All posts by Sophia Kagan

Sophia Kagan is currently a student at the London School of Economics, completing an MSc in International Development Management. Prior to this she was a consultant with the United Nations Industrial Development Programme and an Australian Youth Ambassador with the International Labour Organization in China.
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It’s Arrested Development! Why ‘fixing’ dysfunctional states is a bit like fixing dysfunctional families

The story of a ‘wealthy family who lost everything and the one son who had no choice but to keep them all together’ might not sound like a great allegory for why technical cooperation assistance to least developed countries has so often been unsuccessful, but look closer and important parallels emerge.

Anyone who’s laughed along with protagonist Michael Bluth’s futile attempts to get his family to be frugal, or to find employment to pay for their extravagant spending, will know that prolific spenders will always find creative ways around the limitations you place on them.

Cut personal credit cards and they will find a way to the company checkbook. Place them in jobs and they will shirk. Drive them to rehab clinics and they escape through the back door. Hilarity ensues.

But the joke might be lost on the citizens of countries run by kleptocratic dictators who, despite whatever institutional reform programs international financial institutions choose to throw at them, always seem to get away with lavish consumption.entertainmentArrestedDevelopment

Indeed, Bill Easterly’s The Elusive Quest for Growth: Misadventures in the Tropics reads pretty much like an episode involving the Bluth family… with some import licenses and domestic liability dollarization thrown in. According to Easterly, “a government irresponsible before an adjustment loan has unchanged incentives to continue being irresponsible” and will thus simply create the illusion of adjustment through creative fiscal accounting – freeing up funds for today by “borrowing from tomorrow” (eg. skipping infrastructure maintenance, robbing pension accounts, dodgy privatizations and the like).

Indeed, many would argue that it was not so much the policies of structural adjustment that led to disaster (though I would question the empirical evidence behind uninhibited liberalization!) but rather the fact that the prescription didn’t pay any attention to the wily nature of the patient. Thus, failing to get incentives right for elites meant that they gratefully helped themselves to donors’ money, introduced ostensible reform and surreptitiously sabotaged it.

A (developing) world of sponges? 

So, can we equate Michael’s misguided but sincere attempts to change his financially irresponsible family with equally misguided donor intentions? And, have the disastrous consequences of ignoring political economy realities improved aid-giving?

Probably not, at least according to two recent books on development assistance – Development Aid Confronts Politics: The Almost Revolution by Thomas Carothers and Diane de Gramont, and The Limits of Institutional Reform by Harvard academic Matt Andrews.

Carothers and De Gramont outline why the modern aid enterprise which emerged in the late 1950s and 1960s was an apolitical endeavor, focused on socioeconomic objectives, and then track how this changed in the 1990s. This change was both in terms of increased ‘democratization’ aid, and also improved sensitivity to political realities in relation to aid projects more generally (but specifically public finance management).

The problem is however two-fold. First, according to Carothers and de Gramont the new changes do not go far enough – donors still invest relatively little in trying to understand political realities of countries and often prefer to fall back on ‘best practices’.

Second, just as the ‘political revolution’ is slowly gaining momentum amongst donors, it is increasingly becoming less and less relevant to least developed countries who can often choose from a host of less picky financial sources (eg. China, and other players, as identified in a recent Overseas Development Institute (ODI) Report). Russia rejected US assistance in September last year claiming it was too political, Bolivia followed suit last month and there is growing pushback in other countries too.

But, before we characterise donors as misguided technocrats who have finally ‘seen the light’ about understanding political landscapes, let’s look at Matt Andrews’ book on institutional reform. Andrews argues that donors have for too long been ‘hawkers of best practice’, not only failing to see how ineffective institutional reform has been through basic ignorance, but perhaps even engaging in willful blindness.

Ok, so he doesn’t actually say that in the book, but the implication certainly seems to be that donors are not just overly optimistic about developing countries’ capacity to push through painful reforms (that would never get through in the donor countries) but that they are guilty of lazy policy design and perhaps even ulterior motives. How else can we understand failure rates of between 40-70% according to the donors own calculations?

During the book launch at ODI, Andrews gave an example of a country so under-developed that Ministry of Finance officials were drafting the national budget with paper and pencil – not a single computer in sight. At the same time, it turned out that there was a World Bank consultant engaged to help the Ministry with some kind of sophisticated double accounting.

Some nations may need analysts and therapists, but not both at the same time.
Some nations may need analysts and therapists, but not both at the same time.

Wouldn’t it have been better for the guy just teach the Ministry officials how to use Excel, and for the donors to supply a handful of computers? Perhaps. But that’s not what he’s going to want to put on his resume. He wants to boast about the technical sophistication he brought to this impoverished nation, and so does the army of technical development economists and specialists with sharp minds, expensive degrees and lofty career objectives. They certainly don’t want to experiment with new strategies and risk failure. Stick with the tried and tested and once legislation is passed, reap the media benefits and never mind about whether it actually leads to long-term change.

