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on Network Economics |
| By: | Simone Alfarano; Albert Banal-Estañol; Eva Camacho; Giulia Iori; Burcu Kapar; Rohit Rahi |
| Abstract: | We consider a setting in which privately informed agents are located in a network and trade a risky asset with other agents with whom they are directly connected. We compare the performance, both theoretically and experimentally, of a complete network (centralized market) to incomplete networks with differing levels of connectivity (decentralized markets). We show that decentralized markets can deliver higher informational efficiency, with prices closer to fundamentals, as well as higher welfare for mean-variance investors. |
| Keywords: | Networks, heuristic learning, informational efficiency, experimental asset markets |
| JEL: | C92 D82 G14 |
| Date: | 2024–01 |
| URL: | http://d.repec.org/n?u=RePEc:upf:upfgen:1877&r=net |
| By: | Goulas, Sofoklis (Brookings Institution); Megalokonomou, Rigissa (Monash University); Zhang, Yi (University of Queensland) |
| Abstract: | Recent research has shown that females make classrooms more conducive to effective learning. We identify the effect of a higher share of female classmates on students' disruptive behavior, engagement, test scores, and major choices in disadvantaged and non-disadvantaged schools. We exploit the random assignment of students to classrooms in early high school in Greece. We combine rich administrative data with hand-collected student-level data from a representative sample of schools that feature two novel contributions. Unlike other gender peer effects studies, a) we use a rich sample of schools and students that contains a large and diverse set of school qualities, and household incomes, and b) we measure disruption and engagement using misconduct-related (unexcused) teacher-reported and parent-approved (excused) student class absences instead of self-reported measures. We find four main results. First, a higher share of female classmates improves students' current and subsequent test scores in STEM subjects and increases STEM college participation, especially for girls. Second, a higher share of female classmates is associated with reduced disruptive behavior for boys and improved engagement for girls, which indicates an increase in overall classroom learning productivity. Third, disadvantaged students - those who attend low-quality schools or reside in low-income neighborhoods - drive the baseline results; they experience the highest improvements in their classroom learning productivity and their STEM outcomes from a higher share of female classmates. Fourth, disadvantaged females randomly assigned to more female classmates in early high school choose college degrees linked to more lucrative or prestigious occupations 2 years later. Our results suggest that classroom interventions that reduce disruption and improve engagement are more effective in disadvantaged or underserved environments. |
| Keywords: | quasi-random variation, STEM careers, classroom learning productivity, natural experiment, gender peer effects, disadvantaged students |
| JEL: | J16 J24 I24 I26 |
| Date: | 2023–12 |
| URL: | http://d.repec.org/n?u=RePEc:iza:izadps:dp16689&r=net |
| By: | Adamopoulou, Effrosyni (ZEW Mannheim); Greenwood, Jeremy (University of Pennsylvania); Guner, Nezih (CEMFI); Kopecky, Karen A. (Federal Reserve Bank of Atlanta) |
| Abstract: | The role of friends in the US opioid epidemic is examined. Using data from the National Longitudinal Survey of Adolescent Health (Add Health), adults aged 25-34 and their high school best friends are focused on. An instrumental variable technique is employed to estimate peer effects in opioid misuse. Severe injuries in the previous year are used as an instrument for opioid misuse in order to estimate the causal impact of someone misusing opioids on the probability that their best friends also misuse. The estimated peer effects are significant: Having a best friend with a reported serious injury in the previous year increases the probability of own opioid misuse by around 7 percentage points in a population where 17 percent ever misuses opioids. The effect is driven by individuals without a college degree and those who live in the same county as their best friends. |
| Keywords: | opioid, peer-group effects, friends, instrumental variables, Add Health, severe injuries |
| JEL: | C26 D10 I12 J11 |
| Date: | 2024–01 |
| URL: | http://d.repec.org/n?u=RePEc:iza:izadps:dp16709&r=net |
| By: | Haiyan Hao; Yan Wang |
| Abstract: | Existing Spatial Interaction Models (SIMs) are limited in capturing the complex and context-aware interactions between business clusters and trade areas. To address the limitation, we propose a SIM-GAT model to predict spatiotemporal visitation flows between community business clusters and their trade areas. The model innovatively represents the integrated system of business clusters, trade areas, and transportation infrastructure within an urban region using a connected graph. Then, a graph-based deep learning model, i.e., Graph AttenTion network (GAT), is used to capture the complexity and interdependencies of business clusters. We developed this model with data collected from the Miami metropolitan area in Florida. We then demonstrated its effectiveness in capturing varying attractiveness of business clusters to different residential neighborhoods and across scenarios with an eXplainable AI approach. We contribute a novel method supplementing conventional SIMs to predict and analyze the dynamics of inter-connected community business clusters. The analysis results can inform data-evidenced and place-specific planning strategies helping community business clusters better accommodate their customers across scenarios, and hence improve the resilience of community businesses. |
| Date: | 2024–01 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:2401.04849&r=net |
| By: | Ariel Burstein; Javier Cravino; Marco Rojas |
| Abstract: | We leverage a comprehensive dataset of electronic invoices from Chilean firms to document new facts on price dispersion across buyers of the same manufactured intermediate goods. Over half of firm-tofirm sales in manufacturing are accounted for by products that are purchased by more than one buyer in a given month, with prices ranging by 40 percentage points across buyers for the average product. Price dispersion is pervasive across all manufacturing sectors. Observable characteristics of products and of buyer-seller pairs (including distance, mode of payment, and size of the parties and of the transaction) explain only a small fraction of the variance of price gaps in the data. We use a workhorse model of production networks to quantify the productivity gains from eliminating markup dispersion across buyers of individual products, inferring initial differences in markups from observed price gaps. The increase in aggregate productivity relative to the sales share of treated multi-buyer firms ranges from 2 to 7 percent, depending on the calibration of elasticities of substitution. The gains from eliminating markup dispersion across buyers are as large as those of eliminating markup dispersion across products. |
| Date: | 2024–01 |
| URL: | http://d.repec.org/n?u=RePEc:chb:bcchwp:1006&r=net |