MattAndrews

Going beyond good and bad governance: still using debt as an example

I think the past few blog posts on debt may be evidence of me getting too engaged in one area. Oh well. I think it is super-interesting and important to think of how a government's debt management reflects on its governance. I've had some online and offline responses to my posts that have kept me thinking in this area, and I thought I'd share the thoughts. The risk, as always, is that the fresh ideas make less sense than I'd like. Not a bad risk, however, for those who believe in PDIA: We have a problem (thinking constructively about governance and debt) and my goal is to think about it iteratively to solve it, with (hopefully) lots of feedback and learning.

So, back to debt.

The always-smart and inspirational Natalia Adler reminded me to focus on outcomes when talking about governance, which I think is right (see long-past posts). I think debt levels are an outcome or output indicator. Debt data reflect the way government uses its authority to raise external funds on behalf of citizens. The process of incurring debt is certainly a process, but the final level of debt is a stock that has major implications for many things: How much a country can do now (because of the funds raised), how much the country must pay now, what must be paid in future.

Philipp Krause reminded me that debt levels are not a simple measure of governance. It is hard to say that high levels of debt are good (or great, as Philipp suggests) or bad. It is contextually relative.

Nadim Mata noted that saying 'governance is relative' is a dangerous thing. My word last week was 'uncomfortable'.

So: where do we go with the idea of governance…focusing on outputs or outcomes that people care about yet in a way that accounts for contextual factors…yet is not saying 'all is relative'?

Here is my idea. Love to know your thoughts.

First, I ground my reasoning in theory: Governance is about the exercise of authority by government on behalf of citizens. Drawing on Dani Kaufmann's work, it is about the way governments work within the context of established authorizing mechanisms and rules of the game. In respect of debt, I argue that governments have authority to raise money to further the interests of citizens. They are given this authority because it is clear that there are situations where debt is needed. The authority is not limitless, however, as there is a downside to too much debt (its cost). Different contexts are likely to have different thresholds of what is acceptable in terms of levels of debt a country can incur. This is determined by informal cultural variables, norms, practical constraints, formal rules that might restrain debt, etc. When we look at debt governance, therefore, we look at the way governments exercise the authority to raise debt within the rules of the game in a given context.

Second, I looked for an indicator: I wanted the indicator to be easy to understand, for starters, and contextualized as well. The standardized content comes in the form of the level of debt (as % of GDP). This is the number most people talk about when reflecting on debt issues, which makes it an easy starting point. The conventional approach is to show that high debt = bad and low debt = good (at least this is how I see the conventional position…). But we know it is not so simple, because some countries (like Japan) have had really high debt to GDP ratios for a long time and seem to continue amassing debt. The Japanese experience shows that some groups of citizens authorize their governments to run up high levels of debt. They do so because of various other characteristics (including the fact that Japan is also one of the world's largest creditors…). So, the amount of debt a government can run up before becoming 'bad' is relative to its contextual characteristics and how much and what type of authority it is given.

Third, I asked how we could capture the contextual authority governments have. I started working out some political and social characteristics of different countries and working out the patterns associated with these characteristics. Countries with natural resources like oil seem to have lower debt levels, for instance, and countries that introduced fiscal rules because of major fiscal meltdowns also have lower debt (Sweden is an example). These stories make sense, and for some countries I found myself developing useful categories that helped locate the kind of debt governance one might expect and how this would equate with debt levels (oil independent like Azerbaijan = limited debt; fiscally restrained like Sweden = limited debt; constrained debt like many developing countries who cannot raise debt = limited debt; net creditor like Japan = higher debt). But one only has simple stories with some countries when looking at these kinds of variables, and I found a number of countries really hard to make sense of. Partly, I believe, because the contextual characteristics influencing governance arrangements are imperfectly apparent…like an iceberg we only see some factors.

So, I asked what evidence there may be about how rules of the game manifest in different places. And I thought, simply, to look at what seemed to be 'acceptable' levels of debt in different nations, given actual data from the prior ten years. A country like Japan has averaged over 100% of debt to GDP in this period, for instance, with relatively little standard deviation from this mean. Switzerland has averaged about 22% and there is very little variation between years. What I take from this is that Japanese authorities are authorized to incur high debt levels but Swiss authorities are not. Ireland had an average of about 45% but the variation between years was really high, indicating a major decrease in debt/GDP levels from 61% in 1998 to the high twenties in 2007. What I take from this is that Irish authorities were authorized to decrease debt to GDP ratios in the 2000s, after experiencing high levels in the 1990s. A return to high levels would not be well received, given that this was beyond what was now being authorized.

I developed a variable out of this analysis that shows how much the 2010 debt levels deviate from the level that seems 'accepted' in the past decade. I used a similar basic formula to that employed in a 2010 Oxford Development Studies article, which is essentially the z score (2010 debt = average debt)/std. deviation. I know that I am assuming a range of things about distributions etc. that create problems but I'm forcing myself to simplify so for the time being let's forget this. Japan scores 1.51, suggesting that the level of debt is 1.5 standard deviations above the 98-08 average. Ireland is 2.35, indicating that its 2010 debt levels were nearly 2.5 standard deviations above the 98-08 average. Note that Japan's debt levels were about twice those of Ireland at the time (174% of GDP as compared with 8% of GDP). Theoretically, however, it would appear that Ireland's authorities were way above their authorized range…even at a lower level of debt…and one would have expected some kind of change.

Consider the following figure that shows 2010 debt to GDP levels and deviations from 'acceptable' levels in about 70 countries.

I like this way of thinking about governance in respect of debt management. It allows us to look at an output or outcome of government activity (the debt it has incurred) but in a contextually specific and relative manner (examining if the government is behaving within the scope of authority it enjoys, as reflected in revealed performance over the past decade):

• It might help explain why the Ireland has responded to its smaller debt burden quicker than Greece has responded to its large debt burden (the Greek debt is more accepted, given the history of high debt and high variation).
• It could also explain why debt levels are a key issue in countries like the USA and UK even though many economists say both countries have 'technically' got space to absorb more debt. Given the recent history, citizens in both countries have become used to having lower levels of debt than they had in, for instance, the 1980s. This means that governments in these contexts are operating in contexts where higher debt to GDP levels are not going to be easily authorized and even a debt to GDP level of 88% draws attention in the USA. At this level government is operating about 2.5 standard deviations above its average debt level in the past decade, stretching its authority to raise debt.
• The analysis also allows us to look at countries that use debt sparingly, and we can better understand the stories here. A country like Sweden has debt to GDP levels of about 40% but this was about 1.5 standard deviations below the 98-08 average. This reflects the fact that Sweden has become a more restrained government in this period, where authority to spend and incur debt has been systematically reduced. Cyprus, which I believe is about to default, is also in this area below the line because of higher debt ratios in prior years.

