Total Factor Productivity Growth of Vietnamese Enterprises by Sector and Region: Evidence from Panel Data Analysis

Round 1

Reviewer 1 Report

The article proposes an interesting and timely topic. It seems to be very promising and the article itself has potential, but I would suggest some improvements:

1) The aim of the study should be clearly expressed in the abstract as well as in the introduction. The objective formulated in the introduction is not correct. It cannot be the purpose of an article to measure something in order to give recommendations. Recommendations are obvious, but the aim is to prove what the author wanted to show in the article, what he wanted to verify? 

2) Please complete introduction with brief description of applied methods.

3) Please underly the novelty of the study in the introdution. Research were also carried out on other samples it is worth referring to this. Please see: 

Botrić, V., Božić, Lj., & Broz, T. (2017). Explaining firm-level total factor
productivity in post-transition: manufacturing vs. services sector. Journal of
International Studies, 10(3), 77-90. doi:10.14254/2071-8330.2017/10-3/6 

4) Literature review should be definitely extended. Actually, in the literature review presented, there are no results of existing studies on TFPGs from different sectors - this should be presented:

Ngo, Q & Tran, Q. (2020). Firm heterogeneity and total factor productivity: New panel-data evidence from Vietnamese manufacturing firms.Management Science Letters , 10(7), 1505-1512.

Kaczmarek, J. (2018). Competitiveness profiles of manufacturing mesostructure. International Entrepreneurship Review, 4(3), 231-256. Retrieved from https://ier.uek.krakow.pl/index.php/pm/article/view/1773

5) The article lacks of discussion. Please cofirm your results with prior studies. 

6) In the conclusions please extend limitations of the study and implications for business and literature. 

Author Response

The author thanks the reviewer for the comments that are very helpful to the author to improve the overall quality of the manuscript. The following are the manuscript revisions that I have edited according to the comments of the reviewer.

1. The aim of the study should be clearly expressed in the abstract as well as in the introduction. The objective formulated in the introduction is not correct. It cannot be the purpose of an article to measure something in order to give recommendations. Recommendations are obvious, but the aim is to prove what the author wanted to show in the article, what he wanted to verify?

 Response:

The aim of study is adjusted and clarified in both the abstract and the introduction as follows:

 

In abstract

The sentence “This study identifies and compares TFPG among enterprise sectors as well as enterprises in regions of Vietnam” is replaced by

“The aim of this study is to find imbalance between TFPG and in enterprises growth pattern of sectors and regions in Vietnam”

 

In the introduction

The sentence “From the above reasons, this paper is conducted with the main purpose of measuring the TFPG of enterprises among sectors as well as regions to give implications from the research results for the growth model of enterprises in sectors and regions” is edited to “The above outlines the motivations for this study of enterprise TFPG among sectors and regions of Vietnam. The objective of this paper is to verify the imbalanced development of TFPG and the growth model of enterprises in the sectors and regions of Vietnam”

2. Please complete introduction with brief description of applied methods

 

Response:

Brief description of applied methods is added in the introduction as follows:

Paragraph “In Vietnam, there are some studies measuring TFP and TFPG such as measuring TFP in Agriculture (Bao, 2014; Giang et al., 2019); measuring TFPG in Coal industry (Phuong, 2018); comparison TFPG among modes of transport (Quang, 2019) ... The methods used include both parametric approach (Giang et al., 2019; Quang, 2019) and nonparametric approach (Bao, 2014; Phuong, 2018)” has been replaced by

“Previous TFP and TFPG studies in Vietnam,  have addressed various fields and have been diverse in their scope. These include measuring TFP in agriculture (Bao, 2014; Giang et al., 2019); TFPG in the coal industry (Phuong, 2018); TFP in air transport (Quang, 2017); TFPG among modes of transport (Quang, 2019); TFP in the food industry (Long, 2020), TFP in manufacturing sectors (Huong, 2017; Thanh et al., 2020); TPF for foreign direct investment enterprises (Hien et al., 2019) and for state ownership (Canh et al., 2021). In addition, there are a number of studies examining factors affecting TPF, such as: The impact of the investment climate on TFP in the agricultural sector (Trung & Cuong, 2011); the impact of investment climate on the TFP of manufacturing firms (Giang, 2018); the impact of innovation on the TFP of small and medium sized enterprises (Hue et al., 2019); the determinants of TFP in manufacturing industry (Oanh, 2019).

 

These studies are mainly focused on specific industries or specific ownership sectors. The methods used include both the parametric approach (Trung & Cuong, 2011; Quang, 2017; Giang et al., 2018; Giang et al., 2019; Quang, 2019; Oanh, 2019; Canh et al., 2021) and non-parametric approach (Coelli & Rao, 2005; Kong & Tongzon, 2006; Wu, 2011; Bao, 2014; Phuong, 2018). In addition, some recent studies also utilized a semi-parametric approach (Huong, 2017; Thanh & Van, 2020). Most of the parametric and non-parametric approaches use the Ordinary Least Square (OLS) regression technique to estimate the parameters for the TFPG calculation or are based on OLS such as robust regression (Bao, 2014), Fixed Effect Models (FEM) and Random Effects Model (REM) for panel data (Giang et al., 2019; Canh et al., 2021). The semi-parametric approach uses the estimation technique of Olley and Pakes (1996) (Giang et al., 2018) or the procedure of Ackerberg et al. (2006) (Thanh & Quang, 2020). These approaches are discussed in Section 2.”

 

3. Please underly the novelty of the study in the introduction. Research were also carried out on other samples it is worth referring to this.

 

Response:

The novelty of the study was briefly added in the introduction as follows:

“The key empirical contribution of this paper will be in detailing the different roles of TFP, capital and labor on the growth model of enterprises operating across various sectors and regions in Vietnam with an updated sample to 2018. To the best of the author's knowledge, this is the first attempt to provide useful insights into the repercussions of imbalanced TFP developments between sectors and regions in Vietnam based on a consistent data set and methodology.”

4. Literature review should be definitely extended. Actually, in the literature review presented, there are no results of existing studies on TFPGs from different sectors - this should be presented.

