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Does formalization increase firm investment in human capital? New evidence from Vietnam
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Does formalization increase firm investment in human capital? New evidence from Vietnam Tien Kim Thi Do , Huong Van Vu PII: DOI: Reference:
S1544-6123(20)31703-7 https://doi.org/10.1016/j.frl.2020.101889 FRL 101889
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Finance Research Letters
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27 June 2020 2 December 2020 12 December 2020
Please cite this article as: Tien Kim Thi Do , Huong Van Vu , Does formalization increase firm investment in human capital? New evidence from Vietnam, Finance Research Letters (2020), doi: https://doi.org/10.1016/j.frl.2020.101889
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Does formalization increase firm investment in human capital? New evidence from Vietnam
Tien Kim Thi Do1, Huong Van Vu2,* 1
Faculty of State Management of Economic Affairs and Public Finance, National Academy of Public Administration 2
Center for Socio-Economic Analysis and Databases, VNU University of Economics and Business *Corresponding author, Email: [email protected]; [email protected] 1 Dai Co Viet Road,
Highlights There have be extensive studies on the role of formalization in firm performance, but limited evidence as to how that practice indirectly affects employee welfare. Using instrument variable approaches for an employer-employee panel dataset from Vietnamese SME surveys during the 2009-2015 period. We find that formalization has an insignificant effect on employee wages. However, positive relationships between formalization and non-monetary employee benefits have been noted, including a formal contract for workers, health insurance, annual leave, severance payment and retirement pay. Also significant are several potential mechanisms though which formalization has a positive effect on other workers’ welfare, including an improvement in value added and a reduction in the amount firms spend on bribes.
Abstract 1
There have be extensive studies on the role of formalization in firm performance, but limited evidence as to how that practice indirectly affects firm investment in human capital. Using instrument variable approaches for an employer-employee panel dataset from Vietnamese SME surveys during the 2009-2015 period, this study finds that formalization has an insignificant effect on employee wages. However, positive relationships between formalization and nonmonetary employee benefits have been noted. Also significant are several potential mechanisms though which formalization has a positive effect on workers’ welfare, including an improvement in value added and a reduction in the amount firms spend on bribes.
Keywords Formalization; CSR to employees; Employer-employee; SMEs
1. Introduction Theoretically, formalization has both direct and indirect effects on employee welfare. On the one hand, employees working in informal sectors often have causal contracts, so do not receive social or health insurance and other employee welfare. However, when firms become formally established, the linkage between employees and employers operates under the Code of Labor (Rand & Torm, 2012). Consequently, registration as an official firm (formalization) may improve employee welfares, and these improvements, according to the stakeholder theory, may lead to an increase in a firm’s reputation and value (Ben-Nasr & Ghouma, 2018; Brammer & Pavelin, 2006). Also, formalization may affect employee benefits through the regulatory scrutiny and oversight of firms by regulatory authorities. In this context, formalization may act as a driving factor to promote employee rights and working conditions (Galiani & Weinschelbaum, 2012; Henley, Arabsheibani, & Carneiro, 2009; Rand & Torm, 2012). Furthermore, official registration may improve employee working conditions as a spillover effect from better productivity and profits. On the other hand, when formalization does not improve firm performance, wages and other employee benefits could be cut or delayed to offset poor productivity. In addition, according to the agency theory, higher levels of employee welfare might lead to a decrease in firm value (Ben-Nasr & Ghouma, 2018). As a result, the workforce can be downsized or wages and nonmonetary benefits, such as annual leave, paid leave or sick leave, may be reduced. 2
Empirically, many firm-level studies document the benefits of the tax registration of firms in terms of improvements in productivity and investment, increased market access, growth in market share, profits and the increased ability to network with large enterprises (Demenet, Razafindrakoto, & Roubaud, 2016; McKenzie & Sakho, 2010). However, other studies (e.g., de Adrade, Bruhn, & McKenzie, 2016) reveal that the benefits of informality may be greater than the costs, and informal firms register formally only because they are forced to do so. Furthermore, De Mel, McKenzie, and Woodruff (2013) provide evidence of the insignificant linkage between tax registration and firm performance. Interestingly, however, very few studies have quantitatively assessed the effect of formalization on employee welfares and few studies using aggregate firm-level data (e.g., Rand & Torm, 2012) consider the effect of formalization on the wages of employees. Moreover, these few studies do not account for employee characteristics that can lead to potential bias. Furthermore, no study considers the impact of formalization on employee non-monetary benefits or compliant corporate social responsibility of firms to their employees. 1 It should be noted that there is a trade-off between wages and non-monetary gains (Baicker & Chandra, 2006). Hence, it is essential to investigate whether the benefits of formalization go beyond monetary gains. Going beyond the results of current literature, this study for the first time considers the linkage between formalization and employee benefits in terms of both monetary and non-monetary factors, using a matched employer-employee panel dataset. Such an approach allows us to overcome the potential bias of previous studies which fail to control for both worker and firm characteristics. Also, the study corrects for unobserved factors and potential endogeneity by applying instrumental variable approaches. This study proceeds as follows. In section 2, the research context is presented, while the information on data and methodology is provided in section 3. The main results of the effects of formalization on employee welfare are discussed in section 4. Section 5 concludes the paper and suggest managerial implications from the findings. 2. The research context To promote a formalized economy, several support programs for enterprises have been launched by the Vietnamese government, for example tax credits, tax exemptions, and grants to cover loan applications (Nguyen, Verreynne, & Steen, 2014). However, as left-hand appendix 1 shows, many non-exporting firms are informal. By contrast the right-hand appendix 1 reveals that the majority of exporters are formal businesses, which indicates that formalization may be a crucial factor for participation in export markets.
1
Compliant corporate social responsibility of firms is considered as the compliance of firms to legal expectations for their employees.
3
Figure 1 shows that the majority of informal firms are household enterprises, while other types of ownership (cooperative, limited liability and joint-stock) operate mostly with formal status. Also, it should be noted that during the research period, from 2009-2015, there was a downward trend in the number of informal firms. In this context, many studies on Vietnam show that gaining official status helps firms with access to credit, government services, profit increases and contributions to the state via taxes (Boly, 2020; Rand & Torm, 2012). How does formalization affect employee working conditions and other fringe benefits, however? And what are the mechanisms through which formalization influences employee benefits? The following sections will outline the results that clarify these questions.
