EFFECTS OF HOUSEHOLD LIFE CYCLE CHANGES ON TRAVEL BEHAVIOR EVIDENCE FROM MICHIGAN STATEWIDE HOUSEHOLD TRAVEL SURVEYS 13th TRB National Transportation Planning.

Slides:



Advertisements
Similar presentations
1 Cooperation and conflict within couples: The gendered distribution of entitlement to household income GeNet Conference, Cambridge March 2009 Jérôme.
Advertisements

Employment transitions over the business cycle Mark Taylor (ISER)
Grandparenting and health in Europe: a longitudinal analysis Di Gessa G, Glaser K and Tinker A Institute of Gerontology, Department of Social Science,
Conference on Irish Economic Policy Union membership and the union wage Premium in Ireland Frank Walsh School of Economics University College Dublin
University as Entrepreneur A POPULATION IN THIRDS Arizona and National Data.
David Connolly & Lucy Barker MVA TRPG and SHS Topic Report Long Distance Commuting.
Norman Washington Garrick CE 2710 Spring 2014 Lecture 07
Risk of Low Birth Weight Associated with Family Poverty in Korea Bong Joo Lee Se Hee Lim Department of Social Welfare, Seoul National University. A Paper.
Are Gender Differences Emerging in the Retirement Patterns of the Early Boomers? Kevin E. Cahill Michael D. Giandrea Joseph F. Quinn June 30, th.
‘Klin’-ing up: reforming taxes on labour in Poland Michał Myck, DIW-Berlin (joint work with Leszek Morawski, WNE-UW)
Job Accessibility and Racial Differences in Youth Employment Rates Keith R. Ihlanfeldt, David L. Sjoquist The American Economic Review Volume 80, Issue.
1 Cooperation and conflict within couples: The gendered distribution of entitlement to household income ESPE Conference, Seville June 2009 Jérôme.
BACKGROUND RESEARCH QUESTIONS  Does the time parents spend with children differ according to parents’ occupation?  Do occupational differences remain.
The Characteristics of Employed Female Caregivers and their Work Experience History Sheri Sharareh Craig Alfred O. Gottschalck U.S. Census Bureau Housing.
Married Parents’ Time Use at Home, at Play, and with Children: Variations by Labor Force Status Ariel Kalil, Ph.D. and Kathleen M. Ziol-Guest, Ph.D. Harris.
Statistical Analysis SC504/HS927 Spring Term 2008 Week 17 (25th January 2008): Analysing data.
How Automatic Enrollment Affects the Likelihood and Distribution of 401(k) Contributions: Evidence from a National Survey Barbara Butrica and Nadia Karamcheva.
Opportunities & Challenges Using Passively Collected Data In Travel Demand Modeling 15 th TRB Transportation Planning Applications Conference Atlantic.
The third International Population Geography Conference Liverpool, June 2006 Proximity of adult children to their elderly parents in the Netherlands.
1 Health Status and The Retirement Decision Among the Early-Retirement-Age Population Shailesh Bhandari Economist Labor Force Statistics Branch Housing.
Comparison of Cell, GPS, and Bluetooth Derived External Data Results from the 2014 Tyler, Texas Study 15 th TRB National Transportation Planning Conference.
The Gender Gap in Educational Attainment: Variation by Age, Race, Ethnicity, and Nativity in the United States Sarah R. Crissey, U.S. Census Bureau Nicole.
STATISTICSSTATISTIQUECANADA Aboriginal Labour Force Survey Province of Alberta.
4th Russia-India-China Conference, New Dehli, November Entry to and Exit from Poverty in Russia: Evidence from Longitudinal Data Irina Denisova New.
Crosswalk Data Analysis Lynn White’s Stats Class Spring 2011 Add the names of all the team members to this first slide.
LABOR MARKET INDICATORS  Current Population Survey Every month, 1,600 interviewers working on a joint project of the Bureau of Labor Statistics (BLS)
Bureau of Transportation Statistics U.S. Department of Transportation Overall Travel Patterns of Older Americans Jeffery L. Memmott
Health Programme Evaluation by Propensity Score Matching: Accounting for Treatment Intensity and Health Externalities with an Application to Brazil (HEDG.
Employment, unemployment and economic activity Coventry working age population by disability status Source: Annual Population Survey, Office for National.
National Household Travel Survey Statewide Applications Heather Contrino Travel Surveys Team Lead Federal Highway Administration Office of Highway Policy.
Alicia H. Munnell, Geoffrey T. Sanzenbacher, and Matthew S. Rutledge Center for Retirement Research at Boston College 17 th Annual Meeting of the Retirement.
Why are White Nursing Home Residents Twice as Likely as African Americans to Have an Advance Directive? Understanding Ethnic Differences in Advance Care.
The Great Recession, the Social Safety Net, and Economic Security for Older Americans Richard W. Johnson and Karen E. Smith Urban Institute Presented at.
