I'll be hosting a one-hour live Question & Answer discussion on a new report I co-wrote with Asli Demirguc-Kunt titled "Measuring Financial Inclusion: The Global Findex Database," and will discuss its data methodology and main messages.
The leasing or purchase of agricultural land in the developing world has become a hot button issue as the planet has grown more crowded and the pressure to stake out more arable land – whether for food or biofuels – grows. At the same time, agricultural productivity in many of the poorest communities around the globe has stagnated and, unless higher crop yields can be attained, far too many people will remain trapped in poverty. Helping such smallholders catch the wave of rising interest in farmland is a key aim of the Annual World Bank Conference on Land and Poverty, which began Monday. Our theme this year is ‘Land Governance in a Rapidly Changing Environment.”
It’s clear that this year, many stakeholders who are either taking part in the conference or criticizing the event from outside think that global interest in farmland in the developing world is at a tipping point.
Within the Living Standards Measurement Study (LSMS) team, the anecdote goes that in the late 1970s World Bank President Robert McNamara, while reading through the first World Development Report, was stunned to discover that only a handful of countries were collecting any data for the reporting of poverty figures. He found this situation unacceptable and initiated an effort that among other things resulted in the creati
In an article on a Brookings website, Laurence Chandy and Homi Kharas chide the World Bank for three so-called “contradictions” in its global poverty numbers, including the Bank’s latest update. Let me look more closely at these “contradictions” in turn.
First, Chandy and Kharas chide the Bank’s team for assuming that North Korea has the same poverty rate as China. I wish Chandy and Kharas good luck in trying to measure poverty in a place like North Korea, with almost no credible data of any sort to work with. I could offer a guess that 80% of North Korea’s population is poor today—roughly the same as China before it embarked on its reform effort in 1978. This would add slightly less than 1 percentage point to our estimate of the “$1.25 a day” poverty rate for East Asia in 2008.
Over the last ten years or so, interest in multidimensional poverty analysis has really taken off - not only among academics, but also in the broader policy debate. No one seems to dispute that deprivations exist in multiple domains, and are often correlated. Looking at deprivations in health, education and other dimensions of well-being can complement the fundamental measurement of income and consumption-based poverty, illustrated by the World Bank poverty update announced yesterday. But agreement at this conceptual level clashes with often vociferous disagreement about how best to measure these deprivations.
The seasonality of poverty and food deprivation is a common feature of rural livelihood in Bangladesh, but it is more marked in the northwest region of Rangpur. The recently launched policy interventions in the region provide a test case of what works and what does not in combating seasonal hunger.
The analysis of Bangladesh’s experience with seasonal hunger vis-à-vis year-round poverty shows a clear distinction between what is observed and what is excluded from placement and evaluation of poverty-mitigation policies, based on official poverty statistics. The key recommendations from this analysis are as follows:
I blogged a few months ago about a paper Justin Lin and I were writing that focused on applying the Growth Identification and Facilitation Framework in Nigeria. The paper has just recently been completed and is now available online.
In the meantime, attacks on the UN house in Abuja have highlighted the extreme social tensions experienced by Nigeria. Many of these tensions may be related to the country’s persistent poverty. In fact, notwithstanding high and sustained growth over the past decade, Nigeria’s job creation has barely kept up with the relentless growth of its workforce, and youth unemployment has further risen. Moreover, formal sector employment has fallen, as a result of privatization and civil service retrenchment, while employment in informal family agriculture has increased.
Nigeria urgently needs to increase employment intensity and sustainability of its growth performance, and our paper can be a useful tool for developing a strategy to do so.
More than health insurance for the poor
In our last post, we showed how illness in India causes financial hardship and leaves Indians—especially poor ones—with limited access to affordable good-quality health care that can actually make them better. In this post, we outline a novel government-sponsored health insurance program in the state of Andhra Pradesh (AP)—a program that has the potential not just to reduce financial impoverishment but also raise quality standards in hospital care.
a) “Actors”, and their rights and responsibilities
Initiated by the then chief minister of AP, the medical doctor YSR Reddy, the Rajiv Aarogyasri scheme started in 2007 and is targeted at the below-poverty line (BPL) population. The scheme focuses on life-saving procedures that aren’t covered elsewhere in India’s patchwork of health programs, for which treatment protocols are available, and for which specialist doctors and equipment are required. Currently 938 tertiary care procedures are covered. The scheme revolves around five key “actors”, one unique to Aarogyasri and all with interesting rights and responsibilities.
With Nong Zhu
Migrant workers have been contributing to one-sixth of China’s GDP growth since the mid 1980s. The impact of rural migrants’ contribution is best seen in cities during the Chinese New Year, when they return to reunite with their families, leaving behind a massive urban labor shortage. This happens every year despite urban families and restaurant owners offering high bonuses.
There is a consensus that migration has contributed to increased rural income, but views differ on its impact on rural inequality. My view is that rural households with higher incomes are not more likely than poorer households to participate in migration or benefit disproportionately from it. Adding to my recent blog in People Move, I would like to discuss the reasons behind this.
One is always grateful to see attention paid to the quality and quantity of household data available to study poverty. It is a subject dear to my heart and to my colleagues in the Living Standards Measurement Study (LSMS ) in the World Bank. In sub-Saharan Africa, as a recent Global Dashboard post titled “What do we really know about poverty and inequality?” by Claire Melamed points out, there is still a dearth of data, even after years of government effort and international support. But there are data -- in some countries lots of data -- so it’s worth highlighting what is there. Today I wanted to add some nuance to the discussion of income and assets raised by Claire and, probably more importantly, steer people to some new data that will, we hope, excite the most blasé of you out there.