sources and produce initial draft reports, relying on an international network of sources for intelligence in the field. BERI convenes two permanent panels of about 105 experts from all over the world. These panels provide country ratings and qualitative observations on the basis of these initial reports. One panel assesses political conditions, and the other offers perspectives on the business operating environment. These ratings are constructed using the Delphi method, in which panelists are also supplied with the ratings they produced in previous assessments as well as the panel average score for each measure.

BERI monitors 50 countries three times per year, assessing 57 criteria separated into three indices. The Political Risk Index (PRI) focuses on sociopolitical conditions in a country. Diplomats and political scientists rate the present condition of eight causes and two symptoms of political risk, using a scale from 7 (no problem) to 0 (prohibitive problem). The Operation Risk Index (ORI) identifies major bottlenecks for business development, rating 15 criteria on a scale of 0 (unacceptable conditions) to 4 (superior conditions). The R factor assesses a country’s willingness to allow foreign companies to convert and repatriate profits and to import components, equipment and raw materials. It is composed of 4 sub-indices, one of which assesses the quality of legal framework in terms of statutory laws and actual practice.

BERI also produced a different set of indicators, the Quantitative Risk Measure in Foreign Lending (QLM), measurings the qualitative risk factors in credit exposure in 115 countries using a scale from 0 (high risk) to 100 (low risk). In the table below we list the variables included in each of the governance indicators. We use BERI's data for the last quarters of 1996, 1998, 2000, and 2002-2005.

51
|**Table A6: Business Environment Risk Intelligence(50 developed and develo**|2005<br>**ping c**|2004<br>**ountr**|2003<br>**ies)**|2002|2000|1998|1996|
|---|---|---|---|---|---|---|---|
|**Voice and Accountability**<br>NA|..|..|..|..|..|..|..|
|**Political Stability**<br>||||||||
|Political Risk Index: External Causes of Political Risk: Dependence<br>on/Importance to a Hostile Major Power|X|X|X|X|X|X|X|
|Political Risk Index: External Causes of Political Risk: Negative Influences of<br>Regional Political Forces|X|X|X|X|X|X|X|
|Political Risk Index: Internal Causes of Political Risk: Social Conditions: Wealth<br>Distribution, Population|X|X|X|X|X|X|X|
|Political Risk Index: Internal Causes of Political Risk: Fractionalization of political<br>spectrum and the power of these factions.<br>|X|X|X|X|X|X|X|
|Political Risk Index: Internal Causes of Political Risk: Fractionalization by<br>language, ethnic and/or religious groups and the power of these factions.<br>|X|X|X|X|X|X|X|
|Political Risk Index: Internal Causes of Political Risk: Restrictive (coercive)<br>measures required to retain power.|X|X|X|X|X|X|X|
|Political Risk Index: Internal Causes of Political Risk: Organization and strength<br>of forces for a radical government.|X|X|X|X|X|X|X|
|Political Risk Index: Symptoms of Political Risk: Societal conflict involving<br>demonstrations, strikes, and street violence.|X|X|X|X|X|X|X|
|Political Risk Index: Symptoms of Political Risk: Instability as perceived by non-<br>constitutional changes, assassinations, and guerilla wars.|X|X|X|X|X|X|X|
|**Government Effectiveness**||||||||
|Operation Risk Index: Bureaucratic delays|X|X|X|X|X|X|X|
|**Regulatory Quality**<br>NA|..|..|..|..|..|..|..|
|**Rule of Law**||||||||
|Operation Risk Index: Enforceability of contracts|X|X|X|X|X|X|X|
|Direct Financial Fraud, Money Laundering and Organized Crime (QLM) *|X|X|X|X|X|X|X|
|**Control of Corruption**||||||||
|Political Risk Index: Internal Causes of Political Risk: Mentality, including<br>xenophobia, nationalism, corruption, nepotism, willingness to compromise.|X|X|X|X|X|X|X|
|Indirect Diversion of Funds (QLM) *|X|X|X|X|X|X|X|
|_* country coverage: 115 countries_||||||||

52
# **TABLE A7:  Columbia University (CUD)**

## **A7: State Capacity Survey (CUD)**

http://www.columbia.edu The State Capcity Survey was developed in 1999 under the direction of Marc Levy of the CIESIN at Columbia University, resulting in a set of 31 multiple-choice questions and three open-ended questions. The survey asks questions in five broad categories: political context, state legitimacy, human resources and organizations, institutions, and overall capacity. Data were obtained on 108 and 97 countries from assessments completed by 164 experts during 2000 and 2002, respectively.

In the table below we list the questions included in each of the governance indicators. We use data from the 2000 and 2002 surveys. 2003 and 2004 data were drawn from the 2002 survey.

|<br>**Table A7: State Capacity Survey (108 developed and developing co**|2005 2004 <br>**untries)**|2003|2002|2000|1998 1996|
|---|---|---|---|---|---|
|**Voice and Accountability**||||||
|For the most part, is the state seen as legitimately representing its citizens?|..<br>X|X|X|X|..<br>..|
|To what extent does the state and/or its allied groups engage in repression of its citizens?|..<br>X|X|X|X|..<br>..|
|In carrying out internal security tasks, to what extent does the state rely on tactics commonly<br>considered illegitimate in the international community?|..<br>X|X|X|X|..<br>..|
|**Political Stability**||||||
|Assess the degree to which the decline or collapse of central political authority posed a threat to<br>political stability in this country.|..<br>X|X|X|X|..<br>..|
|Assess the degree to which political protest posed a threat to political stability in this country.|..<br>X|X|X|X|..<br>..|
|Assess the degree to which ethno-cultural and/or religious conflict posed a threat to political<br>stability in this country.|..<br>X|X|X|X|..<br>..|
|Assess the degree to which external military intervention posed a threat to political stability in this<br>country.|..<br>X|X|X|X|..<br>..|
|**Government Effectiveness**||||||
|Rate the administrative and technical skills of the country’s civil service (occupying middle and<br>higher management roles).|..<br>X|X|X|X|..<br>..|
|Rate the efficiency of the country’s national bureaucracies overall.|..<br>X|X|X|X|..<br>..|
|Rate the efficiency of the country’s local-level government bureaucracies overall.|..<br>X|X|X|X|..<br>..|
|Rate the effectiveness of coordination between the central government and local-level government<br>organizations.|..<br>X|X|X|X|..<br>..|
|Rate the state’s ability to formulate and implement national policy initiatives.||||||
|Rate the state’s effectiveness at collecting taxes or other forms of government revenue.|..<br>X|X|X|X|..<br>..|
|Does the central government produce a national budget in a timely manner?|..<br>X|X|X|X|..<br>..|
|Do local governments produce budgets in a timely manner?|..<br>X|X|X|X|..<br>..|
|Rate the state’s ability to monitor socioeconomic trends, activities, and conditions within its borders|..<br>X|X|X|X|..<br>..|
|Rate the state’s ability to create, deliver, and maintain vital national infrastructure.|..<br>X|X|X|X|..<br>..|
|Rate the state’s ability to respond effectively to domestic economic problems.|..<br>X|X|X|X|..<br>..|
|Rate the state’s ability to respond effectively to natural disasters.|..<br>X|X|X|X|..<br>..|
|**Regulatory Quality**||||||
|NA|..<br>..|..|..|..|..<br>..|
|**Rule of Law**||||||
|Rate the state’s adherence to the rule of law, considering the country as a whole.|..<br>X|X|X|X|..<br>..|
|**Control of Corruption**||||||
|Rate the severity of corruption within the state|..<br>X|X|X|X|..<br>..|
|<br>To what extent do the country's primary political decision makers engage in patterns of nepotism,<br>cronyism and patronage?|..<br>X|X|X|X|..<br>..|
|<br>To what extent do the country's civil service (occupying middle and higher management roles)<br>engage in patterns of nepotism, cronyism and patronage?|..<br>X|X|X|X|..<br>..|
|To what extent do patterns of nepotism, cronyism and patronage undermine the state's ability to<br>exercise the basic functions of government effectively?|..<br>X|X|X|X|..<br>..|
|To what extent do patterns of nepotism, cronyism and patronage distort broad patterns of economic<br>development?|..<br>X|X|X|X|..<br>..|

53
# **TABLE A8:  Country Policy and Institutional Assessments (CPIA)**

## **A8: Country Policy & Institutional Assessment (CPIA)**

http://www.worldbank.org The Country Policy and Institutional Assessment (CPIA) annually assesses the quality of World Bank borrowers’ policy and institutional performance in areas relevant to economic growth and poverty reduction. Country assessments began in the World Bank in the late 1970s to help guide the allocation of lending resources. The methodology has evolved over time, reflecting lessons learned and mirroring the evolution of the development paradigm. While in earlier years assessments focused mainly on macroeconomic policies, they now include other factors relevant to poverty reduction, such as social inclusion, equity and governance.

The CPIA consists of equally weighted criteria representing the policy dimensions of an effective poverty reduction and growth strategy. The criteria are grouped in four clusters. Cluster A, Economic Management, covers economic policies. Cluster B, Structural Policies, covers a broad range of structural policies: trade policies, financial depth, market competition, and environmental sustainability. Cluster C, Policies for Social Inclusion and Equity, focuses on social equity and broad-based growth, and aims to capture the extent to which a country's policies and institutions ensure that the benefits of growth are widespread, contribute to the accumulation of social capital, and direct public programs to poor people and reduce their vulnerability to various kinds of shocks. Cluster D, Public Sector Management and Institutions, aims to capture key aspects of good governance, a vital For each of the criteria, countries are assessed on a scale of 1 (low) to 6 (high). The ratings are prepared by the World Bank's country economists and focus on the quality of the country's current policies and institutions, which are the main determinants of the present prospects for aid effectiveness. The rating assigned for each criterion reflects a variety of indicators, observations, and judgments: ratings are based on country knowledge obtained from country dialogue and the Country Assistance Strategy (CAS) process, the available body of economic and sector work (ESW), project preparation and supervision, and project and CAS monitoring and evaluation.

In the table below we list the variables included in each of the governance indicators. We use data for 1996, 1998, 2000, and 2002-2005.

|**Table A8: Country Policy & Institutional Assessme**|2005<br>**nt(136 dev**|2004<br>**elopin**|2003<br>**g co**|2002<br>**untrie**|2000<br>**s)**|1998|1996|
|---|---|---|---|---|---|---|---|
|**Voice and Accountability**||||||||
|NA|..|..|..|..|..|..|..|
|**Political Stability and Lack of Violence**||||||||
|NA|..|..|..|..|..|..|..|
|**Government Effectiveness**||||||||
|Management of external debt|X|X|X|X|X|X|X|
|Management of development programs|..|..|X|X|X|X|..|
|Quality public Administration / Public expenditure management|X|X|X|X|X|X|X|
|Budget Management|X|X|X|X|X|X|X|
|Efficiency of Public Expenditures|X|X|X|X|X|X|X|
|**Regulatory Quality**||||||||
|Competitive environment|X|X|X|X|X|X|X|
|Factor and products markets|..|..|X|X|X|X|X|
|Trade policy|X|X|X|X|X|X|X|
|**Rule of Law**||||||||
|Property rights|X|X|X|X|X|X|..|
|**Control of Corruption**||||||||
|Transparency, accountability and corruption in public sector|X|X|X|X|X|X|..|

54
# **TABLE A9: Economist Intelligence Unit (EIU)**

## **A9: The Economist Intelligence Unit (EIU)**

http://www.eiu.com The Economist Intelligence Unit is a for-profit organization producing analysis and forecasts of the political, economic and business environment in more than 180 countries. The EIU was founded in 1949 and is based in London. In 1997, the EIU launched two quarterly publications which contain some governance measures: The Country Risk Service, and the Country Forecasts. The assessments in these publications are based on regular contributions from a global network of more than 500 information-gatherers. A panel of regional experts checks the accuracy, consistency and impartiality of these assessments. Our databases utilize data about the individual subcomponents of these country risk ratings, that were made available to us by EIU.

In the table below we list the variables included in each of the governance indicators. In this paper, we use data from 1997, 1998, 2000, and 2002-2005.

|**Table A9: Economist Intelligence Unit(120**|**developed and dev**|**elopin**|**g coun**|**tries)**||||
|---|---|---|---|---|---|---|---|
||2005|2004|2003|2002|2000|1998|1996|
|**Voice and Accountability**||||||||
|Orderly transfers<br>|X|X|X|X|X|X|X|
|Vested interests|X|X|X|X|..|..|X|
|Accountablity of Public Officials|X|X|X|X|..|..|X|
|Human Rights|X|X|X|X|..|..|X|
|Freedom of association|X|X|X|X|..|..|X|
|**Political Stability**||||||||
|Armed conflict|X|X|X|X|X|X|X|
|Violent demonstrations|X|X|X|X|..|..|X|
|Social Unrest|X|X|X|X|X|X|X|
|International tensions / terrorist threat|X|X|X|X|X|X|X|
|**Government Effectiveness**||||||||
|Quality of bureaucracy / institutional effectiveness|X|X|X|X|X|X|X|
|Excessive bureacucracy / red tape|X|X|X|X|X|X|X|
|Government policy (pro business stance)|..|..|..|..|X|X|..|
|**Regulatory Quality**||||||||
|Unfair competitive practices|X|X|X|X|..|..|X|
|Price controls|X|X|X|X|..|..|X|
|Discriminatory tariffs|X|X|X|X|..|..|X|
|Excessive protections|X|X|X|X|..|..|X|
|Discriminatory taxes|X|X|X|X|..|..|X|
|**Rule of Law**||||||||
|Violent crime|X|X|X|X|X|X|X|
|Organized crime|X|X|X|X|X|X|X|
|Fairness of judicial process|X|X|X|X|X|X|X|
|Enforceability of contracts|X|X|X|X|..|..|X|
|Speediness of judicial process|X|X|X|X|..|..|X|
|Confiscation/expropriation|X|X|X|X|..|..|X|
|Intellectual property rights protection|X|X|X|X|..|..|X|
|Private property protection|X|X|X|X|..|..|X|
|**Control of Corruption**||||||||
|Corruption among public officials|X|X|X|X|X|X|X|
|_Country coverage_|_120_|_120_|_115_|_115_|_115_|_115_|_115_|

55
# **TABLE A10: European Bank for Reconstruction and Development (EBR)**

## **A10: European Bank for Reconstruction and Development (EBR)**

http://www.ebrd.org The EBRD is an international organization which supports the transition towards open market-oriented economies and promotes private and entrepreneurial initiative in the countries of Central and Eastern Europe and the Commonwealth of Independent States (CIS). The EBRD is based in London.

The EBRD publishes an annual Transition Report, which includes a number of governance variables in its Transition Indicators and Survey of Legal Reforms. The Transition Report presents eight “Transition Indicators” representing "cumulative progress in the movement from a centrally planned economy to a market economy” for 26 transition economies. The subjective indicators are based on a checklist of various objective measures and reflect the views of EBRD staff.

Beginning in 1996, the EBRD has conducted in 26 countries a survey of local public officials, private firms, academics, lawyers, and other experts, in order to assess the progress made in financial legal reform in transition economies. The survey considered two areas of financial legal reform: banking and securities activities. For each area, two indices describing the extensiveness and effectiveness of the financial legal framework were developed, for a total of four ratings. The “extensiveness” ratings measure how closely legal rules affecting investment follow international standards. “Effectiveness” reflects how clear, accessible and adequatelysupported the legal rules are. Both are intended to provide a measure of how conducive the laws of these countries are to fostering investment. Both indices however were discontinued in 2003.

In this paper we use data from the 1996, 1998, 2000, and 2002-2005 Transition Reports. In the table below we list the variables included in each of the governance indicators.

|**Table A10: European Bank for Reconstructi**|2005<br>**on and Development(27**|2004<br>**trans**|2003<br>**ition**|2002<br>**econo**|2000<br>**mies**|1998<br> **)**|1996|
|---|---|---|---|---|---|---|---|
|**Voice and Accountability**||||||||
|NA|..|..|..|..|..|..|..|
|**Political Stability**||||||||
|NA|..|..|..|..|..|..|..|
|**Government Effectiveness**||||||||
|NA|..|..|..|..|..|..|..|
|**Regulatory Quality**||||||||
|Price liberalisation|X|X|X|X|X|X|X|
|Trade & foreign exchange system|X|X|X|X|X|X|X|
|Competition policy|X|X|X|X|X|X|X|
|Commercial Law Extensiveness|..|..|..|X|X|X|..|
|Commercial Law Effectiveness|..|..|..|X|X|X|..|
|Financial Regulations: extensiveness|..|..|..|X|X|X|..|
|Financial regulations: effectiveness|..|..|..|X|X|X|..|
|**Rule of Law**||||||||
|NA|..|..|..|..|..|..|..|
|**Control of Corruption**||||||||
|NA|..|..|..|..|..|..|..|

56
# **TABLE A11:  Freedom House (FRH, FHT, CCR)**

## **A11: Freedom House (FRH, FNT, CCR)**

http://www.freedomhouse.org.

Freedom House is a non-governmental organization which promotes democratic values around the world. Freedom House was established in 1941 and is headquartered in New York City. We rely on data from three Freedom House publications. "Freedom in the World" was launched in 1955, and became an annual publication in 1978, covering 192 countries and/or related and disputed territories. "Nations in Transit" was launched in 1995 and covers 28 post-communist countries. Finally, "Countries at the CrossRoads" was launched in 2004 and covers 30 developing countries. Freedom House develops its assessments using a team of academic advisors, in-house experts, published resources, and local correspondents including human rights activists, journalists, editors and political figures. Freedom House staff also conduct regular fact-finding missions to countries being assessed. An academic advisory board provides input to the project in general. **Freedom in the World (FRH).** This publication evaluates political rights and civil liberties around the world. Freedom House defines political rights as those freedoms that enable people to participate freely in the political process, and civil liberties as the freedom to develop views, institutions and personal autonomy apart from the state. For all countries, the subjective assessments are based on checklists of rights and freedoms. A Freedom House team assigns a rating to each item on the checklist and produces an initial assessment for each country. The team then assess whether the checklists might have missed an important factor for a particular country. The scores are then reviewed to ensure quality and consistency across countries, and a final rating is produced. **Freedom House Nations in Transit (FNT).** This publication evaluates the progress in democratic and economic reform in post-communist countries. Country surveys are written by Freedom House staff or consultants and are reviewed by academics and senior Freedom House staff. Each report is divided into nine sections, ranging from the political process to progress in price liberalization. For each section, a preliminary rating is based on a checklist of issues. The academic oversight board establishes the final ratings by consensus following extensive discussions and debate, which are reviewed by the Freedom House rating committee. **Countries at the Crossroads (CCR).** This publication is a survey of democratic governance that evaluates performance in 30 key countries that are at a crossroads in determining their political future. The Countries at the Crossroads survey offers scholars, analysts, and officials a comparative tool for assessing government performance in the areas of civil liberties, rule of law, anticorruption and transparency, and accountability and In the table below we list the variables included in each of the governance indicators. In this paper we use data from the 1996, 1998, 2000, and 2002-2005 editions of Freedom in the World, the 2004 and 2005 editions of Countries at the Crossroads and the 1996, 1998, 2000, and 2002-2005 editions of Nations in Transit.

57
|**Table A11: Freedom in the World (193 developed and developing countries) / N**<br>**economies) / Countries at the Crossroads(30 developing **|2005 2004 2003 2002 2000 1998 1996<br>**ations in Transit (27 transition**<br>**countries)**|
|---|---|
|**Voice and Accountability**||
|_Political Rights_<br>Is the head of state and/or head of government or other chief authority elected through<br>free and fair elections?<br>Are the legislative representatives elected through free and fair elections?<br>Are there fair electoral laws?|X<br>X<br>X<br>X<br>X<br>X<br>X|
|Are the voters able to endow their freely elected representatives with real power?<br>Do the people have the right to freely organize in different political parties or other<br>competitive political groupings of their choice, and is the system open to the rise and<br>fall of these competing parties or groupings?<br>Is there a significant opposition vote, de facto opposition power, and a realistic<br>possibility for the opposition to increase its support or gain power through elections?<br>Are the people free from domination by the military, foreign powers, totalitarian parties,<br>religious hierarchies, economic oligarchies or any other powerful groups?<br>Do cultural, ethnic, religious and other minority groups have reasonable self-<br>determination, self-government, autonomy or participation through informal consensus<br>in the decision-making process?||
|_Civil Liberties_<br>Are there free and independent media, literature and other cultural expressions?<br>Is there open public discussion and free private discussion?<br>Is there freedom of assembly and demonstration?<br>Is there freedom of political or quasi-political organization?<br>Are citizens equal under the law, with access to an independent, nondiscriminatory<br>judiciary, and are they respected by the security forces?<br>Is there protection from political terror, and from unjustified imprisonment, exile or<br>torture, whether by groups that support or oppose the system, and freedom from war or<br>insurgency situations?<br>Are there free trade unions and peasant organizations or equivalents, and is there<br>effective collective bargaining?<br>Are there free professional and other private organizations?<br>Are there free businesses or cooperatives?<br>Are there free religious institutions and free private and public religious expressions?<br>Are there personal social freedoms, which include such aspects as gender equality,<br>property rights, freedom of movement, choice of residence, and choice of marriage and<br>size of family?<br>Is there equality of opportunity, which includes freedom from exploitation by or<br>dependency on landlords, employers, union leaders, bureaucrats or any other type of<br>denigrating obstacle to a share of legitimate economic gains?<br>Is there freedom from extreme government indifference and corruption|X<br>X<br>X<br>X<br>X<br>X<br>X|

58
|**Table A11: Freedom in the World (193 developed and developing countries) / N**<br>**economies) / Countries at the Crossroads(30 developing cou**|2005 <br>**ations**<br>**ntries)**|2004 <br>**in Tr**<br>**- co**|2003 <br>**ansi**<br>**nt.**|2002<br>**t (27**|200<br>**tran**|0 1998 <br>**sition**|1996<br>|
|---|---|---|---|---|---|---|---|
|_Freedom of the Press_<br>Laws and Practice: Assess whether or not dissent is allowed, if private media are<br>permitted alongside governmental broadcasting, if independent media, in practice, are<br>permitted to express diverse views<br>Political Influence over Media Content: This category reflects political pressure on the<br>content of both privately owned and government media, and takes into account the day-<br>to-day conditions in which journalists work, threats from organized crime, or from<br>religious extremists, for example, often generate self-censorship and so negatively<br>affect the media environment<br>Economic influence over Media Content: Influence may come from the government or<br>from private entrepreneurs. This reflects competitive pressures in the private sector<br>that distort reportage as well as economic favoritism or reprisals by government for<br>unwanted press coverage<br>Actual Incident of Violations of Press Freedom: Murders, arrests, suspension and other<br>violations create a sense of fear which may discourage objective reporting|X|X|X|X|X|X|X|
|_Nations in Transit_||||||||
|Political Process: Deals with elections, referenda, party configuration, conditions for<br>political competition, and popular participation in elections.|X|X|X|X|X|X|X|
|Civil Society: Highlights the degree to which volunteerism, trade unionism, and<br>professional associations exist, and whether civic organizations are influential|X|X|X|X|X|X|X|
|Independent Media: Press freedom, public access to a variety of information sources,<br>and independence of those sources from undue government or other influences.|X|X|X|X|X|X|X|
|_Countries at the Crossroads_||||||||
|Civil Liberties|X|X|..|..|..|..|..|
|Accountability and public voice|X|X|..|..|..|..|..|
|**Political Stability**||||||||
|NA|..|..|..|..|..|..|..|
|**Government Effectiveness**||||||||
|_Nations in Transit:_Government and Administration: Government decentralization,||||||||
|independent and responsibilities or local and regional governments, and legislative and<br>executive transparency are discussed.|X|X|X|X|X|X|X|
|**Regulatory Quality**||||||||
|N/A|..|..|..|..|..|..|..|
|**Rule of Law**||||||||
|_Nations in Transit:_Considers judicial and constitutional matters as well as the legal and|X|X|X|X|X|X|X|
|de facto status of ethnic minorities.||||||||
|_Countries at the Crossroads:_Rule of Law|X|X|..|..|..|..|..|
|**Control of Corruption**||||||||
|<br>_Nations in Transit:_corruption|X|X|X|X|X|X|..|
|_Countries at the Crossroads:_Anti-Corruption and Transparency|X|X|..|..|..|..|..|

59
# **TABLE A12:  Gallup International (GAL, GMS)**

## **A12: Gallup International**

http://www.gallup-international.com Gallup International was founded in May 1947, is registered in Zurich, Switzerland, and has 55 members around the world governed by the same Code of Statutes to ensure technical competence and quality standards.

The Gallup International Millennium Survey polled 57,000 adults in 60 different countries of the world between August and October, 1999. The survey covered a wide range of topics of an ethical, political and religious nature, focusing specifically on issues related to democracy, the United Nations, human rights, women's rights, environment, religion, crime and basic values. This source asks several questions which also appeared in the Gallup 50th Anniversary Survey which we use for 1998.y ( ) The survey interviews citizens all around the world and helps understand the opinion of today's world population on issues like the environment, terrorism, global issues, governance and democracy. In 2004, in conjunction with Transparency International Gallup initiated the Global Barometer survey, interviewing citiznes on corruption issues.

In the table below we list the variables included in each of the governance indicators. In this paper, we use data from the 2002-2005 Voice of the People Surveys, the 2004-2005 Global Barometer Surveys, the 2000 Gallup Millenium Survey and the 1997 50th Anniversary Survey.

|**Table A12: Gallup International Citizens Surveys (69 devel**|**oped and**|**devel**|**oping**|**coun**|**tries**|**)**||
|---|---|---|---|---|---|---|---|
||2005|2004|2003|2002|2000|1998|1996|
|**Voice and Accountability**||||||||
|Trust in National Government|..|..|..|X|..|..|..|
|Trust in the Parliament|..|..|..|X|..|..|..|
|Percent who believe the country is governed by the will of the people|..|..|X|..|X|..|..|
|Percent who believe elections are free and fair|X|X|X|..|X|..|..|
|Percent who believe the government is accountable|..|..|..|..|X|..|..|
|Freedom of speech|..|..|..|..|X|..|..|
|Human Rights|..|X|..|..|..|..|..|
|Satisfaction with Democracy|X|..|..|..|..|..|..|
|**Political Stability**||||||||
|Terrorism / crime|..|X|..|..|..|..|..|
|**Government Effectiveness**||||||||
|Percent who believe the government is efficient|..|..|..|..|X|..|..|
|**Regulatory Quality**||||||||
|NA|..|..|..|..|..|..|..|
|**Rule of Law**||||||||
|Trust in the Legal System|..|..|..|X|..|..|..|
|Concern with level of crime|..|..|..|..|X|..|..|
|**Control of Corruption**||||||||
|Percent who believe the government is corrupt|..|..|..|..|X|..|..|
|Frequency of corruption|X|X|..|..|..|X|..|
|Frequency of household bribery|X|X|..|..|..|..|..|
|Extent of grand corruption|..|X|..|..|..|..|..|
|Extent of petty corruption|..|X|..|..|..|..|..|
|_Country coverage:_|_69_|_62_|49|_46_|_60_|_44_|..|

60
# **TABLE A13:  Global E-Governance (EGV)**

## **A13: Global E-Governance**

http://www.insidepolitics.org/egovt04int.pdf The Global E-Governance Index is compiled by Prof. West of Brown University's Center for Public Policy. Official websites are evaluated for the presence of various features dealing with information availability, service delivery, and public access. Features assessed included online publications, online database, audio clips, video clips, nonnative languages or foreign language translation, commercial advertising, premium fees, user payments, disability access, privacy policy, security features, presence of online services, number of different services, digital signatures, credit card payments, email address, comment form, automatic email updates, website personalization, personal digital assistant (PDA) access, and an English version of the website.

Range for the E-Government index- 0 (bad)-100 (good) based on availability of publications and databases (72 points) and number of online services (28 points).

In the table below we list the variables included in each of the governance indicators. In this paper, we use data from 2002 to 2005.

|**Table A13: Global E-Governance(192**|2005<br>**developed and deve**|2004<br>**lopin**|2003<br>**g cou**|2002<br>**ntries**|2000<br> **)**|1998|1996|
|---|---|---|---|---|---|---|---|
|**Voice and Accountability**||||||||
|NA|..|..|..|..|..|..|..|
|**Political Stability and Lack of Violence**||||||||
|NA|..|..|..|..|..|..|..|
|**Government Effectiveness**||||||||
|Global E-governance Index|X|X|X|X|..|..|..|
|**Regulatory Quality**<br>||||||||
|NA|..|..|..|..|..|..|..|
|**Rule of Law**||||||||
|NA|..|..|..|..|..|..|..|
|**Control of Corruption**||||||||
|NA|..|..|..|..|..|..|..|

61
# **TABLE A14:  Global Insight's DRI/McGraw-Hill (DRI)**

## **A14: Global Insight's Global Risk Service**

http://www.globalinsight.com DRI is an economic consulting and information company which provides data, analysis, forecasts and expert advice to strategic planners, business and financial analysts, and policy makers. It was founded in 1973 and is based in the United States.

In 1996, DRI launched the Country Risk Review (now referred to as Global Risk Service), a quarterly publication providing country risk assessments to international investors. A first draft of the risk ratings in this publication are produced by country analysts, who then submit their preliminary assessment to regional review committees charged with analyzing and challenging these assessment. The global risk service committee evaluates the reviewed assessments to ensure quality and cross-country consistency. The country analysts then produce the final country risk review.

The CRR assesses the relationship between country risk and its effects on the profitability of investments. For each country, DRI identifies a number of “potential sources of risk”, specifies measurable “risk events”, measures how probable those risk events are, and assesses the severity of impact that each outcome would have. Based on these considerations, DRI produces a risk score for each country.

The CRR identifies a total of 33 “immediate risk events” and 18 “secondary risk events” for 117 developed and developing countries. Immediate risk events are classified into policy risks (tax, and non-tax), and outcome risks (price, and non-price). Secondary risk events are classified into domestic political risks, external political risks, and economic risks. These risk events are described in below.

For each risk event, DRI produces a short run and a long run risk rating. These ratings provide subjective estimates of the likelihood that a particular risk event will occur within one and five years respectively. DRI follows a methodology to ensure that the five year forecasts are consistent with the short-term forecasts. Although these indicators nominally measure the likelihood of future changes in governance concepts, in practice the long-run ratings provide good measures of the current levels of governance.

In the table below we list the variables included in each of the governance indicators. Variable definitions consist of risk events. The actual ratings provide an estimated probability of these events happening. In this paper, we use data for the fourth quarters of 1996, 1998, 2000, and 2002-2005.

62
|**Table A14: Global Insight's Global Risk Service(117 developed and de**|2005<br>**velop**|2004 <br>**ing co**|2003 <br>**untri**|2002 <br>**es)**|2000|1998|1996|
|---|---|---|---|---|---|---|---|
|**Voice and Accountability**||||||||
|NA|..|..|..|..|..|..|..|
|**Political Stability**||||||||
|Domestic Political Risks: Military Coup Risk: A military coup d’etat (or a series of such events)<br>that reduces the GDP growth rate by 2% during any 12-month period.<br>|X|X|X|X|X|X|X|
|Domestic Political Risks: Major Insurgency/Rebellion: An increase in scope or intensity of one<br>or more insurgencies/rebellions that reduces the GDP growth rate by 3% during any 12-month<br>period.|X|X|X|X|X|X|X|
|Domestic Political Risks: Political Terrorism: An increase in scope or intensity of terrorism that<br>reduces the GDP growth rate by 1% during any 12-month period.|X|X|X|X|X|X|X|
|Domestic Political Risks: Political Assassination: A political assassination (or a series of such<br>events) that reduces the GDP growth rate by 1% during any 12-month period.|X|X|X|X|X|X|X|
|Domestic Political Risks: Civil War: An increase in scope or intensity of one or more civil wars<br>that reduces the GDP growth rate by 4% during any 12-month period.|X|X|X|X|X|X|X|
|Domestic Political Risks: Major Urban Riot: An increase in scope, intensity, or frequency of<br>rioting that reduces the GDP growth rate by 1% during any 12-month period.|X|X|X|X|X|X|X|
|**Government Effectiveness**<br>Domestic Political Risk: Government Instability: An increase in government personnel turnover<br>rate at senior levels that reduces the GDP growth rate by 2% during any 12-month period.|X|X|X|X|X|X|X|
|Domestic Political Risk: Government Ineffectiveness: A decline in government personnel<br>quality at any level that reduces the GDP growth rate by 1% during any 12-month period.<br>Domestic Political Risk: Institutional Failure: A deterioration of government capacity to cope<br>with national problems as a result of institutional rigidity or gridlock that reduces the GDP<br>growth rate by 1% during any 12-month period.|X<br>X|X<br>X|X<br>X|X<br>X|X<br>X|X<br>X|X<br>X|
|**Regulatory Quality**<br>Policies Non-Tax: Regulations -- Exports: A 2% reduction in export volume as a result of a<br>worsening in export regulations or restrictions (such as export limits) during any 12-month<br>period, with respect to the level at the time of the assessment.|X|X|X|X|X|X|X|
|Policies Non-Tax: Regulations -- Imports: A 2% reduction in import volume as a result of a<br>worsening in import regulations or restrictions (such as import quotas) during any 12-month<br>period, with respect to the level at the time of the assessment.|X|X|X|X|X|X|X|
|Policies Non-Tax: Regulations -- Other Business: An increase in other regulatory burdens, with<br>respect to the level at the time of the assessment, that reduces total aggregate investment in<br>real LCU terms by 10%|X|X|X|X|X|X|X|
|Policies Non-Tax: Ownership of Business by Non-Residents: A 1-point increase on a scale<br>from "0" to "10" in legal restrictions on ownership of business by non-residents during any 12-<br>month period.|X|X|X|X|X|X|X|
|Policies Non-Tax: Ownership of Equities by Non-Residents: A 1-point increase on a scale from<br>"0" to "10" in legal restrictions on ownership of equities by non-residents during any 12-month<br>period.|X|X|X|X|X|X|X|
|**Rule of Law**||||||||
|Outcomes Non-Price: Losses and Costs of Crime: A 1-point increase on a scale from "0" to<br>"10" in crime during any 12-month period.|X|X|X|X|X|X|X|
|Domestic Political Risk: Kidnapping of Foreigners: An increase in scope, intensity, or frequency<br>of kidnapping of foreigners that reduces the GDP growth rate by 1% during any 12-month<br>|X|X|X|X|X|X|X|
|period.||||||||
|Policies Non-Tax: Enforceability of Government Contracts: A 1 point decline on a scale from<br>"0" to "10" in the enforceability of contracts during any 12-month period.|X|X|X|X|X|X|X|
|Policies Non-Tax: Enforceability of Private Contracts: A 1-point decline on a scale from "0" to<br>"10" in the legal enforceability of contracts during any 12-month period.|X|X|X|X|X|X|X|
|**Control of Corruption**||||||||
|<br>Risk Event Outcome non-price: Losses and Costs of Corruption: A 1-point increase on a scale<br>from "0" to "10" in corruption during any 12-month period.|X|X|X|X|X|X|X|

63
**TABLE A15:  Global Insight's Business Conditions and Risk Indicators (WMO) A15: Global Insight's Business Conditions and Risk Indicators** http://www.globalinsight.com World Markets Online (WMO) is an online subscription service from the World Markets Research Center updated daily which provides analysis of the conditions and risks for businesses worldwide. Established in 1996, the World Markets Research Centre is based in London and employs over 190 permanent staff. In 2005, it was incorporated into Global Insight, which also produces DRI ratings (table A14). World Markets Online has developed a risk rating system to enable its clients to compare and contrast the investment climate in over 200 countries around the world. For WMO the principal quality their risk measures endeavor to measure is stability, which they believe businesses need most of all to be able to make secure investments and plan ahead. In addition to stability, WMO believes that businesses also need the right conditions in place; governments must ensure the right policies and safeguards to allow businesses to operate effectively. A country with a high risk rating by WMO is a country where businesses face continual threats to their operations, either from direct physical intervention, or because of the poor conditions and stability in the country concerned. The system rates the quality of conditions and level of stability encountered by investors in each country in terms of political, economic, legal, tax, operational and security environment. Drawing on a worldwide network of information gatherers and analysts, World Markets Research Centre generates a comprehensive range of in-depth country, sector and market services. The process by which the risks are assessed consists firstly of WMO analysts' own experience of the country’s conditions. Daily stories highlight countries’ changing conditions and constantly inform the risk rating levels. In addition to the in-house analysts’ own consensus, World Markets Online also draws upon the expertise and impressions of those working in the field through a wide network of stringers and informal contacts which allows them to access information only available locally as well as to case studies of individual investor's experience. Regular meetings of all the analysts across the regional desks ensure that their ratings are fully comparable globally, and that the factors used for assessment are consistent.

In the table below we list the variables included in each of the governance indicators. In this paper, we use the disaggregated components of the 2002-2005 country risk ratings, prepared for us by a panel of WMO experts.

64
|**Table A15: Global Insight's Business Conditions and Risk Indicators(202 devel**|2005<br>**oped**|2004<br>**and de**|2003<br>**velop**|2002<br>**ing c**|2000<br>199<br>**ountries)**|1996|
|---|---|---|---|---|---|---|
|**Voice and Accountabilit**|||||||
|**y**<br>_Institutional permanence_An assessment of how mature and well-established the political<br>system is. It is also an assessment of how far political opposition operates within the system<br>or attempts to undermine it from outside.<br>|X|X|X|X|..<br>..|..|
|_Representativeness_How well the population and organised interests can make their voices<br>heard in the political system. Provided representation is handled fairly and effectively, it will<br>ensure greater stability and better designed policies.|X|X|X|X|..<br>..|..|
|**Political Stability**|||||||
|_Civil unrest_How widespread political unrest is, and how great a threat it poses to investors.<br>Demonstrations in themselves may not be cause for concern, but they will cause major<br>disruption if they escalate into severe violence. At the extreme, this factor would amount to<br>civil war.|X|X|X|X|..<br>..|..|
|_Terrorism_Whether the country suffers from a sustained terrorist threat, and from how many<br>sources. The degree of localisation of the threat is assessed, and whether the active groups<br>are likely to target or affect businesses.|X|X|X|X|..<br>..|..|
|**Government Effectiveness**|||||||
|_Bureaucracy_**:**An assessment of the quality of the country’s bureaucracy. The better the<br>bureaucracy the quicker decisions are made and the more easily foreign investors can go<br>about their business.|X|X|X|X|..<br>..|..|
|_Policy consistency and forward planning_How confident businesses can be of the continuity<br>of economic policy stance - whether a change of government will entail major policy<br>disruption, and whether the current government has pursued a coherent strategy. This factor<br>also looks at the extent to which policy-making is far-sighted, or conversely aimed at short-<br>term economic advantage.|X|X|X|X|..<br>..|..|
|**Regulatory Quality**|||||||
|_Tax Effectiveness_How efficient the country’s tax collection system is. The rules may be clear<br>and transparent, but whether they are enforced consistently. This factor looks at the relative<br>effectiveness too of corporate and personal, indirect and direct taxation.|X|X|X|X|..<br>..|..|
|_Legislation_An assessment of whether the necessary business laws are in place, and<br>whether there any outstanding gaps. This includes the extent to which the country's<br>legislation is compatible with, and respected by, other countries' legal systems.|X|X|X|X|..<br>..|..|
|**Rule of Law**|||||||
|_Judicial Independence_An assessment of how far the state and other outside actors can<br>influence and distort the legal system. This will determine the level of legal impartiality<br>investors can expect.|X|X|X|X|..<br>..|..|
|_Crime_How much of a threat businesses face from crime such as kidnapping, extortion, street<br>violence, burglary and so on. These problems can cause major inconvenience for foreign<br>investors and require them to take expensive security precautions.|X|X|X|X|..<br>..|..|
|**Control of Corruption**|||||||
|_Corruption_: An assessment of the intrusiveness of the country’s bureaucracy. The amount of<br>red tape likely to countered is assessed, as is the likelihood of encountering corrupt officials<br>and other groups.|X|X|X|X|..<br>..|..|
|Country coverage|202|202|202|186|..<br>..|..|

65
# **TABLE A16:  Heritage Foundation (HER)**

## **A16: Heritage Foundation**

http://www.heritage.org The Heritage Foundation is a research and educational institute whose mission is to formulate and promote conservative public policies. The Heritage Foundation was established in 1973.

In 1995 the Heritage Foundation, in partnership with the Wall street Journal, launched its annual Index of Economic Freedom. This index covers 161 countries and measures economic freedoms and prospects for growth in the global economy. The index is designed for cross country research and is intended to assist international investors and aid donors in the allocation of their resources. This index is based on a detailed assessment of 10 different factors, including foreign investment codes, taxes, tariffs, banking regulations, monetary policy, and the black market. For some of these, assessments are mechanically based on objective data, while others are generated as subjective ratings based on a pre-specified checklist.

In the table below we list the variables included in each of the governance indicators. In this paper, we use Heritage data for 1996, 1998, 2000, and 2002-2005.

|**Table A16: Heritage Foundation: Index of Econ**|2005<br>**omic Freedom(161 developed**|2004<br>**and de**|2003<br>**velopi**|2002<br>**ng co**|2000<br>**untrie**|1998<br>**s)**|1996|
|---|---|---|---|---|---|---|---|
|**Voice and Accountability**||||||||
|NA|..|..|..|..|..|..|..|
|**Political Stability**||||||||
|NA|..|..|..|..|..|..|..|
|**Government Effectiveness**||||||||
|NA|..|..|..|..|..|..|..|
|**Regulatory Quality**||||||||
|Regulation|X|X|X|X|X|X|X|
|Government Intervention|X|X|X|X|X|X|X|
|Wage/Prices|X|X|X|X|X|X|X|
|Trade|X|X|X|X|X|X|X|
|Foreign investment|X|X|X|X|X|X|X|
|Banking|X|X|X|X|X|X|X|
|**Rule of Law**||||||||
|Black market|X|X|X|X|X|X|X|
|Property Rights|X|X|X|X|X|X|X|
|**Control of Corruption**||||||||
|NA|..|..|..|..|..|..|..|

66
# **TABLE A17:  IJET's Country Security Risk Ratings (IJT)**

## **A17: IJET's Country Security Risk Ratings**

https://worldcue.ijet.com/tic/login.jsp iJET is a privately held company founded in October 1999 and is based in Annapolis, MD. iJET monitors the world around-the-clock and alerts travelers, expatriates and decision-makers to events and situations in real-time to help them avoid or minimize risk and travel disruptions abroad. iJET's professional services offer in-depth analysis of changing risks around the world, and allows organizations to monitor, locate and communicate with traveling employees and expatriates.

In our paper, we use the iJET's security risk ratings for 167 countries worldwide in 2004 and 2005.

|**Table A17: IJET Secutiry Ratings **|2005<br> **(167 developed and develo**|2004<br>**ping c**|2003<br>**ountr**|2002<br>**ies)**|2000|1998|1996|
|---|---|---|---|---|---|---|---|
|**Voice and Accountability**||||||||
|NA|..|..|..|..|..|..|..|
|**Political Stability**||||||||
|Security Risk Rating|X|X|..|..|..|..|..|
|**Government Effectiveness**||||||||
|NA|..|..|..|..|..|..|..|
|**Regulatory Quality**||||||||
|NA|..|..|..|..|..|..|..|
|**Rule of Law**||||||||
|NA|..|..|..|..|..|..|..|
|**Control of Corruption**||||||||
|NA|..|..|..|..|..|..|..|

67
# **TABLE A18:  Institute for Management Development (WCY)**

## **A18: Institute for Management Development (WCY)**

http://www.imd.ch.

The Institute for Management Development is an research and educational organization based in Lausanne, Switzerland. It has published the World Competitiveness Yearbook since 1987. Until 1996, this was a joint effort with the World Economic Forum. The World Competitiveness Yearbook analyzes the competitive environment in 47 countries. It is based on both objective data and surveys of perceptions. The survey questions over 4,000 local and foreign enterprises operating in the countries under analysis. Mean scores on the survey questions are reported in the yearbook for all countries. In the table below we list the questions included in the governance database.

