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Title: Higher degree of willingness to move and better post-resettlement income restoration result: The evidence from China’s poverty alleviation resettlement1 Xiujun Tai Shanxi Normal University, Shanxi Province, China Email: taixiujun@163.com Phone: +86 13643573544 Mark Yaolin Wang Melbourne University, Melbourne, Victorary, Australia Aiguo Zhang Shanxi Normal University, Shanxi Province, China Quanbao Jiang Xi’an Jiaotong University, Xi’an, Shaanxi Province, China
1 This paper was jointly supported by the project of National Social Science
Foundation of China (12BJL076) and the project of National Social Science Foundation of China(15BMZ094).
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Higher degree of willingness to move and better post-resettlement income restoration result: The evidence from China’s poverty alleviation resettlement
Abstract: Contrary to the common belief that resettlement in China is forced, the Chinese government’s recent poverty alleviation resettlement policy and guidelines list voluntary resettlement as the number one principle. However, the guidelines are ambiguous about the concept of voluntary resettlement and how to determine such
- voluntarism. Subsequently, this ambiguity also influences the policy design and
- implementation. Using survey information collected from 554 resettled rural
households in Shanxi and Shaanxi provinces in China, this paper examines whether resettlers’ willingness to move and livelihood capital prior to resettlement has an influence on income after relocation. The results show that, despite the stipulation that resettlement must be voluntary, resettlers demonstrate diverse degrees of willingness to move. Our findings show that the greater the participation of the to-be-relocated residents during resettlement, the more likely they are to accept the new living environment, change means of livelihood actively and find a well-paid job. By contrast, those with no significant increase in income are typically either forced to move, are following the crowd or ultimately become reluctant movers as the government cuts off essential services. Our study also shows that for migrants with a low degree of willingness to move, natural and physical capital play major roles in post-move income restoration, whilst for voluntary movers, social, human and financial capital are vital. Key words: willingness-to-move; poverty alleviation resettlement; income restoration; participation; China
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I Introduction
Since 2000, the Chinese government has been making significant efforts to relocate populations living in areas, deemed ‘poverty’ areas, typically locations of harsh and fragile environment. By 2015, the central government had invested 36.3 billion RMB (US$5.5 billion) to resettle over 6.8 million from their poverty-stricken areas, under the so-called Poverty Alleviation Resettlement (PAR) program.2 According to the 13th Five-year Plan (2016-2020), in the next five years, a further 10 million people will be relocated under the PAR program. Unlike China’s other resettlement programs related to engineering projects, such as the Three Gorges Dam, PAR does not have specific deadlines and local residents do not have to forgo their farming or residential land post-resettlement. Theoretically, this offers local government enough time to ensure the conditions to enable resettlement to be ‘voluntary’ and in return, resettlers have more choices about whether to move, when to move and where to move. Thus far, PAR is considered perhaps the least controversial resettlement program in China. In fact, resettlement in China does not have a good reputation. Over the years, conflicts arising from resettlement programs have been increasing, both in number and severity (McDowell and Morrell, 2014). As the push for voluntary resettlement is intended to respect resettlers’ rights and decrease the degree of conflict, both scholars and the Chinese government officials have sought to ascertain modes of transferring involuntary resettlement into those voluntary (Chen, 2004; Chen, 2006;
2 See the news report about China’s 13th five-yea- plan http://finance.ifeng.com/a/20151016/14023471_0.shtml
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Cernea, 2008; Chatterjee, 2009; Sheng, et al., 2009; Mathur, 2013; Wilmesen, 2015). However, two fundamental research gaps can be identified in studies of voluntary
- PAR. The first one is: how does one define voluntarism? In fact, some projects labeled
