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New Measure Reveals Flawed Understanding of Media Freedom
Insights from the Field
Media Freedom
Item Response Theory
Bayesian Measurement Model
Countries
Comparative Politics
BJPS
1 R files
2 Stata files
11 datasets
2 text files
Dataverse
Measuring Media Freedom: An Item Response Theory Analysis of Existing Indicators was authored by Jonathan A. Solis and Philip D. Waggoner. It was published by Cambridge in BJPS in 2021.

### What Is Media Freedom?

Media freedom's role in democracy is well-established but often oversimplified with single indicators. This article analyzes ten existing measures to capture its complexity.

### The Challenge of Measurement

Existing media freedom indices struggle due to the concept's multidimensional nature, making cross-national comparison difficult and unreliable.

### A New Approach: Item Response Theory (IRT)

We treat media freedom as a latent variable using IRT with Bayesian estimation. This method creates robust data from 1948-2017 for all 197 countries studied.

### Validating Our Measurement Model

Multiple validity checks ensure our new Media System Freedom measure accurately reflects underlying political realities across diverse contexts.

### Key Findings: Replication and Refinement

Replicating Egorov, Guriev & Sonin (2009) on media freedom and natural resource wealth shows their original results don't hold once properly measuring the construct.

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British Journal of Political Science
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