1

The Analysis of Total Factor Productivity in the Manufacturing Industries:

Empirical Evidences from Iran, Turkey, South Korea, and USA1

Alimorad Sharifi (PhD)

Karim Azarbaijani (PhD)

Mehdi Sadeghi (PhD)

Arash Dehghani (MA)

Energy Economics and Management Research Group

Research Academy of Administrative Sciences and Economics

University of Isfahan

Postal code 81746-73441, Isfahan-Iran

Tel: +98 311- 7935234, Fax: +98 311- 6687396

Email: asharifi@istt.org

Email: alimorad@ase.ui.ac.ir

ABSTRACT

This paper investigates the total factor productivity (TFP) performance in the manufacturing

industries of selected four countries-Iran, Turkey, South Korea, and the United States- during

1980-2007. The productivity measurement index is based on Caves, Christensen, and Diewert

(1982) method. The findings indicate that there are significant productivity differences between

these countries during the last two decades. The empirical results improve the understanding of

how technical and organizational structures as well as their combinations can affect the

productivity performance of the above-mentioned countries.

Keywords: Total Factor Productivity, Manufacturing industries, CCD Productivity Index, Iran,

Turkey, South Korea, USA.

JEL classification: D24, L60.

1 We are grateful to Prof. Fatma Dogruel for providing us with Turkish data.

2

1. Introduction

The concept of total factor productivity (hereafter referred to as TFP) is the core of

Microeconomic theory which encompasses the optimum utilization of natural resources as well

as factors of production. Both developed and developing countries have emphasized the

importance of total factor productivity growth as one of the essential steps in the process of

economic development. In order to obtain comparative advantage in the global economy, to

achieve higher productivity growth is the main point. In the recent decades it is believed that the

degree of socio-economic development is the optimum rate of utilization of available resources.

The post-WWII experiences of developed countries have shown that the dynamics and

growth of manufacturing industries play important roles in the development of other economic

sectors. Irrespective of the size of manufacturing sector in the economy, however, it is

considered as a basic contributor to economic growth (Wagner and Van Ark, 1996). TFP

comparison among different countries would be a critical issue both in theory and practice since

it is believed that one of the major bottlenecks of the developing countries even resource-rich

ones is the low rate of TFP in the manufacturing industries (?). This will result in distortions both

in factors of production as well as output pricing mechanism. As Nadiri and Rosen (?) have

discussed the behavior of interrelated factor demands the change in one factor price will result in

utilization change of another factor, for instance changes in the price of energy carriers will

consequently change labor and capital utilization. The final result will be total factor productivity

fluctuations.

The main initiative for this research is to find out the sources of TFP differences among

four selected countries, two of them are developing countries, one is energy-exporter while the

other one is energy-importer and the other two one industrialized and the other semi-

industrialized. Although there are major structural differences between the above-mentioned

countries but still it makes sense to analyze the sources of this difference and forecast the near

future. In this paper, the cross-country differences in TFP are estimated based on Caves,

Christensen, and Diewert index (hereafter referred to as CCD). The paper is organized as

follows: Next section reviews the relevant literature and section three outlines the major

approaches for TFP measurement. Fourth section discusses the empirical results while section

five concludes the paper.

3

2. Literature review

There are two general methods to estimate the international TFP differentials: The first

one is based on value added while the second one considers gross domestic output (GDP).

Among the studies which estimate TFP using a value added measure are Dollar et al. (1988),

Maskus (1991), Dollar and Wolff (1993), Van Ark (1993), Van Ark and Pilat (1993), and

Harrigan (1997, 1999). The first three references use overall GDP price levels and as a

consequence this causes distortions to the extent that relative Prices differ across countries.

Harrigan (1997,1999) shows that this distortion is large enough to substantively change the

results of TFP comparisons. The two closely related studies by Van Ark (1993) and Van Ark and

Pilat (1993) deflate value added by a price index which is constructed by direct comparisons of

output Prices at the wholesale level rather than using GDP price levels. Unfortunately, this

theoretically superior procedure is compromised by the very small number of matches across

countries for specific products (see Jorgenson, 1990). In addition to this, Ark (1993) and Ark and

Pilat (1993) studies include only a small number of countries and years.

