Innovation and productivity in small and medium enterprises, a case study of vietnam

UNIVERSITY OF ECONOMICS

INSTITUTE OF SOCIAL STUDIES

HO CHI MINH CITY

THE HAGUE

VIETNAM

THE NETHERLANDS

VIETNAM – THE NETHERLANDS
PROGRAMME FOR M.A IN DEVELOPMENT ECONOMICS

INNOVATION AND PRODUCTIVITY IN
SMALL AND MEDIUM ENTERPRISES:
A CASE STUDY OF VIETNAM

By
PHAM DO TUONG VY

MASTER OF ART IN DEVELOPMENT ECONOMICS

HCMC, NOVEMBER 2016


University of Economics

International Institute of Social Study

Ho Chi Minh City

The Hague

Vietnam

The Netherlands

VIETNAM – THE NETHERLANDS
PROGRAMME FOR M.A IN DEVELOPMENT ECONOMICS

INNOVATION AND PRODUCTIVITY IN
SMALL AND MEDIUM ENTERPRISES:
A CASE STUDY OF VIETNAM

by Pham Do Tuong Vy
A Thesis Submitted in Partial Fulfilment of the Requirements for
the Degree of

Master of Art in
Development Economics

Academic Supervisor: Dr. Vo Hong Duc

HCMC, NOVEMBER 2016


DECLARATION
I hereby declare that this thesis entitled “Innovation and Productivity in
Small and Medium sized Enterprises: A case study of Vietnam”, which is written

and submitted by me in accordance with the requirement for the degree of Master of
Art in Development Economics to the Vietnam – The Netherlands Programme. This
is my original work and all sources of knowledge carried in this thesis have been duly
acknowledged.
HCMC, November 2016

PHẠM ĐỖ TƯỜNG VY


ACKNOWLEDGEMENT

I would like to take this opportunity to express my deepest gratitude for the
help, support and encouragement of the following people, who have contributed to
the completion of this thesis in their very own ways.
Above all, I would like to express my immeasurable appreciation to my
supervisor – Dr. Võ Hồng Đức for his precious time, support and advices to make
this thesis completed.
Furthermore, I would like to send my great thanks to all the lecturers and staffs
at the Vietnam – The Netherlands Programme for their knowledge and supports
during my time joining in the program. In specific, I am extremely grateful to Dr.
Phạm Khánh Nam and Dr. Trương Đăng Thụy for their valuable guidance and
support in the courses and thesis writing process.
To all of my friends in Class 21 and my colleagues at TPF, I could never
thankful enough for your encouragement and support until the very end of this thesis.
Last but not least, my deepest thanks and love to my parents, who have always
been beside me. Without their unconditional love, none of this would have been
possible.


ABBREVIATION

2SLS

Two Stage Least Squares.

CDM

Crépon, Duguet and Mairesse.

FE

Fixed Effect.

GMM

Generalized Method of Moments.

GSO

General Statistic Office.

IV

Instrument Variables.

LP

Levinsohn and Petrin.

OLS

Ordinary Least Squares.

OP

Olley and Parker.

R&D

Research and Development.

SMEs

Small and Medium-sized Enterprises.

TFP

Total Factor Productivity.


ABSTRACT

The majority of enterprises in Vietnam is categorized as small and medium
sized (SMEs) firms which play an important role to the sustainable growth of the
Vietnamese economy. As such, improving the productivity of the SMEs is essentially
needed and this request becomes a crucial mission for the governments. It is generally
accepted that innovation and technology improvement are key drivers of productivity
(Bartelsman & Doms, 2000). However, they have not been well-acknowledged by
the SMEs in Vietnam even though their huge contribution to firm’s productivity is
unarguable.

