A common approach used to show high mobility is a low correlation of present and past incomes is captured, for instance, by the Hart index (cov lnyt, lnyt-1). If we assume, as is often done, that an individual’s income is comprised of a transitory component (short-term blips up or down in a self-employed person’s income that we can smooth, or even measurement error), and a permanent component where each income shock is persistent (say, an income loss after an involuntary job change (an AR (1) process with autoregressive coefficient, ρ), then the Hart index can be broken into three parts.
In Even it Up: Time to End Extreme Inequality, Oxfam has delivered another powerful report making the case that tackling inequality is essential to create a more just world and to eliminate extreme poverty. I was asked to comment on this newly released report at an October 31 event held at the IMF, and was as impressed by the presentation as I was with the report.
Oxfam effectively uses research findings to advocate for policy changes to reduce global inequality. This statistics-laden report also wisely features compelling stories about real people, helping the reader to better understand how vast disparities in wealth adversely affect wellbeing. Oxfam has consistently argued to bring inequality to the fore of policy discussions, and not surprisingly, this report appears to have created a groundswell for their global #Even It Up campaign. While there were instances where I found myself questioning the quality of some references supporting a few statements and estimates, my overall reaction was that the ‘big picture’ claims of the report were well substantiated. In my comments, I suggest that if this report is a call to action, a useful next step for Oxfam or a partner in this work, will be to bring more clarity to what it means to eliminate extreme inequality. Establishing a goal or a measure to monitor progress will help to create better policies, and ensure better collaboration across governments and institutions.
A new working paper by Shahe Emran and Forhad Shilpi looks at the impact of increased agricultural productivity (e.g. through increased rainfall) on hired labor, wages and poverty. The paper finds a positive response of labor hours devoted to market activities as opposed to home production. Evidence also indicates that a positive rainfall shock increases per capita consumption significantly, thus implying that agricultural productivity increase played an important role in poverty reduction achieved in the last two decades in rural Bangladesh.
Today is the International Day for the Eradication of Poverty, and the theme for this year is 'Leave no one behind: think, decide and act together against extreme poverty.' Learn more, and follow on Twitter #endpoverty.
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.
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.)
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.
In the context of development, globalization has always had two facets. For the advocates of globalization, it has facilitated financial and economic integration around the world and has played a substantial role in reducing poverty in many developing countries. For those who oppose it, it has introduced new challenges such as economic structural changes, huge income inequality and development disparities across and within developing countries. The changing development landscape with globalization calls for the necessity of reconsidering effective development aid strategies.
Enhancing the effectiveness of aid has long been the international development community’s core agenda, given the limited resources available for the fight against poverty. With the establishment of the Millennium Development Goals (MDGs) in 2000 and the implementation of the Paris Declaration (PD) on Aid Effectiveness in 2005, the international community has continued to improve the impact of aid on development. However, poverty still persists despite drastic changes in the development landscape.
Development is not easy; making it sustainable, even more difficult. Take for example road traffic rules. We can build better roads and install traffic lights, but cannot guarantee adherence to traffic rules. Even with laws in place, people may be more willing to pay fines than stop at a red light or wear seat belts. How do you make people value their own lives or their betterment? To succeed, we have to motivate people rather than just educate them.