Proceedings of 3rd Asia-Pacific Business Research Conference
25 - 26 February 2013, Kuala Lumpur, Malaysia, ISBN: 978-1-922069-19-1
Comparing Productivity in Foreign-Invested and Local
Plants in Thai Manufacturing
Chayanon Phucharoen+
This study investigates productivity differentials between
foreign-controlled plants and local plants in Thai
manufacturing industries using the firm-level data from the
NSO 2005 industrial census. With Translog production
functions, first we compare total factor productivity (TFP)
and labor productivity of multinational plants and local
plants. Results revealed that only 8 out of 18 studied
industries were reported with superiority of multinational
plants in TFP and labor productivity over local plants. If both
intercept and all slope coefficients are allowed to vary across
foreign and local plants’ samples, we found that
multinational plants’ production function significantly differs
from production function of local plants in fewer numbers of
industries. In addition, the difference in local and foreign
plant’s labor productivity functions are shown in 6 industries.
Regardless of the employed approaches, there is a group of
industries which was consistently reported with productivity
differential.
This group comprises of manufacture of
chemical and chemical product [ISIC24], rubber & plastic
product [ISIC25], fabricated metal [ISIC28], general machine
and equipment [ISIC29], and motor vehicle [ISIC34]
industries. As previous studies, the productivity gap between
foreign and local plants is empirically less convincing than its
conceptual frameworks since most of the industries were
reported with insignificant difference. However, our results
repetitively report that productivity differential statistically
exist in the industries which require high start up cost.
Keyword: Economics
1. Introduction
As the vehicle of globalization, Multinational corporations have played the leading role
in this era; many host nations have been participating in the fierce competition to
attract for the entrance and presence of multinational plants. With the perception that
their presence could eventually contribute to the development in their nations through
various measures; for example, host nation’s balance of payment. A vast number of
researches have been conducted to empirically test these aggregate impacts of FDI
on host nations.
However a much less studied issue is the indirect impacts of
Foreign Direct investment or the MNCs’ externalities to local firms, which could
potentially serve as the answer to the puzzle or at least a passage to solve the puzzle
of whether those privileges provided to attract the Flow of FDI, are empirically justified.
However the prerequisite for those impact studies is a closer examination on whether
productivity differential between foreign-controlled and local controlled plants is
statistically legitimate as suggested by conceptual frameworks.
+
Ph.D. candidate; Faculty of Economics, Chulalongkorn University, Bangkok, Thailand. Tel:+66-81-9356585 Fax:+66-76344251 E-mail:please_send_it@hotmail.com
Proceedings of 3rd Asia-Pacific Business Research Conference
25 - 26 February 2013, Kuala Lumpur, Malaysia, ISBN: 978-1-922069-19-1
The primary aim of this work is not only to investigate whether this gap exists in Thai
manufacturing industries but we also strive to verify in which industries productivity
differential exists. Thus the findings could potentially assist policy makers to optimally
design both investment privileges to multinational plants and competitiveness
development schemes for local plants. First, this study investigates the total factor
productivity of local and foreign plants and we further compare foreign plants’ labor
productivity with local plants’ labor productivity. To enhance the robustness of the
result, we further investigate the difference between foreign and local plants
technology through the comparison of the foreign and local plants’ production
functions. In parallel to this investigation, we also evaluate labor productivity functions
of both multinational and local plants. Through varieties employed approaches, any
industry with the consistent report of productivity difference between these two groups
of plants would imply that foreign plants in that particular industry inherently differ from
their local counterparts.
2. Review of literature
The origin of the theory of MNC is derived from Hymer (1960)’s dissertation, which
fundamentally explain why this type of firms directly invest abroad. At the center of his
framework, there is a firm specific advantage, which is specific asset possessed by a
group of multinational corporations. This firm specific asset could allow MNCs to
overcome the incremental cost of doing business abroad, competitively compete with
local plants in unfamiliar markets/ supply chain networks and rule and regulation
during their entrance or their presence in host nations.
