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Abstract

The China-Pakistan Economic Corridor (CPEC), a major development project in China’s fast-evolving Belt and Road Initiative (BRI), is arguably the most comprehensive of the six BRI economic and infrastructure corridors on land. For Pakistan, it is perceived “as the harbinger of a new era of connectivity and integration” that will not only transform the region’s economic development but also the well-being of Pakistanis. It investigates the impact of CPEC as perceived by the local communities in its ZoI. It also evaluates CPEC’s potential challenges: public support and local communities’ concerns such as their awareness, acceptance, and ownership of CPEC. To accomplish our research objectives, we analyze original microdata from 1,585 respondents living proximate to propose CPEC route(s) of Khyber Pakhtunkhwa province, in Pakistan. After aggregating the data on the basis of age, education, income, and social status, we conduct descriptive, bivariate, and multivariate analyses in an attempt to answer three research questions. We find significantly high level of awareness of CPEC across the board in the older age group of respondents (i.e., 40 years or older), hereinafter referred to as mature, highly educated, that is, respondents with university education. Older respondents expect more environmental and economic benefits than younger respondents, even as the latter expect lower social change and effect on migration than do the former. However, those in the upper social class expect higher economic and political benefits from CPEC, compared with those in the lower social class—an early indication of possible elite capture.

Keywords

awareness China–Pakistan economic corridor expectations elite capture potential challenges local communities western route

If BRI is like a symphony involving and benefiting every country, the construction of CPEC is a sweet melody of the symphony’s first movement.

—Wang Yi, Foreign Minister of China, in Pakistan Observer (December 19, 2019)

The China-Pakistan Economic Corridor (CPEC), a major development project in China’s fast-evolving Belt and Road Initiative (BRI), is arguably the most comprehensive of the six BRI economic and infrastructure corridors on land. For Pakistan, it is perceived “as the harbinger of a new era of connectivity and integration” (Mehdi, 2020) that will not only transform the region’s economic development but also the well-being of Pakistanis. In other words, local communities’ support of CPEC projects is associated with their perceived benefits, particularly business opportunities and overall regional development (Kanwal et al., 2020). Saad et al. (2019) also noted that CPEC projects have changed the perceptions of local communities, particularly about quality of life, better economic opportunities, and poverty reduction. For China, it is expected to provide alternative trade and energy routes and easy access to the Middle East, Africa, and Europe. Therefore, CPEC is a multipronged project that (a) offers China the shortest access to the 21st Century Maritime Silk Road on the Indian Ocean (Roy, 2019; Safdar & Zabin, 2020); (b) develops, connects, and integrates regional economies and markets (Faisal, 2019; Hussain, 2020; Khan et al., 2020; Mirza et al., 2019; Yu et al., 2020); (c) provides China a secure economic corridor, in the event of tension on the South China Sea (Gordon et al., 2020; Hali et al., 2014); and (d) ensures Pakistan’s role as a key BRI stakeholder. Therefore, the success of CPEC will not only change the economic activities of Pakistan but also the geopolitics in the region. For example, it is expected that the project will help lift 1.1 million people from poverty, because of its cross-country communication infrastructure and increasing economic activities. It will also create seven million jobs, with a 2.5% annual growth rate (Dawn, 2020). As Ramay (2020) noted, Pakistan has less sustainable opportunities to eradicate poverty; therefore, this multi-billion-dollar project can change the destiny of the people and the country.

In brief, CPEC has socioeconomic, political, and environmental impacts, both in the short run and in the long-term. Similarly, CPEC faces an array of external (geostrategic competition) and internal challenges (cost-effectiveness, public support in terms of ecocentrism, ownership, and attachment among the local communities). It is against that backdrop, that this study attempts to assess the perceived impact and potential challenges associated with the CPEC and its impact on the local people.

The CPEC Landscape

The major investment of CPEC projects falls under communication infrastructure, energy projects, the Gwadar deep-sea port, and special economic zones. Thus, it attracts investors to various sectors (Khan et al., 2020) that can play a critical role in the region’s economic activities and development. Khan et al. (2020) noted that communication networks will not only bring connectivity but also provide an opportunity to uplift the economic stature of poor cities in the entire country.

To accomplish a cross-national communication infrastructure network and its connectivity, CPEC in Pakistan is aligned with three routes: eastern, central, western. The eastern route is the most feasible, because of its existing communication infrastructure and security for early connectivity. This eastern route goes through Gilgit–Baltistan, in the northern part of Khyber Pakhtunkhwa and Punjab to Baluchistan. Ultimately, it will connect CPEC’s outsize project, Gwadar deep-seaport, considered to be the window to connect China’s Silk Road Economic Belt with the Maritime Silk Road. Another proposed route, the Central route, will connect central Punjab with Quetta and Gwadar deep-sea port in Baluchistan. This route, not much developed, needs massive investment and time to complete. This will help enhance the economic activities and lives of people of central Punjab and the impoverished districts of Baluchistan. While the last route is the western one, which will pass through Khyber Pakhtunkhwa to connect Quetta and Gwadar deep-sea port, it is the shortest among all the three proposed routes and was originally planned under CPEC; however, because of security risks, associated with its being near a tribal belt and the Afghanistan border and also its undulating terrains, the then-government proposed developing an eastern route as its first action. Thus, it made CPEC routes controversial and paved the way to politicize it among the provinces and regional political parties. These smaller provinces, Khyber Pakhtunkhwa and Balochistan, raised their voices to implement the original route which is a ray of hope to change the lives of local people and can bring development to those neglected areas. If these three proposed routes are established on schedule, they will not only develop the communication infrastructure in the country to link the big cities but will also uplift those undeveloped cities. Among all the provinces, Balochistan is the least populated and developed, despite its huge natural resources. Most of its massive natural resources are still untapped and the people also lack necessities such as quality education, health services, and communication infrastructure. It is also one of the provinces most vulnerable to local insurgencies and militant groups that have external support from India and Afghanistan have been fueling public anxieties and discord by attacking CPEC projects and officials.

Therefore, the proposed routes will link Balochistan, the most deprived province in terms of economic development and infrastructure, to the hub of future economic activities in South Asia, where the Gwadar deep-sea port will play a significant role (Rehman, 2019). In other words, Pakistan has a strategic location (see Figure 1) that CPEC will be running from the north of Pakistan to the south, across the entire country, thus, enhancing economic activities.

Figure 1.

CPEC alignments and projects.

