相关论文: A Novel GDP Prediction Technique based on Transfer…

The most recent concern of all people on Earth is the increase in the concentration of greenhouse gas in the atmosphere. The concentration of these gases has risen rapidly over the last century and if the trend continues it can cause many…

The continuous rise in CO2 emission into the environment is one of the most crucial issues facing the whole world. Many countries are making crucial decisions to control their carbon footprints to escape some of their catastrophic outcomes.…

Climate change is a result of a complex system of interactions of greenhouse gases (GHG), the ocean, land, ice, and clouds. Large climate change models use several computers and solve several equations to predict the future climate. The…

This study investigates the long-term effects of temperature variations on economic growth using a data-driven approach. Leveraging machine learning techniques, we analyze global land surface temperature data from Berkeley Earth and…

GDP is a vital measure of a country's economic health, reflecting the total value of goods and services produced. Forecasting GDP growth is essential for economic planning, as it helps governments, businesses, and investors anticipate…

This paper presents an analysis of Green Gross Domestic Product (GGDP) using the System of Environmental-Economic Accounting (SEEA) model to evaluate its impact on global climate mitigation and economic health. GGDP is proposed as a…

Climate change and global warming are among the most significant issues that humanity is currently facing, and also among the issues that pose the greatest threats to all mankind. These issues are primarily driven by abnormal increases in…

Reducing Carbon dioxide (CO2) emission is vital at both global and national levels, given their significant role in exacerbating climate change. CO2 emission, stemming from a variety of industrial and economic activities, are major…

Precise and reliable climate projections are required for climate adaptation and mitigation, but Earth system models still exhibit great uncertainties. Several approaches have been developed to reduce the spread of climate projections and…

High temporal resolution CO2 emission data are crucial for understanding the drivers of emission changes, however, current emission dataset is only available on a yearly basis. Here, we extended a global daily CO2 emissions dataset…

Can we use data on the biographies of historical figures to estimate the GDP per capita of countries and regions? Here we introduce a machine learning method to estimate the GDP per capita of dozens of countries and hundreds of regions in…

This paper studies stochastic convergence of per capita CO$_2$ emissions in 28 OECD countries for the 1901-2009 period. The analysis is carried out at two aggregation levels, first for the whole set of countries (joint analysis) and then…

We propose a non-linear state-space model to examine the relationship between CO$_2$ emissions, energy sources, and macroeconomic activity, using data from 1971 to 2019. CO$_2$ emissions are modeled as a weighted sum of fossil fuel use,…

We estimate cumulative CO2 emissions during the period 2000 to 2050 from developed and developing countries based on the empirical relationship between CO2 per capita emissions (due to fossil fuel combustion and cement production) and…

Air pollution is a significant global health risk, contributing to millions of premature deaths annually. Nitrogen dioxide (NO2), a harmful pollutant, disproportionately affects urban areas where monitoring networks are often sparse. We…

We study the impact of climate volatility on economic growth exploiting data on 133 countries between 1960 and 2019. We show that the conditional (ex ante) volatility of annual temperatures increased steadily over time, rendering climate…

We apply the concept of Rayleigh-Jeans thermalization of classical fields for a description of the world Gross Domestic Product (GDP) distribution over countries. The thermalization appears due to a variety of interactions between countries…

This paper synthesizes evidence on climate change impacts specific to U.S. populations. We develop an apples-to-apples comparison of econometric studies that empirically estimate the relationship between climate change and gross domestic…

A transformation network describes how one set of resources can be transformed into another via technological processes. Transformation networks in economics are useful because they can highlight areas for future innovations, both in terms…

Accurate prediction with multimodal data-encompassing tabular, textual, and visual inputs or outputs-is fundamental to advancing analytics in diverse application domains. Traditional approaches often struggle to integrate heterogeneous data…