Property rights in diverse places: lessons from Dar es Salaam

Posted on September 30, 2013 by
ethnic


A diverse slum in Dar es Salaam: each colour represents a household from a different tribe

 

Last year, while wandering around a slum in Dar es Salaam with a colleague,  I happened upon a local landowner who was visibly displeased with how his plot had been demarcated in a recent large-scale land survey. A few years prior, after returning from a ten day trip, he discovered that someone had purchased the patch of land adjacent to his house which he had been using for growing vegetables. In its place: a new house, already built during his absence. What was particularly astonishing about the dispute was the fact that the man’s long-standing neighbours, with whom he admittedly had a poor relationship, had supported the sale while he was away.

We often think of property rights as being objectively verifiable – if you own something there must be a receipt or a government record somewhere proving your ownership. If you decided to sell your house tomorrow, neither the real estate agent nor any potential buyers are going to rely on your neighbour’s perceptions of your ownership as a basis for the sale: they are going to want to see a government-approved title deed. It is with substantial faith in this formal system of property rights that I could go on my own ten day holiday earlier this month without fear that someone would invade my back garden in the meantime (even if my neighbours did go along with it).

Until relatively recently, most people living in the unplanned settlements of Dar didn’t have access to this kind of formal tenure, so most property rights were characterized by informal forms of tenure. Informal tenure is a bit of a catch-all term, ranging from customary forms of tenure, which rely on established practices and, well, customs to determine ownership, to quasi-legal forms, where households write up their own transfer agreements and have them certified by a local court. Ultimately, much of informal tenure in these settings is determined by one’s relationship with the community: you own the land because the people around you agree that you own the land.

One particular reason why neighbours might be more likely to support each other as well as cooperate and coordinate in enforcing each other’s ownership rights is if they come from the same ethnic background. There’s a large literature documenting how co-ethnics are more likely to trust one another, have a distinct advantage in cooperation, and are often more adept at producing public goods . While some research has suggested that Tanzania  is less susceptible to these co-ethnic biases, there is still good evidence that ethnicity and tribal norms matter in the decisions that people make. For example, respondents in the 2001 and 2005 waves of the Afrobarometer survey were significantly more likely to say they trusted member of their tribe than members of other tribes.

So what happens when you have an extremely ethnically-diverse setting like Dar es Salaam, where informal tenure is the norm, and suddenly formal tenure becomes an option? In 2005, many households living in the city’s slums were suddenly given the option to buy a limited form of land tenure, a 2-5 year renewable lease on their land known as a residential license. Roughly 40% of landowners in the slums did so, leaving a sizeable share of people who did not opt for what was a fairly cheap (approximately $6, not counting future land taxes) way of formalizing their land.

While it is easy to see why households who have little faith in their own informal tenure security might be quick to buy a land title, what about households who are surrounded by those of the same ethno-linguistic background, who might otherwise feel fairly secure? If a given household’s sense of informal tenure, bolstered by the presence of co-ethnics living nearby, is strong enough, will they be less likely to buy a formal land title offered by the government?

I investigate precisely this question in a new CSAE working paper. Using a unique census of two large adjacent slums in Dar es Salaam, I investigated whether households with a greater percentage of coethnic neighbours (those from the same ethnolinguistic background) were less likely to buy a residential license from the government.

Simple correlations suggest that this is the case: households with a larger percentage of coethnics living nearby were significantly less likely to have bought a short-term land title. Yet it isn’t entirely clear that this is a causal relationship: for example, the kind of people who choose to live near those of the same ethnic background might have different beliefs over the effectiveness of formal land tenure, or reside on lower-quality land for which the returns to titling are quite low.

While controlling for a host of household, plot, ethnic and geographic characteristics might reduce these concerns somewhat (and this is all done in the paper), the main issue here is still sorting: certain types of households may choose to live near coethnics. To get around this, I rely on the fact that households who move to a slum have very little control over who moves in after them, so while households may choose where they want to live, they can’t easily choose who moves in next. Thus, relying exclusively on changes in the ethnic composition of nearby households which occur after a household moved into the slum should allay concerns that the main result is being driven by certain types of households.

