How randomised trials became big in development economics


Seán Mfundza Muller, Grieve Chelwa, and Nimi Hoffmann at the Conversation: “…One view of the challenge of development is that it is fundamentally about answering causal questions. If a country adopts a particular policy, will that cause an increase in economic growth, a reduction in poverty or some other improvement in the well-being of citizens?

In recent decades economists have been concerned about the reliability of previously used methods for identifying causal relationships. In addition to those methodological concerns, some have argued that “grand theories of development” are either incorrect or at least have failed to yield meaningful improvements in many developing countries.

Two notable examples are the idea that developing countries may be caught in a poverty trap that requires a “big push” to escape and the view that institutions are key for growth and development.

These concerns about methods and policies provided a fertile ground for randomised experiments in development economics. The surge of interest in experimental approaches in economics began in the early 1990s. Researchers began to use “natural experiments”, where for example random variation was part of a policy rather than decided by a researcher, to look at causation.

But it really gathered momentum in the 2000s, with researchers such as the Nobel awardees designing and implementing experiments to study a wide range of microeconomic questions.

Randomised trials

Proponents of these methods argued that a focus on “small” problems was more likely to succeed. They also argued that randomised experiments would bring credibility to economic analysis by providing a simple solution to causal questions.

These experiments randomly allocate a treatment to some members of a group and compare the outcomes against the other members who did not receive treatment. For example, to test whether providing credit helps to grow small firms or increase their likelihood of success, a researcher might partner with a financial institution and randomly allocate credit to applicants that meet certain basic requirements. Then a year later the researcher would compare changes in sales or employment in small firms that received the credit to those that did not.

Randomised trials are not a new research method. They are best known for their use in testing new medicines. The first medical experiment to use controlled randomisation occurred in the aftermath of the second world war. The British government used it to assess the effectiveness of a drug for tuberculosis treatment.

In the early 20th century and mid-20th century American researchers had used experiments like this to examine the effects of various social policies. Examples included income protection and social housing.

The introduction of these methods into development economics also followed an increase in their use in other areas of economics. One example was the study of labour markets.

Randomised control trials in economics are now mostly used to evaluate the impact of social policy interventions in poor and middle-income countries. Work by the 2019 Nobel awardees – Michael Kremer, Abhijit Banerjee and Esther Duflo – includes experiments in Kenya and India on teacher attendancetextbook provisionmonitoring of nurse attendance and the provision of microcredit.

The popularity, among academics and policymakers, of the approach is not only due to its seeming ability to solve methodological and policy concerns. It is also due to very deliberate, well-funded advocacy by its proponents….(More)”.

A World With a Billion Cameras Watching You Is Just Around the Corner


Liza Lin and Newley Purnell at the Wall Street Journal: “As governments and companies invest more in security networks, hundreds of millions more surveillance cameras will be watching the world in 2021, mostly in China, according to a new report.

The report, from industry researcher IHS Markit, to be released Thursday, said the number of cameras used for surveillance would climb above 1 billion by the end of 2021. That would represent an almost 30% increase from the 770 million cameras today. China would continue to account for a little over half the total.

Fast-growing, populous nations such as India, Brazil and Indonesia would also help drive growth in the sector, the report said. The number of surveillance cameras in the U.S. would grow to 85 million by 2021, from 70 million last year, as American schools, malls and offices seek to tighten security on their premises, IHS analyst Oliver Philippou said.

Mr. Philippou said government programs to implement widespread video surveillance to monitor the public would be the biggest catalyst for the growth in China. City surveillance also was driving demand elsewhere.

“It’s a public-safety issue,” Mr. Philippou said in an interview. “There is a big focus on crime and terrorism in recent years.”

The global security-camera industry has been energized by breakthroughs in image quality and artificial intelligence. These allow better and faster facial recognition and video analytics, which governments are using to do everything from managing traffic to predicting crimes.

China leads the world in the rollout of this kind of technology. It is home to the world’s largest camera makers, with its cameras on street corners, along busy roads and in residential neighborhoods….(More)”.

