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Measuring the Contribution to GDP and Productivity of the Malaysian Services Sector
A joint project of
the Economic Policy Unit of Malaysia and
the World Bank
Economic Policy Unit Dr. Noor Azlan, Director of Malaysian Development Institute
Dr. Ibrahim Abu Ahmad Dr. Roslina Mohd Isa
Christina Yeo Ting Kok Onn
The World Bank Albert G. Zeufack
Barry Bosworth (Brookings Institution) Aaron Flaaen (Brookings Institution)
October 21, 2008
Acknowledgements: We would like to express our thanks to the following institutions and persons for their extensive assistance with the data: (1) Department of Statistics (DOS), (2) Malaysia Productivity Corporation (MPC), (3) Malaysian Industrial Development Authority (MIDA), (4) Malaysian Railway (KTMB), (5) Central Bank of Malaysia, (6) Malaysian Communications and Multimedia Commission (MCMC), (7) Ministry of Finance (MOF), (8) Ministry of Transport (MOT), (9) Human Capital Development Section, EPU, and (10) Ms. Sa’idah Hj. Hashim, Statistician, Distribution and Corridor Development Section, EPU.
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Measuring the Contribution to GDP and Productivity of the Malaysian Services Sector
Executive Summary
The services sector occupies a large and growing component of the Malaysian
economy, accounting for nearly 54 percent of aggregate production and 57 percent of
national employment. Of the 1.9 million jobs that were created during the past ten years,
fully 1.8 million were located in the services sector. As levels of income per capita
continue to rise in Malaysia, the emphasis on services as a source of employment creation
and income growth can be expected to increase.
The purpose of this study is to examine the performance of the Malaysian
services-producing industries in detail, both in comparison to the goods-producing sector
as well as the services-producing industries in other countries. The study has six primary
components. First, in order to provide a macroeconomic context, we compute measures
of labor productivity and total factor productivity (TFP) growth at the level of the total
economy and three major sectors of agriculture, industry, and services. Second, we
extend the productivity analysis to the level of the 12 principle service-producing
industries, and compare their performance with comparable industries in Korea, Taiwan,
and Thailand. Third, we use available data on five detailed industries (airlines, banking,
telecommunications, land transport, and port operations) to construct measures of
productivity performance, with an emphasis on international comparisons where possible.
Fourth, we analyze the current state of Malaysia’s external trade in services, and its
potential for growth in the future. Fifth, we consider how changes in the educational
attainment of the workforce contribute to the performance of the services sector, and to
economic growth more broadly. In a concluding section, we provide a brief report on the
quality of the available data necessary to compute indicators of economic performance
and suggest areas of greatest need for improvement.
I. Macroeconomic Overview
The Asian financial crisis of 1997-98 had a severely negative impact on the
Malaysian economy; and despite a strong recovery, GDP growth remains significantly
below that of the pre-crisis years. GDP grew 9.4 percent annually during the ten-years
preceding the crisis, and a reduced rate of 5.6 percent annually in the years since 1998.
The growth accounting framework allows us to allocate Malaysia’s economic
growth among the contributions of changes in factor inputs (labor and capital) and a
residual called total factor productivity (TFP), which measures any efficiency changes in
the use of those inputs. Our initial growth accounts for the total economy decompose the
slowdown in output growth noted above into changes in employment and changes in
output per worker.
• Roughly a third of the decrease in output growth stems from a slower expansion of employment. The majority is a result of slower growth in output per worker.
• A reduced rate of capital accumulation is the principle cause of the slower growth in labor productivity, while gains attributed to both the educational attainment of the workforce and TFP remained relatively constant during the two sub-periods.
We conclude that within the growth accounting framework outlined above,
Malaysia’s sustainable rate of GDP growth appears to be 6 ½ to 7 percent per year.
Surprisingly, it is the current low rate of capital accumulation in Malaysia that appears to
be the main supply-side contributor to slower growth, a phenomenon that is evident in the
fall in the investment rate from above 40 percent during 1995-97 to around 20 percent in
more recent years.
Disaggregating the growth accounts by major sectors highlights the importance of
the service-producing industries as a driver of economic growth.
• Agriculture: The importance of agriculture has declined over time, with its share of GDP falling from nearly 20 percent in 1987 to around 7-8 percent today. Yet, the agriculture sector has maintained strong rates of improvement in labor productivity, resulting from increased capital per worker, and more recently, gains in TFP.