Determinants of the Megaprojects

Megaprojects like CPEC can be the drivers of change, particularly social change and economic growth. However, it is pertinent to investigate which factors can turn a potentially successful project into a failure. For being successful in promoting expected change, besides adherence to the technical benchmarks and quality standards, involvement of or support for stakeholders and political leadership in the projects is crucial (Mišić & &Radujković, 2015). A common view is that key stakeholders of the mega projects are their developers; however, in the context of the potential impact of these projects on the local politics, communities, economies, and environment, that view is misplaced. Therefore, involvement in or support for the stakeholders for the megaprojects is crucial to enhancing the prospects of their success (Caldas & Gupta, 2017).

Conversely, the positive outcomes of the megaprojects are much-trumpeted at the regional and national levels while their adverse effects, are mostly felt by the local people in their zone of influence (ZoI), are often ignored. Therefore, an in-depth perception analysis focusing on the local communities dwelling in the ZoI megaprojects is imperative for effective impact assessment of the projects. Moreover, it is important that underlying factors, such as intangible gains (sense of belongingness, national pride) and tangible gains (employment, infrastructure development) from the projects, in the local context, are worth investigating (Delphine & Spit, 2019).

Furthermore, megaprojects particularly those undertaken in the developing countries, have numerous social, economic, technological, organizational, environmental, and geopolitical challenges (Mackhaphonh & Jia, 2017). Some of the challenges are countervailing; some are institutional power struggles among antagonistic and incendiary social segments in their attempt to increase their sphere of influence both politically and geographically (Fox, 2020) through elite capture; and some expected gains from an initiative or project are lost to influential and resourceful principals characterized by higher-education and higher-income levels (Herrold-Menzies, 2006).

In sum, megaprojects like CPEC drive forces of socioeconomic changes in a region or country; however, a profound understanding of forces detrimental to the success or failure of these projects is critical to assessing their full potential for enhancing and protecting community well-being.

Significance of the Study

Several studies (Caldas & Gupta, 2017; Delphine & Spit, 2019; Fox, 2020; Herrold-Menzies, 2006; Mišić & Radujković, 2015) have explored the determinants of megaprojects. However, the literature on such projects focuses either on their management or on the perception of local communities among various stakeholders, with limited scope or coverage of ZoI. There is, therefore, a need for a more comprehensive approach toward investigating a range of issues that could determine the success or failure of these mega projects. Besides, identifying the challenges that hinder the broad distribution of the benefits of mega projects and prohibit elite capture, particularly in developing countries, is yet to be investigated.

Several studies attempt to investigate the role of CPEC in economic development, in employment and in the livelihood of local people (Kanwal et al., 2020; Melecky et al., 2019; Saad et al., 2019). Most of these studies either employed anecdotal approaches to uncover various aspects of CPEC or adopted indirect empirical approaches to investigate megaprojects like CPEC, largely by using secondary data in lieu of firsthand data. The present study is more comprehensive in that it adopts an approach to target local communities, gathering firsthand information and exploring key determinants of CPEC through an in-depth focus on the local people dwelling in its ZoI. This requires gathering evidence on the perceptions of the local people vis-à-vis awareness of, and support for, CPEC. Further, this present study attempts to assess the perceived impact of a megaproject on overall development as reported by the local communities, with adequate coverage of the ZoI, through employing a considerably large sample, which is absent from the extant literature. We also focus on the impact the megaproject in halting migration from the ZoI. All in all, this study adopts a comprehensive approach to unpack the nexus between support for, concerns and outcomes of, a megaproject and its determinants. Moreover, we use a novel conceptual framework and an econometric model, both of which incorporate inputs from key informants, experts in the field, and representatives of local communities.

Review of the Literature

This section comprises three parts: (a) social and economic impact, (b) social support and acceptance, and (c) political support.

Social and Economic Impact

The three routes pass through remote areas and their timely completion could lead to visible and significant social change in these “socially vulnerable areas of Pakistan” (Javaid, 2019). Habib et al. (2015) study has identified ex-ante socioeconomic impact of CPEC on its beneficiaries, inhabitants of districts located on the western route of CPEC, in terms of education (attendance and enrollment), and use of health services (lady health workers). Some studies claim that CPEC’s long-term planning will enhance the socio-economic condition of the country and of its stakeholders (Javaid, 2019; Zhang et al., 2018). Noor (2019) noted that the focus on industrialization and socio-economic developments is changing the economic landscape of the country. In addition, China’s western development strategy and CPEC will eradicate poverty and improve the economy of the two partners (Zia, 2019). Whereas the first phase focuses on energy and communication infrastructure, Gwadar deep-sea port, and security, the second phase focuses on the social development of Pakistan by establishing 17 fast-track projects to improve communication infrastructure, industrial, agricultural, health, and education cooperation and the energy projects (Hali, 2020). CPEC has nine special economic zones: (a) the Rashakai Economic Zone, M-1, Nowshera; (b) China Special Economic Zone Dhabeji; (c) Bostan Industrial Zone; (d) Allama Iqbal Industrial City (M3), Faisalabad; (e) ICT Model Industrial Zone, Islamabad; (f) Development of Industrial Park on Pakistan Steel Mills Land at Port Qasim near Karachi; (g) Special Economic Zone at Mirpur AJK; (h) Mohmand Marble City; and, (i) Moqpondass SEZ Gilgit-Baltistan (Siddiqi, 2020). It is evident from the literature that a special focus on socio-economic sectors will improve the economic conditions and lives of people in Pakistan (Hali, 2020; Siddiqi, 2020). Saad (2020) argued, on the one hand, that BRI’s success “is aimed at winning the battle for hearts and minds by making the people shareholders in the journey of economic development.” Saad et al. (2019), on the other hand, concluded that CPEC projects did not change the perceptions of local people regarding their environmental protection and the quality of the education they received. Business opportunities and the ongoing CPEC projects will require skilled labor for which the government has already launched technical training centers whose effects are yet to enhance significantly community well-being. According to Saleem (2017), economic gains from CPEC are expected to mitigate the political resentment in the Baluchistan. Alam (2015) finds a positive relationship between CPEC-related initiatives and the political stability of Baluchistan. Moreover, CPEC, through its initiatives, is geared toward improving socioeconomic conditions and addressing political grievances and underlying causes of conflict.

