1. Introduction
As a significant economic index, poverty is a persistent social problem, and has been a source of concern across the world. Despite the political systems and living standards in different countries, poverty remains a serious social problem [
1]. Multidimensional poverty is a composite indicator. It reflects inequality, sustainability, and economic development [
2]. The theoretical basis of multidimensional poverty can be traced to Amartya Sen’s capabilities approach. The concept and measurement of multidimensional poverty have been regarded as an effective method. This method can complement or replace the traditional income poverty line [
3]. Poverty is multidimensional. Additionally, it should combine material hardship with broken institutions and human frailty [
4]. In the state’s welfare assessment system, the incorporation of non-monetary dimensions would have positive significance for national poverty reduction efforts and policy interventions [
5,
6]. In Sen’s capabilities approach, the income–capability approach was proposed. This indicated that poverty can be judged in a multidimensional way by combining an income indicator at the monetary level and capability indicators at the non-monetary level [
7].
In many countries, migrants are often regarded as poor [
8,
9,
10]. China has a large group of migrant workers. This large-scale rural-to-urban migration constitutes a hallmark of modern society. Migrant workers have become an important labor force in the Chinese urbanization and modernization process. In 2021, the number of migrant workers reached 170 million [
11]. The monthly income levels of migrant workers are gradually increasing, but the poverty rate is also increasing. Income can alleviate the temporary hardship of migrant workers, but it cannot help them escape from poverty. Due to non-citizenship, migrant workers suffer from the deprivation of employment, welfare, social security, public services, and so on. Additionally, it leads them into multidimensional poverty. Illness, COVID-19, and unemployment increase the poverty risk and poverty vulnerability of migrant workers [
12,
13], which will affect social stability and the progress towards poverty alleviation in China.
The poverty of Chinese migrant workers is often hidden [
14]. According to the Chinese poverty line standard in rural areas, they have long been excluded from the rural poverty alleviation program. They are also excluded from the urban low-income social assistance system based on the income level of migrant workers [
15]. Meanwhile, migrant workers still have a large gap compared with the average income level of urban residents [
16]. This hidden poverty puts migrant workers in a vacuum of state regulation between the rural and the urban [
17]. For several decades, Chinese society has inappropriately depicted the negative effects of migrant workers. For example, migrant workers are considered as a trigger of the rise in crime, the decline in the level of public services, the rise in unemployment of local residents, and the reduction of agriculture [
18].
A unique feature of migrant work in China is the hukou system [
19]. In China, migrant workers’ rights, welfare, and public services are seriously deprived by the hukou system [
20]. Most of the migrant workers are marginalized groups in society [
21], representing the disadvantaged and disenfranchised [
22]. However, there are few studies that have focused on the issue of migrant workers’ survival. Additionally, few studies have measured their multidimensional poverty. Poverty is not only a static state but also a dynamic process. The poverty situation of migrant workers changes over time. Therefore, a dynamic analysis is important for the evaluation of multidimensional poverty, which can help us examine the changing trends in the poverty of migrant workers [
23]. However, few studies have discussed the dynamic evolution of multidimensional poverty among Chinese migrant workers. Our study analyzes the poverty persistence of migrants through the duration of poverty, which is rarely seen in existing studies. Based on Sen’s capabilities approach and the A–F method, we measure the multidimensional poverty index (MPI) of migrant workers, in order to provide a comprehensive framework for assessing the multidimensional poverty of Chinese migrant workers using static to dynamic analyses.
3. Results
3.1. Socio-Demographic Characteristics
Table 4 shows the demographic characteristics of the migrant worker samples in this study. The average age of the samples ranged from 33.80 to 35.75. The sex ratio ranged from 167.38 to 159.81. The ratio of male to female migrant workers was approximately 6:4. The proportion of migrant workers with junior high school education was the largest. The proportion of migrant workers with elementary school education or below decreased with time. On the contrary, the proportion of migrant workers with university education or above increased over the years. The descriptive statistics of demographic characteristics suggest that the samples of our study are consistent with the basic situation of migrant workers in China, thus making them suitable for further multidimensional poverty measurement.
