Exploring the effect of air pollution on settlement intentions from migrants: Evidence from China

https://doi.org/10.1016/j.eiar.2021.106671Get rights and content

Highlights

  • The effects of air pollution on migrants' settlement intentions in China is explored.

  • The IV-Probit model is used in this paper.

  • The China Migrants Dynamic Survey from 2015 to 2017 is used in this paper.

Abstract

Based on the China Migrants Dynamic Survey (CMDS) from 2015 to 2017, this paper uses IV-Probit model to investigate the effects of air pollution on migrants' settlement intentions in China. The results show that: First, air pollution has a significant and negative effect on intentions in settling down of the migrants. Specifically, when the concentration of PM2.5 increases by 1 μg/m3, the probability of migrants settling down in the city which they have moved to for work or business will significantly decrease by 1.89%. Second, there is heterogeneity in the effects of air pollution on migrants' settlement intentions. In detail, the sensitivity to air pollution is higher among female groups, who have higher education levels and prefer better air quality in the living place to settle down, and there is an inverted U-shaped relationship between age and settlement intentions. On the one hand, the conclusion of this paper enriches the relevant theoretical achievements of air pollution and migration. On the other hand, it also has a high reference value for developing more reasonable policies related to urban environmental governance and labor mobility.

Introduction

Air pollution is the largest single environmental health risk in the world (Hanna and Oliva, 2015), which is not only fatal, but also directly affects people's physical and mental health and subjective well-being (Song et al., 2019). People have to take measures to protect themselves, such as reducing their outdoor activities (Zhang et al., 2020), buying protective equipment, and even choosing to move away from heavily polluted cities as the pollution continues to worsen. The latter arouses the attention of academia and the public to the phenomenon of migration caused by environmental pollution. The Qin and Zhu (2018) found that if the air pollution in the city is serious 1 day, the frequency of people searching for “emigration” through the Internet will increase the next day. Unlike other countries that allow people to migrate freely, China implements unique household registration system, the so called Hukou system. People with a local hukou have access to public resources such as local education, health care and social welfare, and the hukou is not allowed to be changed at will. At present, there are two types of migrants in China: the first category is the migrant, which refers to the groups who emigrate to the destination city but the hukou remains in original city; the second category is the registered migrant, whose hukou move to the target city within the conditions of settlement. In this study, this study mainly focuses on the first group, using whether the migrants are willing to obtain hukou of the current city to show their settlement intentions. Our question is, in response to the increased demand for good air quality, what is the current impact of air pollution on the willingness of migrants to stay? Is there heterogeneity in sensitivity to air pollution between different population groups? In-depth discussion of these issues can provide micro-evidence for the formulation and implementation of relevant government policies.

A unique interpretation of the impact of air pollution on the settlement intentions of migrants is the “push-pull” theory (Lee, 1966). The theory holds that migration is the result of the combined action of the pull or attraction of the destination city and the push or repulsion of the original city. According to this theory, air pollution is often seen as a negative factor flowing into the area, which may reduce the intentions of migrant population to settle down in the city. This study expects that air pollution will have a negative impact on the migrants' settlement intentions. Combined with the current research, this study summarizes three mechanisms by which air pollution affects the settlement intentions of migrants. Three mechanisms are that air pollution in the current place of residence affects the willingness of the migrant population to settle down by causing irreversible harm to the physical and mental health, increasing the cost of living and reducing work efficiency.

The first mechanism is that air pollution causes irreversible harm to physical and mental health. In terms of physical health, the probability of suffering from respiratory tract and other diseases has increased significantly (Qiu et al., 2019; Weuve et al., 2016; Beatty and Shimshack, 2014; Liao et al., 2016). After a long-time exposure to air pollution, it even leads to the premature death of many people (Jerrett, 2015; Tanaka, 2015). Evidence from India suggested that severe air and water pollution increase early infant mortality (Greenstone and Greenstone and Hanna, 2014). In terms of mental health, previous studies have found that air pollution can cause high levels of anxiety (Power et al., 2015; Pun et al., 2017), low levels of happiness (Song et al., 2020), cognitive impairment (Zhang et al., 2018) and significantly higher rates of depressive symptoms (Li et al., 2014; Zhang et al., 2017a, Zhang et al., 2017b). Faced with higher prevalence risk, the settlement intentions of the migrant population will be significantly reduced, and moving out to cities with better air quality is one of the feasible options set for people.

