International Journal of Entrepreneurship (Print ISSN: 1099-9264; Online ISSN: 1939-4675)

Research Article: 2021 Vol: 25 Issue: 5

Political Capital, Provincial Institution, and Firm Productivity: The Case Of Small And Medium Sized Enterprises In Vietnam

Quang Vu, Hanoi University of Science and Technology


In this paper, we analyze the impact of political capital (or political connections) and the quality of provincial institution on the productivity of private small and medium-sized enterprises (SMEs) in Vietnam - a lower middle-income economy. The study used a panel dataset from the period 2009-2015 and micro-econometric models. Robust to the choice of various control variables and controlling for potential endogeneity of political capital, we find that while political connections, as measured by a dummy variable, do not affect firm productivity, the intensity of political connections has a negative effect on firm productivity. We also find that higher productivity is found for firms with some types of innovation and those in provinces with better institutions. Our study implies that improving the quality of provincial institution, combined with government supports for firms’ innovations, can be an effective way of promoting firm productivity in Vietnam.


There are several theories explaining the association between political connections (or political capital) and firm performance. The resource dependency theory suggests that better political capital offers several benefits for firms. First, it facilitates relatively easy access to relevant resources and improves the chance of receiving business contracts. Also, having good political connections help firms overcome such obstacles as red tape or the weak enforcement of property rights stemming from a poor institution environment (Chen, 2011; Pfeffer & Salancik, 2003). Also, their networking activities and political capital can help firms receive information, advice, and assistance (Westlund & Bolton, 2003). Consequently, better political connections enable firms to accumulate more resources and information, which in turn improve their productivity and development. There is much empirical evidence indicating that political connections have positive effects on firm performance (Dang & La, 2020). The perspective of rent-seeking theory, however, indicates that government bureaucrats might be more interested in rent seeking and political objectives than industry efficiency (Shleifer & Vishny, 2002). In this sense, political capital can therefore be seen as an obstacle, resulting from a close link between firms and government. For instance, when a firm proposes new ideas or alternative methods of doing things, it can be restricted by their responsibility to partners with high political capital (Gargiulo & Benassi, 1999). Also, information redundancy might exist when firms limit their exchanges of knowledge and information to members within their network (Burt, 2009; Uzzi, 1999). In some situations, political connected firms are subject to return, or share benefits with political actors, and these may lead to costs as well as lower efficiency (Luo, 2003). Following the above theoretical framework, several studies have examined determinants of firm performance (Lee, 2020; Rahman, Meah, & Chaudhory, 2019) while there are a few studies analyzing the effect of political capital or political connections on firm performance. Specifically, several studies have found a positive linkage between political connections and firm performance. It was found that firms with better political connections are more likely to receive preferential loans in Indonesia (Leuz & Oberholzer-Gee, 2006). Similar findings are also found by Li, Meng, Wang, and Zhou (2008) who investigated the role of political connections in the performance of private firms in China. They found a positive effect of political capital on firm performance and such an effect tends to be greater in regions with poorer institutions and legal protections. However, political capital was reported to have a negative impact on non-listed companies in Poland and that the effect increases with the number of political connections (Koz?owski & Mielcarz, 2014). Similarly, political connections result in substantial economic costs for firms, as firms had duty to provide local employment during the election time in France (Bertrand, Kramarz, Schoar, and Thesmar, 2004) Also, politically connected firms tend to have lower productivity due to their relatively high labor costs and political connections tend to reduce the efficiency of corporate governance. Using micro econometric methods, Du and Girma (2010) also obtained the same result in China where political connections have a reducing effect on productivity among private companies. The aforementioned literature shows that most existing studies conducted in developed countries and countries with unstable political environments (Rand, 2017). While it is often to believe that political connections may have different impacts in different contexts (Batjargal, 2010), There is little empirical evidence about the association between political connections and the performance of private small and medium enterprises (SMEs) in transitional economies. A better understanding about the role of political capital in firm performance is much of importance for both academics and policy makers. Given the gap in the literature and importance of the research topic, the current study contributes to the literature by quantifying the impact of political connections on SMEs’ productivity in Vietnam.

Several challenges might arise in quantifying the impact of political capital on firm productivity. The estimates can be biased due to the presence of unobservable factors that can affect both the variable of interest and outcomes. Also, another problem is the possible endogeneity of political capital variable. Thus, we address these issues by employing a panel dataset of SME for the period 2009-2015. Notably, we use the instrumental variable estimator to account for the potential endogeneity of endogenous explanatory variables. Differing from previous studies that often measured the variable of political connections by a dummy variable alone, we measured this variable using both dummy and level of political connections. Notably, we examine the effect of political capital, controlling for various important factors such as the quality of provincial institutions and firm-characteristics. The paper is structured as follows. data sources and analytical methods are given in Section 2, while Section 3 shows empirical results and discussion. Section 4 concludes some main findings and offers some policy recommendations.



