Tweet of the day comes from Michael Clemens:
Researchers of earth! Think of a different title for your clever article about Africa. pic.twitter.com/Cf3mIAXvHg
— Michael Clemens (@m_clem) January 18, 2016
a couple of working papers:
1. Disease and Development: A Reply to Bloom, Canning, and Fink by Daron Acemoglu & Simon Johnson
“Bloom, Canning, and Fink (2014) argue that the results in Acemoglu and Johnson (2006, 2007) are not robust because initial level of life expectancy (in 1940) should be included in our regressions of changes in GDP per capita on changes in life expectancy. We assess their claims controlling for potential lagged effects of initial life expectancy using data from 1900, employing a nonlinear estimator suggested by their framework, and using information from microeconomic estimates on the effects of improving health. There is no evidence for a positive effect of life expectancy on GDP per capita in this important historical episode.”
2. The colonial legacy: Income inequality in former British African colonies by A.B. Atkinson
“This paper examines the distribution of top incomes in 15 former British colonies in Africa, drawing on evidence available from income tax records. It seeks to throw light on the position of colonial elites during the period of British rule. Just how unequal were incomes? How did the position of the rich in the colonies compare with that of the rich in the United Kingdom? It investigates how income concentration evolved in the last years of colonial rule, as the British government became more concerned with development, and establishes the degree of inequality at the time of independence in the late 1950s and early 1960s. What was the colonial legacy? How far did colonial inequality persist post-independence?”
and a couple of papers in the May issue of the Journal of Development Economics:
1. Do high-income or low-income immigrants leave faster? by Govert E. Bijwaarda and Jackline Wahbab
“We estimate the impact of the income earned in the host country on return migration of labor migrants from developing countries. We use a three-state correlated competing risks model to account for the strong dependence of labor market status and the income earned. Our analysis is based on administrative panel data of recent labor immigrants from developing countries to The Netherlands. The empirical results show that intensities of return migration are U-shaped with respect to migrants’ income, implying a higher intensity in low- and high- income groups. Indeed, the lowest-income group has the highest probability of return. We also find that ignoring the interdependence of labor market status and the income earned leads to an overestimating the income effect on departure.”
2. The efficiency of human capital allocations in developing countries by Dietrich Vollrath
“For a set of 14 developing countries I evaluate whether differences in wage gaps between sectors – estimated from individual-level wage data – have meaningful effects on aggregate productivity. Under the most generous assumptions regarding the homogeneity of human capital, my analysis shows that eliminating wedges between wages in different sectors leads to gains in output of less than 5% for most countries. These estimated gains of reallocation represent an upper bound as some of the observed differences in wages are due to unmeasured human capital. Under reasonable assumptions on the amount of unmeasured human capital the gains from reallocation fall well below 3%. Compared to similar estimates made using data from the U.S., developing countries would gain more from a reallocation of human capital, but the differences are too small to account for a meaningful portion of the gap in income per capita with the United States.”
3. The minimal impact of a large-scale financial education program in Mexico City by Miriam Bruhn, Gabriel Lara Ibarra, and David McKenzie
“We conduct randomized experiments around a large-scale financial literacy course in Mexico City to understand the reasons for low take-up among a general population, and to measure the impact of this financial education course. Our results suggest that reputational, logistical, and specific forms of behavioral constraints are not the main reasons for limited participation, and that people do respond to higher benefits from attending in the form of monetary incentives. Attending training results in a 9 percentage point increase in financial knowledge, and a 9 percentage point increase in some self-reported measures of saving, but in no impact on borrowing behavior. Administrative data suggests that any savings impact may be short-lived. Our findings indicate that this course which has served over 300,000 people and has expanded throughout Latin America has minimal impact on marginal participants, and that people are likely making optimal choices not to attend this financial education course.” [The part about people making optimal choices by not attending cracked me up–kudos to the authors for such a great abstract]
Tyler Cowen doesn’t, at least not any more. In a provocative NY Times piece today, Tyler says, “sustained, meteoric growth in emerging economies may no longer be possible”. He points to 4 culprits, Automation, Global Supply Sources, Wider Economic Gaps, & Aging Populations.
There is some interesting academic work on the possibility that eventual global convergence is not a sure thing, even if countries ADOPT ALL THE “RIGHT” POLICIES
Here’s Howitt and Meyer (JMCB 2005), “a country may have only a finite window of opportunity in which to raise its skill levels to those required for R&D, failing which the country will remain trapped in implementation or stagnation even if it adopts the same policies and institutions as the world’s technology leaders.”
Even the ever-green prescription of “free-trade” may lead to divergence rather than convergence.
Here’s Bajona and Kehoe (RED 2010), “In models in which convergence in income levels across closed countries is driven by faster accumulation of a productive factor in the poorer countries, opening these countries to trade can stop convergence and even cause divergence….Divergence can occur for parameter values that would imply convergence in a world of closed economies.
In my own research with Norman Maynard (trans-dimensional Bayesian mixture modelling alert!!), we find that in the 1950s and 1960s and most of the 1970s, there were two distinct groups in the global distribution of cross-country income, and there was a high degree of mobility from the poor to the rich group. Since the second age of globalization began in the 1980s, a new distinct group of super-rich countries has formed, the gaps between the poor group and the richest group have grown, and inter-group upward mobility has become a rarity.
Can I get a triple yikes?
Economics, as ever, is truly the dismal science.
Now that classes are over and grading is done, it is a great time to catch up on recent research. Here is a list of papers on Latin America that I am anxious to check out:
Exiting Belindia? Lesson from the Recent Decline in Income Inequality in Brazil by Luis F. Lopez-Calva; Sonia Rocha
Better Jobs in Central America : The Role of Human Capital by the World Bank
Stated social behavior and revealed actions: Evidence from six Latin American countries by Juan Camilo Cárdenas, Alberto Chong, Hugo Ñopo (this is forthcoming from the JDE, which is gated, so the link is to a 2008 working paper)
Risk attitudes and economic well-being in Latin America by Juan Camilo Cardenas, Jeffrey Carpenter (this is also a recent JDE paper; the title is linked to a 2010 working paper version).
Also, from a non-academic perspective, I am eager to read the just published book Midnight in Mexico: A Reporter’s Journey Through a Country’s Descent into Darkness by Alfredo Corchado. Here is a good review of the book in the Washington Post. I am teaching a class on Mexican development next semester. I will mostly use the videos I made for MRU but I am also on the lookout for good background reading for my students. Any suggestions are most welcome.
Oh my. Some experimenters in psychology took previously published articles from, “investigators from prestigious and highly productive American psychology departments” that appeared in, “highly regarded and widely read American psychology journals with high rejection rates (80%) and nonblind refereeing practices.”
They then re-submitted those exact articles for publication with different, less prestigious, names and affiliations attached “e.g., Tri-Valley Center for Human Potential”.
“Of the sample of 38 editors and reviewers, only three (8%) detected the resubmissions. This result allowed nine of the 12 articles to continue through the review process to receive an actual evaluation: eight of the nine were rejected. Sixteen of the 18 referees (89%) recommended against publication and the editors concurred. The grounds for rejection were in many cases described as “serious methodological flaws.””
Only 3 of the 12 were even recognized as already published? 8 of the remaining 9 were rejected when the only difference was name and affiliation?
People, Rogoff-Reinhart syndrome goes well beyond automatic favorable exposure in non peer reviewed outlets. Name and affiliation can carry considerable weight in refereed outlets as well.
And maybe they should. The average Harvard professor is clearly better than the average OU professor.
So is it just cream rising to the top or is it an exclusionary club? And does the study I’ve described help answer that question? Tell me in the comments.