Last Tuesday, as part of CSAE’s weekly seminar series, James Fenske presented his new working paper on ‘War, Resilience and Political Engagement in Africa’ (co-authored with Achyuta Adhvaryu) in which they test whether early-life war exposure influences later-life political engagement in Africa. Their evidence comes from combining data on the location and intensity of conflicts since 1945 with Afrobarometer data on political attitudes and participation from 17 sub-Saharan African countries. After presenting a large number of regression models, specifications and robustness checks the authors conclude that childhood exposure to armed conflict does not have an impact on political attitudes and participation.

Papers that centre on non-results are difficult to sell, as economic journals have a strong bias towards publishing research that ‘proves’ or ‘disproves’ a particular hypothesis. Given that there is a lot of micro evidence on the impacts of conflicts on health, education and political participation outcomes, this non-result is surprising. It may be due to data quality or estimation (identification) issues. However, I think that the authors have been careful in their construction and examination of their cross-regional dataset and find their non-result believable.

One issue I have is with their title and definition of ‘war’. They do not restrict their analysis to wars, as their title suggests. Typically this literature defines ‘wars’ as conflicts resulting in more than 1,000 battle related deaths per year. Their definition is broader and includes all armed conflicts in the 17 Sub-Saharan countries that they are able to include in their study. They include conflicts in Botswana and Tanzania, typically perceived as peaceful countries. On the other hand, wars in the DRC, Ethiopia and Sudan are excluded (due to lack of data on political attitudes and participation).  I would like to see more informative descriptive statistics and a discussion of armed conflict in Sub-Saharan Africa.

Aside from definitional issues, their non-result may be the consequence of asking a non-relevant research question. However, I do think that the authors are posing an important question because it may us help to understand how we can break conflict traps and make the world a safer place.

Ach and James’ paper appears to contradict the recent research by Tim Besley and Marta Reynal-Querol. These authors suggest that historical conflicts have long lasting effects: African countries and regions with pre-colonial deadly conflicts are more likely to experience armed conflict today. Countries experience long lasting conflict traps of recurrent cycles of violence. According to Ach and James this appears not to be the case: an individual’s past does not shape his/her political views and participation. Individuals that experienced conflict in childhood are no more likely to engage in conflict. However, I would argue that certain attitudes and participation patterns do not guarantee peace, because attitudes do not always translate into the actions we would expect. One example is the CSAE work on Kenya’s 2007 election voting behaviour and subsequent violence. More research on the link between attitudes and action is needed.

But how do we square the empirical observations of the high frequency of recurrent conflict and Ach and James’ suggestion that individuals are resilient and no more likely to take up arms after experiencing conflict in childhood? Certain regions may be more conflict prone over the course of history because of the resources that can be extracted from this region, not because of the individuals who live there. The organisation of large scale violence requires resources, not just ‘attitudes’. Geography, settlement patterns and institutions are all interrelated and shape the risk of (recurrent) conflict. Thus, conflict risk may not be down to individuals’ attitudes over the course of their lifetime but the region’s geography, migration and institutions.

If it is correct that in general attitudes shape our actions, the message from Ach and James’ working paper can be interpreted as a very positive one: it suggests that we can escape the conflict trap; conflict does not beget more conflict. Steven Pinker in his book on violence summarizes a lot of evidence showing that the world today is much less violent than it has ever been. His concept of violence is broad and includes wars, homicides, torture, racial hate crimes and gender based violence. Pinker argues that throughout history there have been ‘civilizing’ efforts, resulting in a reduction of violence. His examples are based on evidence from rich countries, mainly because they have seen the largest reduction in the levels of violence. However, if the story by Ach and James is true, it is likely that there is an underlying ‘civilizing’ process, reducing violence in these 17 African countries. What is this ‘civilizing process’? Is it home grown or an ‘imported’concept? How can it be strengthened ? These are potentially interesting questions for future research.

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The recent trade literature has shown a growing interest in the analysis of barriers to trade within countries, especially with reference to developing economies such as China. Apart from pure academic curiosity, this can be explained by two main factors. First, with the expansion of the WTO membership as well as regional free trade agreements, the international barriers to trade are declining rapidly; as a result, intra-national barriers are becoming relatively prominent. Second, barriers within the boundary of a country are likely to be caused by more fundamental market distortions, offering a great opportunity for studying the institutional causes of market imperfections from a trade angle.

Measuring Intra-National Protectionism

Internal barriers to trade are typically in the form of regional protectionism and some of the recent research in this area argues that these distortions may be of similar significance to international trade barriers in affecting market efficiency and thus ultimately welfare.

However, providing evidence for intra-national protectionism is hard. Unlike international trade barriers that can be measured with tariff data or by quantifying non-tariff-barriers, protection by local governments against nonlocal firms within the same country can take many different forms and is typically hidden (especially for practices related to rent-seeking), or at least not explicitly announced or recorded by the authorities or anybody else. The existing empirical literature on China therefore uses implicit measures of protectionism at an aggregate province or industry level: in the absence of significant regional protectionism one would, for instance, expect regional specialisation in production and/or price convergence across provinces to be detectable in the data. The seminal study in this literature by Alwyn Young (2000) compared data from China’s Socialist period with those after the economic reforms and concluded that while China significantly opened up internationally over this time period it had also become internally fragmented. Since then a number of studies have either confirmed or rejected these findings (e.g. Bai et al, 2004; Poncet, 2005; Fan and Wei, 2006; Holz, 2009) but were always confined to analysing protectionism implicitly by investigating aggregate sector or province-level data for signs of specialisation, price convergence etc.