Household Collective/Cooperative 2009
Limited liability company Private/sole proprietorship Joint stock company without stat Household Collective/Cooperative
2011
Joint stock company without stat Private/sole proprietorship Limited liability company Household Joint stock company without stat
2013
Private/sole proprietorship Collective/Cooperative Limited liability company Household Private/sole proprietorship
2015
Collective/Cooperative Limited liability company Joint stock company without stat
1
.5
0 No Formalisation
.5
1
Formalization
Figure 1. Formal status of firms according to type of ownership. 3. Data and methodology 3.1 Data source We examine the influence of formalization on employee benefits in Vietnam for 2009, 2011, 2013, and 2015. Over 2500 small and medium-sized manufacturing enterprises were surveyed each year. These surveys were conducted jointly by the Central Institute for Economic Management of the Ministry of Planning and Investment, the Institute of Labor Science and Social Affairs of the Ministry of Labor, Invalids and Social Affairs, the Department of Economics of the University of Copenhagen, and the United Nations University World Institute
4
for Development Economics Research (UNU-WIDER) together with the University of Copenhagen, Denmark.2 The study uses an employer-employee panel dataset that is a combination between two modules. The first module comprises firm-level data, including information concerning formalization and firm characteristics, such as firm age, size and exports. The second module is made up of employee-level data that contain individual characteristics, such as gender, work experience, education, occupation and employee benefits (employee wage and working conditions). It should be noted that the data from the employee module only represent information from a sub-sample taking part in the surveys at firm level. 3.2 Methodology The empirical model controls for both employee and firm characteristics using the following equation. (1) In which Yit measures employee welfares, including the real monthly wage of the employees sampled. This study also considers non-monetary benefits that are defined as compliant corporate social responsibility of firms to their employees, including whether the employee has a formal contract, receives health insurance, maternal leave, severance pay and retirement pay. i, t denote firm i at year t. Regarding the independent variables, formalization (Fit) is the main variable of interest and is measured as a dummy variable (1 if a firm has a tax code and 0 otherwise) (Boly, 2020; Rand & Torm, 2012). Model (1) also includes the characteristics of workers and enterprises (and those of the owner/manager). Focusing on worker characteristics (Xit), since age, experience, and education are the essential human capital variables that determine workers’ earnings (Trifković, 2017), these variables are controlled for. The worker's gender is another essential characteristic that accounts for wage differences for workers in Vietnam (Trifković, 2017). In an extended estimation, this study also controls for small business characteristics (Zit), carefully selected to include those variables that relate to formalization and employee benefits at the enterprise level (Lavallée & Roubaud, 2019; Rand & Torm, 2012; Trifković, 2017). For instance, we control for enterprise characteristics, such as age and size (total labor force).
2
5
The Provinces covered in the survey data, please to see the appendix 4.
Finally, we include the export status of the enterprise, as this reflects manufacturing capacity that may influence wages and other employee benefits (Lavallée & Roubaud, 2019). A key concern in establishing the impact of formalization on employee benefits is the potential endogeneity of formalization. Unobservable confounding variables may also be correlated with both formalization and employee working conditions. Thus, we employ an identification strategy that relies on an instrument with a strong correlation with the endogenous variable (formalization), but no direct association with worker benefits. Understanding formalization as the term covering those actions that may be informed by the activities of other enterprises in the industry and by the location of the enterprise, we use the average rate of formalization in the peer group made up of sampled enterprises, defined by proximity in geographical location (district) and business activity (sector). Such an approach is widely applied in the literature (e.g., Cuong & Hau, 2020; Van Huong & Cuong, 2019), which notes that there is a considerable difference in development among provinces in Vietnam (Van Vu, Tran, Van Nguyen, & Lim, 2018). Therefore, instruments constructed at the level of location and sector would be likely to pick up these additional spatial and sectorial influences. Furthermore, we control for sectors and time dummies to capture macro variations (Tit). Specifically, an IV strategy relating to the role of formalization on worker benefits includes two stages. The first-rate regression displays the relevance of the instrument, and is defined in equation (2): (2) Where the instrument (IV) is defined earlier, while the covariates overlap with those in equation (1). The second stage regression is estimated as shown in equation (3):
(3) 4. Empirical results and discussion Columns 1 and 2 of Table 1 report the relationship between formalization and the wage outcome for workers, without addressing concerns about endogeneity. In these specifications, only worker characteristics are controlled for. In an extended specification, when the characteristics of small businesses and time-invariant factors are controlled for, a consistent but insignificant relationship between tax registration and the wages of workers is still reported. However, the results may still be biased because of the potential endogeneity of formalization. Hence, an FE-IV estimation is reported in column 4. The first-stage F-statistic shows that the instrument is valid and that the weak instrument problem is not a concern. The second-stage 2SLS estimate in column 4 reinforces the OLS result, that small businesses that engage in formalization in Vietnam report an insignificant reduction in workers’ wages. This finding disagrees with the conclusion in previous studies (e.g., Boly, 2015) that shows that formalization improves workers’ wages. The 6
discrepancy may be explained by the fact that previous studies using only firm-level data may be biased because of their failure to control for employee characteristics. Table 1: The effects of formalization on employee wages VARIABLES
Formalization Worker male Permanent worker
Experience University education Production workers
Pooled OLS
FE
FE
IV-FE
(1) 0.039 (0.055) 0.108*** (0.028) 0.608*** (0.144) 0.001 (0.003) 0.277*** (0.032) -0.262*** (0.031)
(2) -0.207 (0.189) 0.083 (0.052) 0.622*** (0.217) 0.001 (0.006) 0.160*** (0.060) -0.033 (0.058)
(4) 0.010 (0.345) 0.077 (0.054) 0.613*** (0.202) -0.000 (0.006) 0.159** (0.063) -0.031 (0.061) -0.001** (0.001) 0.003 (0.007) 0.347** (0.160) 0.195 (0.146) 0.115 (0.095)
5.855*** (0.150) 3,399 0.287
5.960*** (0.260) 3,399 0.298 2,076
(3) -0.204 (0.189) 0.080 (0.051) 0.607*** (0.207) 0.000 (0.006) 0.159*** (0.060) -0.030 (0.058) -0.001** (0.001) 0.003 (0.007) 0.350** (0.160) 0.195 (0.152) 0.110 (0.096) 5.810*** (0.299) 3,397 0.306 2,075
Firm size Firm age Export Low tech sectors Medium tech sectors Constant Observations R-squared Number of panels Instrumental variables
Weak identification test (Cragg-Donald Wald F statistic) [Stock-Yogo weak ID test critical value at 10%]
2,254 0.305 932 Location-industryyear average of formalization
685.736 16.38
Notes: Standard errors in parentheses, models also controlled for time year dummies; *** p<0.01, ** p<0.05, * p<0.1.
