Gender-Differentiated Poverty among Migrant Workers: Aggregation and Decomposition Analysis of the Chinese Case for the Years 2012–2018
Abstract
:1. Introduction
1.1. Definitions, Features, and Measurements of Poverty
1.2. Poverty Realities of Migrant Workers
1.3. Gender-Differentiated Poverty
1.4. Gender-Differentiated Poverty among Chinese Migrant Workers
- RQ1: Do gender differences exist in the relative poverty levels of migrant workers moving from rural to urban districts of China?
- RQ2: If so, how are such gender differences to be interpreted?
2. Materials and Methods
2.1. Aggregation of Migrant Workers’ Relative Poverty Levels
2.1.1. Construction of the Multidimensional Index Model
2.1.2. Selection of Dimensions/Indicators
2.2.2. Counter-Group Comparison
2.2.3. UCQR Decomposition of Gender Differences
2.3. Research Sample
3. Results
3.1. Statistics of Overall Migrant Workers’ Relative Poverty
3.2. Gender Differences in Migrant Workers’ Relative Poverty
3.3. Gender Bias in Migrant Workers’ Relative Poverty
3.4. Characteristic-Led Gender Bias and Gender Discrimination
4. Discussion
4.1. Main Findings
4.2. Theoretical Implications
4.3. Practical Implications
5. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
Appendix A
References
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Dimensions | Indicators | Cutoff Values | Weights |
---|---|---|---|
Income | Yearly income | Below or equal to 1.5 times the urban subsistence allowances | 1/6 |
Education | Academic education | Did not finish the compulsory education | 1/12 |
Non-academic education | Did not participate in any non-academic education programs | 1/12 | |
Health | Self-reported health status | Self-reports health status as poor | 1/18 |
Chronic disease | Has chronic disease | 1/18 | |
BMI | Below 18.5 or above 24 | 1/18 | |
Employment | Working hours | Above-average eight hours per day | 1/24 |
Formal job contracts | Does not work under a formal contract | 1/24 | |
Employer-provided job insurances | Does not have any employer-provided job insurance | 1/24 | |
Employer-provided housing fund | Does not have any employer-provided housing fund | 1/24 | |
Living | Housing overcrowding | Self-reports living conditions as overcrowded | 1/18 |
Internet access | Does not have access to the Internet | 1/18 | |
Self-reported life satisfaction | Self-reports life as unsatisfactory | 1/18 | |
Social integration | Rich–poor discrimination | Has been treated unfairly due to the rich–poor gap | 1/18 |
Urban–rural discrimination | Has been treated unfairly due to urban–rural differences | 1/18 | |
Participation in organizations | Does not participant in any labor union or workers’ association | 1/18 |
k Value | Years | Relative Poverty Incidence (%) | Average Deprivation | Relative Poverty Index | ||||||
---|---|---|---|---|---|---|---|---|---|---|
Total | Female | Male | Total | Female | Male | Total | Female | Male | ||
1 | 2012 | 98.93 | 34.17 | 64.76 | 0.43 | 0.44 | 0.42 | 0.421 | 0.151 | 0.270 |
2014 | 97.65 | 33.88 | 63.77 | 0.39 | 0.41 | 0.39 | 0.384 | 0.137 | 0.247 | |
2016 | 94.86 | 32.52 | 62.34 | 0.38 | 0.40 | 0.38 | 0.365 | 0.131 | 0.235 | |
2018 | 92.80 | 31.46 | 61.34 | 0.37 | 0.37 | 0.37 | 0.344 | 0.118 | 0.227 | |
2 | 2012 | 76.25 | 25.82 | 50.43 | 0.24 | 0.25 | 0.23 | 0.180 | 0.064 | 0.116 |
2014 | 65.76 | 23.47 | 42.30 | 0.23 | 0.24 | 0.23 | 0.15 | 0.056 | 0.095 | |
2016 | 61.63 | 21.90 | 39.73 | 0.23 | 0.24 | 0.22 | 0.140 | 0.052 | 0.088 | |
2018 | 57.63 | 19.12 | 38.52 | 0.22 | 0.22 | 0.22 | 0.127 | 0.043 | 0.084 | |
