the literature on rational inattention started by Sims (2003), which assumes that people allocate their attention optimally across different pieces of information, incorporating the costs associated with acquiring and processing information (for recent surveys of the rational inattention literature, see Handel and Schwartzstein, 2018; Mackowiak et al., 2018). It should be noted, however, that the central predictions of our model (i.e., those that we test empirically) arise independently of the assumed structure of information processing and could therefore also be generated by a simpler model with costly mental effort or time needed to obtain and process information, not based on entropy reduction.<sup>7</sup> Nevertheless, using a rational inattention approach to model farmers’ demand for advice offers several advantages. First, in the rational inattention literature agents are allowed to choose not only the precision of the signals (i.e., the allocated amount of attention), but also the distribution from which signals are drawn. The structure of information is therefore endogenously determined in these models rather than exogenously imposed, which reduces the number of required assumptions. Second, the rational inattention literature makes use of concepts from the field of information theory (most importantly entropy) which are well-understood and for which a wide range of mathematical tools are readily available. Finally, there is a growing body of empirical evidence providing support for the rational inattention approach (Gabaix et al., 2006; Caplin and Dean, 2013; Goecke et al., 2013; Bartoˇs et al., 2016; Ambuehl et al., 2018).<sup>8</sup> Until now, applications of rational inattention have focused primarily on rich countries. By using the same approach to model farmers’ demand for agricultural advice and extension services, this paper extends the analysis based on rational inattention to the development context.<sup>9</sup> The literature provides several reasons why constraints on information processing may be particularly relevant in the context of less-developed economies. First, people in the developing world (and poor farmers in particular) tend to have less access to information in pre-processed forms than people in richer countries, e.g., because of limited access to media and tools such as online search engines. Second, the poor are often unable to benefit from distraction-saving goods and services, such as stable electric-

> 7Note that what is termed “attention” in the literature (and in our model) usually comprises both cognitive effort and time use more generally, since both are needed for processing information. As pointed out by Banerjee and Mullainathan (2008), the relevant aspect of time use in this context should be thought of as the “quality of time (i.e., mental focus)” rather than the “quantity of time” (p. 493).

> 8For a more detailed overview of different approaches to attention used in economics, including a comprehensive discussion of the assumptions underlying the rational inattention approach, see Handel and Schwartzstein (2018).

> 9Applications of rational inattention initially focused on macroeconomic contexts such as monetary transmission (Mankiw and Reis, 2002; Ma ́ckowiak and Wiederholt, 2009), consumption dynamics (Luo, 2008; Tutino, 2013), and business cycles (Ma ́ckowiak and Wiederholt, 2015). Further studies apply rational inattention in the areas of finance (Van Nieuwerburgh and Veldkamp, 2010; Kacperczyk et al., 2016), industrial organization (Sallee, 2014; Martin, 2017), and labor (Bartoˇs et al., 2016; Acharya and Wee, 2020). In the development context, some existing studies investigate the role of other (i.e., not entropy-based) forms of attention (Banerjee and Mullainathan, 2008; Beaman et al., 2014; Hanna et al., 2014).

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