Recall biases in retrospective survey data are widely considered to be pervasive and have important implications for effective agricultural research. In this paper, we leverage the survey design literature and test three strategies to attenuate mental anchoring in retrospective data collection: question order effects, retrieval cues, and aggregate (community) anchoring. We embed a survey design experiment in a longitudinal survey of smallholder farmers in Malawi and focus on anchoring bias in maize production and happiness exploiting differences between recalled and concurrent responses. We find that asking for retrospective data before concurrent data reduces recall bias by approximately 34% for maize production, a meaningful improvement with no increase in survey data collection costs. Retrieval cues are less successful in reducing the bias for maize reports and involve more data collection time, while community anchors can exacerbate the bias. Reversing the order of questions and retrieval cues do not help to ease the bias for happiness reports.
Coffee is a growth market. Current estimates indicate that global coffee production (in volume) has increased by more than 60% since the 1990s. Coffee is produced by around 25 million farmers, which are mainly smallholders in developing and least developed countries, and over 70% of the coffee produced is exported, resulting in about 20 billion US dollars annual foreign exchange earnings (ICO, 2020). COVID-19 represented a severe joint supply and demand shock to the global coffee sector, particularly during the first months after the start of the pandemic. As noted by Hernandez et al. (2020), the coffee industry experienced important disruptions downstream the value chain, including the functioning of key export infrastructure and international shipping, which combined with local currency devaluations and volatile coffee prices, which resulted in significant challenges for coffee growers, farm workers, and traders.
Self-reported retrospective survey data is widely used in empirical work but may be subject to cognitive biases, even over relatively short recall periods. This paper examines the role of anchoring bias in self-reports of objective and subjective outcomes under recall. We use a unique panel-survey dataset of smallholder farmers from four countries in Central America collected over a period of three years. We exploit differences between recalled and concurrent responses to quantify the degree of mental anchoring in survey recall data. We assess whether respondents use their reported value for the most recent period as a cognitive heuristic when recalling the value from a previous period, while controlling for the value they reported earlier. The results show strong evidence of sizeable anchoring bias in self-reported retrospective indicators for both objective measures (income, wages, and working hours) and subjective measures (reports of happiness, health, stress, and well-being). We also generally observe a larger bias in response to negative changes for objective indicators and a larger bias in response to positive changes for subjective indicators.
Ulrich Koester researches and teaches at the Institute for Agricultural Economics at the Christian-Albrechts-University of Kiel, Germany. He has been a member of the Scientific Advisory Board of the Ministry of Food, Agriculture and Forestry for over 20 years. Moreover, he gained experience working with the International Food Policy Research Institute in Washington D.C. and with numerous international organizations, including the World Bank, FAO, the European Commission, the European Parliament and the European Court of Auditors. His teaching experience is based on courses taught at more than ten universities in general economics and agricultural economics. Part I of the book lays the theoretical foundations for understanding price formation in product and factor markets. In addition to neoclassical theory, institutional economics is of particular importance. Part II presents and evaluates agricultural policy with special reference to the EU, whereby the evaluation framework goes beyond the usual welfare theory analysis. The book is also a valuable aid for students of economic policy, especially because of its detailed evaluation of individual agricultural market policy instruments. The book is aimed at students at universities, technical colleges as well as politicians interested in rational agricultural policy making.
In Cooking Data Crystal Biruk offers an ethnographic account of research into the demographics of HIV and AIDS in Malawi to rethink the production of quantitative health data. While research practices are often understood within a clean/dirty binary, Biruk shows that data are never clean; rather, they are always “cooked” during their production and inevitably entangled with the lives of those who produce them. Examining how the relationships among fieldworkers, supervisors, respondents, and foreign demographers shape data, Biruk examines the ways in which units of information—such as survey questions and numbers written onto questionnaires by fieldworkers—acquire value as statistics that go on to shape national AIDS policy. Her approach illustrates how on-the-ground dynamics and research cultures mediate the production of global health statistics in ways that impact local economies and formulations of power and expertise.
New evidence this year corroborates the rise in world hunger observed in this report last year, sending a warning that more action is needed if we aspire to end world hunger and malnutrition in all its forms by 2030. Updated estimates show the number of people who suffer from hunger has been growing over the past three years, returning to prevailing levels from almost a decade ago. Although progress continues to be made in reducing child stunting, over 22 percent of children under five years of age are still affected. Other forms of malnutrition are also growing: adult obesity continues to increase in countries irrespective of their income levels, and many countries are coping with multiple forms of malnutrition at the same time – overweight and obesity, as well as anaemia in women, and child stunting and wasting.
This first report deals with some of the major development issues confronting the developing countries and explores the relationship of the major trends in the international economy to them. It is designed to help clarify some of the linkages between the international economy and domestic strategies in the developing countries against the background of growing interdependence and increasing complexity in the world economy. It assesses the prospects for progress in accelerating growth and alleviating poverty, and identifies some of the major policy issues which will affect these prospects.