The possession of the firm specific assets would give multinational plants with some
market power or cost advantage in competing with local plant in the host countries. To
be specific, Dunning’s (1977) commented that this advantage could be the possession
of resources like brand names (marketing abilities), skilled labor and knowledge of
technology, size, and efficient production process. To support this particular claim
through the case of previous studies in Thai manufacturing industries; Jongwanich
and Kohpaiboon (2010) revealed that most of the registered patents in Thailand were
granted to foreign entity 90% during 2006-2008 while only 10% of registered patents
were granted to local entities. A hypothesis on the productivity differential between
foreign-controlled and local controlled units could be developed because foreignplants possess this kind of firm specific assets, which mostly in form of intangible
production, marketing knowhow and management practice as generally concluded by
Ramstetter (2006). This possession serves as a source which enables multinational
plants to have a higher productivity than the domestic plants1.
Among the first batch of empirical papers on this area originated by Lall (1976), which
analyzed the performance gap between MNCs and local firms by using firm level data
by using simple descriptive statistic. Willmore (1986) focus on productivity, of the firms
and some of the firm’s characteristic, both value added per worker and wage per
worker were used as the proxies of firm’s productivity, results reveal that foreign
controlled firm generally has higher productivity than local operated firm. Doms and
Jansen (1998) used various definition of productivity; their results generally reveal that
the productivity of foreign plants is significantly greater than the productivity of locally
owned plants in USA. Liu (2000) which conduct the study in China, their results
revealed that multinational status could significantly enhance labor’s productivity of the
firm. While Manikandan (2006) also used the initial technique of t test to test for the
Proceedings of 3rd Asia-Pacific Business Research Conference
25 - 26 February 2013, Kuala Lumpur, Malaysia, ISBN: 978-1-922069-19-1
difference between two sampled groups; foreign firm and local firm in various
industries. However he found that the productivity differential is not statistically valid in
most cases but the difference in firm’s capital intensity do statistically prevails in many
industries.
Ito (2002) focuses on the plant productivity in Thai Automobile Industry; and he found
that foreign plan generally has higher labor productivity than local firm. This superiority
is concluded as the result of a higher capital intensity of foreign firm in the Automotive
industry. Through the use of Translog production function which requires less
restrictive assumptions than the basic Cobb Douglas derived production function.
Ramstetter (2002, 2006) found a greater no. of industries with the reports in
production technology differential than the Cobb Douglas based production function.
However most of the industries were reported with insignificant disparity, and even
more surprisingly; authors found that in those reported industries, multinational plants
were not necessarily shown with greater productivity. Similar result is also found in the
case of Vietnamese manufacturing firms (Ramstetter 2008). Unlike works on
theoretical frameworks, the consensus among empirical works is still a long traveling
destination; results differ across the region, time, and employed methodologies. This
paper aims to investigate this puzzle with the latest firm level data of Thai
manufacturing firms.
3. Methodology and Data
Most of the empirical studies have employed log linearize Cobb Douglas derived
estimating regression as following
Eq. 1
The above regression is further added with the control variables and MNC dummy
2
variable , which is designed to test whether there is a difference in the influence of
firm’s multinational status.
∑
Eq. 2
Where y is the output of the firm, K is capital, L is labor hour, and
is the vector of
control variables. Subscript i represent firm i. Cobb Douglas production function
assumed constant return to scale and perfect substitute of inputs. Translog production
function, which has more flexibility to describe the relationship between firm’s
production activities and firm’s factor of production. Hence Translog production is
Eq.3
mainly employed.
∑
With capital, two types of labors, firm’s age and size as the list of control variables, the
above translog model could be rewritten as estimating model as
Eq.4
Where V is the value added of the firm as plant’s output, K is capital, OPL is working
hour of blue collar workers, and NONOPL is the working hour of white collar workers.
MNCstatus is the dummy on multinational status of the plant (0 if plant is locally
controlled plants, 1 otherwise). As Ramstetter 2003; dSize, dAge and dBOI are the
dummy variable on firm’s size age and whether the firm had received investment
promotion privileges 3 . is the residual of the regression. To investigate if foreign
plants are more productive than local plants we observe
whether it is significant
Proceedings of 3rd Asia-Pacific Business Research Conference
25 - 26 February 2013, Kuala Lumpur, Malaysia, ISBN: 978-1-922069-19-1
and positive. To particularly test for the labor productivity differential, eq.4 is adjusted
to the following regression
Where V/L is the value added per worker, and K/L is capital intensity of the firm. While
is the skill intensity of the firm, and it is measured as portion of skilled and
white collar labor to total labor. The supremacy of foreign firm in labor productivity over
local firm’s could be observed, if
is significant.