The second class of studies uses data on GDP, and deflates all factors (capital, labor,

materials, energy, etc.) in an asymmetric way. This procedure was pioneered by Jorgenson

(1990) and various authors, and is undoubtedly the most theoretically appropriate and least

restrictive method of making TFP comparisons. Jorgenson (1990) has comprehensively

introduced this methodology. Because of stringent data requirements needed for Jorgenson

procedure, however, there have been only two studies applying this method and comparing only

two countries, the United States and Japan (Jorgenson et al., 1987; Jorgenson and Kuroda, 1990).

3. The concept of productivity

Productivity is simply defined as the ratio of output to the input. While there is no

disagreement on this general notion, a look at the productivity literature and its various

applications reveals that there is neither a unique purpose for nor a single measure of

productivity. There are many different productivity measures. The choice between them depends

on the purpose of productivity measurement and, in many instances, on the availability of data.

Broadly, productivity measures can be classified as single (or partial) factor productivity

measures (relating a measure of output to a single measure of input) or multifactor productivity

4

measures (relating a measure of output to a bundle of inputs). The most common multifactor

productivity measure is TFP (Total Factor Productivity). TFP, in particular, has been actively

studied to explain sectoral productivity differences across countries or over time. Since TFP

analysis is one of the most comprehensive ways of comparing relative industry performance as

well as technical change indicator and economies of scale, therefore, the high level of TFP

indicates the good economic performance. This concept has been emphasized in many

investigations for instance Wagner and Van Ark, 1996; Diewert, ; Denny, et al., ).

Moreover, the productivity is comparative concept. The rate of TFP growth is important

for productivity comparison under a given country, a region, an industry at different times, but is

not as useful in comparing the relative productivity of different countries or regions. Hulten

(2001) believes that the TFP growth rate is of interest for intertemporal comparisons of

productivity for a given country or region at different points in time, but it is far less useful for

comparing the relative productivity of different countries or regions. A developing country may,

for example, have a much more rapid growth in TFP than a developed country,but start from a

much lower level.Indeed,a developing country may have a more rapid growth in TFP than a

developed country because it starts from a lower level and is able to import technology.

Productivity comparison across countries needs the different framework from the other

productivity measurements, a framework that was developed in the late 1970s and the early

1980s by Jorgenson and Nishimizu (1978), Christensen, Cummings and Jorgenson (1981) and

Caves, Christensen and Diewert (1982b). In particularly, Caves et al (1982b) developed a

multilateral productivity index based on Malmquist index as CCD productivity Index. CCD

index preserves transitivity in TFP comparisons across countries.

There are three different types of conversion factors: (i) Exchange rates, (ii) Purchasing

power parities (PPPs), and (iii) Unit value ratios (UVRs). The exchange rate is well known for

not being an appropriate conversion factor because it is influenced by short-term capital

movements. PPPs are a less appropriate conversion factor for productivity comparison of the

manufacturing sector, but still can be a reliable conversion factor for specific branches of the

manufacturing sector, which does not depend on the intermediate products of the production

process. Finally, UVRs are considered an appropriate conversion factor for the manufacturing

sector as a whole and its branches. Due to each conversion factor characteristics, the results of

5

productivity comparisons are expected to be different. Table 1 indicates the variations in

productivity level caused by different conversion factors.

