Tag Archives: Morten Jerven

Review: Why Economists Miss the Point on Economic Growth in Africa

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Africa continues to be a fertile ground for economic research. A significant number of economists in the development economics subfield have made careers explaining the “Africa” dummy variable in cross-national growth regressions — that is, explaining Africa’s “growth tragedy.”

In his latest book, Africa: Why Economists Get it Wrong, Morten Jerven argues that this is a misguided approach. Instead of explaining African exceptionalism (why is Africa poorer than the rest of the world?), Jerven argues that scholarly inquiry ought to focus on explaining fluctuations in African growth, and intra-Africa variation in general economic performance. Jerven persuasively argues that explaining African poverty and trying to find ways to fix it have distracted researchers and policymakers alike from the more useful endeavor of understanding how economic growth (and decline) happens in Africa. The former approach accepts as a stylized fact the lack of meaningful growth in Africa’s economic history; while the latter more realistic approach acknowledges that African economic history has been characterized by periods of both growth and decline.

Screen Shot 2015-06-24 at 4.52.42 PMJerven is an economic historian, and it shows (see also here). He begins by reminding readers that African economic history did not begin in 1960, the time around which aggregate national economic data became available for a large number of African countries. Jerven then shows that economic growth in Africa has been cyclical, characterized by periods of both growth and decline. At the same time, periods of growth in Africa have not necessarily coincided with the implementation of “good” policies as the literature suggests. The “lost decades” of the late 70s and much of the 80s (due to oil and commodity shocks and associated debt problems) were a period of decline that also coincided with the “good” policies implemented under structural adjustment programs (SAPs). Without getting into the details of the specific policies in question, Jerven makes the point that African states’ experiences in the 70s and 80s are not representative of the full history of economic growth and development in the region.

Yet, according to Jerven, it is the growth record from these two decades that has become accepted as the “stylized fact” of Africa’s growth experience. The idea of an African growth tragedy has been so sticky that most economists (with a few exceptions) did not notice the uptick in growth in the region over the last decade and a half. A quick survey of syllabuses on African political economy will reveal this fact.

“Why is Africa poor?” is a question common on course descriptions in many American political science and economics departments, giving the impression that the region has always had a growth deficit to be explained.

Second, Jerven takes on the quality of data that have historically been used to study African economies (remember Poor Numbers?). In this part of the book he pokes holes through major papers in the economic growth literature. The data he looks at range from widely used stats on African economies from sources like the Bank, the IMF, country statistical departments, and other academic sources. He also questions the validity of outcome variables (such as institutional quality, property rights protection, et cetera) that are often found on the left hand side in cross-national growth regressions. Jerven does not seek to provide a review of the development economics literature. Instead, his focus is on the substantive implications of statistical models widely employed by economists to explain relative growth between different regions of the world. In doing so he challenges social scientists to think more careful about issues of measurement and the substantive meanings of regional dummies.

Jerven’s critique of what he calls the “Wikipedia With Regressions” style of academic research is welcome, and hopefully will inspire more students of economics and politics (not just in Africa) to invest in acquiring useful knowledge on the specific countries they study. The basic point here is that the cocksure certainty of findings in scholarly studies on the determinants of growth is unwarranted, given the shaky (data) foundations on which many of them stand. Jerven drives the point home by citing Durlauf, Johnson, and Temple who in their review of the growth literature found 145 different regressors that were found to be statistically significant determinants of economic growth.

Lastly, Jerven takes head on the claim that institutions and good governance cause economic growth. His core argument in this section is that “good” institutions are typically the result of, rather than the cause of economic growth. He gives examples of countries that have experienced sustained economic growth without having the typical bundle of institutions that scholars attribute to be the fundamental cause of long-run growth. I am partially persuaded by this argument, especially after having read Working With the Grain (see review here).