Social Support and Acceptance

Rehman (2019) summarized CPEC’s success as three C’s: “capacity, coordination, and consensus.” She wrote, “Pakistan, undeniably, has to scale up its capacity and coordination while building consensus in identifying policy frameworks for the opportunity this platform offers.” She further added that CPEC does not belong to one party or province, so, “it requires strategic levels of consensus-building to ensure each province’s stake in the project is protected and that Pakistan’s government moves forward collaboratively.” Kanwal et al. (2020) noted in their study that CPEC success is based on local citizens’ ownership and support. Their study outcomes indicated that “perceived economic benefit, perceived education, and perceived employment have a significant relation with support for CPEC development” (p. 8). Similarly, Siddiqi and Sajid (2015) investigated popular support, sentiments, and expectations of the general public for CPEC in Balochistan. This study applied qualitative inquiry by employing an iterative thematic strategy for analysis of primary data collected through the semi-structured interviews. Results indicated a high-level optimism, hopes, and expectations from CPEC among Balochies, aside from deep reservations. The study links CPEC’s success with successfully redressing grievances and creating ownership, confidence, and capacity building in the public.

Political Support

CPEC is supported by all leading political parties in Pakistan (Dawn, 2020; The Express Tribune, 2020). Prime Minister Imran Khan affirmed its completion (The Hindu, 2020), as did CPEC Authority Chairman, Asim Saleem Bajwa, who said there will be “[n]o compromise on CPEC as it is the country’s future” [31]. The leading English-language national newspaper made the headline of a virtual conference that “[P]olitical parties unite to support ‘game-changer’ CPEC” (The Express Tribune, 2020). These reports reflect that central and provincial governments and all the leading political parties are supporting the completion of CPEC projects within the allotted timeline in seeking a better economic future for Pakistan.

Jiamei (2015) investigates the depth and breadth of the China-Pakistan relationships through existing interactions and linkages: official interactions, cultural exchanges, and people-to-people contacts between the two countries. Indeed, this people-to-people diplomacy and interactions will pave the way for better understanding and strengthening relationships among the general public of the two countries. There is a need for a similar study within Pakistan as well. Khan (2018) has noted that people-to-people diplomacy can reinforce the connection between Pakistan and China for better prospects. Awan (2020) further observed that there is frequent mutual consultation on important issues between the leaders of two countries, adding that cultural exchanges and frequent interactions will change the dynamics of local people’s approach and behaviors toward CPEC and its related projects.

Deling et al. (2016) assessed general public opinion, particularly ownership of CPEC in China. The study found favorable public opinion on CPEC; however, the official opinion on CPEC overshadowed that of the public. There is heterogeneity, based on demography in online public opinion; therefore, results obtained tend not to be reliable. However, scientific investigations on the assessment of the level of awareness, acceptance, and ownership of CPEC among Pakistanis are non-existent.

Wolf (2016) identified challenges and hurdles, both internally and externally, in CPEC implementation. The study showed that CPEC can have a great impact on cooperation within the region. Moreover, the study revealed that CPEC can be a game-changer at least for the prevailing challenges Pakistan faces. The author also forecast CPEC’s potential to change pristine civil-military ties of the country. However, such a claim should be subjected to further scientific inquiry.

Elite Capture: The Upper Social Class

Elite capture, a prevailing phenomenon in Pakistan, is widespread at the country’s social and political hierarchies. Imran Khan, Pakistan’s prime minister, asserts the need of the nation to break the elites’ hold on and dominance of national resources and public goods, and redistribute them equally and equitably in the population to alleviate poverty and to promote a broader social welfare (Bhatti, 2020). Additionally, Asad Umar, a former finance minister of Pakistan, while giving an account of the magnitude of elite capture, explained that, according to an independent study, it is equivalent to PKR 860 billion per annum in the country (Rana, 2019). Besides, the phenomenon is echoed, time and again, in the mainstream media (Mehdi, 2020; The Express Tribune, 2020); however, its causes are yet to be ascertained through scientific investigations or through concrete government actions in public-sector initiatives or projects, such as those of CPEC.

In conclusion, the lacunae in the extant literature—for example, the lack of comprehensive analysis of the ZoI and the exclusion of the socioeconomic factors that can influence the outcome of CPEC—justify the raisond’être for this present study. Perhaps most important, none of the existing studies estimates the elite capture in the context of CPEC. This study is an attempt to fills those gaps by employing a comprehensive research design.

Concerns about CPEC

There is a panoply of CPEC concerns specific to megaprojects: political aggrandizement, unfavorable outcomes, environmental degradation, feeble social fabric. For instance, the Baluchistan Liberation Movement (BLA) had concerns about CPEC and attributed the responsibility for attacks on CPEC-related projects in Baluchistan to sabotage (Wolf, 2016). Additional concerns: the local people’s and communities’ fear of being displaced from their ancestral lands, and subsequent hardships like loss of land, prolonged loss of livelihood, social alienation of affected communities, and impoverishment of cultural heritage (Ahsan, 2016; Cernea, 2004). All told, megaprojects that ignore sophisticated nature of the areas, for example, fabric of historic urban centers, can result in unfavorable outcomes including a sharp decline in the quality of life of the local people. For instance, Forouhar and Hasankhani (2018), while studying Samen Renewal Project, report a number of adversities including physical, environmental, sociocultural, and economic associated with megaprojects, with a significant decline in the quality of life of the local people, and break up of social fabric.

In sum, the support for and acceptance of CPEC among the local people are essential for its success likewise the other megaprojects (Ahsan, 2016; Cernea, 2004; Deling et al., 2016; Kanwal et al., 2020; Siddiqi & Sajid, 2015; Wolf, 2016). Contrary to this, various concerns among the stakeholders cannot only adversely affect the support of local people toward a megaproject but also hamper its progress (Kovrig, 2018). In a worst-case scenario, this apathy among the local people can morph into a political discord vis-à-vis megaprojects (Forouhar & Hasankhani, 2018; Iqbal, 2018), leading to possible sabotage by opponents.

It is against the preceding background that this study raises three research questions (RQs). It is pertinent to note here that these RQs were developed from a series of in-depth consultative meetings with experts in the field, local people, and administrators.

RQ1: What is the general level of awareness, support, expectations, concerns, benefits, and costs of CPEC among the local people?

RQ2: How do awareness, support, expectations, concerns, benefits, and costs of CPEC vary across groups of local people, based on (a) demography (older and adults), (b) influence (commoner and elite), and (c) expectations (optimists and pessimists)?

RQ3: What are the determinants of awareness, support and concerns of, and expectations from, the local people about benefits and costs associated with CPEC?

To answer those questions, descriptive, bivariate, and multivariate analyses are used, respectively. Before identifying answers to the questions, we provide in the next section this study’s conceptual postulations.

