How Much Should We Trust Micro-data? A Comparison of the Socio-demographic Profile of Malawian Households Using Census, LSMS and DHS data

Tasciotti, Luca; Wagner, Natascha

doi:10.1057/s41287-017-0083-6

Cited by 6 publications

(5 citation statements)

References 42 publications

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“…One caveat to this study is that it relies on self-reported income data, which is somewhat noisy. This is a recognized feature of data collected under large household surveys with comprehensive modules, such as the LSMS-ISA (Fraval et al, 2019; Tasciotti and Wagner, 2018; Wollburg et al, 2021). As described earlier, we addressed outliers through winsoring at the top and bottom 5%.…”

Section: Discussionmentioning

confidence: 99%

“…We recognise the uncertainties and inaccuracies associated with data collected from household surveys (Fraval et al, 2019; Tasciotti and Wagner, 2018; Wollburg et al, 2021). Nevertheless, the World Bank's LSMS is regarded as the de facto standard public database for analysis at the household level (https://www.worldbank.org/en/programs/lsms/initiatives/lsms-ISA#7).…”

Section: Methods and Datamentioning

confidence: 99%

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Land and technology requirements for economically prosperous smallholder farming in sub-Saharan Africa: Evidence from Tanzania

Harris,

Mausch,

Chamberlin

2024

Outlook Agric

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Making a living from a small farm is difficult in sub-Saharan Africa. In this paper, we quantify how difficult, using a simple, robust, relation between per capita daily income from farming (FPDI), land per capita and whole-farm net profitability per hectare. This relation allows the calculation of the land area required to generate various levels of household income as a function of farm performance. We use nationally representative household data for Tanzania to investigate the range of whole-farm profitability and to estimate an upper limit for it. For 6818 cases where households with land reported figures for gross crop and livestock revenues and for costs in any of the three years 2009, 2011 or 2013, actual median whole-farm net profitability was only $454/ha/y even without including the opportunity cost of family labour. When those were considered, median net profitability was negative $238/ha/y, i.e. a net loss. The maximum whole-farm profitability achieved was $4485/ha/y without family labour costs and $2742/ha/y with it. We evaluated actual and potential farm performance for their ability to generate a range of values of FPDI up to $10 per person per day. Most farms are not very profitable, particularly when household labour costs are considered, and few would be considered economically prosperous. Our analysis underscores the fact that improving their operations or adopting new technologies alone is unlikely to lift many smallholder farmers out of poverty in developing countries, given typical farm size distributions and reasonable assumptions about the realized economic returns to adoption of currently available agricultural technologies. While continued agricultural R&D investments are certainly worthwhile, such efforts alone will be insufficient to meaningfully address welfare needs of the world's rural poor. This suggests that agricultural development programs should expand their attention to incorporate off-farm and non-farm components of the rural economy.

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Section: Discussionmentioning

confidence: 99%

Section: Methods and Datamentioning

confidence: 99%

Land and technology requirements for economically prosperous smallholder farming in sub-Saharan Africa: Evidence from Tanzania

Harris,

Mausch,

Chamberlin

2024

Outlook Agric

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“…The PDHS conducted four times in 1990-91, 2006-07, 2012 and 2017-18, have been deployed for our analysis. Particular importance -in the context of the four surveyshas been given to the collection of data on fertility levels [Tasciotti and Wagner (2018)]. The sample design adopted across waves is a stratified, clustered and systematic sample of households.…”

Section: Datamentioning

confidence: 99%

Fertility, electricity and television: is there a link? Evidence from Pakistan, 1990–2018

2022

Self Cite

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In 1960s Pakistan, every woman was giving birth to more than 6 children on average. In 2021, Pakistan still has the second-highest fertility rate in South Asia with every woman giving birth to 3.4 children on average. This paper uses four waves of Demographic and Health Survey data to empirically analyze trends in fertility in Pakistan between 1990 and 2018; accounting for wealth, education and locational differences, this paper looks at three additional pathways for reducing fertility: (i) electrification, (ii) access to TV and (iii) family planning commercials broadcast on television. Results show that electricity does not reduce fertility whereas access to television has a significant effect in reducing fertility rates. The content and evolution of Pakistani soap-operas are also discussed, and it is argued that the role models, the types of households and the messages conveyed by these soap-operas may represent strong pathways for the fertility decline.

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“…This increasing use and importance of data to inform policy decisions requires that the data underlying those decisions is of high quality. Data quality is thus the focus of much attention within the field of development economics (Jerven, ; Jerven & Johnston, ; Tasciotti & Wagner, ). Generally, however, there has been relatively little research examining the quality of data and the methods used to collect it.…”

Section: Introductionmentioning

confidence: 99%

Using paradata to collect better survey data: Evidence from a household survey in Tanzania

Choumert‐Nkolo

Cust

Taylor

2019

Review Development Economics

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Data are a key component in the design, implementation, and evaluation of economic and social policies. Monitoring data quality is an essential part of any serious, large‐scale data collection process. The purpose of this article is to show how paradata should be used before, during, and after data collection to monitor and improve data quality. To do this we use timestamps, global positioning system (GPS) coordinates, and other paradata collected from an 800‐household survey conducted in Tanzania in 2016. We demonstrate how key paradata can be used during each phase of a research project to identify and prevent issues in the data and the methods used to collect it. Our results corroborate the importance of collecting and analyzing paradata to monitor fieldwork and ensuring data quality for micro data collection in developing countries. Based on these findings we also make recommendations as to how researchers can make better use of paradata in the future to manage and improve data quality. We argue for an expansion in the understanding and use of varied paradata among researchers, and a greater focus on its use for improving data quality.

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How Much Should We Trust Micro-data? A Comparison of the Socio-demographic Profile of Malawian Households Using Census, LSMS and DHS data

Abstract: This paper assesses the empirical representativeness of micro-data by comparing the

Cited by 6 publications

References 42 publications

Land and technology requirements for economically prosperous smallholder farming in sub-Saharan Africa: Evidence from Tanzania

Land and technology requirements for economically prosperous smallholder farming in sub-Saharan Africa: Evidence from Tanzania

Fertility, electricity and television: is there a link? Evidence from Pakistan, 1990–2018

Using paradata to collect better survey data: Evidence from a household survey in Tanzania

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