There are many questions I have about the details in the figure above, but what I like is that it allows us to tell a story about how governments are performing in light of the revealed authority in each context. One might use this to say that governance is more risky as it moves further away from the 0 point on the vertical axis; governments aware of this risk will be expected to either reduce their debt or begin serious political communication about the need for more authority to incur debt. This is, I think, what you see now in the USA. It's not that governance is good or bad in this context: Just that authority is being exercised at an extreme…

Building State Capability at Harvard’s Kennedy School

The Center for International Development at Harvard's Kennedy School has just launched its program on Building State Capability. This is some shameless self promotion of that initiative, but if you are interested in these blog postings it is a good place for you to visit.

http://www.hks.harvard.edu/centers/cid/programs/building_state_capability

In particular, you might be interested in looking at our new paper, Escaping Capability Traps.
http://www.hks.harvard.edu/centers/cid/publications/faculty-working-papers/cid-working-paper-no.-240

One of the arguments we make is related to the discussion I have been having about complex contexts. We propose that the best way of introducing reforms into complex contexts is not to do loads of ex ante studies, but rather to

• enter the context through problems people care about, and then
• progress iteratively with small interventions that flush contextual impediments out, build capability and confidence and political support, and
• allow constant feedback…ultimately fostering the emergence of new hybrids.

In a sense, this is like saying that you need to muddle through the sea of icebergs in your context, ensuring that every step helps you navigate better in future.

Note how different this is to the way institutional reforms are commonly done: They are pre-designed as solutions, pre-planned over years, with limited opportunity for feedback and learning.

Doing reform in a sea of icebergs...the reality of contextual challenges

In my last three posts I have made a few comments about context and governance reform.

• I have noted that contexts in which reforms are planned are always full of preexisting institutions (rules of the game): There is no such thing as a blank slate on which to write a new reform script.
• I have also argued that the institutions one is likely to find look like icebergs, comprising visible elements like laws and invisible elements like norms and cultural-cognitive devices. Institutions are not laws or norms or cultural cognitive mechanisms; they are amalgams of all three.

I noted that many outsiders either treat institutions as one of the three or they don't look hard enough at the norms and cultural-cognitive mechanisms they cannot see. These are like the parts of an iceberg that lie below the water line. They are not easy to see, but can cause even the best reform to fail (like the Titanic).

Some say this iceberg sunk the Titanic (see http://www.irishcentral.com/news/Chilling-photograph-of-iceberg-that-sank-the-Titanic-emerges-147487545.html)

I will get even more complex today, with the idea that all contexts actually have multiple institutions at play.

The idea of an 'interinstitutional' context is not new, but it is important. All contexts are like seas of icebergs, with different sizes and shapes. Some dominate others, some are easy to pass by.

When one thinks about institutional reform I always suggest identifying the icebergs in place, and navigating between them. Think about an application, building on the brief discussion about US budgetary politics I began yesterday.

• There are more rules of the game than 'the Constitution' (which many think is the start and end of all budgetary institutions).
• There are formal Constitutional rules that give Congress responsibility, but keep it vague as to who in Congress is actually responsible, for bringing out the budget.
• There are less formal electoral rules that make the President responsible, though without formal authority to speak of.
• There are rules of the game that force political representatives to speak of limited government, because voters like to hear about this.
• There are rules of the game that require political representatives to get as much federal spending to their districts as possible, with 'pork' drawing support.
• There are rules that make defense spending a sacred cow for some, and health and social security spending a sacred cow for others.
• Etc.

One question I have is whether commentators are honest about thinking about all of these rules of the game when criticizing one or other aspect of the system (understanding that half-truthful criticism and blame-game politics seem also to be a dominant 'rule' of the US system). Another question is whether reformers see these multiple rules when thinking about how they will address the problems before them.

Past reforms (including budget controls in the late 1980s) had minimal impacts and just 'went away' because they did not fit into the sea of institutional icebergs in place. In fact, while the US public financial management system underwent its most aggressive period of reform in past decades it also saw its weakest results (at least in terms of fiscal discipline).

I write about this in my recent article (http://faculty.cbpp.uaa.alaska.edu/afgjp/PADM601%20Fall%202011/(Il)logics%20of%20Federal%20Budgeting.pdf):

    "One could list many others [reforms], from planning-programming-budgeting systems to zero-based budgeting, performance-based budgeting, and the Program Assessment Rating Tool, the formalization of internal audit in agencies, process computerization, the adoption of long-term planning, and more. In many respects, the last century was a period of great budgetary reform in the federal government.
    Interestingly, however, the sustainability problem has worsened in this period. Deficits have been more prevalent since these interventions than before. Federal spending has exceeded revenues in 75 percent of the years following the 1921 act, compared with 38 percent of the years between 1792 and     1920. Spending exceeded revenues in 16 of the 20 years after the 1990 Budget Enforcement Act introduced measures to control defi cits. Deficits have exceeded 3 percent of gross domestic product (GDP) in 8 of the 20 years since the Budget Enforcement Act, reaching such levels only 26 times in the prior 198 years (13 of which were related to wars)."

I know it is oversimplified,  but this experience suggests that past reform activity has failed, repeatedly. I fear a poorly considered reform agenda will suffer similar failure. 

• What institutional icebergs need to be navigated to make reforms work better in this context?
• Which institutional icebergs need to be navigated to make reforms work better in your context?
• How can one navigate the sea of icebergs better than is typically done?

Picture from http://www.bbc.co.uk/news/magazine-17257653

Context, history, governance and development

I have been away from the blog awhile, finishing a couple of book manuscripts. It is time to pick up, however, and I'd like to do so by asking some simple questions about context, governance and development.

Last year I wrote a bit about institutional reforms in Malawi . I looked at the creation of Malawi's Anti Corruption Bureau (ACB) in 1994. The reform turned out to be a problematic failure; not once, but on multiple attempts. The experiences raise some important questions about context, history, governance and development.

As a refresher on Malawi's story:

• The ACB was created in the mid-1990s at a time when Malawi had hoped of being a new, vibrant democracy and economy. It was modeled after the Hong Kong anti corruption commission which had also influenced the Botswana version.
• The ACB initially opened thousands of investigations into corruption. Very few investigations went anywhwere, however, and corruption got progressively worse in the country.
• Measures and analytical work done by organizations likeTransparency International and Global Integrity panned the work done by the ACB and noted that the action behind anti corruption laws was limited.
• Donors depressed with the results attempted to launch a new version of the commission in the late 2000s, with new legislation to boot.
• A 2010 NORAD evaluation noted that the anticorruption reforms (past and present) were “Affected by a political context where politics and institutions are highly personalized and a political culture which tends to discourage impartiality.” The report argues that such contextual factors undermined the impact of impartial, formal anticorruption laws and law-enforcers.
• This resonates with comments made over a decade before, which suggested that 1990s reforms should address contextual “reasons why the formal rules governing behaviour in the public sector have broken down, and why informality—of which corruption is one manifestation—has taken over.”
• It appears that these contextual realities were not addressed, however, either in 1994 or in 2009. In both instances reforms focused instead on introducing new and improved formal rules and rule-makers. The result is history repeating itself, with contextual limits emerging again and again to thwart change.