This latter section is the least strong part of the book, and may be the result of trying to do too much in one short text. As a student of institutions I am keenly aware of the importance of elite political stability and institutions that lock in intra-elite commitments for sustainable economic growth. It is not enough to claim that the view that institutions cause growth is misguided because some economies elsewhere have achieved growth without the hypothesized good institutions. I would argue, for instance, that a key difference between the “Asian Tigers” and their African counterparts (some of which we are often reminded were relatively richer in 1960) was the level of stateness (i.e. institutionalization of centralized rule) on account of a much longer experience with statehood. Jerven would have helped his argument by providing alternative explanations for Africa’s economic collapse in the late 1970s and much of the 1980s.

What kinds of institutions matter in “late” economic development? Why did African states almost uniformly fail to contain the oil and commodity shocks and the resultant debt problems that visited them during this period? Has there been institutional variation within Africa over time, and can it explain intra-Africa variation in growth?

Overall, Africa: Why Economists Get it Wrong is a fantastic quick read for anyone (whether in the academy or not) interested in understanding economic growth in Africa. Besides being a brilliant economic historian, Jerven is also an engaging writer with an ability to make even the most technical arguments accessible to the reader. I did not have the book on my original summer reading list but couldn’t stop once I started reading it.

In my view this book is the economics companion to Thandika Mkandawire’s excellent critique of scholarship on African politics. It also raises several very interesting questions that will inspire or reinforce a few dissertations in the field of development economics.

On the IMF and Ebola

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Did IMF policies lead to the inability of the health systems in Liberia, Guinea, and Sierra Leone to contain the ongoing Ebola outbreak?

There has been a lot of back and forth on this question in the blogosphere, the most prominent being posts over at the Monkey Cage Blog by Benton and Dionne on the one hand, and Blattman on the other.

It’s really hard to pin the total collapse of the health sectors in the Mano River Region on specific IMF policies. We don’t have counterfactual Mano River Regions that: (a) did not experience civil wars in the early 1990s, (b) did not have to implement structural adjustment policies (because of severe self-inflicted fiscal distress), and/or (c) reformed their institutions and systems of government to make them more responsive and efficient in providing social services before the outbreak in late 2013.

So the best we can do, really, is to speculate (see this informative post by Morten Jerven).

As Blattman argues, countries that required IMF help from the late 1980s did so because their central banks and treasuries had failed at managing their fiscal and monetary policies (the IMF was essentially a central bank of last resort). Which raises the possibility that perhaps we should blame these countries’ troubles on the Latin American countries that made everyone realize that the developing world’s debt in the early 1980s was unsustainable; or the world commodity crises of the 1970s.

In light of the events of the early 1980s, a plausible simple defense of the IMF is that things could have been much worse (total financial collapse) if it had not intervened. In other words, that it is not clear whether, left to their own devices, highly indebted developing countries would have had an autonomous recovery in a manner that would have laid the foundation for their healthcare systems to be strong enough to identify and contain an Ebola outbreak in their respective remote rural regions in late 2013.

That said, IMF interventions – whatever the justifications – had consequences. The discussion in the blogosphere so far has almost exclusively focused on the fiscal effects of IMF policies (specifically with regard to social spending). But as Herbst has argued in “The Structural Adjustment of Politics in Africa,” there were political consequences as well:

……… there has been almost no attention devoted to what structural adjustment, if implemented, means for the way that politics is actually carried out in African nations. The failure to examine the long-term consequences of economic reform for politics is particularly surprising given that the major instruments of structural adjustment — public sector reform, devaluation, elimination of marketing boards—threaten to change not only the constituencies that African leaders look to for support but the way in which leaders relate to their supporters in the countries south of the Sahara.

……… The paper finds that structural adjustment makes the political climate much riskier for leaders while weakening the central apparatus of the state on which rulers have long relied to stay in power.

Time horizon concerns have significant effects on whether politicians choose to invest in public goods.  The obvious question then is: Without top-down procrustean IMF intervention back then, would highly indebted governments have avoided total economic meltdown via policies that were (relatively more) incentive compatible with their unique political economies? The studies highlighted by Dionne and Benton delve into some of the political economy consequences of SAPs, and the specific ways in which they impacted social service provision.