Table 1- Alternative comparative labor productivity Estimates (Output per employee, Britain=100)

Country Benchmark

Year

Using 1985-

based Proxy

PPP

Using 1990-

based Proxy

PPP

Using UVRs

France 1984 107.5 101.1 117

Germany 1987 109.5 109.6 113.5

Japan 1987 108.3 119.4 159.6

United States 1987 174.8 174.3 186.7

Britain 1984/1987 100 100 100

Source: O’Mahany (1996)

The International Comparison Program (commonly known as ICP) is a worldwide

statistical initiative to collect comparative price data and estimate purchasing power parities

(PPPs) of the world’s economies. Using PPPs instead of market exchange rates to convert

currencies makes it possible to compare the output of economies and the welfare of their

inhabitants in real terms. The ICP-PPPs have the average of being based on large samples of

carefully matched products. These PPPs had been matched to national accounts aggregates,

expressed in national currency, to convert them to a common currency at a uniform price level.

In this case, productivity comparison is more representative and less affected by quality

problems. This paper uses ICP-PPPs because UVRs are only available for a few countries.

4. Methodology

This section briefly describes methodology and data followed and illustrates the sample

and discusses the measurement of the inputs and the outputs used in our analysis. Following

Harrigan (1997, 1999), it is supposed that each country's value added function is translog with

identical second-order terms, so that the value added function of country c can be written as

6

(1)

Where constant returns to scale requires and .

Under the additional assumptions that producers are cost-minimizers and price takers in input

markets, Caves, Christensen and Diewert (1982) show that the geometric mean of the two

distance functions for any two countries a and b gives the TFP index

(2)

Where ,

, and

stand for output or value added, labor input and capital stock of country c in

industry j, respectively. and are geometric averages over all the observations in the sample

and , where is labor's share in total cost in country c and is the arithmetic

average of the labor c shares.

is TFP level of industry j between countries a and b. The

relation (2) is superlative index, meaning that it is an exact index for the flexible translog

functional form which is a second-order approximation to Taylor series. Furthermore it is

transitive:

(3)

Which makes the choice of base country and year inconsequential. Our sample includes 2-digit

ISIC branches of manufacturing sector for Iran, Turkey, South Korea, and the United States of

America. The data are collected from different official statistical sources such as The Iranian

Statistical Center, Turkish Statistical Institute, OECD Statistical Yearbooks, World Bank, and

PENN World tables.

Cross-country comparisons require data on outputs, inputs and price indices. The output

measure mostly used in international productivity comparisons is value added. Once value added

is converted into base year, a US price index is required to make different years comparable to

each other. Denote this US value added deflator as , where for t = 2000 for all

j. As a result, we measure real value added (y) in constant dollar (2000 = 100) as

7

⁄ (4)

Where and are real value added and nominal value added during year t in country c,

respectively. is the purchasing power parity for converting the value added in terms of the

domestic currency into US$ values. For , the ICP-PPPs are taken as proxies for the

manufacturing branch.

Labor is derived from industry employment figures. Although using employment raw

data is inappropriate but there is no alternative to use man-hour employment because of data

limitation. The capital stock is constructed as a distributed lag of past investment flows:

∑ (5)

Where is the capital stock of industry j in country c at the beginning of year t, is the

discount factor, and is real investment during year t. Note that the capital stock in year t does

not include year t investment, but only up through year t-1. In this paper, it is assumed that

. If the actual useful life of a capital good is 20 years, this amounts to dropping about

10% of the total weight used in constructing the capital stock . The nominal investment is

⁄ (6)

Where is nominal investment during year t in country c for industry j and is taken from Gross

Fixed Capital Formation (GFCF). We use the deflator for US investment from the OECD STAN

data, various years. Denote this deflator as , with a base t year of 2000.

is the

purchasing power parity for converting the past values of investment in terms of the domestic

currency into U.S dollar values. are taken from the PENN world tables(V6. 2008).

The cost shares in the raw data are very volatile, and in many cases exceed one. Under

the assumptions about technology and input market behavior used to derive (2) and by following

from Harrigan (1997, 1999), we use a smoothing procedure to generate the cost shares used in

constructing the TFP index. For each industry, we estimate the following regression by OLS over

all time periods t and countries c:

8

(7)

We use the fitted values from this regression as the labor cost shares in constructing the reported

TFP results.