• Industry: Output growth slowed considerably after the financial crisis, from a spectacular 11 percent annual rate to 5.4 percent during 1998-07.
Employment growth, however, fell even more dramatically, down to a 1.4 percent growth during the post-crisis period, and therefore labor productivity actually accelerated in the more recent period. Capital per worker appears to be the main source of the acceleration in labor productivity growth, while the gains in TFP have slowed modestly.
• Services: Output growth also slowed substantially after 1997; however unlike the industry sector, employment growth has remained strong. The result has been a significant falloff in the improvement in labor productivity, from a remarkable 6.4 percent per year during 1987-97 to only 1.8 percent in 1998-07. The contributions from capital per worker also slowed in the latter period, and importantly, TFP growth in services fell dramatically, from 4.4 percent annually to just 1.3 percent in the post-crisis years.
Finally, increases in labor productivity within each sector are not the only source
of economy-wide levels of output per worker; efficiency gains have also resulted from
the movement of workers from low productivity sectors to those with higher productivity.
This “reallocation effect” was very large in the rapid growth era of 1987-1997, adding
about one percent of growth a year, but has had a negligible impact since 1998.
II. Service-Producing Industries
We use additional information supplied by DOS to extend our growth accounting
framework to 12 service-producing industries for the complete period of 1987-2007. The
strong growth in output and labor productivity noted previously for the services sector is
a pervasive characteristic of the underlying industries. High growth rates in the
communications and finance industries are expected, due to increased use of new
information and communication technologies. However, areas such as wholesale and
retail trade and hotels and restaurants also show surprisingly large gains in labor
productivity growth. Our finding of persistent productivity improvements for public
administration is a bit more puzzling, as the national accounts normally incorporate an
assumption of no productivity growth in that industry.
For seven major service-producing industries, we have sufficient data to
deconstruct the gains in labor productivity into the contributions from increased physical
capital, improved human capital (education), and TFP. The results for the full period
display relatively minor variations in the contributions of increased capital per worker
and education, and most of the cross-industry variations in labor productivity
improvement can be attributed to differences in TFP growth.
• The most striking result of this analysis is the magnitude of the slowdown after the financial crisis of 1997-98.
• The slackening of labor productivity growth for finance, business services, and transport and storage industries are predominantly a result of a falloff in rates of TFP growth, whereas the other industries display a more balanced reduction in both capital accumulation and TFP.
• Finally, the contribution from the reallocation effect falls sharply from 1.1 percent per year during 1987-97 period to only 0.1 percent in 1998-07.
We provide an additional perspective of the performance of the service-producing
industries in Malaysia through a comparison to similar industries in other Asian
economies. First, we calculate productivity levels for the major service industries for
Korea, Taiwan, and Thailand measured both in U.S. dollars (using commercial exchange
rates) and international PPP dollars for comparison with Malaysia. Relative to Thailand,
Malaysia has a higher than expected (taking into account levels of GDP per capita)
productivity in trade and finance, but lower than expected in hotels and restaurants and
public services. With regard to Korea and Taiwan, the utilities, transportation,
communications, and “other services” industries have relative levels of labor productivity
that are comparable to differences in overall GDP. Malaysia appears to do well in
finance in comparison to both countries, and in trade, accommodations, and business
services with those in Korea. Interestingly, the productivity levels for government
services are unusually low in Malaysia compared to the other Asian countries.
In addition, we compare the rates of growth in labor productivity across the four
economies, and in this respect the considerable strength of the Malaysian services sector
becomes more apparent. Malaysia has the highest rate of growth of the services sector in
aggregate terms, and the gains in productivity for finance are particularly large.
III. Selected Industries: Performance and Competitiveness
In the third section, we undertake a more detailed analysis of the performance and
competitiveness of five key service-producing industries: airlines, banking,
telecommunications, land transport, and port operations. Where possible, we develop
output indicators in physical units rather than in currency units in order to circumvent the
need for output price deflators and facilitate cross-country comparisons.
Airlines
The data on airlines operations cover the period 1990-2007 and are based on
annual reports and other financial statements from the two largest domestic airline
carriers: Malaysian Airlines and Air Asia. Air traffic has grown substantially over this
seventeen-year period, due in large part to the rapid expansion in recent years of the low-
cost provider, Air Asia.
• Output growth averaged 7.4 percent annually for the whole period, although there is the typical slowdown beginning in 1998-99.