The above two regressions could study the difference in TFP and labor productivity of
foreign and local plants with the assumption that foreign and local plants share the
same regression coefficients in other variables. To allow all of the regression
coefficients to vary across these two groups of plants. I further employ the test
involving the equality of coefficients of different regressions (Pindyck &
Rubinfeld1997).To compare the production functions of local and foreign plants as
stated in the objective, we would drop dMNC variable from the eq.2 and separately
run the model to each local and foreign samples4. To test for the labor productivity
differential between local and foreign plants, similar adjustment as endnote 2 should
be made to eq.5.
The data from NSO 2005’s industrial census are employed throughout this study.
Industrial in the census is classified by ISIC code. There are 23 ISIC main classified
industries comprise of 457,968 plants of which 73,931 plant’s information are in
database. However there are large discrepancies between the report from NSO and
statistical report from other organizations; for example, department of labor, as well as
the problem of duplication of data due to the misperception by respondents; hence the
removal of duplication is needed. If any two or more observations simultaneously have
identical registered categories of industry, value of fixed asset, and gross sale, they
would be treated as duplicated series, and they would be disregarded from the list. I
intend to exclude Tobacco [16], publishing and printing [22], manufacture of oil and
coal product [23], and recycling [37] industries from my analysis since there is limited
no. of foreign controlled plants which could lead to insufficient no. of observation in the
tests. In addition, in order to avoid disproportion representation of the firms and
relatively untrustworthy response in some establishment. Thus I scope my analysis to
firm with the size (classified by no. of labor) in categories 6 and above, which have
total worker greater than 15, and the firm which has sale per labor above Baht 10,000,
and fixed asset per labor above Baht 5,000 per year.
4. Results
Result of each studied objective is shown in accordance to its alternative hypothesis.
4.1. Ha1: TFP of Multinational plants is greater than TFP of local plants.
The following table is the results in average TFP from operating eq.5 without industry
classification of observation.
Proceedings of 3rd Asia-Pacific Business Research Conference
25 - 26 February 2013, Kuala Lumpur, Malaysia, ISBN: 978-1-922069-19-1
Plants in all
industries
Cobb Douglas
Parameter P value
C
5.00792**
0.0000
LOG(K)
0.26556**
0.0000
LOG(OPL)
0.32158**
0.0000
LOG(NONOPL)
0.27957**
0.0000
dMNC
0.26098**
0.0000
dAGE
0.05961**
0.0004
dSIZE
0.83576**
0.0000
dBOI
0.13293**
0.0000
(LOG(K))^2
(LOG(OPL))^2
(LOG(NONOPL))^2
LOG(K)*LOG(OPL)
LOG(OPL)*LOG(NONOPL)
LOG(K)*LOG(NONOPL)
No. of Observation
10,158
Adjusted R square
0.75015
Prob. F test
0.00000
Dependent variable: Value added
Translog
Parameter
P value
7.999148**
0.000
-0.643534**
0.000
0.939107**
0.000
0.656834**
0.000
0.237469**
0.000
0.062129**
0.000
0.791079**
0.000
0.123304**
0.000
0.034448**
0.000
0.010199
0.113
0.047193**
0.000
-0.009272
0.182
-0.063987**
0.000
-0.03051**
0.000
10,158
0.75713
0.00000
Table 1: Result from Cobb Douglas and Translog estimating models with all
5
observations , ** implies variable is significant at 0.05 level of significant, the
focus variable is on dMNC.
Without industrial classification on samples, foreign plants have higher average total
factor productivity than local plants in both Cobb Douglas and Translog based
estimating models6. However, with the observations, classified to each industry, we
found multinational plants statistically outperform the local plants in only 8 industries.
Which are manufacture of woods & wood product(ISIC 20), chemical and chemical
product(ISIC 24), Rubber & Plastic products (ISIC 25), Fabricated metals(ISIC 28),
General Machinery and equipments(ISIC 29), Automobile and Part(ISIC 34),
Furniture(ISIC 3610) and manufacture of toy, leisure and Sport equipments(ISIC
3692to94). For instance; foreign plants in manufacture of chemical industry (ISI24)
has higher average TFP than local plants in the same industry by 29%. From the list
of reported industries, multinational plants have higher TFP than local plants not only
in high technology industries but also in other types of industries; for example,
manufacture of woods and furniture industries. However; foreign plants are reported
with insignificant gap in most industries as previous studies. The result from this
section further invited me to explore the production technology differential between
these two groups of firms.