7
Regarding the role of other covariates for wages, results are generally in line with previous studies. For example, employees who have a higher position and more education earn higher wages. In addition, while there is an insignificant relationship between wage and gender, the permanent status of workers has a positive effect on wages. Accounting for firm-level explanatory variables for wages, exporters and innovators pay their employees higher wages than do non-exporters. These findings are in line with those of previous studies (e.g., Newman, Rand, Tarp, & Trifkovic, 2018). For example, Newman et al. (2018) show that a firm’s export activities have a positive effect on the fulfilment of their responsibilities for employees. Table 2: Formalization and employee welfare VARIABLES Health insurance Xtprobit IVprobit (1) (2) Formalization 0.753*** 0.394*** (0.113) (0.118) Worker male -0.019 -0.026 (0.015) (0.016) Permanent worker 0.071 0.110** (0.044) (0.046) Experience -0.002 -0.001 (0.001) (0.001) University education 0.159*** 0.199*** (0.020) (0.021) Production worker -0.144*** -0.172*** (0.016) (0.018) Firm size Firm age Export Urban Low tech sectors Medium tech sectors Observations
3,711
3,711
Xtprobit (3) 0.512*** (0.094) -0.006 (0.014) 0.062 (0.040) 0.001 (0.001) 0.114*** (0.018) -0.119*** (0.015) 0.005*** (0.000) -0.005*** (0.001) 0.050** (0.024) 0.009 (0.015) -0.097*** (0.020) -0.035 (0.021) 3,709
Xtprobit (4) 0.435*** (0.035) -0.022 (0.016) 0.205*** (0.045) -0.005*** (0.001) 0.237*** (0.024) -0.141*** (0.017)
Formal contract IVprobit (5) 0.254*** (0.048) -0.032* (0.017) 0.202*** (0.048) -0.004*** (0.001) 0.291*** (0.025) -0.173*** (0.018)
3,808
3,808
Xtprobit (6) 0.268*** (0.031) -0.008 (0.015) 0.168*** (0.043) -0.003** (0.001) 0.188*** (0.022) -0.107*** (0.016) 0.007*** (0.000) -0.002*** (0.001) 0.062** (0.028) 0.080*** (0.015) -0.056*** (0.022) -0.007 (0.023) 3,806
Notes: Standard errors in parentheses, models also controlled for time year dummies; *** p<0.01, ** p<0.05, * p<0.1. The analysis based on employee-employer panel dataset in the 2009-2015.
We further examine the role of tax registration for other worker benefits. Specifically, we consider the relationship between formalization and the likelihood of workers’ having a formal contract, health insurance, maternal leave, severance payment and retirement payment. We present both the probit and second-stage results of the instrumental variable probit in Tables 2 8
and 3. Interestingly, although there is no significant linkage between the formalization of firms and wages, formalization has a significant impact on non-monetary benefits. The results suggest that formalization increases recognition of employee according to marginal product of his labor. Firms invest in human capital to keep the workers productive (Holland, 2017). Tables 2 and 3 show that official registration has a positive correlation with the likelihood of workers’ receiving a formal contract, health insurance, maternal leave, severance payment and retirement payment, and the relationship is significant by any specification or method of estimation. For example, Columns 2, 5 and 8 of Table 4 reveal that employees in formal firms are paid more than 10% greater fringe benefits, such as maternal leave, severance pay and retirement pay, than their counterparts working in informal firms, keeping other factors constant. Table 3: Formalization and other employee welfares Maternal leave Severance pay Retirement pay Xtprobit IVprobit Xtprobit Xtprobit IVprobit Xtprobit Xtprobit IVprobit Xtprobit (1) (2) (3) (4) (5) (6) (7) (8) (9) 0.345*** 0.119** 0.241*** 0.327*** 0.128* 0.219*** 0.360*** 0.140** 0.247*** Formalization (0.037) (0.058) (0.035) (0.044) (0.067) (0.039) (0.047) (0.069) (0.041) -0.155*** -0.147*** -0.149*** -0.047*** -0.044*** -0.039*** -0.038*** -0.036** -0.032*** Worker male (0.015) (0.015) (0.014) (0.014) (0.014) (0.013) (0.013) (0.014) (0.013) 0.072 0.070 0.053 0.066 0.069 0.044 0.097** 0.088** 0.067* Permanent (0.046) (0.045) (0.044) (0.042) (0.044) (0.039) (0.043) (0.044) (0.039) worker -0.002* -0.001 -0.001 -0.002 -0.001 0.000 0.002 0.003* 0.003** Experience (0.001) (0.001) (0.001) (0.001) (0.001) (0.001) (0.001) (0.001) (0.001) 0.122*** 0.138*** 0.067*** 0.082*** 0.091*** 0.043** 0.121*** 0.140*** 0.078*** University (0.021) (0.021) (0.020) (0.018) (0.018) (0.017) (0.018) (0.018) (0.016) education -0.140*** -0.145*** -0.104*** -0.107*** -0.122*** -0.082*** -0.096*** -0.113*** -0.074*** Production (0.017) (0.018) (0.016) (0.016) (0.016) (0.015) (0.016) (0.016) (0.014) workers 0.003*** 0.002*** 0.003*** Firm size (0.000) (0.000) (0.000) -0.002** -0.003*** -0.002*** Firm age (0.001) (0.001) (0.001) 0.066*** 0.112*** 0.094*** Export (0.024) (0.020) (0.020) 0.122*** 0.042*** -0.008 Urban (0.015) (0.014) (0.014) dummies -0.086*** -0.056*** -0.087*** Low tech (0.021) (0.019) (0.018) sectors -0.055** 0.006 -0.022 Medium tech (0.022) (0.020) (0.019) sectors Observations 3,595 3,595 3,593 3,686 3,686 3,684 3,666 3,666 3,664 Notes: Standard errors in parentheses, models also controlled for time year dummies; *** p<0.01, ** p<0.05, * p<0.1. The analysis based on employee-employer panel dataset in the 2009-2015. VARIABLES
The literature indicates that in developing countries, formalization could positively affect the outcomes for small businesses (including profits, added value, gaining government support and bribe payments). To check whether these particular mechanisms are at play, we consider the role of formalization at firm level with these indicators. The results in Table 4 indicate that while 9
there is no significant correlation between tax registration and government support, formalization improves added value and reduces corruption. Improvements in added value and a reduction in bribe payments may improve regulatory oversight of the business – especially labor oversight. Therefore, the positive effect of formalization on workers in Vietnamese small businesses seems obvious when conditioned on higher productivity and transparency in the business environment. Table 4: Potential mechanism of the effect of formalization on employee welfare VARIABLES
Formalization Firm size Firm age Innovation Export Leverage Low tech sectors Observations R-squared Number of panels Instrumental variables
Value added
Government support
IV-FE (1) 0.258** (0.130) 0.012*** (0.001) -0.001 (0.002) 0.080*** (0.023) 0.327*** (0.091) 0.166*** (0.056) -0.011 (0.063) 5,291 0.651 2,038
IV-FE (2) 0.100 (0.082) 0.000 (0.000) 0.001 (0.001) 0.052*** (0.014) 0.039 (0.058) -0.023 (0.035) 0.038 (0.040) 5,319 0.100 2,045
Location-industryyear average of formalization
Location-industryyear average of formalization
Firm is a member of business association IV-FE (3) 0.062 (0.065) -0.000 (0.000) 0.002 (0.001) -0.017 (0.011) -0.104** (0.045) -0.013 (0.027) 0.027 (0.031) 5,320 0.930 2,045
Bribe amount
IV-FE (4) -0.001* (0.001) 0.000 (0.000) -0.000 (0.000) 0.000 (0.000) -0.000 (0.001) 0.000 (0.000) -0.000 (0.000) 5,322 -0.001 2,046
Location-industry- Locationyear average of industry-year formalization average of formalization 483.20 483.28
Weak 479.84 483.04 identification test (CraggDonald Wald F statistic) [Stock-Yogo 16.38 16.38 16.38 16.38 weak ID test critical value at 10%] Notes: Standard errors in parentheses, models also controlled for time year dummies; *** p<0.01, ** p<0.05, * p<0.1.