Our study utilizes two data sources, the first is taken from the survey data of SEMs operating in the manufacturing sector in Vietnam. The SMEs surveys were implemented jointly by several orgainzations, namely 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 for Development Economics Research (UNU-WIDER), and the Royal Embassy of Denmark in Vietnam. The SME survey was conducted in every two years from 2009 to 2015. The SME survey covers ten provinces/cities, namely Hanoi, Hai Phong, Ho Chi Minh, Ha Tay, Phu Tho, Nghe An, Quang Nam, Khanh Hoa, Lam Dong, and Long An. Our research sample includes more than 2,000 firms from each survey and forms an unbalanced panel dataset because the number of surveyed enterprises changes from year to year. The SME surveys contain rich information about firm identification, characteristics of employees, assets, human resources, innovation, government supports and other indexes. The second data source is utilized from the Vietnam's Provincial Competitiveness Index (PCI), which is conducted by the Vietnam Chamber of Commerce and Industry (VCCI) in collaboration with the United States Agency for National Development (USAID. The PCI is aggregated from sub-indicators, including market entry costs, land access and stability in land use, transparency, time value, informal payments, labour training and business support services. Two data sources are merged to form a panel dataset at both firm and provincial level. This dataset allows us to perform an empirical analysis of the effect of political connections on firm productivity. Definitions and measurements of included variables are given in Table 1 and Appendix 1. It shows that about 7% of the total SMEs reported that their management board have at least a party membership in 2009, increased to about 9 % in 2011 and 2013 and then reduced to 7% in 2015. Also, the number of connections per firm, on average, slightly reduced from about 40.63 % in 2009 to about 38.13 % in 2015 (Table 1).

Analytical Method

Following De Rosa, Gooroochurn, and Görg (2016), we employed a Cobb-Douglas production function to investigate the effect of political capital on firm productivity which is a common econometric specification in the literature. The model specification is given in equation (1): (1) In equation (1), lnVAit denotes the log of value added of firm i at time t, which is modelled with two inputs, namely lnKijt (the log of capital) and lnLijt (the log of the number of workers). As already mentioned, our interest variable is political capital (PCit) which is measured as a dummy, receiving the value of 1 if the firm holds at least a communist party membership and 0 otherwise (Rand, 2017). We also measure the extent of political connections by government officials that firms have maintained regular contacts within the last three months. Several important control variables were also included in our analysis, following previous empirical studies (Nguyen & Van Dijk, 2012; Van Vu, Tran, Van Nguyen, & Lim, 2018). They are firm-level characteristic factors (Xit) such as firm size, leverage and innovation. We also include the PCI index to control for the quality of the business environment (Zit) where firms operate, accounting for the potential impact of these variables on firm productivity. Finally, some dummy variables for industry and regional fixed effects were also included in the model to capture various effects of industrial and provincial characteristics (Van Vu et al., 2018).

However, our research results is likely to be biased if equation (1) is estimated using ordinary least squares (OLS) or fixed effects estimators, because political capital may be potentially endogenous. To effectively address this issue, we employed an instrumental variable (IV) estimator in our analysis. Using an IV estimation requires the availability of a variable that has a trong effect on the endogenous explanatory variable (poitical capital) but does directly affect the outcome variable (firm productivity). Applying a similar approach in previous studies (Fisman & Svensson, 2007; Huong & Cuong, 2019), our study created an intrumental variable for the political variable by using the industry-location-time averages. The level of the transparency of provincial government in a given province is also used as another instrument. This is because provinces with a higher level of transparency tend to have lower degrees of political connections. There are two septs for using the IV estimation. First, PCit is estimated using instrumental variables and other controlled variables, as described in Model 1. Next, the second step is regressed via a reduced form, as below. In equation (2) is the estimated value of PC in equation (1), while Yit, Zit, and Xit are dependent, instrument and control variables, respectively as indicated in Equation 1.


