| 来源类型 | Working Paper
|
| 规范类型 | 报告
|
| DOI | 10.3386/w26577
|
| 来源ID | Working Paper 26577
|
| Network Data |
| Bryan S. Graham
|
| 发表日期 | 2019-12-23
|
| 出版年 | 2019
|
| 语种 | 英语
|
| 摘要 | Many economic activities are embedded in networks: sets of agents and the (often) rivalrous relationships connecting them to one another. Input sourcing by firms, interbank lending, scientific research, and job search are four examples, among many, of networked economic activities. Motivated by the premise that networks' structures are consequential, this chapter describes econometric methods for analyzing them. I emphasize (i) dyadic regression analysis incorporating unobserved agent-specific heterogeneity and supporting causal inference, (ii) techniques for estimating, and conducting inference on, summary network parameters (e.g., the degree distribution or transitivity index); and (iii) empirical models of strategic network formation admitting interdependencies in preferences. Current research challenges and open questions are also discussed. |
| 主题 | Econometrics
; Estimation Methods
; Microeconomics
; Economics of Information
|
| URL | https://www.nber.org/papers/w26577
|
| 来源智库 | National Bureau of Economic Research (United States)
|
| 引用统计 |
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| 资源类型 | 智库出版物
|
| 条目标识符 | http://119.78.100.153/handle/2XGU8XDN/584251
|
推荐引用方式
GB/T 7714 |
Bryan S. Graham. Network Data. 2019.
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文件名：
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w26577.pdf
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格式：
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Adobe PDF
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