10
5. Conclusion and policy implications Based on an employer-employee panel dataset of four cycles from 2009 to 2015, this paper contributes to the literature by considering for the first time the effect of formalization on workers’ wages and non-monetary employee benefits. The study shows that formalization leads to a significant improvement in workers' welfare. This result is consistent, irrespective of the estimation technique applied, and does not change either with or without adjustment for other control variables. These findings provide the concrete evidence to support government efforts to reduce the number of firms with informal status. The recent outbreak of the Covid-19 pandemic has raised concern about the capacity and survival of private SMEs, especially when they remain informal in status. Hence, one direction for strengthening firm capability is to lead them through a transitional process from informal to formal status. This process may reduce the level of corruption and promote the added value of firms, and these in turn should improve the business environment for firms, the working conditions and welfare of employees. Despite interesting findings and important managerial implications, our study is subject to several limitations that provide potential avenues for future research. For example, this study focuses only on private manufacturing SMEs in Vietnam. Hence, future work could consider large firms. In addition, future studies may focus on enterprises in other economic sectors and other types of ownership to provide a broader understanding of the formalization of Vietnamese enterprises.
Appendices Appendix 1: Formal status of firms according to sectors
11
b) Exporters
a) Non-exporters
Wood
Wood Food and beverages
Furniture, jewellery, music equi
Furniture, jewellery, music equi
Leather
Textiles
Textiles
Fabricated metal products
Non-metallic mineral products
Non-metallic mineral products
Food and beverages
Basic metals
Apparel
Leather
Paper
Apparel
Publishing and printing
Motor vehicles etc.
Chemical products etc.
Chemical products etc.
Rubber
Paper
Basic metals
Publishing and printing
Fabricated metal products
Electronic machinery, computers,
Electronic machinery, computers,
Rubber
Motor vehicles etc.
1
.5
0 Formalization
.5
1
1
.5
No Formalization
0 Formalization
.5
1
No Formalization
Appendix 2: Descriptive statistics of main variables in the model 2009 Real wage in log (number) Employer pays for sick leave (Dummy variable) Employer pays for maternity leave (Dummy variable) Severance pay (Dummy variable) Payment when stop working/retires (Dummy variable) Gender of Worker (Dummy variable) Permanent full-time employee (number) Worker's number of years in firm (number) Education (1 if having professional secondary education, 0 otherwise) Occupation (1 if being production worker, 0 otherwise) Firm size (the number of full-time regular employees)
12
2011
2013
2015
Mean 6.45 0.49
SD 0.42 0.50
Mean 7.54 0.41
SD 0.83 0.49
Mean 7.61 0.42
SD 0.92 0.49
Mean 7.33 0.53
SD 0.87 0.50
0.32
0.47
0.41
0.49
0.37
0.48
0.44
0.50
0.23
0.42
0.24
0.43
0.33
0.47
0.28
0.45
0.20
0.40
0.25
0.43
0.40
0.49
0.28
0.45
0.60
0.49
0.59
0.49
0.59
0.49
0.59
0.49
0.99
0.11
0.97
0.16
0.97
0.17
0.98
0.15
5.44
4.99
6.05
5.52
6.39
5.62
7.73
6.16
0.16
0.37
0.19
0.40
0.21
0.41
0.24
0.43
0.60
0.49
0.59
0.49
0.58
0.49
0.62
0.48
32.25
40.75
22.79
30.65
22.84
33.57
27.85
45.20
Firm age (number) Export (1 if firms participate into export, 0 otherwise) Observations
13.96 0.13
11.05 0.34
998
12.80 0.10
8.49 0.30
14.82 0.10
1380
9.55 0.30
16.01 0.15
1521
8.65 0.36
1342
Appendix 3: Correlation matrix 1
2
3
4
5
6
7
8
9
1. Gender of worker
1.00
2. Permanent worker
0.0005
1.00
3. Experience
-0.0598*
0.0945*
1.00
4. University education
-0.1636*
0.0202
-0.0625* 1.00
5. Production worker
0.3225*
-0.0344* -0.0622* -0.5391* 1.00
6. Firm size
-0.1114*
0.0500*
-0.0287* 0.2363*
7. Firm age
0.0212
0.0175
0.3631*
-0.0873* 0.0757*
8. Export
-0.1191*
0.0325*
-0.0169
0.1327*
-0.1326* 0.3808*
-0.0351* 1.00
9. Formalization
-0.0558*
0.0106
-0.0243
0.1333*
-0.1537* 0.1677*
-0.0723* 0.1017* 1.00
-0.2144* 1.000 -0.0813* 1.00
Appendix 4: Provinces covered in the survey data
Ha Noi Phu Tho Ha Tay
Hai Phong
Nghe An
Quang Nam
Khanh Hoa 13
Long An
Lam Dong HCM C
Conflict of Interest Statement
The authors agree that this research was conducted in the absence of any self-benefits, commercial or financial conflicts and declare absence of conflicting interests with the funders. Acknowledgements
This researc h is funded by the Korean Foundation for Advanced Studies (KFAS) and the Asian Research Center, Vietnam National University, Hanoi (VNU) under project number CA.19.1A
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Cuong, L. K., & Hau, H. T. (2020). Does innovation promote access to informal loans? Evidence from a transitional economy. Finance Research Letters, 101718. De Adrade, G. H., Bruhn, M., & McKenzie, D. (2016). A Helping Hand or the Long Arm of the Law? Retrieved from https://openknowledge.worldbank.org/bitstream/handle/10986/27691/lhu008.pdf?sequen ce=1 De Mel, S., McKenzie, D., & Woodruff, C. (2013). The demand for, and consequences of, formalization among informal firms in Sri Lanka. American Economic Journal: Applied Economics, 5(2), 122-150. Demenet, A., Razafindrakoto, M., & Roubaud, F. (2016). Do informal businesses gain from registration and how? Panel data evidence from Vietnam. World Development, 84, 326341. Galiani, S., & Weinschelbaum, F. (2012). Modeling informality formally: households and firms. Economic Inquiry, 50(3), 821-838. Henley, A., Arabsheibani, G. R., & Carneiro, F. G. (2009). On defining and measuring the informal sector: Evidence from Brazil. World Development, 37(5), 992-1003. Holland, S. B. (2017). Firm investment in human health capital. Journal of Corporate Finance, 46, 374-390. Lavallée, E., & Roubaud, F. (2019). Corruption in the informal sector: evidence from West Africa. The Journal of Development Studies, 55(6), 1067-1080. McKenzie, D., & Sakho, Y. S. (2010). Does it pay firms to register for taxes? The impact of formality on firm profitability. Journal of development economics, 91(1), 15-24. Newman, C., Rand, J., Tarp, F., & Trifkovic, N. (2018). The transmission of socially responsible behaviour through international trade. European Economic Review, 101, 250-267. Nguyen, T., Verreynne, M.-L., & Steen, J. (2014). Drivers of firm formalization in Vietnam: an attention theory explanation. Entrepreneurship & Regional Development, 26(7-8), 574593. Rand, J., & Torm, N. (2012). The benefits of formalization: Evidence from Vietnamese manufacturing SMEs. World Development, 40(5), 983-998. Trifković, N. (2017). Spillover effects of international standards: Working conditions in the Vietnamese SMEs. World Development, 97, 79-101. Van Huong, V., & Cuong, L. K. (2019). Does government support promote SME tax payments? New evidence from Vietnam. Finance Research Letters, 31. Van Vu, H., Tran, T. Q., Van Nguyen, T., & Lim, S. (2018). Corruption, types of corruption and firm financial performance: New evidence from a transitional economy. Journal of Business Ethics, 148(4), 847-858.
