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Social capital and firm performance in transition economies

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Abstract

The study explores how social capital affects the performance of small- and medium-sized enterprises (SMEs) in a transition economy. Social capital is referred to as firm’s social interactions with formal and informal creditors, which is financial social capital, and social interactions with politicians and civil servants, which is political social capital. Using a control function estimation method with longitudinal data from repeated surveys of small- and medium-sized enterprises (SMEs) in Vietnam, we find an inverted U-shaped relationship between social capital and SMEs’ performance, which is measured by gross profit and labor productivity. We further show that there is a positive complementary effect between innovation and social capital in affecting performance of SMEs.

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Availability of data and material

Data are available upon request.

Code availability

Stata.

Notes

  1. We also use network intensity, which is frequency of network assistance to conduct robustness analysis.

  2. As a result, we removed these SMEs from our sample. The number of removed SMEs were 18, 10, 8, 7, 46, and 70 in 2005, 2007, 2009, 2011, 2013 and 2015, respectively.

  3. We used the question “In this year, how many people do you have regular contact at least once every 3 months, which you find useful for your business operations?” in the questionnaire to capture network size of SME, which is answered for politicians and credit provider separately. We also measure financial and political social capital using different variables providing information on the number of times that bank officers and politicians and civil servants assisted the owner/manager over firm operational issues during the previous year. We will discuss about them in Sensitivity Tests section.

  4. This instrument variable is utilized by answering the question “What was the previous main work’s experience/positions of respondent before owning or managing this firm?” in the questionnaire.

  5. \({\overline{Z} }_{1i}\) in Eq. (4) includes \({\overline{LCs} }_{i}\), \({\overline{IN} }_{i}\), \({\overline{X} }_{i}\) and the time averages of social capital and the square of social capital. \({\overline{Z} }_{2i}\) in Eq. (5) includes \({\overline{Z} }_{1i}\) and the time averages of interaction variables (\({SC.IN}_{it}\) and \({SC}^{2}.{IN}_{it}\)), which are able to eliminate the unobserved firm heterogeneity in the second stage.

  6. We use the command xtreg y x, re vce(cluster firmid) in Stata 16 to estimate Eqs. (4) and (5).

  7. To test for inverted U-shaped relationships, we use Lind and Mehlum’s (2019) user-written utest command in Stata.

  8. We use the nlcom and test commands in Stata to test for this difference.

  9. Only value of jointly testing for endogeneity of financial social capital—chi2(2) = 4.15, p-value = 0.1258, in column (3) for operating profit is weak confirmation. However, the residual of financial social capital is still significant at 10%, which may confirm its endogeneity. Furthermore, we estimate Eq. (4) without controlling for endogeneity by using the “native” RE models and the CRE models. The estimation results are consistent with Columns from (1) to (4) in Table 4. The estimation results are available upon request.

  10. The estimation results will be provided upon request.

  11. We re-estimate Eq. (5) by removing \({SC}_{it}^{2}\), \({SC}^{2}.{IN}_{it}\), and \({\widehat{v}}_{it}^{2}\), then we use “margins, dydx(IN) at(FSC = (0(1)60)) vsquish” and “marginsplot, recast(line) yline(0) xlabel(0(2)60) xlabel(, angle(90))” commands in Stata 16 to obtain Figs. 3 and 4.

  12. To control for possible effects of different foreign markets on inducing the innovation and conditioning the social capital, we have included dummies for these markets in the replacement of the export dummy. The results are robust against this change.

  13. The regression results are available upon request.

  14. We estimated Eq. (3) by using glm command in Stata 16 with poisson or negative binomial in family function and log in link function options along with firm-clustered standard errors.

  15. The regression results are available upon request.

  16. We used the question “How many times per year did your networks assist in issues related to the operation of your firm?”. Note that this question was not mentioned in the 2005 survey questionnaire.

    17 The estimation results will be provided upon request.

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This work is supported by Foreign Trade University under the Research Program number FTURP01-2020-01.

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  1. Foreign Trade University, Hanoi, Vietnam

    Hung Quang Doan & Nam Hoang Vu

  2. LUISS University, Rome, Italy

    Hung Quang Doan & Francesca Masciarelli

  3. University G.d’Annunzio, Pescara, Italy

    Andrea Prencipe

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Doan, H.Q., Masciarelli, F., Prencipe, A. et al. Social capital and firm performance in transition economies. Eurasian Bus Rev 13, 751–780 (2023). https://doi.org/10.1007/s40821-022-00227-y

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