Conceptual Framework

For this study, we developed its conceptual framework (see Figure 2) as a mix of (a) additional dimensions from existing studies to fill the lacunae in the existing literature; (b) novel components—such as migration from the ZoI; and (c) local augmentation based on specific information garnered from local wisdom indicated in consultations with key informants, local leaders, field experts and local people. The framework postulates that awareness and concerns of local people can be related to outcomes of CPEC. The aforementioned relationship is explained in terms of support of or opposition to CPEC and how these can be linked to the perceived impact of the megaproject in relation to its benefits and costs. According to Ahmed (2019), local people support CPEC because they expect positive changes in their lives from various components of CPEC. In other words, we assume that the effective engagement of local communities can garner a sense of ownership among them; in its absence, then, serious concerns might arise that can result in strong opposition and even agitation among the local people. Therefore, by combining the three lettered, aforementioned factors, we propose a novel framework that underscores our empirical test in this study.

Figure 2.

Conceptual framework.

Method

This section has five subsections: study area, variable constructs, data collection, research instrument, and econometric model.

Study Area

The study area focuses on the ZoI of CPEC in the Khyber Pakhtunkhwa (KP) Province of Pakistan. The ZoI refers to an area located on the three routes: Eastern, Central, and Western of CPEC (Habib et al., 2015; Khan et al., 2018). There is large number of administrative units identified as districts, Tehsils, Union/Neighborhood Councils, Villages/Neighborhoods on the ZoI of CPEC. From the list of these units, we randomly selected districts: Abbottabad, Attock, Bannu, D. I. Khan, Haripur, Kohat, Mansehra, and Peshawar that cover all the three proposed routes. Sample districts such as Abbottabad, Attock, Mansehra, and Haripur are located on all the three proposed routes, while Bannu, D. I. Khan, Kohat, and Peshawar are on the Western route, which is the shortest among all the CPEC routes that connect Xinjiang, China, to Gwadar deep-sea port, Balochistan, Pakistan. Therefore, the study area is of great significance within the context of local communities’ perceptions and the smooth construction of CPEC routes to ensure maximum benefits for all stakeholders.

Variable Constructs

This study develops four constructs based on the extant literature (Chirikure et al., 2018; Manstead, 2018; Pawlowicz, 2019). The first are the “elites” and “commoners,” two categories based on respondents’ income levels and political participation. The second are the “older” and “younger,” two categories based on their ages. Those 40 years or older are labeled “older” respondents and those younger than 40 years, “younger.” The third are the “well educated,” with a university education while the less educated are high-school graduates. Finally, participants are also divided between “optimists” who have positive approaches toward and expectations from CPEC, and the “pessimists” who have negative ones.

Data Collection

The study employs original microdata, collected from ZoIs, through field surveys between January 2018 and December 2019. Multistage random sampling techniques are used for drawing the sample for analysis. In the first phase, we randomly selected sample districts from the list of all districts (sampling frame) located in ZoIs. In the second, we randomly drew Tehsils (subdistrict level) from the sampling frame of Tehsils situated in the districts, selected in the first phase of sampling. In phases three and four, we have selected union/village/neighborhood councils from the particular sampling frame representing sample tehsils and villages/neighborhoods randomly from its sampling frame representing the selected union/village/neighborhood councils, respectively. At the final phase of randomization, that is, the fifth, we have selected respondents/households from selected villages/neighborhoods by using the right-hand rule. Hence, the unit of analysis of this study is a household, represented by an adult permanent respondent of that particular household, from whom data are collected through a research questionnaire, as explained in the proceeding subsection. These data-collection procedures justify the methodological uniqueness of this study.

Research Instrument

We use a customized, structured questionnaire (Appendix 1) as our research tool. The questionnaire was designed after several consultative meetings of the research team and field experts. The questionnaire comprises two sections. The first includes demographic and socioeconomic information (e.g., age, gender, and education). The second section captures respondents’ perception-based information on various aspects of CPEC. This instrument was pretested on a subgroup of respondents who were then excluded from the full sample. To assess the consistency of the questionnaire, we employed Cronbach’s alpha (.8207), confirming both the internal consistency and validity of the tool (Cronbach, 1951). For data collection, the Urdu, the national language of Pakistan is widely spoken and easily understood across the nation, version of the questionnaire was used because that language is broadly spoken and understood by questionnaire administrators and prospective respondents. The total sample comprised 1,585 respondents (Table 1).

Table 1.

District-Wide Sample Distribution.^a.

District	Population^b	Sample size^c
Abbottabad	1,332,912	160
Attock	1,883,556	215
Bannu	1,167,892	145
D. I. Khan	1,627,132	195
Haripur	1,003,031	145
Kohat	993,874	135
Mansehra	1,017,643	145
Peshawar	4,269,079	445
Totals	13,295,119	1,585

Note. Table 1 prepared by first author.

The sample districts are ZoIs of CPEC.

District population is based on 2017 census data.

Sample represents .01 of total district population.

Econometric Model

Our econometric model is an attempt to quantify our novel conceptual framework. The model is an outcome of inputs from key informants, experts on the ground, and representatives of the local research community.

To explore the determinants and their impact on local communities, we employ the following econometric model, which attempts to estimate research framework proposed for this study. Our key assumption here is the success or favorable outcome or the failure of the project rests on its support from local communities or the opposition it faces among the local people in its ZoI. Stated differently, the impact of a project is a function of its support and/or opposition among the local people, as depicted by equation (1).

I m p a c t = f (S u p p o r t / O p p o s e)

(1)

Where, Impact refers to perceived benefits or costs expected by the local communities from various components of CPEC.

Further, we assume that support or opposition of local people stems from their awareness and concerns related to the project, as presented in equation (2).

S u p p o r t / O p p o s e = f (A w a r e n e s s, C o n c e r n s)

(2)

Subsequently, we have proposed the following empirical model in equation (3), based on our earlier discourse;

\begin{array}{l} {Impact}_{i} = β_{o} + β_{1} \sum C h a r a s t i c s o f R e s p o n d e n t_{i} \\ + β_{2} \sum C o s t s_{i} + β_{3} \sum B e n e f i t s_{i} + μ_{i} . \end{array}

(3)

Where, impact is measured in terms of job creation, improvement in living standards, development of infrastructure, and overall development.

The demographic characteristics analyzed are age, gender, education level, work status, income, and migration (internal and external), whereas, costs and benefits refer to social, political, economic, and environmental.

We estimate equations (1)–(3) by using STATA and subjecting our data to descriptive, bivariate, and multivariate analyses.

Results and Discussion

Results and discussion are presented in three parts, one each for descriptive, bivariate, and multivariate analyses.