Micro-Level Evidence for Protectionism

Our new research paper on ‘Intra-National Protectionism in China’ is, to the best of our knowledge, the first study to provide direct, firm-level evidence for intra-national protectionism and market fragmentation in China. We do so by investigating the unique case of public disclosure of ‘illegal’ drug advertisements by provincial Food and Drug Administrations (FDAs).

In China’s pharmaceuticals market a large number of relatively small enterprises are vying for a share of the large ‘over the counter’ market in generic drugs (China’s health spending is quite large compared with other middle-income or even OECD countries). Since advertisement is crucial for these firms and drug advertisement rules (set by the State FDA) are ambiguous and subject to interpretation, local FDAs can selectively inspect and ‘disclose’ nonlocal firms for ‘illegal’ advertising (i.e. naming firms and sharing information about their violation, but also some form of punishment, including cancelling advertisement licenses).

Why would these FDAs discriminate against nonlocal firms? First, though the provincial FDAs are linked to the State FDA in Beijing through a clear administrative hierarchy, their funding as well as decisions about the appointment of their senior officials is determined by the local province government. Second, China’s system of fiscal decentralisation incentivises provinces to push local firms so as to increase their tax revenue – so far so competitive. However, given the institutional setup and the ambiguous advertisement rules, this also incentivises provinces to protect local producers and discriminate against firms from outside the province.

Our descriptive and regression analysis goes to show that the patterns of ‘disclosure’ disproportionally expose firms from outside the province, thus constituting local protectionism on behalf of the provincial FDAs.

The above figure provides a first illustration of the discrimination we detect in our sample of all state-owned and all medium- and large non-state firms (annual sales in excess of around $600,000 in year 2000 values) in China’s pharmaceutical industry over the 2001-2005 period: if we assume that all firms sell their drugs in all 31 provinces then in the absence of protectionism the share of local firms being disclosed should be in line with the relative size of the local pharmaceuticals industry (the 45 degree line marked in the figure). As can be seen, on average, local firms get disclosed disproportionally less than nonlocal ones.

Since the assumption that all firms sell their products in all provinces is difficult to maintain, we carry out our regression analysis using additional information on advertisement licenses available for a subsample of three provinces: Jiangsu, Zhejiang and Inner Mongolia. Controlling for a host of other factors at the firm-level, including ownership type, firm size and previous history of disclosure as well as province-level idiosyncrasies, we find that the disclosure probability is between 9 and 13 percentage points higher for firms from outside the province, thus providing direct evidence for local protectionism. Investigating whether this form of protectionism increased or decreased over time we find higher discrimination in the more recent years, thus supporting the original findings by Young (2000) at the aggregate level.

Political Connections and the Patterns of Disclosure

A second aspect of our study investigates the impact of a uniquely Chinese form of political connections on this phenomenon. Political affiliation (lishu) to different levels of government (e.g. county, province or central) could be seen as a means to avoid disclosure or entice local officials to focus their efforts on nonlocal firms. Our results here suggest that local FDAs specifically target nonlocal firms with political affiliation to rival provinces: their probability of disclosure is up to twice that of their unaffiliated nonlocal peers.

Conclusions

Our study is the first to provide direct evidence for intra-national protectionism in China. Using a unique dataset for public disclosure of illegal drug advertisement which we matched to a large firm-level survey for the years 2001-2005 we find that nonlocal firms have an average 10% higher probability of being disclosed as having illegal advertisements, with nonlocal firms with a political affiliation (lishu) to a rival province even more likely to be the target of discrimination.

Since the mechanism we detect points to relatively generic institutional roots of regional protectionism, we believe one might suggest these findings have wider validity beyond the pharmaceutical sector. One policy implication is that reducing intra-national barriers probably poses a much greater challenge than lowering international barriers as the former usually requires much deeper and wide-ranging domestic reforms, both economic and political.

The full paper “Intra-National Protectionism in China: Evidence from the Public Disclosure of ‘Illegal’ Drug Advertising” by Markus Eberhardt, Zheng Wang and Zhihong Yu can be found here.

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The final plenary of the CSAE conference, chaired by Prof. Paul Collier, brought together Prof. James Foster (Institute for International Economic Policy at the Elliott School for International Affairs), Prof. Paul Glewwe (University of Minnesota) and Mr. Charles Kenny (Center for Global Development), to discuss issues relevant to moving beyond the Millennium Development Goals.

 A new indicator?

James Foster opened the discussion by highlighting the problem of high cost and low quality data availability and measurement. The credibility of claims to success or to a need for more funds depends on the quality of data and thus necessitates more cost-effective and reliable ways of surveying. As for measurement, ideally we would have an indicator that captures the multidimensionality of development whilst retaining the simplicity of a sole headline figure that makes GDP so attractive despite its crudeness.

But is this possible? Yes, according to Foster, who proposes a new instrument that focuses on the need for transparency to identify which aspects of poverty reduction are actually achieved and how they affect trends in overall poverty. In a way, this is a micro application of the “growth diagnostics” approach to achieving growth by identifying and targeting the most binding constraint, stressing that even if we have a single goal (growth/development) there are many ways to get there and which path we choose will affect the outcome. The proposed measure will both take into account dimensions of poverty such as health, education, and living standards, and register the change in numbers for each of these dimensions. Such a method will enable governments to explain to their people why overall poverty may be increasing even if some aspects of it that depend on social policy are actually improving.