The main results are robust to both this new approach and several different definitions of `coethnic’. In the end, if appears that households living near others of the same ethnic background have observably lower demand for land titles. These effects are, in theory, quite large – households who are completely surrounded by coethnics should be nearly 60% less likely to buy a land title than those who are completely isolated. However, in practice, slums like those in Dar es Salaam are so diverse (see the image at the top of this blog post) that these extremes are rarely realized in practice.

This might actually one of the chief benefits of urbanisation: if Dar es Salaam were more ethnically segregated and dominated by tribal enclaves, then these results suggest that the residential license roll-out would have even been less successful than it was. The absolutely astounding level of (integrated) ethnic diversity seen in the city might be what gives the Tanzanian government a partial advantage in providing property rights, by isolating households from others from the same tribe and forcing them to rely on the state to enforce tenure.

What is the main takeaway from this paper? Not only does ethnicity seem to still be an important factor in the decisions of ordinary Tanzanians, but it appears strong enough to influence the adoption of formal property rights, seen by many as one of the prerequisites to building a modern economy. It also reinforces the importance of informal notions of tenure in these settings, which might compete with, rather than complement, attempts to introduce formal tenure. Finally, while most work on the effect of ethnic heterogeneity on economic outcomes rely on country or regional-level analysis, more could be done to examine how ethnicity affects decisions at the household level.

You can read more here, where I also cover the potential mechanisms driving the result, and go into a bit more detail on what the implications are.

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What is the impact of natural resource booms on income inequality? Some lessons from Australia

Posted on August 13, 2013 by

Commodity price shocks can have powerful but unequal effects on labour, capital and land. A large literature, often referred to as the ‘Dutch Disease’ literature, documents the effects of these commodity booms on factors of production. An increase in global demand for a commodity and its subsequent price will trigger a sharp rise in a country’s exports of that commodity. Typically, this causes an appreciation in the exporter’s real exchange rate, which in turn harms the competitiveness of other sectors which export, such as agriculture and manufacturing. Thus, resource booms caused by a rise in global demand might lead to a decline in employment in these sectors.

Even though the channels through which these commodity booms affect employment in resource-rich countries are well understood, surprisingly little is known about how the impact the distribution of income within these countries. Theoretically, the distributional impact of a commodity price shock should be modest if resources are mobile, as both people and capital can move across sectors to take advantage of increased prices. However, if there are constraints on mobility between sectors, then price shocks might have significant distributional consequences.

Furthermore, those who write about political economy theory often argue that natural resources could have a significant impact on income distribution via institutions (see Stanley Engerman and Kenneth Sokoloff’s book or work by  Acemoglu and Robinson and Acemoglu et al.). They argue that natural resources influence the initial distribution of both wealth and income, and thus of economic power. This distribution of economic power determines, in turn, the shape of future institutions and policies. Therefore income and wealth inequality might persist over the very long run. However, the nature and magnitude of the impact of natural resources on income and wealth distribution might depend on the type of the natural resources, who owns them, and other factors determined at the start.

This ambiguity over what the impact of natural resource booms on income inequality makes this an ideal question to study empirically. In a recent CSAE working paper, I and Jeffrey Williamson address this question by studying the association between commodity prices and income distribution in Australia for a century.

Figure 1: Australian terms of trade from 1890 to 2007Figure 1

The key facts that we discover are as follows: first, Australia has undergone three major commodity price episodes over the past century. These can be seen in Figure 1, which shows how Australia’s terms of trade (the relative price of its exports over imports) and overall deflated price of exports and imports have changed over time. The first half of the 1920s experienced a sharp increase in Australian commodity prices. The second major price shock occurred during the Korean War episode from the late 1940s to the early-mid 1950s and the third has been occurring since 2003 (a detailed historical account of these shocks can be found here). First,  in terms of magnitude, the Korean War boom was the most dramatic. Second, the size and frequency of commodity price shocks experienced by Australia over the periods 1865-1940 and 1960-2007 are large relative to many other commodity exporting countries: Figures 2 and 3 show how the fluctuations in Australia’s commodity prices during these periods compared to other countries.

aus_f2 aus_f3

Finally, we find that these commodity price shocks increased the share of income held by the top 1, 0.05 and 0.01% of Australians considerably both in the long and short run. This result held even after we accounted for a host of other factors such as GDP growth, wartime conditions, trade union density, direct tax shares in GDP, and enterprise wage bargaining. Out of these commodity shocks, both wool and mining prices, rather than other agricultural commodities, have been the main drivers of Australian inequality in the short run. However, in the long run, a sustained increase in the price of renewable resources, such as wool, reduced inequality whereas sustained increases in non-renewable resources, such as minerals, increased inequality.