Going beyond Malawi, to generic questions:

The institutional reform experience in Malawi is not peculiar. It is an example of the many reform  failures that seem to result from the impact of stubborn contextual constraints that are not
effectively considered in most reform designs.

•  Isabelle Werenfels points to such in arguing that Algerian privatization was undermined by, “a country-specific complex interplay of … forces [that] decisively affect the path of any institutional transformation.”
• Andrew Wilder writes similarly about governance reform in Pakistan, where donors consistently push for change “without investing sufficiently in understanding the social, cultural and political contexts within which the
  civil service functions.”

Werenfels’ and Wilder’s comments—and the story from Malawi—raise two important questions:

• What should external actors like donors know about the context in which institutional reform takes place?
• Why do these external actors under-invest in understanding such things?

What do you think?

PS. I'm happy to give my sources to anyone who asks but choose not to include them here because they just make the blog post too bulky.

 

Governance, outcomes and context: What we learn from boxing

My last post continued thinking about outcomes and governance. I am trying to see if we can tie governance indicators to outcomes, such that we have better construct validity of these indicators.

Basic ideas to date, and questions

I argued that this needs to be done in fields where we can focus on outcomes. Child health is one such field. I argued that we need a measure that captures outcomes citizens care about. Under 5 survival rates is my example. I argued that a second dimension of this outcome, costs, is also important. It is not a great outcome if all children are kept alive but it takes all your resources.

Putting all this together, the idea is that good governance in the child health arena will be reflected in high survival rates at low costs. Such outcome indicates that governments have taken the authority given to them by citizens to set up mechanisms and structures that produce welfare value to those citizens. These mechanisms will differ between places and we are not even getting into the detail of what they are...just whether they have delivered.

I made one additional adjustment. I said that we need to control for big contextual drivers that affect the expectations citizens might have of what outcomes should be--and the realities of delivering such. One could call these relevant indicators. In the health area, we know that levels of per capita income are such a variable. So, we need to compare wealthy countries with wealthy countries, poor countries with poor countries, and so forth.

This is where I got to in the last blog. I showed that when we do this we can see how well countries like the USA are performing relative to other wealthy countries (not well) and how well countries like Pakistan are performing relative to other poor countries (well). So, we have a contextually relevant measure of outcomes that tell us something about governance.

But does it? This is the question Alan Hudson asked and which is pregnant in my mind and I am sure many others. Alan raises two dimensions of the question. First, is the measure fully contextualized? There are contextual factors that matter--other than income--that we have not controlled for. Second, is the indicator capturing variations in 'governance'? If we are not fully controlling for context, and country outcomes vary because of contextual factors, aren't we jumping the gun in saying this is about governance?

Great questions. I think they raise empirical questions about measurement and theoretical and applied questions about what governance is. I don't think I will answer them completely here, but let me start. And let me start by going back to sports...

Boxing and governance: can we learn something

I have likened the indicator of income adjusted, costed survival rates as measures of the ability countries have to box at their income weight. They ask a lightweight boxer what his record is in the lightweight division. This is a good indicator of how well that boxer performs against appropriate opposition.

Such indicator is really different to conventional governance indicators. These indicators identify a set of characteristics in the overall best performers and then say these are the basis of good governance. Think of Doing Business indicators that emphasize deregulated industry, or World Governance Indicators that give countries credit for having things like meritoractic civil service systems and decentralized governments. To me, these indicators are akin to having a measure of 'good boxing' that looks at the weight, height and arm reach of a fighter.

This kind of indicator might suggest that good boxers are all over 200 pounds, 6 foot 2 and with an arm reach of 200 cm.  Any boxer that is less than 150 pounds, 5 foot 8 or with a reach less than 180 cm must be bad. Certainly the latter boxer would not succeed against the former, in what the industry calls a 'mis-match'. Like the one shown below.

It is not useful to say that taller, heavier men with longer arm reach will win bouts against significantly shorter, lighter men with less-long arms. I've had some of those scraps on the rugby field and I know they don't work out in my favor! The indicator does not capture how good the fighter is, just how different their basic attributes are--given some intervention in their past (like their birth).

Professional boxing knows this. So it controls for the most defining attribute--weight level--to try and give a better perspective on who is good and who is bad at boxing. Every boxer falls into a weight division and must compete with others in that division. Light middleweights are those weighing between 147 pounds and 154 pounds, for example. They tend to be between 5 foot 6 and 5 foot 11, and their arm reach is between 160 and 190 cm on average.

We know that a fighter is 'good' or 'bad' because of the record they have in their weight division. This is simply the number of wins compared with the number of losses. Floyd Mayweather is 5 foot 8, weighed in the region of 154 pounds in 2007 and 2008, and has a reach of only 183 cm. But he has a record of 42-0. Forty two wins, and no losses (according to wikipedia...I am no boxing genius). Tony Pep, a 6 foot 1.5 inch boxer from Canada, has a record of 43-10-1 (43 wins, 10 losses and 1 draw). One of his losses came against Mayweather.

Mayweather is a good boxer. Pep is less good--but not by any means bad.

Now, if we get to the heavyweights we do the same analysis. Wladimir Klitschko is 6 foot 6, weighs about 210 pounds, and reaches 206 cm with his arm. Wow. He has a fight record of 56 wins and 3 losses and is currently considered world champion. A good boxer.  Axel Schulz was also a heavyweight. Standing at 6 foot 3, he also weighed over 200 pounds and had an arm length of 193 cm. His record was 26 wins, 5 losses and a draw. Not a bad boxer, but not as good as Klitschko.

One wonders if Schulz would have beaten Mayweather. I am not sure if boxing aficionados will jump on me in saying I expect he would have. he just had more size. And in boxing size matters. But that does not mean he was a better boxer than Mayweather. Actually many believe that Mayweather is the best of all time, across all weight divisions.

All this to say that we need to compare like with like, controlling for the broadest factors that affect performance.  This is something we learn from boxing. And it works in governance indicators as well. The approach I have taken shows this.

• The United States is an income heavyweight that does less-well than the countries we can compare it to in the area of child health--its survival rates are just above average but its costs are way above average.
• Singapore is an income heavyweight that does really well when compared against its comparators (its survival rates are higher than average and its costs are lower than average).

See both in the two dimensional graph below, with the horizontal axis showing how many standard deviations all these rich countries are from the average rich country survival rate; the vertical axis shows how far the countries are from the average cost of producing this outcome.

Now, one may say that this does not account for all of the contextual influences on under 5 mortality rates and thus we cannot say "the USA child health sector is governed less-well than that in Singapore."  One would certainly be right in some respects.

