Article Figures & Data
Figures
- Figure 1
Log Real Wages across Markets in CareerBuilder and BLS
Notes: This figure shows a kernel density plot of the log real wage for labor markets for the period 2010Q1–2013Q4 on CareerBuilder.com. The real wage is defined as the average wage across wage-posting vacancies in a given market and year–quarter, divided by the consumer price index for that year–quarter. The BLS plot corresponds to the log average wages from the Occupational Employment Statistics.
- Figure 2
Average HHI by Commuting Zone, Based on Vacancy Shares
Notes: This figure shows the average of the Herfindahl–Hirschman index by six-digit SOC occupation code for labor markets for the period 2010Q1–2013Q4. The categories we use for HHI concentration levels are: “Low”: HHI 0–1,500; “Moderate”: HHI 1,500–2,500; “High”: HHI 2,500–5,000; “Very High”: HHI 5,000–10,000. These categories correspond to the DOJ–FTC guidelines, except that we add the additional distinction between high and very high concentration levels around the 5,000 HHI threshold. Market shares are defined as the sum of vacancies posted in CareerBuilder.com by a given firm in a given market and year–quarter divided by total vacancies posted in the website in that market and year–quarter.
- Figure 3
Histogram ofHHIs Based on Application Shares and Vacancy Shares
Notes: This figure shows a histogram of the Herfindahl–Hirschman index for labor markets for the period 2010Q1–2013Q4. Market shares are defined as either the sum of vacancies posted in CareerBuilder.com by a given firm in a given market and year–quarter divided by total vacancies posted in the website in that market and year–quarter, or as the sum of applications (EOI) through the website to a given firm in a given market and year–quarter divided by the total number of applications to all firms in that market and year–quarter.
- Figure 4
Average HHI by Occupation, Based Vacancy Shares
Notes: This figure shows the average of the Herfindahl–Hirschman index by six-digit SOC occupation code for labor markets for the period 2010Q1–2013Q4. Market shares are defined as the sum of vacancies posted in CareerBuilder.com by a given firm in a given market and year–quarter divided by total vacancies posted in the website in that market and year–quarter.
- Figure 5
Binned Scatter of Log HHI Based on Vacancies and Log Real Wage
Notes: This figure shows a binned scatter plot of log HHI based on vacancy shares and log real wage in the same market, using 18 quantiles.
- Figure 6
Binned Scatter of Log HHI Based on Applications and Log Real Wage
Notes: This figure shows a binned scatter plot of log HHI based on application shares and log real wage in the same market, using 18 quantiles.
- Figure 7
Binned Scatter of Residualized Log HHI Based on Vacancies and Residualized Log Real Wage
Notes: This figure shows a binned scatter plot of the residuals of a regression of log HHI (based on vacancy shares) on log tightness, CZ-by-SOC fixed effects, and CZ-by-year–quarter fixed effects and the residuals of a regression of log real wage in the same market, also on log tightness, CZ-by-SOC fixed effects, and CZ-by-year–quarter fixed effects.
- Figure 8
Effect of Log HHI (Vacancies) on Log Real Wage by Commuting Zone Population Percentile
Notes: Estimated effect from a panel IV regression of log real wage on a fifth-order polynomial in log HHI (in terms of vacancies), instrumented with a fifth-order polynomial in average log 1/N in other commuting zones for the same occupation, controlling for log tightness, CZ-by-six-digit SOC fixed effects and time fixed effects. Data are for the period 2010Q1–2013Q4. We cluster standard errors at the market level.
- Figure 9
Binned Scatter of Residualized Log HHI Based on Vacancies and Residualized Log Real Wage, Cross-Sectional Variation
Notes: Panels A and B show binned scatter plots of the residuals of a regression of log HHI (based on vacancy shares) on log tightness, CZ fixed effects and SOC fixed effects, and the residuals of a regression of log real wage in the same market, also on log tightness, CZ fixed effects, and SOC fixed effects. The wages in Panel A are from CareerBuilder and in Panel B from the BLS Occupational Employment Statistics. Panels C and D show binned scatter plots of the residuals of a regression of the predicted first-stage log HHI (based on vacancy shares) on log tightness, CZ fixed effects, and SOC fixed effects, and the residuals of a regression of log real wage in the same market, also on log tightness, CZ fixed effects, and SOC fixed effects. The predicted first-stage log HHI refers to the predicted values from a first-stage IV regression of log HHI on the average log(1/N) for the same occupation in other markets, controlling for log tightness, CZ fixed effects, and SOC fixed effects. The wages in Panel C are from CareerBuilder and in Panel D from the BLS Occupational Employment Statistics.
