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This paper presents a method for creating machine learning models, specifically a gradient boosting model and a random forest model, to forecast real GDP growth. This study focuses on the real GDP growth of Japan and produces forecasts for the years from 2001 to 2018. The forecasts by the International Monetary Fund and Bank of Japan are used as benchmarks. To improve out-of-sample prediction, the cross-validation process, which is designed to choose the optimal hyperparameters, is used. The accuracy of the forecast is measured by mean absolute percentage error and root squared mean error. The results of this paper show that for the 2001–2018 period, the forecasts by the gradient boosting model and random forest model are more accurate than the benchmark forecasts. Between the gradient boosting and random forest models, the gradient boosting model turns out to be more accurate. This study encourages increasing the use of machine learning models in macroeconomic forecasting.

The objective of this study is to explore the influence of the real income (GDP), renewable energy consumption and non-renewable energy consumption on carbon dioxide (CO 2 ) emissions for the United States of America (USA) in the environmental Kuznets curve (EKC) model for the period 1980–2014. The Zivot-Andrews unit root test with a structural break and the Clemente-Montanes-Reyes unit root test with a structural break report that the analyzed variables become stationary at first-differences. The Gregory-Hansen cointegration test with a structural break and the bounds testing for cointegration in the presence of a structural break show CO 2 emissions, the real income, the quadratic real income, renewable and non-renewable energy consumption are cointegrated. The long-run estimates obtained from the ARDL model indicate that increases in renewable energy consumption mitigate environmental degradation whereas increases in non-renewable energy consumption contribute to CO 2 emissions. In addition, the EKC hypothesis is not valid for the USA. Since we use time-series econometric approaches that account for structural break in the data, findings of this study are robust, reliable and accurate. The US government is advised to put more weights on renewable sources in energy mix, to support and encourage the use and adoption of renewable energy and clean technologies, and to increase the public awareness of renewable energy for lower levels of emissions.

Background Accelerated globalisation has substantially contributed to the rise of emerging markets worldwide. The G7 and Emerging Markets Seven (EM7) behaved in significantly different macroeconomic ways before, during, and after the 2008 Global Crisis. Average real GDP growth rates remained substantially higher among the EM7, while unemployment rates changed their patterns after the crisis. Since 2017, however, approximately one half of the worldwide economic growth is attributable to the EM7, and only a quarter to the G7. This paper aims to analyse the association between the health spending and real GDP growth in the G7 and the EM7 countries. Results In terms of GDP growth, the EM7 exhibited a higher degree of resilience during the 2008 crisis, compared to the G7. Unemployment in the G7 nations was rising significantly, compared to pre-recession levels, but, in the EM7, it remained traditionally high. In the G7, the austerity (measured as a percentage of GDP) significantly decreased the public health expenditure, even more so than in the EM7. Out-of-pocket health expenditure grew at a far more concerning pace in the EM7 compared to the G7 during the crisis, exposing the vulnerability of households living close to the poverty line. Regression analysis demonstrated that, in the G7, real GDP growth had a positive impact on out-of-pocket expenditure, measured as a percentage of current health expenditure, expressed as a percentage of GDP (CHE). In the EM7, it negatively affected CHE, CHE per capita, and out-of-pocket expenditure per capita. Conclusion The EM7 countries demonstrated stronger endurance, withstanding the consequences of the crisis as compared to the G7 economies. Evidence of this was most visible in real growth and unemployment rates, before, during and after the crisis. It influenced health spending patterns in both groups, although they tended to diverge instead of converge in several important areas.

This study applies asymmetric causality to renewable energy (REC), carbon dioxide emissions (CE), and real GDP using non-linear broadcasting between these variables through the non-linear autoregressive distributed lag model (NARDL) to examine the short- and long-run asymmetries in the inconsistency of greenhouse gas emissions among the variables and to unpack the asymmetric causality of selective variables through positive and negative shocks for time series data from the Kingdom of Saudi Arabia between 1990 and 2014. The bounds cointegration test shows the existence of long-term dealings among all considered variables in the presence of asymmetry. The non-linear asymmetric causality test shows that negative shocks in carbon dioxide emissions had only positive impacts on real GDP in the long-term but are unobservable in the short-term. Additionally, the short- and the long-term incidences of positive shocks on real GDP are not similar to the negative shock to REC, implying the existence of asymmetric impacts on REC in both short- and long-term forms. Finally, the asymmetric causal relationship from carbon dioxide emissions to REC is neutral in the long-term. Both positive and negative shocks to REC consistently had an adverse effect on CE in the long-term. The presence of asymmetry between economic growth, CE, and REC could be of major substantial for more helpful policymakers and the action plan of sustainable development goals (SDGs) in Saudi Arabia.