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Does formalization increase firm investment in human capital? New evidence from Vietnam Tien Kim Thi Do , Huong Van Vu PII: DOI: Reference:
S1544-6123(20)31703-7 https://doi.org/10.1016/j.frl.2020.101889 FRL 101889
To appear in:
Finance Research Letters
Received date: Revised date: Accepted date:
27 June 2020 2 December 2020 12 December 2020
Please cite this article as: Tien Kim Thi Do , Huong Van Vu , Does formalization increase firm investment in human capital? New evidence from Vietnam, Finance Research Letters (2020), doi: https://doi.org/10.1016/j.frl.2020.101889
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Does formalization increase firm investment in human capital? New evidence from Vietnam
Tien Kim Thi Do1, Huong Van Vu2,* 1
Faculty of State Management of Economic Affairs and Public Finance, National Academy of Public Administration 2
Center for Socio-Economic Analysis and Databases, VNU University of Economics and Business *Corresponding author, Email: [email protected]; [email protected] 1 Dai Co Viet Road,
Highlights There have be extensive studies on the role of formalization in firm performance, but limited evidence as to how that practice indirectly affects employee welfare. Using instrument variable approaches for an employer-employee panel dataset from Vietnamese SME surveys during the 2009-2015 period. We find that formalization has an insignificant effect on employee wages. However, positive relationships between formalization and non-monetary employee benefits have been noted, including a formal contract for workers, health insurance, annual leave, severance payment and retirement pay. Also significant are several potential mechanisms though which formalization has a positive effect on other workers’ welfare, including an improvement in value added and a reduction in the amount firms spend on bribes.
Abstract 1
There have be extensive studies on the role of formalization in firm performance, but limited evidence as to how that practice indirectly affects firm investment in human capital. Using instrument variable approaches for an employer-employee panel dataset from Vietnamese SME surveys during the 2009-2015 period, this study finds that formalization has an insignificant effect on employee wages. However, positive relationships between formalization and nonmonetary employee benefits have been noted. Also significant are several potential mechanisms though which formalization has a positive effect on workers’ welfare, including an improvement in value added and a reduction in the amount firms spend on bribes.
Keywords Formalization; CSR to employees; Employer-employee; SMEs
1. Introduction Theoretically, formalization has both direct and indirect effects on employee welfare. On the one hand, employees working in informal sectors often have causal contracts, so do not receive social or health insurance and other employee welfare. However, when firms become formally established, the linkage between employees and employers operates under the Code of Labor (Rand & Torm, 2012). Consequently, registration as an official firm (formalization) may improve employee welfares, and these improvements, according to the stakeholder theory, may lead to an increase in a firm’s reputation and value (Ben-Nasr & Ghouma, 2018; Brammer & Pavelin, 2006). Also, formalization may affect employee benefits through the regulatory scrutiny and oversight of firms by regulatory authorities. In this context, formalization may act as a driving factor to promote employee rights and working conditions (Galiani & Weinschelbaum, 2012; Henley, Arabsheibani, & Carneiro, 2009; Rand & Torm, 2012). Furthermore, official registration may improve employee working conditions as a spillover effect from better productivity and profits. On the other hand, when formalization does not improve firm performance, wages and other employee benefits could be cut or delayed to offset poor productivity. In addition, according to the agency theory, higher levels of employee welfare might lead to a decrease in firm value (Ben-Nasr & Ghouma, 2018). As a result, the workforce can be downsized or wages and nonmonetary benefits, such as annual leave, paid leave or sick leave, may be reduced. 2
Empirically, many firm-level studies document the benefits of the tax registration of firms in terms of improvements in productivity and investment, increased market access, growth in market share, profits and the increased ability to network with large enterprises (Demenet, Razafindrakoto, & Roubaud, 2016; McKenzie & Sakho, 2010). However, other studies (e.g., de Adrade, Bruhn, & McKenzie, 2016) reveal that the benefits of informality may be greater than the costs, and informal firms register formally only because they are forced to do so. Furthermore, De Mel, McKenzie, and Woodruff (2013) provide evidence of the insignificant linkage between tax registration and firm performance. Interestingly, however, very few studies have quantitatively assessed the effect of formalization on employee welfares and few studies using aggregate firm-level data (e.g., Rand & Torm, 2012) consider the effect of formalization on the wages of employees. Moreover, these few studies do not account for employee characteristics that can lead to potential bias. Furthermore, no study considers the impact of formalization on employee non-monetary benefits or compliant corporate social responsibility of firms to their employees. 1 It should be noted that there is a trade-off between wages and non-monetary gains (Baicker & Chandra, 2006). Hence, it is essential to investigate whether the benefits of formalization go beyond monetary gains. Going beyond the results of current literature, this study for the first time considers the linkage between formalization and employee benefits in terms of both monetary and non-monetary factors, using a matched employer-employee panel dataset. Such an approach allows us to overcome the potential bias of previous studies which fail to control for both worker and firm characteristics. Also, the study corrects for unobserved factors and potential endogeneity by applying instrumental variable approaches. This study proceeds as follows. In section 2, the research context is presented, while the information on data and methodology is provided in section 3. The main results of the effects of formalization on employee welfare are discussed in section 4. Section 5 concludes the paper and suggest managerial implications from the findings. 2. The research context To promote a formalized economy, several support programs for enterprises have been launched by the Vietnamese government, for example tax credits, tax exemptions, and grants to cover loan applications (Nguyen, Verreynne, & Steen, 2014). However, as left-hand appendix 1 shows, many non-exporting firms are informal. By contrast the right-hand appendix 1 reveals that the majority of exporters are formal businesses, which indicates that formalization may be a crucial factor for participation in export markets.
