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 |