Prioritizing driving factors of household carbon emissions: An application of the LASSO model with survey data

Baiocchi, 2010, The impact of social factors and consumer behavior on carbon dioxide emissions in the United Kingdom, J. Ind. Ecol., 10.1111/j.1530-9290.2009.00216.x Beckel, 2014, Revealing household characteristics from smart meter data, Energy., 10.1016/j.energy.2014.10.025 2020, BP statistical review of world energy statistical review of world Büchs, 2013, Who emits most? Associations between socio-economic factors and UK households’ home energy, transport, indirect and total CO2 emissions, Ecol. Econ., 10.1016/j.ecolecon.2013.03.007 Chancel, 2014, Are younger generations higher carbon emitters than their elders? Inequalities, generations and CO2emissions in France and in the USA, Ecol. Econ., 10.1016/j.ecolecon.2014.02.009 Chen, 2016, Opportunities of integrated systems with CO2 utilization technologies for green fuel & chemicals production in a carbon-constrained society, J. CO2 Util., 10.1016/j.jcou.2016.01.004 Chitnis, 2012, Forecasting scenarios for UK household expenditure and associated GHG emissions: outlook to 2030, Ecol. Econ., 10.1016/j.ecolecon.2012.09.016 Choi, 2017, The impact of metropolitan, county, and local land use on driving emissions in US metropolitan areas: mediator effects of vehicle travel characteristics, J. Transp. Geogr., 10.1016/j.jtrangeo.2017.09.004 Dai, 2012, The impacts of China’s household consumption expenditure patterns on energy demand and carbon emissions towards 2050, Energy Policy, 50, 736, 10.1016/j.enpol.2012.08.023 Ding, 2017, The relationships between household consumption activities and energy consumption in China— an input-output analysis from the lifestyle perspective, Appl. Energy, 10.1016/j.apenergy.2017.06.003 Druckman, 2010, The bare necessities: how much household carbon do we really need?, Ecol. Econ., 10.1016/j.ecolecon.2010.04.018 Druckman, 2015, Understanding households as drivers of carbon emissions Duarte, 2010, The impact of household consumption patterns on emissions in Spain, Energy Econ., 10.1016/j.eneco.2009.08.007 Fan, 2012, Embedded carbon footprint of Chinese urban households: structure and changes, J. Clean. Prod., 33, 50, 10.1016/j.jclepro.2012.05.018 Feng, 2011, The impact of household consumption on energy use and CO2 emissions in China, Energy., 10.1016/j.energy.2010.09.049 Firth, 2010, Targeting household energy-efficiency measures using sensitivity analysis, Build. Res. Inf., 10.1080/09613210903236706 Ghoddusi, 2019, Machine learning in energy economics and finance: a review, Energy Econ., 10.1016/j.eneco.2019.05.006 Golley, 2012, Income inequality and carbon dioxide emissions: the case of Chinese urban households, Energy Econ., 10.1016/j.eneco.2012.07.025 Grossman, 2006, Economic growth and the environment, Q. J. Econ. Han, 2015, Applying quantile regression and Shapley decomposition to analyzing the determinants of household embedded carbon emissions: evidence from urban China, J. Clean. Prod., 10.1016/j.jclepro.2014.08.078 Hsu, 2015, Identifying key variables and interactions in statistical models ofbuilding energy consumption using regularization, Energy., 10.1016/j.energy.2015.02.008 Humeau, 2013, Electricity load forecasting for residential customers: Exploiting aggregation and correlation between households, 2013 Ipcc, 2006 Irfany, 2017, Affluence and emission tradeoffs: evidence from Indonesian households’ carbon footprint, Environ. Dev. Econ., 10.1017/S1355770X17000262 Jiang, 2020, Carbon emission quantification and decarbonization policy exploration for the household sector - evidence from 51 Japanese cities, Energy Policy, 10.1016/j.enpol.2020.111438 Jones, 2014, Spatial distribution of U.S. household carbon footprints reveals suburbanization undermines greenhouse gas benefits of urban population density, Environ. Sci. Technol., 10.1021/es4034364 Khanna, 2016, Effects of demand side management on Chinese household electricity consumption: empirical findings from Chinese household survey, Energy Policy, 10.1016/j.enpol.2016.04.049 Knittel, 2019 Kurniawan, 2018, Cleaner energy conversion and household emission decomposition analysis in Indonesia, J. Clean. Prod., 10.1016/j.jclepro.2018.08.051 Lakshmanan, 2015, Machine learning