Energy policy simulation in times of crisis: Revisiting the impact of renewable and non-renewable energy production on environmental quality in Germany

In this paper, we examine for the first time in the literature the implications of energy policy alternatives for Germany considering the aftermath of coronavirus as well as Electricity and Gas energy supply shortages. Whilst several policy options are open to the government, the choice of investment in renewable energy generation versus disinvestment in non-renewable energy such as coal energy generation provides divergent impacts in the long term. We utilize data from British Petroleum and the World Bank Development Indicator database for Germany covering 1981 to 2020 to explore a Carbon function by applying a battery of Autoregressive distributed lag model (ARDL), dynamic ARDL and Kernel-Based Regularized Least squares approaches. The particular policy tested is the pledge by Germany to decrease emissions by ∼100% in 2050, and this was integrated through the estimation of dynamic ARDL estimation. The simulation result shows that a ＋61% shock in renewable energy production decreases carbon emissions unlike coal energy production which increases carbon emissions in the beginning but the carbon emissions decrease thereafter. The findings highlight the inevitability of cutting down on coal production, and recommends energy investment alternatives. Hence, Germany's energy policy should contemplate more thoroughly on these factors. © 2023 The Author(s)

Data-Driven Business Analytics for the Tourism Industry in the UK: A Machine Learning Experiment Post-COVID

The use of data-driven business analytic models has had a significant impact on several sectors of the economy. In the UK, the tourism industry has contributed significantly to the economy. The contribution of tourism to the UK economy is estimated to be £145.9 billion (7.2%) of UK GDP. Regardless of its economic value, tourism is also one of the most vulnerable sectors, as it is susceptible to natural disasters, civil unrest, crisis, and pandemics, all of which can fully shut down the industry. Hence, an accurate and reliable tourism demand forecast is important. Apart from COVID-19, no other occurrence in modern history has had such a broad impact on the economy, industries, everyone and businesses in the world (Galvani et al., 2020). However, with the impact of COVID19 on the industry, it is imperative to reassess potential recovery plans for the UK economy, particularly for local tourism businesses. Macroeconomic data is collected over many source markets for the UK and a machine learning algorithm is tested to assess the future of the industry. © 2021 IEEE.