Labor Mobility and Industry Agglomeration: Silicon Valley (Part 5)
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One last case where we observe greater symmetry of information is in the automobile industry, particularly during its early period. During its initial stages, employees could easily learn innovations within the firm. One clear example of this was the set of knowledge spillovers relating to the assembly line. Henry Ford is usually credited with the invention of the assembly line; however, it was actually Ransom E. Olds, the founder of Olds Motor Vehicles Company, who invented it. Ford, who was actually a partner of Olds at some point and not an employee, copied the method and perfected it. Thus, we can conclude that at least in the early automobile industry, there was greater symmetry of information between employer and employees. However, as it is well known, the U. S. automobile heavily agglomerated in the Detroit area, and this agglomeration grew and persisted through time. Again, this fact contradicts the result that greater symmetry should result in less agglomeration.
Thus, we have that after relaxing the assumption of asymmetry made by Franco and Mitchell, less agglomeration should be the result in any industry, all other things being equal. However, three cases of industries with greater symmetry and highly agglomerated seem to contradict this result.
Data Source for Labor Mobility
Future investigation to test for the different attributes of agglomeration will require a rich data set, particularly with regards to labor mobility. Rebitzer (2006) uses the U. S. Census Bureau Current Population Survey, but it is merely a monthly survey and lacks the advantages of a longitudinal data set. Another data set, The Longitudinal Employer – Household Dynamics (LEHD) Program at the Census Bureau, has a collection of infrastructure files that provide detailed information of workers, employers, and their interaction in the US economy. Since 2003, the Census Bureau has published the Quarterly Workforce Indicators (QWI). This is a new collection of data series that offers details on the local dynamics of labor markets across industries (http://lehd. did. census. gov/led/datatools/qwiapp. html).
For each state, there are data on total employment, net job flows, job creation, new hires, separations and turnover sorted by industry, year, sex, and age group. For example, in California, the net job flows in software publishers industry was -1,090 in the fourth quarter of 2004. If more detailed information is needed, the variables can be narrowed down over particular subsets of the data. For example, in the California example, we can narrow the set down to only male workers aged from 25 to 34. The net job flow was then -269. Quite significantly for the purposes of studying agglomeration, the data have information for 20 industries under which there are a number of selectable sub-industries. The LEHD serves as an excellent data source from which to construct general panel data on labor mobility.
References:
Burdett, Ken, and Melvyn Coles, (Sep 2003): “Equilibrium Wage-Tenure Contracts,” Econometrica,Vol. 71, No. 5. pp. 1377-1404
Franco, April F. and Matthew F. Mitchell “Covenants not to compete, labor mobility, and industry dynamics,” working paper, University of Iowa.
Rebitzer, James (2006): “Job hopping in Silicon Valley: The microfoundations of a high tech industrial district. ” Review of Economics and Statistics, Vol. 88, No. 3, Pages 472-481.
Richard B. Freeman (1981) “The Effect of Unionism on Fringe Benefits”
Industrial and Labor Relations Review, Vol. 34, No. 4, pp. 489-509
James E. Long, Albert N. Link (1983) “The Impact of Market Structure on Wages, Fringe Benefits, and Turnover”, Industrial and Labor Relations Review, Vol. 36, No. 2, pp. 239-250
Olivia S. Mitchell (1983) “Fringe Benefits and the Cost of Changing Jobs”,
Industrial and Labor Relations Review, Vol. 37, No. 1, pp. 70-78
Dickens, F, Katz, A (1987) “Inter-industry Wage Differences and Industry Characteristics”, NBER WP: 2014
Pakes, Ariel and Saul Nitzan (1984), “Optimal Contracts for Research Personnel, Research Employment and Establishment of ‘Rival’ Enterprises,” Journal of Labor Economics, 1 (4), 345-65.
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