and data mining approaches to climate science Lee, 2014, The influence of urban form on GHG emissions in the U.S. household sector, Energy Policy, 10.1016/j.enpol.2014.01.024 Li, 2019, The impact of social awareness and lifestyles on household carbon emissions in China, Ecol. Econ., 10.1016/j.ecolecon.2019.02.020 Liu, 2011, China’s carbon emissions from urban and rural households during 1992-2007, 1754 Liu, 2017, Assessment of impacts of Hubei pilot emission trading schemes in China – a CGE-analysis using TermCO2 model, Appl. Energy Liu, 2019, Promoting green residential buildings by increasing homebuyers’ willingness to pay: evidence from Sino-Singapore Tianjin eco-city in China, J. Clean. Prod., 238, 10.1016/j.jclepro.2019.117884 Long, 2018, Evaluation of energy-related household carbon footprints in metropolitan areas of Japan, Ecol. Model., 10.1016/j.ecolmodel.2018.03.008 Longhi, 2015, Residential energy expenditures and the relevance of changes in household circumstances, Energy Econ., 10.1016/j.eneco.2015.03.018 Lyons, 2012, Socioeconomic distribution of emissions and resource use in Ireland, J. Environ. Manag., 10.1016/j.jenvman.2012.07.019 Ma, 2019, Carbon-dioxide mitigation in the residential building sector: a household scale-based assessment, Energy Convers. Manag., 10.1016/j.enconman.2019.111915 Maraseni, 2015, A comparison of trends and magnitudes of household carbon emissions between China, Canada and UK. Environ. Dev., 10.1016/j.envdev.2015.04.001 Maraseni, 2016, Dynamism of household carbon emissions (HCEs) from rural and urban regions of northern and southern China, Environ. Sci. Pollut. Res., 10.1007/s11356-016-7237-5 Meangbua, 2019, Factors influencing energy requirements and CO2 emissions of households in Thailand: a panel data analysis, Energy Policy, 10.1016/j.enpol.2019.02.050 Meier, 2010, Determinants of residential space heating expenditures in Great Britain, Energy Econ., 10.1016/j.eneco.2009.11.008 Meng, 2018, More than half of China’s CO2 emissions are from micro, small and medium-sized enterprises, Appl. Energy, 10.1016/j.apenergy.2018.08.107 Mi, 2020, Economic development and converging household carbon footprints in China, Nat. Sustain., 10.1038/s41893-020-0504-y Miao, 2017, Influential factors in crude oil price forecasting, Energy Econ., 10.1016/j.eneco.2017.09.010 Motawa, 2015, Structural equation modelling of energy consumption in buildings, Int. J. Energy Sect. Manag., 10.1108/IJESM-11-2014-0004 Munksgaard, 2000, Impact of household consumption on CO2 emissions, Energy Econ., 10.1016/S0140-9883(99)00033-X Murray, 2011, Read the label! Energy Star appliance label awareness and uptake among U.S. consumers, Energy Econ., 10.1016/j.eneco.2011.04.013 Niamir, 2018, Transition to low-carbon economy: assessing cumulative impacts of individual behavioral changes, Energy Policy, 10.1016/j.enpol.2018.03.045 Niamir, 2020, Demand-side solutions for climate mitigation: bottom-up drivers of household energy behavior change in the Netherlands and Spain, Energy Res. Soc. Sci., 10.1016/j.erss.2019.101356 Papathanasopoulou, 2010, Household consumption, associated fossil fuel demand and carbon dioxide emissions: the case of Greece between 1990 and 2006, Energy Policy, 10.1016/j.enpol.2010.03.043 Qu, 2013, Household carbon dioxide emissions from peasants and herdsmen in northwestern arid-alpine regions, China, Energy Policy, 10.1016/j.enpol.2012.12.065 Rong, 2018, The influencing factors of urban household embedded carbon emissions based on quantile regression Sala-i-Martin, 1997, I just ran two million regressions, Am. Econ. Rev. Schipper, 1989, Linking life-styles and energy use: a matter of time, Annu. Rev. Energy Environ., 10.1146/annurev.eg.14.110189.001421 Schopfer, 2018, Economic assessment of photovoltaic battery systems based on household load profiles, Appl. Energy, 10.1016/j.apenergy.2018.03.185 Schwanen, 2020, Low-carbon mobility in London: a just transition?, One Earth., 10.1016/j.oneear.2020.01.013 Seriño, 2017, Effects of affluence on rising household carbon emission in the Philippines: An application using quantile regression approach. DLSU Bus, Econ. Rev. Seriño, 2015, Estimation and determinants of the Philippines’ household carbon footprint, Dev. Econ., 26, 147 Shi, 2013, Spillover