as so-called ‘voluntary’ resettlement still force people to move through government tactics such as reducing or stopping the supply of water, electricity or other public services (Wilmsen and Wang, 2015), or cajoling residents to move through false promises (Yntiso, 2002). In China, many resettled are simply ‘morally hijacked’ into moving (Kai and Dan, 2007). For example, as state project related resettlement projects are part of broader national strategies, residents who refuse to relocate are accused of a lack of so-called spirit of “sacrifice individual benefit for the national benefit”. Kai and Dan (2007) argue that resettlement cannot be treated as voluntary if resettlers do not have the opportunity to say no. Scholars also argue that the boundary between voluntary and involuntary is often blurred (Xue et al., 2013; Arandel and Wetterberg, 2013). The fact that resettlement is an extensive process also complicates this dichotomy. Through a comparison of China’s PAR program (identified as voluntary resettlement in literature) and Three Gorges resettlement (identified as involuntary resettlement), Wilmsen and Wang (2015) find that some elements of involuntariness are contained in the process of voluntary migration project, whereas the phenomenon of being willing to be resettled as soon as possible exists in involuntary migration program. The second research gap is the relationship between voluntarism and performance in post-resettlement livelihood restoration. It is well established that livelihood capital
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(natural, physical, human, social and financial capital) are major factors influencing livelihood restoration after resettlement (Chambers and Conway, 1992; Ellis, 2007;Sayatham and Suhardiman, 2015; Nguyen,et al, 2016 ). The performance in post-resettlement livelihood restoration is related to the quantity and structure of one’s available livelihood capitals and whether one’s livelihood restoration strategies are appropriate (Fang et al., 2014，Pietkiewicz，2015). During the resettlement process, however, capital quantity and structures change, therefore, household livelihood strategies must change correspondingly. For example, due to reduction or total loss of farmland, a family may have to seek alternative income or seek new labor skills. Therefore, family livelihood will is likely to be insecure, at least in the short term whilst new income sources are being secured (Nakayama et al., 1999; Agnes et al., 2009). Although Cernea’s impoverishment risks and reconstruction (IRR) model (1997; 2000; 2008) and his eight impoverishment risks through displacement have since been demonstrated in many empirical studies, such as massive losses in welfare after relocation (Fang et al., 2014), few studies have focused on whether the risks and welfare losses are related to the lack of livelihood capital after resettlement or related to low degree of willingness to move. We know that voluntary migrants, based on existing definitions, have a higher degree of satisfaction than involuntary movers (Dhakal et al., 2011), and better capital restoration than involuntary ones (Li, et al., 2014), but there are few studies on the correlation between the degree of voluntariness and performance of economic restoration. Understanding this relationship is crucial in
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the search for more effective poverty alleviation policy. At present, most studies rigidly divide resettlement into voluntary and involuntary based on whether or not residents have the right to refuse relocation at time of moving. Xue et al (2013) add compulsorily voluntary and induced voluntary to full voluntary and full involuntary types of resettlement. Thus far, research has paid little attention to the empirical research about whether higher degree voluntariness for removal has a better livelihood restoration after resettlement than lower ones. The objective of this article is to examine the influence of degree of resettlers’ voluntarism on their economic recovery in the post resettlement period, and to examine the relationship between voluntariness and post-relocation livelihood restoration. The rest of the paper is organized as follows: section two introduces the practice of poverty alleviation resettlement in China; section three is research design; section four presents our results; this is followed by discussion section; the final section is conclusions and recommendations.
II The Practice of Poverty Alleviation Resettlement in China
Large-scale PAR in China began from 1983 (Tang, 2005). To encourage poor households living in “Three Wests”3region to move to more favorable natural conditions in Hexi corridor, both Ningxia Hui Autonomous Region government and Gansu province government organized China’s first large scale poverty alleviation resettlement project with the support of the central government (Feng, 1998). Both
3 Three west is the abbreviation of three extreme poverty areas in China, including,Xihaigu region in the Ningxia
Hui Autonomous Region, Dingxi region and Hexi region in Gansu province, which are jointly called Three Wests,.
