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The effects of recreational cannabis access on labor markets: evidence from Colorado

Avinandan Chakraborty

Avinandan Chakraborty

Department of Economics, University of New MexicoAlbuquerque,
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Chakraborty, Avinandan
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Jacqueline Doremus

Jacqueline Doremus

Department of Economics, Orfalea College of Business, California Polytechnic State UniversitySan Luis Obispo,
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Doremus, Jacqueline
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Sarah Stith

Sarah Stith

Department of Economics, University of New MexicoAlbuquerque,
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Stith, Sarah
  
25 nov 2021
The effects of recreational cannabis access on labor markets: evidence from Colorado's Cover Image
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Publicado en línea: 25 nov 2021
Aceptado: 26 abr 2021
DOI: https://doi.org/10.2478/izajole-2021-0005
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© 2021 Avinandan Chakraborty et al., published by Sciendo
This work is licensed under the Creative Commons Attribution 4.0 International License.

Figure 1

Cannabis sales in Colorado counties, by year.Notes: (A) Sales of medical and recreational cannabis. Data were obtained from the Colorado Department of Revenue and are in U.S. dollars. (B) The number of new counties selling cannabis, based on sales data obtained from the Colorado Department of Revenue.
Cannabis sales in Colorado counties, by year.Notes: (A) Sales of medical and recreational cannabis. Data were obtained from the Colorado Department of Revenue and are in U.S. dollars. (B) The number of new counties selling cannabis, based on sales data obtained from the Colorado Department of Revenue.

Figure 2

Effect of recreational cannabis entry on the unemployment rate, Ln(labor force) and Ln(unemployed) – event study.Notes: The points represent the τk coefficient estimates from the estimation of Eq. (3), omitting τ−6. The bars extending from each point represent a 95% confidence interval calculated from the standard errors that are clustered at the county level. There are no standard error bars for the relative half-year k = −6 as the plot reflects that zero is imposed rather than estimated. The x-axis denotes time with respect to the commencement of the sale. Period 0 is when the sale begins. All regressions include county, month, and year fixed effects. Standard errors are clustered at the county level and are reported in parentheses.
Effect of recreational cannabis entry on the unemployment rate, Ln(labor force) and Ln(unemployed) – event study.Notes: The points represent the τk coefficient estimates from the estimation of Eq. (3), omitting τ−6. The bars extending from each point represent a 95% confidence interval calculated from the standard errors that are clustered at the county level. There are no standard error bars for the relative half-year k = −6 as the plot reflects that zero is imposed rather than estimated. The x-axis denotes time with respect to the commencement of the sale. Period 0 is when the sale begins. All regressions include county, month, and year fixed effects. Standard errors are clustered at the county level and are reported in parentheses.

Figure 3

Effect of recreational cannabis entry on Ln(employees), by industry – event study.Notes: The points represent the τk coefficient estimates from the estimation of Eq. (3), omitting τ−6. The bars extending from each point represent a 95% confidence interval calculated from the standard errors that are clustered at the county level. There are no standard error bars for the relative half-year k = −6 as the plot reflects that zero is imposed rather than estimated. The x-axis denotes time with respect to the commencement of the sale. Period 0 is when the sale begins. All regressions include county, month, and year fixed effects. Standard errors are clustered at the county level and are reported in parentheses.
Effect of recreational cannabis entry on Ln(employees), by industry – event study.Notes: The points represent the τk coefficient estimates from the estimation of Eq. (3), omitting τ−6. The bars extending from each point represent a 95% confidence interval calculated from the standard errors that are clustered at the county level. There are no standard error bars for the relative half-year k = −6 as the plot reflects that zero is imposed rather than estimated. The x-axis denotes time with respect to the commencement of the sale. Period 0 is when the sale begins. All regressions include county, month, and year fixed effects. Standard errors are clustered at the county level and are reported in parentheses.

Figure 4

Effect of recreational cannabis entry on Ln(wage), by industry – event study.Notes: The points represent the τk coefficient estimates from the estimation of Eq. (3), omitting τ−2. The bars extending from each point represent a 95% confidence interval calculated from the standard errors that are clustered at the county level. There are no standard error bars for the relative half-year k = −2 as the plot reflects that zero is imposed rather than estimated. The x-axis denotes time with respect to the commencement of the sale. Period 0 is when the sale begins. All regressions include county, month, and year fixed effects. Standard errors are clustered at the county level and are reported in parentheses.
Effect of recreational cannabis entry on Ln(wage), by industry – event study.Notes: The points represent the τk coefficient estimates from the estimation of Eq. (3), omitting τ−2. The bars extending from each point represent a 95% confidence interval calculated from the standard errors that are clustered at the county level. There are no standard error bars for the relative half-year k = −2 as the plot reflects that zero is imposed rather than estimated. The x-axis denotes time with respect to the commencement of the sale. Period 0 is when the sale begins. All regressions include county, month, and year fixed effects. Standard errors are clustered at the county level and are reported in parentheses.