3.2. Poverty Rate
Table 5 and
Figure 2 show the poverty rate of the Chinese migrant workers for each indicator in 2014, 2016, 2018, and 2020. From the trend of the unidimensional poverty rate, the poverty rate of migrant workers in terms of Inc, Edu and LS decreased over the years. The difference between the poverty rate for Inc and Edu in 2014 and 2020 was over 10.0%, which indicates that the income treatment, overall educational level, and life satisfaction of migrant workers are improving. Although the poverty rate for ES, PF, and SP exhibits several peaks, there was still a large decline from 2014 to 2020. The poverty rate for ES, HP, and SP in 2020 was 10.96%, 6.70%, and 9.20%, respectively. These values are lower than those in 2014. The changes in Hea, CD, and MI remained stable, indicating that migrant workers were in a healthy condition or engaged in medical insurance.
It should be noted that the overall value of the labor contract poverty rate is high. From 2014 to 2020, the labor contract poverty rates were close to 50%, which indicates that at least nearly half of migrant workers do not have a labor contract. In addition, compared with other indicators, the poverty rate of the union indicator has the highest value with an increasing trend. The union poverty rate in 2020 was 10.46% higher than that in 2014, which indicates that approximately 90% of migrant workers do not participate in unions. This low union participation demonstrates a high poverty rate in terms of the political rights dimension for migrant workers.
Figure 2 shows the mean values of the poverty rate from 2014 to 2020. The indicators of ES, PF, and LU are over 50%. The indicators of Hea, CD, MI, and LS are lower than 10%. The indicators of Inc, Edu, LC, and SP are between 10% and 50%.
3.3. The Trend towards Multidimensional Poverty
Figure 3 presents a line graph for the multidimensional poverty measurement results of Chinese migrant workers based on the A–F methodology, including the multidimensional poverty index (
M), multidimensional poverty incidence (
H), and average deprivation score (
A). In general, as the value of deprivation k increases, the
M-values and
H-values of migrant workers gradually decrease, while
A-values gradually increase. As mentioned in
Section 2.3, the
A-values are the result of the number of deprived dimensions to the total number of dimensions. This indicates that the larger the value of deprivation k, the lower the
H-values and the
M-values. Furthermore, with high values of the deprivation dimension numbers, the
A-values increase.
From the comparison results from 2014 to 2020, when k = 0.4, the M-values of migrant workers show a decreasing trend (0.1924 > 0.1800 > 0.1730 > 0.1576). When k = 0.1, 0.2, 0.3, and 0.5, the M-values decrease. When k = 0.6, 0.7, 0.8, and 0.9, the M-values are stable. This indicates that the multidimensional poverty of migrant workers stays at the same level within the high range of the deprivation value domain. These results demonstrate that the M-values of the overall migrant worker sample have a decreasing trend in the lower dimension (k ≤ 0.5) and a stable state in the higher dimension (k > 0.5). When k = 1, the A-value equals 1, representing the full deprivation. However, based on the H-values of migrant workers in each year (H = 0 when k = 1), none of migrant workers faced extreme deprivation in the full dimension.
The mean results of the
H-values,
A-values, and
M-values are shown in
Table 6 and
Figure 4. When k = 0.1, the
H-value,
M-value, and
A-value are 90.69%, 0.3207, and 0.3532, respectively. This reveals that 90% of migrant workers are deprived in at least four indicators. When k = 0.4, the
H-value,
M-value, and
A-value are 34.22%, 0.1758, and 0.5134, respectively. This indicates that at least one third of migrant workers are deprived in three dimensions. When k = 0.6, the
H-value,
M-value, and
A-value are 5.61%, 0.0381, and 0.6793, respectively. This shows that only 5.61% of migrant workers face deprivation in more than seven indicators. When k > 0.6 and the
H-value < 2%, migrant workers suffered from higher multidimensional deprivation from 2014 to 2020.