4.2. Ha2: Labor productivity of multinational plants is higher than local
plants’ labor productivity.
The following table is the results in average labor productivity from operating eq.4
without industry classification of observation.
Proceedings of 3rd Asia-Pacific Business Research Conference
25 - 26 February 2013, Kuala Lumpur, Malaysia, ISBN: 978-1-922069-19-1
Plants in all industries
C
LOG(K/L)
LOG(Skill/L)
dMNC
dSize
dAge
dBOI
LOG(K/TH)^2
LOG(SK&White/TH)^2
LOG(K/TH)*LOG(SK&White/TH)
Cobb-Douglas
Translog
Parameter
P value
Parameter
2.09469**
0.35313**
0.007504
0.23270**
0.64557**
0.08799**
0.10208**
0.0000
0.0000
0.5327
0.0000
0.0000
0.0000
0.0000
2.74094**
0.12972**
-0.7264**
0.22510**
0.62740**
0.09005**
0.10469**
0.01745**
-0.10841**
0.07125**
P value
Observation
13,509
13,509
Adjusted R square
0.3592
0.3673
Prob. F test
0.0000
0.0000
0.0000
0.0002
0.0000
0.0000
0.0000
0.0000
0.0000
0.0000
0.0000
0.0000
Table 2: Result from Cobb Douglas and Translog estimating models with all
7
observations , ** implies variable is significant at 0.05 level of significant, the focus
variable is on dMNC.
Again in sample without industrial classification on samples, foreign plants significantly
have higher average labor productivity than local plants in both Cobb Douglas and
Translog based estimating models.
At the industry classified level, Labors in multinational plants have greater productivity
than the labors, who are working in local plants, in 9 industries. The list of these
reported industries is almost identical to the list stated in the case of TFP comparison,
with manufacture of textile industries as added industry. In conjunction with the results
produced from the first objective, most of the industries with the report of the
multinational plants’ supremacy in TFP are also reported with superiority in labor
productivity. Interestingly, local plants in manufacture of footwear and luggage industry
significantly have higher labor productivity than their foreign counterparts.
4.3. Ha3: There is a production technology differential in local and foreign
plants.
If we allow not only intercept and but also all coefficients of the regression to vary
across both samples. The null hypothesis of an identical production technology
between foreign and local plants could be rejected only in 5 industries. These
industries are the subset of the reported industries as reported in 4.1 and 4.2.
However, only high tech industries (manufacture of chemical and chemical product,
Rubber & Plastic products, manufacture of fabricated metals, General Machinery and
equipments, manufacture of Automobile and Part industries) were prevailed with
significant difference in this production function comparison.
Industries with the report of production function differential implies production
technology differential between foreign plants and local plants. Interestingly; not all
industries, which previously reported with TFP differential are reported with production
technology differential. Only industries with high initial investments are recorded with
technology differential. Next we particularly explore the labor productivity function
differential in foreign and local plants.
4.4. Ha4: Labor productivity function of foreign plants is not identical to
labor productivity function of local plants.
Proceedings of 3rd Asia-Pacific Business Research Conference
25 - 26 February 2013, Kuala Lumpur, Malaysia, ISBN: 978-1-922069-19-1
Comparing to the previous alternative hypothesis, the general perception on labor
productivity differential between foreign and local plants is less supporting in this
approach. Foreign firm’s labor productivity regressions statistically differ from local
firm’s labor productivity regression in only 6 industries. Mostly; there are capital
intensive industries, manufacture of chemical and chemical product(ISIC 24), Rubber
& Plastic products (ISIC 25), Basic metal (ISIC 27), Fabricated metals(ISIC 28),
General Machinery and equipments(ISIC 29), Automobile and Part(ISIC 34). The
following table summarizes the results from all of the 4 approaches. Results are
relatively robust across approaches
The alternative hypothesis of multinational plants’ superiority in TFP and labor
productivity is more convincing at aggregate levels than the disaggregate level. At
disaggregate level, multinational plants could outperform local plants in only 8
industries. The study of production function and labor productivity functions between
local and foreign plants even indicate less no. of industries with significant difference.