Transportation Planning, Transportation Demand Analysis Land Use-Transportation Interaction Transportation Planning Framework Transportation Demand Analysis.
Norman W. Garrick Transportation Forecasting What is it? Transportation Forecasting is used to estimate the number of travelers or vehicles that will use.
Presented to: Presented by: Transportation leadership you can trust. Second Day Response Rates: Implications for CMAP’s Travel Tracker Survey 13th TRB.
1 Things That May Affect Estimates from the American Community Survey.
Analysis of Time of Day Models from Various Urban Areas William G. Allen, Jr. Transportation Planning Consultant Windsor, SC TRB Transportation Planning.
Transit Service Quality and Transit Use: TBOT, Task 5.
HAOMING LIU JINLI ZENG KENAN ERTUNC GENETIC ABILITY AND INTERGENERATIONAL EARNINGS MOBILITY 1.
Peak Travel in America: Where Are We Going? 12 th Conference on Transportation Planning Applications Houston 2009 Nancy McGuckin, Travel Behavior Analyst.
Evaluating Transportation Impacts of Forecast Demographic Scenarios Using Population Synthesis and Data Simulation Joshua Auld Kouros Mohammadian Taha.
Irena Dushi, Alicia H. Munnell, Geoffrey T. Sanzenbacher, and Anthony Webb U.S. Social Security Administration and Center for Retirement Research at Boston.
Esteban Calvo, Kelly Haverstick, and Natalia A. Zhivan Center for Retirement Research at Boston College 11 th Annual Joint Conference of the Retirement.
TYBEE ISLAND TOURISM STUDY, OUTLINE 1.Introduction 2.Survey of Tybee Island Visitors 3.Visitor Expenditure Patterns 4.Estimated Annual Visitation.
Things that May Affect the Estimates from the American Community Survey Updated February 2013.
Modeling and Forecasting Household and Person Level Control Input Data for Advance Travel Demand Modeling Presentation at 14 th TRB Planning Applications.
Comparison of an ABTM and a 4-Step Model as a Tool for Transportation Planning TRB Transportation Planning Application Conference May 8, 2007.
Employment, unemployment and economic activity Coventry working age population by ethnicity Source: Annual Population Survey, Office for National Statistics.
VerdierView Graph # 1 OVERVIEW Problems With State-Level Estimates in National Surveys of the Uninsured Statistically Enhancing the Current Population.
Presented to Time of Day Panel presented by Krishnan Viswanathan, Cambridge Systematics, Inc. Jason Lemp, Cambridge Systematics, Inc. Thomas Rossi, Cambridge.
Effect on Model Sensitivities of Combining Transferable Data from Separate Home Interview Surveys Presented to the 11 th Conference on Transportation Planning.
1 Kuo-hsien Su, National Taiwan University Nan Lin, Academia Sinica and Duke University Measurement of Social Capital: Recall Errors and Bias Estimations.
The Financial Feasibility of Delaying Social Security Gopi Shah Goda Shanthi Ramnath John B. Shoven Sita Nataraj Slavov SIEPR/Sloan Working Longer Conference.
Analysis of Travel Behavior Using the ACS J.G. Berman, Siim S öö t and Susumu Kudo Urban Transportation Center, UIC.
Impact of Social Security Reform on Labor Force Participation: Evidence from Chile Alejandra C. Edwards and Estelle James Presented at AEI, November 2009.
“Firm Dynamics and Job Creation in Turkey" I.Atiyas, O.Bakis and Y.K.Orhan II. Girişim İstatistikleri Analizi Çalıştayı 27 Mart 2015.
Sources of Increasing Differential Mortality among the Aged by Socioeconomic Status Barry Bosworth, Gary Burtless and Kan Zhang T HE B ROOKINGS I NSTITUTION.
Kids these days Since the mid-2000s, car use and licensure declined in the US and peer countries, particularly among the young. We explore the dramatic.
Presented to Toll Modeling Panel presented by Krishnan Viswanathan, Cambridge Systematics, Inc.. September 16, 2010 Time of Day in FSUTMS.
ANALYSING EXPLANATORY FACTORS FOR HOUSEHOLD LEVEL TRIP GENERATION MODELLING GEO 6166 | TERM PROJECT NIKHIL MENON SPRING 2014 A CASE STUDY OF THE NETHERLANDS.
Kobe Boussauw – 15/12/2011 – Spatial Planning in Flanders: political challenges and social opportunities – Leuven Spatial proximity and distance travelled:
Modular 1. Introduction of the Course Structure and MyLabsPlus.
Intimate Partner Violence in Peru: An assessment of competing models Corey S. Sparks Alelhie Valencia Department of Demography Institute for Demographic.
Transportation Planning Asian Institute of Technology
Continuous Regional Travel Behaviour Survey
Leslie E. Papke Michigan State University
Impacts of Proxy Reporting in Household Surveys on Trip Rates
Norman Washington Garrick CE 2710 Spring 2016 Lecture 07
Model Work Trips Appropriately Based on Travel Behavior and Change Pattern Differences 2016HTS Characteristics and Changes vs. 2006HTS 16th TRB National.
Presentation transcript:

