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Purpose The purpose of this paper is to focus on modeling economy growth with indicators of knowledge-based economy (KBE) introduced by World Bank for a case study in Iran during 1993-2013. Design/methodology/approach First, for grouping and reducing the number of variables, Tukey method and the principal component analysis are used. Also for modeling, 67 per cent of data is used for training in the two approaches of ARDL bounds testing and gene expression programming (GEP) and 33 per cent of them for testing the models. Then, the result models are compared with fitness function and Akaike information criteria (AIC). Findings The GEP model with fitness 945.7461 for training data and 954.8403 for testing data from 1000 is better than ARDL bounds testing model with fitness 335.5479 from 1000. In addition, according to model comparison tools (AIC), the GEP model has an extremely larger weight in comparison with ARDL bounds model. Therefore, the GEP model is introduced for future use in academia. Practical implications Knowledge and information is one of the most basic sources of wealth in economists’ sight. Thus, using KBE indicators appears essential in economic growth regarding daily progress in knowledge processes and its different theories. It is also extremely important to determine an appropriate model for KBE indicators which play a highly important role in the allocation of the economic resources of the country in an optimal manner. Originality/value This paper introduced a novel expression for economy growth using KBE indicators. All the data and the indicators are extracted from Word Bank service between 1993 and 2013.

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Global warming is a growing concern and carbon dioxide (CO2) emissions are the primary accelerator of global warming in the world. Since global warming is threatening the lives of all mankind and species, the Paris agreement was conceived to avert the negatives of climate change and it was adopted by the majority of countries. This paper seeks to examine the impacts of the Paris agreement, fossil fuel consumption, and net energy imports on CO2 emissions of Germany, France, and Spain in the post-Paris agreement with Panel datasets from 1995 to 2019 using both fully modified OLS (FMOLS) and dynamic OLS (DOLS). The purpose of this study is to analyze how the Paris agreement has changed the amount of CO2 emissions in 3 industrialized countries in western Europe. The findings of the two methods indicate that net energy import and three fossil fuel consumption parameters have meaningful positive effects on CO2 emissions. Key findings suggest that based on FMOLS results the Paris agreement has a very negligible, though negative impact around 0.0087 on carbon dioxide emissions. While according to DOLS results it still has a negative, but also meaningless impact. Based on statistics, oil consumption has the most to do with carbon dioxide emissions, which is followed by gas and coal consumption, thereby substitution with fewer pollutant energies, such as renewable energies can help CO2 emissions mitigation.