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CDatanet (version 2.2.1)

Econometrics of Network Data

Description

Simulating and estimating peer effect models and network formation models. The class of peer effect models includes linear-in-means models (Lee, 2004; ), Tobit models (Xu and Lee, 2015; ), and discrete numerical data models (Houndetoungan, 2024; ). The network formation models include pair-wise regressions with degree heterogeneity (Graham, 2017; ) and exponential random graph models (Mele, 2017; ).

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install.packages('CDatanet')

Monthly Downloads

308

Version

2.2.1

License

GPL-3

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Repository

https://github.com/ahoundetoungan/CDatanet

Maintainer

Aristide Houndetoungan

Last Published

January 7th, 2025

Functions in CDatanet (2.2.1)

Estimating Network Formation Models with Degree Heterogeneity: the Bayesian Random Effect Approach

Estimating Tobit Models with Social Interactions

Computing Peer Averages

CDatanet-package

The CDatanet Package

Removing Identifiers with NA from Adjacency Matrices Optimally

Estimating Count Data Models with Social Interactions under Rational Expectations Using the NPL Method

Printing the Average Expected Outcomes for Count Data Models with Social Interactions

Estimating Network Formation Models with Degree Heterogeneity: the Fixed Effect Approach

Converting Data between Directed Network Models and Symmetric Network Models.

Estimating Linear-in-mean Models with Social Interactions

Creating Objects for Network Models

Simulating Data from Tobit Models with Social Interactions

Summary for the Estimation of Count Data Models with Social Interactions under Rational Expectations

Summary for the Estimation of Tobit Models with Social Interactions

Counterfactual Analyses with Count Data Models and Social Interactions

Summary for the Estimation of Linear-in-mean Models with Social Interactions

Simulating Count Data Models with Social Interactions Under Rational Expectations

Simulating Network Data

Simulating Data from Linear-in-Mean Models with Social Interactions