This study aims to examine the relationship between innovation and
productivity in the Small and Medium-sized Enterprises (SMEs) in Vietnam. To
establish and quantify this relationship, this study employs the two-stage process: (i)
the estimation of total factor productivity for each firm; and (ii) a determination of an
innovation – productivity relationship. In the first stage, total factor productivity is
estimated based on production function using the input and output approach.
However, firms might adjust their input level according to expected productivity
shock. As such, a potential endogeneity caused by possible relationship between input
decision and productivity shocks (unobserved productivity shock) might exist. To
deal with this problem of endogeneity, an approach developed by Levinsohn and
Petrin is applied to estimate firm’s total productivity. In the second stage, the systemGMM approach is adopted to examine the relationship between innovation and
productivity.
An unbalanced panel dataset from five Small and Medium-sized Enterprises
surveys from 2005 to 2013 is used in this study. Findings from this study indicate
that, in the context of Vietnam, when innovation is measured as innovation
expenditure intensity and high-quality labor share in total firm’s labor force,
innovation activities provide positive and significant impact on firm’s productivity.
In addition, past value of firm’s productivity also has significant relationship with its
current level. This finding implies that higher (lower) level of current productivity


could lead to higher (lower) level of productivity in the future. The study also
provides empirical evidence to confirm that larger firms might perform better than
the relatively smaller firms. In contrast, capital structure provides negative impact on
firm’s productivity. However, this study fails to provide any evidence to support the
view that longevity of firm does provide significant impact on productivity of firms.

Key words:

Vietnam SMEs; Total factor productivity; Productivity Shock;

Innovation, GMM.


TABLE OF CONTENTS
CHAPTER 1 ..............................................................................................................1
INTRODUCTION .....................................................................................................1
1.1.

Problem statement .........................................................................................1

1.2.

Research objectives .......................................................................................2

1.3.

Research questions ........................................................................................2

1.4.

Research motivations .....................................................................................2

1.5.

Research scope and data ................................................................................3

1.6.

The structure of this study .............................................................................3

CHAPTER 2 ..............................................................................................................5
LITERATURE REVIEW .........................................................................................5
2.1. Schumpeter Theory of Innovation – How does Innovation play its role in
economic development? ..........................................................................................5
2.2.

Productivity: concept and measurements ......................................................7

2.1.1.

Concept ...................................................................................................7

2.1.2.

Measurements .........................................................................................7

2.1.3.

General productivity determinants .......................................................12

2.3.

Innovation: concept and measurements.......................................................16

2.1.4.

Concept .................................................................................................16

2.1.5.

Measurements .......................................................................................17

2.4. How has the relationship between innovation and firms’ performance been
analysed in the literature? ......................................................................................18
CHAPTER 3 ............................................................................................................23
RESEARCH METHODOLOGY ..........................................................................23
3.1.

An overview of Vietnamese Small and Medium-sized Enterprises ............23

3.1.1.

Statistic overview ..................................................................................23

3.1.2.

Difficulties ............................................................................................26

3.2.

Methodology ................................................................................................27

3.1.3.

Conceptual framework ..........................................................................27

3.1.4.

Model identification ..............................................................................29

3.3.

Research hypotheses and concept measurements........................................34

3.1.5.

Research hypotheses .............................................................................34

3.1.6.

Concept and variable measurements ....................................................34


3.4.

Data sources .................................................................................................36

CHAPTER 4 ............................................................................................................39
EMPIRICAL RESULTS ........................................................................................39
4.1.

Total Factor Productivity of Vietnamese SMEs ..........................................39

4.1.1.

Data descriptions...................................................................................39

4.1.2. Total factor productivity from production function estimation of
Vietnamese SMEs ..............................................................................................42
4.2.

Innovation – Firm’s productivity relationship .............................................45

4.1.3.

Data descriptions...................................................................................45

4.1.4. The relationship between innovation expenditure intensity and firm’s
productivity ........................................................................................................46
4.1.5. The relationship between high-quality labor share in total firm’s labor
force and their productivity ................................................................................49
CHAPTER 5 ............................................................................................................52
CONCLUSION AND POLICY IMPLICATION ................................................52
5.1.

Conclusion remarks .....................................................................................52

5.2.

Policy implications ......................................................................................54

5.3.