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provincial governments implemented beneficial polices for the resettled, including the building of new standard houses, allocation of farmland and the creation of job
- pportunities4. New resettlement modes were adopted: resettlers could have two
houses and could keep their old house in their origin place, in addition to the new one in the resettlement site. They had the freedom to stay in the new place or leave. Another key factor for the success of this kind of resettlement in achieving its original goal is that the entire village was moved to a new location, known locally as “Diaozhuang” resettlement, literally (Diao in Chinese means lifting, Zhuang means village) “a village that has been lifted to another place”. The resettled were physically moved to a new site but villagers were able to maintain their social networks, many of their cultural traditions and living habits. Therefore, although the local government did not offer a substantial resettlement subsidy5, the resettlement program was nonetheless received positively by resettlers (Han and Gao, 2010). Hongsibao PAR district, located in Ningxia Hui Autonomous Region, is another successful case of higher degree voluntary PAR carried out by the local government. From 1998 to 2008, the Ningxia Hui Autonomous Region government spent 10 years to move over 200,000 poor people living in southern Ningxia to the new Hongsibao resettlement district. During the resettlement, resettlers could choose when and where to move. The poverty alleviation offices in the place of origin are responsible for
4 Chinese official claim the government has made a great effort in migrants livelihood restoration, records of
350,000 eco-immigration project carried out by the Ningxia Hui Autonomous Region. Detail can be seen the website of the Central People’s Government （http://www.gov.cn/jrzg/2013-06/19/content_2429020.htm，2013-06-19）,
5 There was an regulation at that time that those who move 1,000 km away can only get an allowance of 300 yuan
each and those who move nearby can only get an allowance of 100 yuan each Detail can be seen the website（http://paper.people.com.cn/mszk/html/2012-12/17/content_1187421.htm?div=-1）
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promoting, organizing, examining and approving the program, including arranging for farmers to visit the newly proposed settlement sites (Bai,2000). Due to providing these policies to guarantee the participation of targeted resettlers in understanding policy, the resettlement program assured the real participation of the resettled. As a result, these resettlers held minimal feelings of sadness and pain for at leaving their hometown as they were, on the contrary, they were looking forward to their future
- life6. For example, Mr. Li, a resettled from Huining County to Lianghu Town,
Guazhou County in Gansu province, explained that resettlement was the correct decision for his household as, with the collective efforts of his family, his household income grew rapidly: “We have an (annual) income of 80,000 yuan, more than that of 10 years in our hometown7.
”
Since 2000, with the implementation of Chinese new leader’s ‘people-oriented governing philosophy’ and an increase in the provision of poverty alleviation funds, voluntary PAR has become an explicit principle in official documents. In June 2001, China’s Rural Poverty Alleviation and Development Program (2001-2010) document was issued by the State Council, in which voluntary resettlement was listed as the most important principle to follow. Such explicit principle is the result of previous controversies around involuntary resettlement. Local governments are required to take fully into account residents’ willingness on whether to move or not for poverty
6 We can see a news report which record the process of migration and resettlement. The detail can be seen at the
website “Ningxia Immigration Musuem”（http://baike.baidu.com/view/13109755.htm）
7 Comes from a real story which describes resettlers’s living after resettlement, the detail can be seen at the
website of Sohu Finance and economics: Poverty-reduction Immigration in Three Wests, a happy life in the secondary house （http://business.sohu.com/20121114/n357523645.shtml）
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resettlement projects, when and where to move, whether the whole village will move
- r only part, whether the resettlement will be centralized or separated in a few places.
