John A List, Julie Pernaudet, Dana L Suskind
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Socioeconomic inequalities in child development crystallize at early stages, with associated disparities in parental investment in children. A key to understanding the data patterns is to document the sources underlying the observed inequalities. We first show that there are dramatic differences in parental beliefs across socioeconomic backgrounds (SES), with parents of higher SES being more likely to believe that parental investments impact child development. We then use two field experiments targeted to low-SES families to explore the mutability of such beliefs and their link to parental investments. In both cases, we find that parental beliefs about child development are malleable. The less intensive version of the program based on educational videos changes parental beliefs, but fails to lastingly increase parental investments and child outcomes. By contrast, in the more intensive version of our program combining home visits and feedback, the augmented beliefs are associated with enriched parent-child interactions and improved vocabulary, math, and social-emotional skills for the children. Together, these results suggest that changing parental beliefs can be an important pathway to raising parental investments and reducing socioeconomic gaps in children's skills, but that simple informational policies may not be sufficient.
Ori Heffetz, John A List
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Carefully designed scientific experiments have been an engine of economic, technological, and social progress for well over a century, which is why the public generally trusts such methods. Unfortunately, governments around the world still routinely oppose controlled trials of public policies.
John A List
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This review summarizes results of field experiments examining individual behaviors across several market settings from - open-air markets to rideshare markets to tax-compliance markets - where people sort themselves into market roles wherein they make consequential decisions. Using three distinct examples from my own research on the endowment effect, left-digit bias, and omission bias, I showcase how field experiments can help researchers understand mediators, heterogeneity, and causal moderation involved in judgment biases in the field. In this manner, the review highlights that economic field experiments can serve an invaluable intellectual role alongside traditional laboratory research.
Eduardo Fe, David Gill, Victoria Prowse
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We investigate how childhood cognitive skills affect strategic sophistication and adult outcomes. In particular, we emphasize the importance of childhood theory-of-mind as a cognitive skill. We collected experimental data from more than seven hundred children in a variety of strategic interactions. First, we find that theory-of-mind ability and cognitive ability both predict level-k behavior. Second, older children respond to information about the cognitive ability of their opponent, which provides support for the emergence of a sophisticated strategic theory-of-mind. Third, theory-of-mind and age strongly predict whether children respond to intentions in a gift-exchange game, while cognitive ability has no influence, suggesting that different measures of cognitive skill correspond to different cognitive processes in strategic situations that involve understanding intentions. Using the ALSPAC birth-cohort study, we find that childhood theory-of-mind and cognitive ability are both associated with enhanced adult social skills, higher educational participation, better educational attainment, and lower fertility in young adulthood. Finally, we provide evidence that school spending improves theory-of-mind in childhood.
Snigdha Gupta, Maggie C. Kane, John A List, Liz Sablich, Lauren Supplee, Dana L Suskind
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Recommendations for Mitigating Threats to Scaling
Snigdha Gupta, John A List, Lauren Supplee, Dana L Suskind
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Failed to Scale: Embracing the Challenge of Scaling in Early Childhood
John A List
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All happy families are alike; each unhappy family is unhappy in its own way. -Leo Tolstoy, Anna Karenina
John A List, Azeem M Shaikh, Atom Vayalinkal
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List et al. (2019) provides a framework for testing multiple null hypotheses simultaneously using experimental data in which simple random sampling is used to assign treatment status to units. As in List et al. (2019), we rely on general results in Romano and Wolf (2010) to develop under weak assumptions a procedure that (i) asymptotically controls the familywise error rate - the probability of one or more false rejections - and (ii) is asymptotically balanced in that the marginal probability of rejecting any true null hypothesis is approximately equal in large samples. Our analysis departs from List et al. (2019) in that it further exploits observed, baseline covariates. The precise way in which these covariates are incorporated is based upon results in Lin (2013) in order to ensure that inferences are typically more powerful in large samples.
Amanda Chuan, John A List, Anya Samek
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Research has shown that giving disadvantaged families financial incentives to invest in their children could decrease socioeconomic inequality by enhancing human capital formation. Yet, within the household how are such gains achieved? We use a field experiment to investigate how parents allocate time when they receive financial incentives. We find that incentives increase investment in the target child. But, parents achieve these gains by substituting away from time spent with the child's sibling(s). An unintended consequence is that intrahousehold inequality increases and aggregate gains from the program are overstated when focusing only on target children.
Kazi Iqbal, Asad Islam, John A List, Vy Nguyen
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Whether, and to what extent, behavioral anomalies uncovered in the lab manifest themselves in the field remains of first order importance in finance and economics. We begin by examining behavior of retail traders/investors making investment decisions in constructed laboratory markets. Our results show that the behaviors of the traders are consistent with myopic loss aversion. We combine the lab results with a unique individual-level matched dataset on daily stock market transactions and portfolio positions over a two year period. We find that lab behaviors help to predict, but do not fully capture, the essential real-world trading analogs of retail traders.
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