Comparison Sheet Format In Excel 41490

Partial file snippet.

Sheet 1: Contents

	
	
		Gender differences in commute time and pay
		

		

		

		

		

	
	
		

		

		

		

		Statistical contact: Vahé Nafilyan
	
	
		Annual Survey of Hours and Earnings, Office for National Statistics
		

		

		

		

		

		

		

		

		

		

		

		E-mail: earnings@ons.gov.uk
	
	
		Labour Force Survey, Office for National Statistics
		

		

		

		

		

		

		

		

		

		

		

		

	
	
		

		

		

		

		

		

		

		

		

		

		

		

		

	
	
		Notes 
		

		

		

		

		

		

		

		

		

		

		

		

	
	
		

		

		

		

		

		

		

		

		

		

		

		

		

	
	
		For ages 16-64 and in employment 
		

		

		

		

		

		

		

		

		

		

		

		

	
	
		

		

		

		

		

		

		

		

		

		

		

		

		

	
	
		Table 1 
		Median travel time (minutes) by gender, 2002 to 2018, GB
		

		

		

		

		

		

		

		

		

		

		

	
	
		Table 2
		Median travel time (minutes) by gender and age, GB
		

		

		

		

		

		

		

		

		

		

		

	
	
		Table 3
		Median travel time (minutes) by gender and age (London and the rest of the country), GB
		

		

		

		

		

		

		

		

		

		

		

	
	
		Table 4
		Median gross weekly earnings (£) by gender and age, GB
		

		

		

		

		

		

		

		

		

		

		

	
	
		Table 5
		Median gross hourly pay (£) by gender and age, GB
		

		

		

		

		

		

		

		

		

		

		

	
	
		Table 6
		Effect of commuting time (minutes) and hourly pay (£) on annual job separation rate by gender, GB
		

		

		

		

		

		

		

		

		

		

		

	
	
		Table 7
		Under and over 30 median commuting time (minutes), by gender and travel to work area
		

		

		

		

		

		

		

		

		

		

		

	
	
		Table 8
		Commuting time (minutes) proportion comparison, LFS and ASHE 
		

		

		

		

		

		

		

		

		

		

		

	



Sheet 2: Notes

	
	
		Contents 
	
	
		

	
	
		Estimating commuting time in the Annual Survey of Hours and Earnings
	
	
		

	
	
		ASHE does not provide direct information on commuting time or mode. However, it contains information on the postcode of the home and workplace of the employee. We use these postcodes to estimate commuting time using a trip planner app, following these steps
	
	
		
	
		
	
		

	
	
		1.       Retrieve the latitude and longitudes of the postcode centroids using the ONS Postcode Directory.
	
	
		2.       Find the nearest road to the postcodes centroids using Open Street Map ( OSRM)
	
	
		3.       Use the PropeR tool to estimate travel time. We estimated travel time by car or public transport, setting the arrival time at 9:00am on Monday. Due to technical limitations, this was only possible if the home and work postcodes were in the same or in an adjacent region.
	
	
		
	
		
	
		

	
	
		We applied this method to compute travel time by car and public transport for the 1,065,549 combinations of postcodes that we have in the 2002 to 2018 ASHE. Driving time could not be obtained for 137,329 postcodes combinations (12.9%). Travel time by public transports could not be calculated for 340,403 postcodes combinations (31.9%).
	
	
		
	
		
	
		
	
		

	
	
		Based on these calculated travel time by car and public transport, we estimated travel time as follows
	
	
		

	
	
		·         Set to missing driving time if road distance is lower than the straight-line distance1: 10,016 records (0.9%)
	
	
		·         Use driving time if driving time is shorter than public transport, unless the employee lives in inner London, or works in Central London, in which case we use travel time by public transport
	
	
		
	
		·         Set to missing if travel time is over 4 hours - 3,014 records (0.02%)
	
	
		·         For postcodes combinations with missing travel time, impute travel time based on a regression model using straight-line distance interacted with region and urban status as predictors.
	
	
		
	
		·         Cap commuting time to 4 hours
	
	
		

	
	
		ONS also publishes self-reported estimates of commuting time in the Labour Force Survey (LFS). These take precedence as our best estimate of commuting time – the calculations used here are for the purposes of this analysis only.
	