Table 2 show the regression results from using various specified models. As given in Column 1 of Table 2, politically connected firms tend to have lower productivity than those without political ties. Possibly this can be explained by the fact that government officials tend to be rent-seeking instead of caring about industry efficiency (Shleifer & Vishny, 2002). Such results seem to support previous findings (e.g., Jackowicz et al., 2014). However, the esimates from Column 1 are still biased due to the potential endogeneity problem of political capital, as discussed in the method section. To account for the possible endognegeity, we employed the instrumental variable method. As shown in the two bottom rows of Table 2, the value of the Cragg-Donald Wald F is 602.26), which is larger than the reported Stock-Yogo weak identification critical value of 19.90. This confirms that using the location-industry average of political connections and transparency at provincial level as instrumental variables is valid in our analysis.

Surprisingly, as shown in Column 2 of Table 2, the impact of political capital on firm productivity turns to be statistically insignificant after controlling for unobserved factors and endogeneity. Nevertheless, as already mentioned, using a dummy variable for measuring political capital does not fully capture the level of political ties. Consequently, we also measured political connections in terms of the extent of political connections. The result in Column 3 of Table 2 shows the negative effect of political connection level on firm productivity when accounting for unobserved factors and endogeneity. For instance, when the level of connections increases by one-unit, firm productivity decreases by 0.1%, holding other factors constant. The research finding suggests that the effect may be concealed by measuring political capital with a dummy variable in previous studies. Notably, our research finding supports the rent-seeking viewpoint. According to Zhang (2014), a plausible explanation for this is that while the extent of political connections may help firms with relatively easy access to credit or government subsidies, such subsidies may increase distortion in the efficient allocation of resources, which in turn leads to slow productivity growth.

With respect to the role of firm-level factors in firm productivity, the coefficients for both labour and capital inputs are highly statistically significant in all model specifications. In addition, we find that not all types of innovations have a positive effect on firm productivity. For example, the application of new technology and modifying existing products have a positive influence on firm productivity but it is not the case for the introduction of new products. Specifically, Column 2 of Table 2 indicates that innovators obtain from 4% to nearly 5% higher productivity than non-innovators, holding all other factors constant. The results are in line with most findings in the literature (Cassiman, Golovko, & Martínez-Ros, 2010). We find that firm age has no effect on firm productivity. All specified models confirm that firms with government support tends to attain higher productivity than those without. This result may reflect the fact that private SMEs in Vietnam are often characterized by those with limited resources, and therefore government support may give them valuable funding sources. As a result, firms receiving government support would invest in R&D and promote their productivity (Wu, 2017). The results also confirm the role of provincial institution in firm productivity. For instance, the PIC has a positive impact on firm productivity in Column 4 of Table 2, which indicates that given a one-score increase in the PCI, firm productivity increase by 0.012%, holding all other factors constant. A useful implication here is that policies or activities for supporting the private sector, combined with the provision of a stable, clear legal framework, are found to promote firm productivity in Vietnam. The findings are consistent with that of Vu et al., (2018) in Vietnam and Choi (2015) in China which found that firms locating in regions with good institutions were more likely to attain higher productivity. It would be interesting to further examine how political connections affect firm productivity in various situations. In Vietnam, larger SMEs with more resources are likely to obtain greater benefits from their political connections, but smaller ones might be negatively affected by a crowding out effect from the costs of these connections. Therefore, we examine how the effect varies by firm size. The results indicate that the coefficients tend to be more negative for small firms, while the corresponding effect is not statistically significant at the 5% level for larger ones. Column 3 of Table 3 indicates that the level of political connections has a negative effect on the productivity of formal firms. A similar finding is also found in China by Du and Girma (2010) where private firms with political capital had lower productivity and did those without.


Differing from previous studies, our study is the first to investigate the impact of political connections as well as the extent of political connections on firm productivity. It was found that political connections as measured by a dummy variable had no effect on firm productivity. The finding is robust even after controlling for various firm characteristics, provincial institutions, unobservable time-invariant factors, and potential endogeneity. However, we find that a higher level of political connections shows a negative effect on firm productivity. As already discussed, the negative effect may reflect the fact that despite having more political connections may help firms with relatively easy access to credit or government subsidies, such connections may increase distortion in the efficient allocation of resources, consequently resulting in lower productivity growth. In addition, our findings suggests that previous studies that often ignored the potential endogeneity of political connections and that often used only a dummy variable for these connections may not capture their real effect on firm productivity. Our research finding also offers some useful policy recommendations. Governments’ financial and technical supports for innovative activities are expected to help SMEs increase their productivity and development. Also, improving the quality of provincial institutions can help firms improve their productivity growth. It suggests that provincial authorities should conduct several measures, from building a clear legal framework as well as a simplification of administrative procedures. These are vital to create a good institution for the productivity growth and the development of SMEs in Vietnam.


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