Comparative Analysis of Hedonic Wage and Discrete Choice Models in Valuing Job Safety

MWTP for risk reduction (safety) by the magnitude of 1/1000,000 (unit: USD)

		MWTP
		Mean	l1	u1
ML	Model 1	1885	1537	2233
	Model 2	2152	1798	2506
PML	Model 3	3022	2739	3305
	Model 4	2963	2672	3253
HWM	FE	25	13	36

Wage Regression by Industry (2016)

	Manufactory	Construction	Catering	Transportation	Finance	Science	Service
female	−0.272*** (0.0232)	−0.198** (0.0785)	−0.201*** (0.0337)	−0.242*** (0.0798)	−0.0981 (0.0703)	−0.161*** (0.0575)	−0.179*** (0.0575)
eduyear	0.100*** (0.0059)	0.0347** (0.0169)	0.0769*** (0.0101)	0.0495** (0.0216)	0.113*** (0.0193)	0.0915*** (0.0140)	0.0501*** (0.0130)
lnwexp	0.0990*** (0.0212)	0.119* (0.0633)	0.0923** (0.0439)	0.0393 (0.0621)	0.193** (0.0838)	0.150*** (0.0423)	0.0162 (0.0430)
healthlevel	0.00211 (0.0144)	0.0684* (0.0395)	0.0174 (0.0204)	0.0403 (0.0420)	−0.0068 (0.0445)	−0.0373 (0.0448)	0.0357 (0.0279)
age	0.0088*** (0.0028)	0.0008 (0.0054)	0.0058 (0.0046)	0.0163* (0.0089)	0.0132* (0.0078)	0.0001 (0.0050)	0.0150** (0.006)
_cons	4.27*** (0.120)	5.21*** (0.368)	4.60*** (0.188)	4.82*** (0.532)	3.94*** (0.391)	4.66*** (0.326)	4.83*** (0.252)
N	1008	129	495	117	194	167	459
R2	0.390	0.122	0.206	0.186	0.283	0.301	0.117

Summary Statistics of Job Attributes and Worker Attributes by Industry

Variables	Definition	Manufacture Obs. 2,257	Construction Obs. 315	Catering Obs. 1,055	Transportation Obs. 263	Finance Obs. 418	Science Obs. 413	Service Obs. 1,204
wage_alt	yearly wage income, unit: 1000 TWD in 2014 values	500.53 (264.22)	545.57 (154.25)	454.33 (147.79)	519.98 (167.09)	607.97 (228.02)	492.48 (175.29)	517.53 (204.61)
risk_alt	industry mortality rates, unit: 1/1,000,000	23.70 (0.00)	114.50 (8.57)	11.32 (1.65)	48.47 (0.20)	4.03 (1.32)	25.17 (3.64)	8.75 (2.66)
workhour_ alt	industry average monthly total work hours, unit: hour	175.74 (0.30)	166.13 (0.15)	162.34 (1.54)	172.74 (0.30)	167.05 (1.09)	172.26 (0.30)	161.10 (1.49)
umem_alt	industry unemployment rates, unit: %	2.84 (0.02)	4.58 (0.00)	3.53 (0.09)	3.19 (0.00)	2.83 (0.32)	4.31 (0.20)	2.69 (0.14)

Wage Regression by Industry (2018)