Response:

Literature review is expanded as follows:

The paragraph “For the none-frontier approach, the parameter technique estimated by the Cobb - Douglas translog function is commonly used for model specification (Tan and Virabhak, 1998; Felipe, 1999; Giang et al., 2019; Quang, 2019).” expanded to:

“For the non-frontier approach, the parameter technique estimated by adapting production functions is also commonly applied. There are two common ways to obtain TFP based on firm-level production functions: Cobb-Douglas production functional form, and a translog production function. It is argued that both approaches have good mathematical properties. However, according to Giang et al (2018), the elasticity of the production to the inputs in the Cobb–Douglas function allows for easier interpretation than the trans logarithmic production. To be more specific, the translog technique generally suffers from a collinearity problem among the regressors (Kinda et al., 2011)

When measuring TFP for firms across broad industries or sectors, a simple production function consisting of two inputs, capital and labor, and an output factor of value-added, is often used because these are factors that most generally reflect inputs and outputs (Tan & Virabhak, 1998; Felipe, 1999; Giang et al., 2018; Giang et al., 2019; Oanh, 2019; Thanh & Quang, 2020; Canh et al., 2019; Giang et al., 2019; Oanh, 2019; Thanh & Quang, 2020; Canh et al. al., 2019). When measured within specific industries or firms, inputs can be extended beyond capital and labor (Bao, 2014; Thanh et al., 2020; Canh et al., 2021), or outputs can be measured by the number of products (Quang, 2019)”

 

In addition, the Literature review also added the following paragraph:

“To overcome the problem of endogeneity between inputs and unobserved productivity, Olley and Pakes (1996) proposed a semi-parametric approach which was later extended by Levinsohn Petrin (2003) and Wooldridge (2009). The robustness to measurement errors is also an advantage of the semi-parametric method (Van Biesebroeck, 2004). This approach is often used to estimate unobserved productivity at the firm level and has been applied to the measurement of manufacturing firms in Vietnam (Huong, 2017; Thanh & Quang, 2020).

Although there are many different approaches, they can be summarized into three main methods: 1) the non-parametric approach using DEA; 2) the parameter approach using the production function (Cobb-Douglas production and the transformed production function); 3) the semi-parametric approach estimating Cobb-Douglas production functional form specified by the methodology of Levinsohn and Petrin (2003). Non-parametric approaches have the benefit of not assuming a specific functional form/shape for the frontier. However they do not provide a general relationship (equation) regarding outputs and inputs to enter as parametric or semi-parametric approaches. The frequent techniques to estimate the production function include OLS estimation, the Olley and Pakes method, and the Levinsohn and Petrin approach”

 

5. The article lacks of discussion. Please confirm your results with prior studies.

 

Response:

Discussion has been improved and separated into section 4.4 as follows:

“… These results are consistent with some recent studies demonstrating that foreign direct investment enterprises in Vietnam have an expanding role in TFP (Hien et al., 2019); and negative TFP growth of state-owned enterprises in China (Ozyurt, 2009). The results also support the outcome of the study by Canh et al. (2021), which argues that state ownership is negatively associated with TFP. The decline in TFPG is because enterprises in the state-owned sector remain inefficient and have fewer incentives to change and change senior management. In addition, the study by Canh et al. (2021) also shows that corruption control hinders TFP. It must also be seen that in the last three decades, state-owned enterprises have been reformed, in which many privileges of the state-owned enterprises have been removed, and the least efficient state-owned enterprises have been merged or equitized. However, the results of this study cast doubt about the effectiveness of state-own enterprise reform measures in Vietnam

The relatively stable TFPG of the non-state enterprise sector in the period 2009-2018 found in this study is evidence that lends support to the view that the private sector is increasingly effective and plays an important role in the economic development of Vietnam. One of the reasons for this result was studied by Canh et al. (2021). They indicated that transparency promotes the TFP of private enterprises more than that of state-owned enterprises. In addition, in Vietnam, small and medium-sized enterprises are mainly in the non-state sector (in the period 2005-2018, the non-state enterprise sector accounted for 96.41% of the number of enterprises but only 59.13% of the labor and 50.83% of the capital). Hence, the TFPG of the non-state sector partly reflects the efficiency of small and medium-sized enterprises; and the TFPG of the non-state sector found in this study is also consistent with the research results of Hue et al. (2019), which indicated that innovation has a positive impact on the TFP of small and medium-sized enterprises in Vietnam.

TFPG differences between regions of any country are obvious, but this study has shown specific differences between six regions in Vietnam by analyzing data up to 2018. It is believed that no previous studies have conducted this type of analysis

… This trend is especially marked in the Central Highlands, where workers are moving away to find employment in other regions. Despite efforts to combat the outward labor migration and increased agricultural employment, negative growth persists. The reason for this phenomenon is that most of the provinces in this region are slow to develop, poor transportation infrastructure, have few industrial zones, and the pace of industrialization and urbanization is quite slow. These findings, therefore, illustrate the unbalanced development of TFP among the regions of Vietnam….”

 

 

6. In the conclusions please extend limitations of the study and implications for business and literature.

 

Response:

The conclusion is extended by clarifying the implications for business and literature, and adding the limitations of the study at the end of section 5 as follows:

“…These findings demonstrate the weakness of the state-owned enterprise sector and the increasing efficiency of the non-state enterprise sector as well as the foreign direct investment enterprise sector. The unbalanced development of TFPG among regions found in this study is indicative of the growing economic gap among regions. This is a scenario not usually expected internationally but for Vietnam is a case in point.

