High-quality employment data drawn from broad sectors of the economy are necessary for transportation planning, whether used for travel demand modeling or policy analysis. Availability of this data varies widely, however, as do the methods that the transportation community uses to combine, adjust, and manipulate employment data drawn from multiple sources. Some analysts begin with proprietary business lists and then use in-house staff to update and correct elements such as local government employment. Others rely on the latest Census Transportation Planning Products (CTPP) data at the workplace location; some have established a working relationship with their State Employment Security Department to obtain Quarterly Census of Employment and Wages (QCEW) micro-data files, and some rely on Longitudinal Employer-Household Dynamics (LEHD) data from the Census Bureau.
Another complication is that the transportation industry does not have a recognized standard for distinguishing, or even understanding the differences, among employment, jobs, labor force, and workers. Furthermore, the definitions used by the major national statistical agencies (including the OMB, Bureau of the Census, Bureau of Labor Statistics, Bureau of Economic Analysis, etc.) and their different statistical products (that are the sources of the statistics for labor force, employment, jobs and workers) need to be assembled and compared with differences evaluated and explained. This compilation will by necessity include workers in family and non-family households as well as group quarters.
Some in the transportation community are using data sets with a good understanding of what the data represent, how it is gathered, and what gaps exist. Still, little is known about the statistical reliability of the data sources, their stability over time, or their update cycles. Additionally, data are being manipulated to be used for purposes for which they were not gathered; QCEW data is collected for employment insurance, and routinely manipulated to be used as employment location data for individual workers, LEHD uses IRS home location to synthesize its population. In the current climate of confusion, clarity and information are more pressing than ever. As agencies move towards greater accountability in transportation planning, they need to have confidence in the information they produce and they need to know their data sources are reliable. In other words, the transportation community needs to examine potential data sources in an appropriate context for their planned use.
The objective of this research is to develop a resource guide for selecting and using employment data which will explain to practitioners the various types of employment and employer data that exist and can be used for transportation travel demand modeling purposes. The resource guide should explain the major differences among employment, jobs, labor force, and workers. Note, however, that this research is not a critical evaluation of vendor data.
This research further develops both the Census Bureau’s own research on the interactions between the worker estimates of American Community Survey and Current Population Survey and the information available in NCHRP 08-36, Task 98: Improving Employment Data for Transportation Planning report that looked at the publicly available sources - Quarterly Census of Employment and Wages (QCEW) collected by the Bureau of Labor Statistics (BLS), and two databases produced from the Census Bureau’s Longitudinal Employment Household Dynamics (LEHD) Program – the Quarterly Workforce Indicators (QWI) and OnTheMap (OTM).
Research Plan and Anticipated Work Tasks
The NCHRP is seeking the insights of proposers on how best to achieve the research objective. Proposers are expected to describe research plans that can realistically be accomplished within the constraints of available funds and contract time. Proposals must represent the proposers’ current thinking described in sufficient detail to demonstrate their understanding of the issues and the soundness of their approach in meeting the research objectives. The work proposed must be divided into tasks and proposers must describe the work proposed in each task in detail.
The research plan should build in appropriate checkpoints with the NCHRP project panel including a kick-off web-conference meeting to be held within one month of the contract’s execution date, and 1 additional webconference tied to panel review and NCHRP approval of any interim deliverables deemed appropriate. NCHRP will host all teleconferences.
At least 2 interim deliverables (not including the draft final deliverable(s) should be included in the work plan that collectively contains the following information at a minimum:
1. Literature review.
2. Survey plan. The survey effort should reach transportation agencies from jurisdictions of varying sizes. NCHRP approval of the survey plan is required prior to its implementation.
3. Detailed survey results.
4. An outline for the guidebook that addresses the structure and format of the resource guide, the topics to be addressed, and other relevant information.
Issues that should be addressed in the research include the following at a minimum (not in any priority order):
1. Common pitfalls and recommendations for how to review employment data when resources and time are scarce
2. A list of possible options if local employment data are not available.
- General information about employment, jobs, labor force, and worker data, including the cost of purchased data
- Validation methods used to confirm the “validity” or completeness of the data and whether this process is undertaken “in house” or contracted out
- Level of geography
- Source of the data (public or proprietary); if the data are proprietary, identify the geographic level(s) that can be shared publicly (i.e. can the data be shared at TAZ or other subarea level but not address level)
- Assessment of data quality
- How the number of employees per site is determined
- The range or actual count used
- Accurate addresses for geo-coding
- Individual branch or store locations as well as just headquarters locations
- Multiple business units that have different business functions
- Occupation code as opposed to the industry code
- Frequency of data collection and their update and/or /review cycle
- Any other data used to supplement the primary source to improve completeness or locational precision
- Want the right numbers of employees broken down by categories or NACE codes and in the right location. No one source is available. Different databases classify differently, and single industries have a variety of jobs.
- Double counting, e.g. hospital and doctors’ offices
- Databases whose ranges are not useful unless being used for comparisons.
- Need for transparency which may conflict with privacy requirements.
- Understanding the assumptions behind purchased data and whether the data are collected or modeled, e.g. Red Box and ATM treated like a video store and a bank respectively.
- An overview of the strengths and weaknesses of public and private datasets, including which datasets may compliment other datasets for certain uses.
- Primary advantages and limitations of the employment data.