3 | 2012 | 24.61 | 11.13 | 13.48 | 0.20 | 0.20 | 0.19 | 0.048 | 0.023 | 0.023 |
2014 | 16.48 | 7.06 | 9.42 | 0.20 | 0.20 | 0.19 | 0.033 | 0.014 | 0.018 | |
2016 | 16.26 | 7.20 | 9.06 | 0.19 | 0.20 | 0.19 | 0.032 | 0.014 | 0.018 | |
2018 | 11.41 | 4.42 | 6.99 | 0.19 | 0.19 | 0.19 | 0.022 | 0.009 | 0.013 | |
4 | 2012 | 3.85 | 2.71 | 1.14 | 0.18 | 0.18 | 0.18 | 0.007 | 0.005 | 0.002 |
2014 | 3.07 | 1.71 | 1.36 | 0.18 | 0.18 | 0.18 | 0.006 | 0.003 | 0.002 | |
2016 | 2.35 | 1.21 | 1.14 | 0.18 | 0.18 | 0.17 | 0.004 | 0.002 | 0.002 | |
2018 | 1.21 | 0.50 | 0.71 | 0.17 | 0.18 | 0.17 | 0.002 | 0.001 | 0.001 | |
5 | 2012 | 0.14 | 0.14 | 0.00 | 0.18 | 0.18 | – | 0.001 | 0.001 | – |
2014 | 0.14 | 0.07 | 0.07 | 0.17 | 0.18 | 0.17 | 0.001 | 0.001 | 0.001 | |
2016 | 0.00 | 0.00 | 0.00 | 0.00 | – | – | 0 | – | – | |
2018 | 0.00 | 0.00 | 0.00 | 0.00 | – | – | 0 | – | – |
Dimensions | Indicators | k = 3 | k = 4 | k = 5 | ||||||
---|---|---|---|---|---|---|---|---|---|---|
Total | Female | Male | Total | Female | Male | Total | Female | Male | ||
Income | Yearly income | 12.56 | 12.78 | 12.20 | 8.30 | 17.24 | 19.48 | 18.98 | 18.60 | 20.00 |
Education | Academic education | 9.14 | 9.21 | 9.09 | 7.52 | 9.81 | 10.25 | 9.49 | 9.30 | 10.00 |
Non-academic education | 13.51 | 13.50 | 13.56 | 15.82 | 11.53 | 11.42 | 9.49 | 9.30 | 10.00 | |
Health | Self-reported health status | 4.38 | 4.42 | 4.35 | 3.68 | 4.88 | 4.08 | 4.78 | 3.10 | 6.67 |
Chronic disease | 3.28 | 3.69 | 2.99 | 2.87 | 4.19 | 2.00 | 4.71 | 6.20 | 0.00 | |
BMI | 5.20 | 5.09 | 5.30 | 5.88 | 4.28 | 4.20 | 6.33 | 6.20 | 6.67 | |
Employment | Working hours | 4.23 | 4.18 | 4.27 | 5.01 | 4.06 | 3.65 | 2.33 | 2.33 | 5.00 |
Joy contracts | 4.30 | 4.34 | 4.27 | 4.22 | 3.61 | 4.40 | 4.65 | 4.65 | 5.00 | |
Employer-provided job insurances | 5.72 | 5.56 | 5.84 | 6.04 | 4.73 | 5.46 | 4.65 | 4.65 | 5.00 | |
Employer-provided housing fund | 7.06 | 6.93 | 7.17 | 8.53 | 5.82 | 5.95 | 4.65 | 4.65 | 5.00 | |
Living | Housing overcrowding | 3.17 | 3.28 | 3.12 | 3.06 | 3.79 | 3.05 | 4.71 | 6.20 | 0.00 |
Internet access | 7.99 | 8.19 | 7.87 | 8.31 | 7.18 | 7.37 | 6.33 | 6.20 | 6.67 | |
Self-reported life satisfaction | 5.84 | 5.82 | 5.86 | 5.71 | 6.22 | 5.52 | 6.20 | 6.20 | 6.67 | |
Social integration | Rich–poor discrimination | 2.81 | 2.58 | 3.00 | 2.37 | 3.68 | 3.97 | 3.10 | 3.10 | 6.67 |
Urban–rural discrimination | 1.48 | 1.15 | 1.74 | 1.25 | 1.22 | 1.68 | 3.10 | 3.10 | 0.00 | |
Participation in organizations | 9.33 | 9.28 | 9.38 | 11.42 | 7.77 | 7.53 | 6.20 | 6.20 | 6.67 |
Variable | Calculation Method | Total | Female | Male | |||
---|---|---|---|---|---|---|---|
Mean | S.D. | Mean | S.D. | Mean | S.D. | ||
Average relative deprivation | Actual value | 0.379 | 0.115 | 0.385 | 0.132 | 0.375 | 0.105 |
Age | Actual value | 37.188 | 10.238 | 35.412 | 9.279 | 38.136 | 10.599 |
Public living facility access | 1 = lowest level, 5 = highest level | 3.341 | 0.874 | 3.373 | 0.841 | 3.324 | 0.891 |
Medical expenditure | Logarithm of actual expenditures | 3.391 | 3.005 | 3.576 | 2.962 | 3.292 | 3.024 |
Appearance | 1 = lowest level, 7 = highest level | 5.316 | 1.093 | 5.330 | 1.110 | 5.309 | 1.084 |
Mandarin proficiency | 1 = lowest level, 7 = highest level | 4.488 | 1.720 | 4.568 | 1.729 | 4.445 | 1.715 |
News sensitivity | 1 = being sensitive, 0 = being insensitive | 0.327 | 0.469 | 0.248 | 0.432 | 0.369 | 0.483 |
Social status identification | 1 = lowest level, 5 = highest level | 2.764 | 1.006 | 2.715 | 1.013 | 2.790 | 1.002 |
Variable | 25 Quantile | 50 Quantile | 75 Quantile | |||
---|---|---|---|---|---|---|
Female | Male | Female | Male | Female | Male | |