The following four principles reflect the essential of this official program: voluntary participation (qunzhong ziyuan, resettlement in local vicinity (jiujin anzhi), move according to one’s financial capability (liangli erxing) and reasonably amount of subsidies (shidang buzhu). However, despite prescriptions, voluntary PAR has in many instances not in fact been fully carried out voluntarily. In some places, despite local governments claim resettlement is voluntary, in practice, because many of rules are not clearly defined as a part of voluntarism，it gives resettlement organizer the right to explain voluntarism according to their needs and make many targeted-resettlement households move “been volunteered” sometimes. For example, people are passively acceptable or forced to move because no other choice is left, such as majority of villagers are moved, leaving few living a ghost village without proper supply of power and other rural service (Gegen, 2006). In an official PAR document released by Jinzhong City of Shanxi province
ⅰ, although the four principles
were mentioned, an order is also given that all “households living in mountain shacks must be moved out”8. In summary, the current Chinese literature distinguishes voluntary resettlement according to the policy statement of the program – which means Chinese research papers will accept a resettlement project as a voluntary one if the central government
8 In China, government documents always express both principle and order, however, in the view of
local offical,
- rders are the first priority even if contradictiory to the principle.We give a example of offical document of
Jinzhong city The detail cna be seen at the wetbsite of Poverty Alleviation and Development Office in Jinzhong City: Opinions for poverty alleviation immigration project in Jinzhong City （http://www.jzfpb.com/show.php?contentid=256，2008-12-18）
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labels the program as voluntary(Xue et al.,2013). Wilmsen and Webber (2015) found
- ut that although resettlement policy participation and voluntary resettlement are
emphasized in many resettlement plans in China, meaningful participation can be seldom seen in practice. Zhang (2013) found the local officials in a resettlement program in Xilinguole, in Inner Mongolia Autonomous Region, determined who of the migrants should go, when and where they should go despite the local government claims the resettlement is voluntary. In recent years, “targeted poverty alleviation” or “taking targeted measures to poverty alleviation” is a new poverty alleviation program which requires local government to merge poverty alleviation resources to make better use of them and take targeted measure to ensure that assistance reaches poverty-stricken villages and
- households. To do so, the Chinese government assigns nominated “poverty counties”,
“poverty villages” and “poverty households” to individual officials, who are then personally responsible for lifting these regions or households out of poverty. For these
- fficials, their annual performance review includes an index that evaluates the relative
achievement of their assigned poverty regions or households in terms of economic
- income. However, monetary compensation that includes only housing subsidy is not
sufficient to reconstruct a new livelihood for poor resettlers who just arrived a new living site. Substantial help from local government is so little that livelihood can depend only on resettlers’ own capital and determination to restore. III Research Design (I) Data
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The data in this study is derived from semi-structured interviews and household surveys in 34 PAR villages, located in western Shanxi and the northern part in Shaanxi provinces, a relatively mountainous region on the Loess Plateau along the Yellow River. The farmland is predominantly dry and hilly; farmers are scattered and, in some places, natural villages are very small, made up of only 50 to 60 individual
- villagers. In some villages, local people must walk through more than 5 km of
mountainous trails to reach the nearest main road or market. These kinds of villages are called shanzhuang wopu, mountain shacks, by local people. To assist the villagers is moving from shanzhuang wopu to flatter regions suitable for production and living, the governments of both provinces have put forward many favorable policies to attract a large number of villagers to move voluntarily (Xue et al., 2013). Six national-level poverty-stricken counties (Ji, Pinglu, Wuxiang and Kelan Countiese in Shanxi province and Yancheng and Dingbian Counties in Shaanxi province) were chosen as the data collection sites. The basic socioeconomic conditions in these sample counties are shown in Table 1. Table 1 here From March to May in 2013, we conducted a total of 260 interviews (222 households, 32 village heads and 6 local poverty alleviation officials) and 554 household surveys. Both household survey and interview recorded detailed information about people’s livelihoods before and after their resettlement, and households’ participation in village policy making during the resettlement process. The survey data will be used in our econometric modeling and household interview
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- ffers us more insight stories about how people’s willingness to move and their
livelihood capitals contribute to their income change post resettlement.
