Labor productivity gap between export and non-exporting firms in industrialization: The case of the Vietnamese manufacturing sector

Firm’s age (log) -14.29*** -34.84*** -3.543** -6.144*** -7.802*** -2.537 
 (1.555) (2.355) (1.738) (1.588) (2.108) (1.803) 
Total fixed assets (log) 0.406*** 0.361*** 0.367*** 0.345*** 0.266*** 0.258*** 
 (0.00515) (0.00542) (0.00556) (0.00488) (0.00554) (0.00565) 
FDI (dummy) 0.228*** 0.255*** 0.192*** 0.281*** 0.515*** 0.494*** 
 (0.0336) (0.0417) (0.0431) (0.0456) (0.0399) (0.0537) 
Manufacturing sector (dummies) Yes Yes Yes Yes Yes Yes 
Constant 109.7*** 266.0*** 28.54** 48.39*** 61.29*** 21.47 
 (11.83) (17.92) (13.22) (12.08) (16.03) (13.71) 
Observations 38,735 32,571 45,550 44,522 35,100 29,111 
Adjusted R squared 0.822 0.731 0.814 0.823 0.744 0.811 
Note: For the sake of brevity, coefficients of manufacturing sectors (dummies) are not presented. 
Robust standard errors in parentheses 
*** p<0.01, ** p<0.05, * p<0.1 
Source: Authors’ estimation from VAES 2010-15 
4.3. Decomposition Results 
Table 5 presents the decomposition results. The labor productivity among firms in the EXs is, on average 58.1 percent higher 
than among firms in the NEXs (log difference of 0.581) and it is significant at 1 percent level. This labor productivity gap is 
further decomposed into an endowment effect and a structural effect. Endowment effect refers to the attributes of certain factors 
experienced by the firm, whereas the structural effect refers to the returns to these attributes or factors. For example, the size of 
a firm. Firms in EXs are on average larger than the firms in the NEXs, and this contributes to the labor productivity gap via the 
endowment effect. Furthermore, the returns of a unit increase in firm-size (or marginal working labor) may have differential 
effects for firms in EXs vs. NEXs, and this would be captured as a structural effect. Our results show that the labor productivity 
gap is almost come from the endowment. That is, the structural effect explains 34.4 percent of the productivity gap while the 
endowment effect explains the remaining 65.6 percent of the productivity gap (0.380 divided by 0.581). Firm-level factors 
contribute significantly to the productivity gap via the structural effect and the endowment effect. These factors are discussed 
below (Table 6). 
Endowment effect 
Recall that firms in the NEXs are less productive than firms in the EXs. Thus, any factor that narrows the productivity gap 
favors firms in NEXs over firms in EXs. The findings for the endowment effect are presented in column 1 of every year in 2010-
2015 in Table 8. The biggest contribution to the productivity gap via the endowment effect comes from the difference between 
NEXs and EXs in the level of total fixed assets followed by firm’s age, and then being an FDI. 
H. T. Nguyen et al. /Accounting 6 (2020) 521
Structural effect 
The structural effect refers to the role of the returns to production factors or attributes of firms that 
lead to the widening or narrowing of the productivity gap. In Table 6, the structural effect is displayed in columns 2 and 3 of 
every year in 2010-2015. The biggest contribution comes from differences between the NEXs and the EXs in returns to total 
fixed assets, firm size and being an FDI. 
Table 5 
Decomposition results: the endowment and structural effects 
VARIABLES 2010 2011 2012 2013 2014 2015 
Labor productivity (log) in the NEXs 7.888*** 7.908*** 8.216*** 8.263*** 8.253*** 8.472*** 
 (0.00794) (0.00948) (0.00775) (0.00802) (0.00931) (0.00970) 
Labor productivity (log) in the EXs 8.469*** 8.868*** 9.000*** 9.041*** 9.234*** 9.315*** 
 (0.0195) (0.0159) (0.0164) (0.0147) (0.0153) (0.0151) 
Labor productivity difference (NEXs 
minus EXs labor productivity) 
-0.581*** -0.960*** -0.784*** -0.777*** -0.981*** -0.843*** 
 (0.0210) (0.0185) (0.0181) (0.0168) (0.0179) (0.0180) 
Endowments -0.380*** -0.632*** -0.544*** -0.596*** -0.596*** -0.511*** 
 (0.0285) (0.0220) (0.0254) (0.0205) (0.0218) (0.0212) 
Coefficients -0.0997*** -0.0695*** -0.272*** -0.230*** -0.265*** -0.165*** 
 (0.0194) (0.0191) (0.0208) (0.0183) (0.0184) (0.0222) 
Interaction -0.101*** -0.258*** 0.0319 0.0486** -0.121*** -0.167*** 
 (0.0271) (0.0229) (0.0273) (0.0217) (0.0224) (0.0251) 
Observations 44,252 41,407 53,994 55,024 44,343 38,532 
Note: Robust standard errors in parentheses 
*** p<0.01, ** p<0.05, * p<0.1 
Source: Authors’ estimation from VAES 2010-15 
2. Conclusions and implication 
The manufacturing sector in Vietnam is accounted for large shares of the labor force and capital accumulation during the process 
of economic growth. It is also expected to contribute to structural transformation and industrialization. Nevertheless, the 
literature related to Vietnam is still silent on evidence on the productivity of the manufacturing sector. This knowledge gap in 
the manufacturing sector’s productivity presents a serious space in the realization of industrialization in Vietnam. 
Results show that the labor productivity of the manufacturing sectors increased during the study period. It can be concluded that 
the firms' productivity contributed to the current industrialization in Vietnam. On top of that, some manufacturing sectors with 
increasing labor productivity in the study period, namely: Fabricated metal products (code 25), Basic metals (code 24), Motor 
vehicles, trailers and semi-trailers (code 29), Computer, electronic and optical products (code 26), Leather and related products 
(code 15), Machinery and equipment not yet classified (code 28), Furniture (code 31), Electrical equipment (code 27), Other 
non-metallic mineral products (code 23), Other transport equipment (code 30), Wearing apparel (code 14), and Food products 
(code 10), and some are not. Thus, it can be argued that Vietnam’s government policy plays a crucial role in stimulating the 
current industrialization. By targeting selective manufacturing sectors, policies might strengthen relevant advanced 
manufacturing sectors with currently high labor productivity, and give supports to potential manufacturing sectors those need 
to go advance in the future. 
By using Oaxaca-Blinder decomposition method, several firm-level variables are found to contribute significantly to the 
productivity gap via the endowment effect and the structural effect. In overall, the endowment effect surpasses the structural 
effect in our sample period. Among the factor contributions, capital stock plays the most important role. Empirical studies about 
the impact of the related policy on the manufacturing industries will be fruitful research agenda. 
52
2
 Ta
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e 6
D
ec
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sit
io
n 
re
su
lts
: F
irm
-le
ve
l f
ac
to
r c
on
tri
bu
tio
ns
VARIABLE 
20
10
20
11
20
12
Endowments 
Coefficients 
Interaction 
Endowments 
Coefficients 
Interaction 
Endowments 
Coefficients 
Interaction 
Em
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m
en
t 
(lo
g)
0.
88
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29
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72
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62
1 
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3 
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69
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7 
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VARIABLE 
20
13
20
14
20
15
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Coefficients 
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Endowments 
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Interaction 
Endowments 
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H. T. Nguyen et al. /Accounting 6 (2020) 523
Acknowledgment 
The authors would like to thank the anonymous referees for constrictive comments on earlier version of this paper. 
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