Financial Development and Economic Growth: The Case of Kazakhstan

Katenova, Maya; Nurmakhanova, Mira

doi:10.21102/irbrp.2017.03.131.11

Cited by 2 publications

(1 citation statement)

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“…As an essential part of the Silk Road Economic Belt, it occupies an important position in the international energy market. In the first decade of the 21st century, Kazakhstan ranked among the top three countries in the world for accelerated economic growth rates, due mainly to this country's energy production and consumption (Azatbek and Ramazanov, 2016;Kalyuzhnova and Patterson, 2016;Katenova and Nurmakhanova, 2017). It has gradually positioned itself as the economic engine in Central Asia.…”

Section: Introductionmentioning

confidence: 99%

Quantitative analysis of the impact factors of conventional energy carbon emissions in Kazakhstan based on LMDI decomposition and STIRPAT model

Chen

et al. 2018

J. Geogr. Sci.

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Quantitative analysis of the impact factors in energy-related CO 2 emissions serves as an important guide for reducing carbon emissions and building an environmentally-friendly society. This paper aims to use LMDI method and a modified STIRPAT model to research the conventional energy-related CO 2 emissions in Kazakhstan after the collapse of the Soviet Union. The results show that the trajectory of CO 2 emissions displayed U-shaped curve from 1992 to 2013. Based on the extended Kaya identity and additive LMDI method, we decomposed total CO 2 emissions into four influencing factors. Of those, the economic active effect is the most influential factor driving CO 2 emissions, which produced 110.86 Mt CO 2 emissions, with a contribution rate of 43.92%. The second driving factor is the population effect, which led to 11.87 Mt CO 2 emissions with a contribution rate of 4.7%. On the contrary, the energy intensity effect is the most inhibiting factor, which caused-110.90 Mt CO 2 emissions with a contribution rate of-43.94%, followed by the energy carbon structure effect resulting in-18.76 Mt CO 2 emissions with a contribution rate of-7.43%. In order to provide an in-depth examination of the change response between energy-related CO 2 emissions and each impact factor, we construct a modified STIRPAT model based on ridge regression estimation. The results indicate that for every 1% increase in population size, economic activity, energy intensity and energy carbon structure, there is a subsequent increase in CO 2 emissions of 3.13%, 0.41%, 0.30% and 0.63%, respectively.

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Section: Introductionmentioning

confidence: 99%