EFFECTS OF HOUSEHOLD LIFE CYCLE CHANGES ON TRAVEL BEHAVIOR EVIDENCE FROM MICHIGAN STATEWIDE HOUSEHOLD TRAVEL SURVEYS 13th TRB National Transportation Planning Applications Conference, Reno 2011 Ayvalik, C., Proussaloglou, K., Cambridge Systematics Faussett, K., MDOT, Bureau of Transportation Planning Wargelin, L., AbtSRBI

Introduction 2  MI Travel Counts II in 2009 (MTC II)  Earlier survey in 2005 (MTC I)  Changes in household travel behavior  Evidence for reduction in traffic volumes, and  Impacts of changes in household socioeconomic characteristics

Introduction 3  Panel design.  Nearly 2,000 households.  MTC I and MTC II participants.  Sampling cells considered  geography,  household size,  number of workers and  vehicles available. Upper Peninsula SEMCOG Small Urban Model Areas TMAs Small Cities Northern Lower Peninsula Southern Lower Peninsula

Background 4  Changes in household sizes  Age distribution  Employment Status

Research Objectives 5  Comparison of travel behavior: MTC I vs. MTC II  Evaluate the significance of observed changes  Nature of changes in travel behavior  Trip rates, trip lengths, peaking, and purpose  Factors that affect changes in travel behavior  Identify bias due to MTC II survey participation  Examine the explanatory power of key household level socioeconomic parameters.

Assessment of Bias 6  Are trip rates of the MTC II respondents in 2005 representative of the MTC I participants ?  Are trip lengths of the MTC II respondents in 2005 similar to the rest of the MTC I participants ?  Do the distributions of trips by time of day and purpose differ ? Comparisons focus travel behavior in 2005.

Bias – Trip Rates 7 Survey ParticipationNMeanStd Dev MTC I Only12, Both Surveys1, All14, ANOVA No Substantial Difference Comparison of Trip Rates by MTC II Participation

8 Average Travel Distances Survey ParticipationNMeanStd Dev MTC I Only10, Both Surveys1, All12, ANOVA No Substantial Difference Comparison of Travel Distances by MTC II Participation Bias – Travel Distances

9 TOD PeriodsMTC I OnlyBoth MTC Waves AM Peak6:00 AM – 8:59 AM19.40%18.60% Mid-Day9:00 AM – 2:59 PM33.60%33.80% PM Peak3:00 PM – 5:59 PM26.50%26.90% Evening6:00 PM – 8:59 PM15.10%15.70% Late Night9:00 PM – 5:59 AM5.50%5.00% Chi-Square Test No Substantial Difference Comparison of Trips by Time of Day and MTC II Participation Bias – Peaking Patterns

10 Trip PurposeMTC I OnlyBoth MTC Waves Home Based Work16.00%16.40% Home Based School9.60%7.90% Home Based Other41.30% Non-Home Based33.20%34.40% Chi-Square Test No Substantial Difference Comparison of Trips by Purpose and MTC II Participation Bias – Trip Purposes

MTC Waves 11  Are trip rates in the MTC I similar to the MTC II ?  Are trip length distributions in the MTC I similar to the MTC II ?  Can changes in the household socioeconomics explain the observed changes in trip rates ?  Focus is on the changes across waves.

MTC Waves - Trip Rates 12 Household Trip RatesMeanStd Dev MTC I Survey MTC II Survey Paired t-test Significant Difference  = 1.34 trips/hh Comparison of Trip Rates Across MTC Waves Consistent changes across geography

13 Average Travel Times (minutes) MeanStd Dev MTC I Survey MTC II Survey Paired t-test Non Significant Difference Comparison of Travel Distances Across MTC Waves MTC Waves – Travel Distances

Changes in Socioeconomics 14  Survey sampling cell definitions are a function of household socioeconomic characteristics.  The sample was divided into two groups based on whether the survey sampling cell has changed across waves.  These groups analyzed separately. MTC II Cell 1Cell 2…Cell n MTC I Cell 1 Cell 2 … Cell n  There is a significant difference in trip rates.  Can changes in socioeconomics explain these changes ?  How can we control socioeconomic characteristics ?