1
Compliant corporate social responsibility of firms is considered as the compliance of firms to legal expectations for their employees.
3
Figure 1 shows that the majority of informal firms are household enterprises, while other types of ownership (cooperative, limited liability and joint-stock) operate mostly with formal status. Also, it should be noted that during the research period, from 2009-2015, there was a downward trend in the number of informal firms. In this context, many studies on Vietnam show that gaining official status helps firms with access to credit, government services, profit increases and contributions to the state via taxes (Boly, 2020; Rand & Torm, 2012). How does formalization affect employee working conditions and other fringe benefits, however? And what are the mechanisms through which formalization influences employee benefits? The following sections will outline the results that clarify these questions.
Household Collective/Cooperative 2009
Limited liability company Private/sole proprietorship Joint stock company without stat Household Collective/Cooperative
2011
Joint stock company without stat Private/sole proprietorship Limited liability company Household Joint stock company without stat
2013
Private/sole proprietorship Collective/Cooperative Limited liability company Household Private/sole proprietorship
2015
Collective/Cooperative Limited liability company Joint stock company without stat
1
.5
0 No Formalisation
.5
1
Formalization
Figure 1. Formal status of firms according to type of ownership. 3. Data and methodology 3.1 Data source We examine the influence of formalization on employee benefits in Vietnam for 2009, 2011, 2013, and 2015. Over 2500 small and medium-sized manufacturing enterprises were surveyed each year. These surveys were conducted jointly by the Central Institute for Economic Management of the Ministry of Planning and Investment, the Institute of Labor Science and Social Affairs of the Ministry of Labor, Invalids and Social Affairs, the Department of Economics of the University of Copenhagen, and the United Nations University World Institute
4
for Development Economics Research (UNU-WIDER) together with the University of Copenhagen, Denmark.2 The study uses an employer-employee panel dataset that is a combination between two modules. The first module comprises firm-level data, including information concerning formalization and firm characteristics, such as firm age, size and exports. The second module is made up of employee-level data that contain individual characteristics, such as gender, work experience, education, occupation and employee benefits (employee wage and working conditions). It should be noted that the data from the employee module only represent information from a sub-sample taking part in the surveys at firm level. 3.2 Methodology The empirical model controls for both employee and firm characteristics using the following equation. (1) In which Yit measures employee welfares, including the real monthly wage of the employees sampled. This study also considers non-monetary benefits that are defined as compliant corporate social responsibility of firms to their employees, including whether the employee has a formal contract, receives health insurance, maternal leave, severance pay and retirement pay. i, t denote firm i at year t. Regarding the independent variables, formalization (Fit) is the main variable of interest and is measured as a dummy variable (1 if a firm has a tax code and 0 otherwise) (Boly, 2020; Rand & Torm, 2012). Model (1) also includes the characteristics of workers and enterprises (and those of the owner/manager). Focusing on worker characteristics (Xit), since age, experience, and education are the essential human capital variables that determine workers’ earnings (Trifković, 2017), these variables are controlled for. The worker's gender is another essential characteristic that accounts for wage differences for workers in Vietnam (Trifković, 2017). In an extended estimation, this study also controls for small business characteristics (Zit), carefully selected to include those variables that relate to formalization and employee benefits at the enterprise level (Lavallée & Roubaud, 2019; Rand & Torm, 2012; Trifković, 2017). For instance, we control for enterprise characteristics, such as age and size (total labor force).
2
5
The Provinces covered in the survey data, please to see the appendix 4.
Finally, we include the export status of the enterprise, as this reflects manufacturing capacity that may influence wages and other employee benefits (Lavallée & Roubaud, 2019). A key concern in establishing the impact of formalization on employee benefits is the potential endogeneity of formalization. Unobservable confounding variables may also be correlated with both formalization and employee working conditions. Thus, we employ an identification strategy that relies on an instrument with a strong correlation with the endogenous variable (formalization), but no direct association with worker benefits. Understanding formalization as the term covering those actions that may be informed by the activities of other enterprises in the industry and by the location of the enterprise, we use the average rate of formalization in the peer group made up of sampled enterprises, defined by proximity in geographical location (district) and business activity (sector). Such an approach is widely applied in the literature (e.g., Cuong & Hau, 2020; Van Huong & Cuong, 2019), which notes that there is a considerable difference in development among provinces in Vietnam (Van Vu, Tran, Van Nguyen, & Lim, 2018). Therefore, instruments constructed at the level of location and sector would be likely to pick up these additional spatial and sectorial influences. Furthermore, we control for sectors and time dummies to capture macro variations (Tit). Specifically, an IV strategy relating to the role of formalization on worker benefits includes two stages. The first-rate regression displays the relevance of the instrument, and is defined in equation (2): (2) Where the instrument (IV) is defined earlier, while the covariates overlap with those in equation (1). The second stage regression is estimated as shown in equation (3):
(3) 4. Empirical results and discussion Columns 1 and 2 of Table 1 report the relationship between formalization and the wage outcome for workers, without addressing concerns about endogeneity. In these specifications, only worker characteristics are controlled for. In an extended specification, when the characteristics of small businesses and time-invariant factors are controlled for, a consistent but insignificant relationship between tax registration and the wages of workers is still reported. However, the results may still be biased because of the potential endogeneity of formalization. Hence, an FE-IV estimation is reported in column 4. The first-stage F-statistic shows that the instrument is valid and that the weak instrument problem is not a concern. The second-stage 2SLS estimate in column 4 reinforces the OLS result, that small businesses that engage in formalization in Vietnam report an insignificant reduction in workers’ wages. This finding disagrees with the conclusion in previous studies (e.g., Boly, 2015) that shows that formalization improves workers’ wages. The 6
discrepancy may be explained by the fact that previous studies using only firm-level data may be biased because of their failure to control for employee characteristics. Table 1: The effects of formalization on employee wages VARIABLES
Formalization Worker male Permanent worker
Experience University education Production workers
Pooled OLS
FE
FE
IV-FE
(1) 0.039 (0.055) 0.108*** (0.028) 0.608*** (0.144) 0.001 (0.003) 0.277*** (0.032) -0.262*** (0.031)
(2) -0.207 (0.189) 0.083 (0.052) 0.622*** (0.217) 0.001 (0.006) 0.160*** (0.060) -0.033 (0.058)
(4) 0.010 (0.345) 0.077 (0.054) 0.613*** (0.202) -0.000 (0.006) 0.159** (0.063) -0.031 (0.061) -0.001** (0.001) 0.003 (0.007) 0.347** (0.160) 0.195 (0.146) 0.115 (0.095)
5.855*** (0.150) 3,399 0.287
5.960*** (0.260) 3,399 0.298 2,076
(3) -0.204 (0.189) 0.080 (0.051) 0.607*** (0.207) 0.000 (0.006) 0.159*** (0.060) -0.030 (0.058) -0.001** (0.001) 0.003 (0.007) 0.350** (0.160) 0.195 (0.152) 0.110 (0.096) 5.810*** (0.299) 3,397 0.306 2,075
Firm size Firm age Export Low tech sectors Medium tech sectors Constant Observations R-squared Number of panels Instrumental variables
Weak identification test (Cragg-Donald Wald F statistic) [Stock-Yogo weak ID test critical value at 10%]
2,254 0.305 932 Location-industryyear average of formalization
685.736 16.38
Notes: Standard errors in parentheses, models also controlled for time year dummies; *** p<0.01, ** p<0.05, * p<0.1.
