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Surveys Gone Bad – When “Yes” means “No”

Posted by Ashirul Amin

… or, A Story of How a Coding C*Screw-Up Made Bangladesh One of the Least Tolerant Countries in the World. (Spoiler: It isn’t!)

What We Thought We Knew

Yesterday, the Washington Post put out a story, A fascinating map of the world’s most and least racially tolerant countries. In that map, India and Bangladesh stuck out like a baboon’s butt as bastions of intolerance in the world. It’s reproduced below; red implies that more people said they “would not want neighbors of a different race”.


In fact, the percentages are more than a little damning:

India, Jordan, Bangladesh and Hong Kong by far the least tolerant. In only three of 81 surveyed countries, more than 40 percent of respondents said they would not want a neighbor of a different race. This included 43.5 percent of Indians, 51.4 percent of Jordanians and an astonishingly high 71.8 percent of Hong Kongers and 71.7 percent of Bangladeshis.”

Three thoughts occurred to me in this order:

  • Wow that’s an odd basket of countries to be lumped together as the most intolerant!
  • Ouch! Yeah I’m Bangladeshi.. and while I’ll be the first to admit we have our own favorite national stereotypes and periods of ethnographically inspired excitement, least tolerant? Really?
  • I wonder if someone fat fingered on this big time.

Thanks to the fact that both Max Fisher of WaPo and World Values Survey folks freely shared their sources, we can take a dive into the data that generated the map to explore thought #3 to our heart’s content.

The short answer is, yes, someone did fat finger this big time. “Yes” and “No” got swapped in the second round of the survey, which means that 28.3% of Bangladeshis said they wouldn’t want neighbors of a different race – not 71.7%.

26K Facebook likers and 2.5K Tweeters, take note.

Now, the long version for the data wonks amongst you. By the way this piece is restricted to Bangladesh – time, and ability to read primary questionnaire being main constraints.

What the WVS Data Really Says

(Spoiler: Data says it’s confused…)

There were 5 waves of data collection:

  • 1981-1984
  • 1989-1993
  • 1994-1999
  • 1999-2004
  • 2005-2007

Bangladesh has data for the third and fourth wave.

First, lets reproduce the 71.7% number.  We can use the interactive query tool WVS has set up on their website at: http://www.wvsevsdb.com/wvs/WVSIntegratedEVSWVSvariables.jsp?Idioma=I

To get this:wvs_sample1

“Mentioned” basically means “Yes” (we’ll explore this in detail in a bit).

What about the 1996 survey? Here’s the same page with 1996 data (table shown only):


If the oddity isn’t jumping out to you yet, let’s use something a little more visually friendly to compare the 1996 and 2002 numbers. WVS also makes available a Online Data Analysis toolkit at http://www.wvsevsdb.com/wvs/WVSAnalizeQuestion.jsp. With a literal tinkering, we can get to this screen:


“Mentioned” (the measure for less tolerance) went from 17.3% to 71.7%, while “Not Mentioned” went from  82.7% to 28.3%.


a) something WTHBBQPWN&%$#* happened in those 6 years that made 54.4% Bangladeshis do a 180 degree on their tolerance levels, OR

b) the coding got messed up and “Mentioned” is either 82.7% and 71.7% in 1996 and 2002 respectively, or 17.3% and 28.3% respectively.

For a survey size of N = 1,500ish, b) is always your safer bet when no obvious change agent is involved, endogenous or exogenous.

(If you’re Bangladeshi, you’re also probably laughing your behind off at a) since the 54.4% number involves tens of millions of people in a generally syncretistic society where appreciation for that heritage has arguably only increased with the younger generations, but that’s “anecdotal” for the purposes of this piece, so we’ll leave that thought there.)

If your data analysis foo is up to the task, I’d encourage you to check out the raw data itself to confirm that this is also the case there. The dataset is generously available at: http://www.wvsevsdb.com/wvs/WVSData.jsp

I used the STATA file for the “WVS FIVE WAVE AGGREGATED FILE 1981-2005″ dataset; you can also choose SPSS or SAS formats if they suit your toolkit better. For Stata, the relevant command is:

tab S002 A124_02 if S003 == 50

Giving the result:

                    | Neighbours: People of
                    |   a different race
               Wave | Not menti  Mentioned |     Total
          1994-1999 |     1,261        264 |     1,525 
          1999-2004 |       425      1,075 |     1,500 
              Total |     1,686      1,339 |     3,025


(S002 is the Wave, A124_02 is the question under study, and S003 contains the country, with Bangladesh being code 50.)

What Should The Data Say?

(Spoiler: Bangladeshis are a tolerant bunch – it’s ok to come visit.)

Ok, now that we are reasonably certain the data is confused, which way will it point once we de-confuse it? For this, we need to turn to the actual questionnaires. These too are available at http://www.wvsevsdb.com/wvs/WVSDocumentation.jsp?Idioma=I.

First, the 1996 survey. The relevant section is reproduced below (Bangladesh_WVS_1996_1.pdf, pg 10):

wvs_sample4The top line is the question, basically asking who the respondent “does not want or would not like to have as a neighbor”.

The first column, উল্লেখ করেছেন, means “Mentioned” – to be selected if the respondent notes a particular group of individuals (V51 – V60) are unwelcome neighbors.

The second column, উল্লেখ করেন নি, means “Not Mentioned” – this is for the more chillaxed bunch.