4. Empirical results

Food, beverage and tobacco industries (ISIC 15-16):

In this industry all three countries Iran, Turkey and South Korea have a wide productivity

gap relative to USA. Among three countries, Korea has highest productivity during the period

and only in 1990 Iran has had higher productivity with respect to Korea and Turkey. Productivity

of Korea has more or less constant process, but an increasing trend in 2002 will begin.

Productivity trend in Iran is more or less constant; this is done while in 1990, Iran has witnessed

a sharp increase in the productivity. But this increase is not continuous and after this increase,

decreasing trend begins. Productivity trend of Turkey during the 1995-2001 is more or less

constant and maximum size of the country's productivity in 1996 and is equal to 50. During this

period Korea has the highest productivity and Turkey and Iran, respectively, are then replaced.

Diagram 1:

Textile, Textile products, leather and footwear industries (ISIC 17-19):

9

All three countries Iran, Turkey, and South Korea in the industry have the productivity

gap relative to USA. From 1980 to 1994 Iran has relative productivity higher than South Korea.

In the period 1995 to 2001 that the statistics are available for the three countries, trend of level

productivity Korea is constant and for Turkey and Iran less downside is descending. Differences

in productivity levels across the three countries during this period are not very significant. From

2002 to 2007, productivity levels of Korea, unlike 1994 to 1980 period, had been more than Iran.

Diagram 2:

Wood products, furniture and cork industries (ISIC 20):

Iran, Turkey, and South Korea in this industry have wide productivity gaps relative to

USA. Korea during the period has increasing trend while the trend of productivity in Turkey

between 1995 and 2001 is more or less constant. Iran has an unstable productivity trend so that

between the years 1987 to 1992 have higher productivity than USA. But after this year it has

declining trend until 2005.

Diagram 3:

10

Pulp, paper and paper products, printing and publishing industries (ISIC 21-22):

South Korea has relatively increasing productivity during 1980-2005 with its peak in

2002. While Iran and Turkey have rather low productivity trend with a wide productivity gap

compared to USA. In this industry, unlike the past three industries, the productivity level in Iran

and Turkey is very far from South Korea.

Diagram 4:

Chemical, rubber, plastic products and fuel products industries (ISIC 23-25):

In this industry unlike above-mentioned four industries, the productivity gap is least for

Iran, Turkey, and South Korea. The productivity level in South Korea has surpassed USA in the

years 1998, 1999, and 2000. Productivity trends in all three countries (Iran, Turkey, and South

Korea) have severe fluctuations, the lowest productivity for South Korea in 1990 with the size of

52 while the highest productivity levels in 1998 with the size of 109. Turkey with good

performance equal to 78 in 1995 but with decreasing trend reaching to 60 in 2000. Regarding the

Iranian case, the country began a period of high productivity but with sudden sharp drop from 78

to 27.5 because of Iran-Iraq war in 1982. Afterwards the has increased with a little acceleration

in 80's. In the 90's it has more acceleration, for instance in 1999, it has reached 82. After this

increasing period, again decreasing trend of productivity in this country has taken place and

dropped to 70 at the end of this period.

Diagram 5:

11

Other non-metallic mineral products industries (ISIC 26):

In this industry, all three countries Iran, Turkey, and South Korea have wide productivity

gaps compared to USA. An interesting point is the trend of productivity in Iran and South Korea,

it can divided into two periods, the first period from 1980 to 1995 in which Iran has performed

better than South Korea while in the second period from 1996 to 2006 the trend has been

reversed with the superiority of productivity in South Korea. Moreover, Iran, Turkey, and South

Korea have failed during this period to decrease their productivity gaps and the former two

countries also have decreasing productivity trends.

Diagram 6:

Basic metal industries (ISIC 27):

The large gap still exists among Iran, Turkey, and South Korea compare to USA,

although the former three countries have been able to reduce their gaps with each other in this

period. From 1980 to 1994 South Korea and Iran have fully benefited to increase their

productivity trend from 19 to 35 and from 14 to 34, respectively. During 1995 to 2001, South

Korea and Iran both have slow increase in productivity while Turkey has its productivity peak in

12

1997 with a sharp drop in productivity afterwards. Between 2002 and 2006, South Korea and

Iran have very close productivity trend, however, Iran in 2004 is relatively higher than South

Korea. But after this year, the productivity difference between the two countries has been low.