• Since employment growth has remained modest in air transport, most of the output growth can be attributed to improvements in labor productivity.
o During the period 1990-1999 the gains in labor productivity were split evenly between increases in capital and gains in TFP.
o Since 1999, however, the increase in output per worker has been due almost exclusively to expansion of Air Asia, and the TFP gains have slowed considerably.
At the international level, we relied on firm-level financial reports of Thai Air and
Singapore Air, as well as an average of 10 major U.S. airlines, to compare with Malaysia
Airlines. Although labor productivity has improved in all four instances over the period
1991-2007, both Malaysia Airlines and Thai Air have lagged behind the average
productivity level of Singapore Air and the U.S. average. The implications of this result
are ambiguous, however, as the lower average wage rates of Malaysia and Thailand
would imply greater use of labor to improve service. Similarly, the lack of any control
for quality in air travel also limits the results of our analysis.
Banking
Similar to other Asian economies, the banking sectors in Malaysia has attracted
particular attention, and underwent significant change, due in large part to its central
position in the Asian financial crisis. Our calculations indicate that the banking industry
has expanded very rapidly over the past 16 years, despite a marked slowdown which
occurred after 1997-98.
• Real output increased at a 15 percent annual rate during the pre-crisis period, and 7 percent annually since 1998.
• Growth in output predominantly consists of improvements in labor productivity, which is expected as the industry is a primary user of new information technologies.
• In both periods, increases in physical capital account for more than half of the output gains, while another third comes from strong TFP growth.
International comparisons of bank output and productivity are limited due to the
difficulty of attaining comparable units of measurement across national borders. The use
of commercial exchange rates to convert currency units is inappropriate with respect to
the banking industry, as banking services are not sufficiently traded in international
markets to achieve a cross-border equalization of prices. Alternatively, we use physical
indicators to compare banking use, but are restricted to a comparison of Thailand and
Malaysia due to the limited availability ofdata from other countires. We find that the per
capita use of banking services in Malaysia in 2005 is almost double that of Thailand; but
that labor productivity within the banking industry is roughly equal in the two countries.
Telecommunications
As a result of the dramatic expansion of mobile phone technology, the
telecommunications industry in Malaysia has achieved an impressive expansion of
service and infrastructure in a relatively short period of time. Statistics on Malaysia’s
market for telephone services show a dramatic growth over the past 16 years, from a very
low penetration rate of 9 percent in 1990 to over 90 percent of the population by the end
of 2006. Similar to other emerging markets, the phenomenal growth in market
penetration in Malaysia is composed almost exclusively of expansion in the mobile
network. Due to the low cost of a mobile-intensive network relative to a predominantly
fixed line network, emerging markets such as Malaysia tend to have significantly higher
labor productivity and lower capital intensity than higher-income countries such as the
United States in telecom services.
Measures of revenue per subscriber indicate that the phone network in Malaysia
lies somewhere in between that of Thailand and Singapore with regard to the price and
utilization rates of phone services. One particular handicap that results from emphasis on
a mobile network is the lack of infrastructure needed for broadband serivces. The
penetration rate of internet services has leveled out at about 15 percent of the population,
and the use of broadband services is even lower.
An alternative method of analyzing the performance of the Malaysian telecom
industry is through a comparison of prices with those of other emerging and high-income
countries.
• Both mobile and fixed line services are less costly in Malaysia compared to Korea and the OECD average using commercial exchange rates.
o However, prices are similar to those of Mexico and considerably higher than in Korea if we use PPP exchange rates.
• A comparison of broadband prices, measured on the basis of megabits per second, show Malaysia’s effective prices are far higher than Korea or the OECD average, but comparable to Mexico.
Land Transport
The land transport industry is particularly important due to its role as a logistics
system that is vital to the performance of a host of other industries, most notably
manufacturing. We have constructed estimates of productivity for both road haulage and
rail transport, relying in part on surveys of the industries conducted by DOS.
Rail Transport. The data on the performance of the rail transport industry in
Malaysia were supplied by KTMB. Since the operations of KTMB constitute a
substantial majority of all rail transport operations in Malaysia, an analysis of this data
should reflect the performance of the industry more broadly. To combine the three
components of the KTMB rail system into a single measure of output, we use a weighted
average of the passenger-ton kilometers of the commuter and intercity systems, and the
ton-kilometers of freight service.
• The growth of output is driven in large part by the rapid expansion of the commuter sector, averaging 13 percent annual growth during 1996-07.
o In contrast, output in the inter-city and freight sectors declined at an annual rate of 0.4 percent.
o Thus the combined measure of KTMB output shows negligible growth in the early years of the period, and then substantial gains beginning in 2003, once the share of the commuter sector grew in relation to the total.