What are the key lessons from this exercise? Our analysis shows that resource booms tend to exacerbate inequality. The recent literature on the economic consequences of inequality argues that high and persistent inequality not only harms growth but also adversely affects institutions (some examples here, here,  here and here ). Therefore, it is important for resource-rich developing countries to use policy to tackle inequality that emerges as a consequence of commodity export booms.

Yet, it is not clear that these sorts of policies are as politically feasible as they might be in more mature economies like Australia. Thus, we hope that future research will utilise better data on price shocks and inequality from developing countries to see whether or not the impacts are larger than what we find in Australia, as the political economy literature would predict.

Nevertheless, our analysis here seems timely and relevant, not just for Australia, but for all resource-rich developing countries as the price volatility experienced by the former following the late 19th century was even greater than that for the average exporting low income country. Thus, studying the distributional impact of commodity price shocks in Australia could yield important lessons for resource-dependent countries in the developing world.

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Fungibility and off-budget aid

Posted on July 23, 2013 by

fungible2

If you’ve been following development blogs for a few years, you probably remember The Great Fungibility Debate of 2010 that was sparked by a paper in the Lancet written by researchers at the Institute for Health Metrics and Evaluation. To briefly recap, the Lancet paper finds that, in the long run, foreign health aid is fully fungible. That is, in the long run, for every dollar of health aid a country receives, it spends about 1 dollar less of its own resources on health. This result attracted much attention in the blogosphere.

Now that the dust has settled, I want to use this space to draw attention to one issue that has been largely absent from the debate and that I believe has a big effect on how we should evaluate the fungibility of aid. For me, this issue goes back to a line in a 2000 paper by McGillivray and Morrissey  who argue that, because a large portion of the aid that is reported by donors is not reflected in the public sector accounts of recipients, such aid measures “…are inappropriate for analyzing fungibility”. What I tried to do in my own work is draw out the consequences of such off-budget aid for the assessment of fungibility in more detail, and suggest some possible ways of accounting for off-budget aid when testing for the fungibility of aid.

Off-budget aid affects how we should test for the fungibility of aid

Roughly speaking, to test for the fungibility of, say, health aid using cross-country donor-reported aid data you would be interested in the coefficient of health aid in a regression where public health expenditure is the dependent variable (let’s call this coefficient beta). If this coefficient is close to 1 there is no fungibility, as every dollar of health aid leads to a 1 dollar increase in public health expenditure. The closer the estimated coefficient gets to 0, the more fungible health aid is.

This standard assessment of the degree of fungibility is, however, no longer valid in the presence of off-budget aid. One way to see this is with a simple example. Suppose a donor builds a hospital and does so in a way that bypasses the recipient government (i.e., using off-budget aid). If the recipient government does not do anything, we end up with one more hospital than in the absence of health aid, so there is no fungibility. But since the money used to build the hospital is off budget, it does not show up in the recipient government’s health expenditure. As a result, we would estimate a beta of 0 rather than 1, even though health aid is not fungible.

More technically, our beta coefficient is a weighted average of the coefficients of on- and off-budget health aid. While 1 and 0 are the appropriate benchmarks for testing whether on-budget aid is fungible or not, for off-budget aid no fungibility implies a coefficient of 0, whereas full fungibility implies a coefficient of -1. As a result, the presence of off-budget aid drags down our estimated beta coefficient, making it look as if aid is fungible if we follow the standard assessment described above (which is what has been done in the literature thus far).

Data I pieced together from various papers and reports for a number of countries suggest that off-budget aid is substantial, often making up more than half of total aid received, so not dealing with off-budget aid in a correct manner potentially matters a lot when you’re trying to find out whether aid is fungible.

How can we deal with off-budget aid when assessing the fungibility of aid?

One way to deal with the presence of off-budget aid is to try and separate on- and off-budget aid and compare the coefficient of each with the appropriate benchmarks (1 and 0 for on-budget aid, 0 and -1 for off-budget aid). In a paper recently published in the World Bank Economic Review, I construct data that split up education and health aid into different modalities, including some modalities that are more on budget (sector programme aid)  and some that are more off budget (technical cooperation). The key finding is that technical assistance (the proxy for off-budget aid) is not very fungible in either sector (the estimated coefficient is close to zero or, at most, slightly negative). This matters because technical assistance makes up a large share of total education and health aid, so it has a big influence on the degree of fungibility of total education and health aid. The paper further shows that implicitly assuming that all health and education aid is on budget would lead one to falsely conclude that education and health aid are mostly fungible.