Tables
SOC Code Occupation Description 11-3011 Administrative services managers 13-2011 Accountants and auditors 13-2051 Financial analysts 13-2052 Personal financial advisers 13-2053 Insurance underwriters 13-2061 Financial examiners 15-1041 Computer support specialists 17-2111 Health and safety engineers, except mining safety engineers and inspectors 17-2112 Industrial engineers 29-1111 Registered nurses 41-4011 Sales representatives, wholesale & manufacturing, technical & scientific products 41-9041 Telemarketers 43-3031 Bookkeeping, accounting, and auditing clerks 43-4051 Customer service representatives 43-6011 Executive secretaries and administrative assistants 43-6012 Legal secretaries 43-6013 Medical secretaries 43-6014 Secretaries and administrative assistants, except legal, medical, and executive 47-1011 First-line supervisors of construction trades and extraction workers 49-3041 Farm equipment mechanics 49-3042 Mobile heavy equipment mechanics, except engines 49-3043 Rail car repairers 51-1011 First-line supervisors/managers of production and operating workers 53-3031 Driver/sales workers 53-3032 Truck drivers, heavy and tractor-trailer 53-3033 Light truck or delivery services drivers Notes: This table shows the six-digit SOC occupations present in our sample.
Mean SD Min. Max. Obs. Real wage 41,547.36 36,216.76 4.71 5,504,385 61,017 Vacancies 82.95 224.39 1 17,928 61,017 Applications 3,612.96 14,416.02 0 528,289 61,017 Searches 441,156.09 1,385,720.05 0 7,880,8601 61,017 Log tightness -2.9 1.36 -7.64 4.48 60,200 Number of firms 20.03 35.78 1 571 61,017 HHI (vacancies, CZ quarterly)—baseline 3,157.02 2,923.92 66.04 10,000 61,017 HHI (applications, CZ quarterly) 3,480.17 3,061.03 0 10,000 61,017 HHI (vacancies, CZ monthly) 3,251.69 3,004.4 74.23 10,000 132,461 HHI (vacancies, CZ semesterly) 3,090.29 2,872.86 58.57 10,000 38,503 HHI (vacancies, CZ yearly) 2,970.47 2,780.11 51.91 10,000 24,060 HHI (vacancies, CZ whole period) 2,541.6 2,498.51 54.76 10,000 8,979 HHI (applications, CZ monthly) 3,790.37 31,32.18 0 10,000 132,461 HHI (applications, CZ semesterly) 3,315.38 3,017.08 0 10,000 38,503 HHI (applications, CZ yearly) 3,120 2,900.47 0 10,000 24,060 HHI (applications, CZ whole period) 2,722.97 2,653.19 0 10,000 8,979 HHI (vacancies, CZ quarterly, population-weighted) 1,690.74 1,942.09 66.04 10,000 61,013 HHI (applications, CZ quarterly, population-weighted) 1,848.51 2,127.09 0 10,000 61,013 HHI (vacancies, county quarterly) 4,222.52 3,331.36 76.09 10,000 111,109 HHI (applications, county quarterly) 4,563.85 3,369.67 0 10,000 111,109 HHI (vacancies, state quarterly) 1,358.48 1,634.58 64.01 10,000 15,124 HHI (applications, state quarterly) 1,458.09 1,781.24 0 10,000 15,124 Notes: This table shows summary statistics for our sample consisting of commuting zone–occupational code (six-digit SOC) labor markets over the period 2010Q1–2013Q4.
