The effect of sectoral natural gas consumption on economic growth: a study of Turkey.

Turkey, which is among the developing countries, is highly dependent on foreign energy. This dependency creates a great burden on the country's economy. In recent years, Turkey has increased its hydrocarbon exploration in the seas in order to ensure energy supply security and to get rid of this burden on its economy. As a result of these exploration activities, Turkey announced that it discovered a natural gas reserve of 540 billion m3 in 2020. This study aimed to guide decision makers in the use of this discovered natural gas. To this end, this paper was examined the relationship between sectoral natural gas consumption and economic growth for Turkey in a multivariate model wherein capital and labour are included as additional variables. Using the annual data for the period 1988-2020, long- and short-run relationships were examined with the autoregressive distributed lag bound testing approach. According to the long-term findings, increases in natural gas consumption in all examined sectors encourage economic growth in Turkey. It has been determined that natural gas consumption in the industrial sector provides the greatest contribution to Turkey's economic growth. In the long run, a 1% increase in the natural gas consumption of the industrial sector increases the economic growth by 0.190%. On the other hand, it was noted that a 1% increase in natural gas consumption in the conversion sector increased growth by 0.134%, while a 1% increase in housing natural gas consumption increased by 0.072%. In line with the findings obtained, policymakers in the Turkish government are advised to substitute the natural gas used in the conversion sector with renewable energy sources and to use the discovered natural gas reserve for heating purposes in housings, in order to have long-run growth rates.

Investigation of the relationship between renewable energy, natural gas, and coal consumption with economic growth in Turkey: evidence from augmented ARDL approach.

Energy is an indispensable requirement for the sustainable development of countries. Turkey has been trying to increase the use of renewable sources in electricity energy production with the policies it has implemented recently. This study investigates the effect of disaggregate energy consumption on economic growth in Turkey via the Augmented ARDL. Robust results are obtained by Augmented ARDL in econometric analysis. In this context, it is to examine the impact of renewable energy, natural gas, and coal consumption. Considering the 2001 crisis in Turkey, we add a dummy variable to the cointegration equation. The paper employs the recently developed augmented ARDL approach in the presence of one structural break to investigate annual time series data during the period 1988-2018. The results obtained in this study showed that all variables were statistically significant eventually. Long-term estimation results suggest that among the energy sources examined in the study, on economic growth has a positive effect coal consumption, natural gas consumption, and renewable energy. Moreover, empirical results indicated that economic growth and energy consumption also contribute to environmental damage. On the contrary, natural gas both increases economic growth and is effective in increasing environmental quality. The fact that the positive effect of renewable energy sources on economic growth eventually is greater than natural gas is the most striking finding of the study. In line with these results, it can be said that Turkey can reduce its energy dependence by increasing the use of domestic and renewable energy sources and providing sustainable economic growth.

Evaluation of renewable energy policies in Turkey with sectoral electricity demand forecasting.

Energy is an essential requirement for sustainable development, society, and the world. Turkey has been trying to increase the use of renewable sources in electricity energy production with the incentive policies it has implemented in recent years. Accordingly, in the 2019-2023 Strategic Plan of the Ministry of Energy and Natural Resources, targets to increase the installed capacity of renewable energy sources have been determined. In this context, this article examines fort the first time, the effect of installed capacity of renewable energy sources on sectoral electricity demand. Thus, the study aims to evaluate the renewable energy policies implemented in Turkey. For this purpose, firstly, sectoral electricity demands were estimated for the period 1988-2017 using the autoregressive distributed lag bound testing approach. Then, forecasts were made for the period 2019-2023 with the econometric simulation method. The findings show that the Installed Capacity variable significantly and negatively affects electricity demand in all sectors in the long run. According to the forecast results made in the second stage of the study, it was observed that the higher the increase rate in the installed capacity of renewable energy sources, the faster the electricity demand would decrease. According to these results, Turkey needs to increase the share of renewable energy sources in electricity production in terms of economic and environmental sustainability.

Surprise and recency in novelty detection in the primate brain.

Primates and other animals must detect novel objects. However, the neuronal mechanisms of novelty detection remain unclear. Prominent theories propose that visual object novelty is either derived from the computation of recency (how long ago a stimulus was experienced) or is a form of sensory surprise (stimulus unpredictability). Here, we use high-channel electrophysiology in primates to show that in many primate prefrontal, temporal, and subcortical brain areas, object novelty detection is intertwined with the computations of recency and sensory surprise. Also, distinct circuits could be engaged by expected versus unexpected sensory surprise. Finally, we studied neuronal novelty-to-familiarity transformations during learning across many days. We found a diversity of timescales in neurons' learning rates and between-session forgetting rates, both within and across brain areas, that are well suited to support flexible behavior and learning in response to novelty. Our findings show that novelty sensitivity arises on multiple timescales across single neurons due to diverse but related computations of sensory surprise and recency and shed light on the computational underpinnings of novelty detection in the primate brain.

A primate temporal cortex-zona incerta pathway for novelty seeking.

Primates interact with the world by exploring visual objects; they seek opportunities to view novel objects even when these have no extrinsic reward value. How the brain controls this novelty seeking is unknown. Here we show that novelty seeking in monkeys is regulated by the zona incerta (ZI). As monkeys made eye movements to familiar objects to trigger an opportunity to view novel objects, many ZI neurons were preferentially activated by predictions of novel objects before the gaze shift. Low-intensity ZI stimulation facilitated gaze shifts, whereas ZI inactivation reduced novelty seeking. ZI-dependent novelty seeking was not regulated by neurons in the lateral habenula or by many dopamine neurons in the substantia nigra, traditionally associated with reward seeking. But the anterior ventral medial temporal cortex, an area important for object vision and memory, was a prominent source of novelty predictions. These data uncover a functional pathway in the primate brain that regulates novelty seeking.