Feldman 1992, Bargh 2006). Impacts from priming can help keep a mental idea (temporarily) within reach (Hopkins 2011). If framing affects how people internalize their response to various experiences, this is also relevant as a potential policy tool for designing interventions.

In social pyschology and other fields, research has linked priming to attitudes, perception, and preferences, as well as to measurement error and reporting (particularly of sensitive data) (Epley and Gilovich 2001, Rasinski, Visser et al. 2005, Bargh 2006, Steele and Ambady 2006, Mazar, Amir et al. 2008, Van de Walle and Van Ryzin 2011). Priming has also shown impacts on political opinions and candidate preferences, and has been used as a tool in media, speeches, and elsewhere (Druckman and Holmes 2004, Althaus and Kim 2006, Cassino and Erisen 2010, Hopkins 2011, Naoi and Kume 2011).

In an early lab experiment, Lerner and Keltner (2001) concluded that fearful recollections lead to an increase in risk-averse behavior and angry recollections to an increase in risk-seeking behavior. In our setting, one can imagine that recall of conflict could lead to either fear or anger, depending on the individual and the context. Meanwhile, Miranda and Persons (1988) suggest that cognitive vulnerability to depression can be triggered by experimental priming. Most studies report that prior experience modulates this connection, with depressed individuals being more influenced by negative primes (Scher, Ingram et al. 2005). However, the evidence is equivocal (Brockmeyer et al. 2012; LeMoult et al. 2012) and, thus requires further testing.

# 3. Data and research design

In 2015 and 2016, the Nigerian Bureau of Statistics, with the support of the World Bank Living Standards Measurement Study (LSMS) team, conducted the third wave of the General Household Survey Panel (GHS-Panel) with over 4,500 nationally-representative households. Data were collected on consumption, behavioral preferences, depressive symptoms, history of conflicts (5 years), deaths of family members (2 years), and economic shocks (2 years), among others. We analyze data for the 4,579 households for which we have complete data sets of consumption expenditures,<sup>6</sup> depression scores, economic activities, educational investment and other variables. Our primary unit of analysis is individuals who responded to the included module on depression (only one individual per household).

Table 1 presents the summary statistics of each variable. Seventy-four percent of respondents to the depression module are household heads (with 21 percent of all households being femaleheaded). Thirty-seven percent of respondents are female, with the average age of the respondents being slightly over 50<sup>7</sup> and the average household size being between five and six. About 74 percent of respondents are married, of which 57 percent are monogamously married, and 17 percent are polygamously married. Some 43 percent are Muslim, while the rest are Christian (with 2 percent having unknown or no religion). On average, 41 percent of the sample lives in an urban

> 6 The methodology implemented when calculating consumption expenditures is included in the survey documentation, available on the World Bank’s Micro Data Catalogue.

> 7 Note that six of the respondents are under the age of 15. In addition, the average age of the household head is 53.

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