Open AccessMultivariate Model for Natural Gas use as a Residential Heating Source in Rural Area
Author(s) -
Bernadett Nagy,
Barna Kovács,
Ádám CSUVÁR,
Alexander Titov
Publication year - 2021
Publication title -
bulletin of university of agricultural sciences and veterinary medicine cluj-napoca. horticulture
Language(s) - English
Resource type - Journals
eISSN - 1843-5394
pISSN - 1843-5254
DOI - 10.15835/buasvmcn-hort:2020.0049
Subject(s) - subsidy , natural gas , logistic regression , settlement (finance) , binomial regression , bivariate analysis , discrete choice , multivariate statistics , business , environmental economics , geography , economics , engineering , econometrics , statistics , mathematics , waste management , finance , market economy , payment
We selected the rural region of Koppány Valley in Hungary to investigate the residents’ natural gas use practices. Natural gas can be a feasible alternative for improving the quality of life in rural areas. The study’s aims were to look at the social, economic, and environmental facets of residential gas use in order to assist regional planning decisions in our selected rural area that would encourage efficiency and energy source switchover. The variables were collected using a quota-based sampling system survey. We chose to use binomial logistic regression model to ex-amine the explanatory variables’ significance. The higher the settlement scale in our data, the more likely it is that gas will be used. Residents who do not trust their mayor have a lower chance of using gas. When compared to insulated homes, non-insulated houses are less likely to use gas. Higher education level, pensioner category, and whether the individual accepts that bio-gas has environmental benefits are not significant categories. Therefore, residential heating technology is more likely to be supply-driven, than demand-driven. We would suggest the application of subsidies for heating equipment replacement, in combination with educational campaigns, in addition to establishing a higher degree of trust in their mayors.