Why is this important? Foster argues that psychology matters and that to move forward we need to focus on what we can achieve rather than report on the failures. Yet, as someone pointed out on Twitter during the session, it might well be that this new composite indicator “conceals rather than reveals”, and therein lies the danger of governments using this flexibility to their advantage in order to show that they’ve been doing well. Of course, the counterargument is that no flexibility will actually be offered to policy-makers in designing their preferred multi-dimensional index, but rather that the new indicator will enhance transparency and the opportunity to monitor progress across different dimensions.

Overall, the idea of this new indicator was positively received by the audience, which offered constructive suggestions for improving it. For example, Paul Collier floated the idea that focusing on living standards may not be enough and that we should expand our focus. For example, what triggered the uprisings during the Arab Spring was not the demand for food and higher living standards, but rather for justice and representation, and eventually employment prospects. African scholars indirectly agreed in that what matters is not whether goals are met, but the “quality of intervention” – the quality of leadership and the level of legitimacy accompanying it. The ends are important, but by setting goals we should not ignore the means through which they are achieved.

 Some thoughts on education

It became clear in the second part of the session, headed by Paul Glewwe, that measuring progress towards achieving the second and third MDGs on education is much trickier than it first appears. For a start, measurement is tricky because of the question of whether to measure completion rather than enrolment rates, as the two do not necessarily always overlap. This is because in many countries children often have to repeat classes, leading to an inflation of measured enrolment rates when, in reality, completion rates are actually much lower. Indeed they often are, especially in the former French colonies that have stricter rules on passing each grade in order to progress onto the next. Is this a good or a bad thing? And does the intuitive judgement come across in the data? There is clearly a tradeoff, as under such a system students may actually learn more (as the system ensures that they have learnt something by the time they complete primary education), even if enrolment rates are lower.

If what we are interested in is learning, rather than education for the sake of it, then we should be measuring something else, not simply enrolment rates. Glewwe stressed that what we should be aiming for is to improve performance in standardized tests such as PISA and TIMSS, and make them more widely attended by children from developing countries. For his final point, Glewwe stressed that we need new MDGs for education which target lower secondary rather than just primary education. While the latter may push people into poverty, the former will push them out of it.

Removing the stigma from the African continent

Last, but definitely not least, Charles Kenny drew attention to the consequences of setting the bar too high and hence missing the targets. He suggested that Africa is “misjudged and abused” by the current MDGs, and that the new goals – as well as the process of setting them- need to be different.

Different, but in what way? It is crucially important that Africans contribute their own say – so far literature and action in relation to the MDGs has been dominated by scholars in the “global north”. Moreover, Kenny stressed that even though goals are important, we should be very careful to not set goals that are unrealistic and overambitious for a continent that starts so far behind (given the lost decade of the 1990s and incredibly-low median income levels) as this contributes to branding Africa as a basket-case and labelling it as a “failure of the MDGs”. This has a twofold effect: firstly, it discourages trade and investment and secondly it encourages aid-sceptic taxpayers and strengthens their opposition to channelling funds towards African development. Both of these are important as it becomes clear that Africa cannot develop alone and assistance and investment from the international community plays a crucial role.

Beyond 2015…

Einstein once said that if he had an hour to solve a problem and his life depended on the solution, he would spend the first 55 minutes defining the problem. Once he knew the proper question, he could solve the problem in less than five minutes. Setting and achieving the new MDGs is a response to the the life-threatening lack of development faced by many people living in developing countries. This plenary session contributed to shifting focus onto the right questions and the prolific research presented in the conference in general covered vast aspects of development, from trade and aid policies to macroeconomic policies, to health, education, and job opportunities. Whether the second step -the solution- will follow through as efficiently and successfully as predicted in Einstein’s thought experiment remains to be seen. Not one, but many lives depend on it.

 You can watch the entire plenary here.

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A CSAE enumerator at work in Ghana in 2008. But how did she find the job? And what would she say if we asked her to refer someone to fill a similar position?

Referrals matter

 ”Another issue concerns your letters of reference. Unless some of your letters have arrived, your materials probably won’t get read. Therefore, you should tell your advisors when you will be sending out your packets…once you send your packet, their letters will be very important.”

Harvard University Economics Department, Frequently Asked Questions about the Job Market (#3)

Every economist understands the importance of job referrals. They matter for the labour markets we study. They matter for the labour markets we see all around us. And they matter — a lot! — for the labour market for academic economists (but perhaps I repeat myself).

There are many reasons that referrals might be useful for getting jobs. They may provide information about a candidate — information that is likely to be more credible than the information that candidates themselves can provide. What’s more, they may provide useful mechanisms for disciplining workers who shirk — if, for example, a worker’s referrer can be punished for a worker’s own poor performance. In short, job referrals may be a useful way for employers to overcome problems of hidden information and hidden action. But not everyone can refer you for a job. If you want to find a good job reference, you need someone (i) who knows you, and (ii) who is known and respected by your prospective employer. (Also, try not to ask your mother…sage advice, if rarely offered…) In sum – referrals matter, and referrals work through networks.

Referrals and gender in Malawi

All of which brings me to the point of this blog post: we were privileged recently to have Jeremy Magruder present a CSAE Lunchtime Seminar on his recent work with Lori Beaman and Niall Keleher on whether job networks disadvantage women in Malawi. I think this is a very interesting and novel paper, and one that — both in terms of experimental design and empirical results — has the potential to open many new avenues for thinking about job referrals.

