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

Avinandan Chakraborty; Jacqueline Doremus; Sarah Stith

doi:10.2478/izajole-2021-0005

Figures & Tables

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.

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 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(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.

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 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 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.

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

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

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

Ln(employees) 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.

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^**
Unemployment rate, %	6,144	1,604	1,948	972	1,620	−4.268^**	−3.605^**	−0.663^**
Ln(labor force)	9.11	9.48	9.74	8.38	8.43	0.258^**	0.048	0.21^**
Ln(labor force)	6,144	1,604	1,948	972	1,620	0.258^**	0.048	0.21^**
Ln(unemployed)	6.02	6.89	6.35	5.68	4.99	−0.539^**	−0.691^**	0.152^**
Ln(unemployed)	6,144	1,604	1,948	972	1,620	−0.539^**	−0.691^**	0.152^**
Ln(all industry employees)	8.76	9.11	9.42	8.03	8.07	0.318^**	0.035	0.282^**
Ln(all industry employees)	6,144	1,604	1,948	972	1,620	0.318^**	0.035	0.282^**
Ln(construction employees)	6.51	6.50	6.94	5.94	6.01	0.436^**	0.072	0.364^**
Ln(construction employees)	4,608	1,416	1,752	540	900	0.436^**	0.072	0.364^**
Ln(manufacturing sector employees)	6.31	6.06	6.53	6.32	6.31	0.470^**	−0.007	0.477^**
Ln(manufacturing sector employees)	3,936	1,281	1,503	432	720	0.470^**	−0.007	0.477^**
Ln(natural resource and mining employees)	5.78	5.86	5.96	5.55	5.59	0.105	0.046	0.059^**
Ln(natural resource and mining employees)	4,608	1,274	1,510	684	1,140	0.105	0.046	0.059^**
Ln(service-providing employees)	8.17	8.58	8.93	7.31	7.36	0.349^**	0.056	0.293^**
Ln(service-providing employees)	6,144	1,604	1,948	972	1,620	0.349^**	0.056	0.293^**

Panel B: quarterly

Ln(all industry wages)	6.59	6.55	6.67	6.49	6.59	0.119^**	0.097^**	0.021^**
Ln(all industry wages)	2,048	527	657	324	540	0.119^**	0.097^**	0.021^**
Ln(construction wages)	6.76	6.73	6.84	6.63	6.71	0.116^**	0.075^*	0.041^**
Ln(construction wages)	1,536	466	590	180	300	0.116^**	0.075^*	0.041^**
Ln(manufacturing wages)	6.70	6.62	6.76	6.65	6.74	0.137^**	0.091⁺	0.046^**
Ln(manufacturing wages)	1,312	421	507	144	240	0.137^**	0.091⁺	0.046^**
Ln(natural resource and mining wages)	6.87	6.86	6.98	6.74	6.82	0.119^**	0.081⁺	0.038^**
Ln(natural resource and mining wages)	1,536	419	509	228	380	0.119^**	0.081⁺	0.038^**
Ln(service-providing wages)	6.49	6.44	6.57	6.40	6.50	0.125^**	0.098^**	0.027^**
Ln(service-providing wages)	2,048	527	657	324	540	0.125^**	0.098^**	0.027^**

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=R_cmy	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

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

Figures & Tables

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Figure 7

Figure A1

Figure A2

Figure A3

Figure A4

Figure A5

Figure A6

Figure A7

Figure A8

Figure A9

Figure A10

Figure A11

Figure A12

Figure A13

Figure A14

Descriptive statistics by treatment status

The effect of recreational dispensary entry – ATT from GSCM

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

Sources for our variable of interest

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

County-level summary statistics

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

Event study estimates post-dispensary entry periods

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

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

Effect of preexisting county-level economic conditions on dispensary entry

Multiple inference – adjusted p–value

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

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

The effect of recreational dispensary entry on employment – regression analysis

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

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

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

The effect of recreational dispensary entry on wages – regression analysis

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