Access to homebuyer credit and housing satisfaction among households buying affordable apartments in urban Vietnam

Nguyen Tuan Anh; Tran Quang Tuyen; Vu Van Huong; Luu Quoc Dat Article Access to homebuyer credit and housing satisfaction among households buying affordable apartments in urban Vietnam Cogent Economics & Finance Provided in Cooperation with: Taylor & Francis Group Suggested Citation: Nguyen Tuan Anh; Tran Quang Tuyen; Vu Van Huong; Luu Quoc Dat (2019) : Access to homebuyer credit and housing satisfaction among households buying affordable apartments in urban Vietnam, Cogent Economics & Finance, ISSN 2332-2039, Taylor & Francis, Abingdon, Vol. 7, Iss. 1, pp. 1-17, https://doi.org/10.1080/23322039.2019.1638112 This Version is available at: https://hdl.handle.net/10419/245266 Standard-Nutzungsbedingungen: Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden. 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If the documents have been made available under an Open Content Licence (especially Creative Commons Licences), you may exercise further usage rights as specified in the indicated licence. https://creativecommons.org/licenses/by/4.0/ Full Terms & Conditions of access and use can be found at https://www.tandfonline.com/action/journalInformation?journalCode=oaef20 Cogent Economics & Finance ISSN: (Print) 2332-2039 (Online) Journal homepage: https://www.tandfonline.com/loi/oaef20 Access to homebuyer credit and housing satisfaction among households buying affordable apartments in urban Vietnam Tuan Anh Nguyen, Tuyen Quang Tran, Huong Vu Van & Dat Quoc Luu | To cite this article: Tuan Anh Nguyen, Tuyen Quang Tran, Huong Vu Van & Dat Quoc Luu | (2019) Access to homebuyer credit and housing satisfaction among households buying affordable apartments in urban Vietnam, Cogent Economics & Finance, 7:1, 1638112, DOI: 10.1080/23322039.2019.1638112 To link to this article: https://doi.org/10.1080/23322039.2019.1638112 © 2019 The Author(s). This open access article is distributed under a Creative Commons Attribution (CC-BY) 4.0 license. Published online: 11 Jul 2019. Submit your article to this journal Article views: 636 View related articles View Crossmark data Citing articles: 1 View citing articles GENERAL & APPLIED ECONOMICS | RESEARCH ARTICLE Access to homebuyer credit and housing satisfaction among households buying affordable apartments in urban Vietnam Tuan Anh Nguyen 1,2 , Tuyen Quang Tran 1 *, Huong Vu Van 1 and Dat Quoc Luu 1 Abstract: This study examines the relationship between the access to homebuyer credits and housing satisfaction among those buying affordable apartments, using a sample of 1,000 respondents from our own survey in 2016 in Hanoi, Da Nang and Ho Chi Minh Cities. Our regression analysis reveals the education level, the size and value of apartments are closely linked with the access to preferential homebuyer credits. Notably, we find that the access to preferential home loans has a strongly positive impact on housing satisfaction, after controlling for all other factors in the model. Thus, the finding confirms that preferential home loan programs play an important role in helping low-income households own affordable apartments and increase their housing satisfation. We also find that some other features of their apartments, such as the number of bathrooms and balconies, the distance from the apartment building to schools, bus stations and markets, are strongly linked with housing satisfaction. Subjects: Urban Economics; Urban Policy; Economics Keywords: affordable apartments; homebuyer credit; housing satisfaction; Vietnam ABOUT THE AUTHORS Dr Tuan Anh Nguyen works as a researcher at the Center for Socio-Economic Analysis and Databases (CSEAD), VNU University of Economics and Business and Commission for the Management of State Capital at Enterprises,Vietnam.Hisresearch interests include housing policies; micro-finan- cial analysis and applied micro econometrics. Dr Tuyen Quang Tran is the director of the Center for Socio-Economic Analysis and Databases (CSEAD), VNU University of Economics and Business. His research interests include rural livelihoods, institution and development, and policy impact evaluation. Dr Huong Vu Van is a senior lecturer in economics at the Department of Development Economics, VNU University of Economics and Business and CSEAD. His research interests include firm performance and urban studies. Dr Dat Quoc Luu is a senior lecturer at the