In the table below we list the variables included in each of the governance indicators. W e use data from the 1996, 1998, 2000,and 2002-2005 editions of the World Competitiveness Yearbook.

|**Table A18: Institute for Management Development(49 deve**|2005<br>**loped a**|2004<br>**nd de**|2003<br>**velop**|2002<br>**ing)**|2000|1998|1996|
|---|---|---|---|---|---|---|---|
|**Voice and Accountability**||||||||
|Transparency of Government policy|X|X|X|X|X|X|X|
|**Political Stability**||||||||
|The risk of political instability is very high|X|X|X|X|X|..|..|
|**Government Effectiveness**||||||||
|Government economic policies do not adapt quickly to changes in the economy|X|X|X|X|X|..|X|
|The public service is not independent from political interference|X|X|X|X|X|X|..|
|Government decisions are not effectively implemented|X|X|X|X|X|X|..|
|<br>Bureaucracy hinders business activity|X|X|X|X|X|X|X|
|The distribution infrastructure of goods and services is generally inefficient|X|X|X|X|X|..|X|
|Political System is not adapted to todays' economic challenges|..|..|..|..|X|..|X|
|Policy direction is not consistent|X|X|..|..|..|..|..|
|**Regulatory Quality**||||||||
|The exchange rate policy of your country hinders the competitiveness of firms|X|X|X|X|..|..|..|
|Protectionism in the country negatively affects the conduct of business|X|X|X|X|X|X|..|
|Competition legislation in your country does not prevent unfair competition|X|X|X|X|X|X|X|
|Price controls affect pricing of products in most industries|X|X|X|X|X|X|X|
|Legal regulation of financial institutions is inadequate for financial stability|..|X|X|X|X|X|X|
|Foreign financial institutions do not have access to the domestic market|..|..|X|X|..|..|X|
|Access to capital markets (foreign and domestic) is easily available|X|X|X|X|..|..|..|
|Ease of doing business is not a competitive advantage for your country|X|X|X|X|..|..|..|
|Financial institutions' transparency is not widely developed in your country|X|X|X|X|..|..|..|
|Customs' authorities do not facilitate the efficient transit of goods|X|X|X|X|X|X|..|
|The legal framework is detrimental to your country's competitiveness|X|X|X|X|X|X|..|
|Foreign investors are free to acquire control in domestic companies|X|X|X|X|X|X|..|
|Public sector contracts are sufficiently open to foreign bidders|X|X|X|X|X|X|X|
|Real personal taxes are non distortionary|X|X|X|X|X|X|X|
|Real corporate taxes are non distortionary|X|X|X|X|X|X|..|
|<br>Banking regulation does not hinder competitiveness|X|X|X|X|..|..|..|
|Political system as obstacle to development|..|..|..|..|X|X|..|
|Labor regulations hinder business activities|..|X|..|..|..|..|..|
|New Legislation restricts competitiveness|X|X|..|..|..|..|..|
|Subsidies impair economic development|X|X|..|..|..|..|..|
|Ease to start a business|X|X|..|..|..|..|..|
|**Rule of Law**||||||||
|Tax evasion is a common practice in your country|X|X|X|X|X|X|..|
|Justice is not fairly administered in society|X|X|X|X|X|X|X|
|<br>Personal security and private property are not adequately protected|X|X|X|X|X|X|X|
|<br>Parallel economy impairs economic development in your country|X|X|X|X|X|X|X|
|<br>Insider trading is common in the stock market|..|X|X|X|..|..|X|
|<br>Patent and copyright protection is not adequately enforced in your country|X|X|X|X|..|X|X|
|**Control of Corruption**||||||||
|Bribing and corruption exist in the economy|X|X|X|X|X|X|X|

68
# **TABLE A19:  International Research & Exchanges Board (MSI)**

## **A19: Media Sustainability Index (MSI)**

http://www.irex.org The International Research & Exchanges Board (IREX) is an international nonprofit organization specializing in education, independent media, Internet development, and civil society programs. Through training, partnerships, education, research, and grant programs, IREX develops the capacity of individuals and institutions to contribute to their societies.

Through the financial assistance of USAID, IREX introduced in 2002 the Media Sustainability Index, a tool designed to inform media development practitioners, public officials, scholars and others concerned about the region’s media. The MSI analyzes issues such as freedom of speech, plurality of media available to citizens, professional journalism standards, business sustainability of media, and the efficacy of institutions that support independent media.

In the table below we list the variables included in each of the governance indicators. We use data from the 2002-2005 Reports

|**Table A19: Media Sustainability I**|2<br>**ndex(19 developing**|24<br>**cou**|2<br>**ntries**|22<br>**)**|2|1|1|
|---|---|---|---|---|---|---|---|
||005|00|003|00|000|998|996|
|**Voice and Accountability**||||||||
|Media Sustainability Index|X|X|X|X|..|..|..|
|**Political Stability and Lack of Violence**||||||||
|NA|..|..|..|..|..|..|..|
|**Government Effectiveness**||||||||
|NA|..|..|..|..|..|..|..|
|**Regulatory Quality**||||||||
|NA|..|..|..|..|..|..|..|
|**Rule of Law**||||||||
|NA|..|..|..|..|..|..|..|
|**Control of Corruption**||||||||
|NA|..|..|..|..|..|..|..|

69
# **TABLE A20:  Latinobarometro (LBO)**

## **A20: Latinobarometro**

http://www.latinobarometro.org Latinobarometro is a public opinion survey representing the opinions, attitudes, behaviour and values of citizens of the countries in which it is conducted. The survey began being applied regularly in 8 countries of the region in 1995, and in 17 countries beginning in 1996. Latinobarometro conducts an annual survey, using representative samples and an identical questionnaire in each country. It asks questions in in the following areas: Economy and International Trade, Integration and Regional Trading Blocks, Democracy, Politics and Institutions, Social Policies, Civic Culture, Social Capital and Social Fraud, the Environment, and Current Issues.

In the table below we list the variables included in each of the governance indicators. We use data from the 1996, 1998, 2000, and 2002-2005 surveys.

|**Table A20: Latinobaromet**|**ro(18 Latin American**|**coun**|**tries)**|||||
|---|---|---|---|---|---|---|---|
||2005|2004|2003|2002|2000|1998|1996|
|**Voice and Accountability**||||||||
|Satisfaction with democracy|X|X|X|X|..|X|X|
|Trust in Parliament|X|X|X|..|..|X|..|
|**Political Stability**||||||||
|Country terrorist threat|..|..|..|X|..|..|..|
|**Government Effectiveness**||||||||
|Trust in Government|X|X|..|X|..|..|..|
|**Regulatory Quality**||||||||
|NA|..|..|..|..|..|..|..|
|**Rule of Law**||||||||
|Trust in Judiciary|X|X|X|X|X|X|X|
|Trust in Police|X|X|..|..|X|X|X|
|Have you been a victim of crime?|X|X|X|X|..|..|..|
|**Control of Corruption**||||||||
|Frequency of corruption|X|X|X|X|X|X|..|

70
# **TABLE A21:  Merchant International Group (MIG)**

## **A21: Merchant International Group (MIG)**

http://www.merchantinternational.com Established in 1982, the Merchant International Group Limited (“MIG”) is a strategic research and corporate intelligence company headquartered in London, which provides a range of support services (from identification to evaluation of all manner of risks, weaknesses and threats) to corporates in non-domestic markets.

MIG developed a framework that identifies ten distinctive categories of Grey Area DynamicsTM. Each refers to a range of events, activities and trends that impact upon business. Their impact is of varying severity and may be positive or negative, though typically, Grey Area DynamicsTM take the form of obstacles to progress in nondomestic markets.

In the table below we list the variables included in each of the governance indicators. We use data from 2002 to 2005.

|**Table A21: Grey Area Dynamics(155 d**|**eveloped and devel**|**oping**|**coun**|**tries**|**)**|||
|---|---|---|---|---|---|---|---|
||2005|2004|2003|2002|2000|1998|1996|
|**Voice and Accountability**||||||||
|NA|..|..|..|..|..|..|..|
|**Political Stability and Lack of Violence**||||||||
|Extremism|X|X|X|X|..|..|..|
|**Government Effectiveness**||||||||
|Bureaucracy|X|X|X|X|..|..|..|
|**Regulatory Quality**||||||||
|Unfair Trade|X|X|X|X|..|..|..|
|Unfair Competition|X|X|X|X|..|..|..|
|**Rule of Law**||||||||
|Legal Safeguards|X|X|X|X|..|..|..|
|Organized Crime|X|X|X|X|..|..|..|
|**Control of Corruption**||||||||
|Corruption|X|X|X|X|..|..|..|
|_Country coverage_|155|155|155|118|..|..|..|

71
# **TABLE A22:  Political Economic Risk Consultancy (PRC)**

## **A22. Political Economic Risk Consultancy (PRC)**

http://www.asiarisk.com/ Founded in 1976 and headquartered in Hong Kong, the Political and Economic Risk Consultancy specializes in strategic information and analysis for companies doing business in the countries in East and Southeast Asia.

PERC has conducted various surveys of expatriate business managers in the East Asia region. The original results of these surveys were published under the titles “Corruption in Asia in 1999” . Based on the average responses in these surveys, PERC has produced country ratings. In this paper, we use data from the 1998, 2000, 2002-2005 surveys.

## **Corruption in Asia**

In this survey, foreign managers working within the East Asia region were questioned about their perception of corruption, the quality of the legal system, and the professionalism and reliability of the police and judiciary. We have obtained their data on corruption for 12 countries, based on a total of 427 responses. With respect to corruption, respondents were asked “To what extent does corruption exist in a way that detracts from the business environment for foreign companies?”

|**Table A22: Political Economic Risk Consultanc**|2005<br>**y (10 As**|2004<br>**ian c**|2003<br>**ountr**|2002<br>**ies)**|2000|1998|1996|
|---|---|---|---|---|---|---|---|
|**Voice and Accountability**||||||||
|NA|..|..|..|..|..|..|..|
|**Political Stability**||||||||
|NA|..|..|..|..|..|..|..|
|**Government Effectiveness**||||||||
|NA|..|..|..|..|..|..|..|
|**Regulatory Quality**||||||||
|NA|..|..|..|..|..|..|..|
|**Rule of Law**||||||||
|NA|..|..|..|..|..|..|..|
|**Control of Corruption**||||||||
|To what extent does corruption exist in a way that detracts from the<br>business environment for foreign companies?|X|X|X|X|X|X|..|

72
# **TABLE A23:  Political Risk Services (PRS)**

## **A23: Political Risk Services (PRS)**

http://www.prsgroup.com The PRS group is an affiliate of Investment Business with Knowledge (IBK), a United States-based corporation providing up-to-date country information for international business. PRS was founded in 1980 and is headquartered in Syracuse, New York. Since 1982, PRS has produced the International Country Risk Guide (ICRG) which provides assessments of a political, economic and financial risks in a large number of developed and developing countries. These assessments are based on the analysis of a worldwide network of experts, and is subject to a peer review process at subject and regional levels to ensure the coherence and comparability across countries. The ICRG assesses three major categories of risk: political (with 12 components), financial (5 components) and economic (6 components). We use components of the Political Risk Index, which report subjective assessments of the factors influencing the business environment in a particular country.

In the table below we list the variables included in each of the governance indicators. In this paper we use data from December 1996, 1998, 2000, and 2002-2005.

73
|**Table A23: Political Risk Services(140 developed and d**|**evelop**|**ing c**|**ountri**|**es)**||||
|---|---|---|---|---|---|---|---|
|**Voice and Accountability**<br>_Military in Politics_The military are not elected by anyone, so their participation in<br>government, either direct or indirect, reduces accountability and therefore represents a<br>risk. The threat of military intervention might lead as well to an anticipated potentially<br>inefficient change in policy or even in government. It also works as an indication that<br>the government is unable to function effectively and that the country has an uneasy<br>environment for foreign business.|2005<br>X|2004<br>X|2003<br>X|2002<br>X|2000<br>X|1998<br>X|1996<br>X|
|_Democratic Accountability._Quantifies how responsive government is to its people, on<br>the basis that the less response there is the more likely is that the government will fall,<br>peacefully or violently. It includes not only if free and fair elections are in place, but<br>also how likely is the government to remain in power or remain popular.|X|X|X|X|X|X|X|
|**Political Stability**||||||||
|_Government Stability._Measures the government’s ability to carry out its declared<br>programs, and its ability to stay in office. This will depend on issues as: the type of<br>governance, the cohesion of the government and governing party or parties, the<br>closeness of the next election, the government command of the legislature, and<br>approval of government policies.|X|X|X|X|X|X|X|
|_Internal Conflict._Assess political violence and its influence on governance. Highest<br>scores go to countries with no armed opposition, and where the government does not<br>indulge in arbitrary violence, direct or indirect. Lowest ratings go to civil war torn<br>countries. Intermediate ratings are awarded on the basis of the threats to the<br>government and busines.|X|X|X|X|X|X|X|
|_External conflict:_The external conflict measure is an assessment both of the risk to the<br>incumbent government and to inward investment. It ranges from trade restrictions and<br>embargoes, whether imposed by a single country, a group of countries, or the<br>international community as a whole, through geopolitical disputes, armed threats,<br>exchanges of fire on borders, border incursions, foreign-supported insurgency, and full-<br>scale warfare.|X|X|X|X|X|X|X|
|_Ethnic tensions_: This component measures the degree of tension within a country<br>attributable to racial, nationality, or language divisions. Lower ratings are given to<br>countries where racial and nationality tensions are high because opposing groups are<br>intolerant and unwilling to compromise. Higher ratings are given to countries where<br>tensions are minimal, even though such differences may still exist.|X|X|X|X|X|X|X|
|**Government Effectiveness**||||||||
|_Bureaucratic Quality._Measures institutional strength and quality of the civil service,<br>assess how much strength and expertise bureaucrats have and how able they are to<br>manage political alternations without drastic interruptions in government services, or<br>policy changes. Good performers have somewhat autonomous bureaucracies, free<br>from political pressures, and an established mechanism for recruitment and training.|X|X|X|X|X|X|X|
|**Regulatory Quality**||||||||
|_Investment Profile._Includes the risk to operations (scored from 0 to 4, increasing in<br>risk); taxation (scored from 0 to 3), repatriation (scored from 0 to 3); repatriation (scored<br>from 0 to 3) and labor costs (scored from 0 to 2). They all look at the government’s<br>attitude towards investment.|X|X|X|X|X|X|X|
|**Rule of Law**||||||||
|_Law and Order._The Law sub-component is an assessment of the strength and<br>impartiality of the legal system, while the Order sub-component is an assessment of<br>popular observance of the law.|X|X|X|X|X|X|X|
|**Control of Corruption**||||||||
|_Corruption._Measures corruption within the political system, which distorts the<br>economic and financial environment, reduces the efficiency of government and<br>business by enabling people to assume positions of power through patronage rather<br>than ability, and introduces an inherently instability in the political system.|X|X|X|X|X|X|X|

74
# **TABLE A24:  Reporters Without Borders (RSF)**

## **A24: Reporters Without Borders**

http://www.rsf.org Reporters Without Borders - headquartered in Paris - is an international organization dedicated to the protection of reporters and respect of press freedom in the world. In 2002, International Reporters Without Borders published its first worldwide press freedom index, compiled for 139 countries. The organisation's initiatives are being carried out on five continents through its national branches and its offices in Abidjan, Bangkok, Buenos Aires, Istanbul, Montreal, Nairobi, New York, Tokyo and Washington. It also works in close co-operation with local and regional press freedom organisations and with members of the "Reporters without Borders' Network." The index was drawn up by asking journalists, researchers and legal experts worldwide to answer 50 questions about the whole range of press freedom violations (such as murders or arrests of journalists, censorship, pressure, state monopolies in various fields, punishment of press law offences and regulation of the media). In the table below we list the variables included in each of the governance indicators. We use data from 2002 to 2005.

|**Table A24: Reporters Without Borders(16**|**5 developed and d**|**evelo**|**ping c**|**ountr**|**ies)**|||
|---|---|---|---|---|---|---|---|
||2005|2004|2003|2002|2000|1998|1996|
|**Voice and Accountability**||||||||
|Press Freedom Index|X|X|X|X|..|..|..|
|**Political Stability and Lack of Violence**||||||||
|NA|..|..|..|..|..|..|..|
|**Government Effectiveness**||||||||
|NA|..|..|..|..|..|..|..|
|**Regulatory Quality**||||||||
|NA|..|..|..|..|..|..|..|
|**Rule of Law**||||||||
|NA|..|..|..|..|..|..|..|
|**Control of Corruption**||||||||
|NA|..|..|..|..|..|..|..|
|Country Coverage|165|165|164|138|..|..|..|

75
# **TABLE A25:  State Department’s Trafficking in people Report (TPR)**

## **A25: State Department's Trafficking in People Report**

http://www.state.gov/g/tip/rls/tiprpt/ Initiated in 2001, the Trafficking in People Reports cover "severe forms of trafficking in persons" defined as: (a) sex trafficking in which a commercial sex act is induced by force, fraud, or coercion, or in which the person induced to perform such act has not attained 18 years of age; or (b) the recruitment, harboring, transportation, provision, or obtaining of a person for labor or services, through the use of force, fraud or coercion for the purpose of subjection to involuntary servitude, peonage, debt bondage, or slavery.

In preparing the reports, the Department of State in Washington asked for information from US embassies and consulates around the world. The embassy reports reflect discussions with host governments, local nongovernmental organizations, immigration officials, police, journalists, and victims, in addition to reviews of government, press, and NGO reports. The State Department's Bureau for International Narcotics and Law Enforcement Affairs; the Bureau of Democracy, Human Rights, and Labor; the regional bureaus; and the Office of the Legal Adviser, with assistance from the intelligence community, reviewed reporting from U.S. embassies and consulates overseas. The Department also reviewed information from other sources including, but not limited to, UNICEF, UNHCR, the International Organization for Migration, Human Rights Watch, Amnesty International, the Protection Project, media reports and other U.S. Government agencies.

In the table below we list the variables included in each of the governance indicators. We use data from 2001 to 2006 Reports (which refer to years 2000-2005).

|**Table A25: State Department(14**|**9 developed and developing count**|**ries)**||||||
|---|---|---|---|---|---|---|---|
||2005|2004|2003|2002|2000|1998|1996|
|**Voice and Accountability**<br>NA|..|..|..|..|..|..|..|
|**Political Stability**||||||||
|NA|..|..|..|..|..|..|..|
|**Government Effectiveness**||||||||
|NA|..|..|..|..|..|..|..|
|**Regulatory Quality**<br>NA|..|..|..|..|..|..|..|
|**Rule of Law**||||||||
|Trafficking in People|X|X|X|X|X|..|..|
|**Control of Corruption**<br>NA|..|..|..|..|..|..|..|
|_Country coverage_|149|142|131|116|82|..|..|

76
# **TABLE A26:  State Department / Amnesty International (HUM / PTS)**

## **A26: State Department / Amnesty International - Human Rights Database**

http://www.humanrightsdata.com http://www.unca.edu/politicalscience/images/Colloquium/faculty-staff/Gibney Doc/Political Terror Scale 1980-2004.xls We gather data from two different studies that have compiled a set of human rights indicators, drawing from the State Department's and Amnesty International's Human Rights Reports The State Department’s Country Reports on Human Rights Practices cover global human rights practices in the previous calendar years. Reports are generated through data gathered by the State Department from all of its embassies and representations throughout the world.

The Amnesty International’s Annual Reports cover global human rights conditions for the previous calendar years. Reports are based on information collected through Amnesty activists as well as from other sources such as media reports

**The Cingranelli-Richards (CIRI) Human Rights Dataset** contains standards-based quantitative information on government respect for 13 internationally recognized human rights for 192 countries. It is designed for use by scholars and students who seek to test theories about the causes and consequences of human rights violations, as well as policy makers and analysts who seek to estimate the human rights effects of a wide variety of institutional changes and public policies including democratization, economic aid, military aid, structural adjustment, and humanitarian intervention.

The **Political Terror Scale** (PTS) was originally codified by Prof. Marc Gibney of the University of North Carolina. The Index captures the reality of domestic political terror, capturing issues such as: imprisonments, tortures, rule of law, security, disappearances and executions.

In the table below we list the variables included in each of the governance indicators. We use data from the 1996, 1998, 2000, and 2002-2005 reports.

|**Table A26: State Department / Amnesty International(192 develope**|2005 <br>**d and devel**|2004 <br>**opin**|2003 <br>**g cou**|2002 <br>**ntrie**|2000 <br>**s)**|1998|1996|
|---|---|---|---|---|---|---|---|
|**Voice and Accountability**||||||||
|Restrictions on domestic and foreign travel (CIRI)|X|X|X|X|X|X|X|
|Freedom of political participation (CIRI)|X|X|X|X|X|X|X|
|Imprisonments because of ethnicity, race, or political, religious beliefs? (CIRI)|X|X|X|X|X|X|X|
|Government censorship (CIRI)|X|X|X|X|X|X|X|
|**Political Stability**||||||||
|Frequency of political killings (CIRI)|X|X|X|X|X|X|X|
|Frequency of disappearances (CIRI)|X|X|X|X|X|X|X|
|Frequency of tortures (CIRI)|X|X|X|X|X|X|X|
|Political terror scale (PTS)|X|X|X|X|X|X|X|
|**Government Effectiveness**||||||||
|NA|..|..|..|..|..|..|..|
|**Regulatory Quality**<br>||||||||
|NA|..|..|..|..|..|..|..|
|**Rule of Law**||||||||
|Independence of judiciary (CIRI)|X|X|X|X|X|X|X|
|**Control of Corruption**||||||||
|NA|..|..|..|..|..|..|..|
|_Country coverage_|192|192|159|159|159|159|159|

77
# **TABLE A27:  The World Business Environment Survey (WBS, WDR)**

## **A27. The World Business Environment Survey (WBS)**

http://www.ifc.org/ifcext/economics.nsf/Content/IC-WBESConditions The World Business Environment Survey (WBS) is a survey conducted by the World Bank in collaboration with several other institutions. It is designed to provide information on the business environment facing private enterprises. It was conducted during 1999 and 2000 in 81 countries. The respondents were managers of firms in at least 100 firms per country. This survey asks several questions similar to those in the 1997 World Development Report survey that we use in constructing the 1998 version of the indicators. We therefore treat the WBS as the continuation of this source.

The component of the WBS covering transition economies is referred to as the Business Environment and Enterprise Performance Survey (BPS), described in Table A2. The questionnaire for this region contains more detailed questions about corruption issues, including questions on "state capture" referring to the manipulation of the institutions of the state for private gain on a grand scale. In addition, new rounds of BPS were conducted in 2002 and 2005. For these reasons, we treat the BPS as a separate source.

In the table below we list the variables included in each of the governance indicators. We use data from the WBES survey in 2000 and the WDR Survey in 1998.

78
|**Table A27: World Business Enterprise Survey (80 developed an**|2005<br>2004<br>**d developing**|2003<br>**coun**|2002<br>**tries)**|2000|1998|1996|
|---|---|---|---|---|---|---|
|**Voice and Accountability**|||||||
|<br>Business have voice to express|..<br>..|..|..|X|X|..|
|Business are informed|..<br>..|..|..|X|X|..|
|**Political Stability**|||||||
|Political instability|..<br>..|..|..|X|..|..|
|Likelihood of uncostitutional|..<br>..|..|..|..|X|..|
|Threat of terrorism|..<br>..|..|..|..|X|..|
|**Government Effectiveness**<br>|||||||
|Quality of customs<br>|..<br>..|..|..|X|X|..|
|Quality of public works (roads,...)|..<br>..|..|..|X|X|..|
|Quality of power company|..<br>..|..|..|X|..|..|
|Quality of Water|..<br>..|..|..|X|..|..|
|Quality of public health|..<br>..|..|..|X|X|..|
|Quality of public education|..<br>..|..|..|X|..|..|
|Quality of central government|..<br>..|..|..|X|..|..|
|Quality of central bank|..<br>..|..|..|X|..|..|
|<br>Efficiency of government in delivering services|..<br>..|..|..|X|X|..|
|Likelihood that when a government official acts against the rules, one can go|||||X||
|to another official or a superior and get correct treatment|..<br>..|..|..|..||..|
|Management time spent with bureaucrats|..<br>..|..|..|..|X|..|
|The efficiency of mail delivery|..<br>..|..|..|..|X|..|
|Predictability of changes in rules and laws|..<br>..|..|..|..|X|..|
|Credibility of government's commitment to policies|..<br>..|..|..|..|X|..|
|**Regulatory Quality**|||||||
|<br>Regulations on starting new businesses|..<br>..|..|..|X|X|..|
|Price controls|..<br>..|..|..|X|X|..|
|Regulations on foreign trade|..<br>..|..|..|X|X|..|
|Foreign currency regulations|..<br>..|..|..|X|X|..|
|General uncertainty about regulations|..<br>..|..|..|X|X|..|
|**Rule of Law**|||||||
|Corruption of bankers|..<br>..|..|..|X|..|..|
|Quality of the Police|..<br>..|..|..|X|..|..|
|Organized crime<br>|..<br>..|..|..|X|..|..|
|Street crime|..<br>..|..|..|X|X|..|
|Courts-- fair & impartial|..<br>..|..|..|X|..|..|
|Courts-affordable|..<br>..|..|..|X|..|..|
|Courts-consistent/predictable|..<br>..|..|..|X|X|..|
|Court's enforceability|..<br>..|..|..|X|..|..|
|Confidence in judicial system today in insuring property rights|..<br>..|..|..|X|X|..|
|General constraint—functioning of the judiciary|..<br>..|..|..|X|..|..|
|Obstacles to competition-violation of patents|..<br>..|..|..|X|..|..|
|<br>Quality of courts|..<br>..|..|..|X|..|..|
|**Control of Corruption**|||||||
|Frequency of additional payments|..<br>..|..|..|X|X|..|
|Dishonest courts|..<br>..|..|..|X|..|..|
|Corruption as obstacle to business|..<br>..|..|..|X|X|..|
|Bribery (% of Gross revenues)|..<br>..|..|..|X|..|..|
|_Country coverage_|..<br>..|..|..|_80_|_74_|..|

79
# **TABLE A28:  World Economic Forum (GCS, GCSA)**

## **A28. World Economic Forum (GCS)**

http://www.weforum.org The World Economic Forum (WEF) is an independent, not-for-profit organization bringing together top leaders from business, government, academia and the media to address key economic, social and political issues in partnership. The WEF was founded in 1971 and is headquartered in Geneva, Switzerland.

Since 1996, the WEF has sponsored the Global Competitiveness Report, an annual publication produced in collaboration with the Harvard Institute for International Development (HIID). As background for this report, the WEF conducts the Global Competitiveness Survey, which measures the perceptions of business executives about the country in which they operate. The survey asks top managers to rank on a 1 to 7 scale their opinion on issues in eight broad areas: 1) Openness, 2) Government, 3) Finance, 4) Infrastructure, 5) Technology, 6) Management, 7) Labor, and 8) Institutions.

In 1998 and 2002 the WEF sponsored separate surveys of countries in Africa and Middle East, respectively. We incorporated them in the Global Surveys, resulting in an increase of country coverage in 1998 and 2002 of 20 and 8 countries, respectively.

In the table below we list the variables included in each of the governance indicators. In this paper, we use data from the 1996, 1998, 2000, and 2002-2005 Surveys Additional questions from the 1998 African Competitiveness Report (covering 23 African countries overall) have also been listed (GCSA).

|**Table A28: World Economic Forum(104 developed and developi**|**ng cou**|**ntries**|**)**|||||
|---|---|---|---|---|---|---|---|
||2005|2004|2003|2002|2000|1998|1996|
|**Voice and Accountability**||||||||
|Firms are usually informed clearly and transparently by the Government on changes in policies<br>affecting their industry|..|X|X|X|..|..|..|
|Newspapers can publish stories of their choosing without fear of censorship or retaliation|X|X|X|X|..|..|..|
|When deciding upon policies and contracts, Government officials favor well-connected firms|X|X|X|X|..|..|..|
|Extent of direct influence of legal contributions to political parties on specific public policy<br>outcomes|..|X|X|X|..|..|..|
|Effectiveness of national Parliament/Congress as a law making and oversight institution|X|X|X|X|..|..|..|
|**Political Stability**||||||||
|The threat of terrorism in the country imposes significant costs on business|X|X|X|X|..|..|..|
|New Governments honor commitments of previous Governments|..|..|..|..|X|X|X|
|Likelihood of dramatic changes in institutions|..|..|..|..|X|X|X|
|The highest power is always peacefully transferred|..|..|..|..|..|X|..|
|Government coups or political instability as an obstacle to development (GCSA)|..|..|..|..|..|X|..|
|Tribal conflict as an obstacle for business development (GCSA)|..|..|..|..|..|X|..|
|**Government Effectiveness**||||||||
|Competence of public sector personnel|X|X|X|X|X|X|X|
|Quality of general infrastructure|X|X|X|X|..|..|X|
|Quality of public schools|X|X|X|X|..|..|X|
|Time spent by senior management dealing with government officials|X|X|X|X|X|X|X|
|Public Service vulnerability to political pressure|..|..|..|..|X|X|X|
|Wasteful government expenditure|X|X|..|..|X|X|..|
|Strength and expertise of the civil service to avoid drastic interruptions in government services in<br>times of political instability (GCSA)|..|..|..|..|..|X|..|
|Government economic policies are independent of pressure from special interest groups.|..|..|..|..|X|..|..|

80
|**Table A28: World Economic Forum(cont.)**||||||||
|---|---|---|---|---|---|---|---|
||2005|2004|2003|2002|2000|1998|1996|
|**Regulatory Quality**||||||||
|<br>Administrative regulations are burdensome|X|X|X|X|X|X|X|
|Tax system is distortionary<br>|X<br>|X<br>|X<br>|X<br>|X|X<br>|X<br>|
|Import barriers as obstacle to growth<br>|X<br>|X<br>|X<br>|X<br>|..|X<br>|X|
|Competition in local market is limited|X|X|X|X|..|X|..|
|It is easy to start company<br>|..<br>|X<br>|X<br>|X<br>|..|X<br>|..<br>|
|Anti monopoly policy is lax and ineffective|X|X|X|X|..|X|X|
|Environmental regulations hurt competitiveness<br>|X|X|X|X|..|..|..|
|Cost of tariffs imposed on business|..|X|X|X|..|X|X|
|<br>Government subsidies keep uncompetitive industries alive artificially|..|..|X|X|..|..|X|
|Complexity of Tax System<br>|X|X|..|..|..|..<br>|..|
|Domestic banks are protected from foreign competition|..|..|..|..|..|X|..|
|Barriers to entry in banking sector are very high|..|..|..|..|..|X|..|
|Interest rates are heavily regulated<br>|..|..|..|..|..|X<br>|..|
|Private sector participation in infrastructure projects is not permitted|..|..|..|..|..|X|..|
|Costs of uncertain rules, laws, or government policies (GCSA)<br>|..|..|..|..|..|X<br>|..|
|Tranfer costs associated with exporting capital as an obstacle to business (GCSA)|..|..|..|..|..|X|..|
|<br>General uncertainty on costs of regulations as an obstacle to business (GCSA)<br>Openness of public sector contracts to foreign investors (GCSA)<br>|..<br>..|..<br>..|..<br>..|..<br>..|..<br>..|X<br>X<br>|..<br>..|
|Policies for dividend remittances as obstacles to development (GCSA)|..|..|..|..|..|X|..|
|Dominance of state owned or state controlled enterpriese (GCSA)<br>|..|..|..|..|..|X<br>|..|
|State interference in private business (GCSA)|..|..|..|..|..|X|..|
|<br>Regulatory discretionality (GCSA)|..|..|..|..|..|X|..|
|Price controls as an obstacle to business develpoment (GCSA)||||||X||
|<br>|..|..|..|..|..||..|
|Regulations on foreign trade as an obstacle to business develpoment (GCSA)|..|..|..|..|..|X|..|
|Foreign currency regulations as an obstacle to business develpoment (GCSA)|..|..|..|..|..|X|..|
|**Rule of Law**||||||||
|Common crime imposes costs on business<br>|X<br>|X<br>|X<br>|X<br>|..<br>|..<br>|..<br>|
|Organized crime imposes costs on business|X|X|X|X|X|X|X|
|Money laundering through banks is pervasive<br>|X|X<br>|X<br>|X<br>|..|..|..|
|Money laundering through non-banks is pervasive|..|X|X|X|..|..|..|
|<br>Quality of Police|X|X|X|X|X|X|X|
|Insider trading is pervasive<br>|..|X|X|X|..|..|X|
|The judiciary is independent from political influences of government, citizens, or firms|X|X|X|X|X|X|..|
|Legal framework to challenge the legality of government actions is inefficient|X|X|X|X|X|X|X|
|Intellectual Property protection is weak|X|X|X|X|..|X|X|
|<br>Protection of financial assets is weak|X|X|X|X|X|..|..|
|Illegal donation to parties are frequent<br>|..|X|X|X|..|..|..|
|Private businesses are morel likely to settle disputes outside courts.|..|..|..|..|X|..|..|
|<br>Compliance with court rulings and /or arbitration awards (GCSA)|..|..|..|..|..|X|..|
|Legal system effectiveness at enforcing commercial contracts (GCSA)<br>|..|..|..|..|..|X|..|
|Citizens’ willingness to accept legal means to adjudicate disputes rather than depending||||||||
|on physical force or illegal means (GCSA)|..|..|..|..|..|X|..|
|Percentage of firms which are unofficial or unregistered / Tax evasion|X|X|X|X|X|X|X|
|**Control of Corruption**||||||||
|<br>Public trust in financial honesty of politicians|X|X|X|X|..|..|..|
|Extent to which legal contributions to political parties are misused by politicians<br>Diversion of public funds due to corruption is common|..<br>X|X<br>X|X<br>X|X<br>X|..<br>..|..<br>..|..<br>..|
|<br>Frequency of bribery in the economy|X|X|X|X|..|X|..|
|Frequentforfirmstomakeextrapaymentsconnectedto:publicutilitiestaxpayments||||||||
|, ,<br>loan applications, awarding of public contracts, influencing laws, policies regulations,<br>decrees, getting favourable judicial decisions|X|X|X|X|X|X|X|
|Extent to which firms' illegal payments to influence government policies impose costs on||||||||
|<br>other firms|X|X|X|X|..|..|..|
|Extent to which influence of powerful firms with political ties impose costs on other firms||||||||
||X|X|X|X|..|..|..|
|_Country Coverage:_|_117_|_104_|_101_|_88_|_80_|_74_|_58_|

81
<!-- Start of picture text --> Appendix B: Components of Aggregate Governance Indicators, 2005<br> Table B1: Voice and Accountability<br>Code Table Concept Measured<br>Representative Sources<br>EIU A9 Orderly transfers<br>Vested interests<br>Accountability of Public Officials<br>Human Rights<br>Freedom of association<br>FRH A11 Civil liberties : Freedom of speech, of assembly and demonstration, of religion, equal opportunity, of excessive governmental<br>intervention<br>Political Rights : free and fair elections, representative legislative, free vote, political parties, no dominant group, respect for<br>minorities<br>Freedom of the Press<br>GCS A28 Newspapers can publish stories of their choosing without fear of censorship or retaliation<br>When deciding upon policies and contracts, Government officials favor well-connected firms<br>Effectiveness of national Parliament/Congress as a law making and oversight institution<br>HUM A26 Travel: domestic and foreign travel restrictions<br>Freedom of political participation<br>Imprisonments: Are there any imprisoned people because of their ethnicity, race, or their political, religious beliefs?<br>Government censorship<br>PRS A23 Military in Politics The military are not elected by anyone, so their participation in government, either direct or indirect,<br>reduces accountability and therefore represents a risk. The threat of military intervention might lead as well to an anticipated<br>potentially inefficient change in policy or even in government.<br>Democratic Accountability. Quantifies how responsive government is to its people, on the basis that the less response there<br>is the more likely is that the government will fall, peacefully or violently. It includes not only if free and fair elections are in<br>place, but also how likely is the government to remain in power.<br>RSF A24 Press Freedom Index<br>WMO A15 Institutional permanence: An assessment of how mature and well-established the political system is.<br>Representativeness :How well the population and organized interests can make their voices heard in the political system<br>Non-representative Sources<br>AFR A2 Elections are free and fair<br>BTI A4 Stateness<br>Political Participation<br>Institutional Stability<br>Political and Social Integration<br>CCR A11 Civil Liberties<br>Accountability and public voice<br>FHT A11 Political Process: Deals with elections, referenda, party configuration, conditions for political competition, and popular<br>participation in elections.<br>Civil Society : Highlights the degree to which volunteerism, trade unionism, and professional associations exist, and whether<br>civic organizations are influential<br>Independent Media: Press freedom, public access to a variety of information sources, and the independence of those<br>sources from undue government or other influences.<br>GAL A12 Fairness of elections<br>Satisfaction with democracy<br>LOB A20 Satisfaction with democracy<br>Trust in Parliament<br>MSI A19 Media Sustainability Index<br>WCY A18 Transparency of Government policy<br><!-- End of picture text --> 82
# **Table B2:  Political Stability**

<!-- Start of picture text --> Code Table Concept Measured<br>Representative Sources<br>DRI A14 Military Coup Risk : A military coup d’etat (or a series of such events) that reduces the GDP growth rate by 2% during any<br>12-month period.<br>Major Insurgency/Rebellion : An increase in scope or intensity of one or more insurgencies/rebellions that reduces the<br>GDP growth rate by 3% during any 12-month period.<br>Political Terrorism: An increase in scope or intensity of terrorism that reduces the GDP growth rate by 1% during any 12-<br>month period.<br>Political Assassination : A political assassination (or a series of such events) that reduces the GDP growth rate by 1%<br>during any 12-month period.<br>Civil War : An increase in scope or intensity of one or more civil wars that reduces the GDP growth rate by 4% during any<br>12-month period.<br>Major Urban Riot: An increase in scope, intensity, or frequency of rioting that reduces the GDP growth rate by 1% during<br>any 12-month period.<br>EIU A9 Armed conflict<br>Violent demonstrations<br>Social Unrest<br>International tensions<br>GCS A28 Country terrorist threat : Does the threat of terrorism in the country impose significant costs on firms?<br>HUM A26 Frequency of political killings<br>Frequency of disappearances<br>Frequency of torture<br>IJT A17 Security Risk Rating<br>MIG A21 Extremism. The term “extremism” covers the threat posed by any individuals or organisations who hold a narrow set of<br>fanatical beliefs. Extremists are likely to believe that any and all means are justified to eradicate the target of hostility, and<br>are not afraid to destroy themselves in the process. This ideological aspect of extremism makes it highly unpredictable,<br>and its close association with violence makes it highly dangerous. The extent to which extremism should be judged a<br>threat to a particular business in a particular market can be assessed along the following lines: integration issues; religious<br>tensions; pressure groups; terrorist activity; xenophobia.<br>PRS A23 Internal Conflict : Assesses political violence and its influence on governance.<br>External conflict: The external conflict measure is an assessment both of the risk to the incumbent government and to<br>inward investment.<br>Government Stability. Measures the government’s ability to carry out its declared programs, and its ability to stay in office.<br>Ethnic tensions : This component measures the degree of tension within a country attributable to racial, nationality, or<br>language divisions.<br>PTS A26 Political Terror Scale<br>WMO A15 Civil unrest How widespread political unrest is, and how great a threat it poses to investors. Demonstrations in themselves<br>may not be cause for concern, but they will cause major disruption if they escalate into severe violence. At the extreme,<br>this factor would amount to civil war.<br>Terrorism Whether the country suffers from a sustained terrorist threat, and from how many sources. The degree of<br>localization of the threat is assessed, and whether the active groups are likely to target or affect businesses.<br>Non-representative Sources<br>BRI A6 Fractionalization of political spectrum and the power of these factions.<br>Fractionalization by language, ethnic and/or religious groups and the power of these factions.<br>Restrictive (coercive) measures required to retain power.<br>Organization and strength of forces for a radical government.<br>Societal conflict involving demonstrations, strikes, and street violence.<br>Instability as perceived by non-constitutional changes, assassinations, and guerrilla wars.<br>WCY A18 Risk of political instability<br><!-- End of picture text --> 83
|**Tabl**<br>**Code **|**e B3:**<br> **Table**|**Government Effectiveness**<br>**Concept Measured**|
|---|---|---|
|**Repre**|**senta**|**tive Sources**|
|**DRI**|A14|_Government Instability_: An increase in government personnel turnover rate at senior levels that reduces the GDP growth rate|
|||<br>by 2% during any 12-month period.|
|||_Government Ineffectiveness:_A decline in government personnel quality at any level that reduces the GDP growth rate by 1%<br>during any 12-month period.|
|||<br>_Institutional Failure:_A deterioration of government capacity to cope with national problems as a result of institutional rigidity<br>that reduces the GDP growth rate by 1% during any 12-month period.|
|**EGV**|A13|Global E-government|
|**EIU**|A9|Quality of bureaucracy|
|||<br>Excessive bureaucracy / red tape|
|**GCS**|A28|Public Spending Composition|
|||Quality of general infrastructure<br>|
|||Quality of public schools|
|||Time spent by senior management dealing with government officials|
|**MIG**|A21|Quality of Bureaucracy.|
|**PRS**|A23|_Bureaucratic Quality._Measures institutional strength and quality of the civil service, assess how much strength and expertise<br>bureaucrats have and how able they are to manage political alternations without drastic interruptions in government services,<br>or policy changes.|
|**WMO**|A15|_Policy consistency and forward planning:_ How confident businesses can be of the continuity of economic policy stance -<br>whether a change of government will entail major policy disruption, and whether the current government has pursued a<br>coherent strategy.|
|||_Bureaucracy_**:**An assessment of the quality of the country’s bureaucracy. The better the bureaucracy the quicker decisions<br>are made and the more easily foreign investors can go about their business.|
|**Non-r**|**epres**|**entative Sources**|
|<br>**ADB**|<br>A1|<br>Management of public debt|
|||Policies to improve efficiency of public sector|
|||Revenue Mobilization|
|||Budget Management|
|**AFR**|A2|<br>Based on your experiences, how easy or difficult is it to obtain household services (like electricity or telephone)?<br>Based on your experiences, how easy or difficult is it to obtain an identity document (like birth certificate, passport)?<br>Government handling of health services<br>Government handling of education|
|**ASD**|A3|Civil service|
|||Revenue Mobilization and Budget Management|
|||<br>Management and Efficiency of Public Expenditures|
|**BPS**|A5|<br>How problematic are telecommunications for the growth of your business<br>How problematic is electricity for the growth of your business.<br>How problematic is transportation for the growth of your business.|
|**BRI**|A6<br>|<br> Bureaucratic delays|
|**BTI**|A4<br>|Consensus Building|
|||Governance Capability|
|||<br>Effective Use of Resources|
|**CPIA**|A8|Management of external debt<br>Quality public Administration<br>Revenue Mobilization|
|||Budget Management|
|**FHT**|A11|<br>_Government and Administration_: Government decentralization, independent and responsibilities or local and regional<br>|
|||governments, and legislative and executive transparency are discussed.|
|**LBO**|A20|<br>Trust in Government|
|**WCY**|A18|<br>Government economic policies do not adapt quickly to changes in the economy<br>The public service is not independent from political interference<br>Government decisions are not effectively implemented|
|||Bureaucracy hinders business activity|
|||The distribution infrastructure of goods and services is generally inefficient<br>Policy direction is not consistent|

84
# **Table B4:  Regulatory Quality**

## **Code Table**

## **Concept Measured**

**Representative Sources DRI** A14 _Regulations_ -- _Exports:_ A 2% reduction in export volume as a result of a worsening in export regulations or restrictions (such as export limits) during any 12-month period, with respect to the level at the time of the assessment. _Regulations_ -- _Imports:_ A 2% reduction in import volume as a result of a worsening in import regulations or restrictions (such as import quotas) during any 12-month period, with respect to the level at the time of the assessment. _Regulations_ -- _Other Business_ : An increase in other regulatory burdens, with respect to the level at the time of the assessment, that reduces total aggregate investment in real LCU terms by 10% _Ownership of Business by Non-Residents:_ A 1-point increase on a scale from "0" to "10" in legal restrictions on ownership of business by non-residents during any 12-month period. _Ownership of Equities by Non-Residents_ : A 1-point increase on a scale from "0" to "10" in legal restrictions on ownership of equities by non-residents during any 12-month period. **EIU** A9 Unfair competitive practices Price controls Discriminatory tariffs Excessive protections **GCS** A28 Administrative regulations are burdensome Tax system is distortionary Import barriers as obstacle to growth Competition in local market is limited Anti monopoly policy is lax and ineffective Environmental regulations hurt competitiveness Complexity of tax System **HER** A16 Regulation Government Intervention Wage/Prices Trade Foreign investment Banking **MIG** A21 _Unfair Competition_ . _Unfair Trade_ . **PRS** A23 _Investment Profile._ **WMO** A15 _Tax Effectiveness:_ How efficient the country’s tax collection system is. _Legislation:_ An assessment of whether the necessary business laws are in place.