Figure 5

The effect of recreational dispensary entry on the unemployment rate, Ln(labor force), and Ln(unemployed) – GSC.Notes: This figure shows the estimates for the main GSC results with the same set of controls as in the DID estimations. The x-axis denotes time with respect to the commencement of the sale. Period 0 is when dispensaries start selling. The path of counties where recreational sale started and counterfactuals are on the left column. The right column shows the difference between the two from the column in terms of months relative to the dispensary sale starting. The standard errors are bootstrapped, and in the mean squared prediction error (MSPE), there is an optimal number of unobserved factors (r*) selected from the model. DID, difference-in-differences; GSC, generalized synthetic control.
The effect of recreational dispensary entry on the unemployment rate, Ln(labor force), and Ln(unemployed) – GSC.Notes: This figure shows the estimates for the main GSC results with the same set of controls as in the DID estimations. The x-axis denotes time with respect to the commencement of the sale. Period 0 is when dispensaries start selling. The path of counties where recreational sale started and counterfactuals are on the left column. The right column shows the difference between the two from the column in terms of months relative to the dispensary sale starting. The standard errors are bootstrapped, and in the mean squared prediction error (MSPE), there is an optimal number of unobserved factors (r*) selected from the model. DID, difference-in-differences; GSC, generalized synthetic control.

Figure 6

The effect of recreational dispensary entry on employment – GSC.Notes: This figure shows the estimates for the main GSC results with the same set of controls as in the DID estimations. The x-axis denotes time with respect to the commencement of the sale. Period 0 is when dispensaries start selling. The path of counties where recreational sale started and counterfactuals are shown on the left column. The right column shows the difference between the two from the column in terms of months relative to the dispensary sale starting. The standard errors are bootstrapped, and in the mean squared prediction error (MSPE), there is an optimal number of unobserved factors (r*) selected from the model. DID, difference-in-differences; GSC, generalized synthetic control.
The effect of recreational dispensary entry on employment – GSC.Notes: This figure shows the estimates for the main GSC results with the same set of controls as in the DID estimations. The x-axis denotes time with respect to the commencement of the sale. Period 0 is when dispensaries start selling. The path of counties where recreational sale started and counterfactuals are shown on the left column. The right column shows the difference between the two from the column in terms of months relative to the dispensary sale starting. The standard errors are bootstrapped, and in the mean squared prediction error (MSPE), there is an optimal number of unobserved factors (r*) selected from the model. DID, difference-in-differences; GSC, generalized synthetic control.

Figure 7

The effect of recreational dispensary entry on wages – GSC.Notes: This figure shows the estimates for the main GSC results with the same set of controls as in the DID estimations. The x-axis denotes time with respect to the commencement of the sale. Period 0 is when dispensaries start selling. The path of counties where recreational sale started and counterfactuals are shown on the left column. The right column shows the difference between the two from the column in terms of quarters relative to the dispensary sale starting. The standard errors are bootstrapped, and in the mean squared prediction error (MSPE), there is an optimal number of unobserved factors (r*) selected from the model. DID, difference-in-differences; GSC, generalized synthetic control.
The effect of recreational dispensary entry on wages – GSC.Notes: This figure shows the estimates for the main GSC results with the same set of controls as in the DID estimations. The x-axis denotes time with respect to the commencement of the sale. Period 0 is when dispensaries start selling. The path of counties where recreational sale started and counterfactuals are shown on the left column. The right column shows the difference between the two from the column in terms of quarters relative to the dispensary sale starting. The standard errors are bootstrapped, and in the mean squared prediction error (MSPE), there is an optimal number of unobserved factors (r*) selected from the model. DID, difference-in-differences; GSC, generalized synthetic control.

Figure A1

State Cannabis Laws in 2018.Note: Data were obtained from the National Conference of State Legislatures.
State Cannabis Laws in 2018.Note: Data were obtained from the National Conference of State Legislatures.

Figure A2

Counties with cannabis-selling dispensaries.Note: The underlying data were obtained from the Colorado Department of Revenue.
Counties with cannabis-selling dispensaries.Note: The underlying data were obtained from the Colorado Department of Revenue.

Figure A3

Unemployment rate, Ln(labor force), and Ln(unemployed) over time.Note: The underlying data were obtained from the Local Area Unemployment Statistics.
Unemployment rate, Ln(labor force), and Ln(unemployed) over time.Note: The underlying data were obtained from the Local Area Unemployment Statistics.

Figure A4

Ln(employees) over time.Note: The underlying data were obtained from the Quarterly Census of Employment and Wages.
Ln(employees) over time.Note: The underlying data were obtained from the Quarterly Census of Employment and Wages.

Figure A5

Ln(wages) over time.Note: The underlying data were obtained from the Quarterly Census of Employment and Wages.
Ln(wages) over time.Note: The underlying data were obtained from the Quarterly Census of Employment and Wages.

Figure A6

Effect of recreational cannabis entry on the unemployment rate, Ln(labor force), and Ln(unemployed) – event study.Notes: The points represent the τk coefficient estimates from the estimation of Eq. (3), omitting τ−6. The bars extending from each point represent a 95% confidence interval calculated from the standard errors that are clustered at the county level. There are no standard error bars for the relative half-year k = −6 as the plot reflects that zero is imposed rather than estimated. The x-axis denotes time with respect to the commencement of the sale. Period 0 is when the sale begins. All regressions include county, month, and year fixed effects. Standard errors are clustered at the county level and reported in parentheses.
Effect of recreational cannabis entry on the unemployment rate, Ln(labor force), and Ln(unemployed) – event study.Notes: The points represent the τk coefficient estimates from the estimation of Eq. (3), omitting τ−6. The bars extending from each point represent a 95% confidence interval calculated from the standard errors that are clustered at the county level. There are no standard error bars for the relative half-year k = −6 as the plot reflects that zero is imposed rather than estimated. The x-axis denotes time with respect to the commencement of the sale. Period 0 is when the sale begins. All regressions include county, month, and year fixed effects. Standard errors are clustered at the county level and reported in parentheses.