A second approach to deal with the presence of off-budget aid uses simple algebraic manipulations to transform our coefficient beta into a coefficient that we can use to assess the fungibility of health aid by comparing it to the standard benchmarks. This transformation depends on the relative variance of off- versus on-budget aid (call it delta) and the correlation between on- and off-budget aid (rho). In essence, this allows us to assess the degree of fungibility under varying assumptions about the role of off-budget aid (i.e. different values of delta and rho). In a recent CSAE working paper, a revised version of which is forthcoming in the Journal of Development Studies, I use data from the Lancet article mentioned at the start of this blog to do exactly this. I find that the full fungibility conclusion arrived at in the Lancet paper depends heavily on the implicit assumption that all health aid is on budget. Taking into account off-budget aid typically reveals a lower degree of fungibility and, under plausible assumptions about the role of off-budget aid, often only modest or zero fungibility is found, even in the long run.

The two approaches can also be combined, as I show in the WBER paper, to check, for instance, what happens when the assumption that technical assistance is completely off budget is relaxed to some extent.

Both these papers suggest that taking into account off-budget aid has a massive impact on our assessment of the degree of fungibility. This implies that papers in this literature that have relied on donor-reported aid measures (in particular, data provided by the OECD DAC) may seriously overestimate the actual degree of fungibility.

In terms of going forward, taking into account off-budget aid presents both challenges and opportunities for research. Challenges because it makes the assessment of the fungibility of aid more complicated. Opportunities because, as better data become available, we might be better able to distinguish on- and off-budget components of aid, which would enable us to test for the fungibility of aid in a more appropriate manner.

I’ve only been able to scratch the surface in this blog post so, if you’re interested, by all means have a look at these two papers on my website and let me know what you think.

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Africa in two recessions

Posted on July 12, 2013 by

Our spring term ended a few weeks ago. I teach an undergraduate course that focuses on the economic history of the twentieth century. Unsurprisingly, the Great Depression is a major focus. The current mainstream view is that monetary shocks were very important in causing the initial contraction in the United States, and that the Gold Standard (the system of fixed exchange rates) was the principal mechanism that transmitted these shocks around the world, turning an otherwise normal recession into a prolonged depression. Countries did not recover until they left gold and devalued, which reduced real wages, increased profitability, raised competitiveness, and lowered interest rates.

But what of Africa?

Africa in the Great Depression

The monetary story also seems to hold for Latin America. For Africa, however, the pattern was different. A year ago, one of the MPhil students in economic and social history found no relationship between export recovery and when the colonial power abandoned gold in a sample of African countries.

Indeed, Susan Martin has argued that the entire period between the wars was a long depression for Africa. For commodity producers, export prices had already declined before 1929. Influenced by images of the American dust bowl, colonial administrators intensified coercive efforts at soil conservation. The Second World War was not a reprieve either: for many Africans, the increased wartime demand for commodities was offset by government controls, rising import prices, conscription, and forced labour. Some of my own work has looked at the wartime transition in the rubber industry in Nigeria’s Benin region.

Africa in the Great Recession

A quick look at the World Development Indicators shows that, while African growth rates have slowed since 2007, they have not turned negative. African growth lags Asia, but remains stronger than in North America or the world as a whole. GDP per capita tells a similar story: African incomes have been growing more slowly since 2007, but did not fall on average. Africa has fared better during the Great Recession than during the Great Depression.

Why?

Jake Bright suggests a set of reasons for this: African growth, a growing consumer class, modernization of banking and telecommunications, and newly-created stock markets have attracted foreign investment, aided by remittances.

Antoinette Sayeh cautions that countries with export markets in advanced countries have had worse experiences with the depression, as have those still engaged in conflict. Her focus is on two factors: strong pre-recession growth (driven by commodity prices, debt relief, and market liberalization) and cushioning factors (high commodity prices, growth in other emerging markets, lack of financial crisis, and a lack of austerity).