7
Regarding the role of other covariates for wages, results are generally in line with previous studies. For example, employees who have a higher position and more education earn higher wages. In addition, while there is an insignificant relationship between wage and gender, the permanent status of workers has a positive effect on wages. Accounting for firm-level explanatory variables for wages, exporters and innovators pay their employees higher wages than do non-exporters. These findings are in line with those of previous studies (e.g., Newman, Rand, Tarp, & Trifkovic, 2018). For example, Newman et al. (2018) show that a firm’s export activities have a positive effect on the fulfilment of their responsibilities for employees. Table 2: Formalization and employee welfare VARIABLES Health insurance Xtprobit IVprobit (1) (2) Formalization 0.753*** 0.394*** (0.113) (0.118) Worker male -0.019 -0.026 (0.015) (0.016) Permanent worker 0.071 0.110** (0.044) (0.046) Experience -0.002 -0.001 (0.001) (0.001) University education 0.159*** 0.199*** (0.020) (0.021) Production worker -0.144*** -0.172*** (0.016) (0.018) Firm size Firm age Export Urban Low tech sectors Medium tech sectors Observations
3,711
3,711
Xtprobit (3) 0.512*** (0.094) -0.006 (0.014) 0.062 (0.040) 0.001 (0.001) 0.114*** (0.018) -0.119*** (0.015) 0.005*** (0.000) -0.005*** (0.001) 0.050** (0.024) 0.009 (0.015) -0.097*** (0.020) -0.035 (0.021) 3,709
Xtprobit (4) 0.435*** (0.035) -0.022 (0.016) 0.205*** (0.045) -0.005*** (0.001) 0.237*** (0.024) -0.141*** (0.017)
Formal contract IVprobit (5) 0.254*** (0.048) -0.032* (0.017) 0.202*** (0.048) -0.004*** (0.001) 0.291*** (0.025) -0.173*** (0.018)
3,808
3,808
Xtprobit (6) 0.268*** (0.031) -0.008 (0.015) 0.168*** (0.043) -0.003** (0.001) 0.188*** (0.022) -0.107*** (0.016) 0.007*** (0.000) -0.002*** (0.001) 0.062** (0.028) 0.080*** (0.015) -0.056*** (0.022) -0.007 (0.023) 3,806
Notes: Standard errors in parentheses, models also controlled for time year dummies; *** p<0.01, ** p<0.05, * p<0.1. The analysis based on employee-employer panel dataset in the 2009-2015.
We further examine the role of tax registration for other worker benefits. Specifically, we consider the relationship between formalization and the likelihood of workers’ having a formal contract, health insurance, maternal leave, severance payment and retirement payment. We present both the probit and second-stage results of the instrumental variable probit in Tables 2 8
and 3. Interestingly, although there is no significant linkage between the formalization of firms and wages, formalization has a significant impact on non-monetary benefits. The results suggest that formalization increases recognition of employee according to marginal product of his labor. Firms invest in human capital to keep the workers productive (Holland, 2017). Tables 2 and 3 show that official registration has a positive correlation with the likelihood of workers’ receiving a formal contract, health insurance, maternal leave, severance payment and retirement payment, and the relationship is significant by any specification or method of estimation. For example, Columns 2, 5 and 8 of Table 4 reveal that employees in formal firms are paid more than 10% greater fringe benefits, such as maternal leave, severance pay and retirement pay, than their counterparts working in informal firms, keeping other factors constant. Table 3: Formalization and other employee welfares Maternal leave Severance pay Retirement pay Xtprobit IVprobit Xtprobit Xtprobit IVprobit Xtprobit Xtprobit IVprobit Xtprobit (1) (2) (3) (4) (5) (6) (7) (8) (9) 0.345*** 0.119** 0.241*** 0.327*** 0.128* 0.219*** 0.360*** 0.140** 0.247*** Formalization (0.037) (0.058) (0.035) (0.044) (0.067) (0.039) (0.047) (0.069) (0.041) -0.155*** -0.147*** -0.149*** -0.047*** -0.044*** -0.039*** -0.038*** -0.036** -0.032*** Worker male (0.015) (0.015) (0.014) (0.014) (0.014) (0.013) (0.013) (0.014) (0.013) 0.072 0.070 0.053 0.066 0.069 0.044 0.097** 0.088** 0.067* Permanent (0.046) (0.045) (0.044) (0.042) (0.044) (0.039) (0.043) (0.044) (0.039) worker -0.002* -0.001 -0.001 -0.002 -0.001 0.000 0.002 0.003* 0.003** Experience (0.001) (0.001) (0.001) (0.001) (0.001) (0.001) (0.001) (0.001) (0.001) 0.122*** 0.138*** 0.067*** 0.082*** 0.091*** 0.043** 0.121*** 0.140*** 0.078*** University (0.021) (0.021) (0.020) (0.018) (0.018) (0.017) (0.018) (0.018) (0.016) education -0.140*** -0.145*** -0.104*** -0.107*** -0.122*** -0.082*** -0.096*** -0.113*** -0.074*** Production (0.017) (0.018) (0.016) (0.016) (0.016) (0.015) (0.016) (0.016) (0.014) workers 0.003*** 0.002*** 0.003*** Firm size (0.000) (0.000) (0.000) -0.002** -0.003*** -0.002*** Firm age (0.001) (0.001) (0.001) 0.066*** 0.112*** 0.094*** Export (0.024) (0.020) (0.020) 0.122*** 0.042*** -0.008 Urban (0.015) (0.014) (0.014) dummies -0.086*** -0.056*** -0.087*** Low tech (0.021) (0.019) (0.018) sectors -0.055** 0.006 -0.022 Medium tech (0.022) (0.020) (0.019) sectors Observations 3,595 3,595 3,593 3,686 3,686 3,684 3,666 3,666 3,664 Notes: Standard errors in parentheses, models also controlled for time year dummies; *** p<0.01, ** p<0.05, * p<0.1. The analysis based on employee-employer panel dataset in the 2009-2015. VARIABLES
The literature indicates that in developing countries, formalization could positively affect the outcomes for small businesses (including profits, added value, gaining government support and bribe payments). To check whether these particular mechanisms are at play, we consider the role of formalization at firm level with these indicators. The results in Table 4 indicate that while 9
there is no significant correlation between tax registration and government support, formalization improves added value and reduces corruption. Improvements in added value and a reduction in bribe payments may improve regulatory oversight of the business – especially labor oversight. Therefore, the positive effect of formalization on workers in Vietnamese small businesses seems obvious when conditioned on higher productivity and transparency in the business environment. Table 4: Potential mechanism of the effect of formalization on employee welfare VARIABLES
Formalization Firm size Firm age Innovation Export Leverage Low tech sectors Observations R-squared Number of panels Instrumental variables
Value added
Government support
IV-FE (1) 0.258** (0.130) 0.012*** (0.001) -0.001 (0.002) 0.080*** (0.023) 0.327*** (0.091) 0.166*** (0.056) -0.011 (0.063) 5,291 0.651 2,038
IV-FE (2) 0.100 (0.082) 0.000 (0.000) 0.001 (0.001) 0.052*** (0.014) 0.039 (0.058) -0.023 (0.035) 0.038 (0.040) 5,319 0.100 2,045
Location-industryyear average of formalization
Location-industryyear average of formalization
Firm is a member of business association IV-FE (3) 0.062 (0.065) -0.000 (0.000) 0.002 (0.001) -0.017 (0.011) -0.104** (0.045) -0.013 (0.027) 0.027 (0.031) 5,320 0.930 2,045
Bribe amount
IV-FE (4) -0.001* (0.001) 0.000 (0.000) -0.000 (0.000) 0.000 (0.000) -0.000 (0.001) 0.000 (0.000) -0.000 (0.000) 5,322 -0.001 2,046
Location-industry- Locationyear average of industry-year formalization average of formalization 483.20 483.28
Weak 479.84 483.04 identification test (CraggDonald Wald F statistic) [Stock-Yogo 16.38 16.38 16.38 16.38 weak ID test critical value at 10%] Notes: Standard errors in parentheses, models also controlled for time year dummies; *** p<0.01, ** p<0.05, * p<0.1.