Figure A7

Effect of recreational cannabis entry on Ln(employees) by industry – event study.Notes: The points represent the τk coefficient estimates from the estimation of Eq. (3), omitting τ−6. The bars extending from each point represent a 95% confidence interval calculated from the standard errors that are clustered at the county level. There are no standard error bars for the relative half-year k = −6 as the plot reflects that zero is imposed rather than estimated. The x-axis denotes time with respect to the commencement of the sale. Period 0 is when the sale begins. All regressions include county, month, and year fixed effects. Standard errors are clustered at the county level and reported in parentheses.
Effect of recreational cannabis entry on Ln(employees) by industry – event study.Notes: The points represent the τk coefficient estimates from the estimation of Eq. (3), omitting τ−6. The bars extending from each point represent a 95% confidence interval calculated from the standard errors that are clustered at the county level. There are no standard error bars for the relative half-year k = −6 as the plot reflects that zero is imposed rather than estimated. The x-axis denotes time with respect to the commencement of the sale. Period 0 is when the sale begins. All regressions include county, month, and year fixed effects. Standard errors are clustered at the county level and reported in parentheses.

Figure A8

Effect of recreational cannabis entry on Ln(wage) by industry – event study.Notes: The points represent the τk coefficient estimates from the estimation of Eq. (3), omitting τ−2. The bars extending from each point represent a 95% confidence interval calculated from the standard errors that are clustered at the county level. There are no standard error bars for the relative half-year k = −2 as the plot reflects that zero is imposed rather than estimated. The x-axis denotes time with respect to the commencement of the sale. Period 0 is when the sale begins. All regressions include county, month, and year fixed effects. Standard errors are clustered at the county level and reported in parentheses.
Effect of recreational cannabis entry on Ln(wage) by industry – event study.Notes: The points represent the τk coefficient estimates from the estimation of Eq. (3), omitting τ−2. The bars extending from each point represent a 95% confidence interval calculated from the standard errors that are clustered at the county level. There are no standard error bars for the relative half-year k = −2 as the plot reflects that zero is imposed rather than estimated. The x-axis denotes time with respect to the commencement of the sale. Period 0 is when the sale begins. All regressions include county, month, and year fixed effects. Standard errors are clustered at the county level and reported in parentheses.

Figure A9

Effect of recreational cannabis entry on the unemployment rate, Ln(labor force), and Ln(unemployed) – event study.Notes: The points represent the τk coefficient estimates from the estimation of Eq. (3), omitting τ−6. The bars extending from each point represent a 95% confidence interval calculated from the standard errors that are clustered at the county level. There are no standard error bars for the relative half-year k = −6 as the plot reflects that zero is imposed rather than estimated. The x-axis denotes time with respect to the commencement of the sale. Period 0 is when the sale begins. All regressions include county, month, and year fixed effects. Standard errors are clustered at the county level and reported in parentheses.
Effect of recreational cannabis entry on the unemployment rate, Ln(labor force), and Ln(unemployed) – event study.Notes: The points represent the τk coefficient estimates from the estimation of Eq. (3), omitting τ−6. The bars extending from each point represent a 95% confidence interval calculated from the standard errors that are clustered at the county level. There are no standard error bars for the relative half-year k = −6 as the plot reflects that zero is imposed rather than estimated. The x-axis denotes time with respect to the commencement of the sale. Period 0 is when the sale begins. All regressions include county, month, and year fixed effects. Standard errors are clustered at the county level and reported in parentheses.

Figure A10

Effect of recreational cannabis entry on Ln(employees) by industry – event study.Notes: The points represent the τk coefficient estimates from the estimation of Eq. (3), omitting τ−6. The bars extending from each point represent a 95% confidence interval calculated from the standard errors that are clustered at the county level. There are no standard error bars for the relative half-year k = −6 as the plot reflects that zero is imposed rather than estimated. The x-axis denotes time with respect to the commencement of the sale. Period 0 is when the sale begins. All regressions include county, month, and year fixed effects. Standard errors are clustered at the county level and reported in parentheses.
Effect of recreational cannabis entry on Ln(employees) by industry – event study.Notes: The points represent the τk coefficient estimates from the estimation of Eq. (3), omitting τ−6. The bars extending from each point represent a 95% confidence interval calculated from the standard errors that are clustered at the county level. There are no standard error bars for the relative half-year k = −6 as the plot reflects that zero is imposed rather than estimated. The x-axis denotes time with respect to the commencement of the sale. Period 0 is when the sale begins. All regressions include county, month, and year fixed effects. Standard errors are clustered at the county level and reported in parentheses.

Figure A11

Effect of recreational cannabis entry on Ln(wage) by industry – event study.Notes: The points represent the τk coefficient estimates from the estimation of Eq. (3), omitting τ−2. The bars extending from each point represent a 95% confidence interval calculated from the standard errors that are clustered at the county level. There are no standard error bars for the relative half-year k = −2 as the plot reflects that zero is imposed rather than estimated. The x-axis denotes time with respect to the commencement of the sale. Period 0 is when the sale begins. All regressions include county, month, and year fixed effects. Standard errors are clustered at the county level and reported in parentheses.
Effect of recreational cannabis entry on Ln(wage) by industry – event study.Notes: The points represent the τk coefficient estimates from the estimation of Eq. (3), omitting τ−2. The bars extending from each point represent a 95% confidence interval calculated from the standard errors that are clustered at the county level. There are no standard error bars for the relative half-year k = −2 as the plot reflects that zero is imposed rather than estimated. The x-axis denotes time with respect to the commencement of the sale. Period 0 is when the sale begins. All regressions include county, month, and year fixed effects. Standard errors are clustered at the county level and reported in parentheses.

