A Novel Prediction Model: ELM-ABC for Annual GDP in the Case of SCO Countries

Abstract

With the development of economic and technologies, the trend of annual Gross Domestic Product (GDP) and carbon dioxide (CO2) emission changes with time passes. The relationship between economic growth and carbon dioxide emissions is considered as one of the most important empirical relationships. In this study, we focus on the member of Shanghai Cooperation Organization, including China, Russia, India, and Pakistan and collect CO2 emission and annual GDP from 1969 to 2014. The statistical methods and tests are used to find the relationship between annual GDP and CO2 emission in these countries. Based on relationship between annual and CO2 emission, a novel multi-step prediction algorithm called Extreme Learning Machine with Artificial Bee Colony (ELM-ABC) is proposed for forecasting annual GDP based on CO2 emission and historical GDP features. According to the experimental results, it proved that the proposed model had a super forecasting ability in GDP prediction and it could predict ten-year future annual GDP for the corresponding countries. Moreover, the forecasting results showed that the annual GDP of China and Pakistan will continue to grow but growth will slow after 2025. The annual GDP in India will exhibit unstable growth. The trend of Russia will follow the pattern between 2010 and 2016.

Exploring Economic Development Trends Through Entropy Analysis

“…Step 1. For one subsector of the three industries, calculate the sum of GDP of a given year for different regions, as shown in equation (1).…”

“…While GDP in a district can be considered constant in a given year, spatial-temporal analysis methods are typically employed to evaluate its aggregation characteristics [1,2]. Spatial regression models are utilized to analyze the factors affecting GDP [12].…”

“…Numerous scholars have conducted research on methods for estimating the national or local level of economic development. In particular, GDP has gained significant attention with the establishment of novel prediction models for GDP [1,2]. Additionally, spatial-temporal analysis methods have been employed to evaluate the spatial pattern evolution of GDP in different regions [3,4].…”

Study of the Relationship between Economic Growth and Greenhouse Gas Emissions of the Shanghai Cooperation Organization Countries on the Basis of the Environmental Kuznets Curve

“…In this regard, the role of the climate policy of new international organizations will be strengthened, which will be a reference point for countries that are practically not involved in the fight against the growth of carbon intensity. The economies of the SCO countries show high growth rates of 4% to 9% per year [17]. In 2021, the total gross domestic product (GDP) of the SCO countries was almost a quarter of the world-USD 23.3 trillion, and GDP at purchasing power parity (PPP) around one-third of the world-USD 44.2 trillion.…”

“…The economies of the SCO countries show high growth rates of 4% to 9% per year [17]. In 2021, the total gross domestic product (GDP) of the SCO countries was almost a quarter of the world-USD 23.3 trillion, and GDP at purchasing power parity (PPP) around one-third of the world-USD 44.2 trillion.…”