One of the primary goals of the Enterprise Surveys is to provide high quality data about the business environment based on establishments’ actual day-to-day experiences. This provides much needed information given how little is known about what businesses experience in developing economies. To raise awareness of the recently released Bangladesh 2013 Enterprise Survey, we provide a few highlights of the surveys below.
As the editors of Let's Talk Development, we want to respond to questions raised recently in social media channels about use of 2011 International Comparison Program (ICP) as well as during events and discussions about poverty and measurements during the Annual Meetings of the World Bank and IMF last week.
The World Bank currently uses an international poverty line of $1.25 (per person per day) in 2005 prices to monitor global poverty. The process draws on several data sources, including the ICP. The most recent global and regional poverty estimates cover the period 1981-2011 and are available from the recently updated Povcalnet database; they are based on data from well over 1,000 household surveys, covering nearly all developing countries. The latest estimates have been published and explained in both the recent Policy Research Report and the Global Monitoring Report, published last week.
The data and processes needed to measure global poverty and gauge improvements in the prosperity of the bottom 40% of people in each country present complex challenges and provoke considerable debate amongst poverty experts.
From the comparability of household surveys and their use in policy design to the utility of purchasing power parity data as a unifying standard for measuring the poor, the devil in global poverty analysis is in the details. It’s also vital to understand the World Bank’s recently adopted twin goals in a broader context, to see how they fit into a broader array of monitorable indicators that each come with their own specific features and insights. We must also listen to client governments and outside partners when they prefer to go beyond income to look at multidimensional social welfare functions.
As current and former World Bank employees, we have all worked to speed the development of African economies and have viewed Africa’s recent spectacular growth with mounting enthusiasm. Thus, we have followed with growing sadness and dismay the stories of human suffering emanating from Liberia, Sierra Leone and Guinea in the context of the Ebola epidemic. These horrifying stories of the effect of Ebola in West Africa are now overshadowing continued good economic news from the rest of the continent.
About a month ago we were asked – together with a much larger team – to estimate the economic costs of the outbreak for the West Africa region. The report, titled “The Economic Impact of the 2014 Ebola Epidemic: Short and Medium Term Estimates for West Africa,” was released yesterday.
Thinking about inequality is back in fashion! In its November 2013 outlook, the World Economic Forum called rising inequality the second biggest risk for 2014-15. The 2014 English translation of French economist Thomas Piketty’s “Capital in the 21st Century” became an instant bestseller among academics and practitioners in both developed and developing countries. Discussions of inequality are popping up everywhere, and even seem to be setting the tone of many round tables and presentations in the World Bank Group’s upcoming Annual Meetings.
Do migrants respond to differences in access to public goods and services in addition to income prospects of potential destinations? This issue is important in developing countries where provision of basic public goods affects not only income prospects but also quality of life. And in these countries, provision of public goods tends to vary widely across areas. In a Tiebout (1956) sorting model, such disparity in the provision of public goods such as roads, electricity, schools, hospitals, etc. should induce people to "vote with their feet" and to migrate to areas with better access to these infrastructures and services.
Simply stated, we never have enough data. This is true from smallest low income countries in Africa to the largest more complex economy in the West. And the need grows continuously as interconnected world markets and leapfrogging technologies smash through any remaining notions of a standard path to prosperity. For many countries in the developing world, the unfortunate paradox is that they have the greatest needs but the fewest resources, both financial and in terms of capacity. In this setting, researchers in statistics and economics have been developing new techniques to expand the usefulness of limited data. The broad body of work is collected under the umbrella “survey-to-survey imputation” and includes two recently-published papers in the World Bank Policy Research Working Paper series, “Updating Poverty Estimates at Frequent Intervals in the Absence of Consumption Data: Methods and Illustration with Reference to a Middle-Income Country,” by Hai-Anh Dang, Peter Lanjouw, and Umar Serajuddin, and “Estimating Poverty in the Absence of Consumption Data: The Case of Liberia,” by Andrew Dabalen, Errol Graham, Kristen Himelein, and Rose Mungai. (Fortunately the authors are much more creative in their approach to analysis than in their approach to naming papers.)
World Bank Group President Jim Kim will be interviewed by journalist Yang Lan in “Building Shared Prosperity in an Unequal World” event on Oct 8, 2014, from 10:00 a.m. to 11:00 a.m. in the Preston Auditorium at World Bank headquarters. Watch the live webcast here.
Kaushik Basu, Shereen Allam, Claudia Costin, Denny Kalyalya and other experts will discuss investing in human capital, social safety nets, and making growth greener as key elements needed for success on Oct 8, 2014, at 3:30 PM EST. Watch the live webcast here.
Obtaining consistent estimates on poverty over time as well as monitoring poverty trends on a timely basis is a priority concern for policy makers. However, these objectives are not readily achieved in practice when household consumption data are neither frequently collected, nor constructed using consistent and transparent criteria.
Conventional wisdom holds that Sub-Saharan African farmers use few modern inputs despite the fact that most growth-inducing and poverty-reducing agricultural growth in the region is expected to come largely from expanded use of inputs that embody improved technologies, particularly improved seed, fertilizers and other agro-chemicals, machinery, and irrigation. Yet following several years of high food prices, concerted policy efforts to intensify fertilizer and hybrid seed use, and increased public and private investment in agriculture, how low is modern input use in Africa really?