As such, overall coverage of regular social assistance could be broadened to help households cope with seasonality. More specifically, while much emphasis is currently placed on responding to unpredictable shocks, seasonal food insecurity could be better tackled by providing regular transfers _early_ in the lean season, when prices are lower and fewer households have fallen into extreme deprivation. Seasonal variation happens every year and more can be done to support Sahelian households if we know it will perennially threaten their wellbeing.

The paper echoes many existing studies that show how household welfare depends directly on shocks and seasonality. As Dercon’s (2002) review demonstrates, consumption responds to seasonal variation in or shocks to household income in a wide range of low- and middle-income countries. These swings in income and consumption often leave households at risk of falling into poverty (Dercon & Krishnan, 2000). The paper also builds on a large literature that describes at least five reasons why households’ ability to manage and cope with shocks and seasonality better differs. First, households with more diversified livelihoods, or incomes that depend less on agriculture, may be less exposed to the effects of seasonality (Alderman & Paxson, 1994; Barrett, Reardon, & Webb, 2001; Harrower & Hoddinott, 2005; Kaminski, Christiaensen, & Gilbert, 2016). Second, households may try to borrow in seasons when incomes or access to food are reduced, but such strategies will be more tenable for those with better access to formal or informal financial markets (Pitt & Khandker, 2002; Khandker, 2012). Third, households can save, store output, or accumulate assets during surplus seasons which can then be sold or consumed when needed, although often households are reluctant to sell their livestock during difficult times if they can stay above some subsistence level of consumption (Hoogeveen, 2003; Fafchamps & Lund, 2003; Kazianga & Udry, 2006). Fourth, certain households may have access to informal insurance whereby communities pool risks and provide support to those in need, although such insurance mechanisms tend to be most relevant to idiosyncratic shocks rather than covariate shocks or seasonal variation (Mace, 1991; Townsend, 1994; Ravallion & Chaudhuri, 1997). Fifth, government policy – and, in particular, access to social protection – influences the base level of income to which households have access: such social protection may be adapted to respond explicitly to shocks and seasonality (Bodewig, 2019).

The rest of this paper is organized as follows. Section 2 describes the data and methodology. Section 3 presents some descriptive statistics, showing the limitations on strategies for coping with and managing seasonality in the Sahel. Section 4 presents the main results, comparing key markers of welfare between the lean and non-lean season. Section 5 describes heterogeneity in the main results, including comparing rural and urban areas. Section 6 concludes and describes the policy implications.

# Section 2. Data and methodology

The main data source used in this paper is the ‘ _Enquête harmonisée sur les conditions de vie des ménages_ ’ (EHCVM), which captures detailed household-level microdata from Burkina Faso, Mali, Niger, Senegal, and Chad. The EHCVM includes a wide range of socioeconomic indicators, including consumption, employment and agricultural activities, food security, assets, education, and health. The EHCVM data are representative at the national and regional levels for each of the five countries.

The timing of the EHCVM makes it possible to assess the impact of seasonality in four of the five Sahelian countries surveyed as the data were collected in two distinct waves during the same agricultural year; the first wave corresponding to the harvest period and the second one to the lean season. The waves collected information on different households, so the EHCVM data do not have a panel structure. However, the 4