85
|**Tabl**<br>**Code **<br>**Non-r**|**e B4:**<br> **Table**<br>**epres**|**Regulatory Quality (cont.)**<br>**Concept Measured**<br>**entative Sources**|
|---|---|---|
|**ADB**<br>**ASD**<br>**BPS**<br>**BTI**<br>**CPIA**<br>**EBRD**<br>**WCY**|A1<br>A3<br>A5<br> <br>A4<br>A8<br>A10<br>A18|Trade policy<br>Competitive environment<br>Labor Market Policies<br>Trade Policy and Forex Regime<br>Enabling Environment for Private Sector Development<br>Information on the laws and regulations is easy to obtain<br>How problematic are anti competitive practices for the growth of your business.<br>How problematic are unpredictable regulations for the growth of your business.<br>How problematic are labor regulations for the growth of your business.<br> How problematic are tax regulations for the growth of your business.<br>How problematic are custom and trade regulations for the growth of your business.<br>Competition<br>Price Stability<br>Competitive environment<br>Trade policy<br>Price liberalization<br>Trade & foreign exchange system<br>Competition policy<br>Access to capital markets (foreign and domestic) is easily available<br>Ease of Doing Business<br>Banking regulation does not hinder competitiveness<br>Competition legislation in your country does not prevent unfair competition<br>Customs' authorities do not facilitate the efficient transit of goods<br>Financial institutions' transparency is not widely developed in your country<br>Easy to start company<br>Foreign investors are free to acquire control in domestic companies<br>Price controls affect pricing of products in most industries<br>Public sector contracts are sufficiently open to foreign bidders<br>Real corporate taxes are non distortionary<br>Real personal taxes are non distortionary<br>The exchange rate policy of your country hinders the competitiveness of enterprises<br>The legal framework is detrimental to your country's competitiveness<br>Protectionism in your country negatively affects the conduct of business in your country<br>Labor regulations hinder business activities<br>Subsidies impair economic development|

86
|**Tabl**|**e B5**|**: Rule of Law**|
|---|---|---|
|**Code**|**Table**|**Concept Measured**|
|**Repr**|**esent**|**ative Sources**|
|**DRI**|A14|_Losses and Costs of Crime_: A 1-point increase on a scale from "0" to "10" in crime during any 12-month period.<br>_Kidnapping of Foreigners_: An increase in scope, intensity, or frequency of kidnapping of foreigners that reduces the GDP<br>growth rate by 1% during any 12-month period.<br>_Enforceability of Government Contracts_: A 1 point decline on a scale from "0" to "10" in the enforceability of contracts during<br>any 12-month period.<br> "" ""|
|||_Enforceability of Private Contracts:_A 1-point decline on a scale from 0 to 10 in the legal enforceability of contracts during|
|||any 12-month period|
|**EIU**|A9|.<br>Violent crime<br>Oid i|
|||rganze crme<br>Fairness of judicial process<br>Enforceability of contracts|
|||Speediness of judicial process<br>|
|||Confiscation/expropriation|
|**GCS**|A28|Common crime imposes costs on business<br>Organized crime imposes costs on business<br>Money laundering through banks is pervasive<br>Quality of Police|
|||The judiciary is independent from political influences of members of government, citizens or firms<br>Legal framework to challenge the legality of government actions is inefficient<br>Intellectual Property protection is weak<br>Protection of financial assets is weak|
|||Tax evasion|
|**HER**|A16|Black market<br>|
|||Property Rights|
|**HUM**|A26|Independence of Judiciary|
|**MIG**|A21|Oranised Crime|
|||g .<br>Legal Safeguards.|
|**PRS**|A23|_Law and Order._The Law sub-component is an assessment of the strength and impartiality of the legal system, while the<br>Order sub-component is an assessment of popular observance of the law (assessed separately).|
|**QLM**|A6|Direct Financial Fraud, Money Laundering and Organized Crime|
|**WMO**|A15|_Judicial Independence_An assessment of how far the state and other outside actors can influence and distort the legal<br>system. This will determine the level of legal impartiality investors can expect.|
|||_Crime_- How much of a threat businesses face from crime such as kidnapping, extortion, street violence, burglary...|
|**Non-**|**repre**|**sentative Sources**|
|<br>**ADB**|<br>A1|<br>Property Rights|
|**AFR**|A2|Based on your experiences, how easy or difficult is it to obtain help from the police when you need it?|
|**ASD**|A3|Rule of Law|
|**BPS**|A5|Fairness, honesty, enforceability, quickness and affordability of the court system<br>Property right protection|
|||<br>How problematic is organized crime for the growth of your business.|
|||How roblematic is judiciar for the rowth of our business|
|||p y g y .<br>How problematic is street crime for the growth of your business.|
|**BRI**|A6|<br>Enforceability of contracts|
|**BTI**|A4|Rule of Law|
|||<br>Private Property|
|**CCR**|A11|<br>Rule of Law|
|**CPIA**|A8|Property rights|
|**FHT**|A11|<br>_Rule of Law_: Considers judicial/constitutional matters as well as the legal and de facto status of ethnic minorities.|
|**GAL**|A12|Trust in the Legal System|
|**LBO**|A20|<br>Trust in Judiciary|
|||Trust in Police|
|||<br>Have you been a victim of crime?|
|**WCY**|A18|<br>Tax evasion is a common practice in your country|
|||Justice is not fairly administered in society|
|||<br>Personal security and private property are not adequately protected<br>Parallel economy impairs economic development in your country|
|||<br>Patent and copyright protection is not adequately enforced in your country|

87
|**Tabl**|**e B6**|**: Control of Corruption**|
|---|---|---|
|**Code **|**Table**|**Concept Measured**|
|**Repre**|**senta**|**tive Sources**|
|**DRI**<br>|A14<br>|Risk Event Outcome non-price: Losses and Costs of Corruption: A 1-point increase on a scale from "0" to "10" in corruption<br>during any 12-month period.<br>|
|**EIU**|A9|Corruption|
|**GCS**|A28|Public trust in financial honesty of politicians|
|||Diversion of public funds due to corruption is common|
|||Frequent for firms to make extra payments connected to: import/export permits<br>Frequent for firms to make extra payments connected to: public utilities|
|||Frequent for firms to make extra payments connected to tax payments|
|||Frequent for firms to make extra payments connected to: awarding of public contracts|
|||Frequent for firms to make extra payments connected to: getting favorable judicial decisions|
|||Extent to which firms' illegal payments to influence government policies impose costs on other firms|
|**MIG**|A21|_Corruption._There is an immense variety of activities that may be construed as corrupt. Bribery is the most obvious.<br>However, what is and is not a bribe is a matter of presentation and perception in much the same way as “corruption” itself.<br>Some of the issues that executives should consider include: accounting standards; anti-corruption policy credibility and<br>enforceability; cronyism, nepotism and vested interests; cultural differences; judicial independence; transparency of<br>decision-making.|
|**PRS**|A23|_Corruption._Measures corruption within the political system, which distorts the economic and financial environment,<br>reduces the efficiency of government and business by enabling people to assume positions of power through patronage<br>rather than ability, and introduces an inherently instability in the political system.|
|**QLM**|A6|<br>Indirect Diversion of Funds|
|**WMO**|A15|_Corruption_: This index assesses the intrusiveness of the country’s bureaucracy. The amount of red tape likely to countered<br>is assessed, as is the likelihood of encountering corrupt officials and other groups.|
|**Non-r**|**epres**|**entative Sources**|
|**ADB**|A1|Transparency / corruption|
|**AFR**|A2|How many elected leaders (parliamentarians or local councilors) do you think are involved in corruption?<br>How many judges and magistrates do you think are involved in corruption?<br>How many government officials do you think are involved in corruption?<br>|
|||How many border/tax officials do you think are involved in corruption?|
|**ASD**|A3|Anti-corruption|
|**BPS**|A5|How common is for firms to have to pay irregular additional payments to get things done<br>On average, what percent of total annual sales do firms pay in unofficial payments to public officials|
|||How often do firms make extra payments to influence the content of new legislation<br>Extent to which firms' payments to public officials to affect legislation impose costs on other firms<br>|
|||How problematic is corruption for the growth of your business.|
|||Frequency of bribery in utility, permits, procurement, health, fire inspection, environent, taxes, customs and judiciary|
|**BRI**|A6|I_nternal Causes of Political Risk_: Mentality, including xenophobia, nationalism, corruption, nepotism, willingness to<br>|
|||compromise, etc.|
|**CCR**|A11|Transparency / corruption|
|**CPIA**|A8|Transparency / corruption|
|**FHT**|A11|<br>Corruption|
|**GAL**|A12|Frequency of corruption|
|||Frequency of household bribery|
|**LBO**|A20|Have you heard of acts of corruption?|
|||Percentage of corrupt public officials|
|**PRC**|A22|Corruption Index|
|**WCY**|A18|Bribing and corruption exist in the economy|

88
# **APPENDIX C: Governance Indicators over Time**

<!-- Start of picture text --> TABLE C1: Voice and Accountability<br>2005 2004 2003 2002 2000 1998 1996<br>Country Code Est. S.E. N. Est. S.E. N. Est. S.E. N. Est. S.E. N. Est. S.E. N. Est. S.E. N. Est. S.E. N.<br>AFGHANISTAN AFG -1.28 0.15 6 -1.38 0.14 9 -1.27 0.17 7 -1.39 0.24 5 -1.86 0.33 2 -1.78 0.30 2 -1.60 0.38 2<br>ALBANIA ALB 0.08 0.12 9 0.02 0.11 9 -0.02 0.12 7 -0.15 0.14 6 -0.10 0.17 6 -0.33 0.20 5 -0.40 0.23 4<br>ALGERIA DZA -0.92 0.12 9 -0.91 0.15 9 -1.08 0.16 8 -1.00 0.18 7 -1.33 0.24 5 -1.55 0.24 4 -1.23 0.22 4<br>AMERICAN SAMOA ASM 0.59 0.55 1 0.44 0.53 1 .. .. .. .. .. .. .. .. .. .. .. .. .. .. ..<br>ANDORRA ADO 1.26 0.20 3 1.23 0.21 3 1.34 0.22 2 1.54 0.30 2 1.36 0.38 1 1.41 0.35 1 1.39 0.43 1<br>ANGOLA AGO -1.15 0.12 8 -1.02 0.16 8 -1.13 0.17 7 -1.46 0.18 7 -1.47 0.24 5 -1.38 0.24 4 -1.50 0.22 4<br>ANGUILLA AIA 0.81 0.55 1 0.75 0.53 1 .. .. .. .. .. .. .. .. .. .. .. .. .. .. ..<br>ANTIGUA AND BARBUDA ATG 0.54 0.20 3 0.48 0.21 3 0.10 0.22 2 0.12 0.30 2 -0.07 0.38 1 -0.01 0.35 1 0.12 0.43 1<br>ARGENTINA ARG 0.43 0.14 11 0.46 0.15 12 0.37 0.16 11 0.02 0.17 11 0.50 0.23 8 0.30 0.23 6 0.55 0.21 6<br>ARMENIA ARM -0.64 0.12 9 -0.66 0.11 9 -0.53 0.12 7 -0.49 0.14 6 -0.37 0.17 6 -0.38 0.20 5 -0.63 0.25 3<br>ARUBA ABW 1.03 0.55 1 0.65 0.53 1 .. .. .. .. .. .. .. .. .. .. .. .. .. .. ..<br>AUSTRALIA AUS 1.32 0.16 8 1.44 0.16 10 1.37 0.16 10 1.49 0.17 9 1.48 0.24 6 1.39 0.24 5 1.68 0.22 5<br>AUSTRIA AUT 1.24 0.16 9 1.26 0.17 9 1.20 0.17 9 1.28 0.18 9 1.12 0.24 6 1.24 0.24 6 1.39 0.22 5<br>AZERBAIJAN AZE -1.16 0.11 10 -0.97 0.10 11 -0.88 0.12 9 -0.92 0.13 9 -0.89 0.17 7 -1.04 0.19 6 -1.16 0.19 4<br>BAHAMAS BHS 1.14 0.19 4 1.14 0.20 4 1.12 0.20 3 1.15 0.26 3 1.09 0.29 2 1.05 0.29 2 1.05 0.34 2<br>BAHRAIN BHR -0.85 0.14 8 -0.72 0.14 9 -0.69 0.17 6 -0.76 0.18 7 -1.22 0.24 5 -1.24 0.24 4 -1.02 0.22 4<br>BANGLADESH BGD -0.50 0.12 9 -0.66 0.15 9 -0.57 0.16 8 -0.56 0.18 8 -0.40 0.24 6 -0.25 0.24 4 -0.40 0.22 4<br>BARBADOS BRB 1.12 0.20 3 1.17 0.21 3 1.21 0.22 2 1.36 0.30 2 1.18 0.38 1 1.41 0.35 1 1.18 0.43 1<br>BELARUS BLR -1.68 0.12 8 -1.53 0.11 9 -1.48 0.12 8 -1.42 0.14 8 -1.32 0.17 6 -1.07 0.20 5 -1.10 0.25 3<br>BELGIUM BEL 1.31 0.16 8 1.36 0.17 8 1.34 0.17 8 1.41 0.18 8 1.10 0.24 6 1.31 0.24 5 1.44 0.22 5<br>BELIZE BLZ 0.92 0.20 3 0.91 0.21 3 0.82 0.21 3 0.77 0.28 3 0.81 0.33 3 0.98 0.30 2 1.05 0.38 2<br>BENIN BEN 0.34 0.15 7 0.27 0.18 6 0.48 0.19 5 -0.08 0.24 5 0.40 0.31 3 0.58 0.29 3 0.70 0.38 2<br>BERMUDA BMU 1.03 0.55 1 1.00 0.53 1 1.03 0.54 1 1.05 0.47 1 .. .. .. .. .. .. .. .. ..<br>BHUTAN BTN -1.05 0.15 5 -1.18 0.20 4 -1.26 0.20 4 -1.18 0.26 4 -1.70 0.33 2 -1.64 0.30 2 -1.47 0.38 2<br>BOLIVIA BOL -0.09 0.12 11 -0.02 0.15 10 0.12 0.16 9 -0.04 0.18 9 0.29 0.24 6 0.41 0.23 6 0.03 0.21 5<br>BOSNIA-HERZEGOVINA BIH -0.11 0.12 9 -0.15 0.11 10 -0.19 0.12 8 -0.36 0.15 8 -0.43 0.19 5 -1.20 0.21 3 -1.28 0.38 2<br>BOTSWANA BWA 0.68 0.14 9 0.77 0.15 10 0.69 0.16 9 0.70 0.18 8 0.79 0.23 7 0.77 0.24 4 0.69 0.22 4<br>BRAZIL BRA 0.36 0.14 10 0.33 0.15 12 0.39 0.16 10 0.27 0.17 11 0.50 0.24 7 0.57 0.23 7 0.16 0.21 6<br>BRUNEI BRN -1.04 0.19 4 -1.10 0.20 4 -1.06 0.19 4 -0.85 0.23 5 -1.17 0.27 3 -1.23 0.26 3 -1.04 0.32 3<br>BULGARIA BGR 0.59 0.11 11 0.57 0.11 12 0.50 0.12 11 0.51 0.13 11 0.54 0.17 8 0.43 0.19 6 0.11 0.18 5<br>BURKINA FASO BFA -0.37 0.13 7 -0.39 0.17 6 -0.28 0.19 5 -0.30 0.23 5 -0.36 0.26 4 -0.29 0.26 3 -0.54 0.32 3<br>BURUNDI BDI -1.15 0.16 5 -1.14 0.18 5 -1.12 0.20 4 -1.22 0.26 4 -1.72 0.31 3 -1.66 0.30 2 -1.34 0.38 2<br>CAMBODIA KHM -0.94 0.16 6 -0.89 0.16 6 -0.76 0.20 4 -0.58 0.26 4 -0.45 0.33 3 -0.95 0.30 2 -0.76 0.38 2<br>CAMEROON CMR -1.19 0.14 9 -1.17 0.16 8 -1.16 0.17 8 -1.12 0.19 7 -1.09 0.24 6 -0.89 0.24 5 -1.12 0.22 4<br>CANADA CAN 1.32 0.16 9 1.37 0.16 10 1.31 0.16 10 1.43 0.17 10 1.18 0.23 8 1.16 0.24 6 1.39 0.22 5<br>CAPE VERDE CPV 0.83 0.18 5 0.79 0.20 5 0.80 0.21 4 0.32 0.29 4 0.82 0.38 1 0.88 0.35 1 0.86 0.43 1<br>CAYMAN ISLANDS CYM 0.81 0.55 1 0.77 0.53 1 0.81 0.54 1 1.50 0.47 1 .. .. .. .. .. .. .. .. ..<br>CENTRAL AFRICAN REPUBLIC CAF -1.15 0.16 5 -1.21 0.18 5 -1.14 0.20 4 -0.86 0.26 4 -0.60 0.33 2 -0.01 0.30 2 -0.21 0.38 2<br>CHAD TCD -1.25 0.16 6 -1.09 0.18 6 -1.00 0.19 5 -1.01 0.26 4 -0.97 0.33 2 -0.91 0.29 3 -0.83 0.38 2<br>CHILE CHL 1.04 0.14 10 1.05 0.15 11 1.07 0.16 10 1.09 0.17 10 0.47 0.23 8 0.59 0.23 6 0.89 0.21 6<br>CHINA CHN -1.66 0.12 10 -1.52 0.15 10 -1.60 0.16 9 -1.37 0.17 9 -1.58 0.24 7 -1.72 0.24 5 -1.36 0.22 5<br>COLOMBIA COL -0.32 0.12 12 -0.53 0.15 10 -0.50 0.16 9 -0.59 0.18 10 -0.43 0.23 8 -0.26 0.23 7 -0.13 0.21 6<br>COMOROS COM -0.28 0.19 4 -0.14 0.20 4 -0.55 0.21 3 -0.52 0.29 3 -0.54 0.38 1 -0.10 0.35 1 -0.18 0.43 1<br>CONGO COG -0.71 0.18 5 -0.81 0.18 6 -0.75 0.18 6 -1.13 0.22 6 -1.55 0.26 4 -1.00 0.26 4 -1.33 0.32 3<br>Congo, Dem. Rep. (Zaire) ZAR -1.64 0.14 7 -1.66 0.15 8 -1.62 0.17 7 -1.96 0.23 5 -1.95 0.26 4 -1.72 0.26 3 -1.29 0.32 3<br>COSTA RICA CRI 0.99 0.14 10 1.13 0.15 11 1.08 0.16 9 1.13 0.17 10 1.26 0.24 6 1.21 0.23 6 1.32 0.21 5<br>CROATIA HRV 0.51 0.11 11 0.46 0.11 11 0.47 0.12 9 0.44 0.13 10 0.32 0.17 7 -0.32 0.19 5 -0.57 0.19 4<br>CUBA CUB -1.87 0.14 7 -1.85 0.15 8 -1.99 0.17 7 -1.77 0.18 7 -1.87 0.24 4 -1.79 0.24 4 -1.46 0.22 4<br>CYPRUS CYP 1.03 0.16 7 1.02 0.17 8 1.03 0.17 7 0.94 0.18 6 1.14 0.24 4 1.00 0.24 4 1.01 0.22 4<br>CZECH REPUBLIC CZE 1.01 0.11 11 1.02 0.11 11 0.92 0.12 10 0.86 0.14 9 0.99 0.17 8 1.08 0.19 7 1.01 0.18 6<br>DENMARK DNK 1.51 0.16 9 1.60 0.16 10 1.51 0.16 10 1.70 0.17 10 1.35 0.23 7 1.40 0.24 5 1.69 0.22 5<br>DJIBOUTI DJI -0.84 0.19 4 -0.85 0.20 4 -0.88 0.21 3 -0.76 0.29 3 -0.63 0.38 1 -0.80 0.35 1 -0.85 0.43 1<br>DOMINICA DMA 1.12 0.20 3 1.13 0.21 3 1.14 0.22 2 0.99 0.30 2 1.18 0.38 1 1.24 0.35 1 1.22 0.43 1<br>DOMINICAN REPUBLIC DOM 0.20 0.14 10 0.26 0.16 9 0.24 0.17 7 0.13 0.19 7 0.48 0.24 6 -0.01 0.24 4 -0.05 0.22 4<br>ECUADOR ECU -0.16 0.12 11 -0.13 0.15 10 -0.09 0.16 9 -0.11 0.18 8 -0.17 0.24 6 0.30 0.23 6 0.00 0.21 5<br>EGYPT EGY -1.15 0.12 9 -1.02 0.15 9 -1.11 0.16 8 -0.88 0.18 8 -0.91 0.24 6 -0.89 0.24 4 -0.80 0.22 4<br>EL SALVADOR SLV 0.26 0.14 9 0.27 0.16 9 0.24 0.16 8 0.01 0.18 8 0.41 0.24 6 0.08 0.23 5 -0.30 0.21 5<br>EQUATORIAL GUINEA GNQ -1.71 0.19 4 -1.71 0.20 4 -1.58 0.21 3 -1.46 0.29 3 -1.55 0.38 1 -1.64 0.35 1 -1.56 0.43 1<br>ERITREA ERI -1.83 0.13 6 -1.91 0.18 6 -1.96 0.19 5 -2.09 0.24 5 -1.51 0.31 3 -1.13 0.30 2 -1.17 0.38 2<br>ESTONIA EST 1.05 0.12 10 1.10 0.11 12 0.99 0.12 10 0.97 0.14 9 0.89 0.16 9 0.78 0.19 6 0.72 0.19 4<br>ETHIOPIA ETH -1.10 0.12 10 -1.05 0.15 9 -1.08 0.16 8 -1.17 0.22 6 -1.06 0.26 5 -0.74 0.26 3 -0.68 0.32 3<br>FIJI FJI 0.18 0.19 4 0.13 0.19 5 0.07 0.19 5 -0.12 0.25 4 0.05 0.31 3 0.03 0.29 3 -0.14 0.38 2<br>FINLAND FIN 1.49 0.16 9 1.52 0.17 9 1.49 0.17 8 1.68 0.18 9 1.47 0.23 7 1.39 0.24 5 1.67 0.22 5<br>FRANCE FRA 1.28 0.16 9 1.25 0.16 10 1.18 0.16 10 1.24 0.17 9 0.98 0.23 8 1.06 0.24 6 1.46 0.22 5<br>FRENCH GUIANA GUF 0.37 0.55 1 0.44 0.53 1 0.38 0.54 1 0.39 0.47 1 .. .. .. .. .. .. .. .. ..<br>GABON GAB -0.71 0.16 6 -0.71 0.17 6 -0.64 0.17 6 -0.45 0.19 6 -0.49 0.24 5 -0.27 0.24 4 -0.61 0.22 4<br>GAMBIA GMB -0.72 0.18 6 -0.64 0.18 7 -0.62 0.18 7 -1.08 0.22 6 -1.06 0.27 3 -1.27 0.26 3 -1.43 0.32 3<br>GEORGIA GEO -0.27 0.12 8 -0.38 0.11 11 -0.37 0.12 8 -0.40 0.15 7 -0.26 0.18 6 -0.44 0.21 4 -0.58 0.25 3<br>GERMANY DEU 1.31 0.16 9 1.37 0.16 10 1.32 0.16 10 1.45 0.17 10 1.18 0.23 8 1.25 0.24 6 1.51 0.22 5<br>Note: “Est.” refers to estimate, “S.E.” refers to standard errors, and “N.” refers to number of sources. The<br>standard errors have the following interpretation: there is roughly a 70% chance that the level of governance lies<br>within plus or minus one standard error of the point estimate of governance.<br><!-- End of picture text --> 89
<!-- Start of picture text --> TABLE C1: Voice and Accountability (cont.)<br>2005 2004 2003 2002 2000 1998 1996<br>Country Code Est. S.E. N. Est. S.E. N. Est. S.E. N. Est. S.E. N. Est. S.E. N. Est. S.E. N. Est. S.E. N.<br>GHANA GHA 0.41 0.14 10 0.33 0.15 11 0.35 0.16 9 0.01 0.18 8 -0.13 0.24 7 -0.51 0.24 5 -0.41 0.22 4<br>GREECE GRC 0.95 0.16 9 0.92 0.17 9 0.96 0.17 9 1.01 0.18 8 0.94 0.24 5 0.82 0.24 5 0.93 0.22 5<br>GRENADA GRD 0.84 0.20 3 0.84 0.20 4 0.90 0.22 2 0.61 0.30 2 0.95 0.38 1 1.01 0.35 1 0.99 0.43 1<br>GUAM GUM 0.59 0.55 1 0.52 0.53 1 .. .. .. .. .. .. .. .. .. .. .. .. .. .. ..<br>GUATEMALA GTM -0.37 0.14 10 -0.38 0.14 12 -0.50 0.16 9 -0.51 0.17 10 -0.21 0.24 6 -0.39 0.23 5 -0.71 0.21 5<br>GUINEA GIN -1.18 0.15 6 -1.12 0.17 6 -1.28 0.19 5 -1.24 0.23 5 -1.18 0.27 3 -1.05 0.26 4 -1.21 0.32 3<br>GUINEA-BISSAU GNB -0.31 0.18 5 -0.65 0.18 6 -0.95 0.18 6 -0.84 0.22 6 -0.87 0.26 4 -0.34 0.26 4 -0.61 0.32 3<br>GUYANA GUY 0.49 0.18 5 0.61 0.20 4 0.68 0.19 4 0.59 0.24 4 0.86 0.26 4 0.92 0.26 3 0.85 0.32 3<br>HAITI HTI -1.41 0.15 6 -1.51 0.15 8 -1.27 0.18 7 -1.15 0.21 7 -0.87 0.26 5 -0.69 0.26 3 -0.54 0.32 3<br>HONDURAS HND -0.14 0.12 10 -0.05 0.15 10 -0.07 0.16 9 -0.23 0.18 8 0.12 0.24 6 0.23 0.23 5 -0.43 0.21 5<br>HONG KONG HKG 0.26 0.17 8 0.22 0.17 8 0.41 0.25 7 0.16 0.19 8 -0.52 0.26 5 -0.30 0.26 5 0.49 0.23 4<br>HUNGARY HUN 1.10 0.12 10 1.16 0.11 11 1.09 0.12 10 1.12 0.14 10 1.09 0.16 9 1.09 0.19 7 1.02 0.18 6<br>ICELAND ISL 1.38 0.17 8 1.42 0.18 8 1.40 0.18 8 1.50 0.22 7 1.38 0.26 5 1.31 0.26 4 1.40 0.31 4<br>INDIA IND 0.35 0.14 10 0.29 0.15 11 0.24 0.16 10 0.36 0.17 10 0.40 0.24 7 0.18 0.24 6 0.23 0.22 5<br>INDONESIA IDN -0.21 0.14 10 -0.43 0.14 12 -0.45 0.16 10 -0.52 0.17 10 -0.54 0.24 7 -1.45 0.24 5 -1.22 0.22 5<br>IRAN IRN -1.43 0.12 8 -1.38 0.15 8 -1.46 0.17 7 -1.10 0.18 7 -0.82 0.24 5 -1.08 0.24 4 -1.16 0.22 4<br>IRAQ IRQ -1.47 0.14 7 -1.72 0.16 7 -1.61 0.17 6 -2.15 0.19 6 -2.24 0.24 5 -2.03 0.24 4 -1.80 0.22 4<br>IRELAND IRL 1.41 0.16 9 1.33 0.16 10 1.27 0.16 9 1.40 0.17 10 1.38 0.23 7 1.30 0.24 6 1.44 0.22 5<br>ISRAEL ISR 0.61 0.16 9 0.48 0.16 10 0.60 0.16 9 0.59 0.17 10 0.89 0.24 6 0.97 0.24 5 1.03 0.22 5<br>ITALY ITA 1.00 0.16 9 1.07 0.17 9 1.02 0.17 9 1.06 0.18 9 1.01 0.23 8 1.17 0.24 6 1.05 0.22 5<br>IVORY COAST CIV -1.50 0.14 7 -1.46 0.15 8 -1.35 0.17 7 -1.28 0.18 7 -1.35 0.24 5 -0.77 0.24 5 -0.25 0.22 4<br>JAMAICA JAM 0.57 0.14 8 0.53 0.16 8 0.47 0.17 7 0.48 0.19 6 0.72 0.24 4 0.68 0.24 5 0.49 0.22 4<br>JAPAN JPN 0.94 0.16 9 0.99 0.16 10 1.00 0.16 10 0.97 0.17 10 0.86 0.23 7 1.01 0.26 4 1.02 0.22 5<br>JORDAN JOR -0.74 0.14 9 -0.67 0.14 10 -0.60 0.17 8 -0.43 0.18 7 -0.38 0.24 5 -0.38 0.24 5 -0.22 0.22 4<br>KAZAKHSTAN KAZ -1.19 0.11 10 -1.21 0.10 11 -1.15 0.12 9 -1.17 0.13 9 -0.99 0.17 8 -0.80 0.19 6 -1.08 0.19 4<br>KENYA KEN -0.12 0.14 10 -0.31 0.14 12 -0.29 0.16 10 -0.69 0.18 8 -0.88 0.24 6 -0.89 0.24 5 -0.56 0.22 4<br>KIRIBATI KIR 0.87 0.20 3 0.85 0.21 3 1.05 0.23 1 1.01 0.37 1 1.12 0.38 1 1.22 0.35 1 1.13 0.43 1<br>KOREA, NORTH PRK -2.06 0.14 7 -2.04 0.15 8 -2.24 0.17 7 -2.38 0.22 6 -2.11 0.27 3 -2.03 0.26 3 -1.92 0.32 3<br>KOREA, SOUTH KOR 0.74 0.14 10 0.76 0.15 11 0.63 0.16 10 0.64 0.17 10 0.72 0.23 7 0.66 0.24 6 0.65 0.22 5<br>KOSOVO LWI -0.46 0.19 3 .. .. .. 0.88 0.89 1 .. .. .. .. .. .. .. .. .. .. .. ..<br>KUWAIT KWT -0.47 0.15 8 -0.45 0.17 7 -0.47 0.17 7 -0.27 0.18 8 -0.39 0.24 4 -0.47 0.24 4 -0.25 0.22 4<br>KYRGYZ REPUBLIC KGZ -1.03 0.12 7 -1.08 0.11 9 -1.06 0.12 7 -0.98 0.15 7 -0.75 0.19 4 -0.52 0.21 4 -0.55 0.25 3<br>LAOS LAO -1.54 0.13 7 -1.54 0.18 5 -1.86 0.20 4 -1.74 0.26 4 -1.52 0.31 3 -1.34 0.30 2 -1.18 0.38 2<br>LATVIA LVA 0.89 0.12 9 0.96 0.11 10 0.94 0.13 8 0.86 0.14 7 0.84 0.17 6 0.73 0.19 6 0.46 0.19 4<br>LEBANON LBN -0.72 0.14 7 -0.79 0.16 7 -0.82 0.17 6 -0.56 0.18 7 -0.50 0.24 5 -0.67 0.24 4 -0.50 0.22 4<br>LESOTHO LSO 0.28 0.18 5 0.26 0.20 5 0.22 0.20 5 -0.20 0.28 4 -0.21 0.32 3 -0.09 0.30 2 -0.04 0.38 2<br>LIBERIA LBR -0.92 0.15 6 -1.26 0.17 7 -1.61 0.18 6 -1.57 0.22 6 -1.24 0.26 4 -1.01 0.26 3 -1.48 0.32 3<br>LIBYA LBY -1.93 0.12 8 -1.78 0.16 7 -1.85 0.17 6 -1.71 0.19 6 -1.75 0.24 4 -1.70 0.24 4 -1.53 0.22 4<br>LIECHTENSTEIN LIE 1.26 0.20 3 1.28 0.21 3 1.27 0.22 2 1.45 0.30 2 1.36 0.38 1 1.41 0.35 1 1.39 0.43 1<br>LITHUANIA LTU 0.90 0.11 10 0.98 0.11 11 0.99 0.12 9 0.85 0.14 8 0.96 0.17 8 0.86 0.19 6 0.71 0.19 4<br>LUXEMBOURG LUX 1.34 0.18 6 1.41 0.19 7 1.33 0.19 7 1.38 0.23 6 1.29 0.26 5 1.32 0.26 4 1.45 0.31 4<br>MACAO MAC 0.37 0.55 1 0.11 0.53 1 0.60 0.54 1 0.39 0.47 1 .. .. .. .. .. .. .. .. ..<br>MACEDONIA MKD 0.03 0.11 10 -0.02 0.11 10 -0.03 0.12 9 -0.36 0.14 7 -0.08 0.18 5 0.01 0.20 5 -0.13 0.19 4<br>MADAGASCAR MDG -0.01 0.15 8 0.06 0.17 7 -0.06 0.18 6 -0.08 0.23 5 0.21 0.26 5 0.36 0.26 4 0.21 0.32 3<br>MALAWI MWI -0.45 0.14 9 -0.52 0.16 9 -0.34 0.17 8 -0.62 0.19 7 -0.31 0.23 7 -0.11 0.24 5 -0.50 0.22 4<br>MALAYSIA MYS -0.41 0.14 10 -0.35 0.14 12 -0.39 0.16 10 -0.30 0.17 10 -0.35 0.23 8 -0.22 0.24 6 -0.11 0.22 5<br>MALDIVES MDV -1.09 0.19 4 -1.07 0.20 4 -1.01 0.21 3 -0.72 0.30 2 -1.02 0.38 1 -1.13 0.35 1 -1.07 0.43 1<br>MALI MLI 0.47 0.15 8 0.35 0.17 9 0.35 0.18 8 0.10 0.22 7 0.26 0.25 5 0.37 0.26 4 0.26 0.32 3<br>MALTA MLT 1.18 0.18 5 1.26 0.20 5 1.28 0.20 4 1.25 0.26 3 1.34 0.29 2 1.31 0.29 2 1.06 0.34 2<br>MARSHALL ISLANDS MHL 1.19 0.21 2 1.14 0.23 2 1.23 0.23 1 1.20 0.37 1 1.27 0.38 1 1.32 0.35 1 1.18 0.43 1<br>MARTINIQUE MTQ 0.59 0.55 1 0.69 0.53 1 0.60 0.54 1 0.61 0.47 1 .. .. .. .. .. .. .. .. ..<br>MAURITANIA MRT -1.09 0.15 5 -1.17 0.20 4 -0.74 0.20 4 -0.68 0.26 4 -0.75 0.31 3 -1.00 0.30 2 -0.91 0.38 2<br>MAURITIUS MUS 0.92 0.15 7 1.01 0.18 6 0.90 0.18 6 0.76 0.20 6 1.29 0.28 4 0.99 0.26 4 0.82 0.24 3<br>MEXICO MEX 0.29 0.14 11 0.31 0.15 12 0.38 0.16 11 0.26 0.17 11 0.05 0.23 8 -0.30 0.23 7 -0.30 0.21 6<br>MICRONESIA FSM 1.11 0.20 3 1.00 0.21 3 0.96 0.23 1 0.89 0.37 1 0.93 0.38 1 0.94 0.35 1 1.14 0.43 1<br>MOLDOVA MDA -0.49 0.11 11 -0.47 0.11 10 -0.38 0.12 8 -0.38 0.13 7 -0.06 0.17 7 -0.13 0.19 6 -0.28 0.19 4<br>MONACO MCO 0.96 0.21 2 0.90 0.23 2 1.05 0.23 1 1.09 0.37 1 1.08 0.38 1 1.14 0.35 1 1.12 0.43 1<br>MONGOLIA MNG 0.36 0.15 7 0.48 0.17 7 0.51 0.18 6 0.44 0.22 6 0.68 0.26 4 0.56 0.20 4 0.32 0.32 3<br>MOROCCO MAR -0.76 0.14 8 -0.56 0.14 10 -0.62 0.16 8 -0.34 0.18 8 -0.51 0.24 4 -0.58 0.24 5 -0.70 0.22 4<br>MOZAMBIQUE MOZ -0.06 0.13 9 -0.11 0.17 9 -0.10 0.18 8 -0.30 0.22 7 -0.30 0.26 4 -0.13 0.26 4 -0.26 0.32 3<br>MYANMAR MMR -2.16 0.14 7 -2.19 0.15 8 -2.18 0.17 7 -2.08 0.18 7 -2.24 0.24 5 -2.02 0.24 4 -1.80 0.22 4<br>NAMIBIA NAM 0.36 0.14 9 0.40 0.15 10 0.33 0.16 9 0.29 0.18 9 0.33 0.23 7 0.38 0.24 4 0.46 0.22 4<br>NAURU NRU 1.03 0.21 2 1.08 0.23 2 0.86 0.23 1 0.77 0.37 1 0.85 0.38 1 0.98 0.35 1 0.84 0.43 1<br>NEPAL NPL -1.19 0.15 6 -1.00 0.15 8 -0.69 0.17 6 -0.55 0.24 5 -0.18 0.31 3 -0.08 0.30 2 0.09 0.38 2<br>NETHERLANDS NLD 1.45 0.16 9 1.51 0.17 9 1.41 0.17 9 1.61 0.18 9 1.36 0.23 7 1.39 0.24 5 1.66 0.22 5<br>NETHERLANDS ANTILLES ANT 0.59 0.55 1 0.44 0.53 1 .. .. .. .. .. .. .. .. .. .. .. .. .. .. ..<br>NEW ZEALAND NZL 1.39 0.16 8 1.48 0.17 9 1.41 0.17 9 1.58 0.18 7 1.34 0.24 6 1.21 0.24 5 1.61 0.22 5<br>NICARAGUA NIC -0.01 0.14 10 0.04 0.14 11 0.08 0.16 9 0.02 0.18 8 0.02 0.24 6 -0.03 0.23 5 -0.28 0.21 5<br>NIGER NER -0.06 0.15 6 -0.13 0.17 6 -0.29 0.19 5 -0.23 0.23 5 -0.17 0.26 4 -1.00 0.26 3 -0.47 0.32 3<br>NIGERIA NGA -0.69 0.14 10 -0.73 0.14 12 -0.65 0.16 10 -0.81 0.17 10 -0.61 0.23 8 -1.55 0.24 5 -1.57 0.22 4<br><!-- End of picture text --> 90
<!-- Start of picture text --> TABLE C1: Voice and Accountability (cont.)<br>2005 2004 2003 2002 2000 1998 1996<br>Country Code Est. S.E. N. Est. S.E. N. Est. S.E. N. Est. S.E. N. Est. S.E. N. Est. S.E. N. Est. S.E. N.<br>NORWAY NOR 1.45 0.16 9 1.55 0.17 9 1.44 0.17 9 1.62 0.18 9 1.33 0.24 6 1.43 0.24 5 1.71 0.22 5<br>OMAN OMN -0.94 0.17 5 -0.87 0.17 6 -0.96 0.17 7 -0.52 0.18 7 -0.92 0.24 4 -0.95 0.24 4 -0.68 0.22 4<br>PALAU PCI 1.19 0.21 2 1.21 0.23 2 1.24 0.23 1 .. .. .. .. .. .. .. .. .. .. .. ..<br>PAKISTAN PAK -1.23 0.14 9 -1.31 0.14 10 -1.18 0.17 8 -1.12 0.19 7 -1.57 0.24 6 -0.68 0.24 4 -1.06 0.22 4<br>PANAMA PAN 0.52 0.14 10 0.56 0.16 9 0.58 0.16 9 0.42 0.17 10 0.72 0.24 6 0.52 0.23 5 0.27 0.21 5<br>PAPUA NEW GUINEA PNG -0.05 0.15 6 -0.07 0.16 7 0.12 0.17 6 -0.23 0.18 6 0.03 0.24 5 0.17 0.24 4 0.09 0.22 4<br>PARAGUAY PRY -0.19 0.12 11 -0.29 0.15 10 -0.45 0.16 9 -0.59 0.17 9 -0.58 0.24 5 -0.29 0.23 6 -0.46 0.21 5<br>PERU PER 0.04 0.12 11 -0.06 0.15 11 0.08 0.16 10 0.18 0.17 10 -0.10 0.23 7 -0.82 0.23 6 -0.81 0.21 5<br>PHILIPPINES PHL 0.01 0.12 11 0.02 0.15 11 0.14 0.16 10 0.13 0.17 9 0.32 0.23 8 0.41 0.24 5 0.11 0.22 5<br>POLAND POL 1.04 0.11 11 1.13 0.11 12 1.05 0.12 11 1.08 0.14 11 1.13 0.16 9 1.00 0.19 7 0.95 0.18 6<br>PORTUGAL PRT 1.32 0.16 9 1.32 0.17 9 1.27 0.17 9 1.27 0.18 9 1.29 0.24 6 1.35 0.24 6 1.27 0.22 5<br>PUERTO RICO PRI 1.03 0.21 2 1.01 0.23 2 0.60 0.54 1 0.61 0.47 1 .. .. .. .. .. .. .. .. ..<br>QATAR QAT -0.75 0.16 7 -0.78 0.15 7 -0.90 0.18 5 -0.51 0.19 5 -0.92 0.26 3 -1.04 0.26 3 -0.91 0.23 3<br>REUNION REU 1.25 0.55 1 1.06 0.53 1 .. .. .. .. .. .. .. .. .. .. .. .. .. .. ..<br>ROMANIA ROM 0.36 0.11 12 0.38 0.11 13 0.39 0.12 11 0.38 0.13 11 0.42 0.17 8 0.20 0.19 5 -0.04 0.18 5<br>RUSSIA RUS -0.85 0.10 13 -0.79 0.11 13 -0.68 0.12 12 -0.45 0.13 12 -0.47 0.16 9 -0.26 0.19 7 -0.43 0.18 6<br>RWANDA RWA -1.32 0.13 6 -1.11 0.18 6 -1.36 0.19 5 -1.49 0.24 5 -1.53 0.31 3 -1.57 0.30 2 -1.48 0.38 2<br>SAMOA SAM 0.62 0.20 3 0.69 0.21 3 0.67 0.22 2 0.63 0.30 2 0.57 0.38 1 0.56 0.35 1 0.72 0.43 1<br>SAN MARINO SMR 1.16 0.21 2 1.19 0.23 2 1.24 0.23 1 1.37 0.37 1 1.36 0.38 1 1.41 0.35 1 1.39 0.43 1<br>SAO TOME AND PRINCIPE STP 0.56 0.20 3 0.54 0.21 3 0.71 0.22 2 0.39 0.30 2 0.90 0.38 1 0.70 0.35 1 0.84 0.43 1<br>SAUDI ARABIA SAU -1.72 0.14 7 -1.58 0.15 8 -1.62 0.17 7 -1.34 0.18 8 -1.37 0.24 5 -1.44 0.24 4 -1.30 0.22 4<br>SENEGAL SEN 0.30 0.14 9 0.18 0.15 9 0.24 0.16 9 0.12 0.18 8 -0.16 0.24 6 -0.71 0.24 5 -0.23 0.22 4<br>SEYCHELLES SYC -0.04 0.19 4 -0.04 0.20 4 0.06 0.21 3 0.13 0.29 3 0.05 0.38 1 0.13 0.35 1 0.06 0.43 1<br>SIERRA LEONE SLE -0.38 0.15 6 -0.55 0.15 8 -0.68 0.18 6 -0.72 0.22 6 -1.35 0.26 4 -1.75 0.26 3 -1.45 0.32 3<br>SINGAPORE SGP -0.29 0.14 10 -0.10 0.16 10 -0.12 0.17 8 0.50 0.18 7 -0.24 0.24 7 -0.15 0.24 6 0.35 0.22 5<br>SLOVAK REPUBLIC SVK 1.04 0.12 10 1.09 0.11 10 0.97 0.13 9 0.88 0.14 8 0.87 0.17 8 0.37 0.19 6 0.34 0.18 5<br>SLOVENIA SVN 1.08 0.12 10 1.13 0.11 11 1.09 0.12 10 1.07 0.14 10 0.94 0.17 8 0.86 0.19 5 0.95 0.19 4<br>SOLOMON ISLANDS SLB 0.27 0.20 3 0.08 0.21 3 0.31 0.23 1 0.40 0.37 1 0.01 0.38 1 1.07 0.35 1 1.02 0.43 1<br>SOMALIA SOM -1.89 0.15 6 -1.66 0.17 7 -1.64 0.18 6 -1.68 0.23 5 -1.43 0.26 4 -1.51 0.26 3 -1.98 0.32 3<br>SOUTH AFRICA ZAF 0.82 0.14 11 0.84 0.15 12 0.82 0.16 11 0.70 0.17 11 0.96 0.23 9 0.79 0.24 6 0.62 0.22 5<br>SPAIN ESP 1.12 0.16 9 1.15 0.16 10 1.13 0.16 9 1.16 0.17 10 1.01 0.23 8 1.09 0.24 6 1.10 0.22 5<br>SRI LANKA LKA -0.26 0.14 8 -0.17 0.14 10 -0.13 0.16 8 -0.12 0.18 8 -0.40 0.24 5 -0.33 0.24 4 -0.28 0.22 4<br>ST. KITTS AND NEVIS KNA 0.87 0.20 3 0.74 0.21 3 0.95 0.23 1 0.92 0.37 1 0.97 0.38 1 1.03 0.35 1 1.00 0.43 1<br>ST. LUCIA LCA 1.04 0.20 3 0.96 0.21 3 1.06 0.23 1 1.04 0.37 1 1.03 0.38 1 1.09 0.35 1 1.07 0.43 1<br>ST. VINCENT AND THE GRENADINES VCT 1.04 0.20 3 0.95 0.21 3 0.96 0.23 1 0.96 0.37 1 1.00 0.38 1 1.05 0.35 1 1.08 0.43 1<br>SUDAN SDN -1.84 0.14 7 -1.80 0.15 8 -1.85 0.17 7 -1.71 0.18 7 -1.88 0.24 5 -1.81 0.24 4 -1.74 0.22 4<br>SURINAME SUR 0.74 0.19 4 0.57 0.20 4 0.57 0.20 3 0.20 0.26 3 0.55 0.29 2 0.16 0.29 2 -0.12 0.34 2<br>SWAZILAND SWZ -1.28 0.15 5 -1.32 0.20 4 -1.26 0.20 4 -1.25 0.26 4 -1.29 0.33 2 -0.99 0.30 2 -1.35 0.38 2<br>SWEDEN SWE 1.41 0.16 8 1.53 0.16 9 1.48 0.16 9 1.63 0.17 10 1.45 0.23 8 1.37 0.24 5 1.66 0.22 5<br>SWITZERLAND CHE 1.43 0.16 9 1.50 0.17 9 1.43 0.17 9 1.61 0.18 9 1.52 0.23 7 1.44 0.24 6 1.67 0.22 5<br>SYRIA SYR -1.67 0.12 8 -1.73 0.15 8 -1.79 0.17 7 -1.59 0.18 7 -1.76 0.24 4 -1.69 0.24 4 -1.45 0.22 4<br>TAIWAN TWN 0.79 0.14 10 0.96 0.15 11 0.79 0.16 10 0.88 0.17 9 0.82 0.23 7 0.68 0.24 5 0.50 0.22 5<br>TAJIKISTAN TJK -1.17 0.11 9 -1.12 0.12 8 -1.17 0.12 7 -1.14 0.15 7 -1.02 0.19 4 -1.47 0.21 3 -1.50 0.25 3<br>TANZANIA TZA -0.31 0.14 9 -0.37 0.15 10 -0.25 0.16 9 -0.51 0.18 8 -0.21 0.23 7 -0.50 0.24 5 -0.85 0.22 4<br>THAILAND THA 0.07 0.12 11 0.25 0.15 10 0.27 0.16 9 0.15 0.17 9 0.27 0.24 7 0.02 0.24 6 -0.05 0.22 5<br>TIMOR, EAST TMP 0.18 0.18 5 0.24 0.17 5 0.28 0.21 3 0.19 0.30 2 .. .. .. .. .. .. .. .. ..<br>TOGO TGO -1.23 0.15 7 -1.23 0.17 6 -1.11 0.19 5 -1.26 0.23 5 -1.13 0.27 3 -1.19 0.26 4 -1.14 0.32 3<br>TONGA TON -0.16 0.19 4 -0.36 0.20 4 -0.14 0.23 1 -0.08 0.37 1 -0.15 0.38 1 -0.11 0.35 1 -0.08 0.43 1<br>TRINIDAD AND TOBAGO TTO 0.44 0.16 7 0.49 0.17 7 0.48 0.17 7 0.53 0.19 6 0.58 0.24 5 0.92 0.24 4 0.72 0.22 4<br>TUNISIA TUN -1.13 0.12 9 -1.06 0.15 9 -1.02 0.16 8 -0.80 0.18 8 -0.85 0.24 5 -0.99 0.24 4 -0.60 0.22 4<br>TURKEY TUR -0.04 0.12 11 -0.10 0.15 11 -0.29 0.16 10 -0.44 0.17 10 -0.74 0.23 8 -0.97 0.24 6 -0.47 0.22 5<br>TURKMENISTAN TKM -1.95 0.12 6 -1.89 0.12 6 -1.93 0.14 5 -1.89 0.17 5 -1.70 0.19 3 -1.68 0.21 3 -1.77 0.25 3<br>TUVALU TUV 1.04 0.20 3 0.92 0.21 3 1.16 0.23 1 1.37 0.37 1 1.36 0.38 1 1.41 0.35 1 1.39 0.43 1<br>UGANDA UGA -0.59 0.14 9 -0.65 0.14 12 -0.78 0.16 10 -0.81 0.18 8 -0.91 0.23 7 -0.58 0.24 5 -0.71 0.22 4<br>UKRAINE UKR -0.26 0.11 11 -0.61 0.10 13 -0.59 0.12 11 -0.68 0.13 10 -0.43 0.17 7 -0.15 0.19 6 -0.46 0.19 4<br>UNITED ARAB EMIRATES ARE -1.08 0.14 8 -0.98 0.17 7 -0.92 0.17 6 -0.49 0.19 6 -0.76 0.24 4 -0.84 0.24 4 -0.74 0.22 4<br>UNITED KINGDOM GBR 1.30 0.16 9 1.37 0.16 10 1.33 0.16 10 1.44 0.17 10 1.21 0.23 8 1.27 0.24 6 1.34 0.22 5<br>UNITED STATES USA 1.19 0.16 9 1.22 0.17 9 1.16 0.17 9 1.30 0.18 9 1.11 0.24 7 1.38 0.24 6 1.48 0.22 5<br>URUGUAY URY 0.99 0.14 10 0.99 0.15 10 0.98 0.16 9 0.89 0.18 8 0.96 0.24 6 0.68 0.23 5 0.72 0.21 5<br>UZBEKISTAN UZB -1.76 0.11 8 -1.73 0.11 10 -1.74 0.12 8 -1.58 0.13 8 -1.51 0.18 6 -1.60 0.20 5 -1.47 0.19 4<br>VANUATU VUT 0.60 0.20 3 0.67 0.21 3 0.91 0.23 1 0.82 0.37 1 0.58 0.38 1 0.58 0.35 1 0.45 0.43 1<br>VENEZUELA VEN -0.50 0.14 11 -0.48 0.14 13 -0.47 0.16 10 -0.46 0.17 10 -0.24 0.24 6 0.26 0.23 7 0.00 0.21 6<br>VIETNAM VNM -1.60 0.14 8 -1.52 0.14 10 -1.58 0.16 8 -1.34 0.18 8 -1.65 0.24 5 -1.73 0.24 4 -1.39 0.22 4<br>VIRGIN ISLANDS (U.S.) VIR 1.03 0.55 1 0.67 0.53 1 .. .. .. .. .. .. .. .. .. .. .. .. .. .. ..<br>WEST BANK WBG -1.22 0.20 3 -1.24 0.22 3 -1.47 0.21 3 -1.15 0.29 3 -0.97 0.38 2 -0.73 0.34 2 -1.64 0.43 1<br>YEMEN YEM -1.07 0.14 7 -0.98 0.14 9 -0.98 0.17 7 -0.90 0.18 7 -0.78 0.24 5 -0.73 0.24 4 -0.99 0.22 4<br>YUGOSLAVIA YUG 0.12 0.11 11 0.11 0.11 11 0.14 0.12 10 -0.30 0.13 8 -0.29 0.17 5 -1.05 0.19 5 -1.45 0.22 4<br>ZAMBIA ZMB -0.35 0.12 9 -0.33 0.15 10 -0.38 0.16 9 -0.46 0.18 8 -0.25 0.23 7 -0.11 0.24 5 -0.23 0.22 4<br>ZIMBABWE ZWE -1.65 0.14 9 -1.55 0.14 9 -1.62 0.17 7 -1.50 0.18 7 -1.24 0.24 6 -0.79 0.24 5 -0.37 0.22 4<br><!-- End of picture text --> 91
# **TABLE C2: Political Stability**

