Is the government of Rwanda massaging statistics on growth and poverty reduction?

This is from the latest installment in the debate over whether Rwanda’s official statistics on economic growth and poverty reduction can be believed:

All poverty lines yield similar trends when used consistently over time, indicating that poverty increased between 5% and 7% points between 2010 and 2014. All changes are statistically significant at the 5% level.

It should be noted that our results differ from those obtained by simply updating the poverty line for inflation using CPI data, as was done by NISR in their 2016 trend report (NISR, 2016). In principle, if the data are of good quality and sufficiently disaggregated, both methods should be equivalent and should not yield significantly different results. This therefore raises questions about the quality / reliability of official CPI data, and/or the quality of price data collected by the EICV. In either case, this would undermine our ability to correctly estimate poverty levels in Rwanda. The discrepancies found here should invite us to more closely scrutinize official statistics coming out of the Rwandan statistical office. GDP growth figures appear to be incompatible with the findings of the EICV survey, given than agriculture still accounts for about one third of GDP and two thirds of the labour force.

More on this here.

The idea that Rwanda is growing without reducing poverty is concerning because it means that the implicit bargain inherent in the country’s political economy — growth in exchange for controlled political development — is not working. It is also likely that the benefits of the country’s recent impressive economic performance are accruing to only a few people, perhaps along ethnic lines. That, again, would be a source of serious concern.

If these data are to be believed, one wonders if Paul Kagame’s refusal to step down is informed by an understanding that the implicit bargain might not hold if he steps down because it was all a mirage to begin with.

More generally, what this means is that Rwanda is developing like any other poor country in which the initial beginnings of rapid growth will be accompanied by rising inequality. The singular problem for Rwanda, of course, is that its history and political economy mean that following this trajectory comes with serious risks to continued political stability.

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

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 WrongMorten 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.

Does Chris Blattman hate state capacity?

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.