Some contextual variables emerge as important.

• First, you will see that bigger countries tend to be located in the upper right quadrant with the USA (relatively high survival rates but relatively high costs as well). The lower right quadrant (with relatively high survival rates at relatively low costs) is in contrast dominated by smaller countries.  When I look at a single measure of outcome performance (as per the last blog), the top 25 child health countries average out with populations of 12 million. The bottom 25 have 31 million. The difference in averages is statistically significant (at 5%) suggesting that bigger countries have a harder time in this area.
• Second, the better performing countries tend to have higher degrees of population density. Statistical analysis suggests that ten times more people are located in equivalent land areas in the better performing countries than the poorer performing countries (again, a statistically significant difference in means).  So it seems that child health outcomes are easier to provide at lower costs in rich countries with smaller, more densely populated populations. Island states are the place to be!
• Third, you can see that the top right quadrant is dominated by the old guard of the OECD. This shows up in the stats. The average number of years' membership in OECD is 41 for the 25 worse performing countries. It is 9 for the 25 better performing countries. It is a statistically significant difference. I will look to interpret it in future posts but some possibilities are: Rich countries that are more newly rich have better child health performance than others; rich countries with newer child health service delivery mechanisms perform better than others; rich countries with younger populations perform better than others.
• Fourth, if we look at the data we find that countries that perform better than others have lower numbers of doctors. The top 25 performing rich countries have about 2.5 doctors per 1,000 while the bottom 25 performers have 3.2 doctors per 1,000. So there is something here about the size of the medical profession (that could be related to the third point on OECD membership and also to the size and spread of population in the first and second points above).
• Fifth, I looked to see if there is any variation between conditions of children in these countries, and it turns out that the better performing countries have lower levels of undernourished children (5 per 1,000 as compared with 5.3 per thousand).

Now one may say we should control for all these factors--and a bunch of others like gini coefficients, number of years kids are in school, teenage pregnancies, and a range of other factors we think or know impact on a country's performance. One may say that we only get to governance issues once these have been controlled. 

So, without taking a firm position, let me say why this may not be a great idea. I will use the boxing metaphor to help me.

• First, boxers in various divisions have something in common--they fall into a particular weight group. Beyond this, they have many things that are not in common. Some heavyweights are taller than others, for instance.
• Second, these variations matter. If we went to do a statistical analysis explaining why some boxers win the heavyweight championship and others do not, we are bound to find that height matters. Apart from Mike Tyson, there has not been a heavyweight champion in the past few decades who is shorter than 6 foot 2 (he stands at 5 foot 10, I believe).
• Third, heavyewights who are shorter than 6 foot 2 still have to compete with other heavyweights. They get no special 'control' to help explain that their losses were against taller opponents. This may have helped David Ruiz improve his record from 44 wins and 9 losses...given 2 of the losses came in decisions against Nikolay Valuev who stands at over 7 ft tall and weighs over 320 pounds (see picture). His record could have been 44 wins, 7 losses, 2 losses against the 7 ft tall guy. No. It was 44 and 9. His context was controlled for in terms of weight, and beyond that he was simply expected to compete. (In fact he did compete, with the losses being controversial...)

• Fourth, one of the reasons why boxing allows someone like Ruiz to be compared and competitive with someone like Valuev is because, when one gets into the ring, factors other then height matter. Ruiz mastered techniques that fighters like Valuev did not. Mike Tyson had aggression, speed and power that many taller fighters lacked. Some fighters have more organized management teams, cut-men in their corners, or preparation approaches. 
• Fifth, many of these other factors are variables that the fighters themselves can control. The techniques they adopt, the number of hours they put in at the gym, their selection of manager. They actually need to control and manage these factors in relation to the factors they cannot control. If a tall fighter wants to use his height as an advantage, he should choose a specific technique, for example. If a fighter has natural speed he needs to engineer a fighting technique that works towards this advantage.
• Sixth, good fighters are the ones who put all the pieces together. They build on their different natural strengths by adopting relevant techniques etc.

I would like to suggest that these sixobservations are important for our thinking about governance:

• Put together, they tell me that there are many factors that an econometric analysis will show explains which rich countries are more likely to provide good child health outcomes.
• Some of these are natural or entrenched contextual advantages  or disadvantages that countries cannot do that much about.  The United States cannot be a small island state like Singapore.
• But there are defining factors that are dynamic and reflect strategic choices countries make to do better. Countries can do something about the medical technologies they adopt, for instance, or the degree to which their children are under nourished.
• The choice or dynamic action is contingent on the natural factors. Countries with large and deconcentrated populations need to adopt different mechanisms to improve their child health performance than Singapore does.
• Governance is about whether governments use their authority to make dynamic adjustments that fit the natural contexts in which they are found. These adjustments should counter the contextual constraints and build on the contextual strengths in place. The USA does not get a pass on poor performance because it is large and dispersed. Good governance is achieved in the USA when it makes the policy, organizational, etc. decisions needed to improve its child health performance given its context. 

 In this analysis, the quality of governance is indicated--not necessarily measured--by the outcomes in evidence. They tell us if the country is performing at, above or below expectation (given its income level), which is an indication of the degree to which authority is exercised in such a way to build on natural strengths and compensate for natural constraints.

What do you think?

The USA lags Pakistan and the Comoros in its governance of child health

CONTEXTUALLY CONTROLLED OUTCOMES GIVE ONE A DIFFERENT PICTURE OF GOVERNANCE

My last post explored the idea of a two-dimensional approach to measuring governance in the child health area. A couple of comments agreed that this is appealing from a policy perspective. It shows visually where welfare is being produced and lost between the quantity and cost elements of the outcome. This is something that you won't currently find in any approach to governance (If I am wrong, please tell me...I'm always looking for new measures).

I also believe that a one-dimensional governance indicator might be calculated through the proposed approach, however, and be something for consideration. It would be a single measure that one could point to in referring to the overall governance outcomes of a field or sector. Again, it does not reflect on governance processes--just the degree to which governments exercise their authority in a way that ensures children stay alive to 5 years and that does not crowd out other outcomes because of excess expenses.

This would essentially involve combining the two elements introduced in my last blog posting to see how far an individual country departs from its income group on both survival rate and cost measures. The combined deviation-from-mean scores are shown in the figure below. The z-score for cost in each country has been subtracted from the z-score for survival rate; for the USA this results in 0.13-2.64=-2.51. The USA fits into the area to the left of the vertical line, which reflects increasingly weaker outcomes, welfare for citizens and hence governance.