Government at a Glance 2019


OECD Report: “Government at a Glance provides reliable, internationally comparative data on government activities and their results in OECD countries. Where possible, it also reports data for Brazil, China, Colombia, Costa Rica, India, Indonesia, the Russian Federation and South Africa. In many public governance areas, it is the only available source of data. It includes input, process, output and outcome indicators as well as contextual information for each country.

The 2019 edition includes input indicators on public finance and employment; while processes include data on institutions, budgeting practices and procedures, human resources management, regulatory government, public procurement and digital government and open data. Outcomes cover core government results (e.g. trust, inequality reduction) and indicators on access, responsiveness, quality and citizen satisfaction for the education, health and justice sectors.

Governance indicators are especially useful for monitoring and benchmarking governments’ progress in their public sector reforms.Each indicator in the publication is presented in a user-friendly format, consisting of graphs and/or charts illustrating variations across countries and over time, brief descriptive analyses highlighting the major findings conveyed by the data, and a methodological section on the definition of the indicator and any limitations in data comparability….(More)”.

The Rising Threat of Digital Nationalism


Essay by Akash Kapur in the Wall Street Journal: “Fifty years ago this week, at 10:30 on a warm night at the University of California, Los Angeles, the first email was sent. It was a decidedly local affair. A man sat in front of a teleprinter connected to an early precursor of the internet known as Arpanet and transmitted the message “login” to a colleague in Palo Alto. The system crashed; all that arrived at the Stanford Research Institute, some 350 miles away, was a truncated “lo.”

The network has moved on dramatically from those parochial—and stuttering—origins. Now more than 200 billion emails flow around the world every day. The internet has come to represent the very embodiment of globalization—a postnational public sphere, a virtual world impervious and even hostile to the control of sovereign governments (those “weary giants of flesh and steel,” as the cyberlibertarian activist John Perry Barlow famously put it in his Declaration of the Independence of Cyberspace in 1996).

But things have been changing recently. Nicholas Negroponte, a co-founder of the MIT Media Lab, once said that national law had no place in cyberlaw. That view seems increasingly anachronistic. Across the world, nation-states have been responding to a series of crises on the internet (some real, some overstated) by asserting their authority and claiming various forms of digital sovereignty. A network that once seemed to effortlessly defy regulation is being relentlessly, and often ruthlessly, domesticated.

From firewalls to shutdowns to new data-localization laws, a specter of digital nationalism now hangs over the network. This “territorialization of the internet,” as Scott Malcomson, a technology consultant and author, calls it, is fundamentally changing its character—and perhaps even threatening its continued existence as a unified global infrastructure.

The phenomenon of digital nationalism isn’t entirely new, of course. Authoritarian governments have long sought to rein in the internet. China has been the pioneer. Its Great Firewall, which restricts what people can read and do online, has served as a model for promoting what the country calls “digital sovereignty.” China’s efforts have had a powerful demonstration effect, showing other autocrats that the internet can be effectively controlled. China has also proved that powerful tech multinationals will exchange their stated principles for market access and that limiting online globalization can spur the growth of a vibrant domestic tech industry.

Several countries have built—or are contemplating—domestic networks modeled on the Chinese example. To control contact with the outside world and suppress dissident content, Iran has set up a so-called “halal net,” North Korea has its Kwangmyong network, and earlier this year, Vladimir Putin signed a “sovereign internet bill” that would likewise set up a self-sufficient Runet. The bill also includes a “kill switch” to shut off the global network to Russian users. This is an increasingly common practice. According to the New York Times, at least a quarter of the world’s countries have temporarily shut down the internet over the past four years….(More)”

African countries are missing the data needed to drive development


David Pilling at the Financial Times: “When statisticians decided to track how well African countries were doing in moving towards their 2030 UN sustainable development goals, they discovered a curious thing: no one had the faintest idea. More accurately, on average, African governments keep statistics covering only about a third of the relevant data. To be fair, the goals, which range from eradicating poverty and hunger to creating sustainable cities and communities, are overly complicated and sometimes unquantifiable.