I was fortunate to see Jeremy present an earlier paper at the Harvard Economic Development Workshop in November 2011. In that work, Jeremy and Lori ran a laboratory experiment in Kolkata. In the experiment, participants were incentivised to refer outsiders — that is, actual outsiders; their friends and contacts beyond the experimental context — to come and join in the experiment. This made for a really interesting paper — now published in the American Economic Review — that broke important new ground in learning about networks and job referrals in developing economies. I remember wondering, when I saw Jeremy present that earlier work, what would happen if the experiment were repeated with ‘real’ jobs for a ‘real’ employer. In Jeremy and Lori’s earlier work, participants were recruited to complete a cognitive puzzle, as a one-off activity. This is an important and useful context to learn about referrals. But there are many reasons that participants may behave differently when faced with the prospect of referring someone for an indefinite job with a real employer — for example, participants may frame their decisions differently if their task feels more productive, or when the net present value of employment is so much larger.

And that’s why I think Jeremy’s recent work with Lori and Niall is so interesting, and such a useful extension to the earlier results — because this is a field experiment (rather than a lab experiment) in which participants were asked to refer people for a real job. In short, the researchers were interested to help Innovations for Poverty Action find new enumerators in Malawi — and, in doing so, to improve the proportion of women enumerators. The authors recruited a pool of enumerators by posting fliers at “a number of visible places in urban areas” (apparently the standard  IPA-Malawi method of enumerator recruitment). Candidates were assessed on their quality as enumerators using a combination of written tests (assessing maths, English, computer skills and so on), and a practical test (in which candidates interviewed an existing IPA enumerator, who played the role of a respondent). Candidates were then invited to refer someone else for a similar job. Some candidates were invited to refer a women, some were invited to refer a man, and some invited to refer someone of either gender. The researchers then used a cross-cutting design, by which some candidates received a fixed fee for their referral, and others received a performance fee (paid if their referral qualified for an enumerator position). The researchers are interested to test who gets referred, and how good they are.

The results are interesting, and quite stark. As the authors put it, “most men seem to respond to an unrestricted referral situation by identifying men, while most women seem to respond to such a situation by referring unqualified people of either gender”. This harms qualified women, who are systematically disadvantaged in the referrals process. Performance pay doesn’t really change this result — if anything, performance pay encourages men to refer higher-ability men, but makes little difference to the women referred by men, or to women’s referrals in general. Of course, it’s not possible to do justice to the scope or the nuance of the authors’ results in a short blog post like this — but the key message is that job referral networks can act as a mechanism by which women are disadvantaged. I think this is a really important result, both for academic understanding of job referral networks and for effective design of quota and hiring policies.

Possible extensions

One of the strengths of this paper is that it opens several avenues for further refinements and extensions (whether in this work or in ubsequent experiments). Personally, I think there are four areas in which the authors might take things further.

First, the model. When Jeremy presented the model at CSAE, he used simulated data, and showed how shifting contractual form (from fixed rate to performance pay) would induce different referrals. This was essentially an application of the Weak Axiom of Revealed Preference (‘WARP’), and I think it captured the intuition of the model very well. However, this is not the modelling approach used in the paper. In the paper, the authors essentially model a referrer as deciding his or her ‘bliss point’ of friend characteristics. I think this approach has several shortcomings, relative to the WARP approach in Jeremy’s presentation. First, it requires the authors to approximate the viable referral set as a linear decreasing function in friend quality. The authors justify this “to make analysis tractable” — but these tractability problems would not arise if the authors used a WARP approach. Second, the authors need to treat the set of potential referrals as continuous. This is a somewhat awkward assumption, because the authors do not mean to imply that every participant has an infinite number of friends to refer; what’s more, it means that the authors can speak only about changes in a referrer’s “perfect friend” (i.e. ‘bliss point’), and formally can say nothing about how referrers make second-best choices under a finite set of friends. (For the same reason, the current approach leads to some notational difficulties — in that the authors model a referrer as maximising over friends (‘j’), but then find themselves differentiating with respect to friends’ social payments (‘alpha’).) Third, it requires the authors to make a strong distributional assumption (that is, the assumption that actual performance deviates from expected performance by a normally-distributed disturbance — something that cannot be true where, as here, actual performance is bounded). In contrast, the WARP approach is ideal for this kind of problem — where an agent faces a finite set of decisions and a shifting contract price, and where researchers want to draw conclusions non-parametrically.

Second, the sample. As noted, the authors recruited their initial sample by posting fliers — that is, they took the same approach that IPA commonly uses to recruit enumerators. I think this is absolutely the correct approach for this experiment; after all, the authors were trying to help IPA improve its enumerator recruitment, so there is great value in selecting a sample using the same initial recruitment mechanism. But I think this raises important avenues for future work. As Jeremy himself suggested in his CSAE presentation, it would be very interesting to see how these results generalise to female-dominated professions. The authors are rightly cautious about external validity, and I think this presents interesting avenues for further work

Third, participant expectations. As the authors rightly acknowledge, the interpretation of these results depends upon how participants form beliefs about the probability that each of their friends will pass the enumerator admission test. However, in this experiment, the authors did not measure participants’ expectations; expectations therefore need to be treated as a latent variable. There is some tension in taking this approach in this context — after all, the authors stress in the paper that participants were told clearly what were the desirable characteristics of a good enumerator, which suggests that participants may not have had a clear understanding of this (and, therefore, may have struggled to form reasonable expectations of their friends’ ability to pass the test). This is reminiscent of Charles Manki’s central complaint in his 1993 paper on ‘adolescent econometricians’:

“…it might be anticipated that economists would make substantial efforts to learn how youth form their expectations…Instead, the norm has been to make assumptions about expectations formation.”

Adeline Delavande, Xavier Gine and David McKenzie have two interesting recent papers (here and here) about methods for measuring subjective expectations in developing economies; it may be that these kinds of methods can add much to future experimental work on referrals.