<!-- Start of picture text --> 2005 2004 2003 2002 2000 1998 1996<br>Country Code Est. S.E. N. Est. S.E. N. Est. S.E. N. Est. S.E. N. Est. S.E. N. Est. S.E. N. Est. S.E. N.<br>AFGHANISTAN AFG -2.12 0.25 5 -2.14 0.23 7 -2.19 0.26 5 -2.35 0.28 4 -2.68 0.40 2 -2.28 0.51 1 -2.06 0.56 1<br>ALBANIA ALB -0.68 0.26 6 -0.79 0.26 6 -0.43 0.31 4 -0.68 0.29 4 -0.85 0.34 5 -1.09 0.30 4 -0.10 0.38 3<br>ALGERIA DZA -1.09 0.22 8 -1.59 0.22 9 -1.74 0.23 8 -1.72 0.22 7 -1.90 0.28 5 -2.66 0.28 4 -2.92 0.34 4<br>AMERICAN SAMOA ASM 0.74 0.46 1 0.72 0.45 1 .. .. .. .. .. .. .. .. .. .. .. .. .. .. ..<br>ANDORRA ADO 1.38 0.40 2 1.40 0.37 2 1.26 0.47 1 1.18 0.43 1 .. .. .. .. .. .. .. .. ..<br>ANGOLA AGO -0.82 0.23 7 -0.90 0.23 8 -0.91 0.25 7 -1.66 0.22 7 -2.47 0.28 5 -2.18 0.27 5 -2.35 0.34 4<br>ANGUILLA AIA 1.20 0.37 2 0.77 0.45 1 .. .. .. .. .. .. .. .. .. .. .. .. .. .. ..<br>ANTIGUA AND BARBUDA ATG 0.80 0.33 3 1.13 0.32 3 0.74 0.47 1 0.68 0.43 1 .. .. .. .. .. .. .. .. ..<br>ARGENTINA ARG -0.26 0.21 10 -0.34 0.20 12 -0.25 0.22 10 -0.87 0.20 11 0.22 0.24 10 0.32 0.26 6 0.23 0.29 6<br>ARMENIA ARM -0.22 0.25 7 -0.41 0.25 6 -0.48 0.29 5 -0.76 0.28 5 -0.98 0.35 5 -0.66 0.30 4 0.19 0.40 2<br>ARUBA ABW 1.37 0.37 2 0.97 0.45 1 .. .. .. .. .. .. .. .. .. .. .. .. .. .. ..<br>AUSTRALIA AUS 0.82 0.21 10 0.79 0.20 11 0.80 0.22 10 1.05 0.21 9 1.13 0.24 8 1.06 0.26 6 1.01 0.29 6<br>AUSTRIA AUT 0.98 0.21 10 0.94 0.21 11 0.98 0.23 9 1.09 0.22 8 1.18 0.25 8 1.28 0.25 7 1.12 0.29 6<br>AZERBAIJAN AZE -1.21 0.22 8 -1.38 0.22 8 -1.52 0.24 7 -1.24 0.22 7 -0.87 0.28 6 -0.72 0.27 5 -0.62 0.36 3<br>BAHAMAS BHS 0.83 0.31 4 0.83 0.31 4 0.97 0.42 2 0.89 0.39 2 0.85 0.68 1 0.46 0.49 1 0.97 0.50 2<br>BAHRAIN BHR -0.28 0.22 8 -0.01 0.23 8 0.10 0.25 6 0.29 0.24 6 -0.10 0.28 5 -0.19 0.28 4 -0.79 0.34 4<br>BANGLADESH BGD -1.65 0.22 8 -1.10 0.22 9 -0.93 0.23 8 -0.73 0.22 8 -0.77 0.28 6 -0.52 0.28 4 -0.87 0.34 4<br>BARBADOS BRB 1.18 0.31 4 1.29 0.29 4 0.89 0.40 2 0.68 0.43 1 .. .. .. .. .. .. 0.98 0.56 1<br>BELARUS BLR 0.01 0.26 6 -0.04 0.24 7 0.16 0.27 6 0.06 0.27 5 -0.21 0.33 6 -0.33 0.30 4 -0.18 0.40 2<br>BELGIUM BEL 0.66 0.21 10 0.72 0.21 10 0.88 0.23 9 0.94 0.21 9 0.79 0.25 8 0.86 0.26 6 0.69 0.29 6<br>BELIZE BLZ 0.31 0.31 4 0.79 0.29 4 0.68 0.36 3 0.43 0.38 2 0.80 0.55 2 0.76 0.51 1 0.71 0.56 1<br>BENIN BEN 0.31 0.29 5 -0.05 0.27 5 0.30 0.32 4 0.52 0.33 3 0.05 0.50 2 0.10 0.46 2 0.98 0.56 1<br>BERMUDA BMU 0.79 0.37 2 0.86 0.37 2 0.74 0.47 1 0.68 0.43 1 .. .. .. .. .. .. .. .. ..<br>BHUTAN BTN 1.01 0.31 4 0.90 0.29 4 0.68 0.36 3 0.68 0.38 2 0.54 0.58 1 0.55 0.51 1 0.78 0.56 1<br>BOLIVIA BOL -1.15 0.22 8 -0.73 0.22 9 -0.30 0.25 7 -0.21 0.22 8 -0.63 0.28 7 -0.09 0.27 5 -0.38 0.34 4<br>BOSNIA-HERZEGOVINA BIH -0.78 0.26 6 -0.66 0.24 8 -1.03 0.28 5 -0.88 0.27 5 -0.55 0.54 3 -0.62 0.51 1 -0.64 0.56 1<br>BOTSWANA BWA 0.94 0.22 8 0.82 0.23 8 0.74 0.23 8 0.67 0.22 8 0.75 0.28 6 0.61 0.27 5 0.66 0.34 4<br>BRAZIL BRA -0.13 0.21 10 -0.13 0.20 12 0.17 0.22 10 -0.06 0.20 11 -0.03 0.24 9 -0.52 0.25 7 -0.43 0.29 6<br>BRITISH VIRGIN ISLANDS VGB 1.50 0.53 1 .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. ..<br>BRUNEI BRN 1.13 0.36 3 1.23 0.35 3 1.04 0.37 3 0.93 0.35 3 1.14 0.48 2 1.18 0.37 2 1.08 0.50 2<br>BULGARIA BGR 0.16 0.22 8 0.06 0.21 10 0.36 0.23 8 0.41 0.22 8 0.09 0.27 8 0.36 0.27 5 -0.08 0.34 4<br>BURKINA FASO BFA -0.05 0.29 5 -0.21 0.28 5 -0.20 0.33 4 -0.28 0.35 3 -0.31 0.43 3 -0.14 0.35 3 -0.41 0.50 2<br>BURUNDI BDI -1.65 0.31 4 -2.27 0.29 4 -2.10 0.36 3 -2.24 0.38 2 -2.06 0.46 3 -2.28 0.51 1 -2.00 0.56 1<br>CAMBODIA KHM -0.44 0.29 5 -0.33 0.29 4 -0.43 0.36 3 -0.37 0.35 3 -0.93 0.55 2 -1.38 0.51 1 -1.39 0.56 1<br>CAMEROON CMR -0.34 0.22 8 -0.59 0.22 8 -0.70 0.25 7 -0.54 0.24 6 -0.67 0.29 6 -0.90 0.26 6 -1.18 0.34 4<br>CANADA CAN 0.91 0.21 10 0.95 0.20 12 0.99 0.22 10 0.98 0.20 10 1.14 0.24 10 1.02 0.25 7 0.82 0.29 6<br>CAPE VERDE CPV 0.88 0.40 2 1.09 0.37 2 0.74 0.47 1 0.68 0.43 1 .. .. .. .. .. .. 0.98 0.56 1<br>CAYMAN ISLANDS CYM 1.20 0.37 2 1.29 0.37 2 0.74 0.47 1 0.68 0.43 1 .. .. .. .. .. .. .. .. ..<br>CENTRAL AFRICAN REPUBLIC CAF -1.13 0.31 4 -1.33 0.29 4 -1.48 0.36 3 -1.85 0.38 2 -0.20 0.58 1 0.07 0.51 1 -0.24 0.56 1<br>CHAD TCD -1.34 0.29 5 -1.23 0.28 5 -1.39 0.34 4 -1.66 0.35 3 -1.08 0.58 1 -1.57 0.46 2 -0.91 0.56 1<br>CHILE CHL 0.85 0.21 10 0.73 0.20 11 0.93 0.22 10 0.90 0.20 11 0.66 0.24 10 0.37 0.26 6 0.52 0.29 6<br>CHINA CHN -0.18 0.21 10 -0.15 0.20 11 -0.19 0.22 10 -0.07 0.20 10 -0.08 0.24 9 -0.11 0.26 6 -0.10 0.29 6<br>COLOMBIA COL -1.79 0.21 10 -2.02 0.21 10 -2.12 0.23 9 -2.05 0.21 10 -1.95 0.24 10 -1.64 0.25 7 -1.50 0.29 6<br>COMOROS COM -0.36 0.40 2 -0.43 0.37 2 -1.07 0.47 1 -0.31 0.43 1 .. .. .. .. .. .. 0.98 0.56 1<br>CONGO COG -1.24 0.26 6 -1.56 0.26 6 -1.66 0.31 5 -1.74 0.29 5 -1.85 0.43 3 -2.25 0.35 3 -0.93 0.50 2<br>Congo, Dem. Rep. (Zaire) ZAR -2.40 0.23 7 -2.29 0.22 8 -2.00 0.24 7 -2.41 0.26 6 -2.93 0.34 4 -3.30 0.32 3 -2.00 0.38 3<br>COSTA RICA CRI 0.76 0.22 8 0.84 0.21 10 0.87 0.23 8 0.93 0.21 9 1.04 0.27 7 0.97 0.26 6 0.66 0.32 5<br>CROATIA HRV 0.32 0.22 8 0.37 0.22 9 0.31 0.25 7 0.32 0.23 7 0.19 0.29 6 0.21 0.28 4 0.02 0.36 3<br>CUBA CUB 0.03 0.23 7 0.20 0.22 8 0.07 0.24 7 0.16 0.22 7 -0.33 0.28 5 -0.24 0.28 4 -0.28 0.34 4<br>CYPRUS CYP 0.29 0.23 7 0.28 0.23 8 0.36 0.25 6 0.30 0.23 6 0.34 0.30 4 0.26 0.28 4 0.44 0.34 4<br>CZECH REPUBLIC CZE 0.69 0.21 10 0.74 0.21 11 0.90 0.23 9 0.92 0.21 9 0.61 0.24 9 0.79 0.25 7 0.86 0.29 6<br>DENMARK DNK 0.91 0.21 10 1.02 0.20 12 1.10 0.22 10 1.14 0.21 9 1.26 0.24 9 1.17 0.26 6 1.01 0.29 6<br>DJIBOUTI DJI -0.74 0.40 2 -0.57 0.37 2 -1.07 0.47 1 -0.81 0.43 1 .. .. .. .. .. .. 0.17 0.56 1<br>DOMINICA DMA 1.00 0.33 3 1.01 0.32 3 0.48 0.47 1 0.43 0.43 1 .. .. .. .. .. .. .. .. ..<br>DOMINICAN REPUBLIC DOM 0.05 0.22 8 -0.02 0.23 8 0.11 0.25 7 0.13 0.23 7 0.05 0.28 7 -0.22 0.32 3 -0.44 0.43 3<br>ECUADOR ECU -0.83 0.22 8 -0.93 0.21 10 -0.95 0.23 8 -0.84 0.21 9 -1.20 0.26 8 -0.65 0.26 6 -0.85 0.30 5<br>EGYPT EGY -0.90 0.21 9 -0.87 0.21 10 -0.72 0.22 9 -0.64 0.21 8 -0.17 0.26 8 -0.33 0.26 6 -0.64 0.29 6<br>EL SALVADOR SLV -0.14 0.25 7 -0.17 0.24 7 -0.24 0.27 6 0.14 0.25 7 0.27 0.32 6 0.13 0.30 4 -0.33 0.38 4<br>EQUATORIAL GUINEA GNQ 0.21 0.35 3 0.26 0.32 3 0.33 0.40 2 0.11 0.38 2 .. .. .. .. .. .. -0.64 0.56 1<br>ERITREA ERI -0.72 0.31 4 -0.55 0.27 5 -0.43 0.32 4 -0.38 0.33 3 -0.29 0.50 2 -0.42 0.51 1 0.23 0.56 1<br>ESTONIA EST 0.68 0.22 9 0.92 0.21 11 1.04 0.23 9 0.89 0.21 9 0.64 0.25 9 0.74 0.27 5 0.60 0.36 3<br>ETHIOPIA ETH -1.48 0.25 7 -1.21 0.23 8 -1.24 0.26 7 -1.32 0.29 5 -1.27 0.42 4 -0.84 0.35 3 -0.90 0.50 2<br>FIJI FJI 0.29 0.33 3 0.22 0.30 4 0.19 0.35 3 0.10 0.33 3 -0.22 0.50 2 0.58 0.46 2 0.71 0.56 1<br>FINLAND FIN 1.48 0.21 10 1.61 0.21 11 1.65 0.23 9 1.54 0.21 9 1.51 0.24 9 1.32 0.26 6 1.22 0.29 6<br>FRANCE FRA 0.33 0.21 10 0.28 0.20 12 0.36 0.22 10 0.60 0.20 10 0.94 0.24 10 0.70 0.25 7 0.82 0.29 6<br>FRENCH GUIANA GUF 0.21 0.46 1 0.17 0.45 1 0.23 0.47 1 0.18 0.43 1 .. .. .. .. .. .. .. .. ..<br>FRENCH POLYNESIA PYF 0.65 0.53 1 .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. ..<br>GABON GAB 0.22 0.23 7 0.18 0.23 7 -0.03 0.25 6 0.13 0.24 6 -0.45 0.28 5 -0.40 0.32 3 -0.43 0.43 3<br>GAMBIA GMB 0.18 0.34 4 0.24 0.31 5 0.41 0.32 5 0.45 0.31 4 0.27 0.48 2 0.55 0.37 2 -0.03 0.50 2<br>GEORGIA GEO -0.80 0.26 6 -1.19 0.24 8 -1.90 0.28 5 -1.83 0.27 5 -0.99 0.36 5 -1.01 0.36 3 -0.95 0.40 2<br>GERMANY DEU 0.67 0.21 10 0.65 0.20 12 0.66 0.22 10 0.89 0.20 10 1.14 0.24 10 1.18 0.25 7 1.07 0.29 6<br><!-- End of picture text --> 92
<!-- Start of picture text --> TABLE C2: Political Stability (cont.)<br>2005 2004 2003 2002 2000 1998 1996<br>Country Code Est. S.E. N. Est. S.E. N. Est. S.E. N. Est. S.E. N. Est. S.E. N. Est. S.E. N. Est. S.E. N.<br>GHANA GHA 0.16 0.22 8 0.03 0.21 10 -0.04 0.23 8 -0.08 0.22 7 -0.15 0.29 6 -0.05 0.26 6 -0.11 0.34 4<br>GREECE GRC 0.35 0.21 10 0.35 0.21 11 0.59 0.23 9 0.61 0.21 9 0.65 0.25 7 0.24 0.26 6 0.16 0.29 6<br>GREENLAND GRL 1.50 0.53 1 .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. ..<br>GRENADA GRD 0.49 0.33 3 0.91 0.32 3 0.48 0.47 1 0.43 0.43 1 .. .. .. .. .. .. 0.98 0.56 1<br>GUADELOUPE GLP 1.50 0.53 1 .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. ..<br>GUAM GUM 0.74 0.46 1 0.62 0.45 1 .. .. .. .. .. .. .. .. .. .. .. .. .. .. ..<br>GUATEMALA GTM -0.89 0.25 7 -0.78 0.23 9 -0.77 0.26 7 -0.57 0.23 8 -1.03 0.32 6 -0.83 0.30 4 -1.40 0.38 4<br>GUINEA GIN -1.11 0.29 5 -0.85 0.28 5 -0.80 0.33 4 -1.46 0.32 4 -1.44 0.48 2 -0.84 0.35 3 -1.53 0.50 2<br>GUINEA-BISSAU GNB -0.51 0.36 3 -0.43 0.31 4 -0.40 0.33 4 -0.58 0.31 4 -1.11 0.43 3 -1.12 0.35 3 -0.79 0.50 2<br>GUYANA GUY -0.38 0.28 6 -0.33 0.28 5 -0.34 0.33 4 -0.48 0.35 3 -0.51 0.43 3 -0.11 0.37 2 -0.05 0.50 2<br>HAITI HTI -1.91 0.29 5 -1.71 0.26 6 -1.15 0.29 6 -1.36 0.29 5 -0.90 0.42 4 -1.48 0.37 2 -0.49 0.50 2<br>HONDURAS HND -0.78 0.25 7 -0.51 0.23 8 -0.45 0.26 7 -0.24 0.23 8 0.04 0.32 6 -0.14 0.30 4 -0.59 0.38 4<br>HONG KONG HKG 1.19 0.23 8 1.20 0.23 9 0.97 0.25 7 0.91 0.23 7 0.99 0.28 6 0.64 0.29 5 0.08 0.37 4<br>HUNGARY HUN 0.79 0.21 10 0.83 0.20 11 0.99 0.22 10 0.97 0.20 10 0.54 0.24 10 1.04 0.25 7 0.54 0.29 6<br>ICELAND ISL 1.58 0.27 7 1.69 0.26 8 1.65 0.30 6 1.46 0.30 5 1.46 0.37 5 1.15 0.35 3 1.01 0.43 3<br>INDIA IND -0.85 0.21 10 -1.09 0.20 12 -1.19 0.22 10 -1.02 0.20 10 -0.65 0.24 9 -0.73 0.25 7 -1.03 0.29 6<br>INDONESIA IDN -1.42 0.21 10 -1.60 0.20 12 -1.94 0.22 10 -1.57 0.20 10 -2.01 0.24 9 -1.57 0.26 6 -0.66 0.29 6<br>IRAN IRN -1.14 0.22 8 -0.98 0.21 9 -1.05 0.23 8 -0.80 0.21 8 -0.51 0.26 6 -0.49 0.27 5 -0.63 0.30 5<br>IRAQ IRQ -2.82 0.23 7 -3.05 0.24 6 -2.30 0.25 6 -1.80 0.24 6 -2.26 0.28 5 -2.89 0.28 4 -3.06 0.34 4<br>IRELAND IRL 1.08 0.21 10 1.07 0.20 12 1.22 0.22 10 1.19 0.21 9 1.17 0.24 9 1.29 0.25 7 0.99 0.29 6<br>ISRAEL ISR -1.16 0.22 9 -1.29 0.21 11 -1.42 0.23 9 -1.55 0.21 9 -0.82 0.26 7 -0.90 0.27 5 -0.70 0.29 6<br>ITALY ITA 0.21 0.21 10 0.18 0.21 11 0.39 0.23 9 0.71 0.21 9 0.64 0.24 10 0.80 0.25 7 0.47 0.29 6<br>IVORY COAST CIV -2.49 0.23 7 -2.21 0.22 8 -2.10 0.24 7 -2.10 0.22 7 -1.02 0.29 5 -0.25 0.26 6 0.02 0.34 4<br>JAMAICA JAM -0.33 0.25 7 -0.27 0.24 7 -0.37 0.27 6 -0.33 0.25 6 0.17 0.34 4 -0.08 0.31 4 0.43 0.43 3<br>JAPAN JPN 0.94 0.21 10 0.90 0.20 12 1.14 0.22 10 1.08 0.20 10 1.06 0.24 9 0.96 0.28 5 0.82 0.29 6<br>JORDAN JOR -0.31 0.22 9 -0.30 0.22 9 -0.32 0.24 8 -0.45 0.23 7 0.05 0.28 6 -0.15 0.26 6 0.18 0.32 5<br>KAZAKHSTAN KAZ 0.03 0.21 9 -0.01 0.21 9 0.24 0.23 8 0.25 0.21 8 0.09 0.26 8 0.10 0.26 6 -0.28 0.32 4<br>KENYA KEN -1.16 0.22 8 -1.07 0.21 10 -1.10 0.23 8 -1.11 0.22 7 -1.15 0.28 6 -1.03 0.26 6 -0.65 0.34 4<br>KIRIBATI KIR 1.38 0.40 2 0.92 0.37 2 .. .. .. .. .. .. .. .. .. .. .. .. .. .. ..<br>KOREA, NORTH PRK -0.12 0.30 4 0.04 0.27 5 0.10 0.28 5 0.52 0.31 4 -1.07 0.43 3 -1.30 0.37 2 -1.64 0.50 2<br>KOREA, SOUTH KOR 0.43 0.21 10 0.44 0.20 12 0.23 0.22 10 0.32 0.20 10 0.20 0.24 9 -0.06 0.25 7 -0.08 0.29 6<br>KUWAIT KWT 0.11 0.22 8 0.14 0.22 8 0.01 0.24 7 0.11 0.22 7 0.52 0.30 4 0.45 0.28 4 -0.01 0.34 4<br>KYRGYZ REPUBLIC KGZ -1.21 0.26 6 -1.18 0.25 6 -1.34 0.28 5 -1.23 0.27 5 -0.29 0.39 3 0.51 0.36 3 0.54 0.40 2<br>LAOS LAO -0.27 0.27 5 -0.76 0.29 4 -0.80 0.36 3 -0.28 0.35 3 -0.11 0.50 2 0.41 0.51 1 0.98 0.56 1<br>LATVIA LVA 0.83 0.22 8 0.89 0.22 9 1.05 0.25 7 0.80 0.23 7 0.48 0.29 6 0.27 0.27 5 0.54 0.36 3<br>LEBANON LBN -1.14 0.23 7 -0.90 0.23 7 -0.77 0.25 6 -0.75 0.24 6 -0.77 0.28 5 -0.90 0.28 4 -0.60 0.34 4<br>LESOTHO LSO 0.31 0.29 4 0.34 0.28 4 0.24 0.30 4 -0.15 0.31 3 0.81 0.58 1 -0.04 0.45 2 0.78 0.56 1<br>LIBERIA LBR -1.45 0.31 4 -2.16 0.28 5 -2.35 0.33 4 -2.32 0.31 4 -1.80 0.43 3 -1.50 0.37 2 -2.71 0.50 2<br>LIBYA LBY 0.30 0.23 7 0.09 0.24 6 -0.14 0.25 6 -0.46 0.24 6 -0.69 0.30 4 -1.51 0.28 4 -1.78 0.34 4<br>LIECHTENSTEIN LIE 1.38 0.40 2 1.50 0.37 2 1.26 0.47 1 1.18 0.43 1 .. .. .. .. .. .. .. .. ..<br>LITHUANIA LTU 0.88 0.22 8 0.85 0.21 10 1.11 0.23 8 0.90 0.22 8 0.25 0.27 8 0.27 0.27 5 0.44 0.36 3<br>LUXEMBOURG LUX 1.41 0.27 7 1.50 0.26 8 1.62 0.30 6 1.58 0.30 5 1.52 0.39 4 1.41 0.35 3 1.23 0.43 3<br>MACAO MAC 1.27 0.46 1 1.32 0.45 1 1.00 0.47 1 0.43 0.43 1 .. .. .. .. .. .. .. .. ..<br>MACEDONIA MKD -1.04 0.23 7 -1.07 0.23 8 -1.13 0.25 6 -1.05 0.26 4 -1.04 0.38 3 -0.52 0.37 3 0.03 0.47 2<br>MADAGASCAR MDG 0.18 0.28 6 0.08 0.27 6 0.16 0.32 5 0.11 0.35 3 0.09 0.42 4 -0.19 0.35 3 -0.07 0.50 2<br>MALAWI MWI 0.15 0.25 7 -0.14 0.24 7 -0.26 0.27 6 -0.03 0.27 5 -0.09 0.33 5 -0.06 0.29 5 -0.16 0.43 3<br>MALAYSIA MYS 0.49 0.21 10 0.24 0.20 12 0.32 0.22 10 0.24 0.20 10 0.15 0.24 10 0.18 0.25 7 0.77 0.29 6<br>MALDIVES MDV 0.76 0.33 3 0.52 0.32 3 1.00 0.47 1 1.18 0.43 1 .. .. .. .. .. .. 0.17 0.56 1<br>MALI MLI 0.06 0.28 6 -0.03 0.25 7 -0.17 0.29 6 -0.26 0.29 5 0.21 0.43 3 0.13 0.35 3 0.45 0.50 2<br>MALTA MLT 1.34 0.28 6 1.34 0.27 6 1.40 0.35 4 1.36 0.39 2 1.00 0.68 1 1.16 0.49 1 1.13 0.50 2<br>MARSHALL ISLANDS MHL 1.10 0.62 1 0.62 0.54 1 .. .. .. .. .. .. .. .. .. .. .. .. .. .. ..<br>MARTINIQUE MTQ 1.20 0.37 2 1.31 0.37 2 0.74 0.47 1 0.43 0.43 1 .. .. .. .. .. .. .. .. ..<br>MAURITANIA MRT -0.31 0.31 4 -0.18 0.29 4 -0.11 0.36 3 0.17 0.38 2 -0.57 0.50 2 0.34 0.51 1 0.51 0.56 1<br>MAURITIUS MUS 0.90 0.30 4 0.89 0.30 4 0.75 0.30 4 0.97 0.30 3 0.97 0.40 3 0.88 0.34 4 0.92 0.47 2<br>MEXICO MEX -0.29 0.21 10 -0.09 0.20 12 -0.10 0.22 10 0.10 0.20 11 -0.28 0.24 10 -0.56 0.25 7 -0.66 0.29 6<br>MICRONESIA FSM 1.08 0.33 3 0.95 0.32 3 .. .. .. .. .. .. .. .. .. .. .. .. .. .. ..<br>MOLDOVA MDA -0.65 0.24 7 -0.36 0.24 7 -0.21 0.25 6 -0.15 0.25 5 -0.29 0.28 6 -0.05 0.27 5 -0.37 0.36 3<br>MONACO MCO 0.99 0.44 2 1.09 0.42 2 .. .. .. .. .. .. .. .. .. .. .. .. .. .. ..<br>MONGOLIA MNG 0.92 0.28 6 0.72 0.26 6 0.88 0.31 5 0.84 0.31 4 0.96 0.43 3 0.39 0.37 2 0.54 0.50 2<br>MOROCCO MAR -0.43 0.22 8 -0.39 0.22 9 -0.35 0.23 8 -0.30 0.22 8 -0.08 0.30 4 -0.10 0.26 6 -0.60 0.30 5<br>MOZAMBIQUE MOZ 0.04 0.25 7 0.08 0.23 8 0.31 0.26 7 0.47 0.29 5 -0.33 0.43 3 -0.65 0.33 4 -0.59 0.50 2<br>MYANMAR MMR -1.00 0.23 7 -1.01 0.22 8 -1.24 0.24 7 -1.39 0.22 7 -1.71 0.28 5 -1.34 0.28 4 -1.29 0.34 4<br>NAMIBIA NAM 0.50 0.22 8 0.52 0.22 9 0.28 0.23 8 0.30 0.22 8 -0.77 0.33 5 0.08 0.30 4 0.62 0.43 3<br>NAURU NRU 1.10 0.62 1 0.62 0.54 1 .. .. .. .. .. .. .. .. .. .. .. .. .. .. ..<br>NEPAL NPL -2.36 0.24 6 -2.01 0.24 6 -1.92 0.27 5 -1.76 0.31 4 -1.33 0.50 2 -0.83 0.51 1 -0.58 0.56 1<br>NETHERLANDS NLD 0.80 0.21 10 0.92 0.21 11 1.13 0.23 9 1.17 0.21 9 1.41 0.24 9 1.42 0.26 6 1.27 0.29 6<br>NETHERLANDS ANTILLES ANT 0.86 0.37 2 0.67 0.45 1 .. .. .. .. .. .. .. .. .. .. .. .. .. .. ..<br>NEW CALEDONIA NCL -0.21 0.53 1 .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. -0.93 0.76 1<br>NEW ZEALAND NZL 1.20 0.22 9 1.43 0.22 9 1.24 0.24 8 1.23 0.23 7 1.12 0.26 7 1.28 0.27 5 1.07 0.32 5<br>NICARAGUA NIC -0.16 0.25 7 -0.20 0.23 8 -0.11 0.26 7 -0.06 0.23 8 0.03 0.32 6 -0.40 0.30 4 -0.86 0.38 4<br>NIGER NER -0.56 0.29 5 -0.49 0.28 5 -0.22 0.33 4 -0.38 0.35 3 -0.25 0.43 3 -0.25 0.37 2 -0.25 0.50 2<br><!-- End of picture text --> 93
<!-- Start of picture text --> TABLE C2: Political Stability (cont.)<br>2005 2004 2003 2002 2000 1998 1996<br>Country Code Est. S.E. N. Est. S.E. N. Est. S.E. N. Est. S.E. N. Est. S.E. N. Est. S.E. N. Est. S.E. N.<br>NIGERIA NGA -1.77 0.22 8 -1.78 0.21 10 -1.65 0.23 8 -1.69 0.22 8 -1.64 0.27 8 -1.15 0.26 6 -1.75 0.30 5<br>NORWAY NOR 1.22 0.21 10 1.30 0.21 11 1.36 0.23 9 1.37 0.22 8 1.22 0.25 8 1.24 0.26 6 1.23 0.29 6<br>OMAN OMN 0.82 0.23 7 0.82 0.22 8 0.94 0.24 7 0.95 0.22 7 0.89 0.28 5 0.71 0.28 4 0.55 0.34 4<br>PALAU PCI 1.10 0.62 1 0.62 0.54 1 .. .. .. .. .. .. .. .. .. .. .. .. .. .. ..<br>PAKISTAN PAK -1.68 0.21 9 -1.67 0.21 10 -1.58 0.23 8 -1.51 0.22 7 -0.88 0.27 7 -1.21 0.26 6 -1.41 0.30 5<br>PANAMA PAN -0.05 0.22 8 0.18 0.22 9 0.25 0.23 8 0.23 0.21 9 0.40 0.27 7 0.09 0.28 4 0.13 0.34 4<br>PAPUA NEW GUINEA PNG -0.81 0.23 7 -0.70 0.22 8 -0.92 0.24 7 -0.85 0.23 6 -0.66 0.28 5 -0.63 0.32 3 -1.41 0.43 3<br>PARAGUAY PRY -0.62 0.25 7 -0.68 0.23 8 -0.87 0.26 7 -1.32 0.23 8 -1.02 0.33 5 -0.56 0.31 4 -0.26 0.43 3<br>PERU PER -1.08 0.21 9 -0.89 0.20 11 -0.84 0.22 9 -0.86 0.20 10 -0.61 0.25 9 -0.60 0.25 7 -1.08 0.29 6<br>PHILIPPINES PHL -1.11 0.21 10 -1.23 0.20 12 -1.22 0.22 10 -0.75 0.20 10 -0.59 0.24 10 -0.12 0.26 6 -0.33 0.29 6<br>POLAND POL 0.23 0.21 10 0.28 0.20 12 0.61 0.22 10 0.57 0.20 10 0.56 0.24 10 0.61 0.25 7 0.40 0.29 6<br>PORTUGAL PRT 0.94 0.21 10 0.83 0.21 11 1.10 0.23 9 1.24 0.22 8 1.25 0.25 8 1.28 0.25 7 1.08 0.29 6<br>PUERTO RICO PRI 0.72 0.28 4 0.84 0.28 4 0.69 0.33 3 0.49 0.33 2 0.70 0.49 1 0.63 0.51 1 0.58 0.51 1<br>QATAR QAT 0.83 0.22 8 0.97 0.23 7 0.95 0.27 5 0.72 0.26 4 1.31 0.31 4 1.16 0.32 3 0.76 0.34 4<br>REUNION REU 0.48 0.46 1 0.42 0.45 1 .. .. .. .. .. .. .. .. .. .. .. .. .. .. ..<br>ROMANIA ROM 0.03 0.21 10 0.15 0.21 11 0.24 0.23 9 0.22 0.22 8 -0.18 0.27 8 0.10 0.28 4 0.31 0.34 4<br>RUSSIA RUS -1.07 0.21 10 -1.02 0.20 12 -0.64 0.22 10 -0.60 0.20 10 -0.74 0.24 10 -0.68 0.25 7 -1.17 0.29 6<br>RWANDA RWA -1.21 0.40 2 -1.08 0.33 3 -1.09 0.35 3 -1.55 0.33 3 -1.76 0.50 2 -2.28 0.51 1 -1.46 0.56 1<br>SAMOA SAM 1.10 0.33 3 1.04 0.32 3 1.00 0.47 1 0.68 0.43 1 .. .. .. .. .. .. .. .. ..<br>SAN MARINO SMR 1.10 0.62 1 1.19 0.54 1 .. .. .. .. .. .. .. .. .. .. .. .. .. .. ..<br>SAO TOME AND PRINCIPE STP 0.61 0.40 2 0.34 0.37 2 -0.03 0.47 1 0.43 0.43 1 .. .. .. .. .. .. 0.98 0.56 1<br>SAUDI ARABIA SAU -0.70 0.22 8 -0.82 0.21 9 -0.39 0.23 8 -0.26 0.21 8 0.26 0.26 6 -0.12 0.27 5 -0.48 0.30 5<br>SENEGAL SEN -0.07 0.26 6 -0.18 0.24 7 -0.38 0.26 7 -0.34 0.25 6 -0.80 0.33 5 -1.24 0.31 4 -0.78 0.43 3<br>SEYCHELLES SYC 0.84 0.31 4 0.64 0.29 4 0.52 0.40 2 0.93 0.43 1 .. .. .. .. .. .. 0.98 0.56 1<br>SIERRA LEONE SLE -0.48 0.31 4 -0.76 0.28 5 -1.01 0.33 4 -1.43 0.31 4 -1.76 0.43 3 -2.32 0.37 2 -2.47 0.50 2<br>SINGAPORE SGP 1.08 0.21 10 1.15 0.21 11 0.88 0.23 9 1.15 0.21 9 1.33 0.24 9 1.04 0.25 7 1.17 0.29 6<br>SLOVAK REPUBLIC SVK 0.69 0.22 9 0.64 0.22 9 0.94 0.24 8 0.86 0.22 8 0.49 0.26 8 0.85 0.26 6 0.36 0.32 5<br>SLOVENIA SVN 0.94 0.22 9 0.99 0.21 10 1.13 0.23 9 1.19 0.21 9 0.80 0.25 8 0.99 0.28 4 0.88 0.36 3<br>SOLOMON ISLANDS SLB -0.05 0.40 2 -0.39 0.37 2 .. .. .. .. .. .. .. .. .. .. .. .. 0.98 0.56 1<br>SOMALIA SOM -2.51 0.31 4 -2.65 0.31 4 -2.36 0.33 4 -2.10 0.31 4 -1.82 0.43 3 -2.35 0.37 2 -2.40 0.50 2<br>SOUTH AFRICA ZAF -0.10 0.21 10 -0.24 0.20 12 -0.25 0.22 10 -0.35 0.20 10 -0.31 0.24 10 -0.96 0.25 7 -1.17 0.29 6<br>SPAIN ESP 0.38 0.21 10 0.10 0.20 12 0.34 0.22 10 0.52 0.20 10 0.89 0.24 10 0.59 0.25 7 0.37 0.29 6<br>SRI LANKA LKA -1.25 0.22 8 -1.14 0.22 9 -1.02 0.23 8 -1.08 0.22 8 -1.93 0.28 6 -1.70 0.28 4 -1.91 0.34 4<br>ST. KITTS AND NEVIS KNA 1.29 0.33 3 1.41 0.32 3 .. .. .. .. .. .. .. .. .. .. .. .. .. .. ..<br>ST. LUCIA LCA 1.10 0.33 3 1.45 0.32 3 .. .. .. .. .. .. .. .. .. .. .. .. 0.98 0.56 1<br>ST. VINCENT AND THE GRENADINES VCT 1.14 0.33 3 1.35 0.32 3 .. .. .. .. .. .. .. .. .. .. .. .. 0.98 0.56 1<br>SUDAN SDN -2.05 0.23 7 -2.01 0.23 7 -2.21 0.24 7 -2.07 0.22 7 -2.53 0.28 5 -2.16 0.32 3 -2.82 0.43 3<br>SURINAME SUR 0.26 0.33 4 0.55 0.31 4 0.45 0.37 3 0.38 0.39 2 -0.06 0.68 1 -0.11 0.49 1 0.43 0.50 2<br>SWAZILAND SWZ -0.04 0.29 4 0.17 0.28 4 -0.08 0.30 4 0.12 0.31 3 0.34 0.58 1 -0.52 0.45 2 -0.04 0.56 1<br>SWEDEN SWE 1.18 0.21 10 1.23 0.20 11 1.49 0.22 10 1.25 0.21 9 1.29 0.24 10 1.28 0.26 6 1.17 0.29 6<br>SWITZERLAND CHE 1.26 0.21 10 1.29 0.21 11 1.53 0.23 9 1.44 0.22 8 1.52 0.24 9 1.52 0.25 7 1.39 0.29 6<br>SYRIA SYR -0.91 0.23 7 -0.64 0.22 8 -0.47 0.24 7 -0.33 0.22 7 -0.66 0.28 5 -0.42 0.28 4 -0.74 0.34 4<br>TAIWAN TWN 0.53 0.21 10 0.50 0.20 12 0.67 0.22 10 0.67 0.20 10 0.47 0.24 9 0.78 0.26 6 0.81 0.29 6<br>TAJIKISTAN TJK -1.35 0.26 6 -1.30 0.25 6 -1.48 0.28 5 -1.30 0.27 5 -1.63 0.37 3 -1.78 0.39 2 -2.80 0.40 2<br>TANZANIA TZA -0.37 0.22 8 -0.53 0.22 9 -0.51 0.23 8 -0.35 0.22 7 -0.52 0.28 6 0.11 0.26 6 -0.20 0.34 4<br>THAILAND THA -0.55 0.21 10 -0.38 0.20 11 0.14 0.22 10 0.31 0.20 10 0.03 0.24 9 0.17 0.25 7 -0.06 0.29 6<br>TIMOR, EAST TMP -0.69 0.31 4 -0.30 0.32 3 -0.55 0.47 1 -1.06 0.43 1 .. .. .. .. .. .. .. .. ..<br>TOGO TGO -1.22 0.29 5 -0.34 0.28 5 -0.46 0.33 4 0.03 0.35 3 -0.54 0.48 2 -1.13 0.35 3 -0.72 0.50 2<br>TONGA TON 0.53 0.33 3 0.80 0.32 3 .. .. .. .. .. .. .. .. .. .. .. .. .. .. ..<br>TRINIDAD AND TOBAGO TTO -0.05 0.22 8 0.06 0.24 7 -0.05 0.27 6 -0.05 0.27 5 0.33 0.33 5 0.65 0.32 3 0.45 0.43 3<br>TUNISIA TUN 0.12 0.22 8 0.11 0.22 9 0.16 0.23 8 0.17 0.22 8 0.59 0.28 6 0.28 0.27 5 0.04 0.34 4<br>TURKEY TUR -0.54 0.21 10 -0.78 0.20 12 -0.81 0.22 10 -0.86 0.20 10 -1.26 0.24 10 -1.19 0.25 7 -1.40 0.29 6<br>TURKMENISTAN TKM -0.34 0.27 5 -0.62 0.26 5 -0.60 0.30 4 -0.32 0.29 4 -0.10 0.40 2 -0.01 0.39 2 0.15 0.40 2<br>TURKS AND CAICOS ISLANDS TCA 1.50 0.53 1 .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. ..<br>TUVALU TUV 1.38 0.40 2 1.02 0.37 2 .. .. .. .. .. .. .. .. .. .. .. .. .. .. ..<br>UGANDA UGA -1.32 0.22 8 -1.32 0.22 9 -1.48 0.23 8 -1.60 0.22 7 -1.51 0.28 6 -1.21 0.26 6 -1.35 0.34 4<br>UKRAINE UKR -0.39 0.21 9 -0.32 0.20 11 -0.14 0.22 9 -0.06 0.21 9 -0.70 0.26 8 -0.38 0.25 7 -0.45 0.30 5<br>UNITED ARAB EMIRATES ARE 0.61 0.22 8 0.77 0.23 8 0.85 0.25 6 0.82 0.24 6 0.91 0.30 4 0.68 0.28 4 0.73 0.34 4<br>UNITED KINGDOM GBR 0.34 0.21 10 0.36 0.20 12 0.53 0.22 10 0.61 0.20 10 0.98 0.24 10 0.73 0.25 7 0.82 0.29 6<br>UNITED STATES USA 0.06 0.21 10 0.12 0.21 11 0.20 0.23 9 0.13 0.21 9 1.08 0.24 9 0.88 0.25 7 0.82 0.29 6<br>URUGUAY URY 0.64 0.22 8 0.43 0.22 9 0.65 0.25 7 0.67 0.22 8 0.88 0.28 7 0.57 0.28 4 0.62 0.34 4<br>UZBEKISTAN UZB -1.91 0.24 6 -1.41 0.22 7 -1.39 0.25 6 -1.15 0.23 6 -1.24 0.30 5 -0.48 0.31 4 -0.16 0.36 3<br>VANUATU VUT 1.27 0.40 2 0.72 0.37 2 .. .. .. .. .. .. .. .. .. .. .. .. 0.98 0.56 1<br>VENEZUELA VEN -1.22 0.21 10 -1.13 0.20 12 -1.28 0.22 10 -1.35 0.20 11 -0.67 0.25 8 -0.47 0.25 7 -0.88 0.29 6<br>VIETNAM VNM 0.34 0.21 9 0.24 0.21 10 0.32 0.22 9 0.35 0.21 9 0.23 0.26 7 0.35 0.26 6 0.17 0.29 6<br>VIRGIN ISLANDS (U.S.) VIR 0.52 0.37 2 0.82 0.45 1 .. .. .. .. .. .. .. .. .. .. .. .. .. .. ..<br>WEST BANK WBG -1.69 0.35 3 -1.62 0.32 3 -1.65 0.40 2 -1.92 0.38 2 -0.67 0.93 1 -0.02 0.73 1 .. .. ..<br>YEMEN YEM -1.61 0.26 6 -1.49 0.24 7 -1.49 0.26 6 -1.53 0.25 6 -1.18 0.33 4 -1.50 0.32 3 -1.09 0.43 3<br>YUGOSLAVIA YUG -0.91 0.22 8 -0.89 0.23 8 -0.90 0.25 7 -1.03 0.24 6 -1.33 0.35 3 -2.01 0.32 3 -1.29 0.43 3<br>ZAMBIA ZMB 0.02 0.23 7 0.05 0.22 9 -0.07 0.23 8 -0.24 0.22 7 -0.73 0.28 6 -0.37 0.26 6 -0.66 0.34 4<br>ZIMBABWE ZWE -1.58 0.22 8 -1.60 0.23 8 -1.77 0.25 7 -1.71 0.23 7 -1.50 0.29 6 -0.71 0.26 6 -0.38 0.32 5<br><!-- End of picture text --> 94
# **TABLE C3: Government Effectiveness**