So going back to the question of whether the IMF reduced the Mano River Region’s capacity to handle Ebola, the simple answer is that we can’t tell for sure. The case for a direct causal relationship is weak at best. But there are also lots of possible causal mechanisms that indirectly implicate the IMF. There is a reason why so many smart academics criticized the implementation of SAPs.

The lesson here is twofold:

(i) Neither the Bank nor the IMF are omnipotent puppet masters able to direct public policy in developing countries. But the same developing countries also lack the ability to perfectly sidestep the policy prescriptions from the IFIs. They have agency, but in very tight corners.

and (ii) International intervention should always, to the extent that is reasonably possible, be embedded in domestic political economies. We (the royal we in development research & practice) like talking about self-enforcing this and that, but then prefer to play “neutral” and “apolitical” interveners all the time. Because we do not live in a world of benevolent social planners, there is seldom anything like a disinterested, value-neutral, and victimless intervention.

Does Chris Blattman hate state capacity?

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The simple answer is NO. The long answer is below.

Blattman’s latest post decries Bill Gates’ (and much of the development community’s) focus on data gathering, and may I add, strengthening of statistics departments. He writes:

I would like to see better GDP numbers–who wouldn’t?–but it’s hard for me to see the constraint on development this revelation would relieve, and why it’s anywhere close to the top ten constraints poor countries face.

The problem with those of us in the development complex, be we academics or Presidents or foundations or NGOs, is we want the world nicely ordered with levers to pull and a dashboard to monitor. And so we put a lot of energies into levers and dashboards and monitors.

I think of poverty and political powerlessness in terms of constraints and frictions–the limitless host of things, little and big, that made it more difficult to run a business profitably or turn a profit or invent a new product or get your kid educated or select the leader who serves your interests. States and institutions and norms and technology and organizations reduce these frictions and relieve these constraints. That is the fundamental driver of development. This is the basic logic behind almost every theory of development in your textbooks, from growth models to poverty traps to everything in between.

Blattman is right that improving the capacity of statistics departments will not do much to alleviate poverty now (although as I write this in the basement of a government library in Nairobi I can’t stop thinking that stats departments need to do more). At the same time however, I would be wary of an outright dismissal of the need for better data gathering by governments, for two reasons.

Firstly, at the core of state capacity is the ability to make legible (depite Scott’s observations) the terrain over which the state claims to have dominion. Strong states are those that know your home address, the number of children you have and how much money you made last year. When governments have the capacity to get better GDP data, they will also know how many kids died or were not immunized last year, etc etc. And perhaps more importantly, they will be able to know how much you made last year and how they can get a bigger share of it. As Besley and Persson have argued, there is a strong case to be made for the centrality of public finance to development. Poor countries have small tax bases yes, but tax evasion in these countries still denies national treasuries lots of cash. And it is not just a question political will. Low capacity plays a role. Imagine trying to implement an income tax in a country of about 20 million adults but where under 4 million are in formal employment and can have their taxes withheld.

Secondly, Blattman seems to be making an argument for the private sector as a key part of greasing frictions that stifle development (which is true). But the private sector initiatives he cites can only flourish when there is strong state monitoring (with reliable data) in the background. Credit bureaus need a strong and enforceable regulatory framework. Otherwise no one will believe their credit reports. Freedom of (government) information laws are cool, but such information must first exist, and in reliable format. In other words stats departments must do their job well.

Lastly, good data also make for more informed politics. Kenya, for instance, could do with more disaggregated GDP data – by counties or lower – as it attempts to implement a devolved system of government and revenue allocation.

All this to say that when states have a handle on how much is produced, they will know how and where to get their share. And the more they demand a bigger share, the more the people will demand some of it to be returned as public goods (and these can also include reliable information that would be accessed via freedom of information laws). Yes, GDP data was invented post-WWII when some countries were already winning against poverty for decades. But even before that the more successful states were the ones that were better at information gathering. Flying blind is simply not an option for states.