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Key Takeaways
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A survey of poverty indicators surfaced 139 candidates, of which 36 were ultimately selected for inclusion in the study based on indicator construction, use, and timeliness.
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The selected 36 poverty indicators relied primarily on 26 data sources, mainly household surveys and administrative government data.
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Most indicators relied on household survey data and used multidimensional indices to comprehensively measure poverty, aside from poverty line and poverty gap measures which relied exclusively on income and consumption.
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Indicators or indicator components were typically based on quantitative estimates of income or consumption, although an increasing number of measurements are instead classifying households according to deprivation of assets, food, or access to services and basic infrastructure.
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Overall, critics find that an emphasis on poverty line measurements has led to an incomplete understanding of poverty’s prevalence and trends over the last several decades (UN Special Rapporteur, 2020).
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No single indicator dominates on considerations of reliability, dimensions, depth or intensity, comparability, etc., but rather each measure involves tradeoffs.
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If the goal is to increase the utility of commonly used indicators, including those considering multiple dimensions of poverty, then investments focused on expanding the coverage, frequency, or scope of nationally representative household surveys is a necessary first step.
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Making cross-country comparisons using any poverty indicator runs the risk of using a common metric based on different data sources and collected in different years that may not fully reflect a household’s welfare. Indices which include multiple subcomponents may be more holistic, but even less reliable as the number of components requiring data increases.
Suggested citation:
Landscape Review of Poverty Measures. EPAR Technical Report #424 (2022). Evans School of Public Policy & Governance, University of Washington. Retrieved <Day Month Year> from https://epar.evans.uw.edu/research
This brief explores how two datasets – The Tanzania National Panel Survey (TZNPS) and the TNS-Research International Farmer Focus (FF) – predict the determinants of inorganic fertilizer use among smallholder farmers in Tanzania by using regression analysis. The (TZNPS) was implemented by the Tanzania National Bureau of Statistics, with support from the World Bank Living Standards Measurement Study – Integrated Surveys on Agriculture (LSMS-ISA) team and includes extensive information on crop productivity and input use. The FF survey was funded by the Bill and Melinda Gates Foundation and implemented by TNS Research International and focuses on the on the behaviors and attitudes of smallholder farmers in Tanzania. The two datasets produce relatively comparable results for the primary predictors of inorganic fertilizer use: agricultural extension and whether or not a household grows cash crops. However, other factors influencing input use produce results that vary in magnitude and direction of the effect across the two datasets. Distinct survey instrument designs make it difficult to test the robustness of the models on input use other than inorganic fertilizer. This brief uses data inorganic fertilizer use, rather than adoption per se. The TZNPS did not ask households how recently they began using a certain product and although the FF survey asked respondents how many new inputs were tried in the past four planting seasons, they did not ask specifically about inorganic fertilizer.
This report investigates the potential environmental and socio-economic benefits and costs of glyphosate resistant cassava. Glyphosate resistant crops (also referred to as glyphosate tolerant) have been rapidly adopted by a number of crop producers because they simplify and/or reduce the cost of weed management. Glyphosate resistant crops also provide external environmental benefits by promoting reduced tillage agriculture, decreasing erosion and increasing soil health. However, glyphosate resistant crops also have some environmental costs, potentially leading to increased use of herbicides and environmental contamination. Because transgenic glyphosate resistant cassava is not currently in use, literature on its potential environmental and socioeconomic costs and benefits is limited. Therefore, this report draws on the literature for glyphosate resistant crops that are in current use, including maize, soybeans, sugar beets and canola (rapeseed). We find that socioeconomic and environmental impacts of glyphosate resistant crops differ by crop-type, agroecological conditions, production systems and local regulatory structure. Therefore, some benefits and costs associated with other glyphosate resistant crops may not be applicable to glyphosate resistant cassava.
This brief provides an overview of the national and zonal characteristics of agricultural production in Tanzania using the 2008/2009 wave of the Tanzania National Panel Survey (TZNPS), part of the Living Standards Measurement Study – Integrated Surveys on Agriculture (LSMS-ISA). More detailed information and analysis is available in the separate EPAR Tanzania LSMS-ISA Reference Report, Sections A-G.
This brief presents a comparative analysis of men and women and of male- and female-headed households in Tanzania using data from the 2008/2009 wave of the Tanzania National Panel Survey (TZNPS), part of the Living Standards Measurement Study – Integrated Surveys on Agriculture (LSMS-ISA). We compare farm activity, productivity, input use, and sales as well as labor allocations by gender of the respondent and of the household head. In households designated “female-headed” a woman was the decision maker in the household, took part in the economy, control and welfare of the household, and was recognized by others in the household as the head. For questions regarding household labor (both non-farm and farm), the gender of the individual laborer is recorded, and we use this to illustrate the responsibilities of male and female household members. An appendix provides the details for our analyses.