Figure A12

The effect of recreational dispensary entry on the unemployment rate, Ln(labor force), and Ln(unemployed) – GSC.Notes: This figure shows the estimates for the main GSC results with the same set of controls as in the DID estimations. The x-axis denotes time with respect to the commencement of the sale. Period 0 is 1 year after dispensaries started selling. The path of counties where recreational sale started and counterfactuals are shown on the left column. The right column shows the difference between the two from the column in terms of months relative to the dispensary sale starting. The standard errors are bootstrapped, and in the mean squared prediction error (MSPE), there is an optimal number of unobserved factors (r*) selected from the model. DID, difference-in-differences; GSC, generalized synthetic control.
The effect of recreational dispensary entry on the unemployment rate, Ln(labor force), and Ln(unemployed) – GSC.Notes: This figure shows the estimates for the main GSC results with the same set of controls as in the DID estimations. The x-axis denotes time with respect to the commencement of the sale. Period 0 is 1 year after dispensaries started selling. The path of counties where recreational sale started and counterfactuals are shown on the left column. The right column shows the difference between the two from the column in terms of months relative to the dispensary sale starting. The standard errors are bootstrapped, and in the mean squared prediction error (MSPE), there is an optimal number of unobserved factors (r*) selected from the model. DID, difference-in-differences; GSC, generalized synthetic control.

Figure A13

The effect of recreational dispensary entry on employment – GSC.Notes: This figure shows the estimates for the main GSC results with the same set of controls as in the DID estimations. The x-axis denotes time with respect to the commencement of the sale. Period 0 is 1 year after dispensaries started selling. The path of counties where recreational sale started and counterfactuals are on the left column. The right column shows the difference between the two from the column in terms of months relative to the dispensary sale starting. The standard errors are bootstrapped, and in the mean squared prediction error s(MSPE), there is an optimal number of unobserved factors (r*) selected from the model. DID, difference-in-differences; GSC, generalized synthetic control.
The effect of recreational dispensary entry on employment – GSC.Notes: This figure shows the estimates for the main GSC results with the same set of controls as in the DID estimations. The x-axis denotes time with respect to the commencement of the sale. Period 0 is 1 year after dispensaries started selling. The path of counties where recreational sale started and counterfactuals are on the left column. The right column shows the difference between the two from the column in terms of months relative to the dispensary sale starting. The standard errors are bootstrapped, and in the mean squared prediction error s(MSPE), there is an optimal number of unobserved factors (r*) selected from the model. DID, difference-in-differences; GSC, generalized synthetic control.

Figure A14

The effect of recreational dispensary entry on wages – GSC.Notes: This figure shows the estimates for the main GSC results with the same set of controls as in the DID estimations. The x-axis denotes time with respect to the commencement of the sale. Period 0 is 1 year after dispensaries started selling. The path of counties where recreational sale started and counterfactuals are on the left column. The right column shows the difference between the two from the column in terms of quarter relative to the dispensary sale starting. The standard errors are bootstrapped, and in the mean squared prediction error (MSPE), there is an optimal number of unobserved factors (r*) selected from the model. DID, difference-in-differences; GSC, generalized synthetic control.
The effect of recreational dispensary entry on wages – GSC.Notes: This figure shows the estimates for the main GSC results with the same set of controls as in the DID estimations. The x-axis denotes time with respect to the commencement of the sale. Period 0 is 1 year after dispensaries started selling. The path of counties where recreational sale started and counterfactuals are on the left column. The right column shows the difference between the two from the column in terms of quarter relative to the dispensary sale starting. The standard errors are bootstrapped, and in the mean squared prediction error (MSPE), there is an optimal number of unobserved factors (r*) selected from the model. DID, difference-in-differences; GSC, generalized synthetic control.

Descriptive statistics by treatment status

All counties Selling Not selling Differences
Before After Before After Diff Diff Diff
(1) (2) (3) (4) (5) (6) = (3)–(2) (7) = (5)–(4) (8) = (6)–(7)
Panel A: monthly
Unemployment rate, % 5.23 7.86 3.59 7.09 3.49 −4.268** −3.605** −0.663**
6,144 1,604 1,948 972 1,620
Ln(labor force) 9.11 9.48 9.74 8.38 8.43 0.258** 0.048 0.21**
6,144 1,604 1,948 972 1,620
Ln(unemployed) 6.02 6.89 6.35 5.68 4.99 −0.539** −0.691** 0.152**
6,144 1,604 1,948 972 1,620
Ln(all industry employees) 8.76 9.11 9.42 8.03 8.07 0.318** 0.035 0.282**
6,144 1,604 1,948 972 1,620
Ln(construction employees) 6.51 6.50 6.94 5.94 6.01 0.436** 0.072 0.364**
4,608 1,416 1,752 540 900
Ln(manufacturing sector employees) 6.31 6.06 6.53 6.32 6.31 0.470** −0.007 0.477**
3,936 1,281 1,503 432 720
Ln(natural resource and mining employees) 5.78 5.86 5.96 5.55 5.59 0.105 0.046 0.059**
4,608 1,274 1,510 684 1,140
Ln(service-providing employees) 8.17 8.58 8.93 7.31 7.36 0.349** 0.056 0.293**
6,144 1,604 1,948 972 1,620
Panel B: quarterly
Ln(all industry wages) 6.59 6.55 6.67 6.49 6.59 0.119** 0.097** 0.021**
2,048 527 657 324 540
Ln(construction wages) 6.76 6.73 6.84 6.63 6.71 0.116** 0.075* 0.041**
1,536 466 590 180 300
Ln(manufacturing wages) 6.70 6.62 6.76 6.65 6.74 0.137** 0.091+ 0.046**
1,312 421 507 144 240
Ln(natural resource and mining wages) 6.87 6.86 6.98 6.74 6.82 0.119** 0.081+ 0.038**
1,536 419 509 228 380
Ln(service-providing wages) 6.49 6.44 6.57 6.40 6.50 0.125** 0.098** 0.027**
2,048 527 657 324 540