Department of Development Economics, VNU University of Economics and Business and CSEAD. His research interests include Supply chain management, Logistic management.. PUBLIC INTEREST STATEMENT This study examines the role of the access to homebuyer credits in buying home and housing satisfaction among those buying affordable apartments in Hanoi, Da Nang and Ho Chi Minh Cities. The study shows that the education level of home buyers, the size and value of their apartments increase the chance of their access to preferential homebuyer credits. Notably, we find that the access to preferential home loans has a strongly positive impact on housing satisfaction. We also find that some other features of apartments, such as the number of bathrooms and balconies, the distance from the apartment building to schools, bus stations and markets, are strongly linked with housing satisfaction. Our research finding confirms that preferential home loan programs play an important role in helping low-income households own affordable apartments and increase their housing satisfaction. Nguyen et al., Cogent Economics & Finance (2019), 7: 1638112 https://doi.org/10.1080/23322039.2019.1638112 © 2019 The Author(s). This open access article is distributed under a Creative Commons Attribution (CC-BY) 4.0 license. Received: 02 May 2019 Accepted: 14 June 2019 First Published: 01 July 2019 *Corresponding author: Tuyen Quang Tran, Center for Socio-Economic Analysis and Databases, VNU University of Economics and Business, Level 2, G4, 144 Xuan Thuy Street, Cau Giay District, Hanoi, Vietnam Email: [email protected] Reviewing editor: Francesco Tajani, University of Bari, Italy Additional information is available at the end of the article Page 1 of 17 JEL classification: D4; D6; D11 1. Introduction Rapid urbanization and population growth have created a high demand of housing units in Vietnam’sbig cities. It is reported that about one fifth (approximately 4.8 million households) of Vietnam’s24.2million households were living in poor accommodation (WB, 2015). Especially, the housing shortage would continue to rise as the number of urban households are projected to increase to 10.1 million in 2020 (from 8.3 million in 2015) and the proportion of urban population is estimated to reach 50% by 2040. This shows that about 374,000 additional units are needed in cities annually (WB, 2015). While Vietnam’s approach to housing policy has shifted from a centrally planned public housing approach to a market-oriented system, this market-based approach has not met the demand for more affordable housing (social and cheap commercial housing) and has pushed up house prices beyond the affordability of low and middle-income households, especially in big cities (Nguyen, Tran, Vu, & Luu, 2018). Despite the housing price in Vietnam is not so high compared to that in neighboring countries, the ratio of house price to income in Vietnam is very high when the figures in Hanoi and Ho Chi Minh cities (HCMC) are 28 times and 18 times higher than that of Singapore, respectively (CBRE, 2014). Thus, affordable apartments 1 have been in huge demand in urban Vietnam (WB, 2015). Access to housing finance is considered to be an important factor for low-income residents in buying affordable apartments in urban Vietnam (WB, 2015). Despite the regulations, procedures and conditions of homebuyer credit (e.g., VND 30 trillion package for low-income households or commercial home loans) are publicly disclosed and quite straightforward, there have been obstacles to accessing the home loans for home buyers in Vietnam (Hoai Lam, 2018; WB, 2015). This motives the current study to examine what factors affecting the access of households to homebuyer credits in Vietnam. Housing satisfaction is commonly used as one of the main indicators measuring the overall housing performance in many empirical studies (Nguyen et al., 2018). This is because housing satisfaction denotes the perceived quality of the home in terms of an overall attitudinal evaluation (Aragonés, Francescato, & Gärling, 2002) and the literature shows that housing satisfaction has been widely employed to evaluate the performance of all types of residential environments (Amole, 2009; Aragonés et al., 2002). Therefore, the current study also investigates whether the access of home buyers to homebuyer credits affects their satisfaction with affordable apartments, after controlling for other household and apartment