Democracy Lab

Burma's Senseless Census

Burma's census disregards the complex ethnic identities of its people. Could this breathe new life into sectarian conflict?

Next year, Burma will embark on its first census-taking process in more than three decades. It's an opportunity, but it's also a significant risk. On the one hand, the census could compel the state to finally recognize long-excluded people and foster a better collective understanding of the daily struggles that most Burmese face. But on the other, the census is set up to obscure Burma's incredible diversity by requiring that Burmese people choose just one ethnic identity, even if they identify with many ethnicities. This comes at a dangerous point in Burma's simmering ethnic conflict, especially since nationalists are now using conceptions of exclusive and timeless ethnicity to justify violence against populations suddenly deemed irrevocably "foreign."

Instead of fueling such demagoguery, politics around the census process should expose the inaccuracy of those narratives and highlight the wonderfully mixed-up nature of ethnicity in Burma. Otherwise, the census seems poised to be part of a new kind of Burmese state practice, one that simply goes from domination (direct and despotic) to a new kind of control (diffused and bureaucratic) that limits rather than enables Burma's people.

Burma has 135 "official national races" (in addition to the Chinese, Indians, Rohingya, etc., who have yet to be recognized as autochthonous despite their long-standing membership in Burma's society). Observers use this number to remark on Burma's incredible diversity -- but this categorization is often myopic. The current categories imply that every citizen fits snugly into one silo: only Shan, only Karen, only Burman. A closer look at Burma's ethnic make-up, however, shows a vast diversity not simply within the country, but within people themselves.

Over three months of field research in Yangon this summer, I asked dozens of Burmese about their lu-myo (race or ethnicity) and found that individuals often describe complex, mixed-ethnic genealogies. For example, a Burmese colleague explained that ethnic identity is highly dependent on context: "For people like me who live in cities and don't speak an ethnic minority language, don't have ethnic minority names, and who are Buddhists, I don't think it would be a problem to identify ourselves as ‘Bamar lu-myo' ['Burman'] at first. But as we talk more about ourselves we include more information about different ethnic roots we have.... I am Bamar, but I'm also Mon, Pa-O, and Chinese." As this suggests, in Burma, ethnicity is lived less as a pseudo-scientific racial category and more as a set of practices shaped by one's environment.

Because context matters, an individual's own lu-myo can also be "on the move," changing between generations or within individuals over their own lifetimes. For instance, a man told me about his father's shifting identity: he was born Rohingya Muslim, but after refraining from Islamic worship practices, marrying a Rakhine Buddhist, taking on Rakhine modes of dress, drinking habits, etc., he now is often considered Rakhine. There are countless examples of this phenomenon: a colleague identifies as Mon though a cousin of hers does not; another scholar found a Karen-identified brother and Kachin-identified sister.

And yet, against these mutating and elusive identifications, the recent conflict in Burma's western Arakan state between Rakhine Buddhists and Rohingya Muslims -- in which mobs of local Buddhists have left hundreds of Rohingya dead and 125,000 displaced -- relies on a concept of ethnicity that is more absolute. (In the photo above, Muslim residents of Rakhine state await aid after losing their homes in sectarian violence in early October.) I interviewed multiple Rakhine individuals who insisted that "all so-called Rohingya" were actually "Bengalis" (considered "outsiders") and should be expelled. At the same time, Wakkar Uddin, a prominent Rohingya activist, told an audience at Columbia University last year that the Rohingya were determined to expel illegal "Bengalis." Significant here is how Buddhist Rakhine reject any potential blurring of boundaries between themselves and Muslims (whether Rohingya or "Bengali"), while the Rohingya are doing the same with themselves and "Bengalis."

The Rakhine/Rohingya case shows that conflicts can ossify conceptions of ethnicity to the point where they are no longer fluid and flexible, particularly when ethnicity becomes in part a vehicle for accessing resources. International media coverage has focused on racist monks or shadowy military elites collaborating with Rakhine demagogues to foment unrest. However, interviews with Rakhine individuals suggest that the conflict is grounded in perceived struggles over resources, especially surrounding the recently completed Shwe Pipeline, which carries gas to China but has left Rakhine state the second-least developed in Burma. Moreover, Rakhine individuals told me they were afraid of "losing their land" to Rohingya, who are ostensibly able to win control of resources by utilizing the support of international Muslim communities.