Finally, what determines the “social payment”? The “social payment” refers to the utility gain that a participant receives from referring a friend for a job — and could be either monetary or non-monetary (for example, the performance of a favour in future). The authors quite rightly emphasise the centrality of this concept — but it is very difficult to know how the social payment is determined, or how it might change across treatments. For me, there are two important questions here. First, does the social payment accrue if someone is referred for a job but fails the recruitment test? The authors model the payment as accruing whether or not a friend passes (“thanks for the opportunity”), but we might imagine many reasons that this is paid only if the friend passes the test (“you wasted my time by inviting me to fail??”). Second — and perhaps more fundamental — why do we think that the social payment is invariant to the form of referral contract? I may feel very differently towards a friend who refers me for a job with a fixed referral fee (“wow — how kind of you to choose me when you could have chosen anyone!”) rather than when the friend refers me under a performance referral rate (“oh, so I’m the guy who will earn you money by passing this test for you?”). The latter concern is potentially a big problem for identification; if the social payment shifts in this way, then the distribution of friend attributes depends on the experimental treatment — and the treatment therefore cannot be used to learn about that distribution. I think it would be useful for the authors to consider this further, both in their theoretical model (for example, by microfounding the social payment), and in their empirical work (for example, by considering heterogeneity across different observable characteristics, where those characteristics might proxy for different kinds of social payment).

Last words

In sum, this is a really exciting paper — a very useful extension of Jeremy and Lori’s earlier work in India, and one that should prompt interesting further experimental work, both in Africa and elsewhere. I’ll look forward to following this paper and the future work that I’m sure it will provoke.

Now we just need to keep our fingers crossed that we can persuade Jeremy (and Lori, and Niall) to come back and present at CSAE again sometime soon…!

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This Monday at the 2013 CSAE conference, Edward Miguel, introduced by James Fenske, paid tribute to Paul Collier for inspiring and informing a lot of his work on Civil Wars in Africa. Since the early 1990’s there has been much emphasis placed on the role of political conflict and violence in constraining Africa’s development. Over 70% of African countries have experienced civil conflict since 1970 and these have had devastating consequences on the human and economic development of the region.

Miguel’s presentation  (based on a new, unpublished paper with Sol Hsiang and Marshall Burke) and current research agenda seeks to build on the ethno-political, cultural and economic factors that have been analysed in the literature and analyse specifically the potential future impact of climate change on conflicts in Africa. His major finding is that there is widespread agreement in the literature and in the data that high temperatures are associated with more violence. In answering the question of whether climate-induced violence might derail Africa’s incipient economic revival, Miguel left a sobering picture and a call for action.

What is the effect of climate on violence?

Their first goal in this new research agenda was to collate and compare existing work being done in this area. They have conducted an extensive literature review and reproduced the results where possible in a common econometric framework (panel data with country and time fixed effects) to allow for comparability. The paper looks at 50 studies, using 37 data sets. The studies come from a range of disciplines using different conceptual frameworks. Broadly speaking they can be separated into three categories:

1. Historical climatology and paleoclimatology (10 studies)
2. Experimental Psychological studies (2 studies)
3. Observational studies using panel data (38 studies)

The historical research uses innovative datasets including tree rings and ocean deposits to investigate the relationship between climate and the collapse of empires. Evidence was presented for Maya, Angkor Wat, Chinese dynasties, and the Akkadian empire. Many of these results confirm the hypothesis but – importantly – do not produce a universal study of societies, and therefore may be subject to looking for “keys under the lamppost”.

Little airtime was given to the experimental psychological studies, but Miguel highlighted that this is a relatively unexplored channel for the impact of climate change. There were a few gasps when the audience was told about Vrij et al.’s (1994) study where Dutch police, in a training exercise, were found to be more likely to shoot at a simulated intruder when randomly placed in a high temperature room (27°C / 80°F) than at lower temperature (21°C / 70°F). The only chuckles of the day were heard when we were told of the research design of Kenrick et al.’s  (1986) study; in which investigators sat in their stationary car at a green light, at the exit to a parking lot, measuring the time taken for people to hoot as well as the intensity.

Most of the weight of Miguel’s argument rests in the third set of studies. These studies are used to quantify the effect of an increase in temperature on violence in Africa. Finding widespread agreement across the studies (21/21), Miguel is confident that their common econometric specification confirms a positive relationship between higher temperatures and violence. The pattern emerges at different scales; ranging from the village level, to the regional, to the country level and even on a global scale. These effects could be “large”: the marginal effect shown in their study indicates that a 1 standard deviation change in temperature is associated with a +11% increase in intergroup conflict. Most of Sub-Saharan Africa is projected to experience average warming of at least 3 s.d. (2°C) by 2050, implying the risk of violent conflict will rise considerably (>30%). Beyond average changes, precipitation variability is likely to increase, potentially exacerbating effects.

What are the channels and what to do about them?

Armed with these findings, Miguel approaches the task of understanding the channels for the influence of climate change. The economic channel seems well established in the literature. Dell et al. (2012) shows that increased temperature reduces economic growth, Lobell et al (2008) demonstrate the effect on agricultural output, and both Graff-Zivin and Neidell (2013) and Hsiang (2010) give evidence on labour productivity. In both the witch killing data and Harari and La Ferrara (2012), lagged growing season weather shocks have a much larger effect than non-growing season weather, suggesting that agricultural output is a key mechanism. However, even with declining reliance on agriculture, African economic growth rates have not become less sensitive to high temperature over time: -1.5% growth per 1°C increase in temperature.