characteristics. Thus, the main objectives of the current study were to (i) examine factors affecting the access to homebuyer credits and (ii) to measure the impact of home loan access on housing satisfaction among those buying affordable apartments in there big cities of Vietnam. We find that the education level of home buyers and some characteristics of apartments have a close link with the access to home loans. Interestingly, our study provides the first evidence that the access to preferential homebuyer credits has a significant and positive effect on housing satisfaction. Thus, the finding confirms that preferential home loan programs play an important role in helping lowincome households own affordable apartments and increase their housing satisfaction. 2. Data and methods 2.1. Study site and data collection This study was conducted in three big cities of Vietnam, namely Hanoi City, Ho Chi Minh City (HCMC) and Da Nang City. These are selected because Hanoi is the capital, HCMC is the largest city while Da Nang is the largest City in the central region. A multistage sampling technique was used for sample selection for the study. In Hanoi, six districts were randomly selected from the list of Nguyen et al., Cogent Economics & Finance (2019), 7: 1638112 https://doi.org/10.1080/23322039.2019.1638112 Page 2 of 17 districts which have both social apartment and cheap commercial apartment projects. In each selected district, one social apartment project and one cheap commercial apartment project were randomly selected. Twenty-five households living in the selected social apartment project and 50 households living in the selected cheap commercial apartment project were randomly selected, yielding a total of 450 households in Hanoi. The similar sampling method was also applied for the survey of 450 households in HCMC. In Da Nang City, two districts were randomly selected from the list of districts having both social apartment and cheap commercial apartment projects. In each selected district, one social apartment project and one cheap commercial apartment project were randomly selected. Fifteen households living in the selected social apartment project and 35 households living in the selected cheap commercial apartment project were randomly selected, generating a total of 100 households in Da Nang. Thus, the total sample for the current study includes 1,000 households in three big cities. The survey was carried out from the beginning of July to the end of September 2016, and the data were collected by means of face-to-face interviews with the heads of households. In our research, respondents are all house owners and thus no house renters were involved in the survey. 2.2. Analytical models The statistical analyses applied in the current study include descriptive statistics and multiple regression analysis. First, we examine factors associated with the access of households to various sources of home loans. Next, we investigate the impact of home loan access, among other household and apartment-related factors, on housing satisfaction among residents living in their affordable apartments in the study area. Because the response variable (access to home loans) is a polychotomous variable having three categories, a multinomial logit model (MLM) was used to identify factors affecting the likelihood of a household being a non-borrower, a borrower with a preferential home loan or a borrower with commercial home loan. A number of studies have used the MNL for estimating the likelihood of a housing borrowing loans from informal or formal credit sources (Doan & Tran, 2015) or the probability of a small and middle-sized enterprise borrowing a formal or informal loan in Vietnam (Nguyen & Luu, 2013). Let P ij (j= 1, 2, 3) expresses the probability of being in a given borrowing group of a household iwith: j= 1 if the household belongs to the non-borrowing group; j= 2 if the household falls into the preferential home loan group; and, j= 3 if the household is in the commercial home loan group. Then, the multinomial logit model is given by Pij j¼kjXi ðÞ¼ exp βkXi ðÞ ∑3 j¼1exp βjXi  j¼1;2;3ðÞ In order to make the model identified, β j is set to zero for one of the categories, and coefficients are then interpreted with respect to that category, called the reference or base category (Cameron & Trivedi, 2005). Thus, set β j to zero for one of three groups (says the non-borrowers), then the MNL model for each group can be rewritten as: Pij j¼kjXi ðÞ¼ exp βkXi ðÞ 1þ∑3 j¼1exp βjXi  j¼1;3ðÞand Pij j¼2jXi ðÞ¼ 1 1þ∑3 j¼1exp βjXi  which can be estimated using the method of maximum likelihood. The probability of a household belonging to a given borrowing group was hypothesized to be affected by the characteristics of households and apartments. Also, two dummy region variables were also included in the model to control for fixed-region effects. Table 1describes the definition and measurements of variables included in the model of borrowing home loans. Nguyen et al., Cogent Economics & Finance (2019), 7: 1638112 https://doi.org/10.1080/23322039.2019.1638112 Page 3 of 17 Home loan HLiðÞ¼β0þβ1X1iþβ2X2iþεi(1) In Equations (1) X1iis the vector of individual and household characteristics while X2iis a set of variables reflecting the physical housing characteristics. HLi represents the home loan decision and εiis an error term. We also investigate factors affecting the level of housing satisfaction in the current study. Housing satisfaction scores of respondents, taken from a multiple-choice question: “Taken altogether, how satisfied are you with your apartment at present?”The five possible responses to the question are “very dissatisfied,”“dissatisfied,”“neither satisfied nor dissatisfied,”“satisfied,”and “very satisfied.”Thus, for our analysis, housing satisfaction is constructed with a value from 1 to 5, corresponding to “very dissatisfied,”“dissatisfied,”“neither satisfied nor dissatisfied,”“satisfied,” and “very satisfied,”respectively. The literature indicates that housing satisfaction is mainly determined by two groups of factors (Addo, 2016; Baiden, Arku, Luginaah, & Asiedu, 2011;He& Yang, 2011; Huang, Du, & Yu, 2015; Ren & Folmer, 2017): (i) objective attributes of the individual or household, i.e. personal and socioeconomic characteristics; (ii) objective characteristics of the environment, i.e. dwelling and neighborhood characteristics. As already mentioned, homebuyer credits are of great importance for purchasing affordable apartments in Vietnam (WB, 2015). Thus, homebuyer credits were also included as a variable of interest in the current study. On the one hand, homebuyer credits may have a positive link with housing satisfaction because they enable home buyers to own apartments immediately, instead of saving enough money to purchase later. On the other hand, paying interest to borrow home loans to buy apartments immediately may put more financial pressure on home loan borrowers, which in turn may have a negative effect on their housing satisfaction. This suggests that the effect of homebuyer credits on housing satisfaction may be ambiguous. Equation (2) was used to examine factors associated with housing satisfaction. Equation (2) used the same explanatory variables as those in Equation (1) but added the variable of home loan (HSiÞand uiis an error term in the model. Unfortunately, an endogenous problem arises when home loan is an explanatory variable but is jointly determined with housing satisfaction (Woolridge, 2013). In this situation, the ordinary least squares (OLS) method produces biased and inconsistent estimates (Angrist & Pischke, 2008) and the method of instrumental variables (IV) can be used to obtain consistent estimators (Woolridge, 2013). Housing satisfaction HSiðÞ¼β0þβ1X1iþβ2X2iþβ3HS ðhome loanÞ3iþui(2) We need to search for a good instrument. A reliable instrumental variable must satisfy the following two conditions. First, the instrument must be strongly correlated with the endogenous regressor (home loan) once other exogenous explanatory variables from the structural equation have been netted out. This is often referred to as the “strength”of instrument or the relevance assumption. Second, it must be exogenous in the structural equation (i.e., uncorrelated with the error term), which is commonly called the “validity assumption”(French & Popovici, 2011). Specifically, the instrument affects housing satisfaction but not the access to home loans. First, the IV method estimates the impact of instrumental variable ðZiÞon home loan. Second, the IV method estimates the impact of home loans on housing satisfaction. By following this procedure, instrument affects life satisfaction only through their impact on housing satisfaction. We used two dummy variables of the region (Da Nang and Hanoi) 2 and the value of apartments (at the buying time) as potential instruments for having homebuyer credits. Different socio-economic