Within the Living Standards Measurement Study (LSMS) team, the anecdote goes that in the late 1970s World Bank President Robert McNamara, while reading through the first World Development Report, was stunned to discover that only a handful of countries were collecting any data for the reporting of poverty figures. He found this situation unacceptable and initiated an effort that among other things resulted in the creati
Like all fields of socio-economic measurement, there is scope for debate on how best to assess development progress. There is often much to be learnt from such debate.
But the debates are not always politically neutral. Some observers chose only to look critically at data and methods when the results diverge from their political priors. And some try to undermine evidence that does not fit their priors by questioning the motives of those producing that evidence. A generous interpretation might construe this as some “postmodern” approach to data, but on closer inspection it often looks more like a debating ploy to make up for weak substantive arguments.
I visited three African countries – Ethiopia, Rwanda, and South Africa– during my first week as Chief Economist at the World Bank in June 2008. Many visits to other African countries followed, but Ethiopia holds for me a special interest. I’ve just visited again, for a fourth time. While I am sure I will go back again after I depart the Bank on June 1 this year, this was my final visit to Africa as Chief Economist.
Over four years, I’ve seen Ethiopia gradually embrace structural transformation and its practical application. Leaders there are acutely aware that, if they are to maintain a robust growth rate (GDP growth has been around 10.5% on average over the past few years), they must move away from agriculture, the dominant sector, toward industrial upgrading and technological innovation, often by imitating economies just a few rungs up the economic ladder. Ethiopia’s agriculture sector is important and should not be neglected, but that alone won’t get the country onto a path toward middle income and finally to high income status.
Small firms are commonly believed to have weak access to finance. Previous studies have shown that small firms report larger financing obstacles and use less external finance than large firms do.
It is then a surprise to find in the new research we just published that small firms are significantly less likely to pledge collateral. Using the World Bank Enterprise Survey (WBES) covering 6800 firms across 43 developing countries, we find that all else being equal, the odds of small firms-- those with less than 20 workers-- pledging collateral for formal loans from financial institutions are about 35-37% lower than those of larger firms. Yet when loans are collateralized, the ratio of collateral value to loan value for small firms is not statistically different from that for larger firms. These results are robust across countries, or within a particular country. Given that small firms have weak access to finance, this is a counter-intuitive, yet interesting finding.
Does an increase in household wealth decrease child labor in poorer households? Available literature in economics suggests that when poorer households need to make their ends meet, they tend not to dispense on child labor. And as households’ income increases, child labor declines in favor of schooling. However, if schools are few and far, and their infrastructure and teachers’ performance are deficient, there is less incentives for parents to send their children to school. Child labor would then appear as a sensible option, not only for increasing family’s current income but also for training children in skilled work. Thus, an appropriate question is: To what extent and under what conditions an increase in household wealth can either decrease or increase child labor in poor households?
When I moved from Norway to Washington with my family almost seven years ago, I went from paying more than $8 per gallon for gasoline in Oslo, to around $3 per gallon in the U.S. Our house is close to a bus stop for getting to the Metro, but the bus service is unreliable. Here is a first-hand illustration of how the price of gasoline affects people’s behavior. It is inexpensive to drive, so relatively few people are strongly dependent on bus service; with limited ridership there is less call for more reliable bus service and less money available to provide it. Where it is more expensive to drive, there is greater demand for higher-quality service and lower demand for more fuel-intensive cars. And fewer people want to live far away from their jobs or schools, or in very large dwellings that are costly to heat and cool. Our work in energy and environmental economics confirms how economically sound energy pricing is crucial for inducing more efficient behavior.
Ideas often come from unexpected quarters. Last week, Ricardo Hausmann came to the World Bank to talk about his work on economic complexity. I missed the seminar, but afterwards read his Atlas of Economic Complexity: Mapping Paths to Prosperity. (I had actually already looked at the stunning – but rather confusing charts – of his coauthor Cesar Hidalgo after reading Tim Harford’s great new book Adapt: Why Success Always Starts with Failure.)
On the face of it, the Atlas of Economic Complexity doesn’t have a lot to do with the topic of this blog post – whether World Bank staff are under-specialized. But bear with me, and I hope I’ll convince you otherwise.
These few words from the ‘The Face of Female Farming’ aptly capture some of the roles and responsibilities of women in our society. Yesterday, the world celebrated the 101th year of International Women’s Day. Today, we continue to celebrate and honor women and girls worldwide by highlighting some interesting work and articles produced by the World Bank in the field of gender over the past year.
In an article on a Brookings website, Laurence Chandy and Homi Kharas chide the World Bank for three so-called “contradictions” in its global poverty numbers, including the Bank’s latest update. Let me look more closely at these “contradictions” in turn.
First, Chandy and Kharas chide the Bank’s team for assuming that North Korea has the same poverty rate as China. I wish Chandy and Kharas good luck in trying to measure poverty in a place like North Korea, with almost no credible data of any sort to work with. I could offer a guess that 80% of North Korea’s population is poor today—roughly the same as China before it embarked on its reform effort in 1978. This would add slightly less than 1 percentage point to our estimate of the “$1.25 a day” poverty rate for East Asia in 2008.
It’s not every day that jumping monkeys and George Clooney are discussed in the context of a framework for development economics. But that’s exactly what happened on March 6 when Justin Yifu Lin presented his book, ‘New Structural Economics: A framework for Rethinking Development Policy’, with Regional Chief Economist for Africa Shanta Devarajan moderating and Harvard Professor Ricardo Hausmann providing a lively counterpoint as discussant. Justin made an impassioned case for how industrial structure is endogenous to endowment structure, arguing that following comparative advantage and involving the state as a facilitator can be the ticket to income growth and poverty reduction. Hausmann argued that comparative advantage is not determined by an economy’s broad endowment of factors, but by what you know how to do. He also argued that imitation (for example, if George Clooney wears a brand of cologne, other men would wear it too) and moving preferentially towards nearby goods (the jumping monkey analogy) are powerful drivers of innovation and success in industry. Watch the video to get the full narrative or download the Powerpoints here.