Dependent Variable: Log HHI (Vacancies) (1) (2) (3) Panel A: Market-Level Regressions Average log (1/N) in other markets 1.005*** 1.046*** 1.074*** (0.0344) (0.0323) (0.0340) Log tightness 0.171*** 0.198*** (0.00471) (0.00558) Market (CZ × six-digit SOC) FE ✓ ✓ ✓ year–quarter FE ✓ ✓ year–quarter FE × CZ FE ✓ Observations 59,485 58,642 56,679 R-squared 0.846 0.852 0.865 Dependent Variable: Log HHI (Vacancies) (1) (2) (3) (4) Panel B: Vacancy-Level Regressions Average log (1/N) in other markets 0.871*** 0.926*** 0.889*** 0.931*** (0.129) (0.124) (0.116) (0.0760) Log tightness 0.341*** 0.451*** 0.252*** (0.0162) (0.0186) (0.0146) CZ × six-digit SOC FE ✓ ✓ ✓ year–quarter FE ✓ ✓ ✓ year–quarter FE × CZ FE ✓ CZ × Job-title FE ✓ Observations 1,023,295 1,021,185 1,020,510 955,641 R-squared 0.902 0.913 0.928 0.948 Dependent Variable: Log(Real Wage) OLS IV (1) (2) (3) (4) (5) (6) (7) (8) Panel A: Market-Level Regressions Log HHI (vacancies) -0.103*** -0.0347*** -0.0399*** -0.0378*** -0.0300*** -0.141*** -0.143*** -0.127*** (0.00456) (0.00377) (0.00392) (0.00406) (0.00422) (0.0191) (0.0181) (0.0176) Log tightness 0.0113*** 0.0132*** 0.00686* 0.0283*** 0.0305*** (0.00320) (0.00357) (0.00360) (0.00427) (0.00479) year–quarter FE ✓ ✓ ✓ ✓ ✓ Market (CZ × six-digit SOC) FE ✓ ✓ ✓ ✓ ✓ ✓ ✓ year–quarter FE × CZ FE ✓ ✓ ✓ Year–Quarter FE × six-digit SOC FE ✓ Observations 61,017 59,485 58,642 56,679 56,677 59,485 58,642 56,679 R-squared 0.042 0.674 0.672 0.715 0.738 -0.018 -0.015 -0.012 Kleibergen–Paap F-stat 854.3 1051 996.7 Panel B: Vacancy-Level Regressions Log HHI (vacancies) -0.0327*** -0.0331*** -0.0314*** -0.0154*** -0.200*** -0.192*** -0.188*** -0.116*** (0.00453) (0.00476) (0.00500) (0.00377) (0.0398) (0.0361) (0.0370) (0.0184) Log tightness 0.000665 0.00429 0.00818*** 0.0540*** 0.0737*** 0.0315*** (0.00342) (0.00462) (0.00297) (0.0133) (0.0180) (0.00601) CZ × six-digit SOC FE ✓ ✓ ✓ ✓ ✓ ✓ year–quarter FE ✓ ✓ ✓ ✓ ✓ ✓ year–quarter FE × CZ FE ✓ ✓ CZ × job-title FE ✓ ✓ Observations 1,023,295 1,021,185 1,020,510 955,641 1,023,295 1,021,185 1,020,510 955,641 R-squared 0.533 0.533 0.541 0.849 0.522 0.524 0.534 0.847 Kleibergen–Paap F-stat 45.62 56.18 58.72 150.1 Dependent Variable: Log(Real Wage) (1) (2) (3) 
-0.141*** -0.149*** -0.137*** (0.0186) (0.0184) (0.0184) Log tightness 0.00387 0.00526 (0.00310) (0.00344) Market (CZ × six-digit SOC) FE ✓ ✓ ✓ year–quarter FE ✓ year–quarter FE × CZ FE ✓ Observations 59,485 58,642 56,679 R-squared 0.674 0.671 0.715 β (lower bound) -0.178 -0.177 -0.157 β (upper bound) 0.0362 0.0357 0.0349 γmax -0.105 -0.112 -0.100 Notes: Data are for the period 2010Q1–2013Q4. We consider the following model in which the instrument is not fully exogenous and therefore can enter in the second stage: log(wm,t) = β·logHHIm,t + γ·z + θ·Xm,t + αt + δm + εm,t, where z is our instrumental variable. We implement the plausibly exogenous instrument regression methodology as follows. We start by running reduced form OLS regressions analogous to our IV specifications, but including the instrument directly in the second stage instead of log HHI. The value of γ in the table refers to the coefficient of the instrument in this regression. We take
as the lower bound for the range of γ and zero as the upper bound, and then compute bounds for the coefficient on log HHI (β) using the plausibly exogenous regression methodology of Conley, Hansen, and Rossi (2010). We implement the methodology by (i) within-transforming all the variables (including the dependent variable, the regressors, and the instruments) by running regressions with each variable on the left-hand side and the corresponding set of fixed effects on the right-hand side, and taking the residuals as the transformed variables, and (ii) running the plausibly exogenous instrument regressions on the within-transformed variables using the plausexog command in Stata developed by Clarke (2017). We cluster standard errors at the market level. We also calculate the value of the lower bound for γ that would make the interval for β be fully to the left of zero. We call this value γmax.* p < 0.1,
** p < 0.05,
↵*** p < 0.01.