The effect of recreational dispensary entry – ATT from GSCM

Unrate Ln(labor force) Ln(unemp)
(1) (2) (3)
Start of sales
Recreational sale −0.566* (0.4191) 0.024 (0.0334) −0.006 (0.0332)
Ln(number of medical patients) 0.018 (0.2547) −0.010* (0.0084) 0.043 (0.0713)
Observations 6,144 6,144 6,144

The effect of recreational dispensary entry on employment – ATT from GSCM

Ln(All) Ln(Cons) Ln(Manu) Ln(NR) Ln(Service)
(1) (2) (3) (4) (5)
Start of sales
Recreational sale −0.035 (0.0203) −0.120 (0.0804) 0.137** (0.0562) −0.298 (0.1314) 0.042 (0.0587)
Ln(number of medical patients) 0.001 (0.0148) −0.502 (0.2495) 0.097 (0.1150) −0.010 (0.0894) 0.007 (0.0229)
Observations 6,144 4,608 3,936 4,608 6,144

Sources for our variable of interest

Variable type Source Chronology
Unemployed, Labor force, and Unemployment rate (2011–2018) Local Area Unemployment Statistics (LAUS)
Employees and wages (2011–2018) Quarterly Census of Employment and Wages (QCEW)
Recreational cannabis sales (2014–2018) Colorado Department of Revenue (CDOR)
Medical cannabis patients (2011–2018) Colorado Department of Public Health and Environment (CDPHE)
Population (2011–2018) United States Census Bureau

The effect of recreational dispensary entry and sales on employment – regression analysis

All Cons Manu NR Service
(1) (2) (3) (4) (5)
Panel A: amount of sales
Recreational sale 0.054* (0.0223) 0.065 (0.0754) 0.094 (0.0700) −0.007 (0.1125) 0.035+ (0.0205)
Recreational sale=1 × < 70 km not-sellingmy=1 −0.014 (0.0221) −0.010 (0.0682) 0.048 (0.0726) −0.011 (0.1112) 0.005 (0.0198)
Ln(number of medical patients) −0.021 (0.0153) −0.173+ (0.0946) −0.195** (0.0648) 0.173 (0.1135) −0.027 (0.0184)
R2 0.998 0.989 0.996 0.970 0.998
Observations 6,144 4,608 3,936 4,608 6,144

County-level summary statistics

Mean SD Min Max N
Panel A: monthly
Unemployment rate (%) 5.23 2.77 1.1 17.4 6,144
Labor force 44,682 90,397 273 417,717 6,144
Unemployed 2,268 5,017 7 33,083 6,144
All industry employees 37,909 84,671 195 524,919 6,144
Construction employees 2,720 5,099 14 24,163 4,992
Manufacturing sector employees 2,929 5,427 10 21,436 4,512
Natural resource and mining employees 802 1,821 8 13,120 5,088
Service-providing employees 26,692 62,824 81 401,921 6,144
Amount of recreational sales 629,296 2,712,311 0 35,343,772 6,144
Number of medical patients 1,622 3,568 2 20,976 6,144
Panel B: quarterly
All industry wages 749.06 200.83 410 2,102 2,048
Construction wages 881.75 227.47 415 2,489 1,664
Manufacturing wages 844.94 339.17 310 2,650 1,504
Natural resource and mining wages 1,071.30 641.53 376 6,475 1,696
Service-providing wages 684.91 216.46 294 2,619 2,048

Event study estimates post-dispensary entry periods for wages, by industry

All Cons Manu NR Service
(1) (2) (3) (4) (5)
event0:treat −0.005 −0.017 −0.006 0.033 0.000
event1:treat 0.008 0.041+ 0.028 0.033 0.009
event2:treat −0.018* −0.018 −0.018 −0.020 −0.003
event3:treat 0.007 0.010 0.005 0.008 0.010
event4:treat 0.011 −0.016 −0.002 0.029 0.015
event5:treat 0.018 0.007 0.026 0.034 0.014
event6:treat 0.004 −0.010 0.027 −0.011 0.012
event7:treat 0.023* 0.010 0.059* −0.027 0.020
event8:treat 0.006 0.012 0.042 0.034 −0.005
event9:treat 0.030* 0.033 0.051 0.025 0.013
event10:treat 0.027* 0.030 0.026 0.045 0.017
event>10:treat 0.018 0.029 0.023 0.039 −0.004
Linear combination
  Coefficient 0.011 0.009 0.022 0.019 0.008
  SE 0.0076 0.0239 0.0265 0.0269 0.0093
Weighted linear combination
  Coefficient 0.013 0.017 0.022 0.026 0.004
  SE 0.0092 0.0314 0.0298 0.0323 0.0105
R2 0.938 0.780 0.933 0.910 0.925
Observations 2,048 1,536 1,312 1,536 2,048

