Download Decomposition of Aggregate Productivity Growth of the Malaysian Manufacturing Sector, 1983-2005

Decomposition of Aggregate Productivity Growth of the
Malaysian Manufacturing Sector, 1983-2005
Noorasiah Sulaiman* and Zakariah Abdul Rashid**
Abstract
This paper examines the productivity growth of the Malaysian
manufacturing industries from 1983 to 2005. Unlike previous
studies that use one source of data, this research uses two
sources of data – Malaysian Input-Output Tables and Malaysian
Industrial Manufacturing Survey. The focus of the analysis is on
the decomposition of aggregate total factor productivity (TFP)
growth into three effects: technical change, linkage and final
demand. The findings show that the final demand is the largest
contributor to growth in overall TFP. In addition, there was a
small contribution from technical change and particularly linkage
effects.
Field of research: developing economies, aggregate
productivity.
1.
Introduction
The growth in total factor productivity (TFP) is essential as TFP measures all factors of
production in the economy. The estimation of TFP has received considerable attention
with a number of studies carried out to measure TFP growth in Malaysia, particularly in
the manufacturing sector. According to the Malaysian Productivity Corporation of
Malaysia (MPC), apart from education, training, capital structure and technical change
(including technical efficiency), the inter-industry structure (linkage), and demand
intensity are the main sources of growth in TFP (MPC, 2006).
Technological progress that involves an effective and efficient utilization of appropriate
technologies, innovation, research and development activities, positive work attitudes, good
management, and organizational system will create higher value-added products and services.
Apart from technological change, growth in the TFP can also be explained by the linkage
structure. Linkage, which involves distribution of resources among sub-sectors or industries,
implies the supply and demand for inputs between industries. The re-allocation of resources to
_________________
* School of Economics, Faculty of Economics and Management, University Kebangsaan Malaysia, 43600
Bangi, Selangor, Malaysia. e-mail: [email protected]
**Malaysian Institute of Economic Research (MIER), Level 2, Podium City Point, Kompleks Dayabumi,
Jln. Sultan Hishamuddin, 50050 Kuala Lumpur. e-mail: [email protected]
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more productive industries or sectors will lead to efficient and effective utilization of resources,
and, hence, contribute to a higher growth of the economy (MPC, 2006). Moreover, the economy
is reconstructed from low value-added activity to a higher value-added activity in the various
economic sectors. Linkage between industries, whether forward or backward, is important in
Malaysian industrial development, especially in the manufacturing sector, which includes key
sectors in resource-based industries such as wood products and oil palm industries.
Furthermore, of greater importance is the linkage between resource and non resource-based
industries, as most multinational companies are involved in non resource-based industries, such
as textile and electronics and electrical products.
In addition, demand intensity that comprises domestic and export components (for products and
services), indirectly indicates the level of productive capacity in the economy. Improvements in
productivity and quality of products and services as well as higher capacity utilization in its
production and strong demand will contribute to Malaysia’s export competitiveness. The
economy has benefited substantially from its export-led industrialization policy of making
Malaysian products more competitive in the world market. As Malaysia’s economic growth is
driven by exports expansion and domestic demand, growth in the manufacturing sector
is significantly supported by exports of manufacturing products, while domestic demand
depends on the performance in domestic oriented industries. For instance, electrical
and electronic products contributed more than 70.0% of the total manufacturing export
(Malaysia, 2006). This reflects that, the change in final demand (exports and domestic
demand) will directly affect the total output produced by the manufacturing sector.
The purpose of this article is to identify the determinants of productivity growth for the
manufacturing sector between 1983 and 2005 by decomposing aggregate growth in
TFP into technical change, linkage and final output demand. Furthermore, this study
has an advantage in terms of the methodology used, as it is able to identify the sources
of growth in TFP into linkage and final output demand. Moreover, the main data from
input output tables are able to provide a different view of TFP’s study by decomposing
sources of growth in TFP from the demand side. This section is followed by Section 2,
which outlines the input-output methodology in estimating TFP growth and
decomposition methods of aggregate TFP growth. The sources of data and input-output
aggregation procedures are also presented. Section 3 presents the results and
discussion concerning aggregate TFP growth and the decomposition of aggregate TFP
growth. Section 4 is the conclusion.
2.