   

The vertical axis in the above figure is the same as that used in the figure below (which illustrates World Governance Indicator scores). This shows that the new indicator is not biased by a country’s income group (as most governance indicators are). Actually, the focus on income-group controlled survival rates and costs leads one to identify three lower income countries as having the (relatively) best governance in the 181 country sample (Comoros, Pakistan and Bangladesh). The worst ten performers come from an assortment of income groups, including higher income (Equatorial Guinea and the USA), upper middle (South Africa and Gabon), lower middle (Kiribati, Timor Leste, and Djibouti) and lower income (Sierra Leone, Rwanda and Burkina Faso).

WGI government effectiveness scores for 181 countries, 2007

 

Readers might ask the obvious questions: is governance in the child health sector really better in Pakistan and the Comoros than it is in the United States?

The answer is yes, given the different contexts of these countries.

While Pakistan and the Comoros have lower under five survival rates than the USA, these survival rates are high relative to the income group of which they are a part, and the cost of generating these survival rates is relatively low, given their comparators. The USA has average survival rates, relative to its high income reference group, produced at very high costs relative to its peers. These high costs cause the United States to score substantially below the high income league averages on the combined u5mr/cost measure—as shown in the top figure. 

Put differently, Pakistan and the Comoros  may be lightweights but they box excellently at that weight level. The USA is a heavyweight that is struggling in its weight division...

Observers might argue that the method adopted as a basis for this indicator is biased against wealthier countries, given that these countries are all abutting the upper limit of child survival (100%) while costs have no such limit and the health care costs in wealthier countries are likely to be higher than in others. The backward tilt in the top figure may reflect this problem, with fewer wealthier countries able to score a combined high positive standard deviation and a large group of (mostly OECD) wealthier countries scoring in the negative standard deviation area.

There is variation in the high-income group of countries, however, and some countries (like Singapore) score better than their comparators in both the survival rate and cost data. Better performing countries in this high income group all have low health care costs per capita, as well, and on the basis of our work we argue that costs may actually have a practical, unofficial upper boundary. Eighty-six percent of the high income countries have costs below 10% of GDP, which we would suggest seems to emerge as a reference point to think about as some kind of comparative limit. (This is calculated on the basis of per capita health spending in 45 OECD and non-OECD countries. All of the wealthier non-OECD countries have per capita figures below 10% of GDP and 83 percent of the OECD countries are below this figure too. A total of 93 percent of the 178 countries in our data set have per capita health spending below 10% of GDP.)

The United States is the only high income country to score more than two standard deviations below its peers on the overall indicator. We suggest that it could learn from a host of other high income countries how to govern its child health arena better (especially countries like Japan and Korea, both of whom are more than one standard deviation above the peer mean). These countries appear to have better governed child health fields, where comparatively strong under-five survival rates are achieved at relatively low costs. This is not to say that the governance structures here have cultural, political or other transferability, but just that they appear to offer an example of good practice within the United State’s income league and our indicator points to lessons the USA could learn from them.

In future posts I will relate the performance of higher income countries with other higher income countries,  and so forth, and discuss how this comparison might be used to test for governance impacts on relative outcomes.

 

 

DO COUNTRIES BOX AT, ABOVE OR BELOW THEIR WEIGHT? Contextually-fitted outcome measures to drive thinking about governance

OUTCOMES ARE USEFUL AS GUIDES FOR GOOD GOVERNANCE

BUT ONLY IF WE CONTROL FOR CONTEXT, BEING REALISTIC ABOUT EXPECTATIONS AND DRAWING LESSONS FROM RELEVANT COMPARATORS

Outcomes as a doorway to better governance indicators

Yesterday I did a post on creating outcome measures that could be useful in facilitating focused governance indicators. I focused on child health and suggested that we look at the survival rates of children to see where countries are experiencing good or bad governance. I took some steps:

First, I argued that we need a theoretical frame for the indicator that ties principals to agents in the production of welfare. Hence the statement,

Citizens grant public organizations the authority to ensure optimal provision of child health care, in whichever way appropriate, reflected in the cost efficient production of the highest possible survival rate of all children under five. Governance systems are ‘good’ when they ensure relatively high survival rates at relatively low average cost.

Second, I suggested that we construct a measure that reflects effectiveness (what level of service is produced, for example) as well as equity (how many citizens have access to the service) and cost (how much do citizens have to pay). I argued that the last consideration is particularly important because efficient production of one good allows citizens resources to consume other goods (further improving welfare).  Inefficiencies in one organizational field will impact effectiveness in others.

Following these steps, I created a two-dimensional measure that allows one to see the zones in which countries are performing (see figure 1 below). There is a (potentially) good governance zone, in the bottom-right hand corner of the figure (see below). Here countries have child survival rates above the global average with costs below the global average. There is also a (potentially) poor governance zone, in the top left corner, where countries are producing survival rates below the global average but spending more than the global average. There are two additional zones that suggest mixed performance (high survival rates at high costs or low survival rates at low costs).

Figure 1 from yesterday: Different countries, different outcomes

 

This is not a governance indicator. It is a two-dimensional measure of outcomes that starts to raise questions about governance. We might wonder if countries in the bottom right zone exhibit specific management or institutional or organizational mechanisms that others do not have, for instance. Perhaps country performance can help us say something about governance.

I asked what more information we needed before saying this, however. Today I will address one set of such issues. Put simply, we need to consider other factors that might explain outcomes. Contextual factors may dominate governance in explaining how well countries perform. We must be careful not to move to a discussion of 'governance' making a difference when we don't actually know if it does.

Many governance indicators have not controlled for contextual factors, and this undermines their construct validity. I discussed this a few weeks ago and related to studies by Melissa Thomas and Kurtz and Schranck. These authors argue that many governance indicators are really just different measures of economic development. World Governance Indicators, in particular, have extremely high correlations with country GDP per capita. We do not know if the WGI's are just capturing a country's level of development or other factors driving social, political and economic development. Consider the graph below, which shows that WGI scores are systematically higher in higher income country groups.

 

Controlling outcome measures for context: What results should we expect?

Some contextual factors impact outcomes in a reliable fashion and muddy the study of governance. We know, for example, that income levels have a significant impact on mortality rate statistics (Pritchett and Summers 1996; Filmer and Pritchett 1999), and that even income scores from 25 years ago can explain inter-country differences in under-five mortality rates.

The fact that Pakistan has a lower survival rate for under five year olds than Singapore may thus be more about its level of development than its governance quality. Indeed, only 3 of the 64 countries in the bottom right ‘good governance’ quadrant of yesterday's figure are low income countries (Vietnam, Uzbekistan and the Kyrgyz Republic). Fifteen out of 24 countries in the top left (inferior governance) quadrant are low income, with the highest income country in this quadrant being from the upper middle income country group (South Africa).

Higher income countries are also disadvantaged by development status, given that health care costs per capita are much higher in these countries. Higher income countries account for 32 out of the 57 countries in the above figure's top right quadrant (better than average survival rates at higher than average costs). This could imply higher costs (and hence lower welfare) in these countries, or a health care product that ensures significantly more than survival for under-fives (perhaps because more developed citizenries demand more than just survival and also because health care cost indicators used in relation to child health include a cross subsidization of health costs for the aged).