• Employment growth is negative in the early years of the period and constant after 2000, and gains in labor productivity account for the entirety of output growth.
o Increases in capital equipment have been positive but negligible, and therefore the bulk of output growth can be traced to improvements in TFP, at an average increase of 3.3 percent over 1996-07.
Road Haulage. Due to a lack of physical measures such as freight moved or
estimates of freight rates, our analysis of the road haulage industry relies on firm-level
surveys conducted by DOS. Although these surveys contain much of the information
necessary to compute measures of productivity, they suffer from an inconsistent level of
coverage over time, for which we attempt to correct using adjustment ratios where
possible.
• Estimates of output, employment and capital stock suffer from excessively large year-to-year variability, which we attribute to the variation in the survey coverage.
• The variability in coverage is less of a problem over longer time periods, and so we construct growth accounts for 1990-97 and 1998-05.
o Output growth slows from an average annual rate of 8.3 percent in 1990-97 to a 3.6 percent average in 1998-05.
o Employment declines more modestly, therefore labor productivity growth falls from 4.4 percent annually before 1997 to a 1 percent average in the second period.
Seaports
Malaysia’s port operations appear to perform well when judged by various
international standards.
• The Global Competiveness Report ranks Malaysia’s ports as 13th in the world, surpassed in East Asia only by Singapore and Hong Kong.
• Output, measured by tonnage throughput, has been growing at an 11 percent rate (2000-07), far above that of Singapore, Taiwan, or Korea.
• The percent of containerized traffic has increased over time, and the level now is comparable to that of Singapore.
We construct the necessary data for productivity calculations by matching annual
data from the census surveys of nine port authorities covering the period 2000-2005 to
output measures of cargo throughput provided by the Ministry of Transport. The results
of these calculations show:
• Strong output growth of 8 percent annually has been evenly split between increases in employment and labor productivity.
• Capital per worker appears to have declined over time, implying a substantial increase in capacity utilization. As a result, TFP growth records strong gains of 5 percent annually.
IV. External Trade in Services
Historically, Malaysia has been very cautious in easing the restrictions on foreign
entry and participation in the service-producing industries, out of concern for the
competitiveness of its domestic firms. However, as a signatory to GATS, it has indicated
its intention to expand foreign involvement in the services sector. Our analysis of
balance of payments data provided by the IMF lead us to the following results:
• Thus far, tere is little evidence of any impact of GATS on services trade in Malaysia
• Malaysia has a strong surplus in tourism but a deficit in transportation in services trade
• Surprisingly, trade in business services has actually shrunk over the period of 1996 to 2006.
• Singapore appears to be the model for the potential of services trade, with strong growth in business services anad a substantial services trade surplus.
V. Educational Attainment
High levels of educational attainment are particularly important for the services sector
as many service-producing industries – such as finance, health-care and education –
require a highly skilled or specialized workforce. We can estimate the productivity of
education through analyzing the differing levels of income that accrue to various levels of
education. Using data from four years of the Malaysian Household Income and
Expenditure Survey, we estimate the return to education by regressing the log of monthly
earnings on years of schooling, along with other control variables such as age and gender.
• The regression results report a fairly stable return to education of about 10 percent for all four surveys, covering the period 1995 to 2004.
• If we drop our assumption of a linear relationship of income and years of schooling, we find that workers with a college diploma earn a 60 percent premium
over those whose highest attainment is at the secondary level. Yet, the largest incremental returns per year of schooling occur upon completion of secondary school and post-graduate studies.
VI. Service-Sector Statistics
With the increasing evidence of the service-producing industries as a source of
significant economic growth and employment, many national statistical agencies are in
need to expand their statistics on services. Malaysia is no exception in this regard. From
the perspective of this study’s emphasis on the performance of the service-producing
industries, three key data priorities have emerged:
• Service Industry Output: In recent years, the DOS has expanded its statistics on the services sector. On particular, the degree of industry detail on value-added in the national accounts has been greatly increased. However, the underlying data sources – a set of industry surveys – produces unreliable indicators of change due to the lack of a reliable business registry from which a “census” of active establishments can be based. Second, the statistical system needs to increase the amount of information on service prices.
• Investment and the Capital Stock: The absence of measures of the capital stock by industry is a major shortfall of the statistical system. It results from the fact that the DOS produces no public statistics on the composition of fixed investment by either industry or type of capital..
