Agricultural development and policy design rely on careful analysis of the factors that influence the welfare and decision making of agricultural households. This dissertation leverages diverse data types, cross-disciplinary knowledge, and applied econometrics to assess the underlying factors that influence child welfare and agricultural production decisions. In doing so, it reveals the role of observed and unobserved differences in shaping our understanding of decision making in agricultural production systems.The first chapter evaluates the impacts of in utero rainfall on child growth in rural Rwanda and assesses whether estimates based on aggregate in utero rainfall are attenuated by intra-seasonal in utero rainfall effects. The in utero period of a child's life is critical for his or her development. For families relying on rain-fed agricultural production, such development can be severely impacted by the timing of rainfall shocks. Yet, evidence of in utero rainfall effects has been mixed. My results suggest that this mixed evidence may be driven by a focus on aggregate rainfall measures, which ignore cropping period specific heterogeneity in rainfall effects on human health.The second chapter assesses the separability hypothesis which posits that agricultural households make their production decisions separately from their consumption decisions. This theory relates closely to the completeness of markets and provides an important avenue for understanding how agricultural households are likely to respond to new policies and programs. The current standard identification strategy for testing whether this separability hypothesis holds is to estimate reduced form regressions of household labor demand on household demographic characteristics, using household fixed effects to address unobserved heterogeneity. Using plot panel data from Rwanda, I apply an alternative test that controls for unobserved heterogeneity in land quality. Using simulations, I then show that the standard approach based on household fixed effects is prone to omitted variable bias from the endogeneity of household demographic characteristics with unobserved land characteristics. Simulations indicate that this bias is exacerbated as the land market becomes more active.The third chapter examines the role of farmer personality in the effectiveness of a community-based extension program for promoting improved bean varieties in Tanzania. I develop a conceptual framework which shows that the information gained from community-based extension activities may be heterogeneous by farmer personality. I then examine this potential heterogeneity empirically using a unique dataset of the Big Six personality traits measured using the Midlife Development Inventory (MIDI). My findings suggest that personality characteristics influenced which farmers benefited from the extension program. In particular, more extraverted farmers appear to have benefited more from residing in villages that received trial packs of improved bean seed relative to less extraverted farmers. This is consistent with their increased sociability and has implications for the types of farmers likely to gain from community-based extension programs.
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