Limitation and potential future research ......................................................54

REFERENCES ........................................................................................................56
APPENDIX 1: Empirical studies on general productivity determinants ..........62
APPENDIX 2: Empirical studies on relationship between innovation and
firm’s performance .................................................................................................65
APPENDIX 3: Durbin – Wu Hausman test for endogeneity ..............................69

APPENDIX 4: Durbin – Wu Hausman test for endogeneity ..............................71


LIST OF TABLES AND FIGURES
Table 3.1:

Classification of SMEs in Vietnam

Table 3.2:

Concepts and measurements of variables used in the study

Table 3.3:

Number of observation in selected industries in dataset

Table 3.4:

Number of observation after filtering

Table 3.5:

Number of observation after filtering in stage 2

Table 4.1:

Descriptive statistics of production function variables

Table 4.2:

Comparison of OLS, Fixed Effect and LP estimators in Foods, Woods
and Rubber and Plastics

Table 4.3:

Comparison of OLS, Fixed Effect and LP estimators in Non-metallic
mineral, Fabricated metal and Furniture

Table 4.4:

Descriptive statistics of TFP and its determinants

Table 4.5:

Regression results of innovation expenditure intensity and firm’s
productivity

Table 4.6:

Regression results of high-quality labor shareity of Vietnamese
SMEs and open up new aspects of innovation – productivity relationship need
intensive research.

55


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61


APPENDIX 1: Empirical studies on general productivity determinants
References

Objectives

Data

Methodology

Key conclusions

1

Cucculelli et
al. (2014)

Data from Xth Capitalia
- UniCredit survey
conducted in Italia from
2004 to 2006.

Two-stage approach:
- Stage 1: TPF is determined using Levinsohn and
Petrin
(2003)
approach.
- Stage 2: OLS estimation: regressing TPF obtained
from stage 1 with firm age, family-managed status
and vector of other control variables (firm size,
human capital, firms listed in stock market, capital
intensity, and ownership concentration.)

- Productivity of non-family firms is higher

than family-managed firms, but the
different
is
small
(3.5%-5%).
- Firm age has positive impact on TFP of
family-managed firms.

2

De Kok et
al. (2006)

- Pioneer on analyzing
the
relationship
between
family
ownership status and
TFP in Italia context.
- Determine the impact
of firm age on TFP in
family owned firm in
Italia.
Estimate
the
relationship between
firm
age
and

productivity growth.

Data from Production
survey
for
Dutch
manufacturing industry
firms from 1994-1999

- At the first few years of operation, firm
productivity is lower than average.
- After ten years of operation, firm age have
no impact on productivity.

3

Huergo and
Jaumandreu
(2004).

Unbalanced panel data
set of over 2300 Spanish
manufacturing
firms
from 1990 to 1998.

4

Dhawan
(2001)

Examine
the
relationship between
innovation
introduction
and
productivity growth.
- If this relationship
exist, whether firm life
span matter?
Examine the effect of
firm size on the firm
productivity in US.

- Productivity is calculated using growth accounting
method.
- OLS estimation with dependent variable is
productivity growth and independent variables are
firm age and control for size, organizational
structure and sectors in manufacturing industry.
- Semiparametric regression for assumed nonlinear
relationship between age and productivity growth
which
calculated
from
Solow
residual.
- Adding innovation variable to the regression to
estimate the relationship between innovation and

productivity growth.

Data
from
COMPUSTAT database
from 1970-1989, US

- Defined productivity as median value of capital
and labor ratio.

62

- Firms at early stage enjoy high
productivity growth (at around (5%) and
this rate decreases continuously for 8 years
until equal the average productivity (about
2%)
- Additionally control for innovation
results in higher productivity growth but
then decreases after 3 years.
- Small firms pay higher interest rate than
large firms.


- OLS estimation of Cobb-Douglas production
function is regressed separately for large firms and
small firms to examine whether small firms and
large firms are different in cost of capital.
- Construct equation on productivity differential
between small and large firms.

- Productivity is estimated using Stochastic Frontier
Analysis. TFP is decomposed into three
components: (i) pure technical efficiency change,
(ii) scale efficiency change, (iii) technical change.
- Through Scale efficiency change and Technical
change, different in firm size can explain
productivity differential.