3.4. The Persistence of Multidimensional Poverty
Figure 5 presents pie charts representing the multidimensional poverty persistence rate among migrant workers. In previous studies, k = 0.3 or k = 1/3 was used as the cutoff to define whether individuals or households were in multidimensional poverty [
44,
45]. Since our study measures multidimensional poverty in 6 dimensions and with 11 indicators, we chose k = 0.3 and k = 0.4 as the poverty cutoffs to examine the multidimensional poverty persistence among migrant workers.
There is significant difference in poverty duration between k = 0.3 and k = 0.4. When k = 0.3, the rates of two periods, three periods, and four periods of poverty persistence are 35.48%, 21.51%, and 43.01%, respectively. In other words, the rate of four periods of poverty persistence is the highest, referring to a long-term poverty situation from 2014 to 2020. When k = 0.4, the rates of two periods, three periods, and four periods of poverty persistence are 50.65%, 29.22% and 20.13%, respectively.
4. Discussion
The rapid modernization and transformation of China has brought about the large-scale movement of migrant workers. China’s marketization process has provided opportunities for the rural surplus labor force to enter into cities. However, due to the discriminatory rural–urban dualization policy, migrant workers are blocked from employment, social security, welfare, and public services. Therefore, many of them are forced into the informal labor market. Some studies have shown that educational level is an important factor influencing migrant workers’ poverty, but the multidimensional poverty of migrant workers is rooted in their exclusion from the household registration system [
46]. In this study, we combined the characteristics of the Chinese migrant workers and the social environment. We constructed a multidimensional poverty index for migrant workers in China in six dimensions. Our study found that the multidimensional poverty of Chinese migrant workers is more serious than was expected. According to the results of our full-sample measurement, approximately 90% of migrant workers are deprived with respect to at least four indicators. This high poverty rate is basically consistent with the measurement results of Zhou et al. Our findings suggest that poverty among migrants requires urgent national and academic attention [
47].
With the improvement of the urban economy, although the income of migrant workers has increased, it is difficult for them to catch up with the growth of median urban per capita income. Even if the income growth brings the decrease in the multidimensional deprivation rate, migrant workers are still cannot afford the high costs of urban living [
48]. This study measures the multidimensional poverty index of Chinese migrant workers. It shows a decreasing trend over the years, with a decrease of 18% in 2020 compared to that in 2014. However, it needs to be considered that the COVID-19 pandemic after 2020 has posed a serious challenge to poverty reduction worldwide. COVID-19 has caused mass unemployment, a return to poverty, and the vulnerability of individual and family livelihoods, which has pushed some back into poverty [
16]. Therefore, post-pandemic migrant poverty and poverty reduction efforts should be considered in future poverty studies.
Compared to income poverty, multidimensional poverty is less volatile [
44]. The statistics of the multidimensional poverty incidence of migrant workers in our study also show that income is not sensitive to poverty evaluation. This shows that income is not the main reason behind the multidimensional poverty measurement for migrant workers, but it is also an indispensable indicator as a classical poverty measurement index. Some studies have shown that income poverty does not have strong explanatory power for the deprivation of living standards and employment rights [
49]. This conclusion is further confirmed in our study.
Table 6 shows the results of Spearman’s correlation test among different deprivation indicators of multidimensional poverty. As shown in
Table 6, the Spearman correlations between income and other indicators are not always strong, although income is generally claimed to be a measure of poverty that reflects deprivation in other dimensions. Our analysis shows that income deprivation is not correlated with some aspects of deprivation, including chronic disease and life satisfaction. Additionally, the correlation between income and health, medical insurance, and labor union poverty was not significant during 2014–2020 (
Table 7). Therefore, it is necessary to identify the poverty of migrant workers from multiple dimensions and with long-term study.
