Knowledge that Transforms

Data is nonrival: a person’s location history, medical records, and driving data can be used by many firms simultaneously. Nonrivalry leads to increasing returns. As a result, there may be social gains to data being used broadly across firms, even in the presence of privacy considerations. Fearing creative destruction, firms may choose to hoard their data, leading to the inefficient use of nonrival data. Giving data property rights to consumers can generate allocations that are close to optimal. Consumers balance their concerns for privacy against the economic gains that come from selling data broadly. (JEL C80, D11, D21, D83, E22, K11, O34)

We examine the channels through which a randomized early childhood intervention in Colombia led to significant gains in cognitive and socio-emotional skills among a sample of disadvantaged children aged 12 to 24 months at baseline. We estimate the determinants of parents’ material and time investments in these children and evaluate the impact of the treatment on such investments. We then estimate the production functions for cognitive and socio-emotional skills. The effects of the program can be explained by increases in parental investments, emphasizing the importance of parenting interventions at an early age. (JEL I24, I28, J13, J24, O15)

In a regime change game, privately informed agents sequentially decide whether to attack without observing others’ previous actions. To dissuade them from attacking, a principal adopts a dynamic information disclosure policy, frequent viability tests. A viability test publicly discloses whether the regime has survived the previous attacks. When such tests are sufficiently frequent, in the unique cutoff equilibrium, agents never attack if the regime passes the latest test, regardless of their private signals. We apply this theory to demonstrate that a borrower can eliminate panic-based runs by sufficiently diffusing the rollover choices across different maturity dates. (JEL C72, D82, G21)

Social network data are often prohibitively expensive to collect, limiting empirical network research. We propose an inexpensive and feasible strategy for network elicitation using Aggregated Relational Data (ARD): responses to questions of the form "how many of your links have trait k ?" Our method uses ARD to recover parameters of a network formation model, which permits sampling from a distribution over node- or graph-level statistics. We replicate the results of two field experiments that used network data and draw similar conclusions with ARD alone.

This paper estimates the effects on rural education of the send-down movement during the Cultural Revolution, when about 16 million urban youth were mandated to resettle in the countryside. Using a county-level dataset compiled from local gazetteers and population censuses, we show that greater exposure to the sent-down youths significantly increased rural children’s educational achievement. This positive effect diminished after the urban youth left the countryside in the late 1970s but never disappeared. Rural children who interacted with the sent-down youths were also more likely to pursue more-skilled occupations, marry later, and have smaller families than those who did not. (JEL I21, J13, J24, N35, O15, P36, R23)

The long-run social discount rate has an enormous effect on the value of climate mitigation, infrastructure projects, and other long-term public policies. Its value is however highly contested, in part because of normative disagreements about social time preferences. I develop a theory of “nondogmatic” social planners, who are insecure in their current normative judgments and entertain the possibility that they may change. Although each nondogmatic planner advocates an idiosyncratic theory of intertemporal social welfare, all such planners agree on the long-run social discount rate. Nondogmatism thus goes some way toward resolving normative disagreements, especially for long-term public projects. (JEL D61, H43)

We formalize the argument that political disagreements can be traced to a “clash of narratives.” Drawing on the “Bayesian Networks” literature, we represent a narrative by a causal model that maps actions into consequences, weaving a selection of other random variables into the story. Narratives generate beliefs by interpreting long-run correlations between these variables. An equilibrium is defined as a probability distribution over narrative-policy pairs that maximize a representative agent's anticipatory utility, capturing the idea that people are drawn to hopeful narratives. Our equilibrium analysis sheds light on the structure of prevailing narratives, the variables they involve, the policies they sustain, and their contribution to political polarization. (JEL D72, D83, D85, F52)

The spatial layout of cities is an important feature of urban form, highlighted by urban planners but overlooked by economists. This paper investigates the causal economic implications of city shape in India. I measure cities’ geometric properties over time using satellite imagery and historical maps. I develop an instrument for urban shape based on geographic obstacles encountered by expanding cities. Compact city shape is associated with faster population growth and households display positive willingness to pay for more compact layouts. Transit accessibility is an important channel. Land use regulations can contribute to deteriorating city shape. (JEL O18, R14, R23, R52, R58)

Expectations of transfers by central governments incentivize overborrowing by local governments. In this paper, we ask if fiscal rules can reduce overborrowing if central governments cannot commit to enforce penalties when rules are violated. We study a model in which the central government’s type is unknown and show that fiscal rules increase overborrowing if the central government’s reputation is low. In contrast, fiscal rules are effective in lowering debt if the central government’s reputation is high. Even when the central government’s reputation is low, binding fiscal rules will arise in the equilibrium of a signaling game. (JEL E62, H62, H63, H77, H81)

“Big data” financial technology raises concerns about market inefficiency. A common concern is that the technology might induce traders to extract others’ information, rather than to produce information themselves. We allow agents to choose how much they learn about future asset values or about others’ demands, and we explore how improvements in data processing shape these information choices, trading strategies and market outcomes. Our main insight is that unbiased technological change can explain a market-wide shift in data collection and trading strategies. However, in the long run, as data processing technology becomes increasingly advanced, both types of data continue to be processed. Two competing forces keep the data economy in balance: data resolve investment risk, but future data create risk. The efficiency results that follow from these competing forces upend two pieces of common wisdom: our results offer a new take on what makes prices informative and whether trades typically deemed liquidity-providing actually make markets more resilient. (JEL C55, D83, G12, G14, O33)