10
5. Conclusion and policy implications Based on an employer-employee panel dataset of four cycles from 2009 to 2015, this paper contributes to the literature by considering for the first time the effect of formalization on workers’ wages and non-monetary employee benefits. The study shows that formalization leads to a significant improvement in workers' welfare. This result is consistent, irrespective of the estimation technique applied, and does not change either with or without adjustment for other control variables. These findings provide the concrete evidence to support government efforts to reduce the number of firms with informal status. The recent outbreak of the Covid-19 pandemic has raised concern about the capacity and survival of private SMEs, especially when they remain informal in status. Hence, one direction for strengthening firm capability is to lead them through a transitional process from informal to formal status. This process may reduce the level of corruption and promote the added value of firms, and these in turn should improve the business environment for firms, the working conditions and welfare of employees. Despite interesting findings and important managerial implications, our study is subject to several limitations that provide potential avenues for future research. For example, this study focuses only on private manufacturing SMEs in Vietnam. Hence, future work could consider large firms. In addition, future studies may focus on enterprises in other economic sectors and other types of ownership to provide a broader understanding of the formalization of Vietnamese enterprises.
Appendices Appendix 1: Formal status of firms according to sectors
11
b) Exporters
a) Non-exporters
Wood
Wood Food and beverages
Furniture, jewellery, music equi
Furniture, jewellery, music equi
Leather
Textiles
Textiles
Fabricated metal products
Non-metallic mineral products
Non-metallic mineral products
Food and beverages
Basic metals
Apparel
Leather
Paper
Apparel
Publishing and printing
Motor vehicles etc.
Chemical products etc.
Chemical products etc.
Rubber
Paper
Basic metals
Publishing and printing
Fabricated metal products
Electronic machinery, computers,
Electronic machinery, computers,
Rubber
Motor vehicles etc.
1
.5
0 Formalization
.5
1
1
.5
No Formalization
0 Formalization
.5
1
No Formalization
Appendix 2: Descriptive statistics of main variables in the model 2009 Real wage in log (number) Employer pays for sick leave (Dummy variable) Employer pays for maternity leave (Dummy variable) Severance pay (Dummy variable) Payment when stop working/retires (Dummy variable) Gender of Worker (Dummy variable) Permanent full-time employee (number) Worker's number of years in firm (number) Education (1 if having professional secondary education, 0 otherwise) Occupation (1 if being production worker, 0 otherwise) Firm size (the number of full-time regular employees)
12
2011
2013
2015
Mean 6.45 0.49
SD 0.42 0.50
Mean 7.54 0.41
SD 0.83 0.49
Mean 7.61 0.42
SD 0.92 0.49
Mean 7.33 0.53
SD 0.87 0.50
0.32
0.47
0.41
0.49
0.37
0.48
0.44
0.50
0.23
0.42
0.24
0.43
0.33
0.47
0.28
0.45
0.20
0.40
0.25
0.43
0.40
0.49
0.28
0.45
0.60
0.49
0.59
0.49
0.59
0.49
0.59
0.49
0.99
0.11
0.97
0.16
0.97
0.17
0.98
0.15
5.44
4.99
6.05
5.52
6.39
5.62
7.73
6.16
0.16
0.37
0.19
0.40
0.21
0.41
0.24
0.43
0.60
0.49
0.59
0.49
0.58
0.49
0.62
0.48
32.25
40.75
22.79
30.65
22.84
33.57
27.85
45.20
Firm age (number) Export (1 if firms participate into export, 0 otherwise) Observations
13.96 0.13
11.05 0.34
998
12.80 0.10
8.49 0.30
14.82 0.10
1380
9.55 0.30
16.01 0.15
1521
8.65 0.36
1342
Appendix 3: Correlation matrix 1
2
3
4
5
6
7
8
9
1. Gender of worker
1.00
2. Permanent worker
0.0005
1.00
3. Experience
-0.0598*
0.0945*
1.00
4. University education
-0.1636*
0.0202
-0.0625* 1.00
5. Production worker
0.3225*
-0.0344* -0.0622* -0.5391* 1.00
6. Firm size
-0.1114*
0.0500*
-0.0287* 0.2363*
7. Firm age
0.0212
0.0175
0.3631*
-0.0873* 0.0757*
8. Export
-0.1191*
0.0325*
-0.0169
0.1327*
-0.1326* 0.3808*
-0.0351* 1.00
9. Formalization
-0.0558*
0.0106
-0.0243
0.1333*
-0.1537* 0.1677*
-0.0723* 0.1017* 1.00
-0.2144* 1.000 -0.0813* 1.00
Appendix 4: Provinces covered in the survey data
Ha Noi Phu Tho Ha Tay
Hai Phong
Nghe An
Quang Nam
Khanh Hoa 13
Long An
Lam Dong HCM C
Conflict of Interest Statement
The authors agree that this research was conducted in the absence of any self-benefits, commercial or financial conflicts and declare absence of conflicting interests with the funders. Acknowledgements
This researc h is funded by the Korean Foundation for Advanced Studies (KFAS) and the Asian Research Center, Vietnam National University, Hanoi (VNU) under project number CA.19.1A
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