	
		
	
		
	
		

	
	
		For table 6, post-estimation calculations based on Cox proportional hazard model which include penalised splines for commuting time and hourly pay as well as additional covariates individual and job characteristics : age (second-order polynomial), hours worked (second-order polynomial), annual leave entitlement (second-order polynomial), occupation (at 2-digit level), sector ( public/private), number of employees (quintiles) living in an urban area, year, and Travel to Work Area. Models are estimated separately for men and women. Standard errors clustered at the individual level.
	
	
		
	
		
	
		
	
		
	
		
	
		

	
	
		1 The straight-line distance is computed based on the postcode centroid, whereas the driving distance is computed based on the nearest road to the postcodes. Therefore, it is possible for the road distance to be lower than the straight-line distance. We therefore only discard travel time if the difference between road distance and the straight-line is lower than minus one kilometre
	



Sheet 3: Table 1

	
	
		Contents 
		

		

		

		

	
	
		Median travel time (minutes) by gender, 2002 to 2018, GB
		

		

		

		

	
	
		

		

		

		 95% Confidence intervals
		
	
		Gender
		Year
		Median travel time
		Lower bound
		Upper bound
	
	
		Male
		2002
		21.10
		20.90
		21.28
	
	
		Male
		2003
		21.23
		21.05
		21.42
	
	
		Male
		2004
		21.57
		21.40
		21.77
	
	
		Male
		2005
		21.55
		21.35
		21.73
	
	
		Male
		2006
		21.92
		21.72
		22.10
	
	
		Male
		2007
		22.13
		21.95
		22.34
	
	
		Male
		2008
		22.50
		22.33
		22.73
	
	
		Male
		2009
		23.05
		22.88
		23.26
	
	
		Male
		2010
		23.17
		22.97
		23.33
	
	
		Male
		2011
		23.15
		22.98
		23.32
	
	
		Male
		2012
		23.27
		23.10
		23.43
	
	
		Male
		2013
		23.57
		23.38
		23.78
	
	
		Male
		2014
		23.68
		23.50
		23.89
	
	
		Male
		2015
		23.65
		23.45
		23.82
	
	
		Male
		2016
		23.70
		23.53
		23.87
	
	
		Male
		2017
		23.92
		23.75
		24.13
	
	
		Male
		2018
		23.85
		23.67
		24.05
	
	
		

		

		

		

		

	
	
		

		

		

		 95% Confidence intervals
		
	
		Gender
		Year
		Median travel time
		Lower bound
		Upper bound
	
	
		Female
		2002
		15.77
		15.63
		15.92
	
	
		Female
		2003
		16.02
		15.88
		16.18
	
	
		Female
		2004
		16.23
		16.08
		16.38
	
	
		Female
		2005
		16.37
		16.23
		16.53
	
	
		Female
		2006
		16.58
		16.45
		16.70
	
	
		Female
		2007
		16.75
		16.58
		16.91
	
	
		Female
		2008
		16.98
		16.82
		17.13
	
	
		Female
		2009
		17.27
		17.13
		17.40
	
	
		Female
		2010
		17.55
		17.42
		17.68
	
	
		Female
		2011
		17.58
		17.47
		17.68
	
	
		Female
		2012
		17.85
		17.72
		17.98
	
	
		Female
		2013
		18.18
		18.03
		18.32
	
	
		Female
		2014
		18.45
		18.32
		18.59
	
	
		Female
		2015
		18.47
		18.32
		18.60
	
	
		Female
		2016
		18.52
		18.37
		18.65
	
	
		Female
		2017
		18.84
		18.73
		18.98
	
	
		Female
		2018
		18.93
		18.82
		19.08
	
	
		Source: Annual Survey of Hours and Earnings 
		
	
		

		

		

		

		

	
	
		1 Commuting time is estimated based on the home and work postcode via a trip planner app. The median is calculated using survey weights. The 95% confidence intervals of the weighted median, estimated via bootstrapping.

The words contained in this file might help you see if this file matches what you are looking for:

...Sheet contents gender differences in commute time and pay statistical contact vah eacute nafilyan annual survey of hours earnings office for national statistics email onsgovuk labour force notes ages employment table median travel minutes by to gb age london the rest country gross weekly pound hourly effect commuting on job separation rate under over work area proportion comparison lfs ashe estimating does not provide direct information or mode however it contains postcode home workplace employee we use these postcodes estimate using a trip planner app following steps nbsp retrieve latitude longitudes centroids ons directory find nearest road open street map osrm proper tool estimated car public transport setting arrival at am monday due technical limitations this was only possible if were same an adjacent region applied method compute combinations that have driving could be obtained transports calculated based as follows middot set missing distance is lower than straightline records s...