5

Tovar et al.
(2011)

Examine the effect of
firm size on the
performance
of
Brazilian Electricity
Industry.

Panel data from 17
Brazilian
electricity
distribution firms from
1998 to 2005.

6

Margaritis
and Psillaki

(2010)

Firm level panel data of
France from 2002 to
2005 in three industries:
Chemicals, Computers
and Textiles.

- Using Data Envelopment Analysis and distance
function approach to estimate firm efficiency.
- Firm leverage is measured as debt to total asset
ratio.
- Dynamic OLS estimation to identify the
relationship among firm efficiency, leverage and
ownership status, other control variables:
profitability (profit/total assets), asset structure
(fixed tangible assets/total assets), growth
opportunities (intangible assets/total assets), size.

7

Kim (2006)

Examine
the
relationship between
firm leverage and their
performance.
- Test whether firm
efficiency has any

effect on their choice
of capital structure.
- Determine the effect
of ownership on firm
capital structure and
efficiency.
Assess
the
relationship between
family
ownership

Panel data of Korean
manufacturing
firms
from 1991 to 1998

- Define Chaebols firms as family-managed, debtdependent, diverse business activities.

63

- Small firms are more productive than
large firms.

- In the period of 1998-2005, TPF growth
is at 0.9%/year, Technical change growth
rate at 4.9%/year, Pure technical efficiency
change growth rate at -3.7%/year,
unchanged at Scale efficiency change.
- Firm size is positively correlated with

TFP growth. Therefore mergers of small
electricity distribution firms could lead to
gain in productivity.
- At low level of leverage, firm's level of
efficiency has positive affect on firm
leverage.
- Firm efficiency also has relation to assets
structure, growth opportunities, size,
profitability, ownership status.

- Family ownership concentration has
significant positive impact on firm
productivity, but at decreasing rate.


statuses,
capital
structure on firm
productivity.

- Productivity is measured as TFP using multilateral
index approach.
- Pooled OLS estimation between TFP and family
ownership concentration, capital structure and other
control variables.

8

Aw, Roberts
and Winston

(2007)

Analyze
firm
behavior in entering
export
market,
investing in R&D and
investing in improving
labor force quality.
- Assess the impact of
these above activities
on firm productivity.

Panel data of Taiwanese
firms in electronic
industry in 1986, 1991
and 1996

- Applied standard bivariate probit model to analyze
firm decision on participate export market and
invest in R&D/worker training. The explanatory
variables: firm age, capital stock, wages,
productivity (calculated using OP approach),
interaction terms, etc.
- Using maximum likelihood estimate to identify
the determinants of firm decision to survive.
- Using maximum likelihood estimate to determine
the marginal contribution of investment in
R&D/worker training on future productivity.

9

Keller and
Yeaple
(2009)

Examine the effect of
FDI and international
trade on productivity
growth in US

COMPUSTAT
panel
data of 1,277 US firms
from 1987 to 1996.

- Firm productivity is determined using Olley and
Pakes (1996) method.
- FDI activities is represented by the share of MNE
affiliate industry employment.
- OLS estimation for the relationship between
productivity growth and FDI and international trade

64

- Significant negative effect of debt ratio on
productivity.
- Family ownership concentration affect
productivity in Chaebols much stronger

than non-Chaebols firms.
- Debt ratio has positive impact on
Chaebols firms’ productivity.
- Firms with higher productivity are more
likely to involve in export. However this
effect is not significant with choice to
invest in R&D/worker training.
- Key determinants of firm's survival are
entrant status and capital stock.
- Current productivity level does affect
future productivity. Investment in
R&D/worker
training
and
export
experience have significant positive
relationship with firm productivity, and the
relationship between these two factors are
complement.
- FDI activities have significant positive
impact on TPF growth (account for 11%
TFP growth). The relationship is then
robust.
- Import do affect TFP growth with the
same direction, but weaker than FDI. In
addition, there is no evidence on robust
result on import and TFP growth.


APPENDIX 2: Empirical studies on relationship between innovation and firm’s performance

Reference

Data

Output
measurement

Innovation
measurement

Methodology

Conclusion

1

Siedschlag,
Zhang and
Cahill
(2010).