With global mitigation efforts currently stalled politically, an adaptation agenda for Africa is desperately needed. Adaptation otherwise is likely to be partial. Even in the USA, the sensitivity of agricultural output and crime to temperature is nearly unchanged over the past few decades (Burke and Emerick 2012). The shape of this strategy remains unclear but much emphasis during the Q+A was placed on institutions and their channel on the adaptation and management of climate shocks. This seems to be relatively unexplored by Edward Miguel and his colleagues at the moment but he seemed sure that it is central to the story.

Edward Miguel and his co-authors have brought together the literature of the impact of climate change on violence in a robust and clear fashion that deserves attention both in academic circles and in the policy debate. Showing a large marginal effect of climate shocks, this literature prompts a rethink of the way we conceive of the costs of climate change. With much room for further discussion and research, it is important for researchers to remain open to other disciplines and frameworks that are being explored on this issue.

You can watch the entire keynote speech here.

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This week I’m in Oxford, for the annual conference on “Economic Development in Africa” at the Centre for the Study of African Economies (CSAE) .  The CSAE conference is unique among top-tier development econ conferences in that it brings together a huge number of scholars based in African universities and research institutes  — as well as people like me, non-Africans working on the economics of Africa.

Looking at the conference program, I thought this might be a good testing ground for this hypothesis about African and Westerners’ divergent priorities.  Do the research topics of African and non-African scholars working on economic development in Africa align?

I decided to take a closer look at the set of 264 papers presented at the conference.  Richard Payne (the CSAE’s IT director, who crafted the conference program and website) kindly shared the spreadsheet underlying the program, with a field indicating the continent-or-origin for the submitting author, and the thematic area they submitted their paper to.  Here’s what the data show:

It’s a bit hard to draw firm conclusions here, given the large number of topic categories.  But if you squint a little (and group topics into broad conceptual categories), what strikes me is the following: African scholars are disproportionately interested in labour (i.e., jobs), firms (possibly jobs again), and monetary policy.  Non-African scholars are disproportionately interested in political economy, conflict, natural resources, and (an outlier) migration.  Roughly speaking, there’s a division between jobs-focused papers by African researchers and papers by non-Africans focused on institutions.

Also, it’s hard to pass up mentioning that “aid” is a much bigger priority for non-African than African researchers.

Between sessions this morning, I mentioned this pattern to another conference attendee — Bob Rijkers from the World Bank — who asked, sensibly, is this just driven by the CSAE’s own acceptance and rejection decisions?

So I went back to Richard and asked for the full (anonymized) set of paper submissions — over a thousand papers in total.  Sure enough, the pattern looks quite different:

There are fewer large differences between African and non-African priorities in the full set of submissions.  Labour is still a much higher priority for African researchers, but so are poverty and agriculture.  On the other end, rather than institutions, it seems there are a lot of non-African researchers working on Africa who focus disproportionately on intra-household issues, risk, and social networks.  Interestingly, conflict remains a much more popular topic for non-African than African researchers.

I’m curious what others make of these patterns?  Scanning the categories in the graph, am I right to see systematic patterns, or does this strike people as random noise?  If the patterns are systematic, I’m also curious what the dynamic relationship looks like: comparing across years, are African papers converging to the non-African topics on the Western academic frontier, or are Western researchers listening to their African colleagues who may be closer to the policy dialogue in their respective countries?  Maybe that’s another blog post.

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“the gentlest hand … modern economy, therefore, is the most effectual bridle ever was invented against the folly of despotism.”  — Sir James Steuart (1767)

Hirschmann, in a classic of modern political economy (Exit, Voice and Loyalty, 1977),  questions the effectiveness of this ‘gentlest hand’, and the traditional notion that despots will be reigned in by economic competition alone. What economists have been slow to embrace, he suggests, is the option of voice: being able to complain—and be heard—when things are broken. Historically, when considering government performance, it has not necessarily been easy to exercise voice, both due to a lack of anyone who will listen, and due to an inability to access and use the information to develop a voice.

Recent noisy uprisings in many countries and regions suggest that voice is a relevant consideration in economic and social change, and that voice is fostered by a range of modern technologies when these are made available. In this post I will look at the Open Data movement, discuss how this increases a people’s voice, and suggest why and how we must embrace this movement.

Open Data is Available

Like open source software, the idea behind Open Data is that this is information which belongs to all people, and which all people should be able to access, analyse, and use as they like. Governments are increasingly making data collected as part of their service delivery available in large online repositories where users can simply search for and download nationally relevant data. Although these initiatives started with governments in developed countries, this is now available in lower-income countries including India, Kenya, Chile, Uruguay and Morocco, among others. There has also been a push to take this Open Data and use it in ways which benefit social development. Initiatives which build on Open Data such as Code4Kenya and CodeandoXChile are piggybacking on the wave of newly available data to build user-friendly government budget interfaces, open school performance indicators, and provide health access information to citizens. These initiatives came about based on the availability of Open Data but are run and maintained principally by a public who responds to no governmental requirements or restrictions, and who speaks nearly entirely to other members of society.

Open Data has a role in defining how people and governments interact

User-friendly Open Data interfaces—such as those which can be linked with smart phones and publicly accessible computer terminals—can certainly provide citizens with a simplified way to search through complicated databases of public services availabilities and requirements. However, on top of simplifying search for public services, Open Data can act as an important check on State performance. Indicators such as public servant salaries, effectiveness of education providers, ability of law enforcement, and directions on how and where to vote have all been created using large Open Data bases which can be followed in real time by all citizens.

