Back to Research@SMU Issue 46
By David Turner
SMU Office of Research & Tech Transfer – Socio-economic surveys of poverty often gather data at the regional or country level. But this helicopter view of the situation misses out on important patterns on the ground, and does not allow for the development of targeted solutions to tackle poverty.
An understanding of the street-level situation is thus vital, even if hard won, according to Tomoki Fujii, Associate Professor at the Singapore Management University (SMU) School of Economics.
“Even well-informed people might not know exactly where the current pockets of poverty are. They may know which regions are poorer, but not which villages,” says the development economist, whose research includes poverty analysis and impact evaluation of policy interventions such as infrastructure projects.
“Knowing where poverty is happening or whether the situation has improved is fundamental to the formulation and success of anti-poverty policies,” says Professor Fujii. But if localised knowledge is so important, why do policymakers have such significant gaps in their data?
Drilling down to the heart of poverty
The difficulty starts with the measurement of poverty, says Professor Fujii. Most poverty statistics are derived from consumption or income data collected in socio-economic surveys, which are typically good for measuring poverty at the country or regional level, but not at the level of villages and towns, he explains. This is because the information is usually obtained through sampling, and in addition, is aggregated.
Another problem is one of practicality. “Data collection is very expensive. You need to ask a huge number of questions about consumption: How many kilogrammes of oranges did your household purchase? What about bananas? What were their market values? You could ask hundreds of questions, and one survey would take several hours. Therefore, it is difficult to collect data from every household or to collect data frequently,” says Professor Fujii.
Although most economic surveys sample a few thousand households, this is still not enough to bring into focus the more fine-grained patterns, which Professor Fujii believes are essential to get a clear picture of poverty and to formulate relevant anti-poverty policies.
“If you know what is happening in small towns and villages, you can then target your policies, for example to provide resources that help people in need,” he says.
In his previous research, Professor Fujii combined socio-economic surveys with other sources such as census data, and uses econometric models to disaggregate poverty statistics into smaller geographical areas that can be plotted on maps, which policymakers can digest easily. His current work builds on a similar idea and aims to offer new ways to produce poverty statistics at a low cost and in a timely manner.
Shining a light on hidden connections
Professor Fujii’s research also sheds light on the impact of policies on poverty and other important socioeconomic outcomes. In his ongoing research with his co-authors, Professor Fujii has examined the impact of rural electrification on child nutrition and fertility in rural Bangladesh.
“Our study period of 2005 to 2010 corresponded with a massive expansion of rural access to electricity, and so provided an interesting opportunity to assess the impact of electrification on various socioeconomic outcomes,” says Professor Fujii.
An especially illuminating finding of this research was that electrification of homes showed a negative relationship with household fertility. In other words, households with electricity tended to have fewer children.[1]
“The natural question is why?” asks Professor Fujii. Could it be that electrification heralded the arrival of ‘other entertainment’, in the form of radios and televisions, for instance?
In fact, Professor Fujii says that the relationship is theoretically ambiguous because it is also possible that households with electricity may have more children. For example, the additional income opportunities due to electricity access may allow households to have more children and increase consumption.
However, he and his co-authors developed a theoretical model that describes how households make decisions about what to spend their money on and how they use their time, with or without access to electricity.
“If we find that rural electrification has a negative relationship with household fertility, then it has to be the case that consumption of non-child-related goods goes up and time spent on children goes down in our model, and this is consistent with our empirical research. Our model thus indicates that an important reason behind the fertility reduction in response to rural electrification is the change in time use,” he explains.
From data to impact
His research also points out that a standard cost-benefit analysis of proposed infrastructure spending would ignore or fail to detect important socio-economic impacts. For example, such an analysis would not have taken into account the relationship between electrification and fertility, even though this has important implications in low income countries with high fertility, such as Bangladesh.
“Electrification might lead people to spend more of their time and resources on other things besides having children,” says Professor Fujii. “Providing access to electricity could be more successful than campaigns directly aimed at reducing fertility.”
In related research, his team also found that electrification is associated with improved child nutrition in rural Bangladesh.[2] Possible reasons for this include reduced competition due to lower fertility and improved access to information. “Today, Bangladesh even has a television drama aimed at educating people about maternal and child health,” explains Professor Fujii.
Furthering his research under the umbrella of poverty and impact evaluation, Professor Fujii will continue to assess potentially impactful anti-poverty initiatives such as training for jobs, and conditional cash transfers – giving households cash if they send their children to school, for instance.
But while economists such as Professor Fujii are increasingly focusing on unnoticed or under-appreciated relationships and insights obtained through impact evaluation, are policymakers taking notice of these findings?
“There is always a gap between research and policymaking because policymakers may not be aware of the frontier research. It is also true to say that policymakers should be careful when applying research findings to policymaking,” says Professor Fujii.
“Take the research I discussed above as an example – what we find applies only to rural Bangladesh, and it is unclear whether similar patterns hold elsewhere. We obviously still have a lot to learn. However, if similar findings are consistently obtained, they will eventually feed into policymaking.”
Back to Research@SMU Issue 46
[1] T. Fujii and A.S. Shonchoy (2017) “Fertility and rural electrification in Bangladesh” SMU Economics and Statistics Working Paper No. 11-2017. Singapore Management University.
[2] T. Fujii, S, Xu, and A.S. Shonchoy (2017) “Impact of electrification on children’s nutritional status in rural Bangladesh.” Forthcoming in World Development.
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