Performance Prediction of the Ferrous Metal Smelting and Rolling Processing Industry in Supply-Side Structural Reform in China

Kaihe Shi,Xiaoxuan Zhang,Danning Du,Lifeng Wu

doi:10.1155/2021/2383473

Abstract

Supply-side structural reforms and environmental protection policies have a great impact on the ferrous metal smelting and rolling processing industry. This paper uses a grey model that introduces a fractional-order cumulative generating operator to study the development of ferrous metal smelting and rolling processing enterprises under the influence of supply-side structural reform in order to derive the future development trend of the industry. The forecast results show that from 2018 to 2022, the number of enterprises and substitute enterprises, inventory, finished products, and assets and liabilities decreases; the scale of income of metal smelting and rolling processing industry increases. The results can serve as a reference for policy makers and industry investors.

Highlights

In recent years, the development of China’s ferrous metal smelting and rolling processing industry (FRI) has been volatile
Fluctuation in price of ferrous metal has been exerting pressure on ferrous metal smelting and rolling processing companies. e impact of these measures on China’s ferrous metal smelting and rolling processing industry continues to increase with the strengthening of supply-side structural reforms and increased environmental protection policies [1]
In the case of fractional cumulative grey model (FGM)(1, 1) equality perturbation, the sample size of the original series is proportional to the size of the perturbation boundary of the model [7]. is implies that from the perspective of stability, the model is relatively stable when the sample size is small

Summary

Introduction

The development of China’s ferrous metal smelting and rolling processing industry (FRI) has been volatile. Ere are few studies on FRI development structure, scale, production, and other indicators. Based on the effectiveness characteristics of short-term series forecasting, the fractional cumulative grey model (FGM) has been widely applied in various fields [4], including in the field of economic research and development [5]. Is implies that from the perspective of stability, the model is relatively stable when the sample size is small Is paper uses FGM(1, 1) to make predictions on corporate data in different FRIs. e forecast targets are the losses, inventory, finished products, assets, and total liabilities of the enterprises, as well as the revenue scale of the FRI. The number and scale of enterprises comprehensively reflect the industry’s market structure and industry development and operating capabilities.

Literature Review

Forecasting Results and Discussion

Conclusions