Event study estimates post-dispensary entry periods

Unrate Ln(labor force) Ln(unemp)
(1) (2) (3)
event0:treat 0.382* 0.041* 0.113**
event1:treat 0.320+ 0.043* 0.093**
event2:treat 0.440 0.041* 0.112*
event3:treat 0.179 0.031+ 0.064+
event4:treat 0.192 −0.007 0.025
event5:treat −0.224 −0.003 −0.062**
event6:treat −0.283+ 0.001 −0.060**
event7:treat −0.300 0.009 −0.066*
event8:treat −0.373 0.013 −0.087**
event9:treat −0.486* 0.015 −0.103**
event10:treat −0.393 0.016 −0.085*
event11:treat −0.564* 0.036* −0.105**
event12:treat −0.026 0.040+ 0.042
event13:treat −0.119 0.038+ 0.012
event14:treat 0.133 0.030 0.039
event15:treat 0.058 0.023 0.014
event16:treat 0.227 −0.014 0.010
event17:treat −0.092 −0.014 −0.081*
event18:treat −0.126 −0.011 −0.099**
event19:treat −0.246 −0.004 −0.137**
event20:treat −0.163 −0.004 −0.117**
event21:treat −0.302 −0.003 −0.132**
event22:treat −0.266 −0.002 −0.119**
event23:treat −0.411 0.024 −0.140**
event24:treat −0.263 0.021 −0.030
event25:treat −0.249 0.023 −0.028
event26:treat 0.098 0.019 0.036
event27:treat 0.143 0.008 0.029
event28:treat 0.195 −0.026 −0.000
event29:treat 0.051 −0.017 −0.035
event30:treat 0.040 −0.010 −0.046
event31:treat −0.024 −0.002 −0.069+
event32:treat 0.050 −0.003 −0.058
event33:treat −0.191 −0.003 −0.109**
event34:treat −0.341 −0.003 −0.157**
event35:treat −0.524+ 0.021 −0.200**
event36:treat −0.412 0.015 −0.048
event37:treat −0.499+ 0.019 −0.079**
event38:treat −0.309 0.015 −0.091
event39:treat −0.266 0.011 −0.096*
event40:treat −0.023 −0.024 −0.052
event>40:treat 0.037 −0.002 −0.020
Linear combination
  Combo coefficient −0.117 0.010 −0.046*
  Combo SE 0.2257 0.0139 0.0212
Weighted linear combination
  Combo coefficient −0.073 0.006 −0.038+
  Combo SE 0.2433 0.0148 0.0218
R2 0.880 0.999 0.996
Observations 4,512 4,512 4,512

The effect of recreational dispensary entry and sales on the unemployment rate, Ln(labor force), and Ln(unemployed) – regression analysis

Unrate Ln(labor force) Ln(unemp)
(1) (2) (3)
Panel A: start of sales
Recreational sale −0.718** (0.2428) −0.014 (0.0105) −0.078** (0.0200)
Ln(number of medical patients) −0.607* (0.2714) 0.001 (0.0111) −0.021 (0.0250)
Ln(population) 1.158 (2.4361) 0.531** (0.1261) 0.338+ (0.1900)
R2 0.882 0.999 0.995
Observations 6,144 6,144 6,144
Panel B: amount of sales
$0 < sales ≤$500,000 (0.2720) −0.752** (0.0099) −0.009 (0.0224) −0.066**
Sales >$500,000 (0.2515) −0.669** (0.0125) −0.021 (0.0251) −0.094**
Ln(number of medical patients) −0.601** (0.2737) 0.000 (0.0108) −0.023 (0.0260)
Ln(population) 1.069 (2.4483) 0.543** (0.1276) 0.369+ (0.1872)
R2 0.882 0.999 0.995
Observations 6,144 6,144 6,144

Event study estimates post-dispensary entry periods for employees, by industry

All Cons Manu NR Service
(1) (2) (3) (4) (5)
event0:treat 0.020 0.017 0.010 0.028 0.024
event1:treat 0.020 0.027 0.006 0.003 0.028
event2:treat 0.017 0.033 0.016 0.020 0.013
event3:treat 0.013 0.032 0.029 0.020 0.006
event4:treat 0.008 0.052+ 0.030 −0.010 0.008
event5:treat 0.015 0.058+ 0.036 0.001 0.018
event6:treat 0.019* 0.050+ 0.030 0.006 0.023**
event7:treat 0.028* 0.042 0.070 0.037 0.027*
event8:treat 0.025+ 0.057* 0.077 0.025 0.026
event9:treat 0.031+ 0.073* 0.093+ 0.020 0.031
event10:treat 0.031 0.093* 0.103* 0.036 0.028
event11:treat 0.048* 0.090* 0.108* 0.030 0.050*
event12:treat 0.052* 0.096+ 0.123* 0.049 0.052+
event13:treat 0.051* 0.088 0.123* 0.053 0.051+
event14:treat 0.044+ 0.072 0.117* 0.069 0.036
event15:treat 0.039+ 0.056 0.126* 0.051 0.036
event16:treat 0.030+ 0.063 0.140** 0.025 0.028
event17:treat 0.039** 0.071 0.152** 0.008 0.037**
event18:treat 0.039** 0.063 0.152** 0.002 0.035**
event19:treat 0.047** 0.046 0.154** 0.006 0.041**
event20:treat 0.044** 0.060 0.160** 0.020 0.038*
event21:treat 0.050** 0.079 0.161** 0.001 0.045*
event22:treat 0.049* 0.080 0.163** −0.010 0.045+
event23:treat 0.066** 0.070 0.158** 0.002 0.066*
event24:treat 0.070** 0.106 0.173** 0.029 0.064*
event25:treat 0.072** 0.090 0.169** 0.013 0.067*
event26:treat 0.063** 0.098 0.172** 0.029 0.051+
event27:treat 0.062** 0.089 0.175** 0.048 0.050*
event28:treat 0.048* 0.101 0.188** 0.034 0.034
event29:treat 0.057** 0.112 0.197** 0.012 0.047**
event30:treat 0.057** 0.102 0.188** −0.003 0.033+
event31:treat 0.063** 0.085 0.185** 0.009 0.040+
event32:treat 0.059** 0.093 0.180** 0.019 0.036
event33:treat 0.067** 0.103 0.189** 0.017 0.054*
event34:treat 0.059* 0.114 0.197** 0.027 0.060*
event35:treat 0.074** 0.103 0.189** 0.042 0.077**
event36:treat 0.073** 0.122 0.179** 0.065 0.067*
event37:treat 0.070** 0.115 0.180** 0.044 0.067*
event38:treat 0.066** 0.117 0.184** 0.062 0.055+
event39:treat 0.067** 0.113 0.193** 0.060 0.057+
event40:treat 0.062** 0.123 0.195** 0.071 0.043
event>40:treat 0.076** 0.107 0.171** 0.105 0.054+
Linear combination
  Coefficient 0.047* 0.080 0.134** 0.028 0.042*
  SE 0.0145 0.0542 0.0333 0.0563 0.0188
Weighted linear combination
  Coefficient 0.054** 0.086 0.142** 0.046 0.044*
  SE 0.0154 0.0657 0.0328 0.0642 0.0204
R2 0.998 0.989 0.996 0.970 0.998
Observations 6,144 4,608 3,936 4,608 6,144