So what’s in store for the next season? 

Where does that leave Michael Bluth and his donor community brethren trying to achieve economic prosperity? Carothers and De Gramont would advise him to hire governance consultants to undertake a careful review of the incentives which drive his relatives and work on reforming them. They would advise being ‘politically smart’ and ‘taking seriously how all aid programs in a country fit into and affect the broader political environment’. Andrews would pipe in with a focus on Problem Driven Iterative Learning (‘PDIA’) – get the Bluths together to focus on their own problems, reflect on the opportunities and stop focusing on best solutions. Andrews positively references such initiatives as Cash on Delivery, though some of the projects undertaken by Tony Blair’s Africa Governance Initiative, which provides technical know-how for policy making also seem to be consistent with his approach.

All jokes aside, this is a serious issue which exposes everyone’s flaws – the donors, the donees and perhaps even us, development practitioners. And of course, not all administrations in developing countries can be compared to money grabbing former socialites! Perhaps the most that a more ‘politically savvy’ approach can teach donors is how to separate those who are unwilling to reform from those who cannot for plausible political reasons (the Carothers and de Gramont approach) and design initiatives appropriately. Next, focus on small steps that reward enforcement not just passing flashy legislation not worth the paper it’s written on (the Andrews approach).

Most of all, don’t hold your breath. Development is long, painful and messy. Lucky that Arrested Development fans are such a patient lot.

How do we develop happiness? (Part 2)

In Part 1 of  ‘How do we develop happiness’, Weh Yeoh looked at the increasing trend of governments to enact policies aimed at increasing their citizens’ happiness.

In Part 2, Sophia Kagan looks at how governments can measure happiness and how these measures can impact on government policies. Is there, hiding amongst the empty political rhetoric, a real way in which policy makers can genuinely make people happier?


The origins of measuring ‘happiness’

Ever since the invention of the abacus, increased income has been the holy grail of progress. Both in rich and poor countries, increased GDP was a constant mantra, almost synonymous with development and growth. That was until a realisation started to creep into the minds of economists and policy makers (based as much on personal anecdotal evidence as on empirical studies) that money doesn’t necessarily make us happy.

Of course, they were not the first to come to that ‘ground breaking’ realisation. Artists, writers and philosophers from Artistotle to Kanye West have assured us that money doesn’t equal happiness. Psychologists have meanwhile been mining for data on happiness levels for decades through surveys and experiments and have also come to the conclusion that the correlation between rising income and subjective happiness is weaker than once thought (yes, the rich are generally happier than the poor but as countries get richer they often don’t get happier).

Although Bhutan’s trial of Gross National Happiness began back in 1972 (see How Do We Develop Happiness? Part 1), the debate about the inadequacies of the GDP measure didn’t reach Western shores until perhaps the 1980s when economist Amartya Sen coined the concept of the “capabilities approach” as another way of figuring out how to improve people’s well-being through public policy. The focus of his new approach was to look at the opportunities or freedom that people have to choose the life they want to lead rather than their consumption (example: a traditional approach might classify a man who has not eaten for 2 days as deprived. However, if he is fasting for religious reasons, the capabilities approach would reflect the fact that it is his decision and freedom not to eat).

Sen’s new approach became so influential that it came to form the framework of the UN’s Human Development Index (‘HDI’), which was created in 1990 with the purpose of shifting “the focus of development economics from national income accounting to people-centered policies’’. Though Sen was loathe to fix in stone a list of capabilities to be measured (arguing that this depends on personal value judgements), the HDI does just that – propounding indicators of human development across three themes of lifespan, educational attainment and income. Over 169 countries are now included in the HDI’s annual league tables (that rank countries according to their performance on indicators) making it perhaps the most widely used index after GDP.

Since the development of the HDI there has been an explosion of splinter indexes and league tables including the Happy Planet Index, the Genuine Progress Indicator, the Satisfaction with Life indicator, the World Values Survey and the International Social Survey Programme. The concept has even made its way to the UN General Assembly, which, in July this year, adopted a non-binding resolution that acknowledges happiness as an indicator of a country’s success. The UN resolution calls on countries to “pursue the elaboration of additional measures that better capture the importance of the pursuit of happiness and well-being in development with a view to guiding public policies”.

