Mixed-frequency Data Sampling Grey System Model

Introduction

This repository contains code to support the implementation of the paper: Yimeng An, Yaoguo Dang, Junjie Wang, Huimin Zhou, Son T. Mai, Mixed-frequency data Sampling Grey system Model: Forecasting annual CO2 emissions in China with quarterly and monthly economic-energy indicators, Applied Energy, Volume 370, 2024, 123531, ISSN 0306-2619, https://doi.org/10.1016/j.apenergy.2024.123531. The model utilizes both quarterly and monthly economic-energy indicators as input.

Background

Forecasting annual $CO_2$ emissions is a crucial task for understanding and addressing environmental challenges. Traditional forecasting models often rely solely on annual data, which may not capture the nuances of short-term fluctuations in economic and energy variables. The Mixed-frequency Data Sampling Grey System Model addresses this limitation by incorporating both quarterly and monthly data, providing more accurate and timely predictions.

Features

• Utilizes quarterly and monthly economic-energy indicators for improved forecasting accuracy.
• Implements a Grey System Model to handle mixed-frequency data effectively.
• Supports forecasting of annual $CO_2$ emissions in China.

Usage

1. Install the required dependencies.
2. Prepare the quarterly and monthly economic-energy indicator data.
3. Use the provided code to implement the Mixed-frequency Data Sampling Grey System Model.
4. Analyze the forecasted annual $CO_2$ emissions in China based on the model's predictions.