<!-- Start of picture text --> 2005 2004 2003 2002 2000 1998 1996<br>Country Code Est. S.E. N. Est. S.E. N. Est. S.E. N. Est. S.E. N. Est. S.E. N. Est. S.E. N. Est. S.E. N.<br>AFGHANISTAN AFG -1.20 0.20 5 -1.19 0.20 6 -1.06 0.21 5 -1.47 0.26 4 -1.34 0.49 1 .. .. .. .. .. ..<br>ALBANIA ALB -0.49 0.15 9 -0.26 0.16 8 -0.42 0.17 7 -0.48 0.17 7 -0.72 0.24 6 -0.63 0.29 5 -0.49 0.26 4<br>ALGERIA DZA -0.37 0.16 10 -0.52 0.16 11 -0.46 0.17 10 -0.59 0.17 9 -0.73 0.21 6 -1.10 0.31 4 -0.60 0.21 4<br>AMERICAN SAMOA ASM 0.21 0.27 1 -0.20 0.39 1 .. .. .. .. .. .. .. .. .. .. .. .. .. .. ..<br>ANDORRA ADO 1.29 0.26 2 1.32 0.38 2 1.25 0.34 2 1.30 0.32 2 .. .. .. .. .. .. .. .. ..<br>ANGOLA AGO -0.96 0.17 9 -1.14 0.17 10 -1.05 0.18 9 -1.23 0.17 9 -1.86 0.21 6 -1.83 0.29 5 -1.33 0.21 4<br>ANGUILLA AIA 1.56 0.27 1 0.96 0.39 1 .. .. .. .. .. .. .. .. .. .. .. .. .. .. ..<br>ANTIGUA AND BARBUDA ATG 0.48 0.26 2 0.43 0.38 2 0.47 0.34 2 0.49 0.32 2 .. .. .. .. .. .. .. .. ..<br>ARGENTINA ARG -0.27 0.15 12 -0.24 0.16 13 -0.37 0.16 11 -0.40 0.15 12 0.36 0.19 10 0.34 0.26 7 0.65 0.19 7<br>ARMENIA ARM -0.17 0.15 10 -0.27 0.15 9 -0.34 0.16 8 -0.37 0.17 8 -0.79 0.25 6 -0.57 0.29 5 -0.39 0.27 3<br>ARUBA ABW 1.29 0.27 1 1.17 0.39 1 .. .. .. .. .. .. .. .. .. .. .. .. .. .. ..<br>AUSTRALIA AUS 1.88 0.16 9 1.97 0.17 10 2.01 0.17 10 1.89 0.16 9 1.89 0.21 7 1.85 0.31 6 2.00 0.21 6<br>AUSTRIA AUT 1.60 0.16 9 1.76 0.18 9 1.84 0.18 9 1.89 0.17 8 1.78 0.22 7 1.55 0.29 7 1.99 0.21 6<br>AZERBAIJAN AZE -0.73 0.13 12 -0.83 0.13 12 -0.79 0.14 11 -0.98 0.14 11 -0.95 0.18 8 -0.86 0.26 6 -1.17 0.19 4<br>BAHAMAS BHS 1.28 0.25 3 1.11 0.32 3 1.22 0.30 3 1.23 0.28 3 0.73 0.56 1 0.65 0.90 1 0.43 0.66 1<br>BAHRAIN BHR 0.42 0.17 8 0.60 0.18 8 0.62 0.21 6 0.70 0.18 7 0.59 0.25 4 0.33 0.40 3 0.61 0.23 3<br>BANGLADESH BGD -0.90 0.15 10 -0.75 0.16 11 -0.61 0.17 10 -0.63 0.17 10 -0.49 0.20 7 -0.44 0.31 4 -0.77 0.21 4<br>BARBADOS BRB 1.17 0.25 3 1.07 0.34 3 1.22 0.32 3 1.30 0.32 2 .. .. .. .. .. .. .. .. ..<br>BELARUS BLR -1.19 0.16 9 -1.09 0.15 10 -1.05 0.16 9 -1.12 0.16 8 -0.99 0.24 7 -0.90 0.29 5 -1.30 0.27 3<br>BELGIUM BEL 1.65 0.16 9 1.77 0.18 9 1.80 0.18 9 1.93 0.17 9 1.56 0.22 7 1.12 0.31 6 1.93 0.21 6<br>BELIZE BLZ 0.13 0.23 4 0.06 0.30 4 0.13 0.27 4 -0.02 0.28 3 -0.36 0.40 2 -0.59 0.47 1 -0.39 0.47 1<br>BENIN BEN -0.69 0.17 8 -0.33 0.22 7 -0.42 0.23 6 -0.53 0.24 5 -0.03 0.32 3 -0.23 0.41 2 -0.02 0.47 1<br>BERMUDA BMU 1.02 0.27 1 1.05 0.39 1 1.05 0.35 1 1.11 0.33 1 .. .. .. .. .. .. .. .. ..<br>BHUTAN BTN 0.33 0.21 5 0.14 0.27 5 0.58 0.25 5 0.71 0.27 4 0.71 0.31 2 0.14 0.47 1 0.25 0.47 1<br>BOLIVIA BOL -0.80 0.16 10 -0.52 0.17 10 -0.30 0.18 8 -0.51 0.17 9 -0.31 0.21 7 -0.11 0.27 6 -0.62 0.21 4<br>BOSNIA-HERZEGOVINA BIH -0.53 0.15 9 -0.55 0.15 10 -0.70 0.16 8 -0.88 0.17 8 -0.54 0.32 4 -0.86 0.36 2 .. .. ..<br>BOTSWANA BWA 0.79 0.15 11 0.85 0.15 12 0.72 0.16 11 0.85 0.16 11 0.84 0.21 7 0.58 0.29 5 0.45 0.21 4<br>BRAZIL BRA -0.09 0.15 12 0.08 0.16 13 0.06 0.16 11 -0.11 0.15 12 -0.13 0.19 9 -0.08 0.25 8 -0.25 0.19 7<br>BRUNEI BRN 0.56 0.25 3 0.09 0.32 3 0.67 0.30 3 0.80 0.28 3 0.73 0.56 1 0.04 0.90 1 1.09 0.66 1<br>BULGARIA BGR 0.23 0.14 11 0.00 0.13 12 -0.07 0.14 11 0.00 0.14 11 -0.12 0.19 9 -1.03 0.26 6 -0.64 0.18 5<br>BURKINA FASO BFA -0.60 0.19 7 -0.60 0.22 7 -0.61 0.23 6 -0.66 0.24 5 -0.38 0.29 4 -0.26 0.38 3 -0.71 0.40 2<br>BURUNDI BDI -1.34 0.20 6 -1.33 0.24 6 -1.32 0.25 5 -1.52 0.26 4 -1.28 0.28 4 -1.02 0.47 1 -0.98 0.47 1<br>CAMBODIA KHM -0.94 0.18 7 -0.89 0.24 6 -0.57 0.25 5 -0.60 0.27 5 -0.50 0.30 3 -1.21 0.47 1 -0.66 0.47 1<br>CAMEROON CMR -0.90 0.16 10 -0.70 0.18 9 -0.58 0.18 9 -0.68 0.18 8 -0.50 0.22 7 -0.68 0.27 6 -1.11 0.21 4<br>CANADA CAN 1.92 0.16 9 2.01 0.17 10 2.02 0.17 10 2.01 0.16 10 1.94 0.21 9 2.13 0.29 7 2.03 0.21 6<br>CAPE VERDE CPV -0.11 0.20 5 -0.14 0.24 5 -0.19 0.22 5 -0.13 0.24 5 0.23 0.36 2 0.26 0.47 1 -0.07 0.47 1<br>CAYMAN ISLANDS CYM 1.29 0.27 1 1.15 0.39 1 1.31 0.35 1 1.93 0.33 1 .. .. .. .. .. .. .. .. ..<br>CENTRAL AFRICAN REPUBLIC CAF -1.47 0.20 6 -1.64 0.24 6 -1.49 0.25 5 -1.52 0.26 4 -1.11 0.36 2 -1.00 0.39 2 -0.92 0.47 1<br>CHAD TCD -1.13 0.18 7 -0.98 0.22 7 -0.78 0.23 6 -0.71 0.26 5 -0.43 0.36 2 -0.56 0.41 2 -0.66 0.47 1<br>CHILE CHL 1.26 0.15 12 1.30 0.16 13 1.23 0.16 11 1.25 0.15 12 1.31 0.19 10 1.31 0.26 7 1.20 0.19 7<br>CHINA CHN -0.11 0.15 11 0.05 0.16 12 0.08 0.16 11 0.14 0.16 11 0.25 0.19 9 0.06 0.26 7 0.15 0.19 7<br>COLOMBIA COL -0.09 0.15 12 -0.13 0.16 12 -0.19 0.17 10 -0.39 0.16 11 -0.22 0.19 10 -0.04 0.25 8 0.17 0.19 7<br>COMOROS COM -1.63 0.22 4 -1.54 0.29 4 -1.45 0.27 4 -0.98 0.26 4 -1.37 0.36 2 -1.09 0.47 1 -0.66 0.47 1<br>CONGO COG -1.31 0.20 7 -1.26 0.23 7 -1.36 0.22 7 -1.44 0.22 7 -1.80 0.29 4 -0.81 0.34 4 -1.19 0.40 2<br>Congo, Dem. Rep. (Zaire) ZAR -1.64 0.17 9 -1.46 0.17 10 -1.38 0.18 9 -1.72 0.20 8 -1.91 0.25 5 -1.96 0.37 3 -1.72 0.36 3<br>COOK ISLANDS COK 0.23 0.90 1 -0.16 0.54 1 -0.24 0.51 2 0.09 0.80 2 -0.06 0.41 1 .. .. .. .. .. ..<br>COSTA RICA CRI 0.30 0.16 10 0.52 0.17 11 0.51 0.17 9 0.49 0.16 10 0.63 0.21 7 0.49 0.29 5 0.11 0.21 5<br>CROATIA HRV 0.44 0.14 11 0.31 0.14 11 0.18 0.15 10 0.24 0.14 10 0.22 0.21 7 0.23 0.27 5 -0.30 0.19 4<br>CUBA CUB -0.94 0.18 7 -0.61 0.19 8 -0.48 0.19 7 -0.37 0.18 7 -0.29 0.25 4 -0.53 0.40 3 -0.29 0.23 3<br>CYPRUS CYP 1.16 0.18 6 1.06 0.19 7 1.16 0.20 6 1.08 0.19 6 1.17 0.27 3 1.33 0.40 3 1.17 0.23 3<br>CZECH REPUBLIC CZE 0.94 0.13 12 0.73 0.13 13 0.73 0.14 12 0.75 0.14 12 0.77 0.18 10 0.69 0.23 9 0.52 0.17 8<br>DENMARK DNK 2.12 0.16 9 2.21 0.17 10 2.11 0.17 10 2.03 0.16 9 1.84 0.21 8 2.20 0.31 6 2.09 0.21 6<br>DJIBOUTI DJI -0.85 0.22 4 -0.75 0.29 4 -0.80 0.27 4 -0.89 0.26 4 -1.14 0.36 2 -0.90 0.47 1 -1.09 0.47 1<br>DOMINICA DMA 0.57 0.25 3 0.39 0.32 3 0.24 0.29 3 0.17 0.28 3 -0.73 0.43 1 -0.90 0.47 1 -0.87 0.47 1<br>DOMINICAN REPUBLIC DOM -0.41 0.16 10 -0.52 0.17 10 -0.45 0.18 8 -0.48 0.17 8 -0.23 0.21 7 -0.67 0.35 3 -0.37 0.22 3<br>ECUADOR ECU -1.01 0.16 10 -0.83 0.16 11 -0.82 0.17 9 -0.90 0.16 10 -1.04 0.20 8 -0.84 0.28 6 -0.98 0.20 5<br>EGYPT EGY -0.35 0.15 11 -0.23 0.15 12 -0.26 0.16 11 -0.33 0.16 11 0.26 0.19 9 -0.09 0.27 6 -0.30 0.20 6<br>EL SALVADOR SLV -0.30 0.16 9 -0.25 0.18 9 -0.41 0.20 7 -0.48 0.18 8 -0.11 0.22 6 -0.01 0.35 3 -0.53 0.21 4<br>EQUATORIAL GUINEA GNQ -1.42 0.22 5 -1.37 0.27 5 -1.26 0.25 5 -1.42 0.26 5 -2.25 0.36 2 -1.64 0.47 1 -1.51 0.47 1<br>ERITREA ERI -0.98 0.20 6 -0.96 0.22 7 -0.67 0.23 6 -0.54 0.24 5 -0.37 0.36 2 0.26 0.47 1 -0.34 0.47 1<br>ESTONIA EST 1.03 0.14 12 0.95 0.13 13 1.04 0.14 12 0.82 0.14 12 1.04 0.19 10 0.45 0.26 6 0.53 0.19 4<br>ETHIOPIA ETH -0.97 0.16 9 -0.87 0.17 10 -0.79 0.18 9 -0.79 0.22 7 -0.46 0.28 5 -0.18 0.38 3 -0.55 0.40 2<br>FIJI FJI -0.09 0.25 3 -0.37 0.28 4 -0.10 0.26 4 0.13 0.26 4 -0.47 0.37 2 -0.07 0.41 2 -0.07 0.47 1<br>FINLAND FIN 2.07 0.16 9 2.06 0.18 9 2.14 0.18 9 2.08 0.17 9 1.89 0.21 8 2.12 0.31 6 2.04 0.21 6<br>FRANCE FRA 1.46 0.16 9 1.49 0.17 10 1.57 0.17 10 1.62 0.16 10 1.54 0.21 8 1.59 0.29 7 1.94 0.21 6<br>FRENCH GUIANA GUF 0.75 0.27 1 0.57 0.39 1 0.79 0.35 1 0.83 0.33 1 .. .. .. .. .. .. .. .. ..<br>GABON GAB -0.63 0.18 8 -0.63 0.19 8 -0.54 0.18 8 -0.41 0.18 8 -0.72 0.21 6 -0.84 0.35 3 -1.02 0.22 3<br>GAMBIA GMB -0.65 0.19 6 -0.64 0.21 7 -0.65 0.21 7 -0.85 0.22 6 -0.10 0.31 3 -0.31 0.44 2 -0.34 0.40 2<br>GEORGIA GEO -0.47 0.15 9 -0.81 0.15 10 -0.74 0.16 8 -0.76 0.17 8 -0.74 0.26 6 -0.47 0.30 4 -0.45 0.27 3<br>GERMANY DEU 1.51 0.16 9 1.44 0.17 10 1.50 0.17 10 1.80 0.16 10 1.92 0.21 8 1.78 0.29 7 2.01 0.21 6<br><!-- End of picture text --> 95
<!-- Start of picture text --> TABLE C3: Government Effectiveness (cont.)<br>2005 2004 2003 2002 2000 1998 1996<br>Country Code Est. S.E. N. Est. S.E. N. Est. S.E. N. Est. S.E. N. Est. S.E. N. Est. S.E. N. Est. S.E. N.<br>GHANA GHA -0.09 0.15 11 -0.21 0.15 12 -0.30 0.16 11 -0.11 0.16 10 0.03 0.22 7 -0.29 0.27 6 0.05 0.21 4<br>GREECE GRC 0.66 0.16 9 0.80 0.18 9 0.83 0.18 9 0.82 0.17 9 0.89 0.22 6 0.74 0.31 6 0.82 0.21 6<br>GRENADA GRD 0.26 0.25 3 0.21 0.32 3 0.24 0.29 3 0.37 0.28 3 -0.02 0.43 1 -0.29 0.47 1 -0.55 0.47 1<br>GUAM GUM 0.21 0.27 1 0.26 0.39 1 .. .. .. .. .. .. .. .. .. .. .. .. .. .. ..<br>GUATEMALA GTM -0.70 0.16 9 -0.84 0.18 10 -0.91 0.19 8 -0.57 0.17 9 -0.50 0.22 6 -0.25 0.35 3 -0.53 0.21 4<br>GUINEA GIN -1.03 0.19 7 -1.01 0.22 7 -0.79 0.23 6 -0.78 0.23 6 -0.34 0.31 3 -0.45 0.39 3 -1.11 0.40 2<br>GUINEA-BISSAU GNB -1.46 0.21 5 -1.27 0.24 6 -1.23 0.22 6 -1.30 0.22 6 -1.35 0.29 4 -0.45 0.39 3 -0.55 0.40 2<br>GUYANA GUY -0.52 0.19 6 -0.12 0.26 5 -0.23 0.25 5 -0.23 0.25 4 -0.16 0.32 3 -0.20 0.44 2 -0.23 0.40 2<br>HAITI HTI -1.39 0.20 6 -1.72 0.22 7 -1.61 0.21 7 -1.64 0.21 6 -1.74 0.31 4 -0.96 0.44 2 -1.16 0.40 2<br>HONDURAS HND -0.64 0.16 9 -0.65 0.18 10 -0.71 0.19 8 -0.67 0.17 9 -0.44 0.22 6 -0.40 0.35 3 -1.07 0.21 4<br>HONG KONG HKG 1.63 0.17 8 1.56 0.19 8 1.40 0.19 8 1.38 0.18 8 1.13 0.24 6 1.55 0.31 6 1.93 0.22 5<br>HUNGARY HUN 0.79 0.13 13 0.70 0.13 14 0.75 0.13 13 0.80 0.13 13 0.83 0.18 11 0.76 0.23 9 0.39 0.17 8<br>ICELAND ISL 2.20 0.20 6 2.22 0.25 6 2.23 0.24 6 1.97 0.24 5 2.11 0.37 4 1.92 0.50 3 1.56 0.45 3<br>INDIA IND -0.11 0.15 11 -0.03 0.16 12 -0.03 0.16 11 -0.09 0.16 11 -0.06 0.19 9 -0.18 0.25 8 -0.45 0.19 7<br>INDONESIA IDN -0.47 0.14 12 -0.42 0.15 13 -0.58 0.16 12 -0.55 0.16 12 -0.39 0.17 10 -0.57 0.26 7 0.08 0.19 7<br>IRAN IRN -0.77 0.17 9 -0.65 0.17 10 -0.47 0.17 9 -0.47 0.17 9 -0.09 0.24 5 -0.32 0.36 4 -0.36 0.22 4<br>IRAQ IRQ -1.64 0.20 6 -1.46 0.20 7 -1.34 0.21 6 -1.81 0.19 6 -1.65 0.25 4 -2.18 0.40 3 -1.30 0.23 3<br>IRELAND IRL 1.63 0.16 9 1.56 0.17 10 1.52 0.17 10 1.63 0.16 9 2.06 0.21 8 1.73 0.29 7 1.70 0.21 6<br>ISRAEL ISR 0.95 0.17 8 1.12 0.18 9 0.97 0.18 9 1.11 0.17 9 1.18 0.23 6 0.92 0.33 5 1.49 0.21 6<br>ITALY ITA 0.60 0.16 9 0.66 0.18 9 0.88 0.18 9 0.90 0.17 9 0.90 0.21 9 0.99 0.29 7 0.93 0.21 6<br>IVORY COAST CIV -1.38 0.17 9 -1.28 0.17 10 -0.97 0.18 9 -0.94 0.17 9 -0.86 0.22 6 -0.13 0.27 6 0.05 0.21 4<br>JAMAICA JAM -0.12 0.17 8 0.14 0.18 8 -0.07 0.20 7 0.01 0.18 7 -0.26 0.24 4 -0.63 0.32 4 -0.35 0.22 3<br>JAPAN JPN 1.16 0.16 9 1.17 0.17 10 1.16 0.17 10 1.11 0.16 10 1.15 0.21 8 1.05 0.36 5 1.33 0.21 6<br>JORDAN JOR 0.08 0.16 10 0.16 0.17 10 0.34 0.18 9 0.33 0.17 8 0.33 0.21 6 0.50 0.27 6 0.13 0.21 5<br>KAZAKHSTAN KAZ -0.71 0.13 12 -0.80 0.13 12 -0.75 0.14 11 -0.88 0.14 11 -0.62 0.19 9 -0.77 0.25 7 -1.03 0.18 5<br>KENYA KEN -0.78 0.15 11 -0.72 0.15 12 -0.65 0.16 11 -0.71 0.16 10 -0.72 0.21 7 -0.98 0.27 6 -0.64 0.21 4<br>KIRIBATI KIR -0.50 0.22 4 -0.77 0.29 4 -0.34 0.38 3 -0.13 0.44 3 -0.20 0.31 2 -0.53 0.47 1 -0.34 0.47 1<br>KOREA, NORTH PRK -1.82 0.20 5 -1.66 0.20 6 -1.40 0.22 5 -1.87 0.26 4 -1.39 0.45 2 -0.58 0.90 1 -0.89 0.66 1<br>KOREA, SOUTH KOR 1.00 0.15 11 0.92 0.16 12 0.91 0.16 11 0.95 0.16 11 0.73 0.19 9 0.43 0.25 8 0.63 0.21 6<br>KOSOVO LWI -0.76 0.27 1 .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. ..<br>KUWAIT KWT 0.39 0.18 7 0.29 0.20 7 0.31 0.19 7 0.13 0.17 8 0.07 0.27 3 0.08 0.40 3 0.17 0.23 3<br>KYRGYZ REPUBLIC KGZ -0.91 0.14 10 -0.83 0.15 10 -0.78 0.16 9 -0.77 0.17 9 -0.65 0.23 5 -0.33 0.30 4 -0.53 0.27 3<br>LAOS LAO -1.09 0.19 7 -1.01 0.24 6 -0.96 0.25 5 -0.62 0.27 5 -0.73 0.28 3 -0.35 0.47 1 -0.07 0.47 1<br>LATVIA LVA 0.68 0.14 11 0.64 0.14 11 0.74 0.15 10 0.71 0.14 10 0.29 0.20 7 0.24 0.26 6 -0.34 0.19 4<br>LEBANON LBN -0.30 0.18 8 -0.32 0.19 8 -0.24 0.19 7 -0.40 0.17 8 -0.23 0.22 5 -0.03 0.31 4 -0.34 0.21 4<br>LESOTHO LSO -0.29 0.19 7 -0.23 0.21 7 -0.35 0.20 7 -0.27 0.22 6 -0.14 0.36 2 -0.39 0.39 2 0.09 0.47 1<br>LIBERIA LBR -1.36 0.21 5 -1.74 0.25 5 -1.75 0.26 4 -1.73 0.25 5 -1.68 0.29 4 -1.87 0.44 2 -1.80 0.40 2<br>LIBYA LBY -0.96 0.18 7 -0.79 0.20 7 -0.93 0.21 6 -0.97 0.19 6 -1.29 0.27 3 -1.51 0.40 3 -0.82 0.23 3<br>LIECHTENSTEIN LIE 1.57 0.26 2 1.64 0.38 2 1.44 0.34 2 1.65 0.32 2 .. .. .. .. .. .. .. .. ..<br>LITHUANIA LTU 0.85 0.14 11 0.72 0.13 12 0.77 0.14 11 0.64 0.14 11 0.46 0.19 9 0.20 0.26 6 -0.16 0.19 4<br>LUXEMBOURG LUX 1.94 0.20 6 2.09 0.25 6 2.08 0.24 6 2.16 0.26 5 1.87 0.46 3 2.04 0.50 3 2.34 0.45 3<br>MACAO MAC 1.29 0.27 1 1.08 0.39 1 1.31 0.35 1 0.83 0.33 1 .. .. .. .. .. .. .. .. ..<br>MACEDONIA MKD -0.28 0.14 10 -0.16 0.14 10 -0.29 0.15 9 -0.39 0.15 7 -0.56 0.25 4 -0.42 0.29 4 -0.29 0.19 3<br>MADAGASCAR MDG -0.12 0.16 9 -0.39 0.20 8 -0.34 0.22 7 -0.41 0.24 5 -0.55 0.28 5 -0.49 0.34 4 -0.95 0.40 2<br>MALAWI MWI -0.78 0.15 10 -0.82 0.17 10 -0.72 0.17 9 -0.60 0.18 8 -0.57 0.22 6 -0.63 0.29 5 -0.67 0.22 3<br>MALAYSIA MYS 1.01 0.15 11 0.95 0.16 12 0.85 0.16 11 0.95 0.16 11 0.71 0.19 10 0.73 0.25 8 0.75 0.19 7<br>MALDIVES MDV 0.18 0.22 4 0.20 0.29 4 0.40 0.26 4 0.73 0.27 4 0.11 0.31 2 0.45 0.47 1 -0.02 0.47 1<br>MALI MLI -0.46 0.16 9 -0.26 0.18 10 -0.39 0.18 9 -0.65 0.21 8 -0.72 0.29 4 -0.26 0.39 3 -0.72 0.40 2<br>MALTA MLT 0.95 0.20 5 1.03 0.26 5 1.04 0.25 5 1.08 0.28 3 0.73 0.56 1 0.65 0.90 1 -0.23 0.66 1<br>MARSHALL ISLANDS MHL -0.96 0.36 3 -0.92 0.39 3 -1.00 0.38 3 -0.42 0.44 3 -0.68 0.31 2 -0.59 0.47 1 .. .. ..<br>MARTINIQUE MTQ 0.75 0.27 1 0.74 0.39 1 0.79 0.35 1 0.83 0.33 1 .. .. .. .. .. .. .. .. ..<br>MAURITANIA MRT -0.19 0.22 5 -0.10 0.27 5 0.06 0.25 5 -0.05 0.26 4 -0.33 0.32 3 -0.23 0.47 1 0.14 0.47 1<br>MAURITIUS MUS 0.60 0.17 7 0.70 0.21 6 0.71 0.21 6 0.49 0.19 6 0.72 0.23 5 0.48 0.30 4 0.62 0.23 2<br>MEXICO MEX -0.01 0.15 12 0.07 0.16 13 0.12 0.16 11 0.25 0.15 12 0.28 0.19 10 0.16 0.25 8 -0.20 0.19 7<br>MICRONESIA FSM -0.09 0.22 4 -0.67 0.29 4 -0.53 0.38 3 -0.41 0.44 3 -0.54 0.31 2 -0.53 0.47 1 .. .. ..<br>MOLDOVA MDA -0.75 0.14 11 -0.79 0.14 10 -0.63 0.15 9 -0.62 0.15 8 -1.14 0.20 7 -0.56 0.26 6 -0.82 0.19 4<br>MONACO MCO -0.12 0.90 1 1.39 0.86 1 -0.64 0.87 1 -0.63 0.88 1 .. .. .. .. .. .. .. .. ..<br>MONGOLIA MNG -0.35 0.17 8 -0.37 0.21 8 -0.37 0.22 7 -0.26 0.23 6 -0.22 0.26 4 0.03 0.35 3 -0.50 0.40 2<br>MOROCCO MAR -0.20 0.16 10 -0.11 0.16 11 -0.02 0.17 10 -0.01 0.16 10 -0.09 0.22 5 0.17 0.27 6 -0.05 0.20 5<br>MOZAMBIQUE MOZ -0.34 0.16 10 -0.42 0.17 11 -0.48 0.17 10 -0.45 0.21 8 -0.53 0.29 4 -0.42 0.34 4 -0.54 0.40 2<br>MYANMAR MMR -1.61 0.18 7 -1.54 0.19 8 -1.35 0.19 7 -1.35 0.18 7 -1.38 0.25 4 -1.69 0.40 3 -1.20 0.23 3<br>NAMIBIA NAM 0.09 0.15 11 0.16 0.15 12 0.15 0.16 11 0.07 0.16 11 0.30 0.22 6 0.04 0.32 4 0.25 0.22 3<br>NAURU NRU -0.44 0.90 1 -1.33 0.86 1 -1.72 0.87 1 -1.18 0.88 1 .. .. .. .. .. .. .. .. ..<br>NEPAL NPL -0.97 0.17 8 -0.84 0.19 8 -0.63 0.20 7 -0.47 0.25 6 -0.63 0.28 3 -1.02 0.47 1 -0.39 0.47 1<br>NETHERLANDS NLD 1.95 0.16 9 2.06 0.18 9 2.07 0.18 9 2.15 0.17 9 2.09 0.21 8 2.50 0.31 6 2.44 0.21 6<br>NETHERLANDS ANTILLES ANT 1.02 0.27 1 1.08 0.39 1 .. .. .. .. .. .. .. .. .. .. .. .. .. .. ..<br>NEW ZEALAND NZL 1.90 0.17 8 2.13 0.19 8 2.13 0.19 8 1.98 0.18 7 1.50 0.23 6 2.01 0.33 5 2.46 0.22 5<br>NICARAGUA NIC -0.78 0.16 9 -0.67 0.18 10 -0.69 0.19 8 -0.81 0.17 9 -0.73 0.22 6 -0.49 0.35 3 -0.64 0.21 4<br>NIGER NER -0.79 0.19 7 -0.78 0.22 7 -0.85 0.23 6 -0.90 0.24 5 -1.02 0.29 4 -1.03 0.44 2 -1.07 0.40 2<br>NIGERIA NGA -0.92 0.15 11 -0.95 0.15 12 -0.87 0.16 11 -1.02 0.16 11 -1.00 0.20 9 -1.42 0.27 6 -1.26 0.20 5<br><!-- End of picture text --> 96
<!-- Start of picture text --> TABLE C3: Government Effectiveness (cont.)<br>2005 2004 2003 2002 2000 1998 1996<br>Country Code Est. S.E. N. Est. S.E. N. Est. S.E. N. Est. S.E. N. Est. S.E. N. Est. S.E. N. Est. S.E. N.<br>NIUE NIU -0.44 0.90 1 .. .. .. -0.19 0.87 1 -0.77 0.88 1 .. .. .. .. .. .. .. .. ..<br>NORWAY NOR 1.99 0.16 9 2.11 0.18 9 2.07 0.18 9 1.89 0.17 8 1.63 0.22 7 2.12 0.31 6 2.13 0.21 6<br>OMAN OMN 0.47 0.20 6 0.66 0.20 7 0.75 0.19 7 0.56 0.17 8 0.85 0.25 4 1.09 0.40 3 0.67 0.23 3<br>PALAU PCI -0.76 0.90 1 0.38 0.86 1 0.32 0.87 1 -0.35 0.88 1 .. .. .. .. .. .. .. .. ..<br>PAKISTAN PAK -0.53 0.15 11 -0.52 0.16 11 -0.56 0.17 10 -0.57 0.17 9 -0.53 0.19 7 -0.74 0.27 6 -0.39 0.20 5<br>PANAMA PAN 0.11 0.16 10 -0.03 0.18 10 -0.13 0.17 9 -0.10 0.16 10 -0.03 0.21 7 -0.04 0.31 4 -0.38 0.21 4<br>PAPUA NEW GUINEA PNG -0.96 0.17 9 -0.80 0.17 10 -0.73 0.18 9 -0.77 0.18 8 -0.64 0.20 6 -0.59 0.35 3 -0.60 0.22 3<br>PARAGUAY PRY -0.83 0.16 9 -1.03 0.18 10 -1.15 0.19 8 -1.21 0.17 9 -1.23 0.24 5 -1.05 0.32 4 -0.92 0.22 3<br>PERU PER -0.60 0.15 11 -0.47 0.16 12 -0.48 0.17 10 -0.38 0.16 11 -0.40 0.20 9 0.19 0.26 7 -0.11 0.20 6<br>PHILIPPINES PHL -0.07 0.15 11 -0.17 0.16 12 -0.16 0.16 11 -0.06 0.16 11 0.12 0.19 10 0.13 0.26 7 0.22 0.19 7<br>POLAND POL 0.58 0.13 13 0.60 0.13 14 0.65 0.13 13 0.64 0.13 13 0.52 0.18 11 0.84 0.23 9 0.50 0.17 8<br>PORTUGAL PRT 1.03 0.16 9 1.05 0.18 9 1.23 0.18 9 1.06 0.17 8 1.14 0.22 7 1.43 0.29 7 1.03 0.21 6<br>PUERTO RICO PRI 1.01 0.24 3 1.11 0.29 3 1.16 0.27 3 1.18 0.28 2 1.59 0.49 1 1.61 0.60 1 1.43 0.66 1<br>QATAR QAT 0.55 0.18 7 0.63 0.21 6 0.59 0.21 6 0.63 0.18 6 0.78 0.25 4 0.63 0.40 3 0.62 0.23 3<br>REUNION REU 1.02 0.27 1 1.05 0.39 1 .. .. .. .. .. .. .. .. .. .. .. .. .. .. ..<br>ROMANIA ROM -0.03 0.13 13 -0.11 0.13 13 -0.16 0.14 12 -0.32 0.14 11 -0.67 0.19 9 -0.63 0.27 5 -0.88 0.18 5<br>RUSSIA RUS -0.45 0.13 13 -0.37 0.13 14 -0.34 0.13 13 -0.47 0.13 13 -0.70 0.18 11 -0.62 0.23 9 -0.79 0.17 8<br>RWANDA RWA -1.05 0.21 5 -0.59 0.23 6 -0.66 0.24 5 -0.80 0.24 5 -0.20 0.36 2 -0.72 0.47 1 -1.24 0.47 1<br>SAMOA SAM 0.35 0.22 4 0.11 0.29 4 0.37 0.26 4 0.27 0.27 4 0.10 0.31 2 -0.12 0.47 1 -0.34 0.47 1<br>SAN MARINO SMR -0.50 0.90 1 -0.22 0.86 1 -0.68 0.87 1 -0.35 0.88 1 .. .. .. .. .. .. .. .. ..