As shown in the table illustrated in the next page, productivity and its function (either
defined as Total Factor Productivity and Labor Productivity) of multinational plants in
{[1] manufacture of chemical and chemical products, [2] manufacture of rubber and
plastic product, [3] manufacture of fabricated metal, [4] manufacture of general
machine and equipment, and [5] manufacture of automotive vehicle and part
industries} are statistically difference from local plants. Since these industries have
been consistently reported with the rejection of null hypothesis in every approach and
interestingly; they are industries which require high start up cost.
HO1 : TFP of
MNC is equal
to TFP of local
plants
HO2: LP of
MMC equal to
the LP of local
plants
HO3 :
Identical
Production
functions
HO4 :
Identical
Labor
productivity
functions
ISIC
code
Industry
15xx
Food products and beverages
Do not reject
Do not reject
Do not reject
Do not reject
17xx
Textiles
Do not reject
Reject HO : [+]
Do not reject
Do not reject
18xx
Wearing apparel
Do not reject
Do not reject
Do not reject
Do not reject
19xx
Luggage and footwear
Do not reject
Reject HO : [-]
Do not reject
Do not reject
20xx
Wood and wood product
Reject HO : [+]
Reject HO : [+]
Do not reject
Do not reject
21xx
Paper and Paper product
Do not reject
Do not reject
Do not reject
Do not reject
24xx
Chemicals and chemical pro.
Reject HO : [+]
Reject HO : [+]
Reject HO
Reject HO
25xx
Rubber and plastics products
Reject HO : [+]
Reject HO : [+]
Reject HO
Reject HO
26xx
Other non-metallic mineral pro.
Do not reject
Do not reject
Do not reject
Do not reject
27xx
Basic metals
Do not reject
Do not reject
Do not reject
Reject HO
28xx
Fabricated metal products
Reject HO : [+]
Reject HO : [+]
Reject HO
Reject HO
29xx
General Machinery and equip.
Reject HO : [+]
Reject HO : [+]
Reject HO
Reject HO
30-33xx
Electrical related industries
Do not reject
Do not reject
Do not reject
Do not reject
34xx
35xx
Automotive and parts
Other transport vehicle
Reject HO : [+]
Do not reject
Reject HO : [+]
Do not reject
Reject HO
Do not reject
Reject HO
Do not reject
3610
Furniture
Reject HO : [+]
Reject HO : [+]
Do not reject
Do not reject
3691
Jewelry
Do not reject
Do not reject
Do not reject
Do not reject
Reject HO : [+]
3692-94 Musical, Sport equip. and toys Reject HO : [+]
Do not reject Do not reject
Table 3: Summary table of all testing approaches at ISIC 4 digit classification: Reject H0 implies the null
hypothesis could be rejected at 0.05 level of significant. [+] implies foreign plants could statistically
outperform the local plants, while [-] means local plants outperform foreign plants.
Proceedings of 3rd Asia-Pacific Business Research Conference
25 - 26 February 2013, Kuala Lumpur, Malaysia, ISBN: 978-1-922069-19-1
The above results suggested that there is strong evidence that foreign plants differ
from Thai local plants in industries which required high start up cost but the
differences in TFP and labor productivity are not confined in this group of industries.
Hence privileges scheme, either given to local or foreign plants, should be redesigned
in consideration to the TFP and labor productivity differential in these industries.
Another implication is that this study could identify a list of industries with the existing
gaps, and then a subsequent spillover study should focus on these reported industries
to identify that whether the presence of foreign plants could generate externalities to
the local plants within the same industries.
5. Conclusion
Conform to the previous studies, most of the industries were not reported with
significant gap as suggested by conceptual framework. With various seemingly related
approaches, we could identify the 5 previously stated industries which foreign plants
inherently differ from local plants. The plausible explanation for these disparities
between foreign and local plants in this group of high start up cost industries is the
accessibility to financial capital by multinational corporations. This accessibility to
financial sources is considered as a form of MNC’s firm specific assets. The
underlying aspiration of this study is to assist authorities to design and develop
investment promotion scheme through the acknowledgement of productivity
differential between foreign and local plants.
Acknowledgement
I sincerely appreciate valuable advice from my Ph.D. dissertation advisor, Associate
professor Dr. Paitoon Wiboonchutikula and co-advisor Assistant professor Dr. Bungon
Tubtimtong and I would like to thank Prof. Eric D. Ramstetter for his advice on this
work.
References
Doms M. and Jensen B. (1998). Comparing wages, skills and Productivity
between domestically and foreign owned manufacturing establishment in the US.