effects of carbon footprint labelling on less developed countries: the example of the east asia summit region, Dev. Policy Rev., 31, 239, 10.1111/dpr.12005 Shi, 2014, Setting effective mandatory energy efficiency standards and labelling regulations: a review of best practices in the Asia Pacific region, Appl. Energy, 133, 135, 10.1016/j.apenergy.2014.07.084 Shi, 2020, Convergence and distribution dynamics of energy consumption among China’s households, Energy Policy, 142, 111496, 10.1016/j.enpol.2020.111496 Shigetomi, 2018, Driving forces underlying sub-national carbon dioxide emissions within the household sector and implications for the Paris agreement targets in Japan, Appl. Energy, 10.1016/j.apenergy.2018.07.057 Tibshirani, 1996, Regression shrinkage and selection via the lasso, J. R. Stat. Soc. Ser. B Tibshirani, 2011, Regression shrinkage and selection via the lasso: a retrospective, J. R. Stat. Soc. Ser. B Stat Methodol., 10.1111/j.1467-9868.2011.00771.x Underwood, 2015, The carbon implications of declining household scale economies, Ecol. Econ., 10.1016/j.ecolecon.2015.04.028 Viegas, 2015, Electricity demand profile prediction based on household characteristics Wang, 2020, Urban-rural carbon footprint disparity across China from essential household expenditure: survey-based analysis, 2010–2014, J. Environ. Manag. Wang, 2019, How do urbanization and consumption patterns affect carbon emissions in China? A decomposition analysis, J. Clean. Prod. Wang, 2019, Identifying the driving factors of black bloom in lake bay through bayesian LASSO, Int. J. Environ. Res. Public Health Wei, 2015, Comparative study on machine learning for urban building energy analysis Wei, 2020, Rising middle and rich classes drove China’s carbon emissions, Resour. Conserv. Recycl., 10.1016/j.resconrec.2020.104839 Wiedenhofer, 2017, Unequal household carbon footprints in China, Nat. Clim. Chang., 10.1038/nclimate3165 Wilson, 2013, An exploration of the relationship between socioeconomic and well-being variables and household greenhouse gas emissions, J. Ind. Ecol., 10.1111/jiec.12057 Wu, 2017, Measurement of inequality using household energy consumption data in rural China, Nat. Energy, 10.1038/s41560-017-0003-1 Xie, 2014, An introduction to the China family panel studies (CFPS), Chin. Sociol. Rev. Xu, 2014, Analysing residential energy consumption using index decomposition analysis, Appl. Energy Xu, 2020, Subsidies, loans, and companies’ performance: evidence from China’s photovoltaic industry, Appl. Energy, 260, 10.1016/j.apenergy.2019.114280 Yao, 2018, Can urbanization process and carbon emission abatement be harmonious? New evidence from China, Environ. Impact Assess. Rev., 10.1016/j.eiar.2018.04.005 Ye, 2013, Effects of natural environment on urban household energy usage carbon emissions, Energy Build., 10.1016/j.enbuild.2013.06.001 Zhang, 2015, Household carbon emission research: an analytical review of measurement, influencing factors and mitigation prospects, J. Clean. Prod., 10.1016/j.jclepro.2015.04.024 Zhang, 2017, How does urbanization affect carbon dioxide emissions? A cross-country panel data analysis, Energy Policy, 10.1016/j.enpol.2017.03.072 Zhang, 2018, Estimating residential energy consumption in metropolitan areas: a microsimulation approach, Energy. Zhang, 2019, Forecasting crude oil prices with a large set of predictors: can LASSO select powerful predictors?, J. Empir. Financ., 10.1016/j.jempfin.2019.08.007 Zhang, 2019, Socio-economic development and electricity access in developing economies: a long-run model averaging approach, Energy Policy, 132, 223, 10.1016/j.enpol.2019.05.031 Zhang, 2019, Unveiling key drivers of indirect carbon emissions of Chinese older households, Sustain. Zhang, 2020, Intertemporal lifestyle changes and carbon emissions: evidence from a China household survey, Energy Econ., 86, 104655, 10.1016/j.eneco.2019.104655 Zhao, 2006, On model selection consistency of lasso, J. Mach. Learn. Res., 7, 2541 Zhao, 2012, Residential energy consumption in urban China: A decomposition analysis, Energy Policy, 10.1016/j.enpol.2011.11.027 Zhu, 2018, The heterogeneous effects of urbanization and income inequality on CO2emissions in BRICS economies: evidence from panel quantile regression, Environ. Sci. Pollut. Res.