The results of this study imply that the government should continue to push ahead with reforms to improve the efficiency of state-owned enterprises. Although the state-owned sector accounts for only 0.84% of enterprises, they provide 14.01% of labor and 31.33% of capital in acting enterprises. Therefore, they still play an important role in maintaining the state-owned sector and remain absolutely necessary. However, the state only needs to hold key areas to ensure social cohesion that other sectors do not want to participate in, such as reducing state ownership and loosening administrative controls. In addition, the state continues to create mechanisms to promote the non-state enterprise sector and foreign direct investment enterprise sector, creating a level playing field for all types of enterprises. In order to reduce the economic gap between regions, the state also needs to have policies to support underdeveloped enterprise areas, declining TFPG, especially in the Central Highlands, such as infrastructure development, policies to support capital and training, and so on. This helps these regions create advantageous conditions for production and business, innovation management, and technology to improve TFP. On their side, enterprises need to focus on increasing capital for growth and development, especially innovating and improving technology and management methods to promote TFPG. Capital increases will be more favorable than labor growth because, from a social perspective, the ability to increase labor will be limited. However, innovation in technology, management to increase TFP is the key issue to improve the efficiency of enterprises…

Although this study has obtained some valuable results, there still exist some limitations. Firstly, due to data limitations, this study only explores TFPG from a macro perspective, such as among sectors and regions, without analyzing the internal performance of each specific industry. Secondly, due to the macro perspective, this study only considers two inputs when studying each specific industry, so the input factors need to be supplemented accordingly. Nevertheless, these issues may provide opportunities for further study”.

Thank you very much for the interest and helpful comments

Reviewer 2 Report

Literature review needs to improve, as a number of most recent and relevant studies have missed by authors. 

There is a need for critical discussion with proper citations on estimated results.

The conclusions session can be improved.

 

Author Response

The author thanks the reviewer for the comments that are very helpful to the author to improve the overall quality of the manuscript. The following are the manuscript revisions that I have edited according to the comments of the reviewer.

1. Literature review needs to improve, as a number of most recent and relevant studies have missed by authors.

 

Response:

A number of most recent and relevant studies has been updated in the introduction as follows:

Paragraph “In Vietnam, there are some studies measuring TFP and TFPG such as measuring TFP in Agriculture (Bao, 2014; Giang et al., 2019); measuring TFPG in Coal industry (Phuong, 2018); comparison TFPG among modes of transport (Quang, 2019) ... The methods used include both parametric approach (Giang et al., 2019; Quang, 2019) and nonparametric approach (Bao, 2014; Phuong, 2018).” replaced by

Previous TFP and TFPG studies in Vietnam,  have addressed various fields and have been diverse in their scope. These include measuring TFP in agriculture (Bao, 2014; Giang et al., 2019); TFPG in the coal industry (Phuong, 2018); TFP in air transport (Quang, 2017); TFPG among modes of transport (Quang, 2019); TFP in the food industry (Long, 2020), TFP in manufacturing sectors (Huong, 2017; Thanh et al., 2020); TPF for foreign direct investment enterprises (Hien et al., 2019) and for state ownership (Canh et al., 2021). In addition, there are a number of studies examining factors affecting TPF, such as: The impact of the investment climate on TFP in the agricultural sector (Trung & Cuong, 2011); the impact of investment climate on the TFP of manufacturing firms (Giang, 2018); the impact of innovation on the TFP of small and medium sized enterprises (Hue et al., 2019); the determinants of TFP in manufacturing industry (Oanh, 2019).

These studies are mainly focused on specific industries or specific ownership sectors. The methods used include both the parametric approach (Trung & Cuong, 2011; Quang, 2017; Giang et al., 2018; Giang et al., 2019; Quang, 2019; Oanh, 2019; Canh et al., 2021) and non-parametric approach (Coelli & Rao, 2005; Kong & Tongzon, 2006; Wu, 2011; Bao, 2014; Phuong, 2018). In addition, some recent studies also utilized a semi-parametric approach (Huong, 2017; Thanh & Van, 2020). Most of the parametric and non-parametric approaches use the Ordinary Least Square (OLS) regression technique to estimate the parameters for the TFPG calculation or are based on OLS such as robust regression (Bao, 2014), Fixed Effect Models (FEM) and Random Effects Model (REM) for panel data (Giang et al., 2019; Canh et al., 2021). The semi-parametric approach uses the estimation technique of Olley and Pakes (1996) (Giang et al., 2018) or the procedure of Ackerberg et al. (2006) (Thanh & Quang, 2020). These approaches are discussed in Section 2”

 

Literature review has been improved as follows:

The paragraph “For the none-frontier approach, the parameter technique estimated by the Cobb - Douglas translog function is commonly used for model specification (Tan and Virabhak, 1998; Felipe, 1999; Giang et al., 2019; Quang, 2019).” expanded to

“For the non-frontier approach, the parameter technique estimated by adapting production functions is also commonly applied. There are two common ways to obtain TFP based on firm-level production functions: Cobb-Douglas production functional form, and a translog production function. It is argued that both approaches have good mathematical properties. However, according to Giang et al (2018), the elasticity of the production to the inputs in the Cobb–Douglas function allows for easier interpretation than the trans logarithmic production. To be more specific, the translog technique generally suffers from a collinearity problem among the regressors (Kinda et al., 2011)

When measuring TFP for firms across broad industries or sectors, a simple production function consisting of two inputs, capital and labor, and an output factor of value-added, is often used because these are factors that most generally reflect inputs and outputs (Tan & Virabhak, 1998; Felipe, 1999; Giang et al., 2018; Giang et al., 2019; Oanh, 2019; Thanh & Quang, 2020; Canh et al., 2019; Giang et al., 2019; Oanh, 2019; Thanh & Quang, 2020; Canh et al. al., 2019). When measured within specific industries or firms, inputs can be extended beyond capital and labor (Bao, 2014; Thanh et al., 2020; Canh et al., 2021), or outputs can be measured by the number of products (Quang, 2019)”

 

In addition, the Literature review also added the following paragraph

“To overcome the problem of endogeneity between inputs and unobserved productivity, Olley and Pakes (1996) proposed a semi-parametric approach which was later extended by Levinsohn Petrin (2003) and Wooldridge (2009). The robustness to measurement errors is also an advantage of the semi-parametric method (Van Biesebroeck, 2004). This approach is often used to estimate unobserved productivity at the firm level and has been applied to the measurement of manufacturing firms in Vietnam (Huong, 2017; Thanh & Quang, 2020).