Gareth Austin (whose other work I recommend) is also cautious. African growth has slowed, and Africans faced higher global food prices even before the recession. He suggests that richer African countries felt the recession first, due to their integration into world financial markets. Poorer countries have been hit by a fall in commodity prices. He does, however, suggest several influences that have cushioned the blow: strong pre-recession fiscal and trade balances due to previous structural adjustment, floating currencies, and early recovery in China and India. Can data help us sort through these explanations? The WDI and IMF World Outlook provide data on many of the variables mentioned above. In particular:

  • The growth rate of PPP GDP-per capita from 2001 to 2006 measures pre-recession growth.
  • Log PPP GDP-per capita in 2006 captures convergence.
  • The change in foreign direct investment from 2006 to 2010 measures the resilience of foreign investment since the recession started.
  • The change in the net barter terms of trade from 2006 to 2011 measures changes in the trade environment, including commodity prices, since the recession started.
  • Central government debt as a fraction of GDP in 2006 measures the pre-recession fiscal position.
  • The weighted mean tariff rate on all products in 2006 measures market liberalization before the recession.
  • The CPIA financial sector rating in 2006 measures the strength of the financial sector before the recession.
  • The change in the official exchange rate from 2006 to 2012 measures the extent of currency devaluation through the recession. This is reported in LCU per USD, so higher values correspond to a decline in the value of the local currency.
  • The change in the government expenditure from 2006 to 2012 (deflated by the GDP deflator) proxies for the extent to which austerity has been avoided.
  • Remittances received in 2006, per capita, are also available.

Are any of these correlated with relative growth performance between 2006 and 2012? I have posted some naive cross-country regressions below. These are neither careful nor causal, but the results are surprising. Only two variables stand out as predictors of growth through the recession: pre-recession growth, and exchange rate devaluation. crr

These correlations are large: I plot them below. A one standard deviation increase in pre-recession growth is correlated with of a 0.40 standard deviation increase in growth since 2006. A one standard deviation increase in the extent of devaluation (column 4) is correlated with a 0.53 standard deviation increase in growth since 2006. gdp2012_2006exrate2012_2006   gdp2012_2006gdp2006_2001

Together, these tell an unusual story: the African countries that have fared well during the Great Recession are those that were doing well before it and those who have devalued their currencies.

You can have a look yourself: download the .do files and data (Stata) used to produce these graphs and tables here.

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Can social norms interfere with efforts to curb rule-breaking?

Posted on June 11, 2013 by

corrupt

In every society, the correct functioning of economic, political and social institutions relies on the establishment and enforcement of norms guiding the behavior of the members of that society. In recent years there has been increasing interest in both the design and implementation of mechanisms for enforcing these norms, relying on social judgement and informal fines and/or rewards. Social enforcement mechanisms seem especially important in countries characterized by poor formal institutions, where, due to limited resources and pervasive corruption, top-down enforcement mechanisms are likely to be ineffective.

One example of an enforcement mechanism which has been gaining in popularity is the “I paid a bribe” website, first launched in India and subsequently replicated in Kenya, Indonesia, Zimbabwe and Pakistan (http://www.ipaidabribe.com ). The website gives citizens the opportunity to anonymously report their bribery experiences, hence increasing the observability of acts of corruption on the part of public officials and civil servants. Although the I Paid a Bribe websites are highly used, their effectiveness in the reduction of corruption has yet to be scientifically tested.

However other types of social enforcement mechanisms are beginning to be tested: a number of empirical evaluations aimed at limiting violations of societal norms such as corruption, absenteeism and poor performance of service providers have been recently conducted in developing countries. The results are mixed, ranging from successes in the monitoring of teacher attendance in Kenyan and Indonesian schools, and of health professionals in Uganda, to the failures of similar mechanisms in the context of Indian schools, and Indonesian road construction programs.

While enforcement mechanisms relying on social observability and informal sanctions seem to be, at least theoretically, a viable solution to the deficiencies of top-down systems, their effectiveness depends crucially on i) on how society views the violation of a given norm, ii) how willing individuals are to socially punish those that violate the rules, and iii) how responsive those that break the rules are to these `social sanctions’.