• Industry Level Employment: Statistics on employment at the level of detailed service industries are limited in large part because the household-based labor force survey is not designed to provide reliable composition of employment below the level of major sectors. This gap could be filled as par of an effort to improve the quality of the existing surveys of the service-producing industries.
VII. Policy Implications
Regarding policy implications, the report identifies three important areas for
further review. First, services trade in Malaysia would benefit from a liberalization of the
regulatory structure and increased access to foreign firms’ involvement in services-
producing industries. Second, expansion in areas such as business services will depend
greatly on the strength of university education in Malaysia, and therefore improving
graduation rates and enhancing the quality of tertiary education are areas in need of
improvement. Finally, we argue that policies aimed to spur competition in services
industries may help to further efficiency gains and therefore lead to increased
competitiveness in international markets.
Measuring the Contribution to GDP and Productivity of the Malaysian Services Sector
Services occupy an increasingly important position in the economy of Malaysia.
In the past ten years, output of the service-producing industries has grown at an annual
rate of 5.5 percent compared to 3.5 percent for industry. Adjusted for inflation, the share
of services production in GDP has risen from 42 percent of GDP in 1987 to 54 percent in
2007. In the ten years of 1997 to 2007, 91 percent of total job growth (1.8 million) was
in the service-producing industries. As incomes in Malaysia catch-up with those of the
high-income industrial countries, this pattern of a growing emphasis on services as a
source of growth in employment and incomes can be expected to continue.
Services comprise a very diverse set of industries about which it is difficult to
generalize. They differ from goods in that they cannot be stored and must in general be
consumed at time of purchase. Services-based activities include: assisting in the
production of other products such as managing the transportation and distribution of
products (logistics), services directed to final demand (personal services and retail trade),
services aimed at improving the quality of other inputs (education and R&D), and
services designed as a general infrastructure of inputs into other industries (finance and
business services). In most of the following discussion, we will use the classification of
industries that is incorporated in the 1993 version of the international system of national
accounts (SNA93) which was recently adopted in Malaysia.
Most countries experience a shift of output toward services as per capita incomes
increase, but the reasons for the shift and its overall implications for growth of the total
economy still generate controversy. Two primary explanations have been given for the
positive association of services with income. On the demand side, it is noted that
services tend to have a higher income elasticity, creating a positive association between
the share of services in total consumption and rising incomes. However, the assumption
of a low elasticity of demand for goods is strongly influenced by the inclusion of food
1
whose income elasticity is low compared to durable goods. In contrast, restaurant meals,
for which expenditures typically rise with income, are classified as part of the service
sector. Outside of food, income elasticities for aggregate goods and services seem
similar. On the supply side, Baumol (1967) argued that the rising share reflects limited
opportunities to raise productivity in many service-producing industries. Wage increases
equal to those in goods production, combined with lower productivity growth, raise
nominal costs in services at a faster rate. The result is a rising share of nominal GDP
being allocated to the production of services, and a belief that the slow productivity
growth in services is a drag on the performance of the overall economy. Thus, for many
years the expansion of the services sector was believed to be a cause for slowing growth
in the aggregate economy.
The whole debate is confounded, however, by difficulties of measuring prices of
services and thus services output. Many countries produce their service-industry
statistics by deflating nominal output with a measure of the price of the inputs – ruling
out productivity growth by assumption – or by simply assuming that service prices rise in
line with the overall consumer price index.1 In the United States, where significant
efforts have been made to improve the measurement of services prices and output, rates
of improvement in labor productivity seem roughly similar in the goods and services-
producing sectors. Recent advancements in information technology have also had a
greater impact on the provision of services, accelerating productivity growth in that
sector (Triplett and Bosworth, 2004).
The purpose of this study is to examine the performance of Malaysia’s services-
producing industries in detail. How do measures of economic performance, such as labor
productivity, compare with those of the goods-producing industries and with similar
services-producing industries in other countries? It provides a basis for evaluating
policies aimed at improving the efficiency and competitiveness of the sector. The study
has six primary components. First, we compute measures of labor productivity and total
factor productivity (TFP) growth at the level of the total economy and the three major
1 A number of the difficulties surrounding the measurement of services were highlighted in Griliches (1992).
2
sectors of agriculture, industry and services. This portion of the analysis is designed to
provide a macroeconomic context for the more detailed examination of individual
industries that follows. Second, we evaluate the performance of service-producers at the
level of 12 principle service-producing industries, and compare their performance with
comparable industries in Korea, Taiwan and Thailand. Third, we use the available data
for five industries (airlines, telecommunications, banking, land transport, and port
facilities) to construct more detailed measures of productivity performance and attempt to
compare or benchmark their performance to that of similar industries in other countries.