Other Rakhine say that international development only benefits Rohingya and ignores Rakhine needs. One man asked, "Why do the NGOs always come to our land but provide nothing for us, only for the Rohingya?" As a Rakhine woman explained, in this context, "Rakhine" has come to mean something very particular: "If we had development, we might say we are just 'Myanmar' [citizens]. But we don't." Rapid and unequal development is making ethnicity a conduit for protecting access to resources, a phenomenon that appears to be spreading across the country.

Given that ethnicity is a fluid but potentially charged concept, the question becomes whether Burma's reform process will embrace the country's complexity, or choose to privilege mono-ethnicity. This is where the census comes in. Interviews with the United Nations Population Fund (UNFPA), the agency providing technical assistance to the census process, reveal that the census has been designed to ignore the existence of multiple identities. Respondents must choose only one of the official 135 ethnicities, or check the "Other" box and write in their ethnicity. If a person with multiple identities refuses to choose one, the census defaults to their father's ethnic identity.

This may have serious political consequences. If people who claim multiple identities choose to report only, for instance, a "Burman" identity, hyper-nationalist movements may argue that these data "prove" that Burma's ethnic issues were always overstated and demand that the government grant collective resources to the besieged majority. Alternatively, if people report only non-Burman identities, the same movement could use those data to construct an equally dangerous argument: "We Burmans, the rightful sons of Burma's soil, are being bred out by the ethnic minorities. We must fight back." Burma's current monk-led, anti-Muslim "969 movement" can be seen as an inchoate version of such politics.

Why, then, would the state choose to implement the census this way? Is this a government conspiracy, a project to foment extremism while displacing official recognition of diversity? It appears not: UNFPA's technical advisors say that it is simply logistically difficult -- for both the census enumerators and its respondents -- to record multiple ethnicities.

But this could have drastic consequences. Comparative historical evidence shows that state census projects can intervene in sociological reality, creating the very categories they count. Indeed, a closer inspection of Burma's current 135 official races show them to already be arbitrary and confused, asserting phantom ethnicities on one hand and eliminating existing identities on the other. As scholar Mufti Myint Thein shows, the government concocted the number 135 in 1982, when many Muslim ethnicities were removed from official recognition (link in Burmese). These acts of reduction provide the grounds for exclusion: as in, "you are group x, and group x is not part of us."

How will Burmese people respond to such a project? During the long years of military control, state messages were often disregarded or ignored by a wary or disinterested populace. But now, Burma's state elites are busy reforming health, education, legal, and tax sectors, and much more, promising a transition from military authoritarianism to an aspiring Weberian-bureaucracy. When institutional changes actually affect people's daily needs, they have reason to listen; when these changes hinge on ideas of ethnic belonging, ethnic conflict may follow. Since Burma's most recent constitution guarantees special political representation if a lu-myo achieves 0.1 percent of the population, ethnicity will be a powerful means for groups to fight for their interests -- but only for the ones that qualify. The census, then, will help determine which groups matter in Burma, and which don't.

So what can census makers do to fix this problem? The best option seems to be to change the current format to allow citizens to select multiple identities to accurately represent their experiences. Even then, this may not be enough to dampen the socially fragmentary effects of Burma's current scramble for development.

Indeed, whether the census is reformed or not, what ultimately matters is how this census information is turned into political narratives about legitimate political belonging. Contesting ethnic violence in Burma will require messages that stress that the military regime was abusive to Burmese people of all ethnic backgrounds -- but that people from these varied groups are still able to forge relationships based on mutual respect and benefit, and are all committed to participating in a future Burma.

In other words, the census can certainly make things worse, but it cannot make things better on its own. Political leaders and citizens must together craft a new concept of citizenship in Burma, one based on the shared politics of daily life there that embraces all of Burma's diverse people without eliding any of their particular identities.

Soe Than WIN/AFP/Getty Images

Democracy Lab

Misunderestimating Corruption

Why sleaze is so hard to calculate.

I have a recurring dream (or perhaps nightmare) about today's practices in social science research. In the dream, a conservative elder gentleman -- selected in a process of great complexity resting on decades of research on sampling -- is subjected to questioning by a highly professional interviewer from a polling firm of great repute. The interviewer is not of the same social class, generation, gender, or ethnic origin as the respondent, reducing the possibility of an empathetic connection. In the course of faithfully administering a questionnaire whose intricate structure has taken hundreds of hours to construct, the interviewer nonchalantly reads a question: "Have you ever committed heinous acts of bestiality? Please answer yes or no." The respondent sputters a "No." The interviewer thanks the respondent profusely for his candor. Later a researcher applies the highest-powered econometric techniques to analyze the data.

