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Federal Department of the Environment, Transport,
Energy and Communications DETEC
Federal Office for Spatial Development ARE
Fundamental Policy Questions
Working from home in
Switzerland, 2015-2050
A. Danalet, A. Justen & N. A. Mathys
21st Swiss Transport Research Conference (STRC)
September 13th 2021
• Goal: Forecast who will work from home among the Swiss population in 2050
• Motivation: Better trip generation forecasts
• Predict the number of trips, in particular to work, possibly for leisure
• Develop better transport forecast, in particular the Transport Outlook 2050
• Guide transport policy and infrastructure investments
• Data:
• Mobility and Transport Microcensus 2015
• Synthetic population calibrated to retrospective data for the reference year 2017
• Forecasted synthetic populations for 2030, 2040 and 2050
2
• A. Danalet, A. Justen & N. A. Mathys
Working from home in Switzerland, 2015-2050
Working from home in Switzerland, 2015-2050
3
• A. Danalet, A. Justen & N. A. Mathys
Working from home in Switzerland, 2015-2050
Reasons to work from home in 2015
4
• A. Danalet, A. Justen & N. A. Mathys
Working from home in Switzerland, 2015-2050
• Binary logit model:
• Some home-based telecommuting
• Not working from home at all
• Sample: 8997 persons
5
• A. Danalet, A. Justen & N. A. Mathys
Working from home in Switzerland, 2015-2050
Choice model of home-based telecommuting
Attributes tested in the model
Level of education
Sex
Structure of the household (5 categories)
Public transport connection quality (home & work)
Urban/rural typology (home & work)
Crow-fly distance from home to work
Business sector in which the person works
Having several part time jobs
Income of the household
Function in the company
Work percentage
Language of the interview
Age
6
• A. Danalet, A. Justen & N. A. Mathys
Working from home in Switzerland, 2015-2050
Estimation results, 2015
• Work related factors
• Working in agriculture: Work from home (WFH) because live and work in farm
• Working in gastronomy, production & service: No WFH, since no digital substitution
• Working in public admin & education
• Independent/executives
• Work percentage
• Socio-economic factors
• Interview in German, men, high income, university education
• Swiss, German, French, Italian and North Western Europe nationality
• Age as a piecewise linear function: 20-34 up, 75+ down
• Spatial factors
• Large home-work distance, bad public transport (home), work in rural area
Green: parameter > 0
Red: parameter < 0
Internal validation
• Estimated on random 80% of the data, applied to the remaining 20%, 10 times
• Rates of home-based telecommuting in the 20%:
• Observed: 27.9% (±2.0%) (min: 26.7%, max: 28.9%)
• Predicted: 25.0% (min: 23.6%, max: 25.8%)
Calibration of the constant
• Alternative specific constant calibrated against observed proportion in the MTMC
• Apply Train, 2003 on the employees of the MTMC
7
• A. Danalet, A. Justen & N. A. Mathys
Working from home in Switzerland, 2015-2050
Internal validation & Calibration of the constant
External validation
• Observed rate of home-based telecommuting in the MTMC 2015: 28.1% (±0.9%)
• Predicted rate of home-based telecommuting in the SynPop 2017: 25.2%
Re-calibration of the constant
• Alternative specific constant calibrated against observed proportion in the MTMC
• Apply Train, 2003, this time on the employees in the SynPop 2017
8
• A. Danalet, A. Justen & N. A. Mathys
Working from home in Switzerland, 2015-2050
External validation & Re-calibration of the constant
9
• A. Danalet, A. Justen & N. A. Mathys
Working from home in Switzerland, 2015-2050
People working from home in 2030, 2040 & 2050
Limitations
• Not included:
• The possible long-term effect of the COVID-19 pandemic
• The possible future technological developments
• Nationality is significant, probably a proxy for other factors. Valid for forecasting?