characteristics across regions might affect the choice of various home loans and the regional variable is more likely to be exogenous. While the value of an apartment might be closely linked with the decision of home loans, this instrument may fail to meet the assumption of instrument exogeneity because the greater value of apartment may directly affect housing satisfaction. The above discussions suggest that Nguyen et al., Cogent Economics & Finance (2019), 7: 1638112 https://doi.org/10.1080/23322039.2019.1638112 Page 4 of 17 Table 1. Definition and measurement of included variables Variables Definition Measurement Dependent variables Housing satisfaction How are you satisfied with your apartment at present? Five point Likert scale Home loan Non-borrowers; borrowers with preferential home loan; borrowers with commercial home loan Three categories: 1;2;3 Explanatory variables Age Age of respondent years Gender Respondent’s gender 1 = male; 0 = female Marriage The marital status of respondents 1 = single; 0 = married Education Bachelor’s Has a bachelor’s degree 1 = yes; 0 = otherwise Master’s or higher Has a master’s degree or higher 1 = yes; 0 = otherwise Employment status Pubic employment Civil servants 1 = yes; 0 = otherwise Wage employment Wage workers that were hired by enterprises, households or individuals 1 = yes; 0 = otherwise Self-employment Self-employment in various economic activities 1 = yes; 0 = otherwise Household characteristics Household size Total number of household members numbers Young members Total number of household members aged 14 and younger numbers Old members Total number of household members aged 60 and older numbers Economic status Monthly average total household income (million Vietnamese dong) (VND) at the time of a household buying the apartment. Middle income From 10 million to 20 million VND 1 = yes; 0 = otherwise High income More than 30 million VND 1 = yes; 0 = otherwise Home loan Preferential loans Borrowed preferential home loan to buy the apartment 1 = yes; 0 = otherwise Commercial loans Borrowed commercial home loan to buy the apartment 1 = yes; 0 = otherwise Physical characteristics of apartments No furniture Apartment with no furniture 1 = yes; 0 = otherwise Partial furniture Apartment being equipped with some basis furniture 1 = yes; 0 = otherwise Size Total size of apartments squared meter Balconies Number of balconies number Bathrooms Number of bathrooms number Living rooms Number of living rooms number Type of apartment Which type of apartment does the respondent own? 1 = Social apartment; 0 = Cheap commercial apartment (Continued) Nguyen et al., Cogent Economics & Finance (2019), 7: 1638112 https://doi.org/10.1080/23322039.2019.1638112 Page 5 of 17 several necessary IV tests must be used to confirm whether both requirements of instruments (relevance and exogeneity) are satisfied or at least using a set of invalid and weak instruments that provides imprecise estimates and misleading results can be avoided (Angrist & Pischke, 2008). 3. Results and discussion 3.1. Descriptive statistics Table 2provides some background information on demographic, educational, employment and economic characteristics of respondents (household heads). It shows that the age, education level, gender, and marital status are quite similar between the two groups of home buyers. However, there are some differences in occupational types between the two groups. For instance, the percentage of respondents working in the public sector is much higher (30%) among those buying cheap commercial apartments than those buying social apartments (22%). The proportion of respondents working in the private sector is lower for the social apartment group while the proportion of respondents working as self-employers is similar between the two groups. The data in Table 2show that 13%, 50% and 38% of the surveyed households are categorized as low-, middle- and high-income groups, respectively. The proportion of low- and middle-income households seems to be higher among those living in SAs, while the number of high-income households is higher for those residing in CCAs. As shown in Table 3, 42% of the surveyed households borrowed home loans and the figures are much higher (57%) for those buying SAs than those buying CCAs (34%). On average, the mean value of home loan is about 500 million VND for the whole sample, and slightly higher for those buying CCAs (520 million VND) than those buying SAs (477 million VND). However, a substantial proportion of household buying SAs received loans from the VND 30 trillion package (73%), while the corresponding figure for those buying CCAs is only 41%. By contrast, the share of households borrowing from other preferential and commercial home loans is higher for those buying CCAs. Regarding the physical characteristics of apartments, the data in Table 4indicate that the average size of apartments is about 71.7 m 2 . However, the average size of SAs is smaller than that of CCAs. The average number of rooms, bathrooms and balconies is quite similar in the two types of apartments. Unsurprisingly, the average price per m 2 is quite higher for CCAs, while the number of apartments per an evaluator is higher for SAs. Finally, there are no significant differences in between the two types of apartments in the distance from the apartment buildings to the nearest school, park, bus station and markets. Table 1. (Continued) Variables Definition Measurement Other characteristics of apartments Lower secondary school The nearest distance to the lower secondary school km Primary school The nearest distance to the primary school km Kindergarten school The nearest distance to the kindergarten school km The evaluators The number of households per an evaluator numbers Markets The nearest distance to the markets/shopping area km Bus The nearest distance to the bus station km Park The nearest distance to the Park km Nguyen et al., Cogent Economics & Finance (2019), 7: 1638112 https://doi.org/10.1080/23322039.2019.1638112 Page 6 of 17 Table 2. Descriptive statistics of home buyers by house types Home buyers Cheap commercial apartments (CCAs) Social apartments (SAs) All Characteristics Mean Sd Mean Sd Mean Sd Age 37.56 9.84 36.25 7.94 37.10 9,23 Gender 0.56 0.50 0.57 0.50 0.56 0,50 Marriage 0.07 0.25 0.08 0.27 0.07 0,26 Not having a bachelor’s degree 0.19 0.39 0.22 0.41 0.20 0,40 Having a bbachelor’s degree 0.73 0.44 0.69 0.46 0.72 0,45 Above a bachelor’s degree 0.08 0.27 0.10 0.30 0.09 0,28 Public employment 0.30 0.46 0.22 0.41 0.27 0,44 Wage employment 0.27 0.45 0.35 0.48 0.30 0,46 Self-employment 0.43 0.50 0.43 0.50 0.43 0,50 Household size 3.59 1.05 3.47 0.96 3.55 1,02 Young members 1.25 0.77 1.25 0.74 1.25 0,75 Old members 0.26 0.59 0.19 0.50 0.24 0,56 Low income 0.11 0.31 0.17 0.38 0.13 0,34 Middle income 0.46 0.50 0.56 0.50 0.50 0,50 High income 0.44 0.50 0.26 0.44 0.38 0,48 Observations 646 354 1000 Nguyen et al., Cogent Economics & Finance (2019), 7: 1638112 https://doi.org/10.1080/23322039.2019.1638112 Page 7 of 17 or services of social housing projects might be lower than that of cheap commercial housing projects, which in turns can reduce the satisfaction with housing among those owning SAs. Those buying apartments with no or partial furniture would be less satisfied with their home than those buying apartments with full furniture. Having on more balcony would lower housing satisfaction by 0.17 points while having more bathrooms would increase housing satisfaction by 0.20 points. Table 7. Factors associated with housing satisfaction (IV method with 2SLS: Two-Stage Least Squares) Explanatory variables Coefficient SE Preferential homebuyer credit 1.81*** (0.689) Commercial homebuyer credit −0.69 (0.871) House type −0.32** (0.150) Age 0.00 (0.007) Gender 0.00 (0.081) Marriage 0.18 (0.212) Bachelor’s degree −0.16 (0.133) Above bachelor’s degree −0.46** (0.191) Public employment −0.16 (0.161) Wage employment −0.07 (0.117) Household size −0.12 (0.092) Young members 0.14 (0.086) Old members 0.18** (0.088) Middle income 0.09 (0.172) High income 0.20 (0.178) No furniture −0.45*** (0.160) Partial furniture −0.40*** (0.123) House size (m 2 ) 0.00 (0.007) Balconies −0.17* (0.095) Bath rooms 0.20* (0.116) Living rooms 0.08 (0.112) Lower secondary school −0.13** (0.062) Primary school −0.05 (0.053) Apartments/an evaluator −0.00 (0.002) Markets −0.12*** (0.040) Park −0.01 (0.019) Bus station −0.15** (0.062) Kindergarten 0.08** (0.034) Constant 4.01*** (0.660) Excluded instrumental variables The value of apartment; Hanoi, Dang Nang Weak identification test (Cragg- Donald Wald F statistic) [Stock-Yogo weak id test critical value at 10 percent] 5.751 5.442 Hansen J statistic (p-value) 0.8246 Endogeneity test of endogenous regressors: (p-value) 0.0107 Observation 1,000 Centered R-squared −0.363 Note: estimates are accounted for apartment project and robust standard errors. *, **, *** mean