Descriptive Analysis

Summary statistics of various variables are presented in Tables 2 and 3. Table 2 summarizes demographic information on respondents, their awareness and support of, and expectations from, CPEC. Table 3 presents concerns regarding CPEC, as well as changes, costs, and benefits expected from it.

Table 2.

Summary Statistics of Key Variables (N = 1,585).

Description	Variable	M	SD	Min	Max
Demographic characteristics
Age (in years)	Age	46	12	18	81
Gender (Male = 1, Female = 0)	Gender	0.986	0.117	0	1
Education	Education	10	4	0	16
Marital status (Single = 1, Married = 2, Divorced = 3, Widowed = 4)	Marital status	2.002	0.345	1	4
Monthly income (in PKR)	Income	28,883	15,805	1,000	100,000
Migrant? (Yes = 1, No = 0)	Migrants	0.460	dummy	0	1
Internal migrant (Yes = 1, No = 0)	Internal migrant	0.422	dummy	0	1
External migrant (Yes = 1, No = 0)	External migrants	0.138	dummy	0	1
Awareness
Aware of CPEC (Yes = 1, No = 0)	Awareness of CPEC	1	dummy	1	1
Support
Support of CPEC (Yes = 1, No = 0)	Support to CPEC	0.903	dummy	0	1
Timely completion
Do you expect timely completion of CPEC (its various component) (Yes = 1, No = 0)	Timely comp	0.717	dummy	0	1

Table 3.

Summary Statistics N = 1,585 (Expected Benefits, Costs, and Impacts).

Description	Variable	M	SD	Min	Max
Expected benefits
Expects environmental benefits from CPEC (Yes = 1, No = 0)	Environmental benefits	0.170	dummy	0	1
Expects economic benefits from CPEC (Yes = 1, No = 0)	Economic benefits	0.582	dummy	0	1
Expects social benefits from CPEC (Yes = 1, No = 0)	Social benefits	0.186	dummy	0	1
Expects political benefits from CPEC (Yes = 1, No = 0)	Political benefits	0.134	dummy	0	1
Expected costs
CPEC has environmental costs? (Yes = 1, No = 0)	Environmental cost	0.482	dummy	0	1
CPEC can cost in terms of law and order (Yes = 1, No = 0)	Law-and-order cost	0.513	dummy	0	1
CPEC can have other costs? (Yes = 1, No = 0)	Other costs	0.002	dummy	0	1
Impact on migration
CPEC will help halt migration row (Yes = 1, No = 0)	Halt migration	0.519	dummy	0	1
CPEC will motivate migrant to return home (Yes = 1, No = 0)	Return home	0.518	dummy	0	1

Table 2 indicates that all respondents are aware of CPEC, with more than 90% supporting it. Additionally, more than two-thirds of the respondents expect job creation and improvement in living standards and infrastructure, hence in overall development. Results in Table 2 also indicate that a majority—that is, more than, 70%—of respondents, are optimistic about the timely completion of the various components of CPEC. These descriptive statistics indicate that CPEC enjoys a high level of acceptance of the local people. This acceptance may stem from expectations of the megaproject, from improvement in living standards and from the development of improved infrastructure.

Conversely, Table 3 sums up concerns, expected changes, costs, and benefits associated with CPEC. A relatively small number, that is, more than one-third of respondents, have social and economic concerns regarding CPEC, while a much smaller number—about 10%—have political concerns about CPEC. These descriptive statistics suggest that a small number of local people had a different form of concerns about CPEC.

However, when it comes to the perceived benefits of CPEC, a fairly large proportion of respondents, about 60%, expect economic benefits from it. However, fewer than one-fifth of the respondents think that CEPC can have environmental, social, and political benefits as well. This gives an early indication that a majority of the local people prefer economic benefits to the other expected benefits.

On the expected costs of CPEC, about one-half of the respondents consider the environment and law and order to be the major costs of CPEC. Interestingly, Table 2 presents an almost similar picture when it comes to the ability of CPEC to halt the migration of local people and to provide an enabling environment—that is, an incentive—for migrants to return home. The descriptive statistics suggest that environmental costs and the deterioration of law and order can undermine progress toward a timely completion of the project. In other words, the creation of economic opportunities in different districts might attract the locals back to their hometowns from which they had migrated to larger cities.

Based on results indicated in the descriptive statistics, we further subject the variables of interest to bivariate analysis.

Bivariate Analysis

This subsection presents bivariate analysis of the covering three dimensions (demographics, social class, and expectations) identified in the previous subsection. The first, demographics, are an age-based comparison of the preferences of respondents aged 40 years or older, labeled older, versus those of younger respondents (18–39 years). The demographic information like age and experience are considered a determinant that influences the perceptions of an individual (Xie et al., 2021). Therefore, it is an effective tool and a proxy for experience-based preferences of respondents, vis-à-vis CPEC. The second, a social class-based comparison, is used for identifying elite capture, in which the lower social stratum is represented by respondents with a monthly income of less than PKR 50,000 (US$316) and education attainment of fewer than 12 years, while upper social class comprises respondents with a monthly income equal to or more than PKR 50,000 (US$316), from all the sources and education attainment of more than 12 years. The income and education-based social classes will identify the inclination of the two broader social classes toward CPEC and the possibility of elite capture, which is closely linked to the equal and equitable distribution of project outcomes. The third, a completion-based analysis, compares the expectations of optimists, that is, respondents who believe that projects under the umbrella of CPEC will be completed on schedule with those of pessimists who think antithetically. The key outcomes-based differences between the two groups are really important for not only pre- but post-completion ownership or acceptance of CPEC.

Those three dimensions are analyzed through key indicators or outcomes—that is, awareness, support, expected cost and benefits, and impact on migration of CPEC.

Table 4 summarizes comparisons based on age or level of maturity. Results show that both younger and older respondents are aware of and support CPEC, which is quite encouraging for the long-run success of CPEC. Similarly, both groups are on the same page regarding the expected cost of CPEC—that is, environmentally, economically, and socially. Again, this is a positive signal on the future of the project.

Table 4.

Age-based Bivariate Analysis (Mean Differences Between Older and Younger Respondents).