(II) Models and Variables Models
According to the livelihood theory, rural household’' livelihood capital ， including natural capital, human capital, physical capital, social capital, and financial capital, is the main factor influencing increases in the incomes of peasant household (Chambers and Conway, 1992) and post resettlement households choose appropriate livelihood strategy according to the amount and structure of their capitals to earn their income (Fang et al., 2014） . Building on this, this paper further argues that voluntariness itself is also an important influencing factor on post-resettlement livelihood outcomes. In
- rder to respond to this question, this paper establishes an econometric model as
equation (1):
k k j j i i
x x x p p Ln
3 2 1
) 1 ( （1） In order to consider whether income has increased after resettlement, this paper adopts a Binary Logistic Model to test our hypothesis. In equation (1),
i
x represents whether the resettlement is voluntary，
j
x represents the migrants’ livelihood capital after resettlement,
k
x represents other control variables which affect livelihood recovery, represents the regression coefficient and represents the residual term. These terms will be further defined below. Variable Measurement
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Dependent variables In this questionnaire, data was collected about resettled households’ income before and after their moves. This is taken as the binary variable, namely income increases after their removal (increase = 1, no increase = 0). Independent variables Voluntary resettlement Attitudes towards resettlement differ among the to-be-resettled. Those who are eager to move away from their old homes are looking forward to a new life; they will
- ften inquire about the latest news regarding the resettlement process, take active part
in meetings with organizers and actively expressed their opinions concerning about the detail of resettlement. Tang (2005) found that voluntary movers are often eager to know about the resettlement policies and are even active in directly contacting cadres in towns and villages. In contrast, those who do not wish to move are seen to show either no concern or even resist the project. So, in order to judge whether the resettled are voluntary movers or not, we need to take into consideration their attitudes towards and behaviors within resettlement, including whether and how they actively participate in the process. For example, during the period in which resettlement policies are publicized, are the resettled active in collecting information about the policies and news? In the period of removal, are they active in carrying out the removal? On the basis of their answers, resettled can be classified into four types: full voluntary, half voluntary, half involuntary and full involuntary (as in Table 2).
Table 2 here
According to the three phases we divide about the resettlement process as shown
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in Table 2, including understanding purpose of the program, decision making, and action, we classfiy resettlers’ willingness to move into four types according to the amount of participation in three phases, as shown in Table 2. This classification of four types can reflect the differencein attitude concerning resettlement. In addition, the livelihood capital owned by the resettled are designated to include natural capital (residential and cultivated land areas), physical capital (house type and area), financial capital (savings and debt), social capital (relationship network) and human capital (educational attainment and skills), among other possibilities. Control variables The control variables mainly include the time required to complete the resettlement process (as the PAR subsidy from the government increases over the years, the earlier the resettlement took place, the lower the subsidy standard) and resettlement type (whether the resettled are moving within the village border or out of the village border). (III) Method The regression method is divided into two steps which include three factors (the voluntariness of resettlement, livelihood capital and the other control variables). The first step is to analyze the influence of the three factors on the resettlers’ income
- restoration. The second step is to apply the same model regression to the four different
types of resettled, from full-voluntary to full-involuntary, aiming to distinguish the factors that influence change in income.
IV Results
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The regression results of the five models are shown in Table 3. Table 3 here As shown in Table 3, the income of half voluntary and full voluntary households increased significantly more than that of full involuntary households, which suggests that degree of voluntarism is positively associated with income restoration after
- resettlement. Though prior researches have not given the clear causal explanation
about resettler’s willingness to move and and their capability of restoring livelihood, we can find some clues to verify the relationship between the degree of voluntarism and income increase. For example, Dhakal et al. (2010) found a majority of voluntary respondents had changed their job and said they were satisfied with the employment
- pportunity, whereas only a few forced respondents had changed job. In investigating
the occupational status of each household member, we also find that 57% of the voluntary households have at least two occupations: farming and migrant work or
- ther non-farming sectors. That is, in busy seasons they are farmers and in slack
seasons they are workers. Nearly 10% of the resettled became self-employed after the move, such as by becoming convenient store operators and producing handicrafts. In contrast, amongst members of full involuntary households, only 32% have two or more occupations, 48% farm exclusively and 20% are unemployed. In addition, the presence of livelihood capital has a significant impact on income increase after resettlement. For example, as households have less cultivated land after resettlement, some have shifted to higher value-added agricultural crops to augment incomes, including cash crops such as greenhouse vegetables, traditional Chinese medicines and fruit trees. This is partially a result of the more convenient
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transportation links at the resettlement site, which increases access to markets. Table 3 also shows that as human capital is important. Resettled households with junior high, high school and above have are also seen to gain faster income increases. Meanwhile, the distance from new home to nearer market is important influence
