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Methodology


1) Methodology Used to Produce Economic Trends for U.S. Congressional, Ohio Senate, and Ohio House Districts, June 2016


The methodology for these estimates combines several data sources. The primary source of the employment estimates was the Census’ Longitudinal Employer-Household Dynamics (LEHD) data. The LEHD combines unemployment data with data from the Census Bureau’s American Community Survey, which provides estimates of both worker counts and worker demographics. For this project, LEHD estimates were supplemented with information from the Levin College of Urban Affairs’ Center for Economic Development (CED). CED edits and maintains a longitudinal database of the Quarterly Census of Employment and Wages (QCEW) for the state of Ohio. The QCEW data are derived from the state’s unemployment insurance tax data and contain establishment level employment, payroll, and industry classification.


Establishment counts, wages, and the percentage change of each of these data elements were added using the QCEW database. Methodological protocols were implemented in order to align both the LEHD and QCEW data series at a district and industry level. Data were assigned to a district based on geographic identifiers, i.e., address, zip code, community, and county.


 

 

2) Methodology Used to Produce Census American Community Survey (ACS) Estimates for U.S. Congressional and Ohio House and Senate Districts, June 2016


The 2010-2014 American Community Survey (ACS)1 provides demographic and socioeconomic estimates for U.S. Congressional and Ohio General Assembly districts. The ACS data provide the basic demographics of households, population, race, age, and gender and socioeconomic data such as income and educational attainment data.


The district data are produced from the ACS summary files, with new fields and percentages calculated as needed. The data are then ranked in descending order by percentage, or by the median in the case of median household income and median housing value.


The 2010-2014 estimates for the districts are based on a relatively large sample and, though margins of error are available, they are not provided in the tables.


1Census ACS 2010-2014 provides relatively recent estimates, but the sample size is much smaller than the long form 2000 SF3 sample. The 5 years of ACS data provide a sample that is only about one half the size of the 2000 SF3 sample; thus estimates are subject to wider confidence intervals.








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