Variable	Mean for each group		Difference (T)–(C)
Variable	(T) Older (n = 1,117)	(C) Younger (n = 468)	Mean (S.E.)
Characteristics
Gender	0.983	0.987	−0.005 (0.007)
Income	27021	29747	−2726*** (796.677)
Migrants	0.647	0.495	0.152*** (0.027)
Internal migrants	0.585	0.346	0.240*** (0.027)
External migrants	0.062	0.148	−0.086*** (0.015)
Awareness
Awareness of CPEC	1.000	1.000	0.000 (0.000)
Support
Support to CPEC	0.919	0.897	0.022 (0.016)
Expected benefits
Environmental benefits	0.235	0.143	0.092*** (0.022)
Economic benefits	0.632	0.560	0.072*** (0.027)
Social benefits	0.135	0.208	−0.073*** (0.020)
Political benefits	0.150	0.128	0.022 (0.019)
Expected cost
Environmental cost	0.487	0.480	0.007 (0.028)
Law-and-order cost	0.498	0.519	−0.021 (0.028)
Other cost	0.006	0.000	0.006 (0.004)
Impact on migration
Halt migration	0.400	0.569	−0.170*** (0.027)
Return home	0.395	0.569	−0.174*** (0.027)

Note. Where ***, ** and * stands for p < .01, p < .05, p < .3, respectively.

However, a divide among the groups, based on environmental, economic, and social benefits, can also be observed. Older respondents expect higher environmental and economic benefits from CPEC than do the younger ones, a logical outcome in that the former have a better understanding based on their life experiences. However, the former expect lesser social benefits than the latter, which is also true in that the young tend to have better exposure to media-profiled events because of their frequent access to social media. Both groups have a similar stance on the political benefits of CPEC.

On the expected impact of CPEC on migration, the youths are more optimistic than older respondents, based on their tendency to better understand the economic power of development infrastructure and the resulting boost to the local economy through the enhancement of business activities.

Results in Table 5 present social class-based comparisons between the upper and lower social classes. A surprisingly high level of awareness of and support for CPEC can be observed across the board, irrespective of social class and influence. This can be an early indication of the remarkable future performance of CPEC. Moreover, no difference is observed among the groups, based on CPEC’s expected cost and impact on migration. However, the upper social class has higher expectations of economic and political benefits of CPEC than the lower social class, a result consistent with mass media claims of the widespread practice of the elite’s capturing the expected benefits of megaprojects. One of the underlying causes of the persistent elite capture is the inability of the lower social class to perceive the economic and social benefits of megaprojects. Therefore, national and local governments have to carve out a major role for their capacity-building efforts directed at marginalized segments of the society—that is, the least affluent and resourceful.

Table 5.

Social Class-Based Bivariate Analysis (Mean Differences Between the Commoner and the Elite).

Variable	Mean for each group		Difference (T)–(C)
Variable	(T) Commoner (n = 1,352)	(C) Elite(n = 233)	Mean (S.E.)
Characteristics
Age	38.648	47.416	−8.768*** (0.749)
Gender	0.991	0.985	0.006 (0.007)
Work status	1.322	2.038	−0.716*** (0.087)
Income	30420	28563	1856 (973)
Migrants	0.567	0.536	0.031 (0.035)
Internal migrants	0.506	0.401	0.106*** (0.035)
External migrants	0.060	0.133	−0.073*** (0.018)
Awareness
Awareness of CPEC	1.000	1.000	0.000 (0.000)
Support
Support to CPEC	0.923	0.900	0.023 (0.019)
Expected benefits
Environmental benefits	0.193	0.166	0.027 (0.028)
Economic benefits	0.639	0.572	0.068* (0.034)
Social benefits	0.180	0.187	−0.007 (0.027)
Political benefits	0.227	0.118	0.109*** (0.029)
Expected cost
Environmental cost	0.515	0.476	0.039 (0.036)
Law-and-order cost	0.481	0.518	−0.038 (0.036)
Other cost	0.004	0.001	0.003 (0.004)
Impact on migration
Halt migration	0.536	0.516	0.020 (0.035)
Return home	0.528	0.516	0.012 (0.035)

Note. Where ***, **, and * stand for p < .01, p < .05, and p < .3, respectively.

Table 6 shows comparisons between the optimists and the pessimists. However, the level of support among the optimists is higher than that of the pessimists. Both groups have similar expectations regarding the environmental benefits of CPEC. However, interestingly, the pessimists expect higher environmental costs than social and economic benefits from CPEC, compared with the optimists. Moreover, the optimists expect CPEC to have higher political benefits and impact on migration.

Table 6.

Completion-based Bivariate Analysis (Mean Differences Between Optimists and Pessimists).

Variable	Mean for each group		Difference (T)–(C)
Variable	(T) Optimists (n = 1,136)	(C) Pessimists (n = 449)	Mean (S.E.)
Characteristics
Age	45.274	46.465	−1.191 (0.702)
Gender	0.987	0.986	0.001 (0.006)
Work status	2.218	1.820	0.399 (0.115)
Income	30127	28471	1656 (1048)
Migrants	0.432	0.583	−0.151*** (0.028)
Internal migrants	0.296	0.464	−0.168*** (0.026)
External migrants	0.136	0.117	0.019 (0.019)
Awareness
Awareness of CPEC	1.000	1.000	0.000 (0.000)
Support
Support to CPEC	0.931	0.893	0.038* (0.015)
Expected benefits
Environmental benefits	0.196	0.160	0.036 (0.022)
Economic benefits	0.459	0.630	−0.171*** (0.028)
Social benefits	0.136	0.206	−0.070*** (0.020)
Political benefits	0.220	0.100	0.120*** (0.022)
Expected cost
Environmental cost	0.419	0.507	−0.088*** (0.028)
Law-and-order cost	0.568	0.491	0.077*** (0.028)
Other cost	0.004	0.001	0.004 (0.003)
Impact on migration
Halt migration	0.626	0.477	0.149*** (0.027)
Return home	0.628	0.474	0.154*** (0.027)

Note. Where ***, **, and * stands for p < .01, p < .05, p < .3, respectively.

In sum, there is across-the-board awareness and support of CPEC, regardless of age-based and social-class-based differences. The older or mature respondents expect more environmental and economic benefits than their younger counterparts, while the latter expect lower social change and effect on migration than the former. However, the upper social class expects higher economic and political benefits from CPEC, compared with the lower social class—an early indication of possible elite capture.

Multivariate Analysis

This subsection applies multivariate analyses to explore further the determinants of CPEC. The analysis comprises an estimation of six models, with dependent variables as key indicators: (a) support (Model 1), (b) job creation (Model 2), (c) contributions toward living standards (Model 3), (d) infrastructure improvement (Model 4), (e) overall development (Model 5), and (f) timely completion of various components of CPEC (Model 6). The independent variables used in the models comprise demographic variables of respondents, that is, gender, income, educational level and age bracket; and migrant status, that is, whether migrant is internal or external. Moreover, we employ additional independent variables identified through bivariate analysis: cost (economic, social, and political) and benefits (environmental, economic, and social).