The Methodology
The input-output (I-O) framework facilitates the study of productivity growth in the whole
context of the economy, by decomposing sources of TFP growth into endogenous and
exogenous factors. These factors include technological change and inter-industry
structure as an endogenous factor and final demand as an exogenous factor. The
estimation of productivity growth in the present study will be based largely on the work
by Raa and Wolff (1991) and Wolff (1985;1994). In the I-O framework, industrial output
is measured by gross commodity output, , while the inputs consist of intermediate
inputs, labour and capital. It is noted that intermediate inputs are classified into domestic
intermediate input and imported intermediate input. Thus, the derivation of technical
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coefficients matrix, will be based on the input matrix of domestic intermediate input
and the input matrix of imported intermediate input.
The definitions of variables are given below:
an input or ‘use’ commodity by industry flow matrix, where
shows the total input
of commodity consumed by industry ;
an output or ‘make’ industry by industry flow matrix, where
shows the total
output of commodity produced by industry ;
column vector showing the gross output of each commodity .
Where: superscript
refers to the transpose of the indicated matrix,
The matrix of technical coefficients, , is derived from the commodity technology model.i
This model has an advantage in reducing TFP growth into a sectoral level rate of
productivity growth (Wolff, 1985). In addition, the model assumes that the number of
activities must equal the number of commodities, where each industry has its own input
structure, and each commodity is produced by the same technology, irrespective of the
industry of production. In addition, industries are considered as an independent
combination of outputs, , each with their separate input coefficients
. Moreover, in
the commodity technology model, prices can depend directly on the technical
coefficients and are invariant with respect to changes in final demand composition, as in
a standard Leontief system.ii
The technical coefficients matrix, labour and capital inputs derived by the commodity
technology model is given by:
= matrix of inter-industry technical coefficients
= row vector of labour coefficients by industry ; and
row vector of capital input coefficients by industry .
The standard measure of TFP growth rate for industry
Where:
is usually defined as;
row vector of commodity prices in industri ;
row vector of output prices in industri
average lending rate of the economy that is used as uniform price of
capital input is assumed constant across industriesiii (a scalar);
refers to proportionate change.
In the I-O framework, aggregate TFP growth can be related to changes in the interindustry coefficients matrix as follows.
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Where,
TFP growth rate for industry ;
, the Leontief (value) inverse coefficient matrix, showing the
ringgit Malaysia value of each input used per ringgit Malaysia of output.
the total value of final output.
The aggregate TFP growth can be expressed as:
The aggregate TFP growth can be decomposed into technical change, inter-industry
structure, and final demand effects.
Where:
change in aggregate TFP growth;
change in sectoral rates of TFP growth (contributions of technical change);
are assumed constant;
change in the Leontief inverse matrix (contribution of linkage);
are assumed
constant; and,
change in total final demand (contribution of output shares in final demand;
are assumed constant.
Sources of Data and Input-Output Aggregations of Sectoral
This study utilizes data from Malaysia’s Input-Output Tables and Industrial
Manufacturing Survey (IMS). This work is the first attempt in measuring growth in TFP
by using input-output data, incorporating data from the IMS. Therefore, this study is
different from all previous studies on TFP growth in Malaysia that had utilized data from
IMS per se. [Tham, (1997); Menon, (1998); Noriyoshi et al., (2002); Renuka, (2001);
Fatimah & Saad, (2004), and Idris, (2007)].
This study employs data for 1983, 1987, 1991, 2000 and 2005 of Malaysia’s InputOutput Tables published by the Department of Statistics (DOS). Labour and capital are
unpublished data presented by industry obtained from IMS also taken from DOS. Both
employment, and total salary and wages are used as labour input, and capital stock
measures by the net fixed assets as at 31 December (gross fixed assets - depreciation
rate + gross fixed capital formation/capital expenditure). Fixed assets, which present
capital input consists of building and other construction, machinery equipment, transport
equipment, and information communication technology’s tools such as computers. The
average lending rate is utilized to represent the price of capital input. Both labour and
capital data are classified at the three digit-level of industrial aggregation according to
the Malaysian Industrial Classification (MIC) and, the Input-Output Industrial
Classification.
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This study uses the Producer Price Index (PPI) for local production by commodity group
of Standard International Trade Classification (SITC) to deflate some of the variables. In
terms of input-output sectoral aggregations, this study has reduced two sets of basic
tables –‘make’ and ‘use’ – into 32 by 32 industries. This covers all 31 industries of the
manufacturing sector and a ‘single sector’, which represents the ‘other sectors’,
including services, agriculture, mining and construction, and the rest of the public
sectors.
3.
