Research and Dissemination
The lack of analytical capacity in many countries has created a vicious cycle of poor analysis undermining the demand for high-quality data. As a result, the quality and quantity of agricultural data have seldom matched their importance in policy-making. A key objective of the LSMS-ISA project is the timely and open dissemination of all research papers and publications produced under the project. Many of these current and future LSMS-ISA publications follow directly from the research priorities defined by the Global Strategy to Improve Agriculture and Rural Statistics endorsed by the United Nations Statistics Commission, with the ultimate goal of revitalizing the research agenda on agricultural statistics from household surveys.
Should African Rural Development Strategies Depend on Smallholder Farms? An Exploration of the Inverse Productivity Hypothesis
by Donald Larson, Keijiro Otsuka, Tomoya Matsumoto, and Talip Kilic
In Africa, most development strategies include efforts to improve the productivity of staple crops grown on smallholder farms. An underlying premise is that small farms are productive in the African context and that smallholders do not forgo economies of scale -- a premise supported by the often observed phenomenon that staple cereal yields decline as the scale of production increases. This paper explores a research design conundrum that encourages researchers who study the relationship between productivity and scale to use surveys with a narrow geographic reach, when policy would be better served with studies based on wide and heterogeneous settings. Using a model of endogenous technology choice, the authors explore the relationship between maize yields and scale using alternative data. Since rich descriptions of the decision environments that farmers face are needed to identify the applied technologies that generate the data, improvements in the location specificity of the data should reduce the likelihood of identification errors and biased estimates. However, the analysis finds that the inverse productivity hypothesis holds up well across a broad platform of data, despite obvious shortcomings with some components. It also finds surprising consistency in the estimated scale elasticities.
Livestock and Livelihoods in Rural Tanzania: A Descriptive Analysis of the 2009 National Panel Survey
by Katia Covarrubias, Longin Nsiima and Alberto Zezza
This report presents an analysis of rural livelihoods in Tanzania, with particular emphasis on the livestock sub-sector, smallholder farmers’ living standards, and issues with access to productive assets. The study is based on data from the Tanzania National Panel Survey (NPS) collected by the National Bureau of Statistics (NBS) from October 2008 to October 2009 as part of the first wave of a nationally representative living standards survey. The report utilizes the extensive information included in this dataset on income sources, productive activities, access to basic services, market participation, access to assets, and a host of other socioeconomic variables to put together a detailed picture of the role of livestock in rural livelihoods.
by Calogero Carletto, Sara Savastano, and Alberto Zezza
This paper revisits the role of land measurement error in the inverse farm size and productivity relationship. By making use of data from a nationally representative household survey from Uganda, in which self-reported land size information is complemented by plot measurements collected using Global Position System devices, the authors reject the hypothesis that the inverse relationship may just be a statistical artifact linked to problems with land measurement error. In particular, the paper explores: (i) the determinants of the bias in land measurement, (ii) how this bias varies systematically with plot size and landholding, and (iii) the extent to which land measurement error affects the relative advantage of smallholders implied by the inverse relationship. The findings indicate that using an improved measure of land size strengthens the evidence in support of the existence of the inverse relationship.
by Klaus Deininger, Calogero Carletto, Sara Savastano, and James Muwonge
Although good and timely information on agricultural production is critical for policy decisions, the quality of underlying data is often low, and improving data quality can result in high payoffs. This paper uses data from a production diary administered concurrently with a standard household survey in Uganda to analyze the nature and incidence of responses, the magnitude of differences in reported outcomes, and factors that systematically affect these. Despite limited central supervision, diaries elicited a strong response, complemented standard surveys in a number of respects, and were less affected by problems of respondent fatigue than expected. The diary-based estimates of output value consistently exceeded those from the recall-based production survey, in line with reported disposition. Implications for policy and practical administration of surveys are drawn out.
by Kathleen Beegle, Calogero Carletto, and Kristen Himelein
Due to survey logistics, agricultural data are usually collected by asking respondents to recall the details of events occurring during past agricultural seasons that took place a number of months prior to the interview. This gap can lead to recall bias in reported data on agricultural activities. The problem is further complicated when interviews are conducted over the course of several months, thus leading to recall of variable length. To test for such recall bias, the length of time between harvest and interview is examined for three African countries with respect to several common agricultural input and harvest measures. The analysis shows little evidence of recall bias impacting data quality. There is some indication that more salient events are less subject to recall decay. Overall, the results allay concerns about the quality of some types of agricultural data collected through recall over lengthy periods.
by Brian Dillon
The rapid spread of mobile telephony throughout the developing world offers researchers a new and exciting means of data collection. This paper describes and analyzes the experience of a research project that used mobile phones to collect high frequency, quantitative economic data from households in rural Tanzania. It discusses the research design, highlights mistakes made and lessons learned, and speculates on the applicability of this method in other settings.
May 7th, 2012
Download a presentation given by the LSMS-ISA team as part of the World Bank's Poverty Reduction and Economic Management (PREM) Network Learning Days 2012. The presentation provides an overview of the use of Computer-Assisted Personal Interviewing and its role in the LSMS-ISA project. It also describes the project's utilization of geo-referencing, as well as various upcoming methodological survey experiments in agriculture, including on land area measurement, soil fertility, and the production of continuous and/or extended harvest crops.
February 27th, 2012
Download a presentation given by the LSMS-ISA team at the World Bank. The presentation describes the main features of the project, discusses the progress of the project to date, reviews challenges that are currently facing the project, and outlines next steps as the project continues to move forward in supporting high quality household and agricultural data in each of its partner countries.
April 26th, 2011
Download a presentation given by the LSMS-ISA team as part of the discussion on Innovations in Survey Design for Policy. The presentation was given during a weeklong learning session presented by the Poverty Reduction and Economic Management (PREM) Network of the World Bank. It introduces the LSMS-ISA project, discusses main features and challenges, and presents examples of methodological validation exercises being conducted under the project.
November 30th, 2010
Download a presentation given by the LSMS-ISA team at the African Economic Research Consortium held in Mombasa, Kenya. The presentation defines the motivation behind the LSMS-ISA project, outlines preliminary findings, and discusses possible new directions for the project moving forward.