Results of all six models, presented in Table 7, show that support for CPEC has a negative association with all cost-based dimensions, while there is a positive relationship with all variables representing benefits; however, the relationship is statistically significant only for environmental and political benefits. The results also indicate that support of local people vis-à-vis CPEC is contingent on its expected costs and benefits; however, in the case of environmental and political costs and benefits, the support is conditional and binding. In other words, a significantly large proportion of the local people have high level of political and environmental sensitivity. Therefore, a great deal of cautiousness is required while dealing with such situations of a high level of sensitivity regarding a megaproject (Kanwal et al., 2020; Siddiqi & Sajid, 2015).

Table 7.

Multivariate Analysis for Dependent Variables (Using Cross-Sectional [OLS] to Estimate).

Independent variables	Model 1	Model 2	Model 3	Model 4	Model 5	Model 6
Independent variables	Support for CPEC	Expected jobs	Living standards	Infrastructure improvement	Overall development	Timely completion
Gender	0.080 (0.119)	−0.107 (0.147)	0.037 (0.162)	−0.144 (0.133)	0.087 (0.111)	−0.246 (0.160)
Income	0.000 (0.000)	0.000 (0.000)	0.000 (0.000)	0.000 (0.000)	0.000*** (0.000)	0.000 (0.000)
Migrants	0.113 (0.217)	0.204 (0.267)	−0.277 (0.295)	0.155 (0.243)	0.141 (0.202)	0.246 (0.292)
Internal migrants	−0.186 (0.217)	−0.277 (0.267)	0.196 (0.295)	−0.160 (0.243)	−0.017 (0.202)	−0.158 (0.292)
External migrants	−0.173 (0.219)	−0.368 (0.271)	0.161 (0.299)	−0.199 (0.246)	0.075 (0.205)	−0.230 (0.295)
Young	0.031 (0.020)	0.118 (0.024)	0.016 (0.027)	0.008 (0.022)	−0.068*** (0.018)	−0.121*** (0.026)
Higher education	0.001 (0.024)	0.048 (0.030)	0.008 (0.033)	0.032 (0.027)	0.095*** (0.023)	0.068* (0.032)
Economic cost	−0.011 (0.026)	−0.056 (0.032)	−0.089** (0.035)	−0.041 (0.029)	0.075*** (0.024)	−0.159*** (0.035)
Social cost	−0.025 (0.027)	−0.066* (0.033)	−0.067 (0.036)	−0.054 (0.030)	0.084*** (0.025)	−0.005 (0.036)
Political cost	−0.002 (0.039)	−0.008 (0.048)	0.021 (0.053)	0.071 (0.044)	0.096*** (0.037)	−0.070 (0.053)
Environmental benefits	0.092*** (0.032)	0.069 (0.039)	0.106** (0.043)	0.038 (0.036)	−0.088*** (0.030)	0.150*** (0.043)
Economic benefits	0.041 (0.028)	−0.032 (0.034)	−0.004 (0.038)	0.014 (0.031)	−0.080*** (0.026)	0.253*** (0.037)
Social benefits	0.020 (0.030)	0.049 (0.037)	0.071 (0.041)	0.059 (0.034)	−0.059* (0.028)	0.240*** (0.041)
Political benefits	0.106*** (0.032)	0.152*** (0.040)	0.204*** (0.044)	0.062 (0.036)	0.037 (0.030)	−0.004 (0.044)
Constant	0.764 (0.122)	0.932 (0.150)	0.772 (0.166)	0.982 (0.137)	0.845 (0.114)	0.861 (0.164)
R-squared	0.231	0.774	0.516	0.227	0.725	0.231
F-statistics	3.200	7.720	5.000	2.140	7.190	10.840
Level of significance	0.000	0.000	0.000	0.008	0.000	0.000
Number of observations	1,303	1,303	1,303	1,303	1,303	1,303

Note. Estimated by OLS (i.e., linear probability model, above mentioned dependent variables), with robust standard errors reported in brackets. Where ***, **, and * stands for p < .01, p < .05, and p < .1, respectively.

The demographic and migrant status is consistent in all six models except for the older and highly educated with great expectations from timely completion and development through CPEC. The economic, social, and political costs have a negative and insignificant associations with most of the outcome variables, except for two—infrastructure improvement (Model 4) and overall development (Model 5). For Model 4, the relationship is statistically insignificant while in case of Model 5, it is significant.

These results imply that either delay in completing components of CPEC or its inability to improve living standards as expected by local people can raise the total perceived cost of the CPEC. Similarly, a soaring social cost can be expected in case of CPEC’s inability to create jobs contrary to the expectation of the local people, as failure to create jobs through a megaproject is associated with high initial social cost of the project (Sultan et al., 2017). Our findings are generally consistent with those of Saad et al. (2019), which claim that CPEC has the potential to create job opportunities for the local people. All in all, according to Ahmed (2019), local people support CPEC because of their expectations of positive changes in their lives from implementing various components of CPEC.

Conversely, our results show that all components of costs, that is, economic, social, and political, which have a positive and significant association with overall development, will increase initially. These findings are consistent with those of Shoukat et al. (2016), who reported that CPEC can develop infrastructure and create jobs through offering new business opportunities.

Our results depict higher level of sensitivity of local people vis-à-vis social and political costs of CPEC. Local people are more exposed to the initial social and political costs of a megaproject (Forouhar & Hasankhani, 2018). It is, therefore, recommended that those at the helm of affairs at CPEC be mindful of social changes, especially those that may result in a cultural backlash or in an unfounded fear of Chinese domination in the region that can spark political turmoil.

We find that the outcome variables have positive association with most of the variables capturing the benefits—that is, the, environmental, economic, social, and political. However, positive and significant relationships persist between environmental and political benefits and support for CPEC, suggesting that all three factors are closely associated.

Similarly, political benefits also have a positive significant relationship with job creation and improvement in living standards. That result indicates that the political benefits of an initiative like CPEC can be associated with improvement in living standards or in jobs creation. Moreover, all three variables—environmental, economic, and social—used to capture benefits are found to have positive and significant relationship with the outcome variables. The results suggest that the development goal of CPEC can never be realized until and unless the megaproject provides the desired level of economic, environmental, and social benefits. The projects under the umbrella of CPEC can accomplish its long-term goals such as jobs creation, environmental safety improvements and improvements in local living standards (Hussain, 2020; McCartney, 2018).