Although there are many different approaches, they can be summarized into three main methods: 1) the non-parametric approach using DEA; 2) the parameter approach using the production function (Cobb-Douglas production and the transformed production function); 3) the semi-parametric approach estimating Cobb-Douglas production functional form specified by the methodology of Levinsohn and Petrin (2003). Non-parametric approaches have the benefit of not assuming a specific functional form/shape for the frontier. However they do not provide a general relationship (equation) regarding outputs and inputs to enter as parametric or semi-parametric approaches. The frequent techniques to estimate the production function include OLS estimation, the Olley and Pakes method, and the Levinsohn and Petrin approach”

 

2. There is a need for critical discussion with proper citations on estimated results.

 Response:

Discussion has been improved and separated into section 4.4, which critical discussion with proper citations on estimated results as follows:

 “… These results are consistent with some recent studies demonstrating that foreign direct investment enterprises in Vietnam have an expanding role in TFP (Hien et al., 2019); and negative TFP growth of state-owned enterprises in China (Ozyurt, 2009). The results also support the outcome of the study by Canh et al. (2021), which argues that state ownership is negatively associated with TFP. The decline in TFPG is because enterprises in the state-owned sector remain inefficient and have fewer incentives to change and change senior management. In addition, the study by Canh et al. (2021) also shows that corruption control hinders TFP. It must also be seen that in the last three decades, state-owned enterprises have been reformed, in which many privileges of the state-owned enterprises have been removed, and the least efficient state-owned enterprises have been merged or equitized. However, the results of this study cast doubt about the effectiveness of state-own enterprise reform measures in Vietnam

The relatively stable TFPG of the non-state enterprise sector in the period 2009-2018 found in this study is evidence that lends support to the view that the private sector is increasingly effective and plays an important role in the economic development of Vietnam. One of the reasons for this result was studied by Canh et al. (2021). They indicated that transparency promotes the TFP of private enterprises more than that of state-owned enterprises. In addition, in Vietnam, small and medium-sized enterprises are mainly in the non-state sector (in the period 2005-2018, the non-state enterprise sector accounted for 96.41% of the number of enterprises but only 59.13% of the labor and 50.83% of the capital). Hence, the TFPG of the non-state sector partly reflects the efficiency of small and medium-sized enterprises; and the TFPG of the non-state sector found in this study is also consistent with the research results of Hue et al. (2019), which indicated that innovation has a positive impact on the TFP of small and medium-sized enterprises in Vietnam.

TFPG differences between regions of any country are obvious, but this study has shown specific differences between six regions in Vietnam by analyzing data up to 2018. It is believed that no previous studies have conducted this type of analysis

… This trend is especially marked in the Central Highlands, where workers are moving away to find employment in other regions. Despite efforts to combat the outward labor migration and increased agricultural employment, negative growth persists. The reason for this phenomenon is that most of the provinces in this region are slow to develop, poor transportation infrastructure, have few industrial zones, and the pace of industrialization and urbanization is quite slow. These findings, therefore, illustrate the unbalanced development of TFP among the regions of Vietnam….”

 

3. The conclusions session can be improved.

 

Response:

The conclusion is extended by clarifying the implications for business and literature, and adding the limitations of the study at the end of section 5 as follows:

“…These findings demonstrate the weakness of the state-owned enterprise sector and the increasing efficiency of the non-state enterprise sector as well as the foreign direct investment enterprise sector. The unbalanced development of TFPG among regions found in this study is indicative of the growing economic gap among regions. This is a scenario not usually expected internationally but for Vietnam is a case in point.

The results of this study imply that the government should continue to push ahead with reforms to improve the efficiency of state-owned enterprises. Although the state-owned sector accounts for only 0.84% of enterprises, they provide 14.01% of labor and 31.33% of capital in acting enterprises. Therefore, they still play an important role in maintaining the state-owned sector and remain absolutely necessary. However, the state only needs to hold key areas to ensure social cohesion that other sectors do not want to participate in, such as reducing state ownership and loosening administrative controls. In addition, the state continues to create mechanisms to promote the non-state enterprise sector and foreign direct investment enterprise sector, creating a level playing field for all types of enterprises. In order to reduce the economic gap between regions, the state also needs to have policies to support underdeveloped enterprise areas, declining TFPG, especially in the Central Highlands, such as infrastructure development, policies to support capital and training, and so on. This helps these regions create advantageous conditions for production and business, innovation management, and technology to improve TFP. On their side, enterprises need to focus on increasing capital for growth and development, especially innovating and improving technology and management methods to promote TFPG. Capital increases will be more favorable than labor growth because, from a social perspective, the ability to increase labor will be limited. However, innovation in technology, management to increase TFP is the key issue to improve the efficiency of enterprises…

Although this study has obtained some valuable results, there still exist some limitations. Firstly, due to data limitations, this study only explores TFPG from a macro perspective, such as among sectors and regions, without analyzing the internal performance of each specific industry. Secondly, due to the macro perspective, this study only considers two inputs when studying each specific industry, so the input factors need to be supplemented accordingly. Nevertheless, these issues may provide opportunities for further study”.

 

Thank you very much for the interest and helpful comments

 

Reviewer 3 Report

I find this paper to be interesting. Sill, it has a lot of errors that have to be fixed:

Major:

(i) Literature review does not summarise what we already know. Indeed, it just briefly explain the main estimation techniques of TFP and its growth.

(ii) The adopted model is very simple and abstract, and there is no provided evidence that it is still used in the research.

(iii) It is not clear whether the sample represents the population? It is not clear how the sample was formed.

(iv) Language needs a deep revision in terms of grammar, style, etc.

(v) No robustness check is performed.

 

Minor:

(i) Table 1 does not summarize the differences between two approaches for TFP estimation.

(ii) Check the equations. The position of the multiplication sign is wrong.

(iii) The presentation of the equations and their explanation, etc., are awkward.

(iv) Tables 4-5 could be moved to the annexes.

(v) Table 6. It is not clear what parameter is presented there.

(vi) Table 7 could be transposed and merged.

 

Author Response

The author thanks the reviewer for the comments that are very helpful to the author to improve the overall quality of the manuscript. The following are the manuscript revisions that I have edited according to the comments of the reviewer.

 

1. Major:

(i) Literature review does not summarise what we already know. Indeed, it just briefly explain the main estimation techniques of TFP and its growth.