Panel data of
723 firms from
Community
Innovation
Survey
of
Ireland
in
period

of
2004-2008.

Labor
productivity.

-CDM model contains three
stages: (1) firm's decision to invest
in innovation; (2) determine
innovation
output
using
innovation inputs and (3)
innovation output and other
production
inputs
in
the
relationship with final output
production.

(1) Foreign owned firms and domestic firms
involved in export activities are more likely to
invest in innovation than firms with domestic
activities only.
(2) Foreign owned firms and domestic firms
involved in export activities are more likely to
have
innovation
output.

Innovation
expenditure have no significant effect on
innovation output.
(3) Innovation outputs have positive
relationship with labor productivity.

2

Belderbos,
Carree and
Lokshin
(2004).

Labor
productivity
growth/Innovati
ve
sales
(products
that
are new to the
market)
productivity
growth.

IV regression between output
variable and innovation variables,
control for firm size, 2-digit
industry dummies, ownership
status, demand-pull and cost-push.

Productivity in the previous period
also is included.

Different types of R&D collaboration and
innovation intensity significantly and
positively affect productivity growth (but
innovation intensity on innovative sales share).

3

Crespi
Pianta
(2009).

Panel
data
from
Community
Innovation
Survey
in
Netherlands in
1996 and 1998
for
2056
manufacturing
firms
32 industries
(including
manufacturing

Innovation
input:
innovation expenditure
(rather
than
R&D
expenditure)
per
employee.
- Innovation output: Three
types
of
innovation
dummies:
product,
process
and
organizational
innovation; interactions;
innovation sales share.
- Innovation expenditure
per sales.
- Dummy variables for
four types of R&D
cooperation: competitors,
suppliers,
customers,
universities or other
research institutions.

- Innovation expenditure
per employee.

Diversify the impact of innovation
on productivity growth through
three separated models: general

Product and process innovations; effort to
build technological competitive advantages,

and

Labor
productivity
growth.

65


and
service
sectors) in 6
Europe
countries from
1996 to 2001.

4

Parisi,

Schiantarelli
and
Sembenelli
(2006).

941
manufacturing
firms in Italy
from
two
surveys
in
1995
and
1998.

- Gross output
growth.
- TFP growth
(TFP
is
determined
using Levinsohn
and
Petrin
(2003)
approach).

5

Santos,
Basso,
Kimura and
Kayo (2014).

Data
of
Brazilian firms
in 2000, 2003,
2005 in which:

ROA
ROS
ROE

Technological
competitiveness:
percentage of firms have
patents; percentage of
firms
targeting
on
improving
product
quality.
- Cost competitiveness:
spending on acquisition of
new
machinery
per

employee; percentage of
firms targeting on flexible
the production process.
-Process and product
innovation dummies.
- R&D expenditure as
percentage of output.

- Human capital.
- Ratio of training
expenditure to sales.
- Ratio of internal R&D
expenditure to sales.

66

model (reflect product and process
innovation);
technological
competitiveness model and cost
competitiveness model.

cost advantages significantly contribute to
growth in productivity.

Cobb-Douglas
production
function to estimate the impact of
innovation activities on output
growth, instrumented by lag of

ln(output/labor),
ln(material/labor),
ln(capital/labor), R&D intensity,
size).
- Tornquist index of TFP is
regressed against innovation
variables, instrumented by the
same set of variables above.
- Descriptive and quantitative
approach: factor analysis.
- Structural equation modelling.

- Positive impact of process and product
innovation on productivity. In details, the
impact of process innovation is bigger than
product innovation. These results are robust in
both approaches: TFP growth and CobbDouglas production function estimation.
- R&D intensity does not have significant
impact on productivity.

Innovation efforts from innovative investment
do not significant explain firm's performance.
Causality relationship between innovation and
performance.


6

Rosenbusch,
Brinckmann

and Bausch
(2011).

7

Lokshin,
Belderbos
and Carree
(2008).