<br>SAO TOME AND PRINCIPE STP -0.75 0.22 4 -0.85 0.29 4 -0.60 0.27 4 -0.68 0.26 4 -0.77 0.36 2 -0.84 0.47 1 -0.66 0.47 1<br>SAUDI ARABIA SAU -0.38 0.17 8 -0.22 0.17 9 -0.10 0.18 8 -0.11 0.17 9 -0.04 0.24 5 -0.38 0.36 4 -0.25 0.22 4<br>SENEGAL SEN -0.15 0.16 9 -0.15 0.17 10 -0.23 0.16 10 -0.19 0.17 9 0.12 0.22 6 0.06 0.29 5 -0.32 0.22 3<br>SEYCHELLES SYC -0.05 0.22 5 -0.27 0.27 5 -0.29 0.25 5 -0.16 0.26 4 -1.00 0.36 2 -0.59 0.47 1 -0.71 0.47 1<br>SIERRA LEONE SLE -1.20 0.20 6 -1.43 0.22 7 -1.57 0.22 6 -1.66 0.22 6 -1.42 0.29 4 -0.53 0.44 2 -0.60 0.40 2<br>SINGAPORE SGP 2.14 0.15 10 2.19 0.17 10 2.42 0.18 9 2.31 0.17 9 2.33 0.22 8 2.57 0.29 7 2.31 0.21 6<br>SLOVAK REPUBLIC SVK 0.95 0.14 12 0.73 0.13 12 0.57 0.14 11 0.46 0.14 10 0.32 0.19 9 0.00 0.24 7 0.17 0.18 6<br>SLOVENIA SVN 0.99 0.14 11 0.95 0.13 12 1.00 0.14 12 0.87 0.14 12 0.79 0.19 9 0.68 0.27 5 0.52 0.19 4<br>SOLOMON ISLANDS SLB -0.69 0.22 4 -1.49 0.29 4 -2.43 0.38 3 -1.70 0.44 3 -0.85 0.31 2 -0.84 0.47 1 -1.03 0.47 1<br>SOMALIA SOM -2.21 0.21 5 -2.05 0.25 5 -1.92 0.26 4 -1.71 0.26 4 -2.34 0.32 3 -1.87 0.44 2 -1.80 0.40 2<br>SOUTH AFRICA ZAF 0.84 0.14 13 0.74 0.14 14 0.64 0.15 13 0.63 0.15 13 0.40 0.18 11 0.12 0.25 8 0.53 0.19 7<br>SPAIN ESP 1.40 0.16 9 1.35 0.17 10 1.53 0.17 10 1.58 0.16 10 1.82 0.21 9 1.95 0.29 7 1.70 0.21 6<br>SRI LANKA LKA -0.41 0.15 10 -0.29 0.16 11 -0.16 0.17 10 0.02 0.17 10 -0.34 0.19 7 -0.41 0.31 4 -0.33 0.21 4<br>ST. KITTS AND NEVIS KNA 1.00 0.25 3 -0.09 0.32 3 -0.42 0.47 2 -0.27 0.46 2 0.06 0.43 1 -0.29 0.47 1 -0.28 0.47 1<br>ST. LUCIA LCA 1.12 0.25 3 0.20 0.32 3 0.15 0.47 2 0.01 0.46 2 0.11 0.43 1 -0.23 0.47 1 0.30 0.47 1<br>ST. VINCENT AND THE GRENADINES VCT 1.07 0.25 3 0.35 0.32 3 -0.10 0.47 2 -0.20 0.46 2 -0.06 0.43 1 -0.29 0.47 1 -0.28 0.47 1<br>SUDAN SDN -1.30 0.17 9 -1.20 0.17 10 -1.20 0.18 9 -1.13 0.17 9 -1.56 0.21 6 -1.70 0.35 3 -1.34 0.22 3<br>SURINAME SUR -0.04 0.23 4 -0.03 0.29 4 -0.18 0.28 4 -0.28 0.28 3 -0.10 0.56 1 0.04 0.90 1 -0.89 0.66 1<br>SWAZILAND SWZ -0.84 0.20 6 -0.70 0.24 6 -0.79 0.23 6 -0.43 0.24 5 -0.63 0.36 2 -0.81 0.39 2 -0.39 0.47 1<br>SWEDEN SWE 1.93 0.16 9 1.99 0.17 10 2.03 0.17 10 1.93 0.16 9 1.77 0.21 9 1.99 0.31 6 2.05 0.21 6<br>SWITZERLAND CHE 2.03 0.16 9 2.28 0.18 9 2.29 0.18 9 2.25 0.17 8 2.18 0.21 8 2.48 0.29 7 2.53 0.21 6<br>SYRIA SYR -1.23 0.18 7 -0.92 0.19 8 -0.79 0.19 7 -0.68 0.18 7 -1.01 0.25 4 -1.28 0.40 3 -0.69 0.23 3<br>TAIWAN TWN 1.11 0.15 10 1.19 0.16 11 1.14 0.17 10 1.10 0.16 10 1.21 0.21 8 1.56 0.31 6 1.26 0.21 6<br>TAJIKISTAN TJK -1.06 0.14 10 -1.01 0.15 10 -1.09 0.16 9 -1.24 0.17 9 -1.26 0.23 5 -1.45 0.32 3 -1.54 0.27 3<br>TANZANIA TZA -0.37 0.15 11 -0.39 0.15 12 -0.40 0.16 11 -0.56 0.16 10 -0.35 0.21 7 -0.60 0.27 6 -1.20 0.21 4<br>THAILAND THA 0.40 0.15 11 0.37 0.16 12 0.29 0.16 11 0.26 0.16 11 0.19 0.20 9 0.04 0.25 8 0.58 0.19 7<br>TIMOR, EAST TMP -0.97 0.22 3 -0.84 0.33 2 -0.94 0.30 3 -0.93 0.32 2 .. .. .. .. .. .. .. .. ..<br>TOGO TGO -1.38 0.19 7 -1.33 0.22 7 -1.27 0.23 6 -1.25 0.24 5 -1.51 0.31 3 -0.51 0.39 3 -0.75 0.40 2<br>TONGA TON -0.48 0.22 4 -0.75 0.29 4 -0.59 0.38 3 -0.65 0.44 3 -0.53 0.31 2 -0.47 0.47 1 -0.23 0.47 1<br>TRINIDAD AND TOBAGO TTO 0.29 0.17 8 0.54 0.20 7 0.52 0.20 7 0.52 0.18 6 0.61 0.23 5 0.42 0.35 3 0.37 0.22 3<br>TUNISIA TUN 0.43 0.16 10 0.53 0.16 11 0.61 0.17 10 0.58 0.16 10 1.07 0.21 7 0.75 0.29 5 0.49 0.21 4<br>TURKEY TUR 0.27 0.15 12 0.07 0.16 13 0.09 0.16 12 -0.05 0.16 12 0.11 0.19 10 -0.38 0.25 8 -0.16 0.19 7<br>TURKMENISTAN TKM -1.57 0.16 7 -1.45 0.16 7 -1.33 0.17 6 -1.52 0.18 6 -1.42 0.29 3 -1.46 0.32 3 -1.47 0.27 3<br>TUVALU TUV 0.23 0.26 2 -1.04 0.33 3 -0.96 0.51 2 0.18 0.80 2 0.19 0.41 1 .. .. .. .. .. ..<br>UGANDA UGA -0.48 0.15 11 -0.45 0.15 12 -0.41 0.16 11 -0.48 0.16 10 -0.19 0.21 7 -0.27 0.27 6 -0.39 0.21 4<br>UKRAINE UKR -0.42 0.13 12 -0.63 0.13 13 -0.58 0.14 12 -0.73 0.14 12 -0.76 0.19 9 -1.00 0.23 8 -0.87 0.18 6<br>UNITED ARAB EMIRATES ARE 0.55 0.17 8 1.02 0.19 7 0.77 0.21 6 0.80 0.18 7 0.64 0.27 3 0.26 0.40 3 0.59 0.23 3<br>UNITED KINGDOM GBR 1.70 0.16 9 1.92 0.17 10 1.96 0.17 10 2.02 0.16 10 2.04 0.21 9 2.39 0.29 7 2.33 0.21 6<br>UNITED STATES USA 1.59 0.16 9 1.79 0.18 9 1.80 0.18 9 1.70 0.17 9 1.74 0.22 8 1.71 0.29 7 2.06 0.21 6<br>URUGUAY URY 0.53 0.16 10 0.50 0.17 10 0.46 0.18 8 0.55 0.17 9 0.57 0.21 7 0.58 0.31 4 0.71 0.21 4<br>UZBEKISTAN UZB -1.20 0.15 10 -1.05 0.14 11 -1.02 0.15 10 -1.12 0.15 10 -0.98 0.19 7 -1.33 0.26 5 -1.07 0.19 4<br>VANUATU VUT -0.33 0.22 4 -0.75 0.29 4 -0.93 0.38 3 -0.39 0.44 3 -0.51 0.31 2 -0.47 0.47 1 -0.23 0.47 1<br>VENEZUELA VEN -0.83 0.15 12 -0.98 0.16 13 -1.04 0.16 11 -1.06 0.15 12 -0.83 0.20 8 -0.89 0.25 8 -0.78 0.19 7<br>VIETNAM VNM -0.31 0.15 11 -0.37 0.15 12 -0.31 0.16 11 -0.34 0.16 11 -0.36 0.18 8 -0.24 0.27 6 -0.28 0.20 6<br>VIRGIN ISLANDS (U.S.) VIR 1.29 0.27 1 0.55 0.39 1 .. .. .. .. .. .. .. .. .. .. .. .. .. .. ..<br>WEST BANK WBG -1.13 0.25 2 -0.91 0.35 2 -1.23 0.32 2 -1.03 0.32 2 0.44 0.80 1 -0.05 0.68 1 .. .. ..<br>YEMEN YEM -0.94 0.18 7 -0.94 0.19 8 -0.70 0.20 7 -0.89 0.18 7 -0.75 0.25 4 -0.48 0.35 3 -0.73 0.22 3<br>YUGOSLAVIA YUG -0.31 0.14 11 -0.12 0.14 11 -0.50 0.15 10 -0.61 0.15 9 -0.80 0.27 3 -1.11 0.36 3 -0.71 0.24 2<br>ZAMBIA ZMB -0.94 0.16 10 -0.82 0.15 12 -0.87 0.16 11 -0.72 0.16 10 -0.63 0.21 7 -0.53 0.27 6 -0.75 0.21 4<br>ZIMBABWE ZWE -1.42 0.15 11 -1.12 0.17 10 -1.17 0.18 9 -0.81 0.17 9 -1.10 0.20 7 -0.94 0.27 6 -0.03 0.21 5<br><!-- End of picture text --> 97
<!-- Start of picture text --> TABLE C4: Regulatory Quality<br>2005 2004 2003 2002 2000 1998 1996<br>Country Code Est. S.E. N. Est. S.E. N. Est. S.E. N. Est. S.E. N. Est. S.E. N. Est. S.E. N. Est. S.E. N.<br>AFGHANISTAN AFG -1.63 0.21 4 -1.78 0.22 4 -1.69 0.23 3 -1.84 0.30 2 -3.69 0.57 1 .. .. .. .. .. ..<br>ALBANIA ALB -0.27 0.18 9 -0.23 0.19 8 -0.44 0.20 7 -0.40 0.21 7 -0.13 0.37 6 -0.62 0.30 6 -0.04 0.31 5<br>ALGERIA DZA -0.63 0.16 10 -0.65 0.17 10 -0.54 0.18 9 -0.62 0.19 8 -0.82 0.32 5 -1.21 0.41 4 -0.81 0.29 5<br>AMERICAN SAMOA ASM 0.36 0.31 1 0.46 0.34 1 .. .. .. .. .. .. .. .. .. .. .. .. .. .. ..<br>ANDORRA ADO 1.33 0.31 1 1.36 0.34 1 1.38 0.31 1 1.42 0.31 1 .. .. .. .. .. .. .. .. ..<br>ANGOLA AGO -1.24 0.17 9 -1.25 0.18 9 -1.28 0.19 8 -1.41 0.19 7 -1.85 0.32 5 -1.33 0.31 5 -1.46 0.29 5<br>ANGUILLA AIA 1.09 0.31 1 0.87 0.34 1 .. .. .. .. .. .. .. .. .. .. .. .. .. .. ..<br>ANTIGUA AND BARBUDA ATG 0.60 0.31 1 0.65 0.34 1 0.65 0.31 1 0.68 0.31 1 .. .. .. .. .. .. .. .. ..<br>ARGENTINA ARG -0.64 0.17 10 -0.74 0.17 10 -0.65 0.17 9 -0.84 0.18 9 0.43 0.32 7 0.77 0.27 6 0.73 0.23 7<br>ARMENIA ARM 0.12 0.18 10 -0.05 0.19 9 0.13 0.20 8 0.08 0.21 8 -0.46 0.37 6 -0.51 0.30 6 -0.81 0.34 4<br>ARUBA ABW 0.85 0.31 1 0.73 0.34 1 .. .. .. .. .. .. .. .. .. .. .. .. .. .. ..<br>AUSTRALIA AUS 1.58 0.19 8 1.71 0.19 8 1.65 0.18 8 1.62 0.19 7 1.43 0.36 5 1.16 0.28 5 1.25 0.24 6<br>AUSTRIA AUT 1.52 0.19 8 1.48 0.19 8 1.55 0.18 8 1.65 0.19 7 1.44 0.36 5 1.08 0.28 6 1.27 0.24 6<br>AZERBAIJAN AZE -0.52 0.16 12 -0.54 0.17 11 -0.60 0.17 10 -0.90 0.18 10 -0.57 0.33 7 -1.11 0.30 6 -1.20 0.28 5<br>BAHAMAS BHS 0.99 0.25 3 0.99 0.26 3 1.03 0.25 3 1.33 0.26 3 0.87 0.67 2 1.06 0.64 2 0.66 0.47 2<br>BAHRAIN BHR 0.69 0.18 8 0.80 0.19 8 0.70 0.20 6 0.95 0.20 7 0.94 0.46 3 0.91 0.49 3 0.60 0.30 4<br>BANGLADESH BGD -1.07 0.17 10 -1.16 0.17 10 -1.05 0.17 9 -1.09 0.19 9 -0.23 0.34 6 -0.13 0.41 4 -0.41 0.29 5<br>BARBADOS BRB 1.00 0.26 3 1.06 0.28 3 1.04 0.26 3 1.11 0.28 2 0.45 0.79 1 0.74 0.74 1 0.30 0.57 1<br>BELARUS BLR -1.53 0.18 9 -1.56 0.19 9 -1.82 0.20 8 -1.70 0.21 7 -2.75 0.38 5 -1.98 0.30 6 -1.09 0.34 4<br>BELGIUM BEL 1.24 0.19 8 1.36 0.19 8 1.35 0.18 8 1.45 0.19 8 0.69 0.34 6 0.95 0.28 5 1.17 0.24 6<br>BELIZE BLZ 0.09 0.24 4 0.08 0.25 4 0.19 0.24 4 0.11 0.26 3 -0.24 0.51 3 0.10 0.52 2 0.10 0.47 2<br>BENIN BEN -0.55 0.19 7 -0.64 0.22 6 -0.62 0.23 5 -0.51 0.24 4 -0.11 0.38 3 -0.13 0.52 3 0.12 0.47 2<br>BERMUDA BMU 1.33 0.31 1 1.39 0.34 1 1.38 0.31 1 1.42 0.31 1 .. .. .. .. .. .. .. .. ..<br>BHUTAN BTN -0.11 0.26 4 -0.75 0.26 4 0.08 0.23 4 -0.41 0.27 3 0.17 0.46 2 -0.23 0.63 1 0.06 0.67 1<br>BOLIVIA BOL -0.53 0.17 9 -0.11 0.18 9 0.07 0.18 8 -0.15 0.19 8 0.59 0.36 6 0.80 0.40 5 0.76 0.29 5<br>BOSNIA-HERZEGOVINA BIH -0.53 0.19 9 -0.52 0.19 9 -0.79 0.21 7 -0.94 0.22 7 -0.80 0.47 4 -1.30 0.33 3 -2.10 0.62 1<br>BOTSWANA BWA 0.76 0.16 10 0.81 0.17 10 0.81 0.18 9 0.77 0.18 9 0.71 0.32 6 0.82 0.31 5 0.60 0.29 5<br>BRAZIL BRA 0.08 0.17 10 0.08 0.17 10 0.28 0.17 9 0.20 0.18 9 0.30 0.32 7 0.23 0.27 7 0.12 0.23 7<br>BRUNEI BRN 0.95 0.27 2 1.18 0.29 2 1.00 0.27 2 1.03 0.28 2 0.20 0.88 1 -0.11 0.88 1 3.34 0.66 1<br>BULGARIA BGR 0.63 0.17 11 0.64 0.17 11 0.58 0.17 10 0.59 0.18 10 0.15 0.34 7 0.39 0.30 6 -0.02 0.27 6<br>BURKINA FASO BFA -0.47 0.19 7 -0.34 0.20 7 -0.30 0.21 6 -0.20 0.23 5 -0.06 0.36 4 -0.27 0.34 4 -0.38 0.41 3<br>BURUNDI BDI -1.22 0.20 6 -1.28 0.23 5 -1.28 0.25 4 -1.33 0.26 3 -0.92 0.36 4 -1.27 0.52 2 -1.33 0.67 1<br>CAMBODIA KHM -0.62 0.20 7 -0.57 0.22 6 -0.49 0.22 5 -0.47 0.25 5 -0.14 0.42 4 -0.27 0.52 2 -0.31 0.67 1<br>CAMEROON CMR -0.76 0.16 10 -0.77 0.18 9 -0.75 0.18 9 -0.80 0.19 8 -0.07 0.32 6 -0.28 0.31 6 -0.83 0.29 5<br>CANADA CAN 1.57 0.19 8 1.65 0.19 8 1.55 0.18 8 1.63 0.19 8 1.29 0.36 6 1.05 0.28 6 1.15 0.24 6<br>CAPE VERDE CPV -0.21 0.23 4 -0.12 0.25 4 -0.10 0.24 4 -0.28 0.24 4 -0.14 0.38 3 -0.61 0.52 2 -0.60 0.47 2<br>CAYMAN ISLANDS CYM 1.33 0.31 1 1.41 0.34 1 1.38 0.31 1 1.42 0.31 1 .. .. .. .. .. .. .. .. ..<br>CENTRAL AFRICAN REPUBLIC CAF -1.23 0.20 6 -1.44 0.22 6 -1.16 0.23 5 -0.89 0.24 4 -0.71 0.41 2 -0.60 0.63 1 -0.31 0.67 1<br>CHAD TCD -0.94 0.19 7 -0.87 0.21 7 -0.84 0.22 6 -0.99 0.24 5 -0.35 0.38 3 -0.70 0.52 3 -0.01 0.67 1<br>CHILE CHL 1.40 0.17 10 1.48 0.17 10 1.52 0.17 9 1.46 0.18 9 1.19 0.32 7 1.10 0.27 6 1.36 0.23 7<br>CHINA CHN -0.28 0.17 10 -0.38 0.17 10 -0.35 0.17 9 -0.46 0.18 9 -0.03 0.32 7 -0.11 0.27 6 -0.15 0.23 7<br>COLOMBIA COL 0.05 0.17 10 -0.03 0.17 10 0.00 0.17 9 -0.10 0.18 9 -0.02 0.32 7 0.43 0.27 7 0.44 0.23 7<br>COMOROS COM -1.63 0.24 3 -1.43 0.27 3 -1.33 0.26 3 -1.05 0.26 3 -0.96 0.41 2 -0.73 0.63 1 -0.74 0.67 1<br>CONGO COG -1.20 0.20 7 -1.06 0.22 6 -1.12 0.21 6 -1.09 0.22 6 -1.09 0.36 4 -0.98 0.48 4 -0.84 0.41 3<br>Congo, Dem. Rep. (Zaire) ZAR -1.66 0.17 8 -1.69 0.19 8 -1.62 0.19 7 -1.67 0.23 6 -2.70 0.32 5 -2.72 0.41 4 -2.24 0.34 4<br>COOK ISLANDS COK .. .. .. -0.05 0.66 1 -0.18 0.44 1 -0.07 0.71 1 -0.06 0.62 1 .. .. .. .. .. ..<br>COSTA RICA CRI 0.61 0.17 9 0.56 0.18 9 0.72 0.18 8 0.76 0.19 8 0.84 0.36 6 0.90 0.40 5 0.59 0.26 6<br>CROATIA HRV 0.45 0.17 11 0.33 0.17 11 0.29 0.17 10 0.17 0.18 10 0.23 0.37 6 0.27 0.30 5 -0.07 0.28 5<br>CUBA CUB -1.75 0.18 7 -1.53 0.19 7 -1.37 0.20 6 -1.22 0.20 6 -1.56 0.46 3 -1.08 0.49 3 -0.76 0.30 4<br>CYPRUS CYP 1.31 0.20 6 1.27 0.21 6 1.23 0.20 5 1.21 0.20 5 1.00 0.46 3 1.02 0.49 3 0.82 0.30 4<br>CZECH REPUBLIC CZE 1.04 0.17 11 0.98 0.16 12 1.08 0.16 11 1.10 0.17 11 0.63 0.31 8 0.70 0.23 8 1.00 0.22 8<br>DENMARK DNK 1.69 0.19 8 1.80 0.19 8 1.76 0.18 8 1.72 0.19 7 1.32 0.36 5 1.25 0.28 5 1.37 0.24 6<br>DJIBOUTI DJI -0.86 0.23 4 -0.72 0.25 4 -0.78 0.24 4 -0.69 0.24 4 -0.73 0.38 3 -0.82 0.52 2 -0.02 0.67 1<br>DOMINICA DMA 0.75 0.27 2 0.68 0.29 2 0.74 0.28 2 0.74 0.28 2 -0.20 0.59 1 -0.60 0.63 1 -0.23 0.67 1<br>DOMINICAN REPUBLIC DOM -0.27 0.17 9 -0.30 0.18 9 -0.22 0.18 8 -0.16 0.19 8 0.45 0.36 6 0.17 0.48 3 0.16 0.32 4<br>ECUADOR ECU -0.83 0.17 9 -0.58 0.18 9 -0.54 0.18 8 -0.61 0.19 8 -0.32 0.36 6 0.12 0.40 5 0.00 0.29 5<br>EGYPT EGY -0.47 0.16 10 -0.46 0.17 10 -0.50 0.18 9 -0.50 0.18 9 -0.08 0.30 7 0.12 0.31 5 -0.05 0.26 6<br>EL SALVADOR SLV 0.12 0.18 8 0.24 0.18 8 0.06 0.19 7 0.05 0.19 7 1.07 0.43 5 1.31 0.48 3 0.69 0.28 5<br>EQUATORIAL GUINEA GNQ -1.31 0.22 5 -1.10 0.24 5 -1.21 0.23 5 -1.45 0.24 5 -1.37 0.38 3 -2.08 0.52 2 -0.97 0.67 1<br>ERITREA ERI -1.84 0.21 5 -1.40 0.23 5 -1.34 0.25 4 -1.11 0.26 3 -0.47 0.41 2 0.02 0.63 1 -0.16 0.67 1<br>ESTONIA EST 1.43 0.16 12 1.45 0.16 12 1.45 0.16 11 1.40 0.17 11 1.24 0.31 8 0.95 0.30 6 1.23 0.28 5<br>ETHIOPIA ETH -1.09 0.17 9 -1.05 0.18 9 -1.09 0.18 8 -1.02 0.22 6 -0.69 0.36 5 -0.22 0.34 4 -1.31 0.41 3<br>FIJI FJI -0.35 0.25 3 -0.57 0.26 3 -0.34 0.25 3 -0.12 0.26 3 -0.88 0.51 2 -0.64 0.52 3 -0.52 0.47 2<br>FINLAND FIN 1.74 0.19 8 1.82 0.19 8 1.90 0.18 8 1.93 0.19 8 1.72 0.36 5 1.35 0.28 5 1.26 0.24 6<br>FRANCE FRA 1.09 0.19 8 1.10 0.19 8 1.16 0.18 8 1.19 0.19 8 0.70 0.36 6 0.85 0.28 6 1.04 0.24 6<br>FRENCH GUIANA GUF 0.85 0.31 1 0.49 0.34 1 0.89 0.31 1 0.93 0.31 1 .. .. .. .. .. .. .. .. ..<br>GABON GAB -0.26 0.18 8 -0.39 0.19 8 -0.25 0.18 8 -0.24 0.19 8 -0.36 0.32 5 0.04 0.48 3 -0.53 0.32 4<br>GAMBIA GMB -0.42 0.20 6 -0.35 0.22 6 -0.52 0.21 6 -0.58 0.23 5 -0.08 0.36 4 -0.39 0.48 3 -1.56 0.52 2<br><!-- End of picture text --> 98
<!-- Start of picture text --> TABLE C4: Regulatory Quality (cont.)<br>2005 2004 2003 2002 2000 1998 1996<br>Country Code Est. S.E. N. Est. S.E. N. Est. S.E. N. Est. S.E. N. Est. S.E. N. Est. S.E. N. Est. S.E. N.<br>GEORGIA GEO -0.54 0.19 9 -0.52 0.19 9 -0.58 0.21 7 -0.83 0.22 7 -0.62 0.38 5 -0.81 0.30 5 -0.92 0.34 4<br>GERMANY DEU 1.38 0.19 8 1.39 0.19 8 1.51 0.18 8 1.54 0.19 8 1.30 0.36 6 1.06 0.28 6 1.31 0.24 6<br>GHANA GHA -0.14 0.16 10 -0.36 0.17 10 -0.22 0.18 9 -0.26 0.19 8 0.03 0.32 6 0.26 0.31 6 0.00 0.29 5<br>GREECE GRC 0.91 0.19 8 0.92 0.19 8 1.05 0.18 8 1.11 0.19 8 0.92 0.36 5 0.74 0.28 5 0.76 0.24 6<br>GRENADA GRD 0.36 0.27 2 0.23 0.29 2 0.36 0.28 2 0.38 0.28 2 0.20 0.59 1 0.14 0.63 1 -0.16 0.67 1<br>GUAM GUM 0.60 0.31 1 0.68 0.34 1 .. .. .. .. .. .. .. .. .. .. .. .. .. .. ..<br>GUATEMALA GTM -0.26 0.18 8 -0.11 0.18 8 -0.16 0.19 7 -0.11 0.19 7 0.46 0.43 5 0.75 0.48 3 0.11 0.28 5<br>GUINEA GIN -0.92 0.19 7 -1.06 0.20 7 -0.84 0.21 6 -0.78 0.22 6 -0.16 0.36 4 0.07 0.48 4 0.00 0.41 3<br>GUINEA-BISSAU GNB -1.11 0.21 5 -0.94 0.23 5 -0.94 0.22 5 -0.97 0.23 5 -1.15 0.36 4 -1.31 0.48 4 0.14 0.52 2<br>GUYANA GUY -0.38 0.22 6 -0.25 0.23 5 -0.25 0.22 5 -0.40 0.24 4 -0.11 0.47 3 0.24 0.48 3 0.28 0.41 3<br>HAITI HTI -1.17 0.20 6 -1.35 0.21 6 -1.06 0.22 6 -0.96 0.23 5 -1.21 0.47 4 -1.00 0.48 3 -1.31 0.41 3<br>HONDURAS HND -0.44 0.18 8 -0.36 0.18 8 -0.50 0.19 7 -0.37 0.19 7 0.25 0.43 5 0.50 0.48 3 -0.31 0.28 5<br>HONG KONG HKG 1.89 0.19 8 1.88 0.19 8 1.75 0.18 8 1.43 0.19 8 1.72 0.36 5 1.44 0.28 6 1.75 0.24 6<br>HUNGARY HUN 1.11 0.16 12 1.15 0.16 12 1.10 0.16 11 1.17 0.17 11 1.00 0.31 8 1.04 0.23 8 0.45 0.22 8<br>ICELAND ISL 1.67 0.22 6 1.71 0.23 6 1.66 0.21 6 1.53 0.22 5 1.30 0.43 4 0.74 0.31 4 0.23 0.33 3<br>INDIA IND -0.34 0.17 10 -0.47 0.17 10 -0.46 0.17 9 -0.39 0.18 9 -0.31 0.32 7 -0.14 0.27 7 -0.13 0.23 7<br>INDONESIA IDN -0.45 0.16 11 -0.44 0.17 11 -0.69 0.16 10 -0.71 0.18 10 -0.41 0.29 8 0.04 0.27 6 0.22 0.23 7<br>IRAN IRN -1.49 0.18 8 -1.20 0.18 8 -1.14 0.19 7 -1.27 0.19 7 -1.35 0.46 3 -1.55 0.49 3 -1.45 0.30 4<br>IRAQ IRQ -1.61 0.19 6 -1.61 0.20 6 -1.44 0.21 5 -2.30 0.20 6 -3.47 0.46 3 -3.88 0.49 3 -2.39 0.30 4<br>IRELAND IRL 1.56 0.19 8 1.61 0.19 8 1.60 0.18 8 1.61 0.19 7 1.61 0.36 5 1.38 0.28 6 1.41 0.24 6<br>ISRAEL ISR 0.89 0.19 8 0.85 0.19 8 0.89 0.18 8 0.99 0.19 8 0.84 0.36 5 0.66 0.28 5 1.12 0.24 6<br>ITALY ITA 0.94 0.19 8 1.08 0.19 8 1.13 0.18 8 1.09 0.19 8 0.70 0.36 6 0.72 0.28 6 0.62 0.24 6<br>IVORY COAST CIV -0.95 0.17 9 -0.83 0.18 9 -0.71 0.18 8 -0.41 0.19 8 -0.39 0.32 6 0.07 0.31 6 -0.13 0.29 5<br>JAMAICA JAM 0.24 0.18 8 0.16 0.18 8 0.26 0.19 7 0.28 0.19 7 0.33 0.43 4 0.54 0.48 4 0.52 0.32 4<br>JAPAN JPN 1.17 0.19 8 1.15 0.19 8 1.03 0.18 8 0.95 0.19 8 0.73 0.36 5 0.48 0.28 5 0.71 0.24 6<br>JORDAN JOR 0.16 0.17 10 0.21 0.17 10 0.22 0.17 9 0.07 0.19 8 0.60 0.36 5 0.52 0.31 6 0.10 0.26 6<br>KAZAKHSTAN KAZ -0.47 0.17 11 -0.70 0.17 10 -0.71 0.18 9 -0.74 0.18 9 -0.54 0.37 6 -0.39 0.30 6 -0.32 0.31 4<br>KENYA KEN -0.32 0.16 10 -0.25 0.17 10 -0.27 0.18 9 -0.55 0.19 8 -0.26 0.32 6 -0.17 0.31 6 -0.43 0.29 5<br>KIRIBATI KIR -0.98 0.27 3 -0.59 0.28 3 -0.99 0.36 2 -1.13 0.48 2 -0.85 0.46 2 -0.97 0.63 1 -0.38 0.67 1<br>KOREA, NORTH PRK -2.31 0.19 5 -2.20 0.20 5 -2.05 0.21 4 -1.93 0.26 3 -1.75 0.67 2 -1.73 0.64 2 -2.19 0.47 2<br>KOREA, SOUTH KOR 0.77 0.17 10 0.76 0.17 10 0.67 0.17 9 0.80 0.18 9 0.49 0.32 6 0.23 0.27 7 0.58 0.24 6<br>KUWAIT KWT 0.43 0.20 7 0.48 0.21 6 0.26 0.20 6 0.33 0.20 7 -0.20 0.46 3 -0.12 0.49 3 0.20 0.30 4<br>KYRGYZ REPUBLIC KGZ -0.67 0.19 10 -0.12 0.19 9 -0.36 0.19 8 -0.45 0.22 8 -0.43 0.34 6 -0.75 0.30 5 -0.28 0.39 3<br>LAOS LAO -1.21 0.20 7 -1.24 0.22 6 -1.38 0.22 5 -1.28 0.25 5 -1.30 0.42 3 -1.19 0.52 2 -1.22 0.47 2<br>LATVIA LVA 1.03 0.17 11 1.05 0.17 11 1.01 0.17 10 0.90 0.18 10 0.46 0.34 6 0.63 0.30 6 0.45 0.28 5<br>LEBANON LBN -0.28 0.18 8 -0.30 0.18 8 -0.28 0.19 7 -0.52 0.19 8 0.21 0.38 4 0.45 0.41 4 0.27 0.29 5<br>LESOTHO LSO -0.55 0.21 6 -0.44 0.23 6 -0.60 0.22 6 -0.45 0.24 5 -0.45 0.38 3 0.12 0.35 3 -0.72 0.47 2<br>LIBERIA LBR -1.70 0.21 4 -1.70 0.25 3 -1.59 0.27 2 -1.57 0.26 3 -1.42 0.39 3 -2.31 0.57 2 -3.00 0.52 2<br>LIBYA LBY -1.44 0.18 7 -1.41 0.19 7 -1.65 0.20 6 -1.61 0.20 6 -2.07 0.46 3 -2.93 0.49 3 -1.75 0.30 4<br>LIECHTENSTEIN LIE 1.58 0.31 1 1.51 0.34 1 1.62 0.31 1 1.66 0.31 1 .. .. .. .. .. .. .. .. ..<br>LITHUANIA LTU 1.13 0.17 11 1.18 0.17 11 1.09 0.17 10 1.01 0.18 10 0.50 0.34 7 0.14 0.30 6 0.28 0.28 5<br>LUXEMBOURG LUX 1.79 0.22 6 1.94 0.23 6 1.95 0.21 6 1.91 0.23 5 1.81 0.48 3 1.13 0.31 4 1.47 0.29 4<br>MACAO MAC 1.09 0.31 1 1.53 0.34 1 1.14 0.31 1 0.68 0.31 1 .. .. .. .. .. .. .. .. ..<br>MACEDONIA MKD -0.20 0.17 10 -0.20 0.17 10 -0.20 0.18 9 -0.12 0.19 7 0.06 0.54 2 -0.22 0.36 3 -0.23 0.36 3<br>MADAGASCAR MDG -0.27 0.18 8 -0.08 0.20 8 -0.04 0.21 7 -0.25 0.23 5 -0.24 0.36 5 -0.50 0.48 4 -0.08 0.41 3<br>MALAWI MWI -0.58 0.17 9 -0.51 0.18 9 -0.32 0.18 8 -0.43 0.19 7 -0.17 0.36 5 0.02 0.34 5 -0.39 0.32 4<br>MALAYSIA MYS 0.50 0.17 10 0.57 0.17 10 0.59 0.17 9 0.53 0.18 9 0.28 0.32 7 0.49 0.27 7 0.80 0.23 7<br>MALDIVES MDV 0.50 0.27 3 0.08 0.28 3 0.47 0.24 3 0.69 0.27 3 -0.01 0.46 2 0.14 0.63 1 0.21 0.67 1<br>MALI MLI -0.50 0.18 8 -0.35 0.20 8 -0.41 0.21 7 -0.42 0.22 6 0.17 0.36 4 0.07 0.48 4 0.12 0.41 3<br>MALTA MLT 1.24 0.23 5 1.26 0.24 5 1.21 0.23 5 1.09 0.26 3 0.38 0.67 2 0.46 0.64 2 0.43 0.47 2<br>MARSHALL ISLANDS MHL -0.77 0.47 2 -0.92 0.43 2 -0.77 0.36 2 -0.79 0.48 2 -0.73 0.46 2 -0.85 0.63 1 .. .. ..<br>MARTINIQUE MTQ 0.85 0.31 1 0.77 0.34 1 0.89 0.31 1 0.93 0.31 1 .. .. .. .. .. .. .. .. ..<br>MAURITANIA MRT -0.14 0.22 5 -0.06 0.24 5 -0.10 0.23 5 0.06 0.24 4 -0.45 0.38 3 -0.51 0.52 2 -0.69 0.47 2<br>MAURITIUS MUS 0.32 0.18 7 0.43 0.20 6 0.46 0.20 6 0.50 0.20 6 0.66 0.36 4 0.55 0.35 4 0.14 0.41 2<br>MEXICO MEX 0.33 0.17 10 0.46 0.17 10 0.43 0.17 9 0.42 0.18 9 0.56 0.32 7 0.68 0.27 7 0.48 0.23 7<br>MICRONESIA FSM 0.19 0.27 3 -0.05 0.28 3 -0.59 0.36 2 -0.69 0.48 2 -0.63 0.46 2 -0.73 0.63 1 .. .. ..<br>MOLDOVA MDA -0.43 0.17 11 -0.54 0.17 10 -0.39 0.18 9 -0.19 0.18 8 -1.17 0.37 6 -0.43 0.30 6 0.04 0.28 5<br>MONGOLIA MNG -0.32 0.19 8 -0.22 0.20 7 -0.40 0.20 6 -0.13 0.23 5 0.30 0.40 4 0.20 0.48 3 -0.71 0.41 3<br>MOROCCO MAR -0.39 0.16 10 -0.14 0.17 10 -0.13 0.18 9 -0.04 0.18 9 0.24 0.32 5 0.27 0.31 6 0.11 0.29 5<br>MOZAMBIQUE MOZ -0.60 0.18 9 -0.43 0.19 9 -0.46 0.20 8 -0.55 0.22 6 -0.12 0.36 4 -0.40 0.34 5 -1.07 0.41 3<br>MYANMAR MMR -2.19 0.18 7 -2.28 0.19 7 -2.02 0.20 6 -1.87 0.20 6 -1.46 0.46 3 -1.25 0.49 3 -1.18 0.30 4<br>NAMIBIA NAM 0.11 0.16 10 0.33 0.17 10 0.16 0.18 9 0.23 0.18 9 0.27 0.36 5 0.46 0.34 4 -0.03 0.37 3<br>NEPAL NPL -0.59 0.18 8 -0.64 0.19 7 -0.49 0.19 6 -0.54 0.25 5 -0.46 0.42 3 -0.38 0.52 2 -0.26 0.47 2<br>NETHERLANDS NLD 1.64 0.19 8 1.73 0.19 8 1.75 0.18 8 1.87 0.19 8 1.82 0.36 5 1.36 0.28 5 1.49 0.24 6<br>NETHERLANDS ANTILLES ANT 0.85 0.31 1 0.61 0.34 1 .. .. .. .. .. .. .. .. .. .. .. .. .. .. ..<br>NEW ZEALAND NZL 1.66 0.19 8 1.78 0.19 8 1.72 0.18 8 1.68 0.19 7 1.37 0.36 5 1.44 0.28 5 1.70 0.24 6<br>NICARAGUA NIC -0.31 0.18 8 -0.22 0.18 8 -0.27 0.19 7 -0.44 0.19 7 0.25 0.43 5 0.37 0.48 3 -0.19 0.28 5<br>NIGER NER -0.53 0.19 7 -0.66 0.20 7 -0.60 0.21 6 -0.69 0.23 5 -0.33 0.36 4 -0.51 0.48 3 -0.96 0.41 3<br><!-- End of picture text --> 99
# **TABLE C4: Regulatory Quality (cont.)**

