Spatially Microsimulating Consumption
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This document discusses using spatial microsimulation to model consumption patterns at small area levels. It describes using census and survey data to generate estimates of time use, income, expenditures, and digital access for small geographic areas. Examples are provided of modeling time spent working, using mass media, household income deprivation, telecom and water bills, and internet access at the local area level in the UK. Future directions are identified, including modeling health behaviors, broadband access, and relative deprivation.
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Paper presented at "Spatial Variation in Energy Use, Attitudes and Behaviours: Implications for Smart Grids and Energy Demand", Policy Studies Institute, Friday, 7 February 2014, London, United Kingdom
Electricity consumption and household characteristics: Implications for censu...
Presentation given at MRS Workshop "Can Big Data replace the Census? What does Big Data give us now?" , March 7, 2016, MRS, London (https://www.mrs.org.uk/event/conferences/can_big_data_replace_the_census/course/4088/id/10035)
Web panel surveys maja fromseier petersen
- Statistics Denmark has developed a new web panel for surveys by recruiting participants from previous representative surveys and collecting contact information like email addresses. However, even this method results in bias in the web panel compared to the population.
- Statistics Denmark has also tested using the "E-boks" system as a panel, which almost all Danish citizens interact with for government services. This "E-boks panel" avoids some bias issues since it covers nearly the entire population. However, response rates were still lower than traditional surveys.
- Those responding to surveys through the E-boks system tended to be older, higher educated, employed individuals earning over a certain income threshold compared to traditional surveys. The E-boks method
Web panel surveys maja fromseier petersen
The document discusses Statistics Denmark's efforts to establish a representative web panel for surveys.
1) Statistics Denmark has recruited over 30,000 Danish citizens to their web panel by asking for email addresses during in-person surveys. However, this method leads to biases as those without internet access or unwilling to provide emails are underrepresented.
2) Even selecting panel members proportionally based on variables like gender, age and education only partially reduces biases. Non-response rates also introduce new biases, though weighting attempts to correct for this.
3) As an alternative, the document proposes using Denmark's digital mailbox system ("E-boks") which has over 4 million users, as the base for a new web panel.
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Sipple - Shared Services: A Common Reform that Works
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The document discusses a web-based tool that classifies areas in England and Wales as rural or urban using a methodology developed by the Rural Evidence Research Centre. The tool utilizes Google Maps and allows users to visualize settlement morphologies and contextual information. It classifies areas based on population density profiles at different scales. The goal is to improve understanding of the rural-urban classification and engage users by enabling them to provide feedback and integrate additional map data layers.
Wang et al DRT Greater Manchester presentation TRB 2012
This document summarizes research analyzing factors that influence demand for demand responsive transport (DRT) services in Greater Manchester, England. The researchers used multilevel modeling to analyze DRT trip data from 16 service areas. The models found that population density, ethnicity, proportion of people working from home, and levels of socioeconomic deprivation significantly impacted DRT demand. Specifically, DRT has potential in low-density, deprived areas with many white residents and few people working from home. The researchers suggest further examining service-level factors and exploring DRT demand in rural areas.
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Using Time Use Data To Trace 'Energy Practices' Through Time
The document discusses trends in energy demand (DEMAND) over time based on time use survey data from 1974 to 2005. It analyzes 10 activity classes and shows changes over time, with declines in activities like travel, cooking and eating, and increases in media use. Food preparation trends are examined in more detail, showing peaks shifting from the evening to the late morning on weekends. The analysis of time use data provides insights into how energy-demanding activities and practices have changed over the past several decades.
Modeling Water Demand in Droughts (in England & Wales)
This document describes an agent-based microsimulation model for estimating domestic water demand under drought conditions in the UK. The model simulates individual households and factors that influence water usage, such as household attributes, appliances, practices, pricing, and drought interventions. Preliminary results show that including drought responses can reduce total water demand by 5% compared to not including responses. Further development of the model will add more influencing factors and link it to drought forecasts to better estimate future water demand scenarios.
Modeling Water Demand in Droughts (in England & Wales)
Paper presented at the International Water Association (IWA) Efficient Conference 2017, Bath, UK 18-20 July
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This document describes an IMPETUS microsimulation model developed to estimate domestic hot water demand in the UK. The model takes into account factors like weather, demographics, technology changes, and personal water usage behaviors. It aims to better address uncertainties around climate change, social practices, and responses to water and energy efficiency measures. Heating water accounts for over half of residential water usage in the UK and is the second largest energy use in homes. The model suggests that installing efficient showerheads can substantially reduce both water consumption and energy demand. Future work will assess the impacts of other water efficiency interventions and behavior changes on energy usage.
SAVE: Lightning Talk
This document discusses a project called Solent Achieving Value from Efficiency (SAVE) that aims to reduce energy usage through LED lighting upgrades and monitor the financial and energy savings. It will conduct a trial evaluation including surveys and collecting energy usage data to analyze the results and share updates.
SAVE: A large scale randomised control trial approach to testing domestic ele...