These kinds of dependable contextual variations are important to consider in both assessing governance through outcomes and in identifying where different countries should look for lessons on how to improve. Like must be compared with like as an approach to control for context in governance indicators.

Roger, Jerrett and I took a simple approach to doing this, starting first by observing which variables do have a dependable influence on the outcome in question. As discussed, in the case of child health, this variable is the nation’s income level (Filmer and Pritchett 1999). Figure 2 below shows just how much variation there has been in mean scores for survival rates over the years, across four ‘income leagues’—lower, lower-middle, upper-middle and higher (based on United Nations  classifications).

Fig. 2. Average survival rates across ‘income leagues’, 1960-2005

 

The figure shows that average under five survival rates in 2005  among lower income countries were lower than the survival rate average in higher-income countries in 1960. Figure 3 shows that the deviation across income leagues is also different, being higher in the lower income group. Higher and upper-middle income groups have seen greater convergence around high under five survival rates.

Fig. 3. Standard deviation in survival rates across ‘income leagues’, 1960-2005

 

Given such data, we should not expect that a lower income country will score a survival rate as high as a higher income country, even if the lower income country has the best form-basedgovernance in the world. Wealthier countries will also likely have higher per capita health costs (even as a proportion of GDP) regardless of whether they govern their systems well or not. 

Given these observations, we create a two-dimensional governance outcome measure that controls for income leagues present across the world, using the United Nations Classification as a guide.

The underlying argument is simply that governance in the field of child health is best assessed through outcomes when comparing lower income countries with other lower income countries, and so forth. It is still comparative, but the comparison is now within income groups and not across all countries. So we ask how far each country’s survival rate and cost scores are from the averages in their league, measured in standard deviations to allow comparison across all countries (applying an approach similar to Anderson and Morrissey 2006 and Lawrence 2006).

Z-scores are calculated for all of the countries, using the score for each country (of the survival rate and cost), and the mean and standard deviation (for both measures) for the relevant country set (low income, lower middle income, upper middle income and higher income (OECD and non-OECD)).  

Figure 4 shows the results, with the USA survival rate ending up 0.13 standard deviations above its high income country group survival rate mean, and 2.64 standard deviations above the high income country group cost average. South Africa stands -2.65 standard deviations below its comparator group (high middle income) in regards to survival rates, and is also 1.12 standard deviations above average mean costs in this group.further research into why outcomes vary between countries, and will help to focus research on real governance and government impacts.  

Fig 4. How outcomes look when controlling for expectations

 

This graph shows where governance systems ensure the provision of child health quality at, above or below their income level; much as one might asks whether a boxer boxes at, above or below his weight level.

As in Figure 1, the lower right-hand quadrant shows those countries that ‘box above’ their income levels by producing higher survival rates than the average of their income group (at zero, the vertical line) at lower costs than the average of their income group (the horizontal line). One should note that some countries change their position given the contextual control:

• Pakistan moved from the lower left quadrant in Figure 1 to the lower right quadrant in Figure 4, for example (because its survival rate was lower than the overall world average but higher than its comparator lower income group average). Pakistan’s performance is below average in comparison to the entire world, but above average when compared with countries in its income group. Much like a middle-weight boxer may routinely lose against a good heavyweight but be the best of the middleweights.
• The USA “boxes at its income level” in terms of the survival rate produced (0.13 standard deviations above the average of higher-income countries) but it “boxes below its income level” in terms of cost of production, with costs over 2 standard deviations higher than the high-income country average. The USA is an economic heavyweight boxing at the middleweight level because of high health care costs. Using the language of governance, we conclude that authority in the US child health field is not being exercised in a manner that maximizes welfare (given the high costs of producing services).
• The situation is more dire in South Africa, where weak governance in this sector is reflected in weak service delivery (lower than average upper middle income group survival rates) and high costs (higher than average upper middle income group cost per capita). South Africa may be an economic middleweight, but its child health care field struggles to compete as a welterweight.

The approach to measuring governance in Figure 4 helps one to identify the top contenders or better governed countries (in this children’s health field) in all income groups:

• 16 low income countries fall into the bottom right quadrant: Pakistan, Comoros, Mauritania, Bangladesh, Eritrea, Madagascar, Papua New Guinea, Lao PDR, Uzbekistan, Kenya, Yemen, Tajikistan, Nepal, Tanzania, Vietnam, and The Gambia.
• 24 lower middle income countries are in this quadrant: Indonesia, Philippines, Thailand, Algeria, Vanuatu, Syrian Arab Republic, Sri Lanka, Azerbaijan, Peru, Cape Verde, Mongolia, Samoa, China, Tonga, Ecuador, Morocco, Armenia, Tunisia, Colombia, Guatemala, Albania, Dominican Republic, Egypt, and Honduras.
• 15 upper middle income countries are also in the good governance area: Libya, Malaysia, Fiji, Mauritius, Venezuela, Romania, Russian Federation, St. Kitts and Nevis, Chile, St. Lucia, Lithuania, Latvia, St. Vincent and the Grenadines, Poland, and the Seychelles.
• And 10 high income countries box above their weight level: Brunei Darussalam, Kuwait, United Arab Emirates, Singapore, Bahrain, Estonia, Cyprus, Korea, Slovak Republic, and the Czech Republic..

It is interesting to note that while we have not controlled for the income bias completely, the above lists show significant variation in income levels amongst the strong performers in each group.

• Six of the fifteen low-income countries listed have per capita incomes below the average of low-income countries. (Using GNP per capita calculated according to the Atlas Method for 2005, available in the World Development Indicator database; Eritrea, Madagascar, Tajikistan, Nepal, Tanzania, and The Gambia  have income levels below the low-income group average.)
• Five of the top ten lower-middle income countries have per capita incomes below the average for their group. (This includes three of the top six performers; Indonesia, the Philippines and Sri Lanka.)
• Four of the top seven in the upper-middle income group also have per capita incomes below their group average. (Fiji, Venezuela, Romania and Russia).
• All ten high income countries boxing above their weight level had per capita incomes below their group averages. (Bahrain, Brunei Darussalam, Cyprus, Czech Republic, Estonia, Korea, Kuwait, Singapore, Slovak Republic and the United Arab Emirates.)

