Electricity consumption analysis based on Turkish Household Budget Surveys

Kayalica, M. Ozgur; Ozozen, Avni; Guven, Denizhan; Kayakutlu, Gülgün; Bayar, Ayşe Aylin

doi:10.1007/s40974-020-00193-z

Cited by 10 publications

(2 citation statements)

References 21 publications

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“…The choice of the control variables included in the vector of Eq. ( 2 ) is based on previous empirical work on the subject (Labandeira et al 2006 ; Sanquist et al 2012 ; Kayalica et al 2020 ). In particular, we account for possible substitutes or complements to household electricity consumption in line with recent research (Garcia-Cerrutti 2000 ; Rehdanz 2007 ; Zhang et al 2018 ; Díaz and Medlock 2021 ).…”

Section: Methodsmentioning

confidence: 99%

Residential demand for electricity: empirical evidence from Greece using pseudo-panels

Kostakis

Lolos

2021

Energ. Ecol. Environ.

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This study investigates the behaviour of residential demand for electricity, employing a pseudo-panel methodology. The case of Greece, over the period 2009–2018, is taken as an example for our empirical investigation. The empirical analysis uses annual household panel data for the construction of 330 cohorts. The specification of cohorts is based on the date of birth, education level and geographical location of the head of the household. The econometric analysis is carried out using static and dynamic specifications and a quantile regression model. The results show that residential demand for electricity is price and income inelastic, both in the short and the long run. Electricity and heating oil appear to be complementary energy sources, while the household size and the education level are important determinants of residential demand for electricity. Income status has a marginal effect on demand for electricity, and the impact of urbanisation is insignificant. The quantile regression results show that, as the level of electricity use increases, demand for electricity becomes less income responsive and more price responsive. Our results show that a mix of structural energy measures along with economic policies could result in a decrease in electricity use and improve energy efficiency.

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Section: Methodsmentioning

confidence: 99%

Residential demand for electricity: empirical evidence from Greece using pseudo-panels

Kostakis

Lolos

2021

Energ. Ecol. Environ.

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“…It is oriented to the elderly at home, communities, and elderly care institutions and provides material and spiritual support for the elderly based on their medical, nursing, health, and nursing needs. Smart senior care systems can monitor the daily life of the elderly and give them intelligent help to solve some of the difficulties that the elderly encounter in their daily life [ 5 ].…”

Section: Introductionmentioning

confidence: 99%

A Neural Network Model of Smart Aging Combining Family Structure Change Factors

Jin

2022

Computational Intelligence and Neuroscience

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In this paper, we analyze the changes in family structure and explore the changes in detail, based on which we construct a neural network model of smart aging. Based on the gender perspective, the individual growth model in the multilayer linear model is used to examine the effects of family structure changes on the elderly in terms of economic exchange, daily care, and emotional support. The results show that there is no significant gender difference in the family structure changes on the elderly in terms of economic exchange and daily care, but there is a significant gender difference in terms of emotional support. To solve the problem of data imbalance in the daily activity categories of the elderly, this paper resamples the data and uses different neural network models for activity recognition of the sensor data generated from the daily activities of the elderly. In this paper, the daily behavior patterns of the elderly over a while are studied by correlating three conditions of time distance, optimal path, and sensor distance to discover the daily behavior patterns of the elderly, while the abnormal behavior patterns can be well separated by EM clustering algorithm. The daily behavior of the elderly is a coarse-grained representation of their daily activities. It is not limited to a specific activity and does not require the sensor ID, trigger time, and location triggered by the activity to be consistent, but in long-term daily activity data, it abstracts the general behavior rules of the elderly activities. Through the research of this paper, the existing system is improved, and the multifaceted needs of the elderly are fully considered, from housing needs to spiritual needs, to face the current elderly care problems with a positive attitude, create a good social elderly care environment for the elderly, and realize the real elderly care.

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Determinants of energy expenditures for Turkish households using quantile regression and data from an original survey in Turkey

Karaaslan

Algül

2023

Environ Sci Pollut Res

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Electricity consumption analysis based on Turkish Household Budget Surveys

Cited by 10 publications

References 21 publications

Residential demand for electricity: empirical evidence from Greece using pseudo-panels

Residential demand for electricity: empirical evidence from Greece using pseudo-panels

A Neural Network Model of Smart Aging Combining Family Structure Change Factors

Determinants of energy expenditures for Turkish households using quantile regression and data from an original survey in Turkey

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