 

Response:

Literature review is improved and expanded as follows:

The paragraph “For the none-frontier approach, the parameter technique estimated by the Cobb - Douglas translog function is commonly used for model specification (Tan and Virabhak, 1998; Felipe, 1999; Giang et al., 2019; Quang, 2019).” expanded to:

“For the non-frontier approach, the parameter technique estimated by adapting production functions is also commonly applied. There are two common ways to obtain TFP based on firm-level production functions: Cobb-Douglas production functional form, and a translog production function. It is argued that both approaches have good mathematical properties. However, according to Giang et al (2018), the elasticity of the production to the inputs in the Cobb–Douglas function allows for easier interpretation than the trans logarithmic production. To be more specific, the translog technique generally suffers from a collinearity problem among the regressors (Kinda et al., 2011)

When measuring TFP for firms across broad industries or sectors, a simple production function consisting of two inputs, capital and labor, and an output factor of value-added, is often used because these are factors that most generally reflect inputs and outputs (Tan & Virabhak, 1998; Felipe, 1999; Giang et al., 2018; Giang et al., 2019; Oanh, 2019; Thanh & Quang, 2020; Canh et al., 2019; Giang et al., 2019; Oanh, 2019; Thanh & Quang, 2020; Canh et al. al., 2019). When measured within specific industries or firms, inputs can be extended beyond capital and labor (Bao, 2014; Thanh et al., 2020; Canh et al., 2021), or outputs can be measured by the number of products (Quang, 2019)”

 

In addition, the Literature review also added the following paragraph:

“To overcome the problem of endogeneity between inputs and unobserved productivity, Olley and Pakes (1996) proposed a semi-parametric approach which was later extended by Levinsohn Petrin (2003) and Wooldridge (2009). The robustness to measurement errors is also an advantage of the semi-parametric method (Van Biesebroeck, 2004). This approach is often used to estimate unobserved productivity at the firm level and has been applied to the measurement of manufacturing firms in Vietnam (Huong, 2017; Thanh & Quang, 2020).

Although there are many different approaches, they can be summarized into three main methods: 1) the non-parametric approach using DEA; 2) the parameter approach using the production function (Cobb-Douglas production and the transformed production function); 3) the semi-parametric approach estimating Cobb-Douglas production functional form specified by the methodology of Levinsohn and Petrin (2003). Non-parametric approaches have the benefit of not assuming a specific functional form/shape for the frontier. However they do not provide a general relationship (equation) regarding outputs and inputs to enter as parametric or semi-parametric approaches. The frequent techniques to estimate the production function include OLS estimation, the Olley and Pakes method, and the Levinsohn and Petrin approach”

 

(ii) The adopted model is very simple and abstract, and there is no provided evidence that it is still used in the research.

 

Response:

The edited version is added discussion the TFP and TFPG measurement models in the Literature review above, and explain the reasons for choosing the estimation model as follows:

Paragraph “Appropriate to the data source, this study measures TFPG by parametric estimation via the Cobb – Douglas production function in non-frontier approach. The general Cobb-Douglas production function follows Equation (1)" is developed and added to:

"As it was appropriate to the data source being collected, this study used the parameter approach and Cobb-Douglas production function estimation to determine TFPG because it provides an equational relationship regarding outputs and inputs, as discussed above. The elasticity of the inputs in the Cobb-Douglas function allows for easier interpretation than the production translog function and is still in common use (Giang et al., 2018; Giang et al., 2019; Oanh, 2019; Canh et al., 2019; Thanh & Quang, 2020; Thanh et al., 2020; Canh et al., 2021). As this study uses estimates for enterprise sectors and enterprise in regions, the enterprises examined do not belong to a specific industry, and the most common factors that reflect inputs are capital and labor. Hence, a Cobb–Douglas production function with two inputs is used in this study, as has been the case with other recent studies (Giang et al., 2018; Giang et al., 2019; Oanh, 2019; Thanh & Quang, 2020). The simple Cobb-Douglas production function follows Equation (1)."

 

(iii) It is not clear whether the sample represents the population? It is not clear how the sample was formed.

 

Response:

The sample is taken from the statistics of the General Statistics Office of Vietnam for all active enterprises as of December 31 of each year. The edited revision further clarified this in section 3.3 and added the number of enterprise-years for each enterprise sector and region in table 2; adding sample introduction after table 2 as follow:

“As can be seen from the sample in Table 2, the non-state sector accounted for the majority (more than 96%) of the enterprise sector. The bulk of enterprises located in two areas, the Southeast and the Red River Delta, which contain the two most extensive economic centers in Vietnam, Ho Chi Minh City and Hanoi”.

 

(iv) Language needs a deep revision in terms of grammar, style, etc.

 

Response:

The revision has been improved terms of grammar, style by a language editing expert. Please see the revised version

 

(v) No robustness check is performed.

 

Response:

The revision has added robustness check by comparing with the estimated results using Fix effect models (FEM) and Random effects model (REM). The results are added at the end of section 4.2 as follows:

“The robustness check is performed by comparing the estimated results of the FMOLS and OLS methods. Accordingly, the OLS method is applied to the FE and RE models, with the appropriate model being selected by the Hausman Test (Correlated Random Effects). The estimated results produced by the OLS method are detailed in the Appendix. Table 5 below shows the estimated coefficient of capital per labor in the models where the FMOLS and OLS methods were applied. According to Table 5, the two methods produce similar estimated results, especially in the non-state enterprise sector, the foreign investment enterprise sector, the Red River Delta region, and the Southeast region (all lower than 3%). Only the Central Highlands region has a relatively significant difference (nearly 25%). Despite certain differences, it is believed that the results from the FMOLS method are more appropriate because the series are cointegrated in each model.”

 

2. Minor:

(i) Table 1 does not summarize the differences between two approaches for TFP estimation.