NBER working paper, page 235-258, (1998)
Dunning H. (1977). Trade, Location of economic activity and MNE: A search for
an eclectic approach. In: Hesselborn and P.M. Wijkman, eds., The international
allocation of economic activity. London: Macmillan, (1977), pp.395-418.
Hymer S.H.(1960). The international operation of National firms: A study of
direct foreign investment. MIT press, Cambridge (1976).
Ito(2002). Are foreign multinationals more efficient? Plant productivity in Thai
Automobile industry. ICSED Working paper, Vol. 2002-19 July (2002).
Jongwanich and Kohpaiboon (2010). Multinational Enterprise, Exporting and
R&D activities in Thailand. Globalization and Innovation in Asia workshop ,Bali (2010)
Lall S.(1976). Financial and profit performance of MNCs in developing
countries: some evidence from an Indian and Columbia Sample. World
development,.4/9: pp 713-724.
Proceedings of 3rd Asia-Pacific Business Research Conference
25 - 26 February 2013, Kuala Lumpur, Malaysia, ISBN: 978-1-922069-19-1
Lui X. (2000). Comparative performance of foreign and local firms in Chinese
industry. Aston University working paper,(2000).
Manikandan(2006), “Performance of foreign Multinational and domestic
companies in India Since Liberalization: A comparative study. Working paper, 2006
Pindyck Robert, and Rubinfeld. Economic model and Economic forecast. 4th
edition.
Ramstetter, Eric D.(2001). Labor Productivity in Foreign Multinational and Local
Plants in Thai Manufacturing, 1996 and 1998. ICSEAD working paper,2001-13, June
(2001).
Ramstetter, Eric D.(2002). Does technology differ in local plants and foreign
multinationals in Thai Manufacturing? Evidence from Translog Production functions for
1996 and 1998. ICSED Working paper, Vol. 2002-2003 May (2002)
Ramstetter, Eric D.(2006). Are productivity differential important in Thai
Manufacturing.
In Eric D. Ramstter and Fredrik Sjohom, eds., Multinational
Corporation in Indonesia and Thailand: Wages, Productivity, and Exporsts.
Hampshire, UK: Palgrave Macmillan, pp114-142.
Ramstetter, Eric D., Phan Minh N. (2008), “Productivity, Ownership and
Producer concentration in Transition: Evidence from Vietnamese Manufacturing”
ICSED Working paper, Vol. (2008)
Willmore(1986), “The comparative performance of foreign and domestic firm in
Brazil”, World development Vol.14, No.4 page 489-502, (1986)
End Note
1
Latest theoretical framework which explains Multinational Corporation’s behavior is the Heterogeneity
model, Helpman (2005). The model generally concludes that to become multinational corporation, this
group of firm must possess sufficiently high productivity, higher than productivity of domestically
operated firm and exporting firm.
2
Two types of labor variables, operative and non operative types of labor, would be simultaneously
employed.
3
To control for the size and age of the firm which might influence plant’s output level, dSize and dAge
would be recorded as 1 if plants has total asset and age greater than industry average’s total asset and
industry’s average age respectively.
4
As the test involving the equality of coefficients of different regressions (Pindyck & Rubinfeld1997), the
test statistic is
where ESSr and ESSur are error sum of square residual of restricted (ESS
from all types of firm sample) and unrestricted regression (combination of ESS from local and foreign
sample) respectively. The eq.1 is adjusted as
This regression would be separately operated with [A] local plant sample, [B] foreign plant sample and
[C] all plants sample. ESSr is error sum of square residual obtained from operating above regression
with [C] all plants sample, while ESSur is the combination of error sum of square residual obtained from
above regression with [A] sample and error sum of square residual operated from above regression
with [B] sample. K is no. of parameter (in this case 12 variables), N and M are the no. of observation in
[A] and [B] respectively.
Proceedings of 3rd Asia-Pacific Business Research Conference
25 - 26 February 2013, Kuala Lumpur, Malaysia, ISBN: 978-1-922069-19-1
5
Full results on each industry are available upon the request.
6
Although the explanatory power of equation by using this model is almost the same as non translog
estimation model. However; Translog production model would be used because it provides more
flexibility in a variable elasticity of substitution than the commonly assumed Cobb Douglas function
7
Full Results on each industry are available upon the request