As this study demonstrates, all the outcome variables have a negative and insignificant relationship with internal and external migration, while they have a positive and insignificant relationship with overall migration. In that context, CPEC does not affect migration in the short term. The implication is that it will take a considerably longer time for CPEC to create job opportunities and to attract migrants to return to their homes.

It is clear from this study that there is an overwhelming awareness of and an across-the-board support for CPEC. Therefore, it is pertinent for both Pakistan and China to capitalize on this support, while working toward accommodating the social and political concerns of the general public by providing timely and across-the-board benefits—that is, jobs creation through timely completion of CPEC projects. To the degree that our findings are consistent with those of earlier studies (e.g., Ali et al., 2018; Hussain, 2020; McCartney, 2018) that show that infrastructure development can benefit local people by providing new opportunities (of employment and business), access to better infrastructure (particularly health and education institutions), and improvement in overall living standards, we conclude that CPEC is on track toward making a significant contribution to social well-being.

Robustness Checks

To check the fit of the six models and the robustness of their results, we used an array of robustness procedures. First, we used robust standard errors (in parentheses) clustered at the village level. Second, to control for village-level unobservable affects, we added village-fixed effects to the list of explanatory variables in all six models, with the goal of clearly estimating our models. The estimation results are more or less consistent with those reported in Table 7. Third, to further confirm the robustness of our results, we estimated all of our models by including pre-CPEC characteristics of villages—that is, before completing CPEC project(s), for example, connectivity with local major business centers. The resulting estimates were generally consistent with results appended in Table 7.

Conclusion and Policy Suggestions

The study analyzes awareness, support, perceived benefits, costs, and impact of a megaproject under the aegis of CPEC. This study shows that CPEC has considerable visibility, public support, and ownerships among the local people. Moreover, the study shows that perceived costs of CPEC are outweighed by its benefits.

The findings of this study have five major implications for policymaking, particularly at the planning and implementation levels of megaprojects.

First, CPEC management, in consultation with other stakeholders, must ensure pragmatic policies to increase the outreach of its project benefits at the grassroots, particularly to the poor and underprivileged segments of society. This will be a gesture to reciprocate the widespread ownership of and support for the megaproject.

Second, the current administration will have to live up to the local people’s expectations of CPEC, particularly in terms of jobs creation, employment, and economic turnarounds. To respond to those expectations, policymakers and implementation teams will have to consider the interests of local communities, ensuring inclusion through various stages of CPEC’s agenda planning and execution. The authorities must have to engage the local people across the board, from upper social class elites to the bottom rung, at different levels of CPEC projects management, that is, identification and implementation with a key priority to create jobs for local people (International Crisis Group, 2018).

At the same time, the success of this megaproject is also crucial for China as it may define the future investment strategies of the Chinese government and China-based companies that set up shop in Belt and Road countries.

Third, this study has also identified various concerns of the local people, especially those about route diversions and subsequent deprivation of the smaller province in terms of job opportunities, and regional economic growth. These concerns emanate from a degree of secrecy regarding certain components of the project. To dispel doubts of the local people, the administration should engage in clear communication by disclosing the details of CPEC’s components to invite a strong support from influencers in the local community. A clear communication mechanism on project progress will create sustainable support and ownership among the local people. To optimize the positive impact of CPEC and minimize its negative effects, CPEC authorities must prioritize the welfare of local people rather than offer a one-time economic boost from the huge spending on a megaproject (Kovrig, 2018). The effective involvement of local people, across the board, is essential to neutralize opposition to CPEC (Landry, 2021).

Fourth, this study also highlights security concerns, at local and regional levels, related to CPEC. The security issues can be managed, to a certain extent, by organizing special security forces for CPEC. However, to eliminate security threats, there is a need for further investigations of the dynamics of local and regional security threats to CPEC. Some of the internal potential threats can be minimized by involving local communities full well in CPEC regional projects, based in different provinces. This ownership among the local people will be an ultimate source to protect those projects from internal factors at a sustainable level.

Finally, there is an urgent need to clarifying doubts and apprehensions of the local people and of stakeholders regarding timely completion of various components and routes of CPEC, in accordance with its original plan and with mechanisms for across-the-board distribution of its benefits equally and equitably among local people (International Crisis Group, 2018). Sustainable cooperation and coordination, both at provincial and central levels, can guarantee its success, which cannot only revolutionize the economic activities in Pakistan but also help in alleviating poverty by providing job opportunities and a lifeline through a well-developed communication infrastructure.

Moreover, people involved the policy making must take into consideration the long-term environmental aspects of CPEC in ecologically sensitive and rural areas. Our findings indicate that the local people are not much concerned about the environmental cost of CPEC at the moment. However, with the passage of time, as more projects are commissioned and the environmental issues associated with them are exacerbated, stringent policies for curtailing environmental effects of the projects must be required.

These policy implications are at the heart of the Chinese wisdom, according to which public-sector investments in mega-infrastructure projects boost economic growth, bring social stability, and hence improved law and order (Mardell, 2020).

Future Research Directions

In future research, we intend to augment the data of this study with village- and household-level data from the study area and to have an in-depth, three-tiered (individual-, household-, and village-level) analysis.

In addition, we suggest a comparative cross-country analysis, which will focus on various aspects of similar projects implemented under BRI in different countries. We expect that the proposed study will improve our knowledge base on BRI beyond Pakistan.

Further, it will be interesting to investigate how CPEC can affect the welfare of local people in terms of improved incomes or consumption patterns, particularly at the grassroots.

Finally, there could be a research study on the political impact or consequences of CPEC in terms of its ability to engender favorable sentiments, goodwill, and public opinion of local people vis-à-vis Pakistan and China through the use of qualitative and quantitative analyses.

Footnotes

Appendix 1 Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This work was supported by the North Minzu University Annual Research Project [Grant Number PKST2020].

ORCID iD

Nadeem Akhtar

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Exploring the Determinants of the China-Pakistan Economic Corridor and Its Impact on Local Communities

Abstract

Keywords

The CPEC Landscape

Determinants of the Megaprojects

Significance of the Study

Review of the Literature

Social and Economic Impact

Social Support and Acceptance

Political Support

Elite Capture: The Upper Social Class

Concerns about CPEC

Conceptual Framework

Method

Study Area

Variable Constructs

Data Collection

Research Instrument

Econometric Model

Results and Discussion

Descriptive Analysis

Bivariate Analysis

Multivariate Analysis

Robustness Checks

Conclusion and Policy Suggestions

Future Research Directions

Footnotes

Appendix 1

Declaration of Conflicting Interests

Funding

ORCID iD

References