 

Response:

The revision added discussion to clarify the differences between two approaches for TFP estimation. The content is presented after Table 1 as follows:

“… adapting production functions is also commonly applied. There are two common ways to obtain TFP based on firm-level production functions: Cobb-Douglas production functional form, and a translog production function. It is argued that both approaches have good mathematical properties. However, according to Giang et al (2018), the elasticity of the production to the inputs in the Cobb–Douglas function allows for easier interpretation than the trans logarithmic production. To be more specific, the translog technique generally suffers from a collinearity problem among the regressors (Kinda et al., 2011)

When measuring TFP for firms across broad industries or sectors, a simple production function consisting of two inputs, capital and labor, and an output factor of value-added, is often used because these are factors that most generally reflect inputs and outputs (Tan & Virabhak, 1998; Felipe, 1999; Giang et al., 2018; Giang et al., 2019; Oanh, 2019; Thanh & Quang, 2020; Canh et al., 2019; Giang et al., 2019; Oanh, 2019; Thanh & Quang, 2020; Canh et al. al., 2019). When measured within specific industries or firms, inputs can be extended beyond capital and labor (Bao, 2014; Thanh et al., 2020; Canh et al., 2021), or outputs can be measured by the number of products (Quang, 2019)

To overcome the problem of endogeneity between inputs and unobserved productivity, Olley and Pakes (1996) proposed a semi-parametric approach which was later extended by Levinsohn Petrin (2003) and Wooldridge (2009). The robustness to measurement errors is also an advantage of the semi-parametric method (Van Biesebroeck, 2004). This approach is often used to estimate unobserved productivity at the firm level and has been applied to the measurement of manufacturing firms in Vietnam (Huong, 2017; Thanh & Quang, 2020).

Although there are many different approaches, they can be summarized into three main methods: 1) the non-parametric approach using DEA; 2) the parameter approach using the production function (Cobb-Douglas production and the transformed production function); 3) the semi-parametric approach estimating Cobb-Douglas production functional form specified by the methodology of Levinsohn and Petrin (2003). Non-parametric approaches have the benefit of not assuming a specific functional form/shape for the frontier. However they do not provide a general relationship (equation) regarding outputs and inputs to enter as parametric or semi-parametric approaches. The frequent techniques to estimate the production function include OLS estimation, the Olley and Pakes method, and the Levinsohn and Petrin approach.”

 

(ii) Check the equations. The position of the multiplication sign is wrong.

 

Response:

The revision edited these errors

 

(iii) The presentation of the equations and their explanation, etc., are awkward.

 

Response:

Author used subscripts of the equations associated with the names of enterprise sectors and regions; explain more formulas. In addition, the revision added the following steps at the end of section 3.1:

“Determining TFPG involves two steps. Step 1: Estimate the contribution coefficients of capital (α) and labor (β) in the Cobb–Douglas production function for each enterprise sector and region by Equation (5). Step 2: Calculate TFPG for each enterprise sector and region in each period by Equation (2)… “

 

(iv) Tables 4-5 could be moved to the annexes.

 

Response:

Tables 4-5 has been moved to annexes in revision

 

(v) Table 6. It is not clear what parameter is presented there.

 

Response:

The table title is changed to “Results of the estimated coefficients of capital”, with the addition of the note: Coefficient is estimates the contribution of capital (α) in Equation (5)

 

(vi) Table 7 could be transposed and merged.

 

Response:

The Tables 7 have been merged into a single table in the revision table

 

 

Thank you very much for the interest and helpful comments

 

Reviewer 4 Report

The aim of the study is to identify and compare total factor productivity growth (TFPG)  among enterprise sectors as well as enterprises in regions of Vietnam. Using a panel data analysis in the period 2005-2018, the author/s find that the growth of Vietnamese enterprises is mainly due to the increase in capital, especially the non-state enterprise sector and the Red River Delta.

Overall, this paper takes into account an interesting topic and the premises were very high, but there are some points need to be addressed and clarified in a better way. In particular, I believe that the paper has a too technical structure, where a little importance is given to the motivation of the contribution and to the interpretation of empirical results, above all in terms of policy implications. However, some points are raised, hoping they can be used to improve the paper.

Major comments

Introduction and Contribution

• The author/s should give more motivation for the contribution of the paper and how their study can reduce the gap with recent literature. How can this work fit into the TFPG literature?
• I would recommend to the author/s to motivate the use of the context in which the analysis is performed. Moreover, a specific section about the context could help to better understand the phenomenon under scrutiny. In other words, what drives the author/s to use the context of Vietnam and the period 2005-2018?
• I would suggest to the authors to insert the hypotheses to be tested and to insert the theoretical part with greater relevance.

Method and Results

• Why did the author/s use the Battese method instead of a non-parametric method for calculating TFPG? More clarifications is needed. Moreover, I believe that it would be necessary to compare the results considering the non-parametric method for the calculation of the total factor productivity growth (TFPG)
• The author/s claim to use data from 2005 to 2018, but then the TFPG calculation is done starting from 2009. Also it is not clear to me why the author/s calculate the changes only considering 09-13, 14-18, 09-18. More clarifications are needed.

Conclusions

• The conclusions are inadequate due to the importance of the link analyzed. Furthermore, I find that there is a lacks of appropriate policy implications that could explain what the results achieved are for, despite the initial premise the author/s say that this work gives interesting food for thought.
• I also think it would be interesting provide examples and suggestions based on your results, especially in term of policy implications.

Minor comments

• Discussion of the results and conclusions are very poor due to the importance of the nexus under scrutiny.
• I would recommend the author/s a moderate editing of English language and style. In fact, several typos can be found throughout the paper.
• Tables 5 and 7 are confusing and difficult to read. I would recommend author/s to format them properly. The same goes for the other tables.

Author Response

The author thanks the reviewer for the comments that are very helpful to the author to improve the overall quality of the manuscript. The following are the manuscript revisions that I have edited according to the comments of the reviewer.

 

1. Major comments

 

(i) Introduction and Contribution

The author/s should give more motivation for the contribution of the paper and how their study can reduce the gap with recent literature. How can this work fit into the TFPG literature?

I would recommend to the author/s to motivate the use of the context in which the analysis is performed. Moreover, a specific section about the context could help to better understand the phenomenon under scrutiny. In other words, what drives the author/s to use the context of Vietnam and the period 2005-2018?

I would suggest to the authors to insert the hypotheses to be tested and to insert the theoretical part with greater relevance.