Results and Discussion
As shown in Table 1, the annual rate of aggregate TFP growth inclined, respectively,
from -16.8% to 13.3%, 23.6% and 50.1% per year during the period of 1983-87, 198791, 91-2000 and 2000-2005. The resulting changes in annual TFP growth between the
three periods is 30.1%, 10.3% and 26.5%, respectively.
Table 1 Annual rate of aggregate TFP growth
Annual rate (%)
Periods
1983-87/87-1991
1987-91/91-2000
91-2000/2000-05
Periods
1983-87
1987-91
91-2000
2000-05
-16.8
13.3
23.6
50.1
change in aggregate TFP growth (%)
30.1
10.3
26.5
Table 2 presents the decomposition results of the change in aggregate TFP growth.
Since discrete time periods were used, the average value of in the time period, , was
used in place of , and the average values of matrix in the period, , in place of (see
equation 2). The change in over two sets of time periods was considered: 1983-87/871991, 1987-91/91-2000 and 91-2000/2000-05.
The change in the aggregate TFP growth between the period of 1983-87 and 1987-91
has inclined from -16.8% to 13.3% per annum, or, it has increased by 150.4 percentage
pointsiv. The first of the decompositions, as mentioned above, is the sub-sectoral TFP
growth effect, resulting from the change in sub-sectoral rates of TFP. This accounts for
11.3% of the incline in aggregate TFP growth. The second is the inter-industry multiplier
effect, from a change in matrix . It is small, accounting for -0.3 of the incline. The third
is the final output effect. It accounts for 89.0% of the overall change in productivity.
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Table 2 Decomposition of the change in aggregate productivity growth
Periods
Percentage contribution
aggregate
technical
change
linkage
output
shares
sum of three
effects
1983-87/87-1991
1.504
11.3
-0.3
89.0
100.0
1987-91/91-2000
1.701
19.7
-1.0
81.3
100.0
91-2000/2000-05
0.139
33.1
1.4
65.5
100.0
Source: estimated from equation (3).
note: estimation of output shares is based on the final output/final demand.
The change in the overall TFP between 1987-91 and 91-2000 periods inclined from
13.3% to 23.6% per annum, or by 170.1 percentage points. The first component of the
result shows a technical change effect (sub-sectoral TFP growth effect) contributing
19.7% to the incline in overall TFP growth. The second component remained the same.
It is small, accounting for -1.0% of the incline. As a result, the component of final output
value shares remained large, contributing to 81.3% of the incline in overall TFP growth.
The period of 91-2000 and 2000-05 indicates that the change in the overall TFP inclined
from 23.6% to 50.1% per annum. The result has also inclined, but only by 13.9
percentage points. The contribution of technical change has increased to 33.1% to the
incline in overall TFP growth. The second component has a positive contribution,
accounting for 1.4% of the incline. However, the component of final output value shares
has declined, contributing 65.5% of the incline in overall TFP growth. The decline in the
contribution of final demand was replaced by the incline in the contribution of technical
change. During this period, the contribution of technical change to the incline in overall
TFP growth has improved substantially. Furthermore, there is a good indication in the
linkage component that has contributed positively to the change in overall TFP growth.
Results for the first two periods show that the component of final output was larger,
contributing more than 80.0% of the incline in TFP growth. This reflects that the final
output component is important in determining the overall change in TFP growth. It has
to be noted that a major advantage of using final output in this study is the change in
aggregate TFP growth, which is related to the shift in final output. Moreover, final output
shifts are usually held to be autonomous, since they reflect changes in consumer taste
and demand patterns. In contrast, the change in gross output shares may be partly due
to changes in the inter-industry matrix , which is considered an endogenous or a
derived effect. Therefore, based on this reason, Wolff (1994) suggests that a change in
final output shares is methodologically closer to a ‘pure’ composition/final demand effect
than the change in gross output shares.
The results from other studies obtained technical change effect as the largest
contribution to the overall change in TFP growth in the United States, while final output
shares were relatively small. The inter-industry effect, however, indicated a negative
contribution (Wolff,1985;1994). In his study, the value share effect was largely offset by
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the inter-industry effect. In contrast, for the Malaysian case, as a rapid growth
developing country, the contribution of technical change was very small. This reflects
that the production structure of the Malaysian economy, in terms of technological
progress has contributed from 10.0% to 20.0% during 1983 to 2000, and increased to
33.0% during the period of 2000 to 2005. From this evidence, it can be argued that in
certain industries in the manufacturing sector, there might have been little progress in
technological change.
