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Taxation exerts pressure on the economic activities of all companies, including economic entities that operate in the energy industry. This study examined the degree to which fiscal pressure influenced the financial performance of 88 publicly listed companies from the energy industry during a time frame of 16 years (2005Q1–2020Q3). By modelling financial data from the oil, gas and electricity sectors with panel data techniques, our results showed that fiscal pressure had a significant effect on the evolution of company financial performance measured by return on assets, return on equity and return on investment. The study revealed that fiscal pressure had a more positive impact on the financial performance of energy companies than a negative impact. This conclusion is important for overall taxation in the energy industry since corporate taxes, excise duties and mandatory labor contributions are basic resources for state budgets. Our empirical results imply important research directions on the prospect of analyzing company performance.

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Getting access to sufficient funding is the keystone for the development of any business, but especially for small and medium enterprises (SMEs). These economic entities are crucial players in the global economy since they include almost 90% of companies, provide jobs for nearly 50% of the global workforce, and enhance long-term economic growth. In this context, our study explores important sources concerning the financing of small and medium enterprises and their impact on economic growth during the period 2005–2020 with data from SMEs covering the 28 countries belonging to the European Union. The set of predictors included Strength of legal rights index, Days sales outstanding, Bad debt loss, Interest rate, Bank support, Business angels, Private lenders, and Public support. The set of dependent variables included Cost of loans, Equity fund, GDP growth rate, and Value added growth rate. Our methodological approach was complex, it considered a panel data analysis with a first-difference generalized method of moments estimator and a multiplex time series analysis. The novelty of the study resides in combining the two methods in order to investigate significant drivers of economic growth across the EU. Empirical results showed that economic growth was mainly triggered by predictors such as Interest rate, Business angels, Bank support, and Public support. Moreover, the valuable mathematical insights elicited by the multiplex time series analysis suggested that European economies cooperated intensively through SME activities. Based on our empirical results, national and regional authorities should enact adequate policies to support business endeavors of small and medium enterprises.