“Present” – A Universal Bias
The concept of present bias is a foundational–and extensively studied–concept within behavioral economics. Simply put, it describes the tendency for economic actors (i.e. people!) to place a higher value on the present as compared to the future. It is widespread to the point of anecdote–most everyone has at some point (irrationally) foregone higher future utility in favor of a lesser (but temporally closer) temptation. This bias is universal enough as to label it “human nature” and, in fact, it has been empirically proven to occur in a wide variety of geographic and socioeconomic settings (Can and Erdem, 2013).
Present bias’s near-universal human presence is not disputed but, given its powerful distorting power over economic rationality and self-interest, its variation and magnitude across societies deserves greater in-depth study. Despite empirical proof of the correlation of poverty and spending on temptation goods (Banerjee and Duflo, 2007); low investment despite high returns (De Mel et al., 2008); and serial use of high-interest loans (Annath et al., 2007), stereotypes of poor people’s “impatience” relative to the richer people and, thus, a degree of unworthiness of aid persist. More useful research on the heterogeneity of present bias (specifically between the “developed” and the “developing” world) can better inform policymakers how to best address this aid- and intervention-hampering behavioral bias.
The microeconomic phenomenon of the poverty trap is extensively documented and studied. (Banerjee, et al. 2012) More recently, behavioral insights have deepened the understanding of economic actions involved in the trap–adding heaps of complexities, but also clarifications–to the standard homoeconomicus model. Theory-backed development policy prescriptions attempt to export the perfection of academic theory (full rationality; drive and ability to optimize; presence of full information and perfect willpower) to such matters as the distribution of developmental aid. Under such model-perfect assumptions, the pinnacle of policy prescriptions boils down to unconditional cash transfers. But, as anyone who has progressed beyond Economics 101 or taken the time to critically assess his/her real world, daily economic behavior can attest, model assumptions do not match real life. And, to the extent that the disparity between rational economic behavior may be greater in developing countries lacking rich economic learned histories and/or suitable, dependable institutions, such countries may benefit more from behavioral-informed policy (to include nudges).
The Role of Bias Disparity in Aid Policy
In a follow-up essay, I plan to assemble literature and empirical studies focusing on the intersection of present bias and poverty. I feel that the presence of heterogeneity of present bias between citizens of Western countries (i.e. aid distributors) and citizens of developing nations (i.e. aid recipients) might have meaningful implications for aid structure, amounts, and effectiveness. Demonstrating poverty-linked changes to present bias may also influence political palatability of aid in a general sense–i.e. if policymakers had evidence that stereotypes of the poor (spend money/aid quickly without much thought for saving).
Balakrishnan, Uttara; Haushofer, Johannes; Jakiela. (2015). “How Soon is Now? Evidence of Present Bias from Convex Time Budget Experiements.”
Banerjee, Abhijit, and Esther Duflo. 2012. Poor economics: A radical rethinking of the way to fight global poverty. PublicAffairs.
Can, Burak and Erdem, Orhan. 2013. “Present Bias in Different Income Groups.”
Cassidy, Rachel. 2017. “Are the Poor Really So Present-Biased?: Experimental Evidence From Pakistan” https://sites.tufts.edu/neudc2017/files/2017/10/paper_175.pdf
McKenzie, David. 2015. “Present Bias 20 Years On – Should We Give Up on S.D.s for Effect Size?”. The World Bank Blog
Vojtech, Bartos; Michal Bauer; Julie, Chytilova; Ian Levely. (forthcoming). “Evidence for Direct Effect of Poverty on Time Preference: An Experiment with Ultra-poor Farmers in Uganda”. University of Munich