	Manufactory	Construction	Catering	Transportation	Finance	Science	Service
female	−0.243*** (0.0282)	−0.175** (0.0828)	−0.240*** (0.0399)	−0.211** (0.0985)	−0.102 (0.0740)	−0.105* (0.0548)	−0.231*** (0.0535)
eduyear	0.110*** (0.0066)	0.0622*** (0.0155)	0.0788*** (0.0110)	0.0730*** (0.0271)	0.096*** (0.0197)	0.110*** (0.0152)	0.0611*** (0.0115)
lnwexp	0.0804** (0.0335)	0.256*** (0.0704)	0.211*** (0.0567)	0.313*** (0.101)	0.178** (0.0885)	0.189*** (0.0573)	−0.007 (0.0503)
healthlevel	0.0183 (0.0155)	0.00363 (0.0405)	0.0606** (0.0278)	0.159*** (0.0564)	0.0279 (0.0408)	0.0310 (0.0413)	0.0277 (0.0255)
age	0.0117*** (0.0031)	−0.0049 (0.0058)	−0.0017 (0.006)	−0.0134 (0.0092)	0.0099 (0.0079)	0.0012 (0.0041)	0.0098 (0.0062)
_cons	4.07*** (0.140)	4.96*** (0.291)	4.40*** (0.246)	4.53*** (0.621)	4.19*** (0.425)	4.03*** (0.363)	4.95*** (0.254)
N	937	125	394	96	177	158	395
R2	0.363	0.188	0.248	0.215	0.173	0.371	0.142

Regression Results-Discrete Choice Model

	CL		ML		PML
	Model 1	Model 2	Model 3	Model 4	Model 5	Model 6
wage_alt	0.0017***	0.0013***	0.0022***	0.0018***	0.0018***	0.0016***
risk_alt	–0.1091***	–0.0986***	–0.1244***	–0.1162***	–0.1632***	–0.1422***
workhour_alt	0.0251**	0.0096	0.1633***	0.1039***	0.1529***	0.1085***
unem_alt	−0.7097***	−0.5777***	0.3434	0.1138	−0.1729	−0.2892
sd(risk_alt)			0.3826***	0.3186***	0.2546***	0.2323***
sd(workhour_alt)			0.4681***	0.4270***	0.4601***	0.4771***
sd(umem_alt)			0.0026	0.0041	2.3677***	2.7743***
Construction
eduyear		−0.2003***		−1.0500**		−1.0161***
age		−0.0134		0.0941		0.1238**
female		−1.0217***		−15.3042***		−11.4380***
_cons	9.0968***	11.2592***	−42.8469***	−19.2340	−19.0045***	−5.0814
Catering
eduyear		−0.1084***		−0.1538*		−0.1549**
age		−0.0296***		−0.0946***		−0.0997***
female		0.6325***		3.2816***		3.2010***
_cons	−2.0309***	0.7968	−1.3451***	2.2099	−1.3025***	2.5388*
Transportation
eduyear		−0.0522		−0.1804		−0.1984***
age		−0.0162		−0.0123		0.0004
female		−0.3839*		−3.2871***		−2.4575***
_cons	−2.9876	1.8339**	−8.5789***	−2.9876	−5.4116***	0.1871
Finance
eduyear		0.2072***		0.2016**		0.2588***
age		0.0058		−0.0370		−0.0454**
female		0.6392***		3.1610***		2.9912***
_cons	−3.7770***	−7.1861***	−8.5789***	−9.0142***		−8.6711***
Science
eduyear		0.0321		0.0385		0.0385
age		0.0105		−0.0011		0.0315
female		0.4214***		0.6866***		1.1440***
_cons	−0.6070***	−1.8486***	−1.9667***	−2.4552***	−2.9669***	−5.4924***
Service
eduyear		0.1624***		0.1287		0.2505***
age		−0.0345***		−0.1047***		−0.1237***
female		1.1372***		3.9960***		4.1265***
_cons	−2.2029***	−4.0223***	−2.1834***	−2.8356	−2.4155***	−4.1438**
N	32,347	32,347	32,347	32,347	32,347	32,347
Pseudo R2	1.41%	1.32%	30.93%	31.52%	27.36%	28.19%
Log-likelihood	−7388.89	−7085.43	−7127.41	−6923.56	−6107.19	−5918.74
AIC	14797.78	14226.87	14280.81	13909.11	12750.25	11899.47