Related files

Share

Help

Contents

Estimating commuting time in the Annual Survey of Hours and Earnings

ASHE does not provide direct information on commuting time or mode. However, it contains information on the postcode of the home and workplace of the employee. We use these postcodes to estimate commuting time using a trip planner app, following these steps



1. Retrieve the latitude and longitudes of the postcode centroids using the ONS Postcode Directory.
2. Find the nearest road to the postcodes centroids using Open Street Map ( OSRM)
3. Use the PropeR tool to estimate travel time. We estimated travel time by car or public transport, setting the arrival time at 9:00am on Monday. Due to technical limitations, this was only possible if the home and work postcodes were in the same or in an adjacent region.



We applied this method to compute travel time by car and public transport for the 1,065,549 combinations of postcodes that we have in the 2002 to 2018 ASHE. Driving time could not be obtained for 137,329 postcodes combinations (12.9%). Travel time by public transports could not be calculated for 340,403 postcodes combinations (31.9%).




Based on these calculated travel time by car and public transport, we estimated travel time as follows

· Set to missing driving time if road distance is lower than the straight-line distance1: 10,016 records (0.9%)
· Use driving time if driving time is shorter than public transport, unless the employee lives in inner London, or works in Central London, in which case we use travel time by public transport

· Set to missing if travel time is over 4 hours - 3,014 records (0.02%)
· For postcodes combinations with missing travel time, impute travel time based on a regression model using straight-line distance interacted with region and urban status as predictors.

· Cap commuting time to 4 hours

ONS also publishes self-reported estimates of commuting time in the Labour Force Survey (LFS). These take precedence as our best estimate of commuting time – the calculations used here are for the purposes of this analysis only.



For table 6, post-estimation calculations based on Cox proportional hazard model which include penalised splines for commuting time and hourly pay as well as additional covariates individual and job characteristics : age (second-order polynomial), hours worked (second-order polynomial), annual leave entitlement (second-order polynomial), occupation (at 2-digit level), sector ( public/private), number of employees (quintiles) living in an urban area, year, and Travel to Work Area. Models are estimated separately for men and women. Standard errors clustered at the individual level.






1 The straight-line distance is computed based on the postcode centroid, whereas the driving distance is computed based on the nearest road to the postcodes. Therefore, it is possible for the road distance to be lower than the straight-line distance. We therefore only discard travel time if the difference between road distance and the straight-line is lower than minus one kilometre

Contents
Median travel time (minutes) by gender, 2002 to 2018, GB
			95% Confidence intervals
Gender	Year	Median travel time	Lower bound	Upper bound
Male	2002	21.10	20.90	21.28
Male	2003	21.23	21.05	21.42
Male	2004	21.57	21.40	21.77
Male	2005	21.55	21.35	21.73
Male	2006	21.92	21.72	22.10
Male	2007	22.13	21.95	22.34
Male	2008	22.50	22.33	22.73
Male	2009	23.05	22.88	23.26
Male	2010	23.17	22.97	23.33
Male	2011	23.15	22.98	23.32
Male	2012	23.27	23.10	23.43
Male	2013	23.57	23.38	23.78
Male	2014	23.68	23.50	23.89
Male	2015	23.65	23.45	23.82
Male	2016	23.70	23.53	23.87
Male	2017	23.92	23.75	24.13
Male	2018	23.85	23.67	24.05

			95% Confidence intervals
Gender	Year	Median travel time	Lower bound	Upper bound
Female	2002	15.77	15.63	15.92
Female	2003	16.02	15.88	16.18
Female	2004	16.23	16.08	16.38
Female	2005	16.37	16.23	16.53
Female	2006	16.58	16.45	16.70
Female	2007	16.75	16.58	16.91
Female	2008	16.98	16.82	17.13
Female	2009	17.27	17.13	17.40
Female	2010	17.55	17.42	17.68
Female	2011	17.58	17.47	17.68
Female	2012	17.85	17.72	17.98
Female	2013	18.18	18.03	18.32
Female	2014	18.45	18.32	18.59
Female	2015	18.47	18.32	18.60
Female	2016	18.52	18.37	18.65
Female	2017	18.84	18.73	18.98
Female	2018	18.93	18.82	19.08
Source: Annual Survey of Hours and Earnings

1 Commuting time is estimated based on the home and work postcode via a trip planner app. The median is calculated using survey weights. The 95% confidence intervals of the weighted median, estimated via bootstrapping.

Related files

Share

Share to social media

Help

Login Area