A closer look at different ways of measuring ‘happiness’

1. Capabilities approach: Examples of this approach are the HDI, the MPI (discussed below) and the Millennium Development Goals. This type of measurement (built around objective measures rather than subjective levels of happiness) has been particularly common in the international development sector where it is perhaps most relevant. Although traditionally measurement of poverty has been focused on household income (think of the seductive simplicity of the $1 or $1.25-a-day measure), this often doesn’t give a comprehensive picture of why and how people are poor. Enter the Multidimensional Poverty Index, a sister index of the HDI which measures acute poverty across 104 countries through indicators including child mortality, nutrition, years of schooling, access to electricity, drinking water, sanitation, cooking, and, even, the flooring of your abode. A household is identified as multi-dimensionally poor if it is deprived in some combination of indicators whose weighted sum exceeds 30 percent of deprivations. Sounds great in theory (after all, the measurement can at least provide policymakers and donors with information about the most vulnerable households and groups), but the indexes are not without their share of critics. Some lament their failure to include more factors (such as environmental degradation or other ecological factors). Others quibble over the formulas used in the number crunching, arguing that it gives an overly negative image of certain countries, such as many of those in Africa (for more info see here and here).

2. Measuring ‘subjective’ happiness (ie through self-reporting and analysis): One example of this is the UK, where the government proposes to collect statistical data about people’s perceptions of their well-being and life priorities (through self-reporting on such questions as how happy or anxious they have been feeling, how satisfied they are with their lives). The advantage of this approach is that you can directly gage what is important to the population using flexible indicators. In addition, this type of measurement can be seen as a democratic way of impacting on government policies. The difficulty is that subjective happiness is just that – subjective. It can be hard to analyse and use to draw useful conclusions.

Of course, both subjective and objective factors can be used together in measuring happiness. In the report commissioned by France’s president Nicholas Sarkozy, drafters Joseph Stiglitz and Amartya Sen attempt to marry objective measurement with self-reporting (though the report is fairly vague on exactly how this is to be done). The OECD has also attempted to combine the two types of measurement in its own index which allows the users to play around with the weighting of the indicators, depending on what you think is most important.

Measure this! How do you objectively measure the intensity of (un)happiness when priorities can be so drastically different? You also run the risk of collecting a whole lot of contradictory data that is hard to use for the purposes of decision making

Are the indexes fairly similar though? Does data from one support the other?

Instinct might tell you that these measures should fit together. After all, if I live in a country with high life expectancy, good education opportunities, good healthcare, then presumably my life satisfaction will be fairly high. And if I have overall life satisfaction then I’m likely to respond fairly well in ‘happiness’ surveys?

Not so, it seems. Partly this might be due to the fact that short term happiness and long term happiness aren’t identical and the fact that self-reporting surveys might measure short-term ‘hedonic’ contentment (or discontentment) or they might measure long-term satisfaction (see Part 1, which discusses how having children may result in short term unhappiness but long term satisfaction). Partly it may be because there are just so many surveys asking so many things that ultimately there’s bound to be some contradiction without coherence and consistency.

Take the case of Australia. Australia has consistently rated high on HDI, moving from 4th place in the world in 2008 and 2009 to 2nd place in 2010. It also ranks very highly on OECD charts. However, some argue that this characterisation is inconsistent with other data and incorrectly implies that Australians are ‘happier’ than they really are. For example, Blanchflower and Oswald (2006) use life satisfaction statistics to find that Australia’s performance is only mediocre, and even poor in some categories such as job satisfaction: looks at all the various indexes long enough and you’ll see a myriad of other contradictions for other countries as well.*

This is confusing. If there’s little correlation between the various happiness measures, might it not be best to stick with something clear like GDP measurements in policy making?

Measuring happiness and using it for public policy is a little tricky but that shouldn’t cause governments to give up. In fact, governments already take well-being issues into account when governing – for example, they look at air quality, urban planning such as community areas and parks to improve citizens’ wellbeing even though they are not strictly speaking GDP-related concerns. Should governments, however, take the step of quantifying citizens’ happiness (both through a needs and an outcome assessment), to make the process more rigorous and scientific? Considering the difficulty of measuring happiness, would it be useful, or just a costly and distracting exercise in navel gazing?

My conclusion is that measuring happiness (or well-being, satisfaction with life or whatever you want to call it) is a good thing when using the right tools because it provides transparency and incentive to government. It is without measurement that government can give lip service to these concepts without taking any genuine action. For example, quantifying greenhouse gas emissions has been important in making real progress beyond aspirational grandstanding. However, overcomplicating the issue with too many measuring sticks is also not ideal. Perhaps it’s best to focus on a few measurable indicators (those employed by HDI can be a good starting point), particularly on measures that are quantifiable, but supplementing where necessary with targeted subjective surveys. Despite scepticism, both objective and subjective indicators have been shown to provide meaningful and reliable data when used in the right way. Not only does this hold the promise of delivering a good measure of quality of life, but it also gives governments a way to better understand their citizens, beyond just knowing what they earn and how much they pay in taxes.

In summary, a matrix of indicators, not just GDP, is likely to give us a much better picture of development in both wealthy and least developed countries. Although the indicators can be hard to determine, there are plenty of measures which gives us a good guide that can be followed and tweaked in future.

*See article here for a response to Blanchflower and Oswald’s assessment