Variable Descriptive Statistics

Category	Variable	Definition	Mean	Min	Max
Individual (Obs. 4035)	wage	Yearly wage in 2014 value (unit: 1000 TWD)	537. 2	28.5	5587.7
	eduyear	Education years	14.1	0.0	22.0
	feduyear	Father’s education years	9.2	0.0	22.0
	female	1 if female, 0 otherwise	0.4	0.0	1.0
	age	age	35.1	25.0	79.0
	marriage	1 if married, 0 otherwise	0.5	0.0	1.0
	scale	Number of employees in the firm	212.2	2.0	500.0
	wexp	Working experience years	13.6	1.0	71.0
	healthlevel	1 for very good health, 5 for very bad health	3.6	1.0	5.0
Industry (seven industries)	risk	industry mortality rates, unit: 1/1,000,000	23.6	0.0	124.3
	workhour_alt	industry average monthly total work hours, unit: hour	169.8	159.8	176.0
	unem_alt	industry unemployment rates, unit: %	3.2	2.6	4.6
Town (218 towns)	TJAN	township-level average January temperature (Celsius) from 1981 to 2005	16.4	13.1	20.8
	TJUL	township-level average July temperature (Celsius) from 1981 to 2005	28.8	26.4	30.3
Regional dummy	NORTH	1 if respondent lives in Northern Taiwan, 0 otherwise	0.5	0.0	1.0
	CENTER	1 if respondent lives in central Taiwan, 0 otherwise	0.2	0.0	1.0
	SOUTH	1 if respondent lives in southern Taiwan, 0 otherwise	0.2	0.0	1.0
	EAST	1 if respondent lives in eastern Taiwan, 0 otherwise	0.0	0.0	1.0

The Hedonic Wage Model Results

	(1)	(2)	(3)	(4)	(5)
	year2016	year2018	pool_1	pool_2	FE
risk_alt	0.0006* (0.0003)	0.0011*** (0.0004)	0.0008*** (0.0002)	0.0012*** (0.0003)	0.0012*** (0.0003)
eduyear	0.0660*** (0.0052)	0.0765*** (0.0054)	0.0710*** (0.0038)	0.0711*** (0.0038)	0.0706*** (0.0038)
feduyear	0.0095*** (0.0029)	0.0063** (0.0030)	0.0082*** (0.0021)	0.0079*** (0.0021)	0.0078*** (0.0021)
female	−0.2149*** (0.0166)	−0.2370*** (0.0190)	−0.2248*** (0.0125)	−0.2301*** (0.0128)	−0.2299*** (0.0128)
age	0.0158*** (0.0039)	0.0113*** (0.0035)	0.0142*** (0.0026)	0.0141*** (0.0026)	0.0138*** (0.0026)
wexp	−0.0017 (0.0034)	0.0011 (0.0031)	−0.0005 (0.0023)	−0.0003 (0.0023)	−0.0003 (0.0023)
marry	0.1471*** (0.0170)	0.1156*** (0.0198)	0.1351*** (0.0130)	0.1349*** (0.0129)	0.1346*** (0.0129)
scale	0.0004*** (0.0000)	0.0004*** (0.0000)	0.0004*** (0.0000)	0.0005*** (0.0000)	0.0005*** (0.0000)
TJAN	−0.0503*** (0.0066)	−0.0519*** (0.0078)	−0.0502*** (0.0050)	−0.0503*** (0.0050)	−0.0507*** (0.0050)
TJUL	0.0874*** (0.0159)	0.1035*** (0.0166)	0.0933*** (0.0115)	0.0899*** (0.0115)	0.0907*** (0.0115)
workhour_alt				−0.0045*** (0.0011)	−0.0042*** (0.0011)
unem_alt				−0.0238* (0.0137)	−0.0170 (0.0137)
year					0.0158** (0.0061)
_cons	2.7904*** (0.4185)	2.3943*** (0.4370)	2.6150*** (0.3026)	3.5419*** (0.3666)	−28.3320** (12.4421)
N	2293	1742	4035	4035	4035
R2	0.349	0.361	0.357	0.359	0.360