Diagram 7:

Fabricated metal products, machinery and equipment, transport equipment industries (ISIC 28-

35):

In this category, all three countries still have large productivity gaps compared to USA.

During 1980 to 1994 both South Korea and Iran have increasing productivity trends. South

Korea has started from 19.5 and reached 30, while Iran with very low productivity of 4.5 has

reached to 11.5 in 1994. From 1995 to 2001, South Korea have experienced a higher rate of

productivity growth, followed by lower rate of productivity in both Turkey and Iran. During the

whole period, South Korea has productivity level more than twice the level of Iranian

productivity.

Diagram 8:

13

5. Conclusions

This study investigates the concept of productivity comparison and then, using the model

introduced by multilateral index of total factor productivity (CCD) which is estimated for four

selected countries. The main findings are as follows:

- In most ISIC industries studied during 1980 to 2006, South Korea has higher

productivity trend compare to both Iran and Turkey. However, a comparison of South

Korean productivity relative to USA represents large gaps in most industries and

years.

- It must be confirmed that South Korea in all reviewed industries except for industry

code 17-19 in the 90’s has been able to reduce its productivity gap with USA.

- The trend of relative TFP in Iran and Turkey, in most industries, has been decreasing

or at least constant.

- The best productivity peroformance in all three countries, Iran ,Turkey, and South

Korea relative to USA has been in code 23-25 where South Korea has been able even

to surpass USA in 1998, 1999 and 2000.

- Iran at the beginning of period has had the lowest relative productivity in the industry

code 28-35, but at the end of the period the country has been able to achieve a good

growth; However, the industry code 21-22 , has the highest loss of relative

productivity for Iran. Turkey has also experienced its lowest relative productivity

with the same industry code. The Lowest level of relative productivity for South

Korea is also in the industry code 17-19.

14

Appendix:

Total Factor Productivity relative to US level

US TFP=100 at each year

Year T

able

2:

Food, bev

erag

e and t

obacc

o (

ISIC

15

-16)

Iran Turkey S. Korea

Table

3:

Tex

tile

, T

exti

le p

roduct

s, l

eath

er a

nd f

ootw

ear

(ISIC

17

-19)

Iran Turkey S. Korea

Table

4:

Wood p

roduct

s, f

urn

iture

and c

ork

(IS

IC2

0)

Iran Turkey S. Korea

1980 31 - 56 63 - 34 20 - 16

1981 37 - 59 60 - 35 25 - 19

1982 37 - 64 66 - 34 36 - 22

1983 32 - 63 59 - 34 25 - 23

1984 28 - 61 55 - 37 22.5 - 23

1985 33 - 60 54 - 36 21 - 23

1986 32 - 58 53 - 38 18 - 23.5

1987 33 - 56 51 - 39 29.5 - 25

1988 45 - 56 60 - 37 40 - 24

1989 36 - 57 54 - 35 38 - 24

1990 59 - 54 59 - 34 40 - 25

1991 49 - 52 57 - 35 36 - 26

1992 40 - 53 51 - 36 32.5 - 26

1993 48 - 57 42 - 36 26 - 28

1994 42 - 60 57 - 37 23.5 - 27

1995 37 47 54 43 39 36 17 13 29

1996 38 50 60 40 39 37 17 14 29

1997 36 39 64 41 40 36 19.5 14 31

1998 38 44 71 33 36 36 18 13 30

1999 37 41 68 33 32 35 17 12 36

2000 33 41 69 29 33 36 14 15 36

2001 29 48 63 30 34 36 13 12 35

2002 33 - 66 30 - 36 15 - 38

2003 33 - 66 31 - 34 15 - 38

2004 33 - 74 29 - 35 12 - 34

2005 38 - 76 30 - 35 12.5 - 34

2006 35 - 81 30 - 35 18 - 37

2007 28 - - 28 - - 17 - -

15

Total Factor Productivity relative to US level

US TFP=100 at each year

Ye

ar

Table5:

Pulp,

paper

and

paper

product

s,

printin

g and

publish

ing

(ISIC21

-22)

Ira

n

Turk

ey

S.Kor

ea

Table6

:

Chemic

al,

rubber,

plastic

produc

ts and

fuel

produc

ts

(ISIC2

3-25)

Ira

n

Turk

ey

S.Kor

ea

Table

7:

Other

non-

metall

ic

miner

al

produ

cts

(ISIC

26)

Ira

n

Turk

ey

S.Kor

ea 198

0

12.

5

- 38 60 - 78 31 - 26

198

1

12.

5

- 43 78 - 72 39 - 27

198

2

16 - 48 27.

5

- 75 45 - 29

198

3

15 - 55 29 - 79 39 - 32

198

4

14 - 61 30 - 88 34 - 30

198

5

14 - 59 29 - 85 34 - 29

198

6

12 - 60 29 - 87 28.

5

- 28

198

7

11 - 56 33 - 76 50 - 33

198

8

11 - 56 29 - 72 49 - 38

198

9

13 - 55 35 - 60 40 - 36

199

0

14 - 52 37.

5

- 52 59 - 37

199

1

18 - 53 34 - 58 49 - 42

199

2

14 - 54 33 - 61 48 - 39

199

3

13 - 54 39 - 67 39 - 38

199

4

20 - 66 49 - 74 43 - 35

199

5

13 12 68 48 78 81 28 18 32

199

6

12 12 68 55 70 84 29.

5

18 33

199

7

11 11 66 62.

5

70.5 96 25 16 35

199

8

10 9 62 65 62 109 23 14 38.5

199

9

10 8 64 82 65 106 23 13 39

200

0

11 8 68 81 60 102 25 13 41

200

1

9.5 8 65 79 68 97 28 12.5 43

200

2

11 - 71 77.

5

- 99 29 - 43.5

200

3

9.5 - 70 76 - 95 33 - 45

200

4

9 - 86 75.

5

- 94 31 - 41

200

5

10 - 70 66 - 92 30.

5

- 36.5

200

6

9 - 65 69.

5

- 81 26 - 33

200

7

9 - - 70 -

25 -

16

Total Factor Productivity relative to US level

US TFP=100 at each year

Year T

able

8:

Basi

c m

etal

(ISIC

27)

Iran Turkey S. Korea

Table

9:

Fabri

cate

d m

eta

l pro

duct

s, m

ach

iner

y an

d e

quip

men

t, t

ransp

ort

equip

men

t (I

SIC

28

-35)

Iran Turkey S. Korea

1980 14 - 19 4.5 - 19.5

1981 10.5 - 23 6 - 22

1982 15 - 26 7 - 23

1983 18.5 - 31 7 - 26

1984 22.5 - 29 6.5 - 26

1985 28 - 32 6.5 - 26

1986 24 - 39 5 - 28

1987 28.5 - 40 5 - 26.5

1988 37.5 - 37 5.5 - 27

1989 25 - 36 6 - 26

1990 34 - 37 19 - 28

1991 34 - 36 14.5 - 28

1992 57 - 36 11 - 28

1993 32.5 - 37 10 - 29

1994 34 - 35 11.5 - 30

1995 32 36 37 9 22.5 32.5

1996 26 34 37 11 22 33

1997 37 51 39 12 25 33

1998 37.5 29 38 9 22.5 35.5

1999 34 27 40 12 21 41

2000 35 31 41 13 24 43

2001 42 36 42 19 25 47.5

2002 40 - 42 14 - 48.5

2003 42 - 43 21 - 48.5

2004 51 - 45 18 - 53

2005 47 - 46 19.5 - 51.5

2006 42 - 41 19 - 50.5

2007 47 - - 16 - -

17

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