Improved Employment Data for Transportation Planning

Transportation planners typically use census data or small sample surveys to help estimate work trips in metropolitan areas. Census data are cheap to use but are only collected every 10 years and may not provide the answers that a planner is seeking. On the other hand, small sample survey data are fresh but can be very expensive to collect. This project involved using database and geographic information systems (GIS) technology to relate several administrative data sources that are not usually employed by transportation planners. These data sources included data collected by state agencies for unemployment insurance purposes and for drivers licensing. Together, these data sources could allow better estimates of the following information for a metropolitan area or planning region: Locations of employers (work sites); · Locations of employees; · Travel flows between employees’ homes and their work locations. The required new employment database was created for a large, multi-county region in central Iowa. When evaluated against the estimates of a metropolitan planning organization, the new database did allow for a one to four percent improvement in estimates over the traditional approach. While this does not sound highly significant, the approach using improved employment data to synthesize home-based work (HBW) trip tables was particularly beneficial in improving estimated traffic on high-capacity routes. These are precisely the routes that transportation planners are most interested in modeling accurately. Therefore, the concept of using improved employment data for transportation planning was considered valuable and worthy of follow-up research. However, the exercise revealed some significant problems with using the current unemployment insurance and drivers license databases as a starting point: The original source data are maintained in formats that proved to be very cumbersome to use for the purposes of the project. These problems could potentially be overcome if the project were institutionalized on a continuing basis. · There are significant non-coverage and other problems with the databases; many businesses, work locations, and employees simply do not appear in the databases for various reasons. For example, about seven percent of all workers in the pilot area are self-employed and not covered by the unemployment insurance program. · There are significant address-related problems with the original databases and with baseline Iowa street addressing information that could be used in geocoding; this led to very serious errors in geocoding data for use in a GIS environment. Whether the address matching problems are generated by a poor street network, by addressing problems in the original source data, or by a combination of the two, “hit rates” for address matching of firm and employee locations are very poor in rural areas and in smaller towns and cities. Hit rates of 10 to 25 percent are not unusual in these locations. On the other hand, the overall hit rate was about 60 percent and the rate for large cities often approached an impressive 80 to 90 percent level. · Data will always need to be presented in an aggregate form to protect the confidentiality of both individuals and businesses. Confidentiality is a very serious concern with the new approach and must be dealt with in a systematic manner. All of these problems combine to diminish the usefulness of the new approach. However, even given the inherent flaws and limitations, these data would be highly useful for planning highways and public transit systems, and also for non-transportation uses such as workforce and economic development planning. For this reason, it is suggested that further effort go into four areas: · Institutionalizing the process of gathering, reducing, and merging the original source data to reduce development costs. This would be particularly helpful in the case of the Iowa Department of Transportation’s drivers license database. · Refining the original source data and street address utilities so many of the address-related and non-address related problems encountered in this research could be eliminated. This recommendation applies in particular to the Department of Workforce Development’s databases. · Overcoming problems with obtaining employment data for metro areas that cross state boundaries. This would be needed to implement improved employment data for transportation planning in several metro areas in Iowa, including Omaha/Council Bluffs, the Quad Cities, Dubuque, and Sioux City. · Developing additional procedures so that the improved data may be more readily used in transportation planning and for other planning purposes