Future work
• To be included in an ordered logit model of the number of trips to work (& leisure)
• Use the data of the MTMC 2020/2021 & add the effect of the COVID-19 pandemic
• Model of the percentage of work made at home
10
• A. Danalet, A. Justen & N. A. Mathys
Working from home in Switzerland, 2015-2050
Limitations and future work
• 39% of employees living in Switzerland will work from home in 2050 (models say)
• Quantitative approach for forecasting home-based telecommuting
• Transport Outlook 2050:
• Telecommuting will increase
• Number of trips to work will decrease due to telecommuting
• Compensation effects, e.g. more and shorter leisure trips, are taken into account
• Detailed results will be published in November 2021
• Data of the MTMC 2015 are available to researchers
• Point data of the synthetic population are not
• Code of the model: github.com/antonindanalet/home_office_in_microcensus
11
• A. Danalet, A. Justen & N. A. Mathys
Working from home in Switzerland, 2015-2050
Conclusion

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Working from home in Switzerland, 2015-2050

  • 1. Federal Department of the Environment, Transport, Energy and Communications DETEC Federal Office for Spatial Development ARE Fundamental Policy Questions Working from home in Switzerland, 2015-2050 A. Danalet, A. Justen & N. A. Mathys 21st Swiss Transport Research Conference (STRC) September 13th 2021
  • 2. • Goal: Forecast who will work from home among the Swiss population in 2050 • Motivation: Better trip generation forecasts • Predict the number of trips, in particular to work, possibly for leisure • Develop better transport forecast, in particular the Transport Outlook 2050 • Guide transport policy and infrastructure investments • Data: • Mobility and Transport Microcensus 2015 • Synthetic population calibrated to retrospective data for the reference year 2017 • Forecasted synthetic populations for 2030, 2040 and 2050 2 • A. Danalet, A. Justen & N. A. Mathys Working from home in Switzerland, 2015-2050 Working from home in Switzerland, 2015-2050
  • 3. 3 • A. Danalet, A. Justen & N. A. Mathys Working from home in Switzerland, 2015-2050 Reasons to work from home in 2015
  • 4. 4 • A. Danalet, A. Justen & N. A. Mathys Working from home in Switzerland, 2015-2050
  • 5. • Binary logit model: • Some home-based telecommuting • Not working from home at all • Sample: 8997 persons 5 • A. Danalet, A. Justen & N. A. Mathys Working from home in Switzerland, 2015-2050 Choice model of home-based telecommuting Attributes tested in the model Level of education Sex Structure of the household (5 categories) Public transport connection quality (home & work) Urban/rural typology (home & work) Crow-fly distance from home to work Business sector in which the person works Having several part time jobs Income of the household Function in the company Work percentage Language of the interview Age
  • 6. 6 • A. Danalet, A. Justen & N. A. Mathys Working from home in Switzerland, 2015-2050 Estimation results, 2015 • Work related factors • Working in agriculture: Work from home (WFH) because live and work in farm • Working in gastronomy, production & service: No WFH, since no digital substitution • Working in public admin & education • Independent/executives • Work percentage • Socio-economic factors • Interview in German, men, high income, university education • Swiss, German, French, Italian and North Western Europe nationality • Age as a piecewise linear function: 20-34 up, 75+ down • Spatial factors • Large home-work distance, bad public transport (home), work in rural area Green: parameter > 0 Red: parameter < 0
  • 7. Internal validation • Estimated on random 80% of the data, applied to the remaining 20%, 10 times • Rates of home-based telecommuting in the 20%: • Observed: 27.9% (±2.0%) (min: 26.7%, max: 28.9%) • Predicted: 25.0% (min: 23.6%, max: 25.8%) Calibration of the constant • Alternative specific constant calibrated against observed proportion in the MTMC • Apply Train, 2003 on the employees of the MTMC 7 • A. Danalet, A. Justen & N. A. Mathys Working from home in Switzerland, 2015-2050 Internal validation & Calibration of the constant
  • 8. External validation • Observed rate of home-based telecommuting in the MTMC 2015: 28.1% (±0.9%) • Predicted rate of home-based telecommuting in the SynPop 2017: 25.2% Re-calibration of the constant • Alternative specific constant calibrated against observed proportion in the MTMC • Apply Train, 2003, this time on the employees in the SynPop 2017 8 • A. Danalet, A. Justen & N. A. Mathys Working from home in Switzerland, 2015-2050 External validation & Re-calibration of the constant
  • 9. 9 • A. Danalet, A. Justen & N. A. Mathys Working from home in Switzerland, 2015-2050 People working from home in 2030, 2040 & 2050
  • 10. Limitations • Not included: • The possible long-term effect of the COVID-19 pandemic • The possible future technological developments • Nationality is significant, probably a proxy for other factors. Valid for forecasting? Future work • To be included in an ordered logit model of the number of trips to work (& leisure) • Use the data of the MTMC 2020/2021 & add the effect of the COVID-19 pandemic • Model of the percentage of work made at home 10 • A. Danalet, A. Justen & N. A. Mathys Working from home in Switzerland, 2015-2050 Limitations and future work
  • 11. • 39% of employees living in Switzerland will work from home in 2050 (models say) • Quantitative approach for forecasting home-based telecommuting • Transport Outlook 2050: • Telecommuting will increase • Number of trips to work will decrease due to telecommuting • Compensation effects, e.g. more and shorter leisure trips, are taken into account • Detailed results will be published in November 2021 • Data of the MTMC 2015 are available to researchers • Point data of the synthetic population are not • Code of the model: github.com/antonindanalet/home_office_in_microcensus 11 • A. Danalet, A. Justen & N. A. Mathys Working from home in Switzerland, 2015-2050 Conclusion