Self-Employment in the United States: An Under-researched Topic Bill Beyers Dept. of Geography University of Washington Seattle Economists Club February 4, 2015

Overview of Presentation A brief look at background literature Alternative estimates of self-employment National trends in wage & salary and self- employment Geographic patterns of self-employment Changes in wage & salary and self- employment in the Great Recession

Background Literature Marshall & Wood lean on Christopherson’s work, viewing self-employment as an aspect of flexibility in the labor force. Rubalcaba viewed it as an employment opportunity, especially for women Dickson argues “Lone Rangers” are related to declining sectors, but questions if there are bases to reverse these declines Beyers & Lindahl’s “Lone Eagles” Various case studies BLS work based on the Current Population Survey; the U.S. Census nonemployer program; BEA proprietors/self employment estimates

Dawson, Henley & Latreille’s UK survey of motivations for self-employment

Data Sources BEA data online Series SA- 25 – Full & part-time employment by industry Series SA – 27 – full & part-time wage and salary employment by industry The difference between these two series is the level of self-employment by industry Data were developed for states in 1990, 2007, and 2011 Data also from Census Nonemployer Series and BLS estimates of self-employment from the Current Population Survey

U.S. Total Self Employment (1) BLS data exclude incorporated self-employed

U.S. Total Self-Employment (2) BLS data include incorporated self-employed

National Total Employment

Location Quotients – All self- employment BEA Alaska– 0.96 Hawaii – 0.93

Location Quotients BEA Producer Services 2011 Alaska – 0.73 Hawaii – 0.99

Location Quotients – BEA Arts, Entertainment and Recreational Services 2011 Alaska – 1.23

Shift-Share Analysis - BEA A technique that allows focus on changes in regions compared to national change Three models – ; ;

BEA Competitive Shift Alaska –0.9% Hawaii –0.6% Percentages are of total positive or negative shift values

BEA Competitive Shift Alaska -1.0% Hawaii -1.2% Percentages are of total positive or negative shift values

BEA Cluster Analysis Used Ward’s algorithm to define clusters of 6 industry groups for the year 2011 **** * Small clusters – only 3 states each

Cluster Classification of State Self- Employment BEA

Correlations Highly significant correlations for all comparisons. What does this mean regarding the choice of the data source used to measure proprietors activity? Should these federal agencies attempt to reconcile their measures of proprietors?

Self-Employment in the Great Recession The next few slides explore changes in self- employment by industry in the Great Recession While wage & salary employment had a steep decline, BEA’s measure of self-employment kept growing But there were different experiences by industry, as reported in the next slide

Change in Wage & Salary and Self- Employment

Finance Change WS & SE

Real Estate Change WS & SE

Administrative Services Change WS & SE

Arts, Entertainment and Recreation Industry Change W&S and SE

Other Services Change – WS & SE

Concluding Comments The rapid growth of self-employment in the U.S. has varied geographical patterns, and correlates with industry and other variables Little research has been reported on the geography of self-employment Earnings from self-employment still must be analyzed Business-cycles have impacts on patterns of self- employment growth There are clear differences in the level of self- employment reported by the 3 federal agencies, but their geographic concentration appears have similarities