- Innovation
information
from PINTEC
of Brazilian
Institute
of
Geography
and Statistics.
Financial
information
from Serasa
and
Gazeta
Mercantil.
42 empirical
studies
on
21,270 SMEs.

304

Netherlands
manufacturing
firms
from
1996 to 2001.

- Ratio of acquisition of
machinery expenditure to
sales.
- Ratio of external R&D
expenditure to sales.
- Ration of introduction of
technological innovation
expenditure to sales.

Categorized into
three types:
accounting
returns
- growth
- stock market
performance

- Innovation orientation.
Innovation
input
measurements: internal
(R&D expenditure) and
external
(R&D

cooperation).
Innovation
output
measurements
(innovation
sales,
patents).

Meta-analyses on 42 empirical
studies of 21,270 SMEs.

Labor
productivity: net
value added per
employee.

Internal
R&D
expenditure.
External
R&D
expenditure (contracted
R&D).

GMM estimation for the dynamic
panel equation from augmented
Cobb-Douglas
production
function. Innovation variables
included in the model are: internal

67

- Positive effect of innovation on firm's
performance when innovation is measured in
three types, but the effect of innovation
orientation is larger than innovation outcomes.
- Effect of innovation on firm's performance
in young firms is larger than in more
established firms.
- Internal innovation activities have significant
impact on performance while innovative
collaboration with external involves have no
significant impact on performance.
- Cultural environment also have impact on the
innovation-performance relationship.
- Internal and external R&D are complement
in the relationship with productivity with
decreasing returns to scales effect.
- Internal R&D have positive impact on firm's
productivity, this relationship is robust with


R&D expenditure, external R&D
expenditure, quadratic forms and
interaction form.

68

different

dynamic
techniques.

panel

econometric


APPENDIX 3: Durbin – Wu Hausman test for endogeneity
IV (2SLS) estimation
--------------------

Estimates efficient for homoskedasticity only
Statistics consistent for homoskedasticity only

Number of obs =
F(

6,

1942) =

1949
50.27

Prob > F

=

0.0000

Total (centered) SS

=

386439909.4

Centered R2

=

-0.9527

Total (uncentered) SS

=

655444519.7

Uncentered R2 =

-0.1513

Residual SS

=

754587147.2

Root MSE

=

622.2

---------------------------------------------------------------------------------TFP |

Coef.

Std. Err.

z

P>|z|

[95% Conf. Interval]

-----------------+---------------------------------------------------------------invexpintensity |

-1657.575

803.1596

-2.06

0.039

-3231.739

-83.4112

dummy |

968.7459

471.593

2.05

0.040

44.44065

1893.051

.706479

.0460183

15.35

0.000

.6162849

.7966732

lntotalassets |

-21.87988

28.06836

-0.78

0.436

-76.89286

33.13309

capitalstructure |

-372.9817

203.9315

-1.83

0.067

-772.6802

26.71677

firmage |

-3.555249

2.472536

-1.44

0.150

-8.40133

1.290831

_cons |

598.6118

444.9574

1.35

0.179

-273.4886

1470.712

|
TFP |
L1. |
|

---------------------------------------------------------------------------------Underidentification test (Anderson canon. corr. LM statistic):
Chi-sq(1) P-val =

7.005
0.0081

-----------------------------------------------------------------------------Weak identification test (Cragg-Donald Wald F statistic):

7.005

Stock-Yogo weak ID test critical values: 10% maximal IV size

16.38

15% maximal IV size

8.96

20% maximal IV size

6.66

25% maximal IV size

5.53

Source: Stock-Yogo (2005).

Reproduced by permission.

69

-----------------------------------------------------------------------------Sargan statistic (overidentification test of all instruments):

0.000

(equation exactly identified)
-endog- option:
Endogeneity test of endogenous regressors:

12.577
Chi-sq(1) P-val =

Regressors tested:

0.0004

invexpintensity

-----------------------------------------------------------------------------Instrumented:

invexpintensity

Included instruments: dummy L.TFP lntotalassets capitalstructure firmage
Excluded instruments: L.invexpintensity
------------------------------------------------------------------------------

.

70