## _Productivity-enhancing technology in rural areas_

On economic mobility, another important area for future work is developing individual-level questions on use of technologies, including frequency and purpose of use, that can help expand economic opportunities and access to markets. Mobile phones, for example, can reduce costs of business and farm-related transactions, provide information on market prices and job opportunities, broaden personal and business networks, and ease access to financial services, including mobile money accounts that allow women better control over their income (Demirgüç-Kunt et al, 2017). Among the LSMS, the 2016-17 Malawi and 2013-14 Uganda LSMS-ISA ask about individual ownership of a mobile phone (in the household roster for Malawi and the module on asset ownership for Uganda), but not questions about how they use their phones that can improve policy design; only the 2015-16 Ethiopia LSMS-ISA asks about individual mobile money accounts in the module on savings. The link between mobile phone use and agriculture is also missing. The 2017 Global Findex provides guidance on use-related questions that can be policy-relevant (for example, how individuals have used their mobile phones in financial transactions, whether these transactions are for agriculture, and with what frequency).

Another important issue within rural areas is the use of improved agricultural technology and inputs. Recent LSMS-ISA agriculture modules ask about the use of improved seeds and other inputs at the plot level, that could be compared across men and women plot owners/managers (along with jointly managed/owned plots), and linked to indicators of production and income. However, because women also make up a much smaller share of independent farmers, and are often not equally targeted by agricultural extension and technology initiatives, simply looking at use of improved technologies without understanding who is left out — and why — can skew an understanding of demand for technology. Direct questions on reasons for/against adoption that have been documented in more focused country-level studies are lacking in broader socioeconomic surveys, including skills/knowledge (Udry, 2018); information networks (Munshi, 2004; Moser and Barrett, 2006); other economic activities farmers may be involved in (Ibrahim, 2013); credit and other liquidity constraints (de Janvry et al, 2016); and other factors such as individuals’ desire to minimize volatility in expected profits (Zhu, 2019).

# Constraints to economic opportunity

Along with data on migration, access to skills and technology, socioeconomic surveys need to better capture constraints that rural individuals often face in seeking these economic opportunities. Some surveys have introduced questions on whether women need permission to leave the house for work (as in the DHS), as well as safety and commuting time to work; these are important for understanding mobility constraints for wage workers, but are less relevant for home-based workers or farmers.

Asking about a wider range of constraints in surveys is also in line with Kabeer (2012), who presents a research agenda on specific barriers and alleviating factors to women’s economic mobility. Survey questions in this area would essentially be qualitative/subjective in nature, but if asked carefully (and honed through cognitive testing to account for language and local context) could be helpful in understanding where policy might be more effectively targeted. Respondents could choose from multiple options affecting their economic mobility, including (a) time/distance to work, as well as markets and other institutions (financial, administrative, etc.); (b) social and work-related norms affecting the ability to work, work longer hours, and/or advance in one’s position — including discrimination in hiring and advancement, and the risk of harassment; (c) unpaid work burdens at home affecting available time, including childcare; and (d) lack of skills in that field (specifying which skills are needed). For self-employed individuals, additional response categories could include (a) access to inputs/technology (across both farm and off19