Effect of preexisting county-level economic conditions on dispensary entry

Dependent variable=Rcmy 6-month change 1-year change
Pop change 0.000* (0.0000) 0.000 (0.0000)
Unrate change 0.013* (0.0050) 0.039* (0.0191)
Ln(labor force change) −0.049 (0.0497) −0.379 (0.3405)
Ln(Unemp change) 0.021 (0.0256) −0.005 (0.0554)
Ln(All Emp change) 0.007 (0.0345) −0.032 (0.1537)
Ln(Cons Emp change) 0.022 (0.0478) 0.026 (0.0593)
Ln(Manu Emp change) 0.097 (0.0839) 0.149 (0.0926)
Ln(NR Emp change) 0.028 (0.0381) 0.030 (0.0874)
Ln(Service Emp change) −0.002 (0.0186) −0.122 (0.1650)
Ln(All wage change) 0.053 (0.0549) 0.084 (0.1125)
Ln(Cons wage change) 0.022 (0.0473) 0.019 (0.080)
Ln(Manu wage change) −0.009 (0.0407) −0.028 (0.0875)
Ln(NR wage change) −0.011 (0.019) −0.100 (0.0697)
Ln(Service wage change) −0.024 (0.0310) −0.001 (0.1016)

Multiple inference – adjusted p–value

Dependent variable p–value Sharpened q–values
Panel A: monthly
Unemployment rate 0.009** 0.024*
Ln(labor force) 0.915 1
Ln(unemployed) 0.001** 0.007**
Ln(all industry employees) 0.005** 0.019*
Ln(construction employees) 0.292 0.638
Ln(manufacturing sector employees) 0.001** 0.007**
Ln(natural resource and mining employees) 0.823 1
Ln(service–providing employees) 0.015* 0.031*
Panel B: quarterly
Ln(All industry wages) 0.952 1
Ln(Construction wages) 0.761 1
Ln(Manufacturing wages) 0.594 1
Ln(Natural resource and mining wages) 0.424 0.941
Ln(Service–providing wages) 0.74 1

Effect of recreational dispensary entry and sales on the unemployment rate (Unrate), Ln(labor force), and Ln(unemployed) – regression analysis

Unrate Ln(labor force) Ln(unemp)
(1) (2) (3)
Panel A: start of sales
Recreational sale −0.684** (0.2522) 0.001 (0.0115) −0.068** (0.0194)
Ln(number of medical patients) −0.621* (0.2692) −0.006 (0.0126) −0.025 (0.0249)
Linear combination
  Coefficient −0.407* 0.008 −0.068**
  SE (0.2264) (0.0125) (0.0238)
Weighted linear combination
  Coefficient −0.339 0.008 −0.060*
  SE (0.2433) (0.0133) (0.0243)
R2 0.881 0.999
Observations 6,144 6,144 6,144
Panel B: amount of sales
$0 < sales ≤ $500,000 −0.727** (0.2803) 0.003 (0.0109) −0.058** (0.0223)
Sales > $500,000 −0.630** (0.2641) −0.001 (0.0144) −0.081** (0.0245)
Ln(number of medical patients) −0.613** (0.2724) −0.006 (0.0128) −0.027 (0.0261)
R2 0.882 0.999 0.995
Observations 6,144 6,144 6,144

The effect of recreational dispensary entry on the unemployment rate (Unrate), Ln(labor force), and Ln(unemployed) – regression analysis

Unrate Ln(labor force) Ln(unemp)
(1) (2) (3)
Panel A: start of sales
Recreational sale −0.688** (0.2548) 0.000 (0.0116) −0.069** (0.0197)
Ln(number of medical patients) −0.618* (0.2703) −0.006 (0.0127) −0.025 (0.0250)
R2 0.881 0.999 0.995
Observations 6,048 6,048 6,048
Panel B: amount of sales
$0 < sales ≤ $500,000 −0.729** (0.2809) 0.003 (0.0109) −0.058** (0.0223)
Sales > $500,000 −0.634** (0.2693) −0.003 (0.0146) −0.083** (0.0253)
Ln(number of medical patients) −0.610** (0.2736) −0.006 (0.0128) −0.027 (0.0263)
R2 0.881 0.999 0.995
Observations 6,048 6,048 6,048