The millennium development goals that they superseded had eight goals with 21 indicators. The SDGs have 17, with 232 indicators. Yet statisticians for the Mo Ibrahim Foundation, which compiled the report, are on to something. African states don’t know enough about their people. 

In this age of mass surveillance, that might seem counterintuitive. Surely governments, not to mention private companies, have too much information on their citizenry? In fact, in many African nations with weak states, big informal economies and undocumented communities, the problem is the reverse. How many people are there in Nigeria? What is the unemployment rate in Zimbabwe? How many people in Kibera, a huge informal settlement in Nairobi, have access to healthcare? The answers to such basic questions are: we don’t really know.  Nigeria last conducted a census in 2006, when the population — a sensitive topic in which religion, regionalism and budget allocations are messily intertwined — came out at 140m. These days it could be 180m or 200m. Or perhaps more. Or less.

President Muhammadu Buhari recently complained that statistics quoted by international bodies, such as those alleging that Nigeria has more people living in absolute poverty than India, were “wild estimates” bearing “little relation to facts on the ground”. The riposte to that is simple. Work out what is happening and do something about it. Likewise, unemployment is hard to define, let alone quantify, in a broken economy such as Zimbabwe’s where cited jobless statistics range from 5 to 95 per cent. Is a struggling subsistence farmer or a street-side hawker jobless or gainfully employed?

For that matter what is the status of a government employee who receives her salary in a useless electronic currency?  According to Seth Berkley, chief executive of the Vaccine Alliance, keeping tabs on unregistered people in the sprawling “slums” of Africa’s increasingly massive megacities, is harder than working out what is going on in isolated villages. If governments do not know whether a person exists it is all too easy to ignore their rights — to healthcare, to education or to the vote. The Mo Ibrahim Foundation found that only eight countries in Africa register more than 90 per cent of births. Tens of millions of people are literally invisible. Mr Ibrahim, a Sudanese billionaire, calls data “the missing SDG”….(More)”

Digital dystopia: how algorithms punish the poor


Ed Pilkington at The Guardian: “All around the world, from small-town Illinois in the US to Rochdale in England, from Perth, Australia, to Dumka in northern India, a revolution is under way in how governments treat the poor.

You can’t see it happening, and may have heard nothing about it. It’s being planned by engineers and coders behind closed doors, in secure government locations far from public view.

Only mathematicians and computer scientists fully understand the sea change, powered as it is by artificial intelligence (AI), predictive algorithms, risk modeling and biometrics. But if you are one of the millions of vulnerable people at the receiving end of the radical reshaping of welfare benefits, you know it is real and that its consequences can be serious – even deadly.

The Guardian has spent the past three months investigating how billions are being poured into AI innovations that are explosively recasting how low-income people interact with the state. Together, our reporters in the US, Britain, India and Australia have explored what amounts to the birth of the digital welfare state.

Their dispatches reveal how unemployment benefits, child support, housing and food subsidies and much more are being scrambled online. Vast sums are being spent by governments across the industrialized and developing worlds on automating poverty and in the process, turning the needs of vulnerable citizens into numbers, replacing the judgment of human caseworkers with the cold, bloodless decision-making of machines.

At its most forbidding, Guardian reporters paint a picture of a 21st-century Dickensian dystopia that is taking shape with breakneck speed…(More)”.

Urban Slums in a Datafying Milieu: Challenges for Data-Driven Research Practice


Paper by Bijal Brahmbhatt et al: “With the ongoing trend of urban datafication and growing use of data/evidence to shape developmental initiatives by state as well as non-state actors, this exploratory case study engages with the complex and often contested domains of data use. This study uses on-the-ground experience of working with informal settlements in Indian cities to examine how information value chains work in practice and the contours of their power to intervene in building an agenda of social justice into governance regimes. Using illustrative examples from ongoing action-oriented projects of Mahila Housing Trust in India such as the Energy Audit Project, Slum Mapping Exercise and women-led climate resilience building under the Global Resilience Partnership, it raises questions about challenges of making effective linkages between data, knowledge and action in and for slum communities in the global South by focussing on two issues.