The document describes a study that tested demand response interventions in the UK using a large randomized controlled trial approach. Over 4,000 households were recruited and randomly assigned to control and intervention groups. Initial results found that messages encouraging shifting electricity use away from peak hours had little impact, while the addition of a financial incentive reduced consumption by up to 5% in the targeted hours. The study is using high frequency electricity consumption data and modeling techniques to analyze flexibility at a local level, which could help target interventions and inform network investment decisions.
Hunting for (energy) demanding practices using big & medium sized data
Dr. Ben Anderson presents on hunting for energy demanding practices using big and medium sized data. He discusses linking transactional energy use data to surveys and time use studies to identify household practices that influence demand, such as cooking and cleaning routines. New sources of data like smart meter traces are also explored for revealing rhythms of demand. Challenges include scaling up micro-level insights and taking post-disciplinary approaches to analyze data of different sizes.
Small Area Estimation as a tool for thinking about temporal and spatial varia...
Anderson, B (2014) Small Area Estimation as a tool for thinking about temporal and spatial variation in energy demand. Paper presented at AURIN/NATSEM Microsimulation Workshop, University of Melbourne, Thursday 4th December 2014
Modeling Electricity Demand in Time and Space
Anderson, B (2014) Modeling Electricity Demand in Time and Space, Paper presented at ANZRSAI 2014, Christchurch, New Zealand, 2/12/2014
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Mathieu Durand-Daubin (EDF R&D-ECLEER)
Ben Anderson (Southampton University)
Paper presented at BEHAVE 2014, Said Business School, Oxford, 3rd September 2014
The Rhythms and Components of ‘Peak Energy’ Demand
Ben Anderson – University of Southampton (@dataknut)
Jacopo Torriti – University of Reading
Richard Hanna – University of Reading
Paper presented at BEHAVE 2014, Said Business School, Oxford, 3rd September 2014.
Do ‘eco’ attitudes & behaviours explain the uptake of domestic energy product...
"Do ‘eco’ attitudes & behaviours explain the uptake of domestic energy production technologies?"
Paper presented at "What Makes Us Act Green?", June 25 2014, London
The Distribution of Domestic Energy-Tech in Great Britain: 2008 – 2011
This document summarizes research on the distribution of domestic energy technologies in Great Britain from 2008 to 2011. It finds that adopters of these technologies tend to be home-owning residents of detached, rural homes who report environmentally friendly views and actions. Those seriously considering adoption also tend to have higher energy spending. Rejecters of these technologies are more often urban renters living in non-detached housing who report less environmentally friendly attitudes. The research finds some differences between adopters of solar PV and solar thermal technologies and highlights equity issues in the uneven distribution of benefits from these technologies.
Patterns of Water: Thinking about diversity, demand and consumption
Presentation on @ESRC funded water practices/demand research to @scotgov @GreenerScotland with @dralibrowne 4th December 2013, Scottish Government, Victoria Quay, Leith
Census 2022: An overview
An overview of the new ESRC Transformative research project given by Andy Newing to MRS Census and Geodemographic Group (CGG) hosted by GFK NOP, 19th November 2013 at Ludgate House, London
On the social scientific value of transactional data
- The document discusses using transactional data, like telephone call records, for social scientific research.
- Three case studies are presented that analyze telephone call data: one finds higher "localness" of calls correlates with greater deprivation, another finds weekly and fortnightly patterns in call durations, and a third attempts to classify households based on their calling patterns.
- The studies demonstrate how transactional data can provide new insights but also have limitations like non-random samples. Overall, the document argues transactional data is a promising new resource for sociology if used carefully.
Practices by Proxy: Climate, Consumption and Water (and troubles with data)
Please cite as:
Anderson, B (2012) Practices By Proxy: Climate, Consumption and Water, Paper presented at “Can Climate Change Policies Be Fair?”, Royal Statistical Society, July 5th 2012, London
Practices by proxy: Climate, Consumption and Water
Anderson, B., Browne, A., and Medd, W., (2012) Practices by proxy: climate, consumption and water. Paper presented at Living Costs and Food Survey user meeting, Tuesday 20 March 2012 at the Royal Statistical Society, London
Non-response and attrition in a multi-method longitudinal household panel survey
Paper presented at the Methodology of Longitudinal Surveys International Conference, 12-14 July 2006, University of Essex, Colchester, UK
Seven core issues for water demand management under CC and uncertainty: Refle...
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Using Time Use Data To Trace 'Energy Practices' Through Time
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Modeling Water Demand in Droughts (in England & Wales)
Modeling Water Demand in Droughts (in England & Wales)
Modeling Water Demand in Droughts (in England & Wales)
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A Social Practices-based Microsimulation Model for Estimating Domestic Hot Wa...
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The Rhythms and Components of ‘Peak Energy’ Demand
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The Distribution of Domestic Energy-Tech in Great Britain: 2008 – 2011
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Practices by proxy: Climate, Consumption and Water
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