Dependent Variable: Log( Real Wage) Control for Vacancies Excluding HHI = 1 SOC-2 Job Titles OLS
(1)IV
(2)OLS
(3)IV
(4)OLS
(5)IV
(6)OLS
(7)IV
(8)Log HHI (vacancies) -0.0373*** -0.150*** -0.0377*** -0.131*** -0.0491*** -0.303*** -0.00644*** 0.0337 (0.00405) (0.0217) (0.00425) (0.0185) (0.00522) (0.0296) (0.00247) (0.0350) Log tightness 0.0127*** 0.0378*** 0.0135*** 0.0359*** 0.0181*** 0.0683*** -0.00673*** -0.0102*** (0.00374) (0.00604) (0.00424) (0.00582) (0.00504) (0.00765) (0.000772) (0.00237) Log vacancies 0.00208 -0.0143*** 0.00467 (0.00331) (0.00459) (0.00363) CZ FE × six-digit SOC FE ✓ ✓ ✓ ✓ ✓ ✓ year–quarter FE × CZ FE ✓ ✓ ✓ ✓ ✓ ✓ ✓ ✓ CZ × Job-title FE ✓ ✓ Observations 56,679 56,679 51,607 51,607 36,023 36,023 231,072 182,354 R-squared 0.715 0.709 0.709 0.705 0.675 -0.101 0.879 -0.002 Kleibergen–Paap F-stat 565.6 907.1 667.3 462.8 Notes: Data are for the period 2010Q1–2013Q4. We cluster standard errors at the market level. In IV specifications, we use as instrument the average of log(l/2V) for the same six-digit SOC occupation in other commuting zones. Robust standard errors in parentheses.
* p < 0.1,
** p < 0.05,
↵*** p < 0.01.
Dependent Variable: Log(Real Wage) 1/N
(1)HHI (EOI)
(2)County
(3)Cross-Section
(4)Cross-Section (BLS Wages)
(5)Fraction Posting Wage
(6)Search Tightness
(7)Log (1/N) -0.0882*** (0.0123) Log HHI (EOI) -0.102*** (0.0142) Log HHI (vacancies) -0.142*** -0.0927*** -0.0352*** -0.157*** -0.125*** (0.0153) (0.0156) (0.00555) (0.0231) (0.0185) Log tightness 0.00898*** 0.00301 0.0248*** 0.0300*** 0.00308 0.0325*** (0.00345) (0.00350) (0.00337) (0.00997) (0.00349) (0.00510) Fraction posting wage 0.147*** (0.0305) Log (vacancies/searches) 0.0252*** (0.0447) CZ FE × six-digit SOC FE ✓ ✓ ✓ ✓ year–quarter FE × CZ FE ✓ ✓ ✓ ✓ County FE × six-digit SOC FE ✓ year–quarter FE × county FE ✓ CZ FE ✓ ✓ Six-digit SOC FE ✓ ✓ Observations 56,679 56,679 94,714 8,895 6,228 56,679 57,383 R-squared 0.714 0.711 0.722 0.606 0.937 0.709 0.712 Kleibergen–Paap F-stat 2008 1973 1473 1546 1494 643 800.8 Notes: Data are for the period 2010Q1–2013Q4. We cluster standard errors at the market level. In all cases, we report results from a panel IV specification using the average of log(l/2V) for the same six-digit SOC occupation in other commuting zones.
* p < 0.1,
** p < 0.05,
↵*** p < 0.01.
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