Age | 0.002 *** | 0.002 *** | 0.005 *** | 0.002 *** | 0.004 *** | 0.003 *** |
(0.001) | (0.001) | (0.001) | (0.001) | (0.001) | (0.001) | |
Public living facility access | 0.002 | −0.009 * | 0.001 | −0.009 * | 0.002 | −0.014 *** |
(0.009) | (0.005) | (0.009) | (0.004) | (0.008) | (0.005) | |
Medical expenditure Appearance | 0.001 | 0.006 *** | 0.004 | 0.006 *** | 0.004 * | 0.006 *** |
(0.003) | (0.002) | (0.003) | (0.002) | (0.002) | (0.002) | |
Appearance | −0.025 *** | −0.005 | −0.017 *** | −0.007 ** | −0.008 | −0.007 ** |
(0.004) | (0.003) | (0.005) | (0.003) | (0.005) | (0.003) | |
Mandarin proficiency | −0.012 * | −0.006 | −0.017 ** | −0.007 * | −0.006 | −0.013 *** |
(0.006) | (0.005) | (0.008) | (0.004) | (0.008) | (0.005) | |
News sensitivity | −0.043 ** | −0.030 *** | 0.002 | −0.020 ** | −0.014 | −0.019 ** |
(0.019) | (0.010) | (0.018) | (0.008) | (0.015) | (0.009) | |
Social status identification | −0.018 *** | −0.017 *** | −0.026 *** | −0.019 *** | −0.023 *** | −0.016 *** |
(0.007) | (0.005) | (0.008) | (0.004) | (0.007) | (0.005) | |
Constant | 0.445 *** | 0.352 *** | 0.451 *** | 0.443 *** | 0.441 *** | 0.513 *** |
(0.063) | (0.035) | (0.067) | (0.032) | (0.060) | (0.037) | |
R2 | 0.146 | 0.071 | 0.159 | 0.099 | 0.123 | 0.13 |
Variable | Model 1 | Model 2 | ||||
---|---|---|---|---|---|---|
25 Quantile | 50 Quantile | 75 Quantile | 75-25 Quantile | 50-25 Quantile | 75-50 Quantile | |
Total effect | 0.014 | 0.034 | 0.05 | 0.036 | 0.020 | 0.016 |
Characteristic effect | −0.012 | −0.009 | −0.001 | 0.011 | 0.003 | 0.008 |
Explicable part (%) | −84.5% | −26.7% | −1.8% | 31.4% | 14.5% | 53.1% |
Age | −0.013 | −0.013 | −0.007 | 0.005 | −0.001 | 0.006 |
Public living facility access | 0.001 | 0.001 | 0.001 | 0.001 | 0.001 | 0.001 |
Medical expenditure | 0.001 | 0.001 | 0.002 | 0.001 | 0.001 | 0.001 |
Appearance | −0.001 | −0.001 | −0.001 | 0.001 | 0.001 | 0.001 |
Mandarin proficiency | −0.002 | −0.001 | −0.001 | 0.001 | 0.001 | 0.001 |
News sensitivity | −0.001 | 0.002 | 0.003 | 0.003 | 0.002 | 0.001 |
Social status identification | 0.002 | 0.002 | 0.002 | 0.001 | 0.001 | 0.001 |
Coefficient effect | 0.026 | 0.043 | 0.051 | 0.024 | 0.017 | 0.007 |
Inexplicable part (%) | 184.5% | 126.7% | 101.8% | 68.6% | 85.5% | 46.9% |
Age | 0.086 | 0.062 | 0.029 | −0.057 | −0.023 | −0.034 |
Public living facility access | 0.038 | 0.059 | 0.080 | 0.042 | 0.021 | 0.021 |
Medical expenditure | −0.008 | −0.007 | 0.014 | 0.022 | 0.002 | 0.021 |
Appearance | −0.044 | 0.041 | 0.055 | 0.100 | 0.086 | 0.014 |
Mandarin proficiency | −0.040 | −0.009 | −0.003 | 0.037 | 0.032 | 0.006 |
News sensitivity | 0.009 | 0.002 | −0.002 | −0.011 | −0.007 | −0.004 |
Social status identification | −0.011 | −0.023 | −0.074 | −0.064 | −0.012 | −0.052 |
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Peng, J.; Chen, J.; Zhang, L. Gender-Differentiated Poverty among Migrant Workers: Aggregation and Decomposition Analysis of the Chinese Case for the Years 2012–2018. Agriculture 2022, 12, 683. https://doi.org/10.3390/agriculture12050683
Peng J, Chen J, Zhang L. Gender-Differentiated Poverty among Migrant Workers: Aggregation and Decomposition Analysis of the Chinese Case for the Years 2012–2018. Agriculture. 2022; 12(5):683. https://doi.org/10.3390/agriculture12050683
Chicago/Turabian StylePeng, Jiquan, Juan Chen, and Liguo Zhang. 2022. "Gender-Differentiated Poverty among Migrant Workers: Aggregation and Decomposition Analysis of the Chinese Case for the Years 2012–2018" Agriculture 12, no. 5: 683. https://doi.org/10.3390/agriculture12050683