A number of factors emerge as intuitive answers to questions about why different countries fit into these different ‘governance quadrants’. Many of these are not about the processes of governance but rather about the governance context:

• It seems, for example, that country size might matter in influencing governance outcomes (Singapore has better survival rates at lower cost than the United States, a high-income comparator). Is it easier to govern a small health sector cost effectively than a large one?
• Newly-rich countries also seem to do better on this indicator than their other high-income comparators, producing high survival rates at much lower costs. Do newly rich countries have a leapfrogging benefit, whereby they build capacities and relational mechanisms on the basis of the latest technology and lessons from older wealthier countries, who are locked into their more outdated systems?
• Countries with higher Gini coefficients, relative to their income league, seem to perform differently, perhaps reflecting the complexities of governing unequal countries. The USA has the highest Gini for high income countries, and a much higher cost of producing health care; countries like South Africa might argue that their inequality puts them in a higher income league than appropriate (upper-middle) which results in an unfairly harsh benchmarking.
• Higher-income countries seem to do better when there is a greater direct public sector expenditure outlay, which may speak to the complexities of governing market-driven systems. The high cost of a private sector-led US system stands in contrast to other lower cost government led systems in the OECD, for example, suggesting different costs drivers and abilities to contain cost in these systems.

These and other second-stage observations provide important avenues for further research into why outcomes vary between countries, and will help to focus research on real governance and government impacts.  I will explore these more in coming weeks but wonder what you think of the approach in general?

 

Choosing Outcomes To Shape Governance Indicators Around

Today's Question to Guide the Design of Governance Indicators: Which Outcomes Should Government Be Engaged in?

I'm back in Boston and into thinking about governance, governance indicators and outcomes. I have replied to a couple of great conments on past posts--thanks to those who are engaging so thoughtfully.

One of the comments, by the ever-sharp Clay Wescott, suggested that we need a step by step approach to connecting governance indicators to outcomes. I agree. I think my starting step is even earlier than what Clay proposes, however. I think we need to start by asking what outcomes we have in mind when we think about governance. Given we are thinking about governments in particular, the question I ask is: What outcomes do citizens commonly authorize governments to help facilitate?

This question emerges from the assumption that principals delegate authority to agents in order to achieve outcomes. Mirroring basic theories of public finance, I argue that citizens delegate authority to governments when faced with restrictive costs or complicated problems of cooperation and coordination. I could extend my perspective to sociological theory on the state, agreeing that sometimes citizens give governments authority because they beleive it is appropriate to do so (regardless of the presence of cost or coordination-type problems).

I am arguing that citizens are still looking for outcomes in return for the delegated authority, however, no matter why they give such. Further, the quality of public sector governance is reflected in whether public organizations exercise authority in a way that facilitates outcome and value production.

This does not mean that the governments produce services directly. They could regulate a sector. They could subsidize a sector. Etc etc.

Given such thinking, I suggest that public sector governance indicators should focus on domains where most would agree that citizens accord governments authority to influence outcomes. This could include “public goods” interpreted narrowly (such as defense) and more broadly (maybe the Millennium Development Goals (MDGs)).  I wonder what areas quickly come to mind: Perhaps macroeconomic management, policing and defense, education, health care, and environmental protection.

I would love to see a top 5 from readers. What outcomes do we think governments around the globe are authorized to  facilitate?

I think the question is important and takes us from dominant approaches to governance that have assumed that 'small' or 'limited' governance makes sense--regardless of country or outcome being considered.  It calls us  into the debate on the functional role of government--not necessarily its form. 

As an example, in the coming weeks I will be discussing an area in which governments are always involved--child health--and an indicator that cannot be achieved without the enaggement of governments--child survival to five years old.  What other examples would you like to explore?

Stop saying 'Country x has a governance score of y': It makes no sense

If we focus on Governance Outcomes, we need to focus indicators on specific Organizational Fields: Whole of government indicators—or government only indicators—make little sense

Last week I did a blog post on my ideas about linking governance indicators to outcomes. A range of people have responded positively to the idea, though most via email. Try writing comments in and let’s get a conversation going on the topic.

Anyway, I thought I would provide some more discussion on what I see as the implications of focusing governance indicators on outcomes and share specific examples of how this may be done. I will do this in the next few days. I aim to be a little provocative and get some responses…so fire away, please!

What is the appropriate unit of analysis in governance?

To kick things off, I thought it might be useful to think about the way in which an outcomes focus might challenge the unit of analysis in governance discussion and measurement. Given the theoretical approach I outlined last week, it is my belief that governance can, by definition, be assessed only in the context of specific fields in which outcomes are produced. I mean something specific about ‘field’ here, building on the definition in organizational theory: “The particular set of organizations that, in the aggregate, constitute a recognized area of institutional life” (see DiMaggio & Powell, 1983). The field includes “suppliers, resource and product consumers, regulatory agencies, and other organizations” involved in getting things done in a particular functional area.

Such a system is an appropriate unit of analysis for governance research because it is the domain in which outcomes are produced (yes, a bit repetitive but important). Note a few things. First, The Government is in a sense too large a unit of analysis for a governance indicator. Governments are engaged in multiple fields producing multiple outcomes. Governance indicators that pretend to say something about an entire government are problematic from this perspective. Do they refer to governance as it relates to child health outcomes or to educational outcomes or to safety and security outcomes. Or do we think that one set of questions gives valid information about governance issues relating to all three? Second, The Government is in a sense too small a unit of analysis for a governance indicator. Fields involve multiple players, particularly principals and agents, who are constantly engaged in allocating, receiving and managing authority to do specific things, with particular functional results expected. The quality of governance is reflected in how well the entire field engages to produce these results. National governments (the focus of many governance indicators) are usually only one player in any given field. We need to go beyond measuring governance within and through national governments to link outcomes and governance indicators.

The implication, therefore, is that it really makes no sense to have a ‘governance score’ for governments in Mauritius or Botswana or China or Bolivia. We should have indicators for the fields in which outcomes are produced in these countries, thus ‘the child health sector in Mauritius’ and ‘the safety and security domain in Botswana’ etc.

If we focus on fields, we need to expect variation and complexity

One should note some additional important features of organizational fields (as discussed by Richard Scott in his classic text on organizations). They come in different sizes and with different relational structures (often driven by resource access). This can yield fields that are placid and do not change very much with time, disturbed or turbulent and subject to many shocks, randomized, reactive or clustered (See Emery & Trist, 1965). In each variation the relational and normative governance challenges may be different, and one should expect very different governance processes to have become embedded. One should also expect different structural and process solutions in each.

Organizational fields also reflect different authority typologies—or ways in which authority is cognitively and normatively influenced. In some places one should expect social choice to determine who has authority and how it is exercised. In others authority will be more coalitional, and in others it will be federative. Authority structures could also be unitary. Once again, the different authority typologies will probably yield different solutions to governance problems. These differences also emerge because of physical differences in fields—some being geographically centered and some being dispersed. A central organizing mechanism may make the first work. A decentralized mechanism may be appropriate to facilitate best outcomes in the second.

Building on this idea, governments can be expected to play different roles in different fields, largely because the sets of players and institutional logics differ in different fields, rates of change in fields vary, and demands on controlling and shaping behavior are not always the same. The education and health care fields look very different in the USA, for example. The roles of federal, state and local governments differ between these two fields, as does the relative size and scope of engagement by private and non-profit players.