First, it reveals dilemmas of achieving data accuracy when working with slum communities in developing cities where populations are dynamically changing, and where digitisation and use of ICT has limited operational currency. The second issue focuses on data ownership. It foregrounds the need for complementary inputs and the heavy requirement for support systems in informal settlements in order to translate data-driven knowledge into actionable forms. Absence of these will blunt the edge of data-driven community participation in local politics. Through these intersecting streams, the study attempts to address how entanglements between southern urbanism, datafication, governance and social justice diversify the discourse on data justice. It highlights existing hurdles and structural hierarchies within a data-heavy developmental register emergent across multiple cities in the global South where data-driven governmental regimes interact with convoluted urban forms and realities….(More)”.

‘Digital colonialism’: why some countries want to take control of their people’s data from Big Tech


Jacqueline Hicks at the Conversation: “There is a global standoff going on about who stores your data. At the close of June’s G20 summit in Japan, a number of developing countries refused to sign an international declaration on data flows – the so-called Osaka Track. Part of the reason why countries such as India, Indonesia and South Africa boycotted the declaration was because they had no opportunity to put their own interests about data into the document.

With 50 other signatories, the declaration still stands as a statement of future intent to negotiate further, but the boycott represents an ongoing struggle by some countries to assert their claim over the data generated by their own citizens.

Back in the dark ages of 2016, data was touted as the new oil. Although the metaphor was quickly debunked it’s still a helpful way to understand the global digital economy. Now, as international negotiations over data flows intensify, the oil comparison helps explain the economics of what’s called “data localisation” – the bid to keep citizens’ data within their own country.

Just as oil-producing nations pushed for oil refineries to add value to crude oil, so governments today want the world’s Big Tech companies to build data centres on their own soil. The cloud that powers much of the world’s tech industry is grounded in vast data centres located mainly around northern Europe and the US coasts. Yet, at the same time, US Big Tech companies are increasingly turning to markets in the global south for expansion as enormous numbers of young tech savvy populations come online….(More)”.

Digital Media and Wireless Communication in Developing Nations: Agriculture, Education, and the Economic Sector


Book by Megh R. Goyal and Emmanuel Eilu: “… explores how digital media and wireless communication, especially mobile phones and social media platforms, offer concrete opportunities for developing countries to transform different sectors of their economies. The volume focuses on the agricultural, economic, and education sectors. The chapter authors, mostly from Africa and India, provide a wealth of information on recent innovations, the opportunities they provide, challenges faced, and the direction of future research in digital media and wireless communication to leverage transformation in developing countries….(More)”.

How cities can leverage citizen data while protecting privacy


MIT News: “India is on a path with dual — and potentially conflicting — goals related to the use of citizen data.

To improve the efficiency their municipal services, many Indian cities have started enabling government-service requests, which involves collecting and sharing citizen data with government officials and, potentially, the public. But there’s also a national push to protect citizen privacy, potentially restricting data usage. Cities are now beginning to question how much citizen data, if any, they can use to track government operations.

In a new study, MIT researchers find that there is, in fact, a way for Indian cities to preserve citizen privacy while using their data to improve efficiency.

The researchers obtained and analyzed data from more than 380,000 government service requests by citizens across 112 cities in one Indian state for an entire year. They used the dataset to measure each city government’s efficiency based on how quickly they completed each service request. Based on field research in three of these cities, they also identified the citizen data that’s necessary, useful (but not critical), or unnecessary for improving efficiency when delivering the requested service.

In doing so, they identified “model” cities that performed very well in both categories, meaning they maximized privacy and efficiency. Cities worldwide could use similar methodologies to evaluate their own government services, the researchers say. …(More)”.