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Locational and firm-level determinants of total factor productivity in Vietnamese manufacturing

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Total factor productivity (TFP) has received much attention from both academics and policy makers in the past decade, as it promises an answer to the question of sustainable growth in the context of limited inputs. This article examines the TFP of manufacturing companies in Vietnam and the factors at the firm level, in addition to locational drivers, especially at the provincial level, that drive the change in TFP. We use a strongly balanced panel dataset of 1,130 manufacturing firms from 2014 to 2018 and the Wooldridge method to calculate the TFP and a general least squares estimator with a heteroskedastic and uncorrelated error structure to examine the determinants. The results show that the TFP of firms is driven by factors at both the firm and the province levels. Specifically, firm size and capital intensity have a positive impact on TFP, while differences in firm type also influence TFP outcomes. Furthermore, six locational factors significantly impact firms' TFP, with a particular emphasis on Information and Communications Technology (ICT) readiness, transparency index, and corruption index. Most importantly, we found that transparency and corruption have a nonlinear inverse U-shaped association with the TFP of firms, implying that there is an optimal midpoint of governance quality that maximizes the TFP of firms. The article then provides certain implications for both policymakers and firms in improving their TFP.
Title: Locational and firm-level determinants of total factor productivity in Vietnamese manufacturing
Description:
Total factor productivity (TFP) has received much attention from both academics and policy makers in the past decade, as it promises an answer to the question of sustainable growth in the context of limited inputs.
This article examines the TFP of manufacturing companies in Vietnam and the factors at the firm level, in addition to locational drivers, especially at the provincial level, that drive the change in TFP.
We use a strongly balanced panel dataset of 1,130 manufacturing firms from 2014 to 2018 and the Wooldridge method to calculate the TFP and a general least squares estimator with a heteroskedastic and uncorrelated error structure to examine the determinants.
The results show that the TFP of firms is driven by factors at both the firm and the province levels.
Specifically, firm size and capital intensity have a positive impact on TFP, while differences in firm type also influence TFP outcomes.
Furthermore, six locational factors significantly impact firms' TFP, with a particular emphasis on Information and Communications Technology (ICT) readiness, transparency index, and corruption index.
Most importantly, we found that transparency and corruption have a nonlinear inverse U-shaped association with the TFP of firms, implying that there is an optimal midpoint of governance quality that maximizes the TFP of firms.
The article then provides certain implications for both policymakers and firms in improving their TFP.

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