Now, let’s look at the 2002 survey. The relevant section is reproduced below (Bangladesh_WVS_2002_1.pdf, pg 19):

wvs_sample5The top line has the same question as above, verbatim. The first or second column headers are not the same though.

The first column, প্রতিবেশী হিসেবে পছন্দ করবো, means “Would like [X] as a neighbor” – to be selected if the respondent notes a particular group of individuals (V68 – V77) are welcome neighbors.

The second column, প্রতিবেশী হিসেবে পছন্দ করবো না, means “Would not like [X] as a neighbor” – this is for the less chillaxed bunch.


Yeah… oops!

’1′ and ’2′ stand for totally the opposite things in the two surveys.

Unless we are willing to allow that the data input folks consciously converted a ’2′ in 2002 to a ’1′ in 1996 to connect প্রতিবেশী হিসেবে পছন্দ করবো না to উল্লেখ করেছেন, I think it’s reasonable to assume that ’1′ was also coded for “Mentioned”/উল্লেখ করেছেন in the 2002 dataset, leading to a flip in the results for that question for that wave. Spot checks also suggest that this is what would be consistent with surveys from other countries.

With everything righted the right way, here then is what the final numbers look like:


Yes, 28.3%, not 71.7%.


  1. I only looked at the question that was used for the tolerance/intolerance WaPo piece. This inconsistency shouldn’t be extrapolated to any part of the rest of the Bangladesh survey unless one has double checked for that.
  2. I ran this for the Bangladesh dataset only. No idea if any of this applies to any other country dataset – same caution as above applies.

Is Bangladesh Killing Cash Soon?: In Pursuit of a Mobile Money Ecosystem

Posted by Sadruddin Salman

Bangladesh, with a population of nearly 160 million and a landmass of 147,570 square kilometers, is among the most densely-populated countries in the world.  It remains a low-income country, with a per capita income of US$ 652 in FY09 and 40 percent of its population living in poverty. Despite periods of political turmoil and frequent natural disasters, in the past decade Bangladesh has been marked by sustained growth(with nearly six percent on an average in past one decade), stable macroeconomic management, significant poverty reduction, rapid social transformation and human development. Foreign remittances sent by expatriate Bangladeshis remain one of the most consistent sources of foreign currency in Bangladesh, which earned Bangladesh 7th position among the top remittance-receiving countries in 2010, as reported byMigration and Remittance Fact Book 2011 of the World Bank.

Still, the majority of the Bangladeshis are unbanked, and access to financial services is very limited. Commercial banks have very low penetration in rural areas, where over 75 percent of the population lives. There are less than two ATMs for every 100,000 adults in the country. All of these characteristics make it a good business case for expanding accessibility to financial services through innovations.

Mobile networks have expanded quite rapidly in Bangladesh over the past decade. Currently, there are six mobile network operators (MNOs) in Bangladesh covering more than 90 percent of the geographic territory and 99 percent (coverage wise) of the population in Bangladesh. Consumer demand in Bangladesh makes the mobile market one of the fastest growing in the world. For instance, over the past 15 months, Bangladesh recorded nearly 1.4 million subscribers per month. The total number of mobile phone active subscribers reached about 73 million at the end of March 2011, with about a 45 percent penetration rate in the whole country. The Government and the Central Bank now recognize that the mobile banking is as a unique opportunity for the banks to increase their presence in rural and remote areas of the country and serve a huge unbanked population.

Banglalink, the fastest growing telecom operator in recent years, is the pioneer in testing out mobile mone initiatives in Bangladesh. The products it has recently launched along with other partners (such as banks and post offices) are as follows: (i) M-remittance (International and Local): which allows people to receive international remittance in the m-wallet account; enables local fund transfer P2P from one m-wallet to another m-wallet; facilitates cash deposit from “cash points” and other sources; and provides for cash withdrawal from “cash points”; (ii) M-payment (Utility): allows payment of utility bills using m-wallet; and (iii) M-collection: facilitates the purchase of train tickets.

M-remittance services are meant to address widespread issues such as inability to send money frequently, delays experienced while sending money, and issues related to insecure distribution and inconsistent delivery methods. It is also helping small entrepreneurs (agents) use part of the remittances which the receivers often do not withdraw all at once. The use of m-remittance services offered by Banglalink is picking up gradually. Around 1000 transactions are being reported across the country at the Banglalink mobile money agents/points. Users like the service for its fast and cost effective disbursement, as Banglalink found in its own market study.

Among many recent initiatives is the creation of a new organization called bKash — a scalable mobile money platform that will allow poor Bangladeshis to store, transfer and receive money safely via mobile phones. bKash is a joint venture of BRAC Bank Limited and Money in Motion LLC, USA, created out of a generous $10m grant from the Bill and Melinda Gates Foundation to ShoreBank International, an international consulting firm. The grant forms part of the Foundation’s $500m pledge over the next five years to expand savings and build a “new financial infrastructure” to bring savings services to the poor.

With mobile density of 45 percent and mobile retail density averaging 0.5 in each village, like many other countries such as Kenya, South Africa and the Philippines, Bangladesh also has enormous opportunity for financial inclusion through creating a solid “mobile money ecosystem”. This arguably will contribute to greater efforts at poverty reduction and economic development in Bangladesh.

(The writer/blogger is a Graduate student of Development Economics and International Finance at the Fletcher School of Law & Diplomacy, Tufts University)