<!-- Start of picture text --> 2005 2004 2003 2002 2000 1998 1996<br>Country Code Est. S.E. N. Est. S.E. N. Est. S.E. N. Est. S.E. N. Est. S.E. N. Est. S.E. N. Est. S.E. N.<br>NIGERIA NGA -1.01 0.16 10 -1.28 0.17 10 -1.24 0.18 9 -1.22 0.18 9 -0.45 0.30 7 -0.56 0.31 6 -1.02 0.29 5<br>NORWAY NOR 1.46 0.19 8 1.50 0.19 8 1.44 0.18 8 1.50 0.19 7 0.87 0.36 5 1.11 0.28 5 1.17 0.24 6<br>OMAN OMN 0.49 0.20 6 0.53 0.21 6 0.59 0.20 6 0.60 0.20 7 0.71 0.46 3 0.36 0.49 3 0.46 0.30 4<br>PAKISTAN PAK -0.60 0.17 10 -0.89 0.17 10 -0.78 0.17 9 -0.83 0.19 8 -0.81 0.34 6 -0.20 0.31 5 -0.54 0.29 5<br>PANAMA PAN 0.25 0.17 9 0.32 0.19 8 0.32 0.18 8 0.45 0.19 8 0.92 0.36 6 1.12 0.41 4 0.55 0.29 5<br>PAPUA NEW GUINEA PNG -0.86 0.18 8 -0.82 0.19 8 -0.63 0.18 7 -0.49 0.20 6 -0.67 0.34 5 -0.52 0.48 3 -0.75 0.37 3<br>PARAGUAY PRY -0.77 0.18 8 -0.60 0.18 8 -0.67 0.19 7 -0.59 0.19 7 -0.86 0.43 4 -0.31 0.48 4 0.75 0.32 4<br>PERU PER 0.10 0.17 9 0.14 0.18 9 0.21 0.18 8 0.17 0.19 8 0.50 0.36 6 0.78 0.31 6 0.49 0.26 6<br>PHILIPPINES PHL -0.02 0.17 10 -0.20 0.17 10 0.06 0.17 9 0.02 0.18 9 0.28 0.32 7 0.61 0.27 6 0.40 0.23 7<br>POLAND POL 0.82 0.16 12 0.77 0.16 12 0.54 0.16 11 0.62 0.17 11 0.64 0.31 8 0.75 0.23 8 0.38 0.22 8<br>PORTUGAL PRT 1.20 0.19 8 1.22 0.19 8 1.30 0.18 8 1.45 0.19 7 0.97 0.36 6 1.07 0.28 6 1.20 0.24 6<br>PUERTO RICO PRI 1.01 0.28 3 0.83 0.30 3 1.09 0.28 3 1.21 0.30 2 1.12 0.57 1 1.03 0.64 1 0.88 0.54 1<br>QATAR QAT 0.20 0.20 7 0.14 0.21 6 0.15 0.20 6 0.11 0.20 6 0.44 0.46 3 0.39 0.49 3 0.28 0.34 3<br>REUNION REU 1.09 0.31 1 1.15 0.34 1 .. .. .. .. .. .. .. .. .. .. .. .. .. .. ..<br>ROMANIA ROM 0.17 0.16 12 0.13 0.16 12 -0.20 0.16 11 0.01 0.18 10 -0.31 0.34 7 0.23 0.30 5 -0.59 0.27 6<br>RUSSIA RUS -0.29 0.16 12 -0.23 0.16 12 -0.34 0.16 11 -0.38 0.17 11 -1.64 0.31 8 -0.39 0.23 8 -0.64 0.22 8<br>RWANDA RWA -0.73 0.20 5 -0.70 0.22 5 -0.68 0.24 4 -0.92 0.24 4 -0.61 0.38 3 -0.96 0.52 2 -1.11 0.67 1<br>SAMOA SAM 0.01 0.27 3 -0.07 0.28 3 -0.07 0.24 3 -0.09 0.27 3 -0.10 0.42 3 -0.73 0.63 1 -0.23 0.67 1<br>SAO TOME AND PRINCIPE STP -0.84 0.24 3 -0.79 0.27 3 -0.62 0.26 3 -0.46 0.26 3 -0.59 0.41 2 -0.97 0.63 1 -0.38 0.67 1<br>SAUDI ARABIA SAU -0.01 0.18 7 -0.06 0.19 7 0.01 0.20 6 0.02 0.20 7 -0.17 0.46 3 -0.19 0.49 3 -0.13 0.30 4<br>SENEGAL SEN -0.30 0.17 8 -0.27 0.18 8 -0.20 0.18 8 -0.26 0.19 7 -0.12 0.36 5 -0.30 0.48 4 -0.53 0.32 4<br>SEYCHELLES SYC -0.09 0.24 4 -0.49 0.26 4 -0.37 0.25 4 -0.52 0.26 3 -1.40 0.41 2 -1.22 0.63 1 -1.19 0.67 1<br>SIERRA LEONE SLE -0.94 0.19 6 -1.10 0.21 6 -1.20 0.22 5 -1.31 0.24 4 -1.11 0.36 4 -1.41 0.48 3 -0.51 0.41 3<br>SINGAPORE SGP 1.79 0.17 9 1.89 0.18 9 1.89 0.18 8 1.88 0.19 8 2.07 0.36 6 1.51 0.28 6 1.95 0.24 6<br>SLOVAK REPUBLIC SVK 1.16 0.16 12 1.14 0.16 12 0.91 0.16 11 0.73 0.17 11 0.29 0.31 8 0.22 0.25 7 0.30 0.24 7<br>SLOVENIA SVN 0.86 0.17 11 0.93 0.17 11 0.85 0.16 11 0.83 0.17 11 0.58 0.31 8 0.65 0.30 5 0.45 0.28 5<br>SOLOMON ISLANDS SLB -1.05 0.27 3 -1.38 0.28 3 -2.38 0.36 2 -1.92 0.48 2 -1.61 0.46 2 -1.10 0.63 1 -1.26 0.67 1<br>SOMALIA SOM -2.35 0.21 4 -2.35 0.25 3 -2.06 0.27 2 -2.05 0.28 2 -2.46 0.47 3 -2.47 0.48 3 -3.00 0.52 2<br>SOUTH AFRICA ZAF 0.59 0.16 11 0.55 0.17 11 0.56 0.17 10 0.50 0.17 10 -0.03 0.28 8 0.36 0.27 7 0.16 0.23 7<br>SPAIN ESP 1.25 0.19 8 1.31 0.19 8 1.32 0.18 8 1.38 0.19 8 1.31 0.36 6 1.04 0.28 6 0.99 0.24 6<br>SRI LANKA LKA -0.12 0.17 10 0.08 0.17 10 0.13 0.17 9 0.14 0.19 9 0.25 0.32 6 0.63 0.41 4 0.41 0.29 5<br>ST. KITTS AND NEVIS KNA 1.14 0.27 2 0.05 0.29 2 0.15 0.51 1 0.12 0.54 1 0.20 0.59 1 0.39 0.63 1 -0.16 0.67 1<br>ST. LUCIA LCA 1.14 0.27 2 0.16 0.29 2 0.15 0.51 1 0.12 0.54 1 0.20 0.59 1 0.39 0.63 1 -0.16 0.67 1<br>ST. VINCENT AND THE GRENADINES VCT 1.14 0.27 2 0.18 0.29 2 0.15 0.51 1 0.12 0.54 1 0.20 0.59 1 0.27 0.63 1 -0.23 0.67 1<br>SUDAN SDN -1.29 0.17 8 -1.12 0.19 8 -1.19 0.19 7 -1.22 0.19 7 -0.90 0.32 5 -1.15 0.48 3 -1.70 0.32 4<br>SURINAME SUR -0.46 0.24 4 -0.49 0.25 4 -0.58 0.24 4 -0.64 0.26 3 -1.04 0.67 2 -0.73 0.64 2 -0.68 0.47 2<br>SWAZILAND SWZ -0.44 0.21 6 -0.42 0.23 6 -0.50 0.22 6 -0.17 0.24 5 -0.44 0.38 3 0.49 0.35 3 -0.01 0.47 2<br>SWEDEN SWE 1.47 0.19 8 1.63 0.19 8 1.68 0.18 8 1.68 0.19 7 1.30 0.36 6 1.01 0.28 5 1.16 0.24 6<br>SWITZERLAND CHE 1.47 0.19 8 1.56 0.19 8 1.59 0.18 8 1.59 0.19 7 1.47 0.36 5 1.05 0.28 6 1.25 0.24 6<br>SYRIA SYR -1.22 0.18 7 -0.93 0.19 7 -0.94 0.20 6 -0.97 0.20 6 -0.85 0.46 3 -1.14 0.49 3 -0.80 0.30 4<br>TAIWAN TWN 1.07 0.17 9 1.11 0.18 9 1.04 0.18 8 1.00 0.19 8 0.94 0.36 5 0.99 0.28 5 1.03 0.24 6<br>TAJIKISTAN TJK -1.05 0.19 10 -1.05 0.19 9 -1.09 0.19 8 -1.29 0.22 8 -1.39 0.34 5 -1.70 0.30 4 -1.89 0.39 3<br>TANZANIA TZA -0.51 0.16 10 -0.48 0.17 10 -0.33 0.18 9 -0.53 0.19 8 0.00 0.32 6 0.19 0.31 6 -0.35 0.29 5<br>THAILAND THA 0.38 0.17 10 0.12 0.17 10 0.31 0.17 9 0.28 0.18 9 0.68 0.32 7 0.21 0.27 7 0.42 0.23 7<br>TIMOR, EAST TMP -1.09 0.29 2 -1.16 0.32 2 -1.41 0.26 2 -1.28 0.31 1 .. .. .. .. .. .. .. .. ..<br>TOGO TGO -0.81 0.19 7 -0.73 0.20 7 -0.65 0.21 6 -0.64 0.23 5 -0.54 0.36 4 -0.67 0.48 4 0.36 0.52 2<br>TONGA TON -0.69 0.27 3 -0.76 0.28 3 -1.06 0.36 2 -1.25 0.48 2 -0.25 0.46 2 -1.10 0.63 1 -0.16 0.67 1<br>TRINIDAD AND TOBAGO TTO 0.65 0.19 8 0.70 0.19 7 0.71 0.19 7 0.64 0.20 6 0.73 0.43 5 0.73 0.48 3 0.44 0.32 4<br>TUNISIA TUN -0.07 0.16 10 -0.09 0.17 10 0.05 0.18 9 -0.05 0.18 9 0.30 0.32 6 0.55 0.31 5 0.29 0.29 5<br>TURKEY TUR 0.18 0.17 11 0.07 0.17 11 0.06 0.17 10 0.02 0.18 10 0.31 0.32 7 0.75 0.27 7 0.44 0.23 7<br>TURKMENISTAN TKM -1.95 0.19 7 -1.95 0.20 7 -1.99 0.21 6 -1.93 0.22 6 -2.23 0.38 4 -2.41 0.30 4 -2.60 0.39 3<br>TUVALU TUV -0.37 0.31 1 -0.05 0.32 2 0.09 0.44 1 0.33 0.71 1 0.35 0.62 1 .. .. .. .. .. ..<br>UGANDA UGA 0.01 0.16 10 -0.04 0.17 10 0.06 0.18 9 -0.05 0.19 8 0.08 0.32 6 0.46 0.31 6 0.14 0.29 5<br>UKRAINE UKR -0.26 0.17 11 -0.48 0.17 11 -0.62 0.17 10 -0.66 0.18 10 -1.28 0.34 7 -0.88 0.25 7 -0.63 0.26 6<br>UNITED ARAB EMIRATES ARE 0.44 0.18 8 1.03 0.20 7 0.82 0.20 6 0.94 0.20 7 0.45 0.46 3 0.35 0.49 3 0.90 0.30 4<br>UNITED KINGDOM GBR 1.53 0.19 8 1.74 0.19 8 1.69 0.18 8 1.75 0.19 8 1.53 0.36 6 1.44 0.28 6 1.58 0.24 6<br>UNITED STATES USA 1.47 0.19 8 1.46 0.19 8 1.44 0.18 8 1.44 0.19 8 1.45 0.36 6 1.35 0.28 6 1.39 0.24 6<br>URUGUAY URY 0.26 0.17 9 0.31 0.18 9 0.34 0.18 8 0.45 0.19 8 0.93 0.36 6 0.92 0.41 4 0.92 0.29 5<br>UZBEKISTAN UZB -1.71 0.17 10 -1.67 0.17 10 -1.66 0.17 9 -1.47 0.19 9 -1.46 0.34 6 -1.80 0.30 5 -1.40 0.31 4<br>VANUATU VUT 0.05 0.27 3 -0.44 0.28 3 -1.29 0.36 2 -1.23 0.48 2 -0.81 0.46 2 -0.35 0.63 1 -0.09 0.67 1<br>VENEZUELA VEN -1.15 0.17 10 -1.11 0.17 10 -1.16 0.17 9 -0.57 0.18 9 -0.65 0.32 7 0.08 0.27 7 -0.19 0.23 7<br>VIETNAM VNM -0.64 0.17 10 -0.60 0.17 10 -0.54 0.17 9 -0.71 0.19 9 -0.72 0.32 6 -0.61 0.31 5 -0.48 0.26 6<br>VIRGIN ISLANDS (U.S.) VIR 1.09 0.31 1 1.22 0.34 1 .. .. .. .. .. .. .. .. .. .. .. .. .. .. ..<br>WEST BANK WBG -1.14 0.29 2 -0.89 0.32 2 -1.09 0.30 2 -1.01 0.30 2 0.58 1.19 1 -0.21 1.20 1 .. .. ..<br>YEMEN YEM -0.83 0.18 7 -1.02 0.19 7 -0.71 0.19 6 -0.64 0.20 6 -0.50 0.47 3 -0.43 0.48 3 -0.69 0.32 4<br>YUGOSLAVIA YUG -0.53 0.17 10 -0.52 0.17 10 -0.68 0.18 9 -0.62 0.18 9 -0.90 0.88 1 -1.90 0.88 1 -1.45 0.36 3<br>ZAMBIA ZMB -0.62 0.17 9 -0.57 0.17 10 -0.59 0.18 9 -0.59 0.19 8 0.25 0.32 6 -0.06 0.31 6 0.31 0.29 5<br>ZIMBABWE ZWE -2.20 0.16 10 -2.27 0.17 10 -2.20 0.18 9 -1.74 0.18 9 -1.67 0.30 7 -0.43 0.31 6 -0.81 0.26 6<br><!-- End of picture text --> 100
<!-- Start of picture text --> TABLE C5: Rule of Law<br>2005 2004 2003 2002 2000 1998 1996<br>Country Code Est. S.E. N. Est. S.E. N. Est. S.E. N. Est. S.E. N. Est. S.E. N. Est. S.E. N. Est. S.E. N.<br>AFGHANISTAN AFG -1.68 0.21 6 -1.81 0.18 8 -1.68 0.18 6 -1.70 0.25 4 -2.37 0.42 2 -1.23 0.77 1 -1.25 0.79 1<br>ALBANIA ALB -0.84 0.16 11 -0.87 0.16 10 -0.90 0.17 9 -0.99 0.17 9 -0.87 0.18 9 -1.03 0.23 7 -0.37 0.27 5<br>ALGERIA DZA -0.71 0.14 14 -0.71 0.13 14 -0.59 0.14 12 -0.65 0.15 11 -0.90 0.18 9 -0.92 0.22 7 -0.67 0.19 6<br>AMERICAN SAMOA ASM 1.15 0.35 1 0.84 0.33 1 .. .. .. .. .. .. .. .. .. .. .. .. .. .. ..<br>ANDORRA ADO 1.03 0.33 2 1.39 0.32 2 1.20 0.32 1 1.47 0.33 1 .. .. .. .. .. .. .. .. ..<br>ANGOLA AGO -1.28 0.15 13 -1.34 0.14 12 -1.34 0.15 11 -1.55 0.16 11 -1.52 0.18 10 -1.38 0.20 8 -1.50 0.19 6<br>ANGUILLA AIA 1.67 0.35 1 1.14 0.33 1 .. .. .. .. .. .. .. .. .. .. .. .. .. .. ..<br>ANTIGUA AND BARBUDA ATG 0.73 0.33 2 0.93 0.32 2 0.94 0.32 1 0.95 0.33 1 .. .. .. .. .. .. .. .. ..<br>ARGENTINA ARG -0.56 0.13 15 -0.72 0.12 16 -0.57 0.13 15 -0.87 0.13 15 0.07 0.15 14 0.06 0.18 11 0.24 0.16 10<br>ARMENIA ARM -0.46 0.14 13 -0.58 0.14 13 -0.47 0.15 11 -0.53 0.16 11 -0.60 0.17 9 -0.46 0.20 8 -0.51 0.24 5<br>ARUBA ABW 0.88 0.35 1 0.91 0.33 1 .. .. .. .. .. .. .. .. .. .. .. .. .. .. ..<br>AUSTRALIA AUS 1.80 0.14 12 1.83 0.13 13 1.85 0.13 13 1.77 0.14 11 1.89 0.16 10 1.91 0.20 9 1.85 0.16 9<br>AUSTRIA AUT 1.87 0.14 12 1.79 0.13 12 1.83 0.14 12 1.83 0.14 12 1.94 0.17 11 1.93 0.20 10 1.95 0.16 9<br>AZERBAIJAN AZE -0.84 0.13 15 -0.89 0.12 16 -0.84 0.13 14 -0.87 0.13 13 -1.09 0.16 11 -0.93 0.19 9 -0.91 0.17 6<br>BAHAMAS BHS 1.33 0.24 4 1.31 0.24 4 1.29 0.25 3 1.25 0.25 3 0.99 0.42 2 0.85 0.46 2 0.76 0.47 2<br>BAHRAIN BHR 0.71 0.15 11 0.78 0.14 12 0.85 0.15 9 0.84 0.15 10 0.47 0.21 8 0.68 0.24 6 0.70 0.19 6<br>BANGLADESH BGD -0.87 0.14 14 -0.89 0.13 14 -0.79 0.13 13 -0.83 0.14 13 -0.71 0.18 11 -0.77 0.22 7 -0.74 0.19 6<br>BARBADOS BRB 1.22 0.23 4 1.19 0.23 4 1.27 0.24 3 1.34 0.27 2 1.22 0.48 1 0.43 0.54 1 -0.33 0.56 1<br>BELARUS BLR -1.04 0.16 11 -1.22 0.15 12 -1.20 0.16 11 -1.14 0.17 10 -1.11 0.18 10 -1.17 0.23 7 -1.07 0.28 4<br>BELGIUM BEL 1.47 0.14 12 1.50 0.13 12 1.47 0.14 12 1.42 0.14 12 1.53 0.17 11 1.24 0.20 9 1.62 0.16 9<br>BELIZE BLZ 0.02 0.21 6 0.07 0.21 6 0.18 0.21 6 -0.13 0.23 5 0.27 0.30 4 -0.08 0.34 3 0.66 0.50 2<br>BENIN BEN -0.59 0.17 10 -0.60 0.18 9 -0.51 0.20 8 -0.34 0.22 7 -0.46 0.26 6 -0.48 0.31 4 -0.05 0.50 2<br>BERMUDA BMU 0.88 0.35 1 1.09 0.33 1 1.20 0.32 1 1.21 0.33 1 .. .. .. .. .. .. .. .. ..<br>BHUTAN BTN 0.52 0.24 6 0.39 0.23 5 0.36 0.22 5 0.18 0.25 4 -0.48 0.36 3 -0.17 0.41 2 -1.25 0.79 1<br>BOLIVIA BOL -0.78 0.14 14 -0.59 0.13 13 -0.44 0.14 12 -0.67 0.14 13 -0.58 0.17 11 -0.45 0.21 9 -0.71 0.19 7<br>BOSNIA-HERZEGOVINA BIH -0.74 0.15 11 -0.75 0.14 12 -1.01 0.16 10 -0.99 0.17 11 -0.96 0.21 7 -1.12 0.26 4 -0.24 0.79 1<br>BOTSWANA BWA 0.70 0.14 12 0.70 0.14 13 0.71 0.14 12 0.62 0.14 12 0.56 0.19 10 0.50 0.23 7 0.76 0.21 5<br>BRAZIL BRA -0.41 0.13 15 -0.34 0.12 16 -0.28 0.13 15 -0.37 0.13 16 -0.21 0.15 14 -0.17 0.18 12 -0.31 0.16 10<br>BRUNEI BRN 0.45 0.31 3 0.53 0.30 3 0.54 0.29 3 0.52 0.30 4 0.79 0.58 2 0.78 0.58 2 0.66 0.59 2<br>BULGARIA BGR -0.19 0.13 14 -0.08 0.12 15 -0.06 0.13 14 -0.07 0.13 15 -0.22 0.14 13 -0.31 0.19 9 -0.14 0.17 7<br>BURKINA FASO BFA -0.54 0.19 10 -0.63 0.18 9 -0.49 0.20 8 -0.55 0.22 7 -0.61 0.25 7 -0.52 0.29 5 -0.81 0.44 3<br>BURUNDI BDI -1.17 0.19 8 -1.40 0.22 7 -1.52 0.24 6 -1.44 0.26 5 -1.01 0.22 6 -0.93 0.34 3 -0.24 0.79 1<br>CAMBODIA KHM -1.13 0.16 10 -1.12 0.17 10 -1.05 0.18 8 -0.94 0.19 8 -0.83 0.23 7 -0.83 0.28 4 -0.97 0.40 2<br>CAMEROON CMR -1.02 0.15 12 -1.12 0.15 11 -1.02 0.15 11 -1.23 0.16 11 -1.06 0.20 10 -0.85 0.22 8 -1.24 0.21 5<br>CANADA CAN 1.81 0.14 12 1.80 0.13 13 1.79 0.13 13 1.72 0.13 14 1.87 0.16 13 1.83 0.20 10 1.84 0.16 9<br>CAPE VERDE CPV 0.21 0.21 6 0.14 0.20 6 -0.01 0.21 5 0.04 0.21 5 0.36 0.29 3 0.57 0.36 2 0.04 0.56 1<br>CAYMAN ISLANDS CYM 0.88 0.35 1 1.14 0.33 1 1.20 0.32 1 1.47 0.33 1 .. .. .. .. .. .. .. .. ..<br>CENTRAL AFRICAN REPUBLIC CAF -1.29 0.19 8 -1.54 0.19 7 -1.50 0.21 6 -1.09 0.23 5 -0.74 0.33 3 -0.96 0.41 2 -0.24 0.79 1<br>CHAD TCD -1.23 0.18 9 -1.17 0.18 9 -1.09 0.20 7 -0.87 0.22 6 -0.89 0.28 4 -1.07 0.31 4 -0.24 0.79 1<br>CHILE CHL 1.20 0.13 15 1.21 0.12 16 1.17 0.13 15 1.18 0.13 14 1.23 0.15 14 1.18 0.18 11 1.22 0.16 10<br>CHINA CHN -0.47 0.13 15 -0.41 0.12 15 -0.41 0.13 14 -0.28 0.13 14 -0.42 0.15 13 -0.35 0.19 10 -0.50 0.16 9<br>COLOMBIA COL -0.71 0.13 16 -0.74 0.12 15 -0.83 0.13 14 -0.86 0.13 15 -0.73 0.15 15 -0.72 0.18 12 -0.51 0.16 10<br>COMOROS COM -0.96 0.26 4 -0.93 0.25 4 -0.99 0.26 3 -1.05 0.27 3 -1.26 0.35 2 -1.06 0.44 1 .. .. ..<br>CONGO COG -1.42 0.17 9 -1.17 0.17 9 -1.23 0.18 9 -1.29 0.19 9 -1.26 0.22 7 -1.31 0.25 6 -1.33 0.32 4<br>Congo, Dem. Rep. (Zaire) ZAR -1.76 0.16 11 -1.76 0.15 12 -1.69 0.15 11 -1.84 0.19 10 -1.94 0.20 9 -2.04 0.25 6 -1.89 0.29 5<br>COOK ISLANDS COK .. .. .. 0.63 0.57 1 0.75 0.46 1 0.86 0.47 1 0.65 0.75 1 .. .. .. .. .. ..<br>COSTA RICA CRI 0.54 0.14 13 0.57 0.13 14 0.70 0.14 13 0.61 0.14 14 0.72 0.17 12 0.81 0.20 10 0.60 0.18 8<br>CROATIA HRV 0.00 0.13 14 0.05 0.12 14 0.05 0.13 13 0.04 0.13 14 0.08 0.16 10 -0.20 0.19 8 -0.58 0.17 6<br>CUBA CUB -1.14 0.16 10 -1.19 0.14 11 -1.21 0.15 10 -0.98 0.16 10 -0.73 0.21 7 -0.62 0.24 6 -0.79 0.19 6<br>CYPRUS CYP 0.85 0.15 9 0.82 0.15 10 0.85 0.15 9 0.72 0.16 8 0.95 0.22 6 0.87 0.24 6 0.57 0.19 6<br>CZECH REPUBLIC CZE 0.70 0.12 15 0.65 0.12 16 0.69 0.12 15 0.65 0.12 15 0.51 0.14 14 0.59 0.17 12 0.60 0.15 10<br>DENMARK DNK 1.99 0.14 12 1.95 0.13 13 1.94 0.13 13 1.91 0.14 13 1.87 0.16 11 1.92 0.20 9 2.00 0.16 9<br>DJIBOUTI DJI -0.87 0.21 6 -0.78 0.21 5 -0.74 0.22 4 -0.62 0.23 4 -0.64 0.29 3 -0.43 0.36 2 .. .. ..<br>DOMINICA DMA 0.66 0.28 3 0.61 0.26 3 0.57 0.27 2 0.60 0.29 2 -0.41 0.41 1 -0.44 0.44 1 .. .. ..<br>DOMINICAN REPUBLIC DOM -0.66 0.14 13 -0.54 0.13 13 -0.44 0.14 11 -0.50 0.14 12 -0.27 0.17 11 -0.22 0.23 6 -0.57 0.20 5<br>ECUADOR ECU -0.84 0.14 14 -0.70 0.13 14 -0.64 0.14 13 -0.69 0.14 12 -0.74 0.16 12 -0.73 0.20 10 -0.45 0.18 8<br>EGYPT EGY 0.02 0.13 15 -0.02 0.13 15 0.01 0.13 14 0.01 0.14 13 0.10 0.15 12 0.01 0.20 9 0.19 0.17 8<br>EL SALVADOR SLV -0.37 0.15 11 -0.40 0.15 11 -0.43 0.16 10 -0.50 0.16 10 -0.59 0.20 10 -0.43 0.24 7 -0.53 0.21 6<br>EQUATORIAL GUINEA GNQ -1.33 0.20 7 -1.33 0.20 7 -1.12 0.21 6 -1.24 0.22 6 -1.58 0.29 3 -1.77 0.36 2 .. .. ..<br>ERITREA ERI -0.81 0.22 7 -0.73 0.21 7 -0.66 0.23 6 -0.34 0.26 4 -0.17 0.31 4 -0.15 0.41 2 -0.24 0.79 1<br>ESTONIA EST 0.82 0.12 15 0.88 0.12 16 0.74 0.13 15 0.72 0.13 15 0.63 0.14 13 0.44 0.19 9 0.30 0.17 6<br>ETHIOPIA ETH -0.77 0.15 12 -0.80 0.15 12 -0.73 0.16 11 -0.41 0.21 9 -0.47 0.25 8 -0.16 0.29 5 -0.32 0.44 3<br>FIJI FJI -0.25 0.23 4 -0.09 0.21 5 -0.14 0.21 5 -0.41 0.23 5 -0.77 0.31 3 -0.50 0.31 4 0.05 0.50 2<br>FINLAND FIN 1.96 0.14 12 1.94 0.13 12 1.95 0.14 12 1.90 0.14 13 2.02 0.16 11 1.98 0.20 9 2.05 0.16 9<br>FRANCE FRA 1.35 0.14 12 1.39 0.13 13 1.40 0.13 13 1.31 0.14 13 1.36 0.16 13 1.35 0.20 10 1.62 0.16 9<br>FRENCH GUIANA GUF 0.88 0.35 1 0.54 0.33 1 0.94 0.32 1 0.95 0.33 1 .. .. .. .. .. .. .. .. ..<br>GABON GAB -0.48 0.15 11 -0.60 0.14 11 -0.53 0.15 11 -0.32 0.15 11 -0.65 0.18 10 -0.56 0.23 6 -0.36 0.20 5<br>GAMBIA GMB -0.29 0.18 8 -0.28 0.18 9 -0.14 0.19 9 -0.49 0.21 8 -0.44 0.27 5 -0.40 0.32 4 0.20 0.59 2<br>GEORGIA GEO -0.82 0.14 12 -0.83 0.13 14 -1.13 0.15 11 -1.25 0.16 12 -0.65 0.17 10 -0.84 0.21 7 -0.90 0.24 5<br>GERMANY DEU 1.76 0.14 12 1.71 0.13 13 1.72 0.13 13 1.69 0.13 14 1.84 0.16 13 1.85 0.20 10 1.86 0.16 9<br><!-- End of picture text --> 101
<!-- Start of picture text --> TABLE C5: Rule of Law (cont.)<br>2005 2004 2003 2002 2000 1998 1996<br>Country Code Est. S.E. N. Est. S.E. N. Est. S.E. N. Est. S.E. N. Est. S.E. N. Est. S.E. N. Est. S.E. N.<br>GHANA GHA -0.23 0.14 14 -0.21 0.13 15 -0.21 0.13 14 -0.24 0.14 13 -0.11 0.17 12 -0.23 0.20 9 -0.17 0.19 6<br>GREECE GRC 0.66 0.14 12 0.74 0.13 12 0.74 0.14 12 0.68 0.14 12 0.66 0.17 10 0.65 0.20 9 0.74 0.16 9<br>GRENADA GRD 0.32 0.28 3 0.28 0.26 3 0.19 0.27 2 0.20 0.29 2 0.29 0.41 1 0.19 0.44 1 .. .. ..<br>GUAM GUM 1.15 0.35 1 0.99 0.33 1 .. .. .. .. .. .. .. .. .. .. .. .. .. .. ..<br>GUATEMALA GTM -1.04 0.14 12 -0.98 0.14 14 -0.96 0.15 12 -0.92 0.15 13 -0.87 0.18 11 -0.87 0.21 8 -0.70 0.19 7<br>GUINEA GIN -1.11 0.19 9 -1.11 0.18 9 -0.95 0.20 8 -0.78 0.21 7 -1.04 0.27 5 -0.98 0.29 5 -1.13 0.44 3<br>GUINEA-BISSAU GNB -1.33 0.21 7 -1.16 0.20 7 -1.19 0.20 7 -1.16 0.22 6 -1.33 0.26 6 -1.31 0.29 5 -1.65 0.59 2<br>GUYANA GUY -0.80 0.18 8 -0.63 0.20 7 -0.48 0.21 7 -0.52 0.23 5 -0.23 0.28 5 -0.03 0.32 4 -0.03 0.44 3<br>HAITI HTI -1.62 0.20 7 -1.67 0.18 10 -1.63 0.19 8 -1.91 0.20 8 -1.53 0.27 7 -1.05 0.32 4 -1.29 0.44 3<br>HONDURAS HND -0.78 0.14 13 -0.70 0.14 13 -0.81 0.15 12 -0.88 0.15 12 -0.98 0.18 11 -0.79 0.21 8 -0.90 0.19 7<br>HONG KONG HKG 1.50 0.14 10 1.38 0.14 10 1.33 0.14 10 1.17 0.14 11 1.44 0.18 9 1.52 0.21 8 1.67 0.17 7<br>HUNGARY HUN 0.70 0.12 16 0.75 0.11 17 0.78 0.12 16 0.79 0.12 16 0.77 0.13 15 0.73 0.17 12 0.62 0.15 10<br>ICELAND ISL 2.10 0.16 8 2.03 0.17 8 2.02 0.17 8 1.92 0.18 7 1.95 0.21 7 1.82 0.26 6 1.67 0.26 5<br>INDIA IND 0.09 0.13 14 -0.01 0.12 15 0.03 0.13 14 -0.02 0.13 15 0.15 0.15 13 0.13 0.18 11 -0.06 0.16 9<br>INDONESIA IDN -0.87 0.13 15 -0.82 0.12 17 -0.89 0.12 15 -0.97 0.13 16 -1.03 0.15 14 -1.06 0.19 10 -0.41 0.16 9<br>IRAN IRN -0.76 0.14 13 -0.69 0.13 13 -0.59 0.14 12 -0.58 0.14 11 -0.51 0.19 8 -0.54 0.23 7 -0.83 0.18 7<br>IRAQ IRQ -1.81 0.17 8 -1.94 0.16 8 -1.52 0.17 7 -1.70 0.16 8 -1.55 0.21 7 -1.70 0.24 6 -1.63 0.19 6<br>IRELAND IRL 1.63 0.14 12 1.58 0.13 12 1.57 0.13 12 1.61 0.14 12 1.71 0.16 11 1.68 0.20 10 1.73 0.16 9<br>ISRAEL ISR 0.76 0.14 11 0.75 0.14 12 0.79 0.14 12 0.90 0.14 13 0.96 0.17 10 1.01 0.21 8 1.14 0.16 9<br>ITALY ITA 0.51 0.14 12 0.64 0.13 12 0.79 0.14 12 0.76 0.14 13 0.88 0.16 13 1.03 0.20 10 0.85 0.16 9<br>IVORY COAST CIV -1.47 0.16 11 -1.45 0.15 12 -1.40 0.15 11 -1.26 0.16 11 -0.68 0.20 9 -0.51 0.22 8 -0.74 0.21 5<br>JAMAICA JAM -0.55 0.14 11 -0.44 0.14 11 -0.61 0.15 10 -0.52 0.15 10 -0.25 0.19 7 -0.35 0.22 7 -0.26 0.20 5<br>JAPAN JPN 1.33 0.14 12 1.35 0.13 13 1.34 0.13 13 1.31 0.13 14 1.66 0.16 12 1.63 0.23 8 1.56 0.16 9<br>JORDAN JOR 0.43 0.13 13 0.36 0.13 13 0.39 0.14 11 0.30 0.14 10 0.47 0.17 9 0.49 0.20 9 0.15 0.18 7<br>KAZAKHSTAN KAZ -0.79 0.12 15 -0.98 0.12 16 -0.99 0.13 14 -0.98 0.13 14 -0.89 0.15 13 -0.91 0.18 10 -0.79 0.17 6<br>KENYA KEN -0.94 0.14 14 -1.01 0.13 16 -1.06 0.13 14 -1.08 0.14 13 -1.03 0.18 10 -1.02 0.20 9 -0.83 0.19 6<br>KIRIBATI KIR 0.76 0.26 4 0.36 0.25 4 0.20 0.34 2 0.60 0.37 2 -0.08 0.39 2 -0.75 0.44 1 .. .. ..<br>KOREA, NORTH PRK -1.15 0.18 7 -1.24 0.17 8 -1.07 0.18 7 -0.96 0.24 6 -1.18 0.36 4 -1.29 0.42 3 -1.10 0.44 3<br>KOREA, SOUTH KOR 0.73 0.13 14 0.66 0.12 15 0.60 0.13 14 0.79 0.13 15 0.52 0.15 13 0.70 0.18 11 0.77 0.16 9<br>KOSOVO LWI -0.95 0.32 1 .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. ..<br>KUWAIT KWT 0.67 0.15 10 0.65 0.15 10 0.70 0.15 10 0.70 0.15 11 1.03 0.22 6 0.98 0.24 6 0.61 0.19 6<br>KYRGYZ REPUBLIC KGZ -1.07 0.14 13 -0.87 0.14 14 -0.81 0.14 12 -0.78 0.15 12 -0.98 0.17 9 -0.76 0.21 7 -0.75 0.26 4<br>LAOS LAO -1.12 0.17 11 -1.11 0.17 9 -1.13 0.18 8 -0.99 0.19 8 -1.05 0.23 7 -1.14 0.28 4 -1.42 0.34 3<br>LATVIA LVA 0.43 0.13 14 0.45 0.12 14 0.49 0.13 13 0.36 0.13 13 0.09 0.15 10 -0.04 0.19 9 0.14 0.17 6<br>LEBANON LBN -0.36 0.15 11 -0.32 0.14 11 -0.35 0.15 10 -0.33 0.14 11 -0.22 0.19 9 0.05 0.22 7 -0.32 0.19 6<br>LESOTHO LSO -0.19 0.19 8 -0.04 0.17 8 -0.21 0.18 8 -0.08 0.19 7 -0.26 0.25 5 -0.26 0.30 4 -0.36 0.50 2<br>LIBERIA LBR -1.60 0.26 5 -1.68 0.25 5 -1.62 0.27 4 -1.76 0.26 6 -1.60 0.29 5 -1.87 0.37 3 -2.22 0.59 2<br>LIBYA LBY -0.73 0.16 11 -0.60 0.15 10 -0.75 0.15 8 -0.87 0.16 8 -1.01 0.22 6 -1.19 0.24 6 -1.05 0.19 6<br>LIECHTENSTEIN LIE 1.03 0.33 2 1.27 0.32 2 1.20 0.32 1 1.47 0.33 1 .. .. .. .. .. .. .. .. ..<br>LITHUANIA LTU 0.46 0.13 14 0.53 0.12 15 0.52 0.13 14 0.41 0.13 14 0.18 0.14 13 0.07 0.19 9 -0.19 0.17 6<br>LUXEMBOURG LUX 1.96 0.18 8 2.00 0.18 8 1.98 0.19 7 2.01 0.21 7 1.95 0.31 5 1.82 0.31 5 1.75 0.28 5<br>MACAO MAC 0.78 0.34 2 1.37 0.33 1 1.20 0.32 1 0.68 0.33 1 .. .. .. .. .. .. .. .. ..<br>MACEDONIA MKD -0.38 0.14 12 -0.37 0.13 12 -0.34 0.14 11 -0.46 0.15 10 -0.40 0.21 6 -0.43 0.23 5 -0.62 0.20 3<br>MADAGASCAR MDG -0.15 0.17 11 -0.29 0.17 10 -0.25 0.19 9 -0.30 0.22 6 -0.75 0.25 7 -1.11 0.29 5 -0.90 0.44 3<br>MALAWI MWI -0.35 0.14 13 -0.31 0.14 13 -0.33 0.15 12 -0.40 0.15 11 -0.59 0.18 10 -0.70 0.21 8 -0.25 0.20 5<br>MALAYSIA MYS 0.58 0.13 14 0.55 0.12 16 0.48 0.13 14 0.48 0.13 15 0.39 0.15 14 0.57 0.18 11 0.80 0.16 9<br>MALDIVES MDV 0.33 0.26 4 0.14 0.25 4 0.24 0.24 3 0.23 0.25 3 -0.72 0.39 2 -0.75 0.44 1 .. .. ..<br>MALI MLI -0.12 0.17 11 -0.19 0.16 12 -0.19 0.18 11 -0.51 0.20 9 -0.69 0.23 8 -0.67 0.29 5 -0.83 0.44 3<br>MALTA MLT 1.38 0.20 7 1.22 0.20 6 1.37 0.22 5 1.03 0.25 3 0.63 0.42 2 0.59 0.46 2 0.00 0.47 2<br>MARSHALL ISLANDS MHL -0.27 0.38 3 -0.22 0.34 3 -0.29 0.34 2 -0.10 0.37 2 -0.67 0.39 2 -0.44 0.44 1 .. .. ..<br>MARTINIQUE MTQ 0.88 0.35 1 0.97 0.33 1 0.94 0.32 1 1.21 0.33 1 .. .. .. .. .. .. .. .. ..<br>MAURITANIA MRT -0.54 0.20 8 -0.54 0.20 7 -0.44 0.21 7 -0.42 0.23 5 -0.61 0.27 5 -0.57 0.34 3 -0.66 0.50 2<br>MAURITIUS MUS 0.79 0.15 10 0.82 0.15 9 0.98 0.16 9 0.84 0.15 9 0.75 0.18 8 0.72 0.21 7 0.67 0.21 3<br>MEXICO MEX -0.48 0.13 15 -0.38 0.12 16 -0.32 0.13 15 -0.38 0.13 16 -0.45 0.15 15 -0.48 0.18 12 -0.17 0.16 10<br>MICRONESIA FSM 0.72 0.26 4 0.44 0.25 4 -0.37 0.34 2 -0.26 0.37 2 -0.63 0.39 2 -0.44 0.44 1 .. .. ..<br>MOLDOVA MDA -0.59 0.13 14 -0.63 0.13 13 -0.60 0.14 12 -0.58 0.14 11 -0.61 0.16 11 -0.16 0.19 9 -0.25 0.17 6<br>MONACO MCO 0.83 0.76 1 0.77 0.74 1 .. .. .. .. .. .. .. .. .. .. .. .. .. .. ..<br>MONGOLIA MNG -0.26 0.17 10 0.02 0.18 10 0.11 0.19 8 0.24 0.21 7 0.12 0.27 6 -0.08 0.25 5 0.43 0.44 3<br>MOROCCO MAR -0.10 0.14 13 0.00 0.13 15 -0.01 0.14 13 0.06 0.14 13 0.18 0.19 9 0.37 0.20 9 0.14 0.18 7<br>MOZAMBIQUE MOZ -0.72 0.15 14 -0.69 0.14 14 -0.71 0.15 13 -0.61 0.18 11 -0.71 0.22 7 -1.00 0.23 7 -1.29 0.32 4<br>MYANMAR MMR -1.56 0.17 9 -1.63 0.16 10 -1.73 0.16 9 -1.67 0.17 9 -1.25 0.24 7 -1.14 0.28 5 -1.38 0.21 5<br>NAMIBIA NAM -0.01 0.14 12 0.10 0.14 13 0.19 0.14 12 0.29 0.14 12 0.82 0.20 9 0.63 0.24 6 0.32 0.23 3<br>NAURU NRU 0.83 0.76 1 0.77 0.74 1 .. .. .. .. .. .. .. .. .. .. .. .. .. .. ..<br>NEPAL NPL -0.81 0.15 11 -0.74 0.14 12 -0.66 0.15 10 -0.46 0.19 9 -0.44 0.23 7 -0.34 0.28 4 -0.41 0.34 3<br>NETHERLANDS NLD 1.78 0.14 12 1.78 0.13 12 1.78 0.14 12 1.76 0.14 13 1.89 0.16 12 1.97 0.20 9 1.91 0.16 9<br>NETHERLANDS ANTILLES ANT 0.88 0.35 1 0.91 0.33 1 .. .. .. .. .. .. .. .. .. .. .. .. .. .. ..<br>NEW ZEALAND NZL 1.95 0.14 11 1.93 0.14 11 1.92 0.14 11 1.82 0.14 9 1.89 0.17 9 2.09 0.21 8 2.05 0.17 8<br>NICARAGUA NIC -0.70 0.15 11 -0.72 0.15 13 -0.56 0.16 11 -0.72 0.16 11 -1.01 0.20 9 -0.92 0.24 7 -0.73 0.21 6<br>NIGER NER -0.82 0.19 9 -0.93 0.18 9 -0.81 0.20 8 -0.83 0.22 7 -0.90 0.26 6 -0.79 0.32 4 -1.31 0.44 3<br>NIGERIA NGA -1.38 0.14 14 -1.50 0.13 16 -1.55 0.13 14 -1.46 0.14 15 -1.10 0.16 14 -1.34 0.20 9 -1.26 0.18 7<br><!-- End of picture text --> 102