Although oil price shocks have long been viewed as one of the leading candidates for explaining U.S. recessions, surprisingly little is known about the extent to which oil price shocks explain recessions. We provide a formal analysis of this question with special attention to the possible role of net oil price increases in amplifying the transmission of oil price shocks. We quantify the conditional effect of oil price shocks in the net oil price increase model for all episodes of net oil price increases since the mid-1970s, analyze its determinants, and show that the linear model fits the data better.

The globalized world has experienced significant environmental degradation together with raising global production and population. In this context, the employment of renewable energy use has become crucial for a sustainable environment and development. In the research, the mutual causality among renewable energy, trade and financial globalization, real GDP per capita, and CO2 emissions in EU transition economies experiencing the integration with global economy was explored through bootstrap panel Granger causality test for the period of 1995–2015. The causality analysis revealed a unilateral causality from trade globalization to renewable energy in Estonia, Latvia, and Slovenia, and from renewable energy to trade globalization in Croatia and Lithuania. However, no significant causality between financial globalization and renewable energy was revealed. On the other side, a unilateral causality from CO2 emissions to renewable energy in Lithuania and Slovenia, and from renewable energy to CO2 emissions in Czechia, Hungary, and Latvia and a reciprocal causality between renewable energy to CO2 emissions in Romania and Slovakia and a unilateral causality from real GDP per capita to renewable energy in Czechia, Romania, and Slovenia was discovered in the causality analysis.

This paper examines whether the hypothetical environmental Kuznet curve (EKC) exists or not and investigates how trade openness affects CO 2 emissions, together with real GDP and total primary energy consumption. The study sample comprises ten newly industrialized countries (NICs-10) from 1971 to 2013. The results support the existence of hypothetical EKC and indicate that trade openness negatively and significantly affects emissions, while real GDP and energy do positive effects of emissions. Moreover, the empirical results of short-run causalities indicate feedback hypothetical linkage of real GDP and trade, unidirectional linkages from energy to emissions, and from trade to energy. The error correction terms (ECTs) reveal in the long run, feedback linkages of emissions, real GDP, and trade openness, while energy Granger causes emissions, real GDP, and trade, respectively. The study recommendations are that our policymakers should encourage and expand the trade openness in these countries, not only to restrain CO 2 emissions but also to boost their growth.

This paper analyses the relationship between real GDP and CO2 emissions for 17 transitional economies based on a series of annual data from 1997 to 2014. The analysis was conducted using Dynamic Ordinary Least Squares (OLS) (DOLS) and Fully Modified OLS (FMOLS) approaches. The results clearly suggest the existence of a statistically significant long-run cointegrating relationship between CO2 emissions and real GDP. A 1% change in GDP leads to around a 0.35% change of CO2 emission on average for the considered group of countries. Close values of long-run coefficients for all estimations confirm the robustness of the estimated results. The authors state that transitional economies need to follow global policy incentives, and try to implement new mechanisms and instruments for the purpose of reducing CO2 emissions, such as environmental taxes, emissions-trading schemes, and carbon capture and storage, if they want to achieve future CO2 emission reductions, while attaining economic growth.

This research explores the impact of environment, life expectancy, and real GDP per capita on health expenditures in a sample of 27 EU member states over the 2000–2018 period through causality and cointegration analyses. The causality analysis revealed a significant unilateral causality from variables of greenhouse gas emissions, life expectancy, and real GDP per capita to health expenditures. In other words, greenhouse gas emissions, life expectancy, and real GDP per capita had a significant impact on health expenditures in the short run. The cointegration analysis indicated that life expectancy and real GDP per capita had a significant positive impact on health expenditures at the overall panel. On the other side, the country level cointegration coefficients revealed that life expectancy had a considerable positive impact on health expenditures, real GDP per capita had a moderate positive impact on the health expenditures in most of the countries in the panel, but the environment proxied by greenhouse gas emissions had a low positive or negative impact on the health expenditures in a limited number of countries.

The assessment of the informal economy's impact on economic growth in the Association of Southeast Asian Nations (ASEAN) member states was carried out using three different static panel data models: pooled Ordinary Least Squares (OLS), random effects, and fixed effects models. This comprehensive study covered a period of twenty-seven years and included ten countries, yielding a total of 270 observations. The estimated coefficient for the informal economy in the random effects model was 0.0780, while in the fixed effects model it was 0.1747, both of which were statistically significant at the 5% level. These results indicated that an increase in the formal economy would contribute positively to real GDP growth in the ASEAN member states. Additionally, both panel data models revealed that the inflation rate significantly affected real GDP, although the estimated coefficients were negative, with values of -0.0723 for the RE model and -0.0995 for the FE model, both significant at the 1% level. Conversely, the research did not find a significant relationship between population growth rate and real GDP. Notably, there was no significant correlation between any of the variables and real GDP when analyzed under the OLS model.