Remarkably, the contribution of final output shares to change in overall TFP was
large. This may imply that the final demand component determined the contribution to
the change in overall TFP growth. The final demand is essential as foreign direct
investment functioning on the production of the export goods. Other studies that came
up with similar results found that most of the sources of growth for the key sectors from
1978 to 1991 came from final demand, especially domestic demand expansion and
several key sectors such as sawmills and furniture and fixtures were dominated by
export demand expansion (Rohana, Zakariah & Kamaruzaman, 2008). The same
conclusion indicating that domestic-demand expansion was the dominant source of
growth in the Malaysian economy in the sub-period 1978-83, while exports expansion
was dominant in light and heavy industry (Zakariah & Ahmad,1999).
In terms of linkage effects, this study reveals that linkage patterns among
industries were negative during the first two periods of the study. This implies that
linkages contribute negatively to the growth in TFP. This also highlights that linkages
between industries may only occur among the local firms, while linkages between local
and foreign firms might not exist in general. For instance, the characteristic of
multinational companies in Singapore that are engaged in processing industries, which
import unfinished components and export finished products, results in weak intramanufacturing linkages, while linkages within the multinationals’ network of plants
located throughout the world tend to be stronger (Tsao, 1985). This may be due to the
characteristic of multi-national companies, which usually bring their subsidiary
companies into the host country for the purpose of supplying parts and components to
the leading companies.
4.
Conclusion
This study concludes that Malaysian overall TFP growth was contributed mainly from
the exogenous influence of the economy’s final demand, comprising exports and
domestic demand, while technological change played a small role. Endogenously,
technical change and linkage contributed a small fraction to the overall TFP growth.
Based on the past performances of its overall TFP growth, potentially, the economy can
enhance its overall TFP growth by managing its domestic and export demands, which
can be done through some combination of monetary and fiscal policy measures. This
also implies that although the economy is known to be a small open developing
economy, it has significant control on the economy in determining its overall TFP
growth. From a policy viewpoint, the economy’s relative size and structure of private
consumption expenditure can be used to influence its overall TFP growth.
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The indirect contribution of final output demand to growth in TFP, however, is related
strongly to the contributions of foreign direct investment. As Malaysian industrial
strategies invite foreign investment through various incentives, especially exports
promotion of the manufactured products, the manufacturing sector leads the GDP
growth as well. Similarly, as a leading export country and since export expenditure can
significantly influence the economy overall TFP growth, export promotion activities in
terms of increasing the volume and the dispersion of export destinations should be used
actively. This can be done through normal measures of export promotion. However, it is
important to note that export expenditure by foreign buyers is somewhat autonomous
and, if export markets face difficulties, there is a very limited measure to rectify it except
in the long run by diversifying the export destinations.
Captured by the contribution of linkages, contribution of technological change to overall
TFP growth is still very limited. However, enhancing inter-industry structure, creating
stronger inter-sectoral linkages, which is currently visible only in the economy’s
resource-based industries, should be extended to the non-resource based industries as
well. Perhaps, the country’s industrial policy review should give more focus to
strengthening inter-industrial linkages, especially among the non-resource based
industries, that is, improving linkages between multinational corporations and their local
vendors.
References:
Central Bank, 2007. Annual Report, 2006, Bank Negara Malaysia: Kuala Lumpur.
______ various years. Annual Report, Bank Negara Malaysia: Kuala Lumpur.
Department of Statistics, various years. Malaysia Input-Output Tables, Putrajaya, Kuala
Lumpur.
______ various years. Industrial Manufacturing Survey, Putrajaya: Kuala Lumpur.
______ various years. Labour Force Survey: various years, Putrajaya: Kuala Lumpur.
Malaysia Economic Reports, various years. Annual Report, National Printing
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Fatimah S. & Saad M.S., 2004. Total factor productivity growth in Malaysian
manufacturing sector: emphasis on heavy industries, International of Economics and
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Idris J., 2007. Determinants of total factor productivity growth in Malaysia, Journal of
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Menon, J., 1998. Total factor productivity growth in foreign and domestic firms in
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endnotes:
i
also, see Kop Jansen & Raa (1990) for more discussion of models of secondary production and the
properties of such models.
ii
This is also true for most other models of secondary production. See Kop Jansen & Raa (1990) for more
details.
iii
In this study, the authors used average lending rate, it is implicitly assumed to be homogenous across
industries.
iv
see Table 3: the coefficient value of change in aggregate TFP growth (Δρ).
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