Union wage effect: Evidence from Ghana

Figures & data

Figure 1. Trade union coverage (No. of unionized work/total no. of work %).

Source: Author`s construction based on GLFS 2015.

Figure 2. Registration status of trade unions present at workplace.

Source: Author`s construction based on GLFS 2015 Data.

Table 1. Regional trend of union coverage from 1991/1992 to 2015

Administrative Regions
	1991/1992	1998/1999	2005/2006	2012/2013	2015*	Average
Western	74.8	63.2	45.0	26.0	16.4	45.1
Central	49.4	21.2	43.9	31.4	9.7	31.1
Greater-Accra	42.3	30.7	30.5	27.4	10.1	28.2
Volta	53.2	57.9	40.2	40.5	9.4	40.2
Eastern	47.7	60.0	34.2	28.2	8.6	35.7
Ashanti	61.5	41.4	31.4	23.4	15.7	34.7
Brong-Ahafo	70.0	49.7	43.2	38.3	8.0	41.8
Northern	33.3	77.8	37.0	32.8	8.4	37.9
Upper-East	40.0	84.6	45.8	36.0	26.6	46.6
Upper-West	70.0	77.8	55.9	44.6	10.2	51.7
Overall	53.9	46.4	36.2	30.6	12.3	35.9

*Ghana Labour Force Survey Data.

Source: Author`s Construction based on GLSS 3, 4, 5 and 6 as well as GLFS 2015.

Table 2. Sources of data extracted for the study

	GLSS 6 (2012/2013)	GLFS (2015)
Sampled Households	18 000	5 838
Sampled Household Members	72 372 (31 664)	19 367 (9 604)
Enumeration Areas	1 200	—–

Notes: Number of sampled household members employed for the study are in parenthesis.

Table 3. Summary statistics of all variables

	GLSS 6 (2005/2006)			GLFS (2015)
Variable	Mean	Minimum	Maximum	Mean	Minimum	Maximum
Wages (Real Monthly Earnings)-Dependent Variable	0.51	0	304.12	0.66	0	131.46
Labour Market Experience (years)	10.95	0	91	10.97	0	99
Age	32.97	15	99	33.45	15	60
Hours of Work	39.67	0	120	32.89		99
Unionism status:
Union Present	0.32	0	1	0.12	0	1
Union Absent	0.68	0	1	0.88	0	1
Educational Attainment: None	0.02	0	1	0.34	0	1
Basic	0.75	0	1	0.36	0	1
Secondary	0.16	0	1	0.19	0	1
Tertiary	0.07	0	1	0.11	0	1
Gender: Male	0.50	0	1	0.44	0	1
Female	0.50	0	1	0.56	0	1
Sector of Employment:
Agriculture	0.45	0	1	0.40	0	1
Industry	0.14	0	1	0.17	0	1
Services	0.41	0	1	0.43	0	1
Locality: Urban	0.48	0	1	0.49	0	1
Rural	0.52	0	1	0.51	0	1
Formality status: Formal sector	0.41	0	1	0.57	0	1
Informal Sector	0.59	0	1	0.43	0	1
Firm Size	1002.79	0	9999	——-	——–	———

Source: Author`s construction based on GLSS 6 and GLFS (2015) datasets.

Table 4. Heckman`s two-step estimates of the union wage premium from 2005/2006 to 2015 (Observed wage equation)

	GLSS 6 (2012/2013)		GLFS (2015)
Dependent Variable: Log of Real Monthly Earnings	Coef.	z-cal.	Coef.	z-cal.
Log of hours of work	0.152***	4.58	0.100**	2.46
Union Present	0.123***	2.83	0.131**	2.28
Labour market Exp.	0.020***	8.34	0.029***	6.12
Age	0.036***	2.92	0.037*	1.89
Age^2	−0.000**	−3.06	−0.001**	−2.14
Education: Basic	0.197	0.82	0.121**	1.19
Secondary	0.385	1.58	0.092***	0.75
Tertiary	0.993***	4.04	0.847***	5.12
Male	0.361***	7.98	0.314***	5.77
Sector :Industrial	0.528***	6.37	0.047	0.33
Service	0.263***	3.38	−0.299**	−2.26
Urban	0.171***	4.33	0.105*	1.78
Formal employment	0.378***	8.27	0.274***	4.24
Firm size	0.000	0.52	—-	—-
Firm size^2	−0.000	−0.45	—-	—-
Constant	−2.895***	−7.27	−0.405	−0.79
Inverse Mills Ratio	−0.126*	−1.73	−0.117	−1.11
rho	−0.146		−0.151
sigma	0.951		0.774
Wald Chi2	848.42		253.98
Prob. > Chi2	0.000		0.000
No. of observations	5 863		5 061
Censored Observations	3 525		4 088
Uncensored Observations	2 338		973

Notes: ***, ** and * means significant at 1%, 5% and 10% respectively.

Source: Author`s Estimation based on GLSS 6 and GLFS (2015) datasets.