Open Data needs to be used 

The challenge in Open Data then is in generating interfaces to make these large databases accessible. This is a two-part challenge: one part is simply facilitating the visualisation of data and the second part is in opening up access by increasing data-literacy. The first of these challenges, opening large databases and making them understandable in a simple way, is well under way. The World Bank hosts an enormous range of data (8,079 indicators to be exact) which can now be directly (and freely) accessed through programs such as R and Stata.  Front-ends for these programs such as the worldstat Stata module I have made available online are also increasingly common (see figure 1).

Figure 1: worldstat Africa, stat(MORT) cname

The second part of the challenge, making citizens more data-literate, is perhaps the principal bottleneck in the Open Data movement. While it is certainly a good thing that a larger array of data is available to be communicated with the public, the limits of what is actually done with this freed data are set only by the degree that people are unsure of how to access and what to do with this. Where a larger group of citizens are actively accessing, exploring and communicating the results housed in Open Data repositories, society as a whole will be more engaged with the decisions governments make, and more importantly, how these map into social results. This suggests that digital education may be a worthwhile investment in school curricula – particularly for young girls and boys who truly are digital natives. The availability of massive open online courses, or MOOCs, is a start (such as free access to Harvard’s core computer science class via edX), but for countries to create educated citizens who can contribute to the democratic process (and as an added bonus to a dynamic labour market) teaching coding early would seem to be a worthwhile investment given recent trends in digital development and what we know about first mover advantage.

Open Data needs to be submitted

A burgeoning body of Open Data now exists. We can access information about what our governments spend, where they spend, and what the results of this investment look like. However, there is still much that can be done in this area. There is no need for Open Data to be restricted to national government databases. Economists and others who frequently collect and work with data can also submit their data via open repositories such as Google’s Public Data Explorer. What’s more, the marginal effort in uploading data to these interfaces where it can be used by all is minimal once collection has taken place. We should, wherever practical, begin to consider this as the typical way to communicate data, and barring serious concerns regarding privacy and sensitive information, should encourage national governments to follow the trend of opening up (de-identified) national datasets.

Hirschmann’s words then, as much as any other time, surely still ring true:

“Yet, in this age of protest, it has become quite apparent the dissatisfied … members of an organisation … can ‘kick up a fuss’ and thereby force improved quality or service upon delinquent management.”

We are, as ever, in an age of protest, and the voice society develops will grow louder and harder to refute when it is backed up with relevant data. This data—from independent international organisations and from national governments—is moving to become completely open. The only limit placed on its use is that on human ingenuity, and as long as citizens know where and how to look, this constraint will be insignificant.

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In the evaluation of social programs, the first order concern is their effect on beneficiaries. However, there is a growing awareness about “spillovers” or “peer effects”, which could affect non-beneficiaries. In Mexican villages where PROGRESA cash transfers were implemented, non-eligible households were more likely to send their children to school. Thanks to transfers and loans from eligible households, their consumption also went up.

This post makes a related, but different point: social programs, especially programs other than cash transfers, may also change the market equilibrium, which affects beneficiaries and non-beneficiaries alike. Workfare programs for example, by providing public employment to beneficiaries, may increase private sector wages. Another example is in kind transfers, which deliver basic commodities at subsidized prices and may decrease market prices.

In 2005, the Indian Parliament passed the National Rural Employment Guarantee Act (NREGA), which entitled each rural household to 100 days of employment on public works per year. There is no eligibility condition, and workers are paid according to each state’s minimum wage legislation. The program was introduced gradually across Indian districts from 2006 to 2009 and rapidly reached a massive scale; in 2012, official sources reported 51 million beneficiary households.

In a new CSAE working paper, we compare districts where NREGA was introduced first to districts where it came into force later to estimate the impact of the program on rural employment and wages. We show that the introduction of the program is correlated with an increase in public employment and an equivalent fall in non-public employment. The daily wage for casual work increases by 5.5%. These effects are concentrated during the first half of the year when most NREGA employment is provided. Independent studies yield similar findings.

We use these estimates to compute the welfare impact of NREGA for households depending on their monthly per capita consumption. We first consider gains from participation in the program and find that the poorest quintiles are more likely to benefit from public employment provision. We also consider the impact of a rise in private sector wages, which may affect all households, and show that it generates substantial welfare gains to the poor (30 to 60% of total welfare gains) and implies a welfare loss for the rich, who are net buyers of labor.

The first conclusion of this study is that equilibrium effects are important, and should be taken into account to evaluate the impact of social programs on beneficiaries and non-beneficiaries. The second conclusion is that through changes in market prices social programs make some people lose: large landholders are unlikely to participate to NREGA but will see their labor costs rise. Governments may want to use these effects to trigger redistribution, but they may also provoke political resistance.

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I received news this weekend that the keynote speech for the upcoming CSAE conference will be on “Conflict, climate and economic development in Africa.” The speaker will be Berkley’s Ted Miguel. If you didn’t have a reason to attend the conference before, you do now!

Spurred in no small part by the pioneering work of Oxford’s own Paul Collier and Anke Hoeffler, the first wave of research into the economics of conflict established that economic variables are good predictors of the incidence of conflict. Economists, then, might have something to say about the causes of war and other types of violence. This, of course, remains an active literature: Djankov and Reynal-Querol, for example, have recently argued that the correlation between poverty and civil war is not causal, but instead reflects the deep underlying causes of both poverty and conflict. Spolaore and Wacziarg have come to the striking conclusion that more genetically similar countries go to war more often, even controlling for  physical distance.