post-resettlement income increase. The majority of our case study villages elected to either resettle within village borders, or to establish a new village, meaning that social ties generally preserved and there is no need to negotiate with other villages for site choice or access to irrigation water and other resources. Therefore, the number of relatives in 5 km is an important positive factor – 5 km only takes relatives less than half hour of commuting time to come help. Debt in resettlement and householder’s age are also negatively correlated with income increase. These observations can be explained by the fact that debt limits the family’s funds for production and that the
- lder the householder is, the more difficult it is for him to source a new means of
livelihood, which negatively affect a family’s livelihood transformation. In sum, by comparing these influencing factors in Model 2 to Model 5, we find that the main influencing factors on voluntary resettlement households (i.e. full voluntary and half-voluntary households) are social, human and financial capital (see Model 2 and Model 3, Table 3) In contrast, the main factors influencing involuntary resettlement households (including full involuntary and half-involuntary households) are natural and physical capital (see Model 4 and Model 5, Table 3). For example, the area of total residential and cultivated land are positively correlated with the income increase of both full and half involuntary households, but are not found to
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significantly influence full and half voluntary households’ income increase. This may be explained by the fact that most full voluntary and half-voluntary households have multiple income sources, rather than solely relying on agricultural production. Similarly, household size appears to have a significant positive influence on the income restoration of voluntary households, but a dramatic negative influence on involuntary ones. Labor force has a different influencing effect on income increase for voluntary resettlers and involuntary resettlers. Involuntary households have less cultivated land and no diversified employment engagement, which means more household members have to engage in less productive agricultural sector and reduce the possibility of their income increase.
V Discussion
With econometric models, we found the higher degree of willingness to move, the more income increase. However, one question still remains. Many prior researches found households who move voluntarily also have more livelihoods capital and want to acquire more development opportunity in new resettlement site (Tang, 2005). In
- ther words, the econometric models (as shown in Table 3) has endogeneity in the
resettlers voluntarism and livelihood capital, which may influence the above conclusion. In order to verify the relationship between voluntarism and livelihood capital, we compare the main capital features of the four types of resettlement before and after move (as shown in Table 4)
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Table 4 here Before resettlement, only farmland and per capita debt have a significant difference among four type resettlers, we didn’t found others livelihood capital have significant difference among four type resettlers. In fact, rural households living remote mountainous area have the same livelihood mode and little difference in capital accumulation between voluntary and involuntary households. However, after resettlement, households which are seen to move more voluntarily are generally better educated, have larger social networks and income. This means that they have greater capacity to exploit new means of livelihoods than involuntary households. Meanwhile, during the resettlement process, natural and physical capital, predominantly land, is lost to a large extent, meaning that human, financial and social capital have an expanded role to play in livelihood restoration and recreation after the resettlement. We can also compare the speed of income restoration among four type resettlers after resettlement to provide further proof for our question (Shown in Figure 1). Figure 1 here In Figure 1, a comparison is made between the subjectively perceived time required to of restore income to pre-resettlement levels of the four household types. A large proportion of the full voluntary migrant households were able to restore their income in less than 4 years, however, most full non-voluntary households required 6 years in order to achieve this state. In the process of resettlement preparation, decision making and project implementation, these households of greater voluntary tend to be more actively
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engaged in shaping public policies, take advantage of existing livelihood capitals, and help to integrate resettlers in new communities faster and better. However, those households, who are unwilling to move at first but choose to move in the end due to kinds of pressures, like to depend on government’ support passively and can not transfer their livelihood mode depend on their own effort actively. Cernea (1997) believe that local participation in planning and implementation is essential for reducing risk in the reconstruction of residents’ post -resettlement well-being. Based
- n our study, an important consideration is the people’s willing to move expressed an
attitude or confidence for future livelihood mode change. During our household interviews, it was possible to sense the differences in attitudes between the two
- verarching types of households, voluntary and involuntary. Voluntary households
frequently talk about active factors such as their plans for the future and preparation for changes in life. Even those voluntary households who remain are in poverty after resettlement do not appear to regret their decisions, and believe their difficulties are
- temporary. Involuntary households, however, are filled with criticism towards local
- governments. Even those households whose living standards have been raised by
resettlement believe that local governments have failed to carry out all the promises required of them. Some households also claim to have returned to their original homes. In fact, voluntarism only reflect resettlers’ confidence and attitudes of changing their livelihood ,which are actually important factors in income differences between resettled groups.
