Ponzini G, Baryahirwa S, Brunelli C, Ilukor J, Kilic T, Mugabe S, Mupere A, Okello P, Oumo F, and Ssennono V.
Bako D, D’Orazio M, Missiroli S, Ssennono VF, Brunelli C, Kilic T, Ponzini G, and Bolliger F.
Winters P, Hogue E, Steiner M, Keramati C, Rokhideh M, and Eissler S.
Brunelli C, and Gourlay S.
Villarino MEJ, Buenaseda-Tejada MG, and Patterson SE.
Rühl D, Tiberti M, Mendez-Gomez-Humaran I, and Cachia F.
Bolliger F, Bako D, Brunelli C, Georgieva N, Koudelka K, Missiroli S, and Pare L.
Zezza A, Gourlay S, and Molini V.
This Technical Note for Country Teams provides guidance to survey practitioners using non-standard units (NSUs) of measurement for the collection of production (harvest) quantities in 50x2030 surveys and beyond.
This Technical Note for Country Teams provides guidance to survey practitioners for the collection of on-farm harvest and post-harvest losses data in household and farm surveys.
An overview of the 50x2030 Initiative's objectives, organization, and survey systems. Includes a description of each of the Initiative’s components, with the bulk of the discussion on Data Production.
An in-depth look at the questionnaires that have been developed under the 50x2030 Initiative. Explains the differences between the two survey systems offered and how the questionnaire instruments fit together.
A technical note on how 50x2030 survey tools satisfy the data requirements of SDG Indicator 5.a.1, which measures gender parity in ownership and tenure rights over agricultural land. The paper provides guidance on calculating the Indicator and advises on the potential for detailed analysis beyond the Indicator.
A presentation of the Initiative’s approach to increase data use among a variety of stakeholders. Activities prioritize improving capacities, data policies and practices, and communication between data producers, intermediaries, and decision-makers.
A detailed look at the key technical features of a suitable sample design for the survey programs proposed by the 50x2030 Initiative.
Summary of 50x2030 FY22 activities and a closer look at the work done in each participating country to strengthen evidence-based policy development.
Summary of the 2-4 November 50x2030 Soil Sessions meetings which gathered experts to prioritize research areas on soil health monitoring and innovative technologies that can transform the way soil data is collected in agricultural surveys.
This document outlines the activities planned under the 50x2030 Initiative between 1 July 2021 and 30 June 2022.
Report covering the activities implemented and results achieved under the Initiative between 1 July 2020 and 30 June 2021.
This document outlines the activities planned under the 50x2030 Initiative between 1 July 2020 and 30 June 2021.
Report covering the activities implemented and results achieved under the Initiative between 1 July 2019 and 30 June 2020.
A conceptual overview of the Initiative's results framework, capturing inputs, outputs, outcomes and impact.
Adoption of non-labor agricultural inputs remains low among small-scale farmers in many low-income countries, yet accurate measurement of the quality of these inputs and quantities used is essential for assessing economic returns, understanding the drivers of agricultural productivity, and proposing and evaluating policies for increasing agricultural production. This paper determines that while accurate documentation of measured and perceived agricultural input quality is important, the marginal productivity effects of input use hinge on the timing and method of application and on a host of complementary inputs.
This paper uses data from a methodological experiment in Armenia to assess the implications of survey design on the measurement of individual land rights and SDG indicator monitoring. The findings suggest that in the context of Armenia, the measurement of SDG 5.a.1 and 1.4.2 (a) is robust to respondent approach and data disaggregation level, driven largely by the high rates of documentation. Meanwhile, land rights that are less objective, such as the right to bequeath and perception of tenure security, are sensitive to these survey design choices.
The COVID-19 pandemic disrupted survey and data systems globally and especially in low- and middle-income countries. Lockdowns necessitated remote data collection, and phone surveys were implemented at a national scale in many places that previously had limited experience with them. As in-person data collection resumes, the experience gained provides the grounds to reflect on how phone surveys may be incorporated into survey and data systems. Ultimately, the integration of phone interviews with in-person data collection offers a promising opportunity to leverage the benefits of phone surveys while addressing their limitations for agricultural and rural populations in low- and middle-income countries.
Agricultural productivity is hindered in smallholder farming systems due to several factors, including farmers’ inability to meet crop-specific soil requirements. This paper focuses on soil suitability for maize production and creates multidimensional soil suitability profiles of smallholder maize plots in Uganda, while quantifying forgone production due to cultivation on less-than-suitable land and identifying groups of farmers that are disproportionately impacted.
Adoption of non-labor agricultural inputs, including pesticides and mineral fertilizers, remains low among small-scale farmers in many low-income countries. Accurate measurement of the quality of these inputs and of quantities deployed is essential for assessing economic returns, understanding the drivers of agricultural productivity, and proposing and evaluating policies for increasing agricultural production. This paper reviews the evidence regarding the quality of mineral fertilizer and pesticides, inclusive of herbicides, available in local markets in Sub-Saharan Africa.
This paper exploits plot-level panel data for almost 20,000 plots on 8,000 farms in three Sub-Saharan African countries with information on harvest, input use, and different proxies of losses; household and community-level data; as well data from other sources such as crop cutting and survey experiments, to provide new insights into the reliability of survey-based crop loss estimates and their attribution to disasters.
This paper reports on a randomized experiment conducted among Malawian agricultural households to study nonclassical measurement error in self-reported plot area and farmers’ responses to new information that was provided to correct nonclassical measurement.
This working paper leverages unique survey data from Mali to demonstrate that self-reported crop yields, vis-a-vis (objective) crop cut yields, are subject to non-classical measurement error that biases the estimated returns to inputs, including land, labor, fertilizer, and seeds.
Information on minimum losses can help provide a benchmark for farm management, formulation of policies and investment decisions. This study connects this information to farming practices and production technologies, which can also help assess the effectiveness of loss reduction practices and the underlying policies and incentives that promote them.
This paper provides recommendations on how large-scale household surveys should be conducted to generate data needed to train models for satellite-based crop type mapping in smallholder farming systems.
This paper assesses the relationship between the length of recall and nonrandom error in agricultural survey data using data from the World Bank’s Living Standards Measurement Study–Integrated Surveys on Agriculture in Malawi and Tanzania.