An unstable labor relation is a key factor for poverty, which leads to a low social status and social security [
50]. This is corroborated by our study. Migrant workers have a high poverty rate in terms of employment security, labor contracts, and housing fund indicators in our study. In addition, education is considered the main determinant of poverty [
51], but our study shows that in terms of the poverty rate of migrant workers, the education indicator is not an essential cause. The education poverty rate is between 20% and 40%, which is not the highest among all indicators. In the unequal labor market, some studies suggest that a high education level cannot ensure freedom from poverty and unstable employment. Additionally, this instability in work is gradually becoming a “new normal” [
52]. The growing rate of employment without labor contracts results in not only fewer working opportunities but also poverty. Such unequal labor relations have been internalized as a market “norm” and passively accepted by most workers, which covers up the seriousness of the poverty problem [
53]. By comparing the results of different years, our study found that the poverty rates related to the labor contract indicator are high. This confirms the findings of
Jo McBride and
Andrew Smith, suggesting that there is a “routinization” of in-work poverty. The precariousness of employment reduces an individual’s ability to resist risks, increases their vulnerability to poverty, and weakens the adaptation and social integration of migrants [
54].
Poverty is a dynamic process with continuity, and should be analyzed from both a static and dynamic perspective [
55]. While the angle of multidimensional poverty has been widely used in poverty research, the Chronic Poverty Research Center (CPRC) has proposed the concept of “chronic poverty” based on the poverty trap theory, which aims to examine the dynamics of poverty from the perspective of longitudinal research. Chronic poverty is defined as the situation in which people live below the poverty line for five years or more. Causing difficulty in earning a livelihood, chronic poverty represents a severe problem in a country [
56]. Chronic poverty has a close relationship with multidimensional poverty. Multidimensional poverty can be estimated in both the long and short term [
57]. Chronic poverty can be measured from a multidimensional perspective [
58]. The results of our study confirm the strong connection between chronic poverty and multidimensional poverty. In terms of poverty duration, about 30% of migrant workers were in continuous poverty from 2014 to 2020, which reveals a possibility that they might have been in multidimensional poverty for seven years. This indicates that the multidimensional poverty of migrant workers has a strong persistence. That is to say, the problem of chronic poverty is serious. This study also found that an increase in the poverty cutoff leads to a decrease in the value differences among the poverty indicators. This result shows that migrant workers in severe multidimensional poverty suffered from comprehensive deprivation, which made it more difficult for them to leave poverty. Therefore, ignorance of multidimensional and persistent poverty may result in extreme poverty and irreversible social effects. This poverty problem related to migration also exists in other countries [
59,
60,
61]. However, many studies have researched migration poverty based on household or income poverty. Our study measures poverty and its persistence for Chinese immigrant workers individually. This could be used as a methodological sample for other countries to study individual and chronic poverty.
5. Conclusions
Based on Sen’s capabilities approach, the A–F methodology and the Chinese Family Panel Studies data during 2014–2020, this study examines the multidimensional and persistent poverty of migrant workers in China. The multidimensional poverty of migrant workers was analyzed from a static to a dynamic perspective. This provided a comprehensive framework, which has been seldom covered in current research. From a static perspective, one third of migrant workers are in multidimensional poverty. The in-work poverty of migrant workers is serious, which is reflected by continuous and unstable labor relations. In addition, income, education, and health are not the main determinants of migrant workers’ multidimensional poverty. Income poverty is not a key factor in the multidimensional deprivation of migrant workers. From a dynamic perspective, the multidimensional poverty of migrant workers was obviously alleviated. The multidimensional poverty index decreased by 18% from 0.1924 in 2014 to 0.1576 in 2020. However, approximately 30% of migrant workers were in multidimensional poverty in 2014, 2016, 2018, and 2020, which may indicate that these migrant workers have suffered from persistent poverty. Specifically, because the data are sampled every two years, we cannot analyze the poverty of these immigrants annually, which is also the main limitation of this paper. The persistent poverty problem of these migrant workers needs attention and help from the government, as they are unable to leave poverty through their own efforts.