1,721,032 research outputs found

    The impact of climate funds on economic growth and their role in substituting fossil energy sources

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    In recent years, the climate funds stood out as tool to counter the climate change and its environmental impact financing adaptation. Moreover they represent an instrument to promote practices to support the developing countries in their path towards the sustainability.The aim of this paper is to evaluate the effectiveness of the introduction of policies implementing the use of climate funds. To reach it we analyze the funds received by the recipient through a counterfactual analysis. The results show that the policy contributed to the decreasing of greenhouse gas (GHG) emissions and promoted the change in generation energy systems supporting the replacement of fossil sources with renewable sources. Moreover, in these countries highlights the leverage effect of the climate finance for the economic development

    A binary time series model with a long-memory structure

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    Markov chains and Mixture Transition Distribution are the most traditional models for binary time series. More recently, Startz (2008) has introduced a novel model for binary data, the so-called Binomial AutoRegressive Moving Average model basically based on the comparison between theoretical and empirical autopersistence functions. However, some economic phenomena show a long memory structure not captured by any of these formulations. For quarterly U.S. binary data on recession, we show that a long-memory model for binary data can substantially improve the fit

    The dynamic of the United States' Co2 emissions: An empirical multidimensional analysis

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    In recent years, energy policies have enhanced electricity generation from renewable energy sources (RES). The aim of this paper is to contribute to the literature on the determinants of carbon emissions and to provide an evaluation of policy effectiveness in promoting energy efficiency. We implement a Dynamic Factor Analysis (DFA) to select a smaller number of common dynamic factors that summarize the multidimensional determinants of CO2 emissions. The novelty of this paper lies on the estimation of the determinants of emission trend that uses a high number of control variables observed over a long time period. The results show that the CO2 trend is influenced by economic development in the short run. The negative signs of demographic and energy factors reveal the existence of a path through environmental sustainability in the U.S. The growth of the population and of energy emissions is accompianed by a a decrease of CO2 emissions in the long run

    Do determinants of eco-innovations vary? An investigation of innovative SMEs through a quantile regression approach

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    Ecological innovations (EIs) are believed to play a crucial role both for the future competitiveness of companies and environmental protection. Thus, many researchers have investigated the determinants stimulating the adoption of EIs, but they usually consider determinants as a static concept. In this paper, these determinants are hypothesized to vary with companies’ propensity to adopt them, that is, the degree to which companies consider relevant the choice to invest in EIs. In this view, the paper investigated a sample of 222 innovative SMEs following a multi-step procedure. By means of a composite indicator, firstly the SMEs’ propensity to adopt EIs was calculated. Secondly, in order to identify the determinants that stimulate SMEs to invest in eco-innovation, the procedure of Principal Component Analysis based on the ScotLass algorithm was applied. Thirdly, the determinants individuated as the principal components extracted were investigated through OLS and quantile regression. The results suggest that among the SMEs with a higher propensity to invest in EIs, the more evident determinants are the ambition to reach better economic performance, the capacity to establish networking, and the endogenous competencies of SMEs. Also, the variable structural nature concerning the firm’s size shows a high relevance

    Forecasting the COVID-19 effects on energy poverty across EU member states

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    The COVID-19 pandemic is manifesting its devastating effects in multiple directions, even indirectly affecting the health of citizens, for instance, by increasing the level of energy poverty (EP). As part of the studies that are trying to frame the consequences of the pandemic, this paper aims to identify the effects on EP in the coming years in a bid to identify the countries of the European Union most affected and the time span necessary to return to a path to reduce EP. For this purpose, an analysis based on the supervised learning algorithms of dynamic factor models is carried out. The outcomes of this investigation show that the negative effects of the pandemic on the level of EP will be reabsorbed very slowly, not before 2025, and in any case with substantial differences between countries, further widening the gap between countries with low levels of EP and those with greater EP levels

    Energy dependence, renewable energy generation and import demand: Are EU countries resilient?

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    In this paper, we provide an in-depth analysis of factors determining energy import demand of EU countries. We suggest a novel approach to study the role of renewable versus non renewable energy sources in shaping the demand for energy imports. The aim of the paper is twofold. First, we provide a comprehensive analysis of the EU energy market structure using country-by-country I–O tables to show the rate of interdependency between EU member states in terms of renewable and non renewable energy flows. Second, we investigate on the role of renewable energy sources in reducing energy dependency in EU countries. The econometric analysis uses data from 26 EU countries observed between 2007 and 2016 available from the Eurostat energy statistics database. The descriptive analysis of I–O electricity tables shows some degree of heterogeneity between countries in terms of energy in- and out-flows. Such heterogeneous market structure suggests the use of panel models in the econometric analysis. Moreover, a lasso regression method has been employed for variables selection to avoid the collinearity. The results show that benefits may arise from replacing energy imports with domestic energy production and from reducing energy dependency rate. Moreover, if import substitution occurs with domestic renewable energy sources additional positive effects are produced in terms of either energy dependency, energy security and sustainable development
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