# **2. Measuring farm labor**

# **2.1. Overview**

Measuring labor in smallholder farming is inherently complex and prone to measurement error.<sup>2</sup> Like informal household enterprises in other sectors, smallholder farmers rarely keep any records, so that respondents need to rely on recall strategies to report on labor and other inputs. The seasonality and irregularity of smallholder agriculture pose additional challenges, especially if the objective is to obtain measures of labor for the entire season.

Current practices on how to collect data on farm labor, that is the labor provided by family members on their own farm (excluding hired labor), differs widely across surveys. Agricultural surveys, such as those conducted under the World Bank’s Living Standards Measurement Study – Integrated Surveys on Agriculture (LSMS-ISA) initiative, typically collect data on farm labor in a dedicated agricultural module.<sup>3</sup> However, these modules differ with respect to the unit of data collection, recall period, sequencing of questions, selection of respondent(s), etc. The following paragraphs elaborate on the first two of these issues, that is the unit of data collection and the recall period, which are important features for the analysis in this paper.

# **2.2. Unit of data collection**

Most (though not all) agricultural surveys use the plot as the main unit of data collection (FAO 2017). This reflects long-standing guidance for the design and implementation of household surveys in developing countries. Reardon and Glewwe (2000) recommend that in countries with ‘hard-to-survey’ agriculture, which includes most smallholder farming in Sub-Saharan Africa, data on farm inputs and practices is preferably collected at the plot-level (as opposed to the farm- or household-level). This is because a single farm may consist of multiple plots – cultivated under different production systems – and farmers tend to refer to each plot as they describe agricultural production activities. In such a situation, plot-level data collection reflects the natural flow of conversation between the interviewer and the farmer. In addition, collecting data at the plot level yields more observations than collecting data at the household-level, enables the analyst to control for land quality, and facilitates the analysis of agricultural productivity (as the plot can be used to link crops to inputs) and intra-household differences (e.g. productivity gaps between maleand female-managed plots).

For data on farm labor, recommended practice is to collect such data either in terms of aggregate persondays per plot, or to ask, specifically, about each household member’s labor input on each plot (Reardon and Glewwe 2000). The former approach is used in the 2009 Ghana Socio-Economic Panel Survey, which asks, separately for men, women and children, about the number of days, average hours per day and average

> 2 This section draws on Arthi et al (2018).

> 3 Multi-topic household surveys typically also administer a general labor module, which gathers information on different types of employment and work (e.g. farm work, non-farm household enterprise work, wage work, etc.) for each household member. These person-level measures of farm labor typically refer to the past 7 days and cannot easily be extrapolated to the entire agricultural season.

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