The second mechanism is that air pollution increases the cost of living. The rising cost of living may motivate residents in cities affected by serious air pollution to move out. In order to deal with the risks to life and health caused by air pollution, people take some preventive or mitigation measures to avoid or reduce adverse effects, such as buying masks, air purifiers and other more expensive prevention products. There is no doubt that these measures mean a higher cost of living. (Neidell, 2008; Zhang and Mu, 2018; Ito and Zhang, 2020). In addition, in order to avoid the negative effects of air pollution on the health, people have to reduce outdoor activities such as sports and tourism (Zhang et al., 2020), and spend more money on indoor fitness. Deschenes et al. (2020) found that every unit increase of PM2.5 concentration increases the obesity rate by 0.82%, which may result in 1.89 billion yuan of medical costs in China. In addition, opportunity cost has also increased due to environmental pollution, such as the extension of residents' commuting. Previous study has manifested that people have to pay higher prices for areas with good air quality when buying houses in China (Han and Zhao, 2021). Air pollution increases both the direct cost and opportunity cost of residents, which increases the probability that residents choose to migrate to cities with lower costs.

The third mechanism is that air pollution has a negative impact on work efficiency. This will also affect migrants' settlement intentions. People generally do not like to work in a heavily polluted environment (Masuda et al., 2021), and there is a significant correlation between air pollution and the reduction of labor supply (He et al., 2019; Carson et al., 2011). Hanna and Oliva (2015) found that reduction in air pollution caused by the closure of a large oil refinery increases 3.5% in the working week of people nearby. In addition, air pollution will reduce the productivity of workers (Zivin and Neidell, 2012; He et al., 2019). Evidence from Indonesia suggests that dust haze from fires makes it more difficult for the elderly to carry heavy objects than those in non-haze areas (Frankenberg et al., 2005). Liu and Yu (2020) argued that indoor air pollution caused by cooking reduces people's ability to cope with daily activities. The decline in labor supply or productivity is a symbol of low work efficiency, which will reduce the migrants' settlement intentions in China.

Compared with the above push factors, the effects of air pollution on settlement intentions of migrant are different due to different individual characteristics. It is generally believed that the deterioration of the ecological environment will not necessarily lead to the emigration of residents, and there is a certain critical value for the “pressure” caused by local air pollution. When this critical value is not exceeded, residents continue to stay in their current city. Therefore, each resident has a critical value that matches his own characteristics, and the heterogeneity of personal characteristics determines the magnitude of the critical value. Scholars have found that there are differences in the sensitivity of groups with different characteristics to air pollution. Poor health or the elderly are relatively vulnerable to air pollution (Dons et al., 2018), and these groups are less willing to stay in areas with high levels of air pollution. Across-city and urban migrants are less affected by air pollution (Liu and Yu, 2020). The effect of air pollution on children's migration with parents is also very different because of diverse individual characteristics and family characteristics (Li et al., 2020). These findings show that people with different characteristics have different sensitivity to air pollution, which also means that there is heterogeneity in the effect of air pollution on migrants' interest in settling down.

This paper focuses on the relationship between air pollution and the settlement intentions of migrants, which has important theoretical and practical significance. In terms of theory, first, this paper enriches the research on the relationship between air pollution and migration. Different from other previous studies, this paper uses large-scale microscopic survey data at the individual level to fully explore the heterogeneous impact of air pollution on residence intention, which is very important for us to understand the individual response to environmental change (Thiede et al., 2016). Second, with the improvement of people's demand for good environmental quality, the introduction of environmental indicators into the analysis of settlement location of migrant population has important theoretical significance for accurately understanding the settlement decision-making behavior of migrants. Starting from the reality, first, the migrant population is large in scale and is gradually becoming the key driving force of China's regional economic growth. According to the China Migrant Population Development Report of 2017, the migrant population in China totaled 245 million by the end of 2016, accounting for 17% of the total population. The large-scale migrant population provide the necessary labor supply for the development of the secondary and tertiary industries in the city. A full understanding of settlement intentions of the migrants will help city managers to take corresponding measures to increase the accumulation of human capital and promote the high-quality growth of the local economy. Second, compared with the registered population, the choice of residence for the migrants is more flexible and is easily affected by the relevant policies of the city. This study provides an empirical basis for the government to formulate relevant policies.