<!-- Start of picture text --> TABLE C5: Rule of Law (cont.)<br>2005 2004 2003 2002 2000 1998 1996<br>Country Code Est. S.E. N. Est. S.E. N. Est. S.E. N. Est. S.E. N. Est. S.E. N. Est. S.E. N. Est. S.E. N.<br>NORWAY NOR 1.99 0.14 12 1.97 0.13 12 1.96 0.14 12 1.88 0.14 12 1.90 0.17 10 2.12 0.20 9 2.07 0.16 9<br>OMAN OMN 0.72 0.16 9 0.94 0.15 10 0.86 0.15 9 0.77 0.15 10 1.09 0.21 7 1.11 0.24 6 1.08 0.19 6<br>PALAU PCI -0.07 0.76 1 0.77 0.74 1 .. .. .. .. .. .. .. .. .. .. .. .. .. .. ..<br>PAKISTAN PAK -0.81 0.13 14 -0.83 0.13 15 -0.69 0.13 13 -0.75 0.14 13 -0.75 0.17 12 -0.79 0.20 9 -0.49 0.18 7<br>PANAMA PAN -0.11 0.14 13 -0.08 0.14 13 -0.09 0.14 13 -0.10 0.14 13 -0.14 0.17 11 -0.15 0.21 8 0.21 0.19 7<br>PAPUA NEW GUINEA PNG -0.92 0.16 10 -0.76 0.14 11 -1.04 0.15 10 -1.03 0.16 9 -0.49 0.19 9 -0.41 0.23 6 -0.38 0.21 4<br>PARAGUAY PRY -1.00 0.14 13 -1.16 0.14 13 -1.12 0.15 12 -1.14 0.15 10 -0.93 0.18 9 -0.86 0.22 8 -0.56 0.20 6<br>PERU PER -0.77 0.13 15 -0.65 0.13 15 -0.55 0.13 14 -0.56 0.14 14 -0.60 0.16 13 -0.63 0.19 11 -0.40 0.17 9<br>PHILIPPINES PHL -0.52 0.13 15 -0.67 0.12 15 -0.65 0.13 14 -0.59 0.13 13 -0.55 0.15 14 -0.10 0.19 10 -0.16 0.16 9<br>POLAND POL 0.32 0.12 16 0.41 0.11 17 0.51 0.12 16 0.51 0.12 17 0.54 0.13 15 0.49 0.17 12 0.42 0.15 10<br>PORTUGAL PRT 1.10 0.14 12 1.16 0.13 12 1.27 0.14 12 1.23 0.14 12 1.07 0.16 10 1.24 0.20 10 1.32 0.16 9<br>PUERTO RICO PRI 0.62 0.28 3 0.73 0.24 3 0.74 0.24 3 1.06 0.26 2 0.97 0.45 1 0.78 0.57 1 0.71 0.64 1<br>QATAR QAT 0.87 0.16 9 0.70 0.17 9 0.76 0.17 7 0.76 0.16 7 0.89 0.25 6 1.06 0.29 4 0.91 0.23 3<br>REUNION REU 1.15 0.35 1 1.07 0.33 1 .. .. .. .. .. .. .. .. .. .. .. .. .. .. ..<br>ROMANIA ROM -0.29 0.12 16 -0.23 0.12 16 -0.22 0.13 15 -0.23 0.13 15 -0.32 0.14 13 -0.35 0.19 8 -0.34 0.17 7<br>RUSSIA RUS -0.84 0.12 17 -0.81 0.11 17 -0.86 0.12 16 -0.90 0.12 17 -0.99 0.13 15 -0.90 0.17 12 -0.90 0.15 10<br>RWANDA RWA -1.00 0.20 8 -0.77 0.19 8 -0.85 0.21 7 -0.92 0.22 7 -0.90 0.27 5 -1.27 0.34 3 -0.24 0.79 1<br>SAMOA SAM 1.09 0.26 4 0.84 0.25 4 0.91 0.24 3 1.00 0.25 3 -0.10 0.31 3 -1.06 0.44 1 .. .. ..<br>SAN MARINO SMR 0.83 0.76 1 0.77 0.74 1 .. .. .. .. .. .. .. .. .. .. .. .. .. .. ..<br>SAO TOME AND PRINCIPE STP -0.63 0.26 4 -0.43 0.25 4 -0.56 0.26 3 -0.56 0.27 3 -0.77 0.35 2 -1.06 0.44 1 .. .. ..<br>SAUDI ARABIA SAU 0.20 0.15 11 0.20 0.14 12 0.33 0.14 11 0.32 0.14 12 0.37 0.19 9 0.60 0.23 7 0.71 0.18 7<br>SENEGAL SEN -0.26 0.15 12 -0.22 0.14 13 -0.23 0.14 13 -0.28 0.15 12 -0.36 0.19 9 -0.28 0.22 7 -0.22 0.20 5<br>SEYCHELLES SYC 0.21 0.24 5 -0.03 0.24 5 0.25 0.25 4 0.44 0.27 3 -0.53 0.35 2 -0.44 0.44 1 .. .. ..<br>SIERRA LEONE SLE -1.12 0.20 8 -1.11 0.18 10 -1.27 0.20 8 -1.27 0.24 7 -0.95 0.25 7 -0.79 0.32 4 -1.08 0.44 3<br>SINGAPORE SGP 1.83 0.13 13 1.83 0.13 13 1.83 0.14 12 1.67 0.14 11 1.91 0.16 12 2.04 0.20 10 2.10 0.16 9<br>SLOVAK REPUBLIC SVK 0.41 0.12 15 0.44 0.12 15 0.31 0.13 14 0.29 0.13 14 0.23 0.14 12 0.07 0.18 10 0.07 0.16 8<br>SLOVENIA SVN 0.79 0.13 14 0.83 0.12 15 0.95 0.13 15 1.00 0.13 15 0.81 0.14 13 0.86 0.19 8 0.47 0.17 6<br>SOLOMON ISLANDS SLB -0.90 0.26 4 -1.01 0.25 4 -1.58 0.34 2 -1.59 0.37 2 -1.41 0.39 2 -0.75 0.44 1 .. .. ..<br>SOMALIA SOM -2.36 0.26 5 -2.29 0.25 5 -2.11 0.27 4 -2.07 0.29 4 -1.78 0.28 5 -1.88 0.32 4 -1.75 0.59 2<br>SOUTH AFRICA ZAF 0.19 0.12 16 0.19 0.12 17 0.07 0.12 16 0.04 0.13 17 0.15 0.14 16 0.21 0.18 11 0.31 0.16 9<br>SPAIN ESP 1.13 0.14 12 1.17 0.13 13 1.22 0.13 13 1.11 0.13 14 1.29 0.16 13 1.33 0.20 10 1.19 0.16 9<br>SRI LANKA LKA 0.00 0.14 13 0.02 0.13 15 0.07 0.13 13 0.17 0.14 13 -0.26 0.17 11 -0.21 0.22 7 0.24 0.19 6<br>ST. KITTS AND NEVIS KNA 0.82 0.28 3 0.72 0.26 3 0.24 0.46 1 0.26 0.51 1 0.29 0.41 1 -0.44 0.44 1 .. .. ..<br>ST. LUCIA LCA 0.82 0.28 3 0.67 0.26 3 0.24 0.46 1 0.26 0.51 1 0.29 0.41 1 -0.44 0.44 1 .. .. ..<br>ST. VINCENT AND THE GRENADINES VCT 0.82 0.28 3 0.72 0.26 3 0.24 0.46 1 0.58 0.51 1 0.29 0.41 1 -0.44 0.44 1 .. .. ..<br>SUDAN SDN -1.48 0.17 10 -1.47 0.16 11 -1.57 0.16 10 -1.36 0.17 10 -1.19 0.20 9 -1.39 0.26 5 -1.52 0.22 4<br>SURINAME SUR -0.15 0.22 6 -0.44 0.22 6 -0.35 0.23 5 -0.46 0.25 4 -0.70 0.42 2 -0.82 0.46 2 -0.88 0.47 2<br>SWAZILAND SWZ -0.75 0.19 8 -0.84 0.18 7 -0.80 0.19 7 -0.70 0.20 6 -0.17 0.28 4 -0.36 0.30 4 0.35 0.50 2<br>SWEDEN SWE 1.84 0.14 12 1.86 0.13 13 1.91 0.13 13 1.82 0.14 13 1.87 0.16 13 1.89 0.20 9 2.00 0.16 9<br>SWITZERLAND CHE 2.02 0.14 12 1.99 0.13 12 2.01 0.14 12 1.95 0.14 12 2.11 0.16 12 2.27 0.20 10 2.14 0.16 9<br>SYRIA SYR -0.42 0.16 11 -0.36 0.14 11 -0.47 0.15 9 -0.35 0.16 9 -0.48 0.21 7 -0.42 0.24 6 -0.58 0.19 6<br>TAIWAN TWN 0.83 0.13 13 0.82 0.13 14 0.87 0.13 13 0.83 0.14 13 0.76 0.16 12 1.02 0.20 9 0.98 0.16 9<br>TAJIKISTAN TJK -0.99 0.15 13 -1.14 0.15 12 -1.11 0.15 11 -1.32 0.16 11 -1.38 0.19 7 -1.53 0.25 5 -1.47 0.31 3<br>TANZANIA TZA -0.47 0.14 14 -0.48 0.13 15 -0.50 0.13 14 -0.54 0.14 13 -0.26 0.17 11 -0.34 0.20 9 -0.75 0.19 6<br>THAILAND THA 0.10 0.13 15 0.00 0.12 15 0.04 0.13 14 0.18 0.13 14 0.30 0.15 13 0.30 0.18 11 0.45 0.16 9<br>TIMOR, EAST TMP -0.55 0.26 4 -0.69 0.28 5 -1.08 0.27 2 -1.17 0.33 1 .. .. .. .. .. .. .. .. ..<br>TOGO TGO -1.07 0.19 9 -1.14 0.18 9 -0.99 0.20 8 -0.72 0.22 7 -0.99 0.27 6 -0.91 0.29 5 -1.29 0.59 2<br>TONGA TON 0.45 0.26 4 0.18 0.25 4 -0.08 0.34 2 0.00 0.37 2 -0.48 0.39 2 -0.75 0.44 1 .. .. ..<br>TRINIDAD AND TOBAGO TTO -0.07 0.15 10 -0.05 0.15 9 0.12 0.15 9 0.25 0.16 8 0.38 0.18 8 0.30 0.23 6 0.31 0.20 5<br>TUNISIA TUN 0.21 0.14 14 0.20 0.13 13 0.16 0.14 12 0.28 0.14 12 0.30 0.18 10 0.27 0.20 8 0.02 0.19 6<br>TURKEY TUR 0.07 0.13 16 0.02 0.12 16 0.02 0.13 15 -0.15 0.13 16 -0.07 0.15 14 -0.01 0.18 11 -0.02 0.16 9<br>TURKMENISTAN TKM -1.41 0.15 9 -1.45 0.14 9 -1.37 0.16 8 -1.20 0.16 8 -1.22 0.18 6 -1.28 0.22 6 -1.26 0.26 4<br>TUVALU TUV 1.20 0.33 2 0.85 0.29 3 1.35 0.46 1 1.74 0.47 1 1.38 0.75 1 .. .. .. .. .. ..<br>UGANDA UGA -0.74 0.14 14 -0.77 0.13 16 -0.68 0.13 14 -0.82 0.14 13 -0.62 0.17 12 -0.30 0.20 9 -0.93 0.19 6<br>UKRAINE UKR -0.60 0.12 15 -0.83 0.12 17 -0.84 0.13 15 -0.87 0.13 15 -0.80 0.14 13 -0.88 0.17 11 -0.73 0.16 8<br>UNITED ARAB EMIRATES ARE 0.58 0.15 11 0.83 0.15 10 0.90 0.15 9 0.94 0.15 10 1.34 0.22 7 0.99 0.24 6 0.74 0.19 6<br>UNITED KINGDOM GBR 1.69 0.14 12 1.74 0.13 13 1.79 0.13 13 1.74 0.13 14 1.80 0.16 13 1.97 0.20 10 1.91 0.16 9<br>UNITED STATES USA 1.59 0.14 11 1.52 0.13 11 1.61 0.14 11 1.58 0.14 12 1.79 0.16 11 1.66 0.20 10 1.76 0.16 9<br>URUGUAY URY 0.43 0.14 13 0.40 0.13 13 0.50 0.14 11 0.49 0.14 11 0.46 0.17 11 0.44 0.21 8 0.49 0.19 7<br>UZBEKISTAN UZB -1.31 0.14 13 -1.32 0.13 15 -1.19 0.13 13 -1.31 0.13 13 -1.03 0.16 10 -1.13 0.19 8 -1.08 0.18 5<br>VANUATU VUT 0.53 0.26 4 0.00 0.25 4 -0.53 0.34 2 -0.26 0.37 2 -0.36 0.39 2 -0.75 0.44 1 .. .. ..<br>VENEZUELA VEN -1.22 0.13 15 -1.12 0.12 17 -1.16 0.13 15 -1.14 0.13 15 -0.93 0.15 12 -0.75 0.18 12 -0.72 0.16 10<br>VIETNAM VNM -0.45 0.13 14 -0.60 0.13 16 -0.47 0.13 14 -0.47 0.13 14 -0.77 0.16 12 -0.94 0.20 9 -0.55 0.17 8<br>VIRGIN ISLANDS (U.S.) VIR 1.15 0.35 1 1.19 0.33 1 .. .. .. .. .. .. .. .. .. .. .. .. .. .. ..<br>WEST BANK WBG -0.52 0.31 2 -0.40 0.30 2 -0.31 0.29 2 -0.36 0.31 2 0.23 0.72 1 1.24 0.63 1 .. .. ..<br>YEMEN YEM -1.10 0.15 10 -1.06 0.15 12 -1.06 0.16 9 -1.29 0.16 9 -1.00 0.21 7 -0.72 0.23 6 -1.10 0.20 5<br>YUGOSLAVIA YUG -0.81 0.15 12 -0.78 0.14 12 -0.97 0.15 11 -0.99 0.15 11 -1.14 0.22 5 -1.06 0.27 4 -1.26 0.23 3<br>ZAMBIA ZMB -0.62 0.14 14 -0.61 0.13 15 -0.61 0.13 14 -0.56 0.14 13 -0.55 0.17 11 -0.49 0.20 9 -0.40 0.19 6<br>ZIMBABWE ZWE -1.47 0.14 14 -1.66 0.13 14 -1.54 0.14 12 -1.43 0.14 12 -0.79 0.16 11 -0.20 0.20 9 -0.28 0.18 7<br><!-- End of picture text --> 103
<!-- Start of picture text --> TABLE C6: Control of Corruption<br>2005 2004 2003 2002 2000 1998 1996<br>Country Code Est. S.E. N. Est. S.E. N. Est. S.E. N. Est. S.E. N. Est. S.E. N. Est. S.E. N. Est. S.E. N.<br>AFGHANISTAN AFG -1.37 0.23 3 -1.38 0.21 6 -1.30 0.22 4 -1.34 0.28 3 -1.64 0.48 1 .. .. .. .. .. ..<br>ALBANIA ALB -0.76 0.15 7 -0.81 0.16 7 -0.71 0.16 6 -0.86 0.18 6 -0.68 0.19 7 -0.99 0.23 5 0.07 0.49 2<br>ALGERIA DZA -0.43 0.15 10 -0.50 0.15 10 -0.65 0.16 10 -0.76 0.17 9 -0.69 0.22 7 -0.77 0.25 5 -0.35 0.28 4<br>AMERICAN SAMOA ASM 0.78 0.34 1 0.75 0.40 1 .. .. .. .. .. .. .. .. .. .. .. .. .. .. ..<br>ANDORRA ADO 1.25 0.34 1 1.06 0.40 1 1.28 0.39 1 1.31 0.40 1 .. .. .. .. .. .. .. .. ..<br>ANGOLA AGO -1.09 0.16 9 -1.20 0.16 9 -1.21 0.16 9 -1.19 0.17 9 -1.52 0.22 7 -1.16 0.22 6 -1.06 0.28 4<br>ANGUILLA AIA 1.25 0.34 1 0.80 0.40 1 .. .. .. .. .. .. .. .. .. .. .. .. .. .. ..<br>ANTIGUA AND BARBUDA ATG 0.78 0.34 1 0.89 0.40 1 0.81 0.39 1 0.85 0.40 1 .. .. .. .. .. .. .. .. ..<br>ARGENTINA ARG -0.44 0.14 12 -0.50 0.14 13 -0.46 0.15 12 -0.81 0.15 12 -0.40 0.17 12 -0.29 0.19 10 -0.12 0.20 7<br>ARMENIA ARM -0.64 0.14 9 -0.70 0.15 9 -0.64 0.14 8 -0.69 0.16 8 -0.81 0.20 7 -0.78 0.21 6 -0.69 0.43 2<br>ARUBA ABW 1.25 0.34 1 1.11 0.40 1 .. .. .. .. .. .. .. .. .. .. .. .. .. .. ..<br>AUSTRALIA AUS 1.95 0.15 9 2.02 0.13 11 1.97 0.14 11 1.90 0.15 10 2.00 0.20 8 2.14 0.22 7 2.02 0.20 7<br>AUSTRIA AUT 1.99 0.15 10 2.13 0.15 10 2.11 0.16 9 1.87 0.17 8 1.88 0.21 8 1.96 0.21 9 1.81 0.20 7<br>AZERBAIJAN AZE -1.01 0.13 11 -1.21 0.13 12 -1.08 0.13 11 -1.07 0.13 11 -1.13 0.15 10 -1.08 0.20 7 -1.03 0.29 3<br>BAHAMAS BHS 1.32 0.30 2 1.36 0.35 2 1.37 0.35 2 1.43 0.35 2 0.80 0.73 1 0.60 0.90 1 0.41 0.71 1<br>BAHRAIN BHR 0.64 0.17 7 0.73 0.17 8 0.75 0.19 6 0.95 0.18 7 0.31 0.24 5 0.34 0.30 4 0.10 0.28 4<br>BANGLADESH BGD -1.18 0.16 10 -1.29 0.15 10 -1.16 0.15 10 -1.02 0.15 10 -0.68 0.17 8 -0.47 0.25 5 -0.49 0.28 4<br>BARBADOS BRB 1.17 0.31 2 1.17 0.34 2 1.20 0.33 2 1.31 0.40 1 .. .. .. .. .. .. .. .. ..<br>BELARUS BLR -0.90 0.16 7 -0.97 0.16 8 -0.87 0.15 8 -0.76 0.18 7 -0.12 0.20 7 -0.66 0.23 6 -0.99 0.58 1<br>BELGIUM BEL 1.45 0.15 9 1.51 0.15 9 1.58 0.16 9 1.63 0.17 9 1.32 0.21 8 1.17 0.22 8 1.23 0.20 7<br>BELIZE BLZ -0.22 0.26 3 -0.22 0.27 3 -0.08 0.27 3 -0.24 0.32 2 0.11 0.39 2 -0.36 0.43 1 .. .. ..<br>BENIN BEN -1.00 0.21 6 -0.50 0.24 5 -0.42 0.24 5 -0.50 0.26 4 -0.07 0.46 2 -0.82 0.36 2 .. .. ..<br>BERMUDA BMU 1.25 0.34 1 1.24 0.40 1 1.28 0.39 1 1.31 0.40 1 .. .. .. .. .. .. .. .. ..<br>BHUTAN BTN 0.84 0.25 5 0.75 0.26 4 0.87 0.23 4 0.52 0.23 3 0.48 0.27 2 0.40 0.43 1 .. .. ..<br>BOLIVIA BOL -0.81 0.15 11 -0.86 0.16 10 -0.68 0.16 9 -0.86 0.16 9 -0.73 0.19 9 -0.48 0.22 8 -0.93 0.28 4<br>BOSNIA-HERZEGOVINA BIH -0.32 0.15 8 -0.54 0.15 9 -0.53 0.15 7 -0.63 0.18 7 -0.55 0.24 4 -0.41 0.28 2 .. .. ..<br>BOTSWANA BWA 1.10 0.17 9 0.93 0.17 10 0.98 0.17 10 0.78 0.17 10 0.95 0.22 8 0.67 0.24 5 0.45 0.31 3<br>BRAZIL BRA -0.28 0.14 11 -0.05 0.14 13 0.03 0.15 12 -0.10 0.15 12 -0.01 0.17 11 0.03 0.19 11 -0.10 0.20 7<br>BRUNEI BRN 0.25 0.30 2 0.37 0.35 2 0.28 0.35 2 0.32 0.35 2 -0.19 0.73 1 0.00 0.90 1 0.41 0.71 1<br>BULGARIA BGR -0.05 0.13 11 -0.03 0.13 12 -0.09 0.13 11 -0.19 0.14 11 -0.20 0.16 11 -0.56 0.19 8 -0.71 0.28 4<br>BURKINA FASO BFA 0.06 0.22 6 -0.03 0.24 5 0.04 0.24 5 0.11 0.27 4 -0.76 0.34 4 -0.54 0.30 3 -0.32 0.71 1<br>BURUNDI BDI -0.86 0.24 4 -0.84 0.26 4 -0.94 0.26 4 -0.94 0.29 3 -1.35 0.29 4 -0.86 0.43 1 .. .. ..<br>CAMBODIA KHM -1.12 0.18 7 -0.98 0.21 6 -0.89 0.20 5 -0.94 0.19 5 -0.79 0.22 4 -1.34 0.33 2 -1.00 0.55 1<br>CAMEROON CMR -1.15 0.16 9 -0.84 0.18 8 -1.00 0.18 8 -1.06 0.20 7 -1.12 0.24 7 -1.27 0.23 6 -1.17 0.31 3<br>CANADA CAN 1.92 0.15 10 1.96 0.15 11 2.08 0.16 10 2.08 0.16 10 2.25 0.19 10 2.44 0.21 8 2.34 0.20 7<br>CAPE VERDE CPV 0.21 0.24 4 0.30 0.27 4 0.31 0.27 4 0.42 0.29 4 0.25 0.46 2 -0.36 0.43 1 .. .. ..<br>CAYMAN ISLANDS CYM 1.25 0.34 1 1.20 0.40 1 1.28 0.39 1 1.31 0.40 1 .. .. .. .. .. .. .. .. ..<br>CENTRAL AFRICAN REPUBLIC CAF -1.08 0.24 4 -1.18 0.26 4 -1.18 0.26 4 -1.13 0.29 3 -1.10 0.46 2 -0.61 0.43 1 .. .. ..<br>CHAD TCD -1.22 0.21 5 -1.24 0.23 5 -1.12 0.23 5 -0.91 0.28 4 -0.65 0.46 2 -0.90 0.36 2 .. .. ..<br>CHILE CHL 1.34 0.14 12 1.39 0.14 12 1.23 0.15 12 1.51 0.15 12 1.50 0.17 12 1.13 0.19 10 1.40 0.20 7<br>CHINA CHN -0.69 0.12 12 -0.59 0.13 12 -0.51 0.13 12 -0.40 0.14 12 -0.38 0.17 11 -0.20 0.17 9 0.00 0.20 7<br>COLOMBIA COL -0.22 0.14 13 -0.28 0.14 11 -0.46 0.15 11 -0.55 0.15 11 -0.51 0.17 12 -0.67 0.19 11 -0.45 0.20 7<br>COMOROS COM -0.93 0.25 3 -0.77 0.28 3 -0.88 0.28 3 -0.89 0.29 3 -1.04 0.46 2 -0.86 0.43 1 .. .. ..<br>CONGO COG -1.01 0.18 7 -0.99 0.19 7 -1.02 0.19 7 -1.04 0.20 7 -1.05 0.28 5 -1.06 0.29 4 -0.86 0.47 2<br>Congo, Dem. Rep. (Zaire) ZAR -1.34 0.16 8 -1.39 0.16 9 -1.36 0.16 9 -1.42 0.19 8 -1.56 0.25 6 -1.65 0.29 4 -2.13 0.38 3<br>COOK ISLANDS COK .. .. .. 0.07 0.73 1 -0.24 0.42 1 -0.25 0.31 1 -0.29 0.30 1 .. .. .. .. .. ..<br>COSTA RICA CRI 0.38 0.15 10 0.55 0.15 11 0.84 0.16 10 0.86 0.16 10 0.98 0.18 9 0.63 0.20 9 0.84 0.26 5<br>CROATIA HRV 0.07 0.13 11 0.06 0.13 11 0.03 0.13 10 0.23 0.14 10 -0.03 0.17 9 -0.39 0.21 6 -0.51 0.29 3<br>CUBA CUB -0.26 0.18 6 -0.32 0.18 7 -0.32 0.18 7 -0.17 0.18 7 -0.39 0.24 5 -0.35 0.30 4 0.03 0.28 4<br>CYPRUS CYP 0.69 0.17 6 0.73 0.17 7 0.94 0.19 6 0.90 0.19 6 1.04 0.27 4 1.32 0.30 4 1.72 0.28 4<br>CZECH REPUBLIC CZE 0.42 0.12 12 0.33 0.12 13 0.38 0.12 12 0.33 0.14 12 0.39 0.16 12 0.29 0.17 10 0.65 0.20 7<br>DENMARK DNK 2.23 0.15 10 2.38 0.15 11 2.33 0.16 10 2.29 0.16 9 2.31 0.20 9 2.51 0.22 8 2.44 0.20 7<br>DJIBOUTI DJI -0.64 0.25 3 -0.74 0.28 3 -0.88 0.28 3 -0.69 0.29 3 -1.23 0.46 2 -0.86 0.43 1 .. .. ..<br>DOMINICA DMA 0.68 0.29 2 0.57 0.30 2 0.41 0.29 2 0.51 0.32 2 -0.27 0.51 1 -0.36 0.43 1 .. .. ..<br>DOMINICAN REPUBLIC DOM -0.66 0.15 10 -0.53 0.16 9 -0.40 0.16 8 -0.43 0.17 8 -0.37 0.20 8 -0.59 0.28 4 -0.34 0.31 3<br>ECUADOR ECU -0.81 0.15 11 -0.79 0.16 11 -0.82 0.16 10 -1.04 0.16 10 -1.05 0.19 10 -0.81 0.23 8 -0.79 0.27 5<br>EGYPT EGY -0.42 0.15 11 -0.22 0.15 12 -0.41 0.15 11 -0.30 0.16 11 -0.36 0.19 10 -0.23 0.21 7 0.14 0.25 6<br>EL SALVADOR SLV -0.39 0.18 7 -0.32 0.19 7 -0.34 0.20 7 -0.53 0.19 7 -0.24 0.21 7 -0.34 0.26 5 -0.80 0.31 3<br>EQUATORIAL GUINEA GNQ -1.79 0.24 4 -1.72 0.26 4 -1.73 0.26 4 -1.75 0.28 4 -2.13 0.46 2 -0.86 0.43 1 .. .. ..<br>ERITREA ERI -0.37 0.24 5 -0.54 0.24 5 -0.30 0.24 5 -0.18 0.26 4 0.01 0.36 3 0.40 0.43 1 .. .. ..<br>ESTONIA EST 0.88 0.12 11 0.86 0.12 13 0.79 0.12 12 0.70 0.13 12 0.71 0.15 12 0.43 0.19 8 0.07 0.29 3<br>ETHIOPIA ETH -0.79 0.17 9 -0.84 0.18 8 -0.78 0.18 8 -0.37 0.24 6 -0.01 0.30 5 -0.25 0.30 3 -1.05 0.71 1<br>FIJI FJI -0.60 0.29 2 0.02 0.27 3 -0.17 0.27 3 0.16 0.28 3 0.46 0.38 2 0.14 0.36 2 .. .. ..<br>FINLAND FIN 2.39 0.15 10 2.51 0.15 10 2.46 0.16 9 2.50 0.17 9 2.49 0.20 9 2.49 0.22 8 2.43 0.20 7<br>FRANCE FRA 1.40 0.15 10 1.40 0.15 11 1.47 0.16 10 1.39 0.16 10 1.41 0.19 9 1.69 0.21 8 1.53 0.20 7<br>FRENCH GUIANA GUF 0.78 0.34 1 0.75 0.40 1 0.81 0.39 1 0.85 0.40 1 .. .. .. .. .. .. .. .. ..<br>GABON GAB -0.61 0.16 8 -0.64 0.17 8 -0.53 0.17 8 -0.55 0.18 8 -0.81 0.22 7 -0.96 0.28 4 -1.32 0.31 3<br>GAMBIA GMB -0.70 0.21 5 -0.74 0.21 6 -0.56 0.22 6 -0.72 0.24 5 -0.22 0.42 3 -0.56 0.41 2 0.41 0.71 1<br><!-- End of picture text --> 104
<!-- Start of picture text --> TABLE C6: Control of Corruption (cont.)<br>2005 2004 2003 2002 2000 1998 1996<br>Country Code Est. S.E. N. Est. S.E. N. Est. S.E. N. Est. S.E. N. Est. S.E. N. Est. S.E. N. Est. S.E. N.<br>GEORGIA GEO -0.57 0.14 9 -0.88 0.14 11 -0.95 0.14 8 -1.07 0.16 8 -0.78 0.18 8 -0.71 0.21 5 -1.12 0.43 2<br>GERMANY DEU 1.92 0.15 10 1.92 0.15 11 2.02 0.16 10 1.83 0.16 10 1.67 0.19 9 2.15 0.21 9 1.92 0.20 7<br>GHANA GHA -0.38 0.15 11 -0.33 0.15 12 -0.27 0.15 11 -0.33 0.17 10 -0.56 0.21 9 -0.48 0.21 7 -0.49 0.28 4<br>GREECE GRC 0.40 0.15 10 0.53 0.15 10 0.57 0.16 9 0.57 0.17 9 0.84 0.21 7 0.78 0.22 8 0.42 0.20 7<br>GRENADA GRD 0.68 0.29 2 0.57 0.30 2 0.59 0.29 2 0.68 0.32 2 0.12 0.51 1 -0.10 0.43 1 .. .. ..<br>GUAM GUM 0.78 0.34 1 0.35 0.40 1 .. .. .. .. .. .. .. .. .. .. .. .. .. .. ..<br>GUATEMALA GTM -0.98 0.16 9 -0.70 0.16 11 -0.78 0.17 9 -0.76 0.16 9 -0.70 0.19 8 -0.71 0.23 6 -1.02 0.28 4<br>GUINEA GIN -0.84 0.22 5 -1.07 0.24 5 -0.83 0.24 5 -0.65 0.26 5 -0.48 0.42 3 -0.88 0.35 3 0.41 0.71 1<br>GUINEA-BISSAU GNB -1.08 0.23 4 -0.74 0.24 5 -0.74 0.24 5 -0.54 0.24 5 -0.60 0.34 4 -0.64 0.35 3 -1.05 0.71 1<br>GUYANA GUY -0.58 0.22 5 -0.47 0.25 4 -0.41 0.25 4 -0.45 0.29 3 -0.44 0.36 3 -0.33 0.41 2 -0.32 0.71 1<br>HAITI HTI -1.45 0.24 4 -1.39 0.23 6 -1.71 0.22 6 -1.65 0.23 5 -1.07 0.31 4 -0.91 0.41 2 -1.05 0.71 1<br>HONDURAS HND -0.67 0.16 9 -0.76 0.16 9 -0.74 0.17 9 -0.80 0.16 9 -0.71 0.19 8 -0.82 0.23 6 -1.03 0.28 4<br>HONG KONG HKG 1.68 0.13 10 1.56 0.13 10 1.49 0.14 9 1.45 0.15 9 1.43 0.19 8 1.67 0.17 9 1.64 0.20 6<br>HUNGARY HUN 0.63 0.12 12 0.63 0.12 13 0.63 0.12 13 0.56 0.13 13 0.71 0.15 13 0.63 0.17 11 0.70 0.20 7<br>ICELAND ISL 2.49 0.17 7 2.36 0.18 7 2.40 0.20 6 2.22 0.21 5 2.42 0.26 5 2.25 0.27 4 1.93 0.25 4<br>INDIA IND -0.31 0.12 12 -0.38 0.13 13 -0.39 0.13 12 -0.41 0.14 12 -0.31 0.17 11 -0.24 0.16 11 -0.32 0.20 7<br>INDONESIA IDN -0.86 0.12 13 -0.96 0.12 15 -1.01 0.13 13 -1.19 0.13 13 -1.05 0.15 12 -1.03 0.17 9 -0.49 0.20 7<br>IRAN IRN -0.47 0.17 9 -0.59 0.16 9 -0.45 0.16 9 -0.40 0.17 9 -0.67 0.24 6 -0.70 0.30 5 -0.88 0.27 5<br>IRAQ IRQ -1.27 0.18 6 -1.47 0.18 6 -0.95 0.19 6 -1.50 0.19 6 -1.25 0.24 5 -1.43 0.30 4 -1.45 0.28 4<br>IRELAND IRL 1.70 0.15 10 1.54 0.15 11 1.58 0.16 10 1.69 0.16 9 1.50 0.20 9 2.09 0.21 9 2.01 0.20 7<br>ISRAEL ISR 0.76 0.15 9 0.78 0.15 10 0.95 0.16 9 1.02 0.16 9 1.11 0.20 7 1.34 0.22 7 1.62 0.20 7<br>ITALY ITA 0.41 0.15 10 0.55 0.15 10 0.75 0.16 9 0.78 0.17 9 0.79 0.19 10 0.93 0.21 9 0.52 0.20 7<br>IVORY COAST CIV -1.23 0.18 7 -1.15 0.18 8 -1.08 0.18 8 -0.95 0.19 8 -0.68 0.25 6 -0.40 0.23 6 0.46 0.31 3<br>JAMAICA JAM -0.50 0.16 7 -0.55 0.17 7 -0.56 0.17 7 -0.49 0.18 7 -0.24 0.24 5 -0.33 0.26 5 -0.34 0.31 3<br>JAPAN JPN 1.24 0.13 11 1.22 0.13 12 1.14 0.14 11 1.21 0.14 11 1.28 0.18 10 1.10 0.17 9 1.34 0.20 7<br>JORDAN JOR 0.33 0.14 9 0.40 0.15 10 0.28 0.15 9 0.02 0.17 8 0.08 0.20 7 0.15 0.21 7 -0.09 0.26 5<br>KAZAKHSTAN KAZ -0.94 0.13 11 -1.16 0.13 12 -1.08 0.13 11 -1.08 0.14 11 -0.92 0.17 10 -0.93 0.20 8 -0.90 0.28 4<br>KENYA KEN -1.01 0.15 11 -0.88 0.15 13 -0.94 0.15 11 -1.09 0.17 10 -1.14 0.21 8 -1.03 0.21 7 -1.12 0.28 4<br>KIRIBATI KIR 0.22 0.27 3 0.28 0.28 3 0.09 0.31 2 -0.09 0.27 2 -0.29 0.27 2 -0.61 0.43 1 .. .. ..<br>KOREA, NORTH PRK -1.32 0.23 3 -1.50 0.24 4 -1.57 0.24 4 -1.22 0.30 3 -1.01 0.45 2 -0.61 0.90 1 -0.32 0.71 1<br>KOREA, SOUTH KOR 0.47 0.12 12 0.12 0.13 13 0.30 0.13 12 0.33 0.14 11 0.33 0.17 11 0.04 0.16 11 0.61 0.20 7<br>KOSOVO LWI -0.67 0.21 2 .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. ..<br>KUWAIT KWT 0.84 0.17 7 0.79 0.18 7 0.83 0.18 7 0.99 0.17 8 0.84 0.27 4 1.01 0.30 4 0.70 0.28 4<br>KYRGYZ REPUBLIC KGZ -1.06 0.14 9 -1.00 0.14 10 -0.89 0.14 9 -0.86 0.15 9 -0.93 0.17 7 -0.76 0.21 5 -0.84 0.43 2<br>LAOS LAO -1.10 0.20 7 -1.04 0.21 5 -1.01 0.20 5 -0.94 0.19 5 -0.88 0.22 4 -0.77 0.33 2 -1.00 0.55 1<br>LATVIA LVA 0.33 0.13 10 0.22 0.13 11 0.36 0.13 10 0.06 0.14 10 -0.04 0.17 9 -0.17 0.19 8 -0.59 0.29 3<br>LEBANON LBN -0.39 0.17 7 -0.51 0.17 7 -0.50 0.17 7 -0.40 0.17 8 -0.57 0.22 6 -0.39 0.25 5 -0.18 0.28 4<br>LESOTHO LSO -0.15 0.22 6 -0.16 0.22 6 -0.31 0.22 6 -0.28 0.25 5 0.54 0.39 3 0.14 0.30 2 .. .. ..<br>LIBERIA LBR -1.08 0.26 3 -1.04 0.30 3 -1.11 0.30 3 -1.32 0.28 4 -1.36 0.34 4 -1.50 0.41 2 -1.78 0.71 1<br>LIBYA LBY -0.89 0.18 7 -0.82 0.18 6 -0.84 0.19 6 -0.83 0.19 6 -0.99 0.27 4 -0.97 0.30 4 -0.95 0.28 4<br>LIECHTENSTEIN LIE 1.25 0.34 1 1.29 0.40 1 1.28 0.39 1 1.31 0.40 1 .. .. .. .. .. .. .. .. ..<br>LITHUANIA LTU 0.26 0.13 11 0.36 0.13 12 0.38 0.13 11 0.24 0.14 11 0.22 0.16 11 0.01 0.20 7 -0.12 0.29 3<br>LUXEMBOURG LUX 1.84 0.19 6 2.02 0.20 6 1.91 0.23 5 2.21 0.27 4 2.01 0.39 3 2.10 0.30 4 1.97 0.27 3<br>MACAO MAC 0.55 0.20 2 1.33 0.40 1 0.81 0.39 1 -0.07 0.40 1 .. .. .. .. .. .. .. .. ..<br>MACEDONIA MKD -0.50 0.14 9 -0.56 0.14 9 -0.73 0.14 8 -0.75 0.17 6 -0.52 0.23 4 -0.36 0.23 4 -1.06 0.38 1<br>MADAGASCAR MDG 0.00 0.20 7 -0.06 0.22 6 0.07 0.22 6 0.03 0.27 4 -0.83 0.30 5 -0.86 0.35 3 0.41 0.71 1<br>MALAWI MWI -0.85 0.15 9 -0.84 0.16 9 -0.84 0.17 9 -0.94 0.18 8 -0.23 0.21 8 -0.55 0.22 6 -1.05 0.31 3<br>MALAYSIA MYS 0.27 0.12 12 0.29 0.13 14 0.36 0.13 12 0.33 0.14 12 0.21 0.17 11 0.67 0.16 10 0.57 0.20 7<br>MALDIVES MDV -0.28 0.27 3 -0.17 0.28 3 0.02 0.25 3 -0.18 0.23 3 -0.53 0.27 2 -0.61 0.43 1 .. .. ..<br>MALI MLI -0.29 0.20 7 -0.32 0.20 8 -0.35 0.21 8 -0.17 0.23 7 -0.45 0.31 5 -0.64 0.35 3 -0.32 0.71 1<br>MALTA MLT 1.04 0.24 4 1.20 0.26 4 1.24 0.27 4 0.80 0.35 2 0.14 0.73 1 0.60 0.90 1 0.41 0.71 1<br>MARSHALL ISLANDS MHL -0.43 0.42 2 -0.57 0.38 2 -0.87 0.31 2 -0.96 0.27 2 -0.80 0.27 2 -0.61 0.43 1 .. .. ..<br>MARTINIQUE MTQ 0.78 0.34 1 0.84 0.40 1 0.81 0.39 1 0.85 0.40 1 .. .. .. .. .. .. .. .. ..<br>MAURITANIA MRT -0.26 0.24 5 -0.04 0.26 4 0.25 0.26 4 0.15 0.29 3 -0.73 0.36 3 -0.36 0.43 1 .. .. ..<br>MAURITIUS MUS 0.32 0.17 6 0.30 0.18 6 0.36 0.18 6 0.43 0.18 6 0.52 0.22 6 0.24 0.22 5 0.54 0.33 2<br>MEXICO MEX -0.41 0.14 12 -0.28 0.14 13 -0.16 0.15 12 -0.25 0.15 12 -0.49 0.17 12 -0.46 0.19 10 -0.35 0.20 7<br>MICRONESIA FSM -0.28 0.42 2 -0.08 0.28 3 -0.39 0.31 2 -0.42 0.27 2 -0.42 0.27 2 -0.36 0.43 1 .. .. ..<br>MOLDOVA MDA -0.76 0.13 11 -0.95 0.14 10 -0.92 0.13 9 -0.92 0.15 8 -0.92 0.17 9 -0.57 0.20 7 -0.21 0.29 3<br>MONGOLIA MNG -0.55 0.21 6 -0.52 0.23 6 -0.28 0.21 6 -0.08 0.20 5 -0.28 0.23 4 -0.34 0.27 3 0.41 0.71 1<br>MOROCCO MAR -0.09 0.15 9 -0.04 0.15 11 -0.07 0.16 10 -0.09 0.17 9 0.30 0.24 6 -0.11 0.21 7 0.26 0.27 5<br>MOZAMBIQUE MOZ -0.68 0.16 10 -0.81 0.16 10 -0.80 0.17 10 -0.83 0.20 8 -0.39 0.28 5 -0.87 0.24 5 -0.54 0.47 2<br>MYANMAR MMR -1.44 0.20 5 -1.60 0.20 6 -1.44 0.20 6 -1.43 0.21 6 -1.30 0.28 4 -1.37 0.38 3 -1.25 0.31 3<br>NAMIBIA NAM 0.06 0.17 9 0.05 0.17 10 0.10 0.17 10 0.11 0.17 10 1.10 0.24 7 0.33 0.26 4 0.85 0.35 2<br>NEPAL NPL -0.71 0.17 7 -0.70 0.18 8 -0.51 0.17 7 -0.44 0.18 6 -0.63 0.22 4 -0.66 0.33 2 -0.29 0.55 1<br>NETHERLANDS NLD 1.99 0.15 10 2.04 0.15 10 2.10 0.16 9 2.20 0.17 9 2.30 0.20 9 2.42 0.22 8 2.33 0.20 7<br>NETHERLANDS ANTILLES ANT 1.25 0.34 1 0.57 0.40 1 .. .. .. .. .. .. .. .. .. .. .. .. .. .. ..<br>NEW ZEALAND NZL 2.24 0.15 8 2.40 0.15 8 2.36 0.16 8 2.31 0.17 7 2.31 0.20 7 2.48 0.22 7 2.42 0.20 6<br>NICARAGUA NIC -0.62 0.18 8 -0.37 0.18 9 -0.49 0.19 8 -0.49 0.18 8 -0.96 0.21 7 -0.83 0.26 5 -0.14 0.31 3<br>NIGER NER -0.83 0.22 5 -0.90 0.24 5 -1.02 0.24 5 -1.03 0.27 4 -0.91 0.42 3 -0.94 0.41 2 -0.32 0.71 1<br><!-- End of picture text --> 105
<!-- Start of picture text --> TABLE C6: Control of Corruption (cont.)<br>2005 2004 2003 2002 2000 1998 1996<br>Country Code Est. S.E. N. Est. S.E. N. Est. S.E. N. Est. S.E. N. Est. S.E. N. Est. S.E. N. Est. S.E. N.<br>NIGERIA NGA -1.22 0.15 11 -1.30 0.15 13 -1.27 0.15 11 -1.36 0.16 11 -1.16 0.18 11 -1.13 0.20 8 -1.28 0.27 5<br>NORWAY NOR 2.04 0.15 10 2.08 0.15 10 2.00 0.16 9 2.01 0.17 8 2.07 0.21 8 2.29 0.22 8 2.19 0.20 7<br>OMAN OMN 0.69 0.18 6 0.84 0.18 7 0.68 0.18 7 1.01 0.17 8 0.68 0.24 5 0.83 0.30 4 0.15 0.28 4<br>PAKISTAN PAK -1.01 0.15 11 -1.06 0.15 12 -0.76 0.15 10 -0.85 0.16 9 -0.94 0.18 8 -0.82 0.21 8 -1.04 0.27 5<br>PANAMA PAN -0.27 0.15 10 -0.15 0.15 10 -0.22 0.16 10 -0.27 0.16 10 -0.40 0.18 9 -0.34 0.25 6 -0.53 0.28 4<br>PAPUA NEW GUINEA PNG -1.08 0.17 8 -0.94 0.16 9 -0.94 0.16 9 -0.82 0.16 8 -0.92 0.18 7 -0.77 0.28 4 -0.27 0.31 3<br>PARAGUAY PRY -1.19 0.16 10 -1.18 0.16 9 -1.29 0.17 9 -1.25 0.16 9 -1.08 0.21 7 -1.03 0.25 6 -0.52 0.31 3<br>PERU PER -0.49 0.15 12 -0.38 0.15 12 -0.30 0.16 11 -0.27 0.16 11 -0.16 0.18 11 -0.24 0.20 9 -0.09 0.25 6<br>PHILIPPINES PHL -0.58 0.12 13 -0.58 0.13 13 -0.46 0.13 12 -0.55 0.14 12 -0.53 0.17 12 -0.34 0.17 9 -0.41 0.20 7<br>POLAND POL 0.19 0.12 13 0.15 0.12 14 0.39 0.12 13 0.37 0.13 13 0.48 0.15 13 0.43 0.17 10 0.46 0.20 7<br>PORTUGAL PRT 1.13 0.15 10 1.20 0.15 10 1.30 0.16 9 1.33 0.17 8 1.37 0.20 8 1.49 0.21 9 1.34 0.20 7<br>PUERTO RICO PRI 1.10 0.28 3 0.94 0.27 3 0.98 0.27 3 1.20 0.32 2 1.34 0.48 1 1.41 0.57 1 1.29 0.58 1<br>QATAR QAT 0.82 0.19 6 0.68 0.21 6 0.69 0.21 5 0.91 0.21 5 0.67 0.28 4 0.75 0.38 3 -0.05 0.31 3<br>REUNION REU 0.78 0.34 1 0.93 0.40 1 .. .. .. .. .. .. .. .. .. .. .. .. .. .. ..<br>ROMANIA ROM -0.23 0.12 13 -0.29 0.12 13 -0.29 0.12 12 -0.35 0.14 11 -0.50 0.16 11 -0.44 0.20 7 -0.18 0.28 4<br>RUSSIA RUS -0.74 0.12 14 -0.81 0.12 14 -0.82 0.12 13 -0.96 0.13 13 -1.04 0.15 13 -0.76 0.17 11 -0.78 0.20 7<br>RWANDA RWA -0.81 0.25 4 -0.40 0.25 4 -0.47 0.26 4 -0.32 0.26 4 -0.01 0.36 3 -0.61 0.43 1 .. .. ..<br>SAMOA SAM 0.17 0.27 3 0.15 0.28 3 0.10 0.25 3 -0.01 0.23 3 -0.20 0.27 2 -0.36 0.43 1 .. .. ..<br>SAO TOME AND PRINCIPE STP -0.77 0.25 3 -0.59 0.28 3 -0.60 0.28 3 -0.32 0.29 3 -0.01 0.46 2 -0.86 0.43 1 .. .. ..<br>SAUDI ARABIA SAU 0.23 0.17 7 0.18 0.17 8 0.29 0.18 8 0.48 0.17 9 0.03 0.24 6 0.28 0.30 5 -0.33 0.27 5<br>SENEGAL SEN -0.23 0.16 9 -0.39 0.17 9 -0.42 0.16 10 -0.22 0.18 9 -0.45 0.22 7 -0.51 0.26 5 -0.40 0.31 3<br>SEYCHELLES SYC 0.01 0.24 4 0.15 0.26 4 0.18 0.26 4 0.29 0.29 3 0.12 0.46 2 -0.36 0.43 1 .. .. ..<br>SIERRA LEONE SLE -0.99 0.23 4 -0.80 0.24 6 -0.88 0.24 5 -0.77 0.24 5 -0.87 0.34 4 -0.79 0.41 2 -1.78 0.71 1<br>SINGAPORE SGP 2.24 0.13 11 2.42 0.13 11 2.39 0.14 10 2.35 0.15 10 2.44 0.18 10 2.43 0.17 9 2.38 0.20 7<br>SLOVAK REPUBLIC SVK 0.43 0.12 11 0.37 0.12 11 0.34 0.13 11 0.26 0.14 11 0.20 0.16 11 -0.15 0.18 8 0.46 0.26 5<br>SLOVENIA SVN 0.88 0.12 10 1.00 0.13 11 1.01 0.12 12 0.90 0.13 12 1.03 0.15 11 0.77 0.21 6 1.15 0.29 3<br>SOLOMON ISLANDS SLB 0.02 0.27 3 -0.55 0.28 3 -1.30 0.31 2 -1.35 0.27 2 -1.02 0.27 2 -0.61 0.43 1 .. .. ..<br>SOMALIA SOM -1.74 0.26 3 -1.68 0.30 3 -1.57 0.30 3 -1.24 0.30 3 -1.68 0.36 3 -1.50 0.41 2 -1.78 0.71 1<br>SOUTH AFRICA ZAF 0.54 0.14 13 0.41 0.14 14 0.33 0.15 13 0.34 0.15 13 0.49 0.17 13 0.49 0.19 10 0.70 0.20 7<br>SPAIN ESP 1.34 0.15 10 1.41 0.15 11 1.47 0.16 10 1.45 0.16 10 1.62 0.19 10 1.52 0.21 9 0.85 0.20 7<br>SRI LANKA LKA -0.31 0.16 9 -0.17 0.15 11 -0.21 0.15 10 -0.20 0.15 10 -0.16 0.17 8 -0.30 0.25 5 -0.23 0.28 4<br>ST. KITTS AND NEVIS KNA 1.00 0.29 2 0.23 0.30 2 0.24 0.41 1 0.30 0.48 1 0.12 0.51 1 -0.10 0.43 1 .. .. ..<br>ST. LUCIA LCA 1.15 0.29 2 0.28 0.30 2 0.24 0.41 1 0.30 0.48 1 0.51 0.51 1 -0.10 0.43 1 .. .. ..<br>ST. VINCENT AND THE GRENADINES VCT 1.00 0.29 2 0.28 0.30 2 0.24 0.41 1 0.30 0.48 1 0.12 0.51 1 -0.10 0.43 1 .. .. ..<br>SUDAN SDN -1.40 0.18 7 -1.35 0.18 8 -1.32 0.18 8 -1.05 0.19 8 -1.15 0.24 6 -0.81 0.33 3 -1.16 0.35 2<br>SURINAME SUR 0.05 0.27 3 0.33 0.31 3 0.35 0.31 3 0.18 0.35 2 0.14 0.73 1 0.00 0.90 1 -0.32 0.71 1<br>SWAZILAND SWZ -0.60 0.22 6 -0.70 0.23 5 -0.55 0.23 5 -0.32 0.25 4 -0.20 0.46 2 -0.13 0.30 2 .. .. ..<br>SWEDEN SWE 2.10 0.15 9 2.18 0.15 10 2.24 0.16 10 2.28 0.16 9 2.43 0.19 10 2.48 0.22 8 2.38 0.20 7<br>SWITZERLAND CHE 2.12 0.15 10 2.13 0.15 10 2.19 0.16 9 2.20 0.17 8 2.17 0.20 9 2.52 0.21 9 2.30 0.20 7<br>SYRIA SYR -0.59 0.18 7 -0.58 0.18 7 -0.52 0.18 7 -0.31 0.18 7 -0.79 0.24 5 -0.64 0.30 4 -0.75 0.28 4<br>TAIWAN TWN 0.63 0.13 11 0.63 0.13 12 0.65 0.14 11 0.71 0.14 11 0.63 0.18 10 0.80 0.17 9 0.82 0.20 7<br>TAJIKISTAN TJK -1.08 0.15 9 -1.20 0.16 8 -1.06 0.15 8 -1.08 0.16 8 -1.12 0.18 5 -1.18 0.25 3 -1.76 0.58 1<br>TANZANIA TZA -0.73 0.15 10 -0.67 0.15 11 -0.73 0.15 11 -0.96 0.17 10 -1.06 0.20 9 -1.04 0.21 7 -1.10 0.28 4<br>THAILAND THA -0.24 0.12 13 -0.30 0.13 12 -0.35 0.13 12 -0.32 0.14 12 -0.37 0.17 11 -0.32 0.16 10 -0.33 0.20 7<br>TIMOR, EAST TMP -0.77 0.28 2 -0.47 0.37 3 -0.52 0.30 2 -0.53 0.40 1 .. .. .. .. .. .. .. .. ..<br>TOGO TGO -0.70 0.21 6 -0.88 0.24 5 -0.87 0.24 5 -0.66 0.27 4 -0.70 0.42 3 -0.51 0.35 3 -1.05 0.71 1<br>TONGA TON -1.28 0.27 3 -0.47 0.28 3 -0.65 0.31 2 -0.75 0.27 2 -0.66 0.27 2 -0.36 0.43 1 .. .. ..<br>TRINIDAD AND TOBAGO TTO 0.01 0.16 8 -0.05 0.17 7 0.04 0.17 7 -0.06 0.18 6 0.31 0.22 6 0.06 0.28 4 0.37 0.31 3<br>TUNISIA TUN 0.13 0.15 10 0.26 0.15 10 0.36 0.16 10 0.41 0.16 10 0.63 0.21 8 0.15 0.22 6 -0.03 0.28 4<br>TURKEY TUR 0.08 0.14 13 -0.25 0.14 13 -0.27 0.15 12 -0.45 0.15 12 -0.36 0.18 11 -0.07 0.19 10 0.10 0.20 7<br>TURKMENISTAN TKM -1.30 0.15 6 -1.36 0.15 6 -1.19 0.15 6 -1.21 0.17 6 -1.19 0.22 4 -1.19 0.23 4 -1.54 0.43 2<br>TUVALU TUV -0.15 0.34 1 0.52 0.37 2 -0.77 0.42 1 0.06 0.31 1 -0.14 0.30 1 .. .. .. .. .. ..<br>UGANDA UGA -0.87 0.15 10 -0.85 0.15 12 -0.81 0.15 11 -0.98 0.17 10 -0.88 0.20 9 -0.69 0.21 7 -0.54 0.28 4<br>UKRAINE UKR -0.63 0.12 12 -0.96 0.13 14 -0.94 0.13 12 -1.01 0.14 12 -1.03 0.16 11 -0.97 0.17 10 -0.79 0.26 5<br>UNITED ARAB EMIRATES ARE 1.13 0.17 7 1.32 0.17 7 1.17 0.19 6 1.17 0.18 7 0.62 0.27 4 0.72 0.30 4 0.22 0.28 4<br>UNITED KINGDOM GBR 1.94 0.15 10 2.03 0.15 11 2.11 0.16 10 1.96 0.16 10 2.10 0.19 10 2.26 0.21 9 2.08 0.20 7<br>UNITED STATES USA 1.56 0.15 10 1.78 0.13 11 1.76 0.14 10 1.76 0.15 10 1.73 0.20 9 1.89 0.21 8 1.87 0.20 7<br>URUGUAY URY 0.78 0.15 10 0.63 0.16 10 0.71 0.16 9 0.79 0.16 9 0.72 0.19 9 0.36 0.24 7 0.50 0.28 4<br>UZBEKISTAN UZB -1.07 0.13 9 -1.16 0.14 11 -1.11 0.13 10 -1.04 0.14 10 -0.87 0.16 8 -1.04 0.20 6 -1.05 0.29 3<br>VANUATU VUT 0.26 0.27 3 -0.49 0.28 3 -0.67 0.31 2 -0.81 0.27 2 -0.90 0.27 2 -0.36 0.43 1 .. .. ..<br>VENEZUELA VEN -1.00 0.14 12 -1.00 0.14 14 -1.09 0.15 12 -0.97 0.15 12 -0.71 0.18 10 -0.84 0.19 10 -0.76 0.20 7<br>VIETNAM VNM -0.76 0.13 11 -0.81 0.13 13 -0.68 0.13 12 -0.71 0.13 12 -0.78 0.16 10 -0.67 0.17 8 -0.68 0.25 6<br>VIRGIN ISLANDS (U.S.) VIR 0.78 0.34 1 0.62 0.40 1 .. .. .. .. .. .. .. .. .. .. .. .. .. .. ..<br>WEST BANK WBG -1.09 0.31 2 -0.61 0.34 2 -0.95 0.33 2 -0.93 0.37 2 0.72 0.54 1 0.43 0.58 1 .. .. ..<br>YEMEN YEM -0.63 0.17 6 -0.83 0.17 8 -0.72 0.18 7 -0.74 0.18 7 -0.75 0.25 5 -0.64 0.28 4 -0.25 0.31 3<br>YUGOSLAVIA YUG -0.55 0.13 10 -0.55 0.14 9 -0.55 0.14 9 -0.77 0.16 8 -1.13 0.25 3 -1.03 0.27 4 -0.98 0.35 2<br>ZAMBIA ZMB -0.82 0.16 10 -0.81 0.15 11 -0.85 0.15 11 -0.92 0.17 10 -0.84 0.20 9 -0.61 0.21 7 -1.04 0.28 4<br>ZIMBABWE ZWE -1.24 0.15 10 -1.29 0.16 10 -1.23 0.16 9 -1.24 0.17 9 -0.97 0.20 9 -0.22 0.20 8 -0.11 0.26 5<br><!-- End of picture text --> 106