 

Response:

The author has added some relevance in the introduction as follows

Paragraph “In Vietnam, there are some studies measuring TFP and TFPG such as measuring TFP in Agriculture (Bao, 2014; Giang et al., 2019); measuring TFPG in Coal industry (Phuong, 2018); comparison TFPG among modes of transport (Quang, 2019) ... The methods used include both parametric approach (Giang et al., 2019; Quang, 2019) and nonparametric approach (Bao, 2014; Phuong, 2018).” is replaced by:

“Previous TFP and TFPG studies in Vietnam,  have addressed various fields and have been diverse in their scope. These include measuring TFP in agriculture (Bao, 2014; Giang et al., 2019); TFPG in the coal industry (Phuong, 2018); TFP in air transport (Quang, 2017); TFPG among modes of transport (Quang, 2019); TFP in the food industry (Long, 2020), TFP in manufacturing sectors (Huong, 2017; Thanh et al., 2020); TPF for foreign direct investment enterprises (Hien et al., 2019) and for state ownership (Canh et al., 2021). In addition, there are a number of studies examining factors affecting TPF, such as: The impact of the investment climate on TFP in the agricultural sector (Trung & Cuong, 2011); the impact of investment climate on the TFP of manufacturing firms (Giang, 2018); the impact of innovation on the TFP of small and medium sized enterprises (Hue et al., 2019); the determinants of TFP in manufacturing industry (Oanh, 2019).

 

These studies are mainly focused on specific industries or specific ownership sectors. The methods used include both the parametric approach (Trung & Cuong, 2011; Quang, 2017; Giang et al., 2018; Giang et al., 2019; Quang, 2019; Oanh, 2019; Canh et al., 2021) and non-parametric approach (Coelli & Rao, 2005; Kong & Tongzon, 2006; Wu, 2011; Bao, 2014; Phuong, 2018). In addition, some recent studies also utilized a semi-parametric approach (Huong, 2017; Thanh & Van, 2020). Most of the parametric and non-parametric approaches use the Ordinary Least Square (OLS) regression technique to estimate the parameters for the TFPG calculation or are based on OLS such as robust regression (Bao, 2014), Fixed Effect Models (FEM) and Random Effects Model (REM) for panel data (Giang et al., 2019; Canh et al., 2021). The semi-parametric approach uses the estimation technique of Olley and Pakes (1996) (Giang et al., 2018) or the procedure of Ackerberg et al. (2006) (Thanh & Quang, 2020). These approaches are discussed in Section 2.”

 

The motivation to use the context of Vietnam and the period 2005-2018 has been further clarified in the introduction:

“Vietnam is located in Southeast Asia and is a developing country. TFP, therefore, plays a key role in the development process to narrow the economic gap with other countries. Consequently, enterprises have a particularly important role to play in the economy….”

 

The reason for choosing the period 2005-2018 has been further clarified in section 3.3 Research Data as follows: “The years examined  are 2005 and the years in the period 2008-2018. These years were selected as these are the only years for which the GSO of Vietnam has a full range of official data. The statistical data relates to all active enterprises as of December 31 of each year”

 

(ii) Method and Results

Why did the author/s use the Battese method instead of a non-parametric method for calculating TFPG? More clarifications is needed. Moreover, I believe that it would be necessary to compare the results considering the non-parametric method for the calculation of the total factor productivity growth (TFPG)

 

Response:

The author added the discussion of approaches to measuring TFP at the end of section 2 and the reasons for choosing the method in section 3.1 as follows:

Added the discussion of approaches to measuring TFP at the end of section 2: Although there are many different approaches, they can be summarized into three main methods: 1) the non-parametric approach using DEA; 2) the parameter approach using the production function (Cobb-Douglas production and the transformed production function); 3) the semi-parametric approach estimating Cobb-Douglas production functional form specified by the methodology of Levinsohn and Petrin (2003). Non-parametric approaches have the benefit of not assuming a specific functional form/shape for the frontier. However they do not provide a general relationship (equation) regarding outputs and inputs to enter as parametric or semi-parametric approaches. The frequent techniques to estimate the production function include OLS estimation, the Olley and Pakes method, and the Levinsohn and Petrin approach

 

Replace paragraph: “Appropriate to the data source, this study measures TFPG by parametric estimation via the Cobb – Douglas production function in non-frontier approach. The general Cobb-Douglas production function follows Equation (1)" by paragraph:

As it was appropriate to the data source being collected, this study used the parameter approach and Cobb-Douglas production function estimation to determine TFPG because it provides an equational relationship regarding outputs and inputs, as discussed above. The elasticity of the inputs in the Cobb-Douglas function allows for easier interpretation than the production translog function and is still in common use (Giang et al., 2018; Giang et al., 2019; Oanh, 2019; Canh et al., 2019; Thanh & Quang, 2020; Thanh et al., 2020; Canh et al., 2021). As this study uses estimates for enterprise sectors and enterprise in regions, the enterprises examined do not belong to a specific industry, and the most common factors that reflect inputs are capital and labor. Hence, a Cobb–Douglas production function with two inputs is used in this study, as has been the case with other recent studies (Giang et al., 2018; Giang et al., 2019; Oanh, 2019; Thanh & Quang, 2020). The simple Cobb-Douglas production function follows Equation (1).

 

The author/s claim to use data from 2005 to 2018, but then the TFPG calculation is done starting from 2009. Also it is not clear to me why the author/s calculate the changes only considering 09-13, 14-18, 09-18. More clarifications are needed.

 

Response:

The author further clarified this paragraph and added at the end of section 3.1 as follows: “…Although the data collected to estimate the parameters in Step 1 is from 2005-2018, when calculating TFPG in Step 2, it was applied only to the last five or ten years for homogeneity of comparison. The specific five-year periods were 2009-2013 and 2014-2018, and for the 10 year period 2009-2018 was used”

 

(iii) Conclusions

The conclusions are inadequate due to the importance of the link analyzed. Furthermore, I find that there is a lacks of appropriate policy implications that could explain what the results achieved are for, despite the initial premise the author/s say that this work gives interesting food for thought.

I also think it would be interesting provide examples and suggestions based on your results, especially in term of policy implications.

 

Response:

The revision has added a deeper conclusion and provides examples and suggestions based on your results, especially in term of policy implications as follows

“…These findings demonstrate the weakness of the state-owned enterprise sector and the increasing efficiency of the non-state enterprise sector as well as the foreign direct investment enterprise sector. The unbalanced development of TFPG among regions found in this study is indicative of the growing economic gap among regions. This is a scenario not usually expected internationally but for Vietnam is a case in point.