Indeed, societies greatly differ in both the degree of importance given to different rule-breaking behaviors and the severity with which violation of the rules are judged. In some societies it may be the case that petty crimes – such as cutting the line in a public office or at a bus stop – may not be viewed harshly or subject to much disapproval, whereas in other contexts these might be seen as more serious infractions, warranting some sort of social sanction. Even more serious crimes (such as tax evasion and corruption) may be harshly condemned socially in one country while being widely accepted or even informally-rewarded in another. Therefore, it is possible that  relying on social judgement and informal sanction-based enforcement mechanisms to thwart certain rule-breaking behaviors such as bribery and embezzlement of public resources might succeed in some environments, yet fail in others. Put differently, social norms and culture may play a significant role in determining the effectiveness of any given social enforcement mechanism.

In recent research with Tim Salmon, we asked whether pre-existing social norms and culture significantly affect the effectiveness of enforcement mechanisms which rely on social judgement and informal sanctions. To answer this question, we experimentally-investigated the extent to which the effectiveness of enforcement mechanisms is dependent on the cultural background of the potential rule breaker. Our approach was to take a sample of individuals from many different socio-cultural backgrounds, place them all in exactly the same formal institutional context, give them the chance to engage in different forms of rule breaking and then investigate how they responded to the same enforcement mechanism.

To this end, we conducted a specially-designed laboratory experiment with a sample of individuals who both grew up and currently live in the US, yet identified culturally with different countries, corresponding to the countries of origin of their ancestors (prior to migrating to the US). Given the immediate implications for designing social enforcement mechanisms in developing countries, we were especially interested in the role social judgement might have in deterring bad behaviour in individuals who identified culturally with countries with poor rule-of-law.

The experimental study
We conducted a laboratory experiment that simulated three rule-breaking situations: theft, bribery and embezzlement. Our experimental participants engaged in these rule-breaking games under three separate scenarios, each with a different degree of `social observability’ and the potential for others to express social disapproval. The first `treatment’ or situation was one in which the rule breaker’s actions were completely hidden from the victim. The second and third treatments allowed for, respectively, the victim to be informed of the rule breaking behavior and then finally for both the direct victim and players acting as “other members of society” to send social messages to the rule breakers.  Our aim was to investigate whether individuals in the potential rule breaking role respond differently if they knew that their action would be hidden from others or if they knew that it would be visible to the victim and potentially judged by others. The social messages that victims and other members of society could choose to send to rule-breakers are displayed in Figure 1.

Figure 1: Possible Social Messages

Figure 1: Possible Social Messages

Our Cross-Cultural Sample
The study involved 432 student subjects enrolled in a large US state university. We captured differences in cultural heritages by asking participants whether they and their families identify culturally with a country other than or in addition to the USA. About 50% of the students answered positively. A total of 52 countries are represented in our sample, ranging from Low Rule of Law countries such as Liberia and Nigeria to High Rule of Law countries such as Sweden and Norway. Figure 2 shows the distribution of the countries of origin of our experimental participants ordered according to the World Bank’s Rule of Law governance indicator.

Figure 2: Cultural Heritages and Rule of Law

Figure 2: Cultural Heritages and Rule of Law

Results and Policy Implications
By combining our experimental and survey data, we were able to see whether individuals with different cultural backgrounds respond differently to increased observability of their actions and to the possibility of social judgement. Our results indicate that this is the case: in particular, while subjects that identify culturally with high rule of law countries responded to the possibility of social judgement by decreasing their rule-breaking behavior, those who identified with low rule of law countries did not.

Our findings suggest that, while development policies that rely purely on social judgement and informal sanctions to prevent rule breaking behavior may work with high rule of law populations, they may be less likely to work with populations accustomed to low-rule-of law contexts. A more general implication of these results is that when designing and implementing a social enforcement mechanism, one must give very careful thought to the specific populations being targeted by the mechanism and the cultural contexts in which they are embedded.

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Does conflict affect political engagement in Africa?

Posted on May 7, 2013 by

UNMIS-peacekeeping

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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Local protectionism in developing economies: evidence from pharmaceutical firms in China

Posted on April 22, 2013 by

This post is written with Zheng Wang

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.

markus

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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CSAE Conference Plenary: The Millennium Development Goals – Beyond 2015.

Posted on March 25, 2013 by

kenny

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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Networks, gender and job referrals in Malawi

Posted on March 22, 2013 by

CSAEEnumerator

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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CSAE conference keynote: Ted Miguel on Conflict, Climate and African Development

Posted on March 20, 2013 by

miguel

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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