Table 5. Quantile regression estimates of the union wage premium (2012/2013 and 2015)

	GLSS 6 (2012/2013)			GLFS (2015)
Dependent Var:	θ=0.25	θ=0.50	θ=0.75	θ=0.25	θ=0.50	θ=0.75
Log of Real Monthly Earnings	Coef.(${\beta }_{\theta }$)	Coef.(${\beta }_{\theta }$)	Coef.(${\beta }_{\theta }$)	Coef.(${\beta }_{\theta }$)	Coef.(${\beta }_{\theta }$)	Coef.(${\beta }_{\theta }$)
Log of Hours of work	0.2070*** (5.31)	0.127*** (4.34)	0.155*** (5.08)	$\hspace{0.17em}$ 0.093 (1.45)	0.075* (1.70)	0.002 (0.03)
Union Present	0.109*** (2.80)	0.068* (1.90)	0.067* (1.78)	0.322*** (4.07)	0.220*** (4.02)	0.088 (1.21)
Labour Market Exper.	0.020*** (8.02)	0.018*** (7.52)	0.016*** (6.30)	0.027*** (4.76)	0.022*** (5.92)	0.025*** (4.10)
Age	0.094*** (9.25)	0.078*** (9.66)	0.060*** (6.63)	0.043* (1.70)	0.056** (2.79)	0.055* (1.86)
Age^2	−0.001*** (−8.51)	−0.001*** (−9.38)	−0.001*** (−6.17)	−0.001* (−1.79)	−0.001*** (−2.89)	−0.001*** (−1.92)
Basic Educ.	−0.228* (−1.74)	0.069 (0.64)	0.144 (0.55)	0.254** (2.13)	0.232** (2.12)	0.139 (0.82)
Secondary Educ.	−0.038 (−0.29)	0.242** (2.18)	0.300 (1.14)	0.278** (2.42)	0.290*** (2.84)	0.305** (1.56)
Tertiary Educ.	0.720*** (5.18)	0.917*** (8.09)	0.869*** (3.29)	1.169*** (7.59)	1.159*** (8.26)	1.026*** (4.55)
Male	0.336*** (10.34)	0.320*** (9.20)	0.376*** (12.11)	0.329*** (5.07)	0.264*** (5.44)	0.304*** (4.20)
Sector of Employment: Industry	0.488*** (5.18)	0.496*** (6.84)	0.527*** (6.81)	0.194 (1.07)	0.287* (1.65)	−0.121 (−0.36)
Services	0.262*** (2.90)	0.210*** (3.10)	0.180** (2.50)	−0.143 (−0.90)	−0.037 (−0.23)	−0.544* (−1.74)
Formal	0.358*** (8.91)	0.380*** (9.88)	0.349*** (8.29)	0.326*** (4.01)	0.187*** (3.12)	0.231** (2.60)
Urban	0.113*** (3.09)	0.074** (2.22)	0.108*** (3.05)	0.113 (1.51)	0.056 (0.93)	0.091 (1.36)
Inverse Mills Ratio	6.393* (1.82)	3.998 (0.85)	6.394 (1.82)	−2.051 (−0.49)	2.751 (0.72)	6.840 (1.62)
Inverse Mills Ratio^2	−8.027* (−1.92)	−5.900 (−1.05)	−8.027 (−1.92)	2.465 (0.64)	−2.189 (−0.64)	−5.857 (−1.52)
Constant	−0.668*** (−2.77)	0.244 (1.22)	0.866*** (2.74)	1.141 (0.84)	0.299 (0.24)	0.450 (0.30)
Pseudo R-Squared	0.234	0.233	0.188	0.297	0.292	0.207
Bootstrap Rep.	500	500	500	500	500	500
No. of observations	3 590	3 590	3 590	1 095	1 095	1 095

Notes: ***, ** and * means significance levels are at 1%, 5% and 10% respectively.

t-values are in parentheses.

Source: Author`s construction based on GLSS 6 and GLFS (2015) datasets.

Table A1. Heckman`s two-step estimates of the union wage premium from 2005/2006 to 2015 (Selection equation)

	GLSS 6 (2012/2013)		GLFS (2015)
Binary Dependent Variable: Employed	Coef.	z-cal.	Coef.	z-cal.
Age	0.137***	16.81	0.075***	4.99
Age Squared	−0.002***	−18.40	−0.001***	−4.56
Married	0.191***	3.83	0.114*	1.94
Separated	−0.127	−1.06	−0.066	−0.29
Divorced	−0.130	−1.24	−0.261	−1.57
Educ.: Basic	0.056	0.26	0.229***	3.37
Secondary	0.256	1.19	0.873***	12.48
Tertiary	0.725***	3.35	1.719***	22.98
Household Head	0.900***	21.11	0.485***	10.70
Log of Non-Labour Income of Household	−0.070***	−5.25	#
Father`s Education	0.133***	2.88	#
Mother`s Education	−0.027	−0.58	#
Accra	0.334***	7.13	0.078***	1.38
Constant	− 3.109***	−11.75	−3.218***	−13.03
No. of observations	5 863		5 061

Notes: ***, ** and * means significant at 1%, 5% and 10% respectively. # denotes the absence of variable in the dataset.

Source: Author`s Estimation based on GLSS 6 and GLFS (2015) Data sets.

Figure A1. Kernel`s earnings distribution (Based on GLSS 6–2012/2013).

Source: Author`s Construction Based on Data Extracted from GLSS 6.

Figure A2. Kernel`s earnings distribution (Based on 2015 GLFS).

Source: Author`s Construction Based on Data Extracted from GLFS, 2015.