VI Conclusions
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In China, due to powerful government and rigid resettlement procedures, many residents in designated poverty regions are forced to relocate for purposes of poverty alleviation, moves which are seen to be either ‘compulsorily’ or ‘induced’ voluntary (Xue et al, 2013; Liu and Zhao, 2014; Xie, 2010). To be able to judge whether such resettlement is voluntary or not, we need to be able to judge their attitudes towards resettlement and participation in the resettlement process from a micro perspective. With the development of market economy in China, more and more rural households would like to relocate from remote mountainous areas to the more convenient plains, where economic opportunities are more prevalent. Simultaneously, however, many households still earn their living in traditional ways and do not wish to leave their places of origin. Things become even more complicated when local governments request their relocation and push such projects through by all means. These resettlers might follow the crowd to new homes and lives in the resettlement site, however, attitudes toward resettlement appear to affect the degree of input and effort into post-resettlement livelihood generation, which affects the household’s income restoration. Our research shows those who wish to be resettled tend to take active part in the resettlement process - a group we have called “full voluntary” resettlers in this paper - and that this group have a higher income increase and faster income restoration relative to the others. Those who are reluctant to move - known as “full involuntary” resettlers - tend to experience a decrease in incomes and slower income restoration. In addition, the capital factors influencing income restoration vary. For involuntary households, natural and physical capital play major roles in income
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restoration, whilst for voluntary groups, human, social and financial capital are key. The degrees to which households’ attitudes to resettlement are voluntary and their participation in the process are significant factors influencing the households’ income
- increase. In the restoration period, voluntary households take a more active part in
associated resettlement projects organized by local governments, and appear to be better able to analyse and judge their own post-resettlement conditions, organize their
- wn resources, and accelerate livelihood reestablishment. Li et al. (2013) finds that
voluntary migrants show more initiative and are more adaptive in livelihood transformation, by being more able to adapt to the changes caused by resettlement. By taking advantage of the new conditions of the resettlement sites in tandem with their
- wn existing resources, this group is able to generate new livelihood strategies to
match those in the former sites. However, as many of the involuntary resettled blame their unfavorable livelihood conditions on local governments’ mandatory relocation policies, their slower income restoration might also be influenced by a preoccupation with waiting for, relying on and demanding greater compensation, rather than generating meaningful income. These findings are meaningful in China. A clear policy prescription is that the central government must push local governments to focus more energy on understanding the attitudes of the to-be-resettled and actively engaging their
- participation. Local governments should guide these households to better understand
policy and participate in decision-making. It is useful to eliminate the resettlers’ worries about losing all kinds of resources such as land, livelihood, community and
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social network, or being cheated out of entitlements such as compensation and favourable site choices in the future (Cao, 2010). PAR should be designed to give people real participation opportunities and meaningful consultation before moving, help households to generate functional livelihood capitals, and support them in restoring and sustainable livelihood models after resettlement. Of course, it is difficult for government officials to judge resettlers’ willingness to move, as many to-be-relocated households hold out in the hope of higher
- compensation. Furthermore, things become more complicated neither side will make
the first concession. We think government and resettlement organizers could do more to push cooperation between local government and resettled residents. For example, the local resettlement official could implement a local committee including elected resident representatives who can then take charge of communication, decision-making, and so on.
