Presented by Krishnan Viswanathan Cambridge Systematics, Inc. Co-authors Vidya Mysore, Florida Department of Transportation Nanda Srinivasan, Cambridge.

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Presentation transcript:

presented by Krishnan Viswanathan Cambridge Systematics, Inc. Co-authors Vidya Mysore, Florida Department of Transportation Nanda Srinivasan, Cambridge Systematics, Inc. May 7, 2007 Using LEHD Data for Travel Demand Models : The Florida Experience

1 Outline Motivation Longitudinal Employer Household Dynamics (LEHD) Description Some Comparisons FSUTMS Data Analysis Summary Future Directions

2 Motivation Review and possible use of LEHD and Employment data for travel demand modeling Current and future directions of Census and other available data sources for transportation Review of QCEW [Quarterly Census of Employment and Wages] (Employment data from AWI, state agency) and LEHD Data Data integration

3 LEHD Description LEHD combines federal and state administrative data on employers and employees with core Census Bureau censuses and surveys Local Employment Dynamics (LED) is a voluntary partnership between state labor market information agencies and the U.S. Census Bureau to develop new information about local labor market conditions

4 LEHD Description The data for LEHD will be based on Quarterly Census of Employment and Wages (QCEW/ES-202) Number of people employed and the wages paid to the employees each quarter Multi-establishment employers also provide individual worksite data Preliminary annual data are available in June and final annual data are available in October of each year. Quarterly data are available six months after the end of each quarter

5 LEHD Description Origin Destination Database Work Profile – block group # establishments # workers Worker distribution age earnings industry Demand/ Growth Indicators Job creation/loss Hires/separations Earnings hires/separations Home Block (U/I Wage Data) Workplace Block (QCEW Data) # of Workers (primary job) and # of Jobs Home Profile – block group # workers Worker distribution age earnings industry Acknowledgments : US Census Bureau

6 LEHD Description Origin Destination Database Year h_geocodefull w_geocodefull jobs_all jobs_prim jobs_priv_all jobs_priv_prim Year YYYY FIPS state, FIPS county; Census tract, Census block; home FIPS state, FIPS county; Census tract, Census block; work Number of jobs to which workers made this trip Number of primary jobs to which workers made this trip Number of private sector jobs to which workers made this trip Number of private sector primary jobs to which workers made this trip

7 LEHD Description OD with ACS: Possible Model for Integration Home Block (U/I Wage Data) Workplace Block (QCEW Data) # of Workers (primary job) and # of Jobs Home Profile – block group # workers Worker distribution age earnings industry Work Profile – block group # establishments # workers Worker distribution age earnings industry Demand/ Growth Indicators Job creation/loss Hires/separations Earnings hires/separations ACS Data Trip Time Mode Distance Acknowledgments : US Census Bureau

8 Some Comparisons An old well reviewed favorite – CTPP New kid on the block – LEHD North East Regional Planning Model (NERPM) region – Duval, St. Johns, Clay and Nassau Counties (Jacksonville is major city) CBD CTPPLEHD CTPP1.00 LEHD

9 Some Comparisons Travel Statistics Region TravelCTPPJOBS_PRIMARY Total : All resident workers in NERPM Region 519, ,702 Travel within NERPM region 509, ,951 Travel from NERPM region to CBD 49,460 46,366 Travel outside NERPM region 10, , percent (CTPP) vs. 77 percent (LEHD) travel within region Similar results in an earlier BTS Study by Cesar Singh Under a quarter of LEHD travel is outside the region Travel shares to CBD is approximately the same

10 Some Comparisons Residual Plot

11 Some Comparisons CBD Distance CTPP LEHD – Primary Jobs

12 Some Comparisons CBD Distance

13 FSUTMS Data Analysis Models Used QCEW Data Analysis Comparison between InfoUSA and QCEW data Results

14 Models Used 2005 NERPM CF Model 2000 Polk TPO Model

15 QCEW (ES202) Data Analysis December 2004 data used for analysis Data overlaid to TAZ Geocoded the data for address matching ZDATA2 data developed from QCEW Data Model Total QCEW Employment Lat/Long Information Available Geocoded to Model TAZ Address Matched to TAZ NERPM728,044487,954468, ,957 Polk438,190182,675169, ,370

16 Comparison between InfoUSA and QCEW Data NERPMQCEWInfoUSAModel MAN. INDUSTRIAL 113,00389,31854,903 OTHER INDUSTRIAL 34,69942,644137,255 COMMERCIAL 145,355126,640182,157 SERVICE 352, ,766420,058 TOTAL645,712533,368794,373 POLKQCEWInfoUSA Model (2000) INDUSTRIAL 41,13335,761 41,684 COMMERCIAL 179,46858,486 59,775 SERVICE 116,54099, ,611 TOTAL 337, , ,070

17 Results Model HBW TripsLEHD Primary Jobs

18 Results Model HBW TripsCTPP JTW Trips

19 Results Model HBW Trips LEHD Primary Jobs

20 Results Model HBW Trips CTPP JTW Trips

21 Summary Under reporting of internal trips Model results are reasonable QCEW data good source for employment data Issues regarding data suppression

22 Future Directions Potential data source for model calibration, more review of long distance trips to work Coordination effort for data aggregation with AWI Work with Census Bureau to produce LEHD for Florida model Variability of data over time

23 Acknowledgments Jim Baxter, Modeling Manager, FDOT District 1 Milton Locklear, Modeling Manager, FDOT District 2 Kathie Hughes, David Thurmond, AWI Pam Schenker, ex-AWI