The results of this study imply that the government should continue to push ahead with reforms to improve the efficiency of state-owned enterprises. Although the state-owned sector accounts for only 0.84% of enterprises, they provide 14.01% of labor and 31.33% of capital in acting enterprises. Therefore, they still play an important role in maintaining the state-owned sector and remain absolutely necessary. However, the state only needs to hold key areas to ensure social cohesion that other sectors do not want to participate in, such as reducing state ownership and loosening administrative controls. In addition, the state continues to create mechanisms to promote the non-state enterprise sector and foreign direct investment enterprise sector, creating a level playing field for all types of enterprises. In order to reduce the economic gap between regions, the state also needs to have policies to support underdeveloped enterprise areas, declining TFPG, especially in the Central Highlands, such as infrastructure development, policies to support capital and training, and so on. This helps these regions create advantageous conditions for production and business, innovation management, and technology to improve TFP. On their side, enterprises need to focus on increasing capital for growth and development, especially innovating and improving technology and management methods to promote TFPG. Capital increases will be more favorable than labor growth because, from a social perspective, the ability to increase labor will be limited. However, innovation in technology, management to increase TFP is the key issue to improve the efficiency of enterprises.

….

Although this study has obtained some valuable results, there still exist some limitations. Firstly, due to data limitations, this study only explores TFPG from a macro perspective, such as among sectors and regions, without analyzing the internal performance of each specific industry. Secondly, due to the macro perspective, this study only considers two inputs when studying each specific industry, so the input factors need to be supplemented accordingly. Nevertheless, these issues may provide opportunities for further study”

 

 

2. Minor comments

(i) Discussion of the results and conclusions are very poor due to the importance of the nexus under scrutiny.

 

Response:

Discussion has been clarified and added to section 4.4 with the following paragraphs

“….These results are consistent with some recent studies demonstrating that foreign direct investment enterprises in Vietnam have an expanding role in TFP (Hien et al., 2019); and negative TFP growth of state-owned enterprises in China (Ozyurt, 2009). The results also support the outcome of the study by Canh et al. (2021), which argues that state ownership is negatively associated with TFP. The decline in TFPG is because enterprises in the state-owned sector remain inefficient and have fewer incentives to change and change senior management. In addition, the study by Canh et al. (2021) also shows that corruption control hinders TFP. It must also be seen that in the last three decades, state-owned enterprises have been reformed, in which many privileges of the state-owned enterprises have been removed, and the least efficient state-owned enterprises have been merged or equitized. However, the results of this study cast doubt about the effectiveness of state-own enterprise reform measures in Vietnam.

The relatively stable TFPG of the non-state enterprise sector in the period 2009-2018 found in this study is evidence that lends support to the view that the private sector is increasingly effective and plays an important role in the economic development of Vietnam. One of the reasons for this result was studied by Canh et al. (2021). They indicated that transparency promotes the TFP of private enterprises more than that of state-owned enterprises. In addition, in Vietnam, small and medium-sized enterprises are mainly in the non-state sector (in the period 2005-2018, the non-state enterprise sector accounted for 96.41% of the number of enterprises but only 59.13% of the labor and 50.83% of the capital). Hence, the TFPG of the non-state sector partly reflects the efficiency of small and medium-sized enterprises; and the TFPG of the non-state sector found in this study is also consistent with the research results of Hue et al. (2019), which indicated that innovation has a positive impact on the TFP of small and medium-sized enterprises in Vietnam.

… This trend is especially marked in the Central Highlands, where workers are moving away to find employment in other regions. Despite efforts to combat the outward labor migration and increased agricultural employment, negative growth persists. The reason for this phenomenon is that most of the provinces in this region are slow to develop, poor transportation infrastructure, have few industrial zones, and the pace of industrialization and urbanization is quite slow. These findings, therefore, illustrate the unbalanced development of TFP among the regions of Vietnam”

 

(ii) I would recommend the author/s a moderate editing of English language and style. In fact, several typos can be found throughout the paper.

 

Response:

The revision has been improved terms of grammar, style by a language editing expert. Please see the revised version

 

(iii) Tables 5 and 7 are confusing and difficult to read. I would recommend author/s to format them properly. The same goes for the other tables.

 

Response:

Tables 5 have been moved to the appendix and tables 7 have been merged into a single table

 

 

 

Thank you very much for the interest and helpful comments

 

Round 2

Reviewer 1 Report

I accept the article in the current version. 

Author Response

Reviewer's comment

I accept the article in the current version

I don't feel qualified to judge about the English language and style

 

Response to Reviewer 1 Comments

The manuscript has been edited language by a native English-speaking colleague. Please see the revision attached which is marked up using the “Track Changes” function.

Reviewer 3 Report

I find that paper addresses majority of my previous concerns and thus could be considered for the publication. Still, problems with English persist:

The aim of this study is to find imbalance between TFPG and in enterprises growth pattern of sectors and regions in Vietnam.

Total factor productivity (TFP) was enjoyed by the non-state and inward foreign investment sectors during the five years, 2014-2018.

In contrast, there was a downward trend in, the Central Highlands and the Red River Delta, which was especially marked in the Central Highlands.

And so on and so on…

Author Response

Reviewer's comment

I find that paper addresses majority of my previous concerns and thus could be considered for the publication. Still, problems with English persist:

The aim of this study is to find imbalance between TFPG and in enterprises growth pattern of sectors and regions in Vietnam.

Total factor productivity (TFP) was enjoyed by the non-state and inward foreign investment sectors during the five years, 2014-2018.

In contrast, there was a downward trend in, the Central Highlands and the Red River Delta, which was especially marked in the Central Highlands.

And so on and so on…

Extensive editing of English language and style required

 

Response to Reviewer 1 Comments

The manuscript has been edited language by a native English-speaking colleague. Please see the revision attached which is marked up using the “Track Changes” function.

Reviewer 4 Report

The author/s responded adequately to the comments.

Author Response

Reviewer's comment

The author/s responded adequately to the comments

English language and style are fine/minor spell check required

 

Response to Reviewer 1 Comments

The manuscript has been edited language by a native English-speaking colleague. Please see the revision attached which is marked up using the “Track Changes” function.