Household Sizes 15  27 percent of the households had a change in size  The average household size was reduced by about 8.5 percent (2.44 vs. 2.23). MTC II - Household Sizes MTC I - Household Sizes One- Person Two- Person Three- Person Four- Person or More All One-Person Two-Person Three-Person Four-Person or More All Percent Changed in MTC II 21.2%28.9%47.5%16.2%27.0%

Household Workers and Vehicles 16  39 percent of the households had a change.  Zero-worker households grew substantially.  One-third of the households had a change in vehicle ownership level; no net gain or loss in the sample. MTC II - Workers in the Household MTC I - Workers in the Household Zero- Worker One- Worker Two- Worker Three- Worker or More All Zero-Worker One-Worker Two-Worker Three-Worker or More All Percent Change in MTC II 40.7%35.8%34.1%73.7%38.6%

Trip Rate Comparison 17 Trip Rates for Same-Cell Households MeanStd Dev MTC I MTC II Same Cell Households Paired t-test Statistically Significant Difference (N=922, p=0.001)  Small but detectable level difference between the MTC waves still exists.

18 SourceF ValuePr > F HHSIZE <.0001 HHSIZE -95.6<.0001 HHWRKR HHSIZE - * HHWRKR Different Cell Households ANOVA Statistically Significant Model (N=1018, R 2 = 0.18)  Changes in the household size was a significant contributor.  Reduction in number of workers also had a marginal effect.  The effect was more prominent when coupled with reduction in the household size. Trip Rate Comparison

Life Cycle Cohorts 19  Sampling cell as a proxy still showed a detectable difference.  Household life cycle – to account for differences in trip rates.  13 distinct household level cohorts – to reflect various life cycle characteristics.  Sample divided into two groups – changes in life cycle.

Life Cycle Cohorts 20 1Unemployed Singles 2Professional Singles 3Professional Young Couples 4Professional Couples with Kids 5Traditional Family – (One Worker Couples with Kids) 6 Professional Seasoned Couples (Two Worker Couples older than 55) 7Homemaker-Breadwinner Couples (One Worker Couples) 8Retired Couples 9Retired Singles 10Non-Traditional Structure with Kids (Single parents and/or presence other relatives) 11Non-Traditional Structure with Kids No Workers 12Non-Traditional Structure with Workers No Kids 13Non-Traditional Structure No Workers No Kids

Analysis with Life Cycle Cohorts 21  Are the levels of change in trip rates equivalent across the life cycle cohorts ?  Can changes in life cycle cohorts explain differences in trip rates ?  What types of life cycle changes have the highest impact on household travel behavior ?

Same Life Cycle Households 22 Life Cycle and Demographic Variables P-values MTC Only MTC Wave  Changes in household sizes and vehicle ownership explained substantial amount of the difference in rates.  For retired couples trips were reduced significantly potentially due to changes in mobility levels. Life Cycle and Demographic Variables P-values MTC Only P-values Full MTC Wave MTC*Non-Traditional Structure with Workers No Kids*Increase in HH Size MTC*Retired Couples0.009 MTC*Non-Traditional Structure with Kids*Decrease in HH Size MTC*Retired Singles*Decrease in Vehicle Ownership 0.081

Households with Life Cycle Change 23 Life Cycle and Demographic Variables P-values MTC Only MTC Waves<.0001  Life cycle changes indicating variations in household size and workers explained differences in in trip rates across MTC waves.  Changes in non- traditional households had significant interaction effects with changes in household size and number of workers. Life Cycle and Demographic Variables P-values MTC Only P-values Full MTC Waves< MTC*Kids Moving Out<.0001 MTC*Separation<.0001 MTC*Complex Changes*Increase in the HH Size MTC*Complex Changes*Decrease in the HH Size MTC*Complex Changes0.011 MTC*Retirement0.017 MTC*Complex Changes*Decrease in the HH Workers MTC*Marriage0.034 MTC*Complex Changes*Kids Moving Out MTC*Lose Job0.059

Conclusions 24  MTC II study design allowed to build a panel data at the household level.  There is a statistically significant reduction in household trip rates across waves (1.34 trips/hh).  Are the observed changes due to sampling bias, changes in household structure, or in economic climate ?

Conclusions 25  No sampling bias found.  Main socioeconomic changes across the waves included slight increases in the shares of  smaller households  households with higher levels of vehicle ownership.  Higher shares for older age groups in MTC II.

Conclusions 26  When changes in socioeconomics are accounted for, differences in trip rates were partially explained.  “Retired Couples” had a statistically significant difference in household trip rates across the MTC waves.  changes in the economic conditions,  deteriorating health, or  restrictions in mobility.  Changes in household life cycles improved the explanatory power.

QUESTIONS 27