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Reference
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Table 1 Socioeconomic Indicators in the Sample Counties in 2011
Index Ji County Pinglu County Wuxiang County Kelan County Yanchang County Dingbian County Population (10,000) 10.45 24.60 21.17 8.40 14.85 33.05 Per capita land (mu1) 2.23 1.81 2.91 8.48 15.32 6.30 Rural income (yuan/per) 3138 3249 2995 2918 2895 3620 Poverty population（10,000） 4.30 ——2 6.51 5.40 3.58 6.14 PAR subsidy* (yuan/person) 4200 3400 4200 4200 2500 3800 Data sources: Statistic data of the six counties in 2011 * The government work reports of six County in 2011. Note: 1. Mu is a unit to measure land area in China, 1mu=666.67meters square
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Table 2 Taxonomy of the resettled
full voluntary half voluntary Half involuntary full involuntary Policy understanding √ √ √ × × √ × × Participated positive √ √ × √ × × × × Active removal √ × √ √ √ × √ × Notes: √ shows active participation in the period, such as positively knowing about the policies, attending meetings and moving in time. × shows no participation in the period.
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Table 3. Results of analysis logistic models on households’ income increase Independent variables Model 1 (Whole sample) Model 2 (Full Voluntary) Model 3 (Half Voluntary) Model 4 (Half Involuntary) Model 5 (Full Involuntary)
Types
resettled households Half involuntary
0.089
Half voluntary
0.429**
Full voluntary
0.206**
Physical capital House structure Townhouse
0.455* 1.077 0.448** 0.398** 0.004
Floor space（㎡）
0.466 0.830 0.003 1.020* 0.080**
Natural capital Residential land（mu）
0.275
0.289** 0.454***
Cultivated farmland（mu） 0.412***
0.006 0.887*** 1.022**
Financial capital Expense on new houses （10,000 yuan）
0.031 0.004
Debt （10,000 yuan）
0.001
Loan for move
(10,000 yuan)
0.086* 0.072** 0.003 0.304 1.002
Human capital Household head’s(? which member of the household? the head of household?) age
0.205 0.037
Household size
0.256* 0.189***
Household head’s(??) education Primary school
1.287 1.379 1.080 0.030 0.002
Middle school
0.619** 1.265** 1.12*** 0.676* 0.338**
Senior high school and above
1.141*** 0.702* 1.32*** 0.246 0.108
Social capital Number
relatives within 5 kilometers (of
1.083* 1.784** 1.001* 0.553 0.290
Social network size
0.530 0.923* 0.603** 0.340 0.447
Other factors Resettlement time
0 .228** 0.429** 0.377 0.085 0.006
Resettlement type Outside village
0.004 0.026 0.107
SLIDE 30 30 Sample size
554 76 185 212 81
1034.46 778.52 890.06 914.44 786.24
***，**，*show the significant on 1%, 5% and 10% respectively. Ns means no significant (the same as below)
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Table 4. Capital features of households before and after resettlement
Period Full voluntary half voluntary Half involuntary full involuntary F-test Per capita cultivated farmland(mu) Before 3.37 3.36 3.85 4.02 ** After 2.02 2.03 2.05 2.02 NS Per capita woodland(mu) Before 1.23 1.17 1.03 1.54 NS After 2.72 2.04 3.03 2.66 NS Average household size (persons) Before 0.98 0.89 0.91 0.95 NS After 1.96 1.77 1.62 1.03 ** Relatives and friends (persons) Before 7.16 8.03 8.52 10.48 *** After 5.44 5.21 4.25 3.37 ** Available persons to routine help(persons) Before 6.24 7.23 6.37 6.33 NS After 5.26 4.67 4.07 4.01 * Annual per capita income(yuan) Before 3599.81 3659.56 3521.42 3391.43 NS After 4899.72 4540.18 3838.75 3333.37 *** Per capita debt (yuan) Before 1044.45 885.57 934.22 676.55 *** After 15453.2 16766.4 16344.8 15022.8 NS
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.1 .2 .3 .4 .5 Proportion of Households 2 4 6 8 10 Restoration Time(Year) Half Nonvoluntary Voluntary Nonvoluntary Half Voluntary Figure 1 Time required for four types of resettled households to restore income