Based on the above theoretical and practical implications, the research ideas and methods are as follows: First, the PM2.5 concentration data of 286 prefecture-level and above cities from 2014 to 2016 is calculated by using global PM2.5 satellite raster data, which is used as the measurement index of urban air pollution level. Second, this study uses the data of the China Migrants Dynamic Survey (CMDS) from 2015 to 2017 to construct migrants' settlement intentions dataset. Then, based on the matching data of air quality, micro-data from CMDS as well as abundant city characteristics data, this study uses the IV-Probit model to empirically investigate the effect of air pollution on migrants' settlement intentions. Benchmark regression shows that air pollution has a significant and negative impact on the migrants' intensions to settle down, and then this study further identifies whether this effect is heterogeneous. If this study can identify the differences in the effects of air pollution on individuals with different characteristics, this study can provide more targeted policy recommendations for city managers. Finally, the heterogeneity test is conducted based on age, gender, years of education, personal health status, and air quality of the original city. The results show that the migrants with higher level of education, poor physical health, and the better air quality in their hometown are more sensitive to air pollution when they choose to settle down in a city.

This paper contributes to the literature in the following three aspects: First, this paper uses PM2.5 satellite raster data with high accuracy and China Migrants Dynamic Survey (CMDS) data to accurately identify the effects of air pollution on migrants' settlement intentions at the micro level. The robust research findings provide new empirical evidence for migrants' residential choices. Second, in order to alleviate the adverse effects of endogenous problems on the results of this paper, in addition to controlling city characteristics and fixed effects, this study also introduces the ventilation coefficient as a tool variable of PM2.5. Third, this paper theoretically reveals the micro-mechanism that air quality may affect high-quality economic development through channels such as human capital accumulation, and provides relevant evidence for this.

Section snippets

Data and variable description

This paper investigates the effects of air pollution on migrants' settlement intentions in China. At present, studies have classified the factors affecting settlement intentions of migration into three main categories (Li et al., 2020; Liu and Yu, 2020; Hanna and Oliva, 2015), including individual characteristics, family characteristics and city characteristics. Based on these theoretical foundations, in this study, this study takes air pollution as the core explanatory variable that affects

Empirical results and analysis

In this section, this study lists the benchmark regression results and IV-Probit regression results. Table 2 reports the coefficients and marginal effects of the main explanatory variables. As a reference, this paper first uses the Probit model to estimate Eq. (2). The results are reported under columns (2)–(3) of Table 2, in which the second column reports the coefficients and the third column reports the marginal effects. As the focus of the research, this study finds that air pollution has a

RDD check

This paper implements the standardization of the variable PM2.5 concentration, that is, subtracting the breakpoint value from the PM2.5 concentration, and observing whether the migrants' settlement intentions at the air quality breakpoint shows a discontinuous change. Fig. 2 shows that migrants' settlement intentions have a significant downward jump at the air quality breakpoint 0, which preliminarily manifests that good air quality can increase the intension to settle down to a certain extent.

Heterogeneity analysis

To capture the effect of individual heterogeneity of air pollution on migrants' willingness to settle down, this paper uses IV-Probit model to carry out grouping regression from multiple perspectives, focusing on the characteristics of the individual, including age, gender, years of education and air quality of original area. Table 6, Table 7 respectively report the heterogeneity regression results of these five individual characteristics.

Conclusions and enlightenment

Air pollution has become a pervasive problem in many developing countries, and its negative impact on residents' physical and mental health has received widespread attention. With the pursuit of the quality of life, people are more sensitive to the problem of air pollution. This study explores the effect and the heterogeneity of air pollution on the settlement intentions of migrants by using nationwide survey data on Chinese migrants and city-level data regarding air pollution and

Declaration of Competing Interest

The authors declared that they have no conflicts of interest to this work. We declare that we do not have any commercial or associative interest that represents a conflict of interest in connection with the work submitted.

Acknowledgments

The authors gratefully acknowledge the financial support from the National Natural Science Foundation of China (71874189, 72173094). We also would like to thank the anonymous referees for their helpful suggestions and corrections on the earlier draft of our paper, upon which we have improved the content.

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    Qian Yue, Yan Song, and Ming Zhang contributed equally to this work, and should be considered as co-first authors.

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