In part because it is easier to make causal claims with panel data, a very active subset of this literature has focused on the role of economic shocks. I have been struck by how much recent theoretical (e.g. Besley and Persson) and empirical (e.g. Dube and Vargas) work has reinforced Collier and Hoeffler’s cost-benefit approach.

Evidence has been published both for and against drought as a cause of civil war in Africa. Similarly, there is controversy whether terms-of-trade shocks have or have not spurred conflict.  As an economic historian, I have to point out that these are not new issues. Ying Bai and James Kai-sing Kung have linked Sino-Nomadic conflict over the very long run to climate shocks. Namrata Kala and I have argued that beneficial temperature shocks increased slave exports during the time of the slave trade.

So: I find this a very interesting literature! Since I am late to the party, I have to make some guesses about where the field is headed if I want to contribute something. As best as I can tell, this field is headed in two directions:

1. Why do shocks precipitate conflict in some places and not others?

The connection between economic shocks and conflict appears to depend on many things. Notably, Kung and Ma have found that the link between droughts and peasant rebellions in historical China was weakened by the intensity of Confucianism. Similarly, Ruixue Jia has argued that the spread of drought-resistant sweet potatoes helped break the link between drought and peasant revolts. Eric Chaney has shown that the link between fluctuations in the Nile flood and political changes in pre-modern Islamic Egypt operated through a very specific set of local institutions. Still, there are many variables that may interfere in the link between economic shocks and conflict.

2. What are the long run effects?

We have learned a lot in the last decade about how living through war affects child soldiers, soccer players, and children who grow up during war, among others. Recent work has shown that war exposure is bad for child health, warps portfolio decisions, and changes how individuals behave, though it may increase political participation. Achyuta Adhvaryu and I will debut a paper in this sub-field at the CSAE conference next month.

At the macro-level, Melissa Dell tells an interesting story of path dependence about the Mexican revolution. Areas experiencing drought on the eve of the revolution were more likely to participate in the insurgency. This translated into greater land reform in these municipalities. Due to the weaknesses of the ejido system, these districts are poorer and less industrial today.

Other studies of the macro-economic effects of conflict, however, have yielded surprising conclusions. Though the temporary disruptions caused by war can be massive, economies prove surprisingly resilient. Hiroshima and Nagasaki returned to their long-run trends within a generation. The intensity with which different parts of Vietnam were bombed during the war are does not predict differences in the extent of poverty. Economies, then, have been quite resilient, as would be predicted by many standard growth models. But, if we believe “new” growth theories, in which human capital matters, this becomes surprising. Here, the micro-economic and macro-economic evidence appears to be out-of-sync.

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I am teaching a short module in the M.Sc. In Economics for Development this term on “deep roots” of economic development. Enrico Spolaore and Romain Wacziarg provide an excellent summary of this literature here. One half of one of one lecture will be on “ethnicity,” which raises the question – is ethnicity is really something “deep”?

This is important, because there several recent papers suggest that the historical legacies of institutions particular to specific ethnic groups – so-called “ethnic institutions” – matter for real outcomes. A forthcoming paper by Stelios Michalopoulos and Elias Papaioannou and an older paper by Nicola Gennaioli and Ilia Rainer find that parts of Africa with more centralized pre-colonial states have a greater density of night-time lights and better provision of public goods in the present. Elise Huillery, similarly, has linked pre-colonial states to modern outcomes through the degree of hostility to colonial rule. Other ethnic institutions also matter: the Tswana kgotlas that constrained elites before colonial rule may still check their power today. In some cases, these institutions have been transformed under colonial rule, (e.g. chieftaincy in Sierra Leone, land tenure in Ghana), but still matter for present-day outcomes such as investment and public goods. In my own work, I have argued that pre-colonial patterns of land rights predict present-day patterns of land acquisition in Ghana, and that the distribution of polygamy over space in Africa is in part a legacy of pre-colonial ethnic institutions.

So, is ethnicity deeply rooted? A small number of studies have attempted to show that some of the causes of ethnic diversity are very old. Stelios Michalopoulos has found a remarkably robust correlation between geographic heterogeneity and ethnic diversity. Though this is consistent with several theories, he believes it is driven ultimately by specialization; ethnic groups develop subsistence practices adapted to their environments, and these activities come to define them. The diversity in geographic endowments within ethnic homelands also predicts inequality across ethnic groups today. Pelle Ahlerup and Ola Olsson take a different view. Over time, they argue that peripheral members of one group split off as the centre finds providing public goods to be too costly. Though theirs is a primarily theoretical paper, they show that countries that have been inhabited longer by humans are more diverse today. Javier Birchenall argues instead that pathogen stress encouraged isolation in pre-industrial societies, leading to greater diversity over time.  Klaus Demset, Ignacio Ortuño-Ortín and Romain Wacziarg show it is the oldest linguistic cleavages that best predict the onset of conflict in the recent past.

But, strikingly, there is a substantial amount of research showing that ethnicity is malleable. Parts of Africa that were hit harder by the slave trade are more ethnically diverse today, a correlation that holds even when distance from regions of slave demand are used to control for possible reverse-causation. Mahmood Mamdani has famously argued that the identities of “Hutu” and “Tutsi” are ultimately political entities shaped by colonialism. Even where ethnic identities are clear, they are exploited selectively. Africans identify more with their ethnic group relative to their country when elections draw near. When allowed to act anonymously in a lab, Ugandans treat their co-ethnics no better than members of other ethnic groups. Ethnic groups that are adversaries when both are large enough to contest power in one country become allies when they are only minority groups in another country.

Together, these results present something of a puzzle. If “ethnic institutions” matter, we should know where ethnicity comes from, and why it changes.

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