Despite the success of using survey data in my years of research, the above daydream reveals a persistent worry from which I cannot shake myself free. Economists, in general, extensively use data about embarrassing, immoral, or illegal acts obtained by directly questioning possible perpetrators of those acts. Highly reputable organizations such as the World Bank and Transparency International publicize country corruption scores based on self-reports of bribes paid. Development economics relies on surveys that touch upon issues like adherence to unpopular political opinions or participation in corruption. But all of these activities involve great dissonance between the sophistication of the statistical methodology employed and the naiveté implicit in assuming that those dishonest enough to bribe will be endearingly honest in answering the man or woman behind the clipboard.

We know that survey respondents are often not candid when responding to questions that bear on how others view them, or indeed on how they view themselves. In one of the more amusing examples, men systematically report a greater number of opposite-sex sexual partners than women do, even though simple mathematics tells us that the average values for male and female respondents must be equal. Even in matters of the mundane, people lie. In a classic study, 19 percent of survey respondents in Chicago were found to incorrectly claim possession of a library card.

I have been interested in how much this lack of candor affects data on corruption for some time. In early work, Omar Azfar, who sadly passed away four years ago, and I developed a technique, similar to the famous line from Hamlet, to detect which particular people were reticent to truthfully answering questions on corruption. The exact details are arcane, but the method effectively relied on cornering respondents so that if they were to remove even the remotest implication of guilt from their answers, they would also be claiming that a coin tossed seven times always came up tails. Since elementary probability theory shows that the chance of getting seven tails in a row is very tiny, a set of answers protesting too much the respondent's innocence necessarily implies that the respondent has not told the truth!

Managers of Romanian firms were the unfortunate subject of our experiment. Our results allowed us to identify 10 percent of respondents as reticent for sure, and our best estimate was that a further 32 percent were reticent but not identifiable by our methods. Corruption estimates were raised by 33 percent when we took reticence into account. Those identified as unwilling to tell the truth were only half as willing as other respondents to admit to lying in their own interest!

The methodology used in Romania was a crude test of an idea and therefore could be greatly improved upon. I have accomplished this in recent work with Aart Kraay of the World Bank. Again the methods are too arcane to describe here, but they depend upon the fact that being reticent implies different distortions in the responses to two different types of survey questions. The two types of questions are conventional ones -- have you paid a bribe? -- and random response questions -- answer yes if either your coin-toss came up heads or if you have paid a bribe. Although random response questions were originally proposed as a means of encouraging candor, in fact they do not do that well at all. Instead, they induce different patterns of responses than conventional questions.  We were able to mesh together the two different response patterns and estimate two different characteristics of respondents -- guilt on matters of bribery and reticence in answering survey questions. (With only one type of question, it is impossible to estimate two different characteristics. And that is the problem inherent in all existing surveys on sensitive topics.) 

Earning our undying gratitude, a World Bank team included our questions in a survey of Peruvian firms and the Gallup Organization fielded them in 10 Asian countries in its World Poll. Using conservative assumptions, we found that respondents in Peru answered conventional questions on corruption candidly only 50 percent of the time. Adjustment for this reticence doubled the estimate of the incidence of bribe-paying. With less conservative but still reasonable assumptions, the estimate of bribe-paying was triple the standard one. Across the Asian countries, the proportion of conventional questions answered candidly varied from a high of 79 percent in Indonesia to a low of 53 percent in India, meaning our estimates of corruption were 25 percent higher than standard estimates in Indonesia and 100 percent higher in India.

Organizations that produce country data on such compelling subjects as corruption are fond of producing rankings, and the media is quick to convert plain vanilla estimates into startling comparisons. But our research shows that such comparisons might be off the mark because different samples of respondents have different propensities for reticence. For example, in Peru, conventional measurement indicates that very small firms are three times as likely to pay bribes as large firms, but this ratio increased to six-fold when using our new methods. Bribe-paying in the region of Arequipa looked quite similar to that in Lima until we applied our methods and then found three times as much in Arequipa as in Lima. The situation is similar for cross-country comparisons, with our methods making India look much worse and Indonesia much better, comparatively speaking.

Much rests on estimates of corruption -- for example, aid decisions by the World Bank, the Millennium Challenge Corporation, and USAID. Research on how to build policies and institutions to combat corruption is dependent on corruption data obtained from surveys. These are vital matters for economic development and they could be accomplished much more effectively if data were available that was free from the biases caused by the reticence of survey respondents. Perhaps researchers have given short shrift to this problem because they have downplayed the effect of reticence. Judging by our latest results these researchers have -- to borrow George W. Bush's evocative neologism -- misunderestimated the problem.