These differences matter because public sector governance is about the exercise of authority by government agents, on behalf of citizen principals, to maximize the welfare of those principals; and all of these elements are field-specific. In some fields citizens delegate authority to government to regulate, in other fields to provide services directly.

So, governance indicators should focus on fields…where outcomes emerge…but with flexibility to reflect context.

As a result of the expected variation in structures between fields within and across countries, and the implications of such for governmental roles, we believe that governance indicators should be defined by the field in which outcomes are produced, players can be identified, and authority structures delineated. This allows governance indicators to look like specific rather than general health measures. Prominent governance indicators pay indirect homage to this, including the WGI, which separates “government effectiveness” from “rule of law” in its components; but these are categories of interest and not defined areas in which authority is exercised—the key driver of the governance definition. As a result, the measures become difficult to interpret. Practitioners, policy-makers and researchers would be better served with indicators focused on specific outcomes in specific fields that make immediate sense and can be acted upon.

I see the child health arena as one field, with identifiable outcomes and navigable organizational fields—where one can identify key agents, organizations, organizing logics and systems connecting and structuring such (even though these do vary across countries and over time, shown in studies on changes to health care fields). Child health is the complex product of multiple players bringing multiple inputs to bear in these fields, under specific authority structures, with different effects in different settings. (Other field-based studies include Beaumont, 2003, on anti-poverty systems and Parto, 2005, on waste subsystems in the Netherlands and the UK and Knill & Lehmkuhl, 2002, on regulation of the internet.)

Making good good governance indicators--the construct validity question

IF YOU HOPE PEOPLE WILL DO WHAT YOU MEASURE

MAKE SURE YOU MEASURE WHAT YOU WANT THEM TO DO

I was asked to give some thoughts on construct validity in governance-type indicators. Here are some thoughts and references to sources that help me in developing such thoughts.

First, I would start with the critique Melissa Thomas provides of the world governance indicators. She asks simply, 'what do they measure' and in so doing raises a major construct validity question, with two dimensions: (1) is there underlying theory about how the things measured in the indicator affect the outcomes designers care about? (2) is there evidence that the things being measured are related to these outcomes?

See her full paper at, http://www.sais-jhu.edu/sebin/q/r/What%20Do%20the%20Worldwide%20Governance%20Indicators%20Measure.pdf

See also the response by Kaufmann, Kraay and Mastruzzi. http://info.worldbank.org/governance/wgi/pdf/kkmresponseejdr2final.pdf They argue a blend of 'construct validity isn't relevant' and 'you don't prove we have a construct validity problem anyway.'

Whatever you think of Thomas's paper and the response, the issue is simply whether the thing being measured correlates with the thing it is meant to be an indicator of. As with simple ideas, however, there is more complexity to consider. Indeed, there are multiple dimensions of this construct validity test.

1. Construct validity requires content validity: does the measure reflect on all facets of the construct? Lawshe proposed a way of testing this, suggesting that panels of experts be given a list of all the questions one intends to ask about a construct, and asked whether each question relates to an essential, useful bot not essential, or Unnecessary aspect of the construct. They could also propose questions that have been left out.

With enough feedback, one can then get an idea about the core content of a construct. If a question is roundly endorsed as 'essential' for example it would be part of the non-negotiable part of the indicator. If it were anything less, one would have to decide if the question was a negotiable, cutting edge or unnecessary element in the indicator.

I have some cautionary notes. First, make sure the experts explain their results- providing theoretical reasoning to back their argument. Make sure they are not just making a normatively biased call. Second, make sure your panel of experts has a good understanding of the construct you are trying to measure and why you are measuring it (see yesterday's discussion on indicators and outcomes). Third, make sure your panel is not biased, reflecting only one normative opinion of the construct. This is one of the problems I think the world governance indicators and other governance indicators has encountered. Kurtz and Schranck and others simply say (with justification) that these indicators reflect neoliberal bias and the perspectives of private sector operators. Fourth, I think you need to go beyond lawshe to actually test the correlation with questions and outcomes, continually, so that over time you build evidence in support of your content decisions.

I have included a couple of links to studies that do this ( in areas like education and health care).

• This is a citation to a study on Ccnstruct validity of 3 indicators of psychological distress in relation to perceived health by Koopmans and Lamers. http://www.mendeley.com/research/assessing-construct-validity-three-indicators- psychological-distress-relation-perceived-health-physical-illness/ The study asks about how each indicator relates to the outcome in question. It uses regression analysis to test the relationship. Combining theoretical and empirical work like this helps foster content validity.
• See also Willis, Stoelwinder and Harris. Their work focuses on interpreting indicators in health care. The authors test the assumption that quality indicators reflect on the quality of care in hospitals. http://www.ncbi.nlm.nih.gov/pubmed/18603538
• See also Mathews, Hackett and Pennell on construct validity of accountability measures and performance indicators in schools.http://www.learningpt.org/sipsig/mathews.html

2. Convergent validity is another aspect of construct validity. This asserts that a measure parading as an indicator of x should converge with other indicators of x. The Tests here are quite simple. Look at indicators that purport to reflect on the same construct and see if they are correlated. An example is Townsend and Kaiser who looked at indicators of fruit intake and psychosocial health. http://www.ncbi.nlm.nih.gov/pubmed/16029687

The world governance indicator folks have done this, and argue emphatically that their indicators correlate highly with other indicators of constructs implied in the broad idea of good governance. There are some problems with this, though. First, the 'good governance' concept is so broadly presented in this work that one is bund to found overlap. Second, the world governance indicators are calculated on the basis of many of these 'related measures'. So, one should expect correlation. But this is mathematical convergence, not theoretical convergence.

Another approach to testing construct validity of a new indicator involves taking the new indicator and testing it side by side with a prior indicator that is acknowledged as having some construct validity already. I like Burke, Burke and Crowder in this regard. http://aei.sagepub.com/content/31/4/1.abstract

The article looks at how student skills of a new indicator of early literacy scores correlated with an older indicator of a similar construct that was already known to predict Later reading efficiency.

3. Discriminant validity is the third aspect I will draw on now. It notes that a measure meant to indicate x should not indicate y, z and other constructs. It is kind of like the opposite of convergent validity in that you should be able to see that it does not correlate with (and rather diverges from) indicators of other things.

This is a dimension where world governance indicators have struggled. The argument of people like me is that these indicators correlate with measures of economic well being, such that it is hard to say they are not just another way of measuring this. Neumann and Graeff suggest this is one of the questionable parts of the good governance indicators they look at. http://www.springerlink.com/content/t417158753238u2q/

An empirical consequence of this problem is that governance indicators typically correlate with other economic, social and political indicators. This means that there could be measurement problems with regressions with governance indicator scores as explanatory variables and democracy, GDP level, etc also as explanatory variables.