Univariate Modelling of Energy Consumption in Turkish Agriculture

Unakıtan, Gökhan; Türkekul, Berna

doi:10.1080/15567249.2010.492379

Cited by 5 publications

(3 citation statements)

References 18 publications

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“…Time series models have been developed for jurisdictions including Israel [20], Northern Spain [21], Turkey [22,23], the UK [24], and India [25]. Time series models also include those dedicated to short term forecasting [26][27][28], together with medium term forecasting models [29,30], and long term predictions [31][32][33].…”

Section: By Modelling Methodsmentioning

confidence: 99%

Statistical analysis of driving factors of residential energy demand in the greater Sydney region, Australia

Fan

MacGill

Sproul

2015

Energy and Buildings

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Section: By Modelling Methodsmentioning

confidence: 99%

Statistical analysis of driving factors of residential energy demand in the greater Sydney region, Australia

Fan

MacGill

Sproul

2015

Energy and Buildings

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“…In today's world of agriculture, energy is a critical component [1]. Recognizing this, the research on the economics of energy use in agriculture has received considerable attention, especially in developed countries [2].…”

Section: Introductionmentioning

confidence: 99%

Linkage of Electricity with Agricultural Growth and Technology Factors: An Illustration of India’s Case

2022

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Understanding the relationship between electricity consumption and economic growth is crucial for formulating efficient energy policies for all sectors in general, and for agriculture in particular. To study this, an empirical examination of the long-run co-movement and the causal relationship between electricity consumption and real gross state domestic product (GSDP) from agriculture and its allied sectors is attempted. The agricultural sector involves the use of different input technologies that are further influenced by electricity consumption. To account for this technology-enabling effect of electricity, we further take up an analysis of the relationship between electricity consumption and agricultural technology factors: fertilizer consumption, the share of irrigation, area under cereal, and the extent of mechanization. We use both state (data from 17 states for the period 1993–2017 for the electricity–GSDP relationship) and country-level data (for the period 1980–2018 for the electricity–technology factors relationship) in the analysis. Since short-period time series datasets analysis may yield unreliable and inconsistent results, we employed modern heterogeneous panel co-integration and panel-based error correction model techniques for analyzing the energy–growth linkage. When the heterogeneous states effect is taken into account, the empirical results fully support a positive long-run co-integrated connection between GSDP and electricity consumption. We could detect both long-run and short-run unidirectional causality running from electricity consumption to agricultural growth. Further electricity consumption was also found to augment the use of technology factors in agriculture. This calls for implementing policies and strategies for achieving higher electricity use in agriculture and improved efficiency in its utilization simultaneously.

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“…The authors concluded that the ARIMA forecasting of the total primary energy demand appears to be more reliable than the summation of the individual forecasts. Unakıtan and Türkekul [15] also assessed annual time series data for energy consumption using the ARIMA model. Erdoğdu [16] studied on the future growth of gas demand in Turkey and developed a forecasting model using an ARIMA framework.…”

Section: Introductionmentioning

confidence: 99%

A Framework for Sustainable Urban Water Management through Demand and Supply Forecasting: The Case of Istanbul

et al. 2015

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Abstract:The metropolitan city of Istanbul is becoming overcrowded and the demand for clean water is steeply rising in the city. The use of analytical approaches has become more and more critical for forecasting the water supply and demand balance in the long run. In this research, Istanbul's water supply and demand data is collected for the period during 2006 and 2014. Then, using an autoregressive integrated moving average (ARIMA) model, the time series water supply and demand forecasting model is constructed for the period between 2015 and 2018. Three important sustainability metrics such as water loss to supply ratio, water loss to demand ratio, and water loss to residential demand ratio are also presented. The findings show that residential water demand is responsible for nearly 80% of total water use and the consumption categories including commercial, industrial, agriculture, outdoor, and others have a lower share in total water demand. The results also show that there is a considerable water loss in the water distribution system which requires significant investments on the water supply networks. Furthermore, the forecasting results indicated that pipeline projects will be critical in the near future due to expected increases in the total water demand of Istanbul. The authors suggest that sustainable management of water can be achieved by reducing the residential water use through the use of water efficient OPEN ACCESSSustainability 2015, 7 11051 technologies in households and reduction in water supply loss through investments on distribution infrastructure.

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Univariate Modelling of Energy Consumption in Turkish Agriculture

Cited by 5 publications

References 18 publications

Statistical analysis of driving factors of residential energy demand in the greater Sydney region, Australia

Statistical analysis of driving factors of residential energy demand in the greater Sydney region, Australia

Linkage of Electricity with Agricultural Growth and Technology Factors: An Illustration of India’s Case

A Framework for Sustainable Urban Water Management through Demand and Supply Forecasting: The Case of Istanbul

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