Poverty and Shared Prosperity 2016 is the first of an annual flagship report that will inform a global audience comprising development practitioners, policy makers, researchers, advocates, and citizens in general with the latest and most accurate estimates on trends in global poverty and shared prosperity. This edition will also document trends in inequality and identify recent country experiences that have been successful in reducing inequalities, provide key lessons from those experiences, and synthesize the rigorous evidence on public policies that can shift inequality in a way that bolsters poverty reduction and shared prosperity in a sustainable manner. Specifically, the report will address the following questions: • What is the latest evidence on the levels and evolution of extreme poverty and shared prosperity? • Which countries and regions have been more successful in terms of progress toward the twin goals and which are lagging behind? • What does the global context of lower economic growth mean for achieving the twin goals? • How can inequality reduction contribute to achieving the twin goals? • What does the evidence show concerning global and between- and within-country inequality trends? • Which interventions and countries have used the most innovative approaches to achieving the twin goals through reductions in inequality? The report will make four main contributions. First, it will present the most recent numbers on poverty, shared prosperity, and inequality. Second, it will stress the importance of inequality reduction in ending poverty and boosting shared prosperity by 2030 in a context of weaker growth. Third, it will highlight the diversity of within-country inequality reduction experiences and will synthesize experiences of successful countries and policies, addressing the roots of inequality without compromising economic growth. In doing so, the report will shatter some myths and sharpen our knowledge of what works in reducing inequalities. Finally, it will also advocate for the need to expand and improve data collection—for example, data availability, comparability, and quality—and rigorous evidence on inequality impacts in order to deliver high-quality poverty and shared prosperity monitoring.
Poverty remains a pervasive and complex phenomenon in Sub-Saharan Africa. Part of the agenda in recent years to tackle poverty in Africa has been the launching of social safety nets programs. All countries have now deployed safety net interventions as part of their core development programs. The number of programs has skyrocketed since the mid-2000s though many programs remain limited in size. This shift in social policy reflects the progressive evolution in the understanding of the role that social safety nets can play in the fight against poverty and vulnerability, and more generally in the human capital and growth agenda. Evidence on their impacts on equity, resilience, and opportunity is growing, and makes a foundational case for investments in safety nets as a major component of national development plans. For this potential to be realized, however, safety net programs need to be significantly scaled-up. Such scaling up will involve a series of technical considerations to identify the parameters, tools, and processes that can deliver maximum benefits to the poor and vulnerable. However, in addition to technical considerations, and at least as importantly, this report argues that a series of decisive shifts need to occur in three other critical spheres: political, institutional, and fiscal. First, the political processes that shape the extent and nature of social policy need to be recognized, by stimulating political appetite for safety nets, choosing politically smart parameters, and harnessing the political impacts of safety nets to promote their sustainability. Second, the anchoring of safety net programs in institutional arrangements †“ related to the overarching policy framework for safety nets, the functions of policy and coordination, as well as program management and implementation †“ is particularly important as programs expand and are increasingly implemented through national channels. And third, in most countries, the level and predictability of resources devoted to the sector needs to increase for safety nets to reach the desired scale, through increased efficiency, increased volumes and new sources of financing, and greater ability to effectively respond to shocks. This report highlights the implications which political, institutional, and fiscal aspects have for the choice and design of programs. Fundamentally, it argues that these considerations are critical to ensure the successful scaling-up of social safety nets in Africa, and that ignoring them could lead to technically-sound, but practically impossible, choices and designs.
Human capital—the knowledge, skills, and health that people accumulate over their lives—is a central driver of sustainable growth, poverty reduction, and successful societies. More human capital is associated with higher earnings for people, higher income for countries, and stronger cohesion in societies. Much of the hard-won human capital gains in many economies over the past decade is at risk of being eroded by the COVID-19 (coronavirus) pandemic. Urgent action is needed to protect these advances, particularly among the poor and vulnerable. Designing the needed interventions, targeting them to achieve the highest effectiveness, and navigating difficult trade-offs make investing in better measurement of human capital now more important than ever. The Human Capital Index (HCI)—launched in 2018 as part of the Human Capital Project—is an international metric that benchmarks the key components of human capital across economies. The HCI is a global effort to accelerate progress toward a world where all children can achieve their full potential. Measuring the human capital that children born today can expect to attain by their 18th birthdays, the HCI highlights how current health and education outcomes shape the productivity of the next generation of workers and underscores the importance of government and societal investments in human capital. The Human Capital Index 2020 Update: Human Capital in the Time of COVID-19 presents the first update of the HCI, using health and education data available as of March 2020. It documents new evidence on trends, examples of successes, and analytical work on the utilization of human capital. The new data—collected before the global onset of COVID-19—can act as a baseline to track its effects on health and education outcomes. The report highlights how better measurement is essential for policy makers to design effective interventions and target support. In the immediate term, investments in better measurement and data use will guide pandemic containment strategies and support for those who are most affected. In the medium term, better curation and use of administrative, survey, and identification data can guide policy choices in an environment of limited fiscal space and competing priorities. In the longer term, the hope is that economies will be able to do more than simply recover lost ground. Ambitious, evidence-driven policy measures in health, education, and social protection can pave the way for today’s children to surpass the human capital achievements and quality of life of the generations that preceded them.