The effect of recreational dispensary entry on employment – regression analysis

All Cons Manu NR Service
(1) (2) (3) (4) (5)
Panel A: start of sales
Recreational sale 0.043** (0.0152) 0.054 (0.0552) 0.131** (0.0360) −0.019 (0.0674) 0.037* (0.0155)
Ln(number of medical patients) −0.022 (0.0143) −0.175+ (0.0918) −0.190** (0.0606) 0.170 (0.1178) −0.026 (0.0183)
R2 0.998 0.988 0.995 0.965 0.998
Observations 6,048 4,512 3,840 4,512 6,048
Panel B: amount of sales
$0 < sales ≤ $500,000 0.029+ (0.0155) 0.053 (0.0489) 0.148** (0.0381) −0.032 (0.0661) 0.025 (0.0173)
Sales > $500,000 0.062** (0.0181) 0.055 (0.0677) 0.110** (0.0387) −0.003 (0.0829) 0.054** (0.0172)
Ln(number of medical patients) −0.019 (0.0149) −0.175+ (0.0921) −0.195** (0.0593) 0.173 (0.1182) −0.024 (0.0181)
R2 0.998 0.988 0.995 0.965 0.998
Observations 6,048 4,512 3,840 4,512 6,048

The effect of recreational dispensary entry and sales on the unemployment rate (Unrate), Ln(labor force), and Ln(unemployed) – regression analysis

Unrate Ln(labor force) Ln(unemp)
(1) (2) (3)
Panel A: amount of sales
Recreational sale −0.365 (0.3154) −0.004 (0.0195) −0.089** (0.0299)
Recreational sale=1 × < 70km not-sellingmy=1 −0.430 (0.2864) 0.006 (0.0183) 0.028 (0.0311)
Ln(number of medical patients) −0.580* (0.2774) −0.006 (0.0132) −0.028 (0.0258)
R2 0.882 0.999 0.995
Observations 6,144 6,144 6,144

The effect of recreational dispensary entry on wage – ATT from GSCM

Ln(All) Ln(Cons) Ln(Manu) Ln(NR) Ln(Service)
(1) (2) (3) (4) (5)
Start of sales
Recreational sale −0.003 (0.0178) 0.007 (0.0531) 0.011 (0.0321) 0.036 (0.0424) −0.004 (0.0152)
Ln(number of medical patients) −0.017 (0.0161) 0.006 (0.1258) −0.027 (0.0474) 0.114** (0.0698) −0.010 (0.0438)
Observations 6144 4608 3936 4608 6144

The effect of recreational dispensary entry and sales on wages – regression analysis

All Cons Manu NR Service
(1) (2) (3) (4) (5)
Panel A: amount of sales
Recreational sale 0.003 (0.0148) 0.036 (0.0288) 0.007 (0.0214) 0.043 (0.0368) 0.006 (0.0135)
Recreational sale=1 × < 70 km not-sellingmy=1 −0.004 (0.0135) −0.039 (0.0250) 0.004 (0.0341) −0.024 (0.0258) −0.003 (0.0112)
Ln(number of medical patients) 0.004 (0.0113) −0.077 (0.0476) −0.036 (0.0306) 0.067+ (0.0345) 0.002 (0.0178)
R2 0.937 0.778 0.932 0.909 0.925
Observations 2,048 1,536 1,312 1,536 2,048

The effect of recreational dispensary entry on wages – regression analysis

All Cons Manu NR Service
(1) (2) (3) (4) (5)
Panel A: start of sales
Recreational sale 0.001 (0.0101) 0.007 (0.0265) 0.010 (0.0197) 0.028 (0.0318) 0.004 (0.0127)
Ln(number of medical patients) 0.004 (0.0113) −0.081+ (0.0469) −0.036 (0.0271) 0.061+ (0.0341) 0.002 (0.0176)
R2 0.932 0.768 0.932 0.900 0.919
Observations 2,016 1,504 1,280 1,504 2,016
Panel B: amount of sales
$0 < sales ≤ $500,000 0.006 (0.0106) 0.008 (0.0254) 0.025 (0.0249) 0.029 (0.0294) 0.009 (0.0139)
Sales > $500,000 −0.007 (0.0119) 0.006 (0.0338) −0.012 (0.0196) 0.026 (0.0384) −0.004 (0.0134)
Ln(number of medical patients) 0.002 (0.0109) −0.081+ (0.0469) −0.041 (0.0280) 0.061+ (0.0339) 0.001 (0.0173)
R2 0.932 0.768 0.932 0.900 0.919
Observations 2,016 1,504 1,280 1,504 2,016

The effect of recreational dispensary entry and sales on the Unemployment Rate (Unrate), Ln(labor force), and Ln(unemployed) – regression analysis

Unrate Ln(labor force) Ln(unemp)
(1) (2) (3)
Panel A: amount of sales
Recreational sale −0.689* (0.2745) −0.002 (0.0131) −0.073** (0.0210)
Recreational sale=1 × < 50km not-sellingmy=1 0.014 (0.3418) 0.010 (0.0132) 0.015 (0.0369)
Ln(number of medical patients) −0.622* (0.2704) −0.006 (0.0126) −0.026 (0.0255)
R2 0.881 0.999 0.995
Observations 6,144 6,144 6,144
Month FE
Year FE
County FE
Idioma:
Inglés
Calendario de la edición:
1 veces al año
Temas de la revista:
Negocios y Economía, Economía política, Microeconomía, Macroeconómica, Política económica, Matemáticas y estadística para economistas, Econometría
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