Inflation volatility under rational inattention: A semi-parametric model and the Directional Volatility Ratio
Description
This dataset includes data and Matlab scripts to replicate results in the article "Inflation volatility under rational inattention: A semi-parametric model and the Directional Volatility Ratio" by Alfredo Garcia-Hiernaux, Maria T. Gonzalez-Perez and David E. Guerrero. To run the code, follow instructions in 'Readme.txt'. In this article, we propose a semi-parametric volatility model to estimate inflation volatility within a conceptual framework that incorporates rational inattention and price stickiness. The model is applied to inflation data for Germany, France, Spain, the Eurozone, the United States, the United Kingdom, Japan, and Canada over the period 2002-2024, and the United States during the Great Inflation and Moderation (1965-1990). Our estimator outperforms standard parametric and non-parametric alternatives in forecasting inflation volatility and exhibits a strong empirical relationship with survey-based measures of inflation uncertainty. We also introduce the Directional Volatility Ratio (DVR), a novel measure that captures time varying asymmetries in the relationship between inflation levels and volatility. The DVR is effective for tracking shifting inflation trends, identifying turning points, and characterizing inflation risk across different regimes.
Files
Steps to reproduce
# Replication Package for "Inflation volatility under rational inattention: A semi-parametric model and the Directional Volatility Ratio" ## Description This package replicates all results, figures, and tables from the paper. ## Requirements - MATLAB R2021a or later (earlier versions may work but are not tested). - Toolboxes: Econometrics Toolbox, Statistics and Machine Learning Toolbox. - User functions included in this folder. ## Data The data are located in the `series` folder. Each file contains the price index for a country/region. The data are monthly and not seasonally adjusted. ## Instructions 1. Download the function files to a folder of your choice. 2. Ensure that the folder containing the functions also includes the data folder (named ‘series’). This folder includes the public series to replicate results. 3. Open MATLAB and navigate to the replication folder. Run the code from within the folder where the functions are located. 4. Follow the steps in 'Readme.txt' in order, to replicate the article tables and figures. ## Outputs Running the scripts will generate figures and tables in the current folder. If you wish to organize them, create folders named `figures` and `tables` and modify the saving commands in the scripts accordingly. ## Contact For questions, please contact David E. Guerrero, Universidad Complutense de Madrid (davidesg@ucm.es).