statistically significant at 10%, 5% and 1%, respectively. Nguyen et al., Cogent Economics & Finance (2019), 7: 1638112 https://doi.org/10.1080/23322039.2019.1638112 Page 14 of 17 Unsurprisingly, the longer distance from apartment buildings to lower secondary school, bus station and markets would reduce the level of housing satisfaction among homebuyers. In general, our findings are consistent with previous findings which found that housing satisfaction is substantially affected by a number of physical characteristics of the environment, e.g., dwelling and neighborhood characteristics (Addo, 2016; Baiden et al., 2011; Diaz-Serrano, 2009). As aforementioned, one of the main purposes in our study is to examine the relationship between the access to homebuyer credits and housing satisfaction. Surprisingly, we find that respondents with preferential home loans tend to be more satisfied with their home than their non-borrowing counterparts. Specifically, preferential home loan borrowers would have residential satisfaction scores 1.81 points higher than their counterparts, keeping all other factors constant. This may stem from the fact the access to preferential homebuyer credits enabled low-income households to own apartments immediately, instead of saving enough money to purchase later. However, we find no impact on borrowing commercial home loans on housing satisfaction. 4. Conclusion and policy implication The main objective of the current study was to investigate the access to homebuyer credits and its impact on housing satisfaction among residents who live in their own affordable apartments in sampled apartments of Ha Noi, Da Nang and HCMC, Vietnam. We find that 42% of the surveyed respondents took out loans to buy apartments. The figures are much higher (57%) for those buying SAs than those buying CCAs (34%). A higher proportion of households buying SAs received loans from the VND 30 trillion package (73%), while the corresponding figure for those buying CCAs is only 41%. We find that the access to preferential home loans is significantly affected by the education level of homebuyers, the size and value and type of apartments. In addition, our study confirms that the access of households to preferential home loans was not affected by their occupation, age and gender and household income. The study finds that 60% the respondents were satisfied or very satisfied with their residences. About 20% were neither satisfied nor dissatisfied while nearly 20% were dissatisfied or very dissatisfied with their housing. Interestingly, our econometric analysis provides the first evidence that the access to preferential homebuyer credits had a significantly increasing impact on the level of housing satisfaction, even after controlling for many other factors and the endogeneity of homebuyer credits. The above findings, therefore, confirm that the preferential home loans not only helped households own affordable apartments but also increased their housing satisfaction. A policy implication here is that housing credit policies such as the VND 30 trillion package should be continued in order to help low-income households to access affordable housing. Our multiple regression analysis also finds a number of other factors affecting housing satisfaction. Those buying SAs tend to be less satisfied with their housing than did those buying CCAs. Possibly, this might suggest that social apartment projects might have lower quality of services or construction, which made homebuyers less satisfied with their housing. As expected, we find that those buying apartments that are closer to schools, bus stations and markets would feel more satisfied with their housing. This suggests that a prime location of apartment projects would be an important residential housing factor and that affordable apartment projects should be developed in relatively convenient locations. However, Nguyen et al. (2018) noted that such a policy implication raises some challenging questions. A prime location often requires many investments in socioeconomic infrastructure (e.g., roads, schools), while such investments may offer low short-term returns for housing developers. Therefore, land prices in relatively prime locations are often too high to make a project affordable for low-income households. This implies that the government policies should support the development of an affordable housing market by investing in socioeconomic infrastructure or by putting forward more incentives and preferential policies to encourage developers who invest in less convenient locations. Nguyen et al., Cogent Economics & Finance (2019), 7: 1638112 https://doi.org/10.1080/23322039.2019.1638112 Page 15 of 17 Acknowledgment The authors thank H.E.L.P Social Joint Stock Company for funding this research. Funding This paper is part of the project funded by H.E.L.P Social Joint Stock Company which was conducted in Hanoi, Da Nang and Ho Chi Minh cities, from June to September 2016. The project was carried out by Anh Tuan Nguyen (PhD student), Tuyen Quang Tran, Dat Luu Quoc and Huong Vu Van at VNU University of Economics and Bussiness, Vietnam National University, Hanoi. The main aim of the project was to identify factors affecting the decision of buying affordable apartments among those living in Big cities of Vietnam. It also examines factors associated with housing satisfaction and the role of homebuyer credits in buying home and housing satisfaction. Author details Tuan Anh Nguyen 1,2 E-mail: [email protected] Tuyen Quang Tran 1 E-mail: [email protected] E-mail: [email protected] Huong Vu Van 1 E-mail: [email protected] Dat Quoc Luu 1 E-mail: [email protected] 1 Center for Socio-Economic Analysis and Databases, VNU University of Economics and Business, Hanoi, Vietnam. 2 Commission for the Management of State Capital at Enterprises, Vietnam. Citation information Cite this article as: Access to homebuyer credit and housing satisfaction among households buying affordable apartments in urban Vietnam, Tuan Anh Nguyen, Tuyen Quang Tran, Huong Vu Van & Dat Quoc Luu, Cogent Economics & Finance (2019), 7: 1638112. Notes 1. In the current study, affordable apartments include housing for low and middle-income households, which were defined according to the Resolution No. 02/NQ-CP on 7 January 2013 and WB (2015). Low-income housing is housing with price less than 16 million VND per square meter, while medium-income housing is from 16-30 million VND per square meter. 2. The omitted category is Ho Chi Minh City. 3. Preferential homebuyer credits include the VND 30 trillion package for low-income households and other preferential home loans. 4. This is calculated as: RRR (relative risk ratio)-1=e β - 1=e 0.85 -1=1.34 times (or 134%). Conflict of Interest The author declares that he has no conflict of interest in this research. References Addo, I. A. (2016). Assessing residential satisfaction among low income households in multi-habited dwellings in selected low income communities in Accra. Urban Studies,53(4), 631–650. doi:10.1177/ 0042098015571055 Amole, D. (2009). Residential satisfaction in students’ housing. Journal of Environmental Psychology,29(1), 76–85. doi:10.1016/j.jenvp.2008.05.006 Angrist, J. D., & Pischke, J.-S. (2008). 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Housing and Society,23(2), 15–35. doi:10.1080/08882746.1996.11430239 © 2019 The Author(s). Thisopen access article is distributed under a Creative Commons Attribution (CC-BY) 4.0 license. You are free to: Share —copy and redistribute the material in any medium or format. Adapt —remix, transform, and build upon the material for any purpose, even commercially. The licensor cannot revoke these freedoms as long as you follow the license terms. Under the following terms: Attribution —You must give appropriate credit, provide a link to the license, and indicate if changes were made. You may do so in any reasonable manner, but not in any way that suggests the licensor endorses you or your use. No additional restrictions You may not apply legal terms or technological measures that legally restrict others from doing anything the license permits. Cogent Economics & Finance (ISSN: 2332-2039) is published by Cogent OA, part of Taylor & Francis Group. Publishing with Cogent OA ensures: •Immediate, universal access to your article on publication •High visibility and discoverability via the Cogent OA website as well as Taylor & Francis Online •Download and citation statistics for your article •Rapid online publication •Input from, and dialog with, expert editors and editorial boards •Retention of full copyright of your article •Guaranteed legacy preservation of your article •Discounts and waivers for authors in developing regions Submit your manuscript to a Cogent OA journal at www.CogentOA.com Nguyen et al., Cogent Economics & Finance (2019), 7: 1638112 https://doi.org/10.1080/23322039.2019.1638112 Page 17 of 17