Fourth, we look at recent developments with respect to Malaysia’s external trade in
services. Changes in information and communication technologies, together with the
adoption of the General Agreement on Trade in Services (GATS), has increased the
potential for international trade in services. Fifth, we consider how changes in the
educational attainment of the workforce contributes to the efficacy of the services sector
and economic growth more broadly. Finally, in a concluding section we use the results
of the analysis to report some findings about the quality of the available data on output
and economic performance in the services-producing industries and suggest areas of
greatest need for improvement.
I. Macroeconomic Overview
Malaysia was severely affected by the financial crisis of 1997-98 that impacted
several of the East Asian economies. Output fell by 7 percent in 1998; and, although the
country had one of the strongest recoveries from the crisis, the growth of potential GDP
has remained far below that of the pre-crisis years. As shown in figure 1, GDP growth
averaged a remarkable 9.4 percent annually in the ten years preceding the crisis and 5.7
per year in the years since 1998. Surpluses on the current account have permitted a
substantial buildup of external reserves; and, combined with restructuring of the financial
sector, the economy has been made less vulnerable to external financial shocks.
However, the 2001 global recession in IT-related products emphasized the need to
broaden the economy beyond the export of electronic manufactures. In the next section, a
set of growth accounts, covering the total economy and the three major sectors of
3
agriculture, industry, and services, is used to highlight some key features of growth in
recent years.
Growth accounts.
The growth accounting framework allows us to allocate the growth in output
among the contributions from changes in factor inputs (capital and labor) and a residual,
typically called total factor productivity (TFP). In this context, TFP is best interpreted as
a measure of improvements in the efficiency with which the factor inputs are used.
The methodology is explained in more detail in Appendix A, but essentially
indexes of the growth in the capital and labor inputs are combined into a single index
using shares of capital and labor income weights, and the excess of the growth in output
relative to that of the inputs is attributed to TFP. The measures of output (value added)
are taken directly from the national accounts as published by the Department of Statistics
(DOS).2 The employment estimates are obtained from the labor force survey, which is
also conducted by DOS. The measures of the labor inputs are also adjusted for the
improvement in quality that results from increased levels of education.3 The measures of
educational attainment are obtained from the annual labor force surveys.
The greatest difficulties arise with the measurement of the capital input. At
present, DOS does not publish estimates of capital investment or capital stocks at the
level of individual industries. To fill this gap, we have relied on measures that have been
prepared at the Malaysian Productivity Corporation, but they are based on very limited
data. The absence of more detailed estimates of the capital input is a major limitation of
the productivity analysis.
Second, the Malaysian national accounts do not include estimates of labor
compensation by industry. The growth accounts use factor income shares as weights in
2 The analysis is based on the new national accounts with 2000 as the benchmark year. The data for years prior to 2000 (1987 base) were linked at the sector level with a ratio adjustment in 2000. Thus, the growth rates of the old series were maintained. 3 Again, details of the adjustment are provided in the appendix but it is based on the assumption that the earnings (productivity) of workers in Malaysia rise by an average of seven percent for each year of schooling. In a later section, we examine the relationship between education and increases in the earnings of workers – and by association their productivity.
4
measuring the contributions of capital and labor. At present, measures of labor income
are available only for the benchmark year of 2000. Consequently, the growth accounts
are computed using the 2000 income shares for all years.4 As discussed later, the
resulting labor shares are very low compared to the experience of other countries,
averaging only 0.4 for the total economy.
Total Economy.
A summary of the results for the total economy are shown in table 1. The table
highlights three periods: the full span from 1987 to 2007, the pre-crisis years of 1987-
1997, and a post-crisis interval that skips over the recession of 1998.5 The first row
shows the average annual rate of growth in total GDP. The economy did rebound from
the 1997-98 crisis, but the average growth rate appears to have declined by about 4
percentage points per year. While a 5.7 percent annual rate of growth is still remarkable
by international standards, it reflects a common phenomenon that large transitory shocks
seem to have substantial permanent costs when they occur in high-growth economies. It
is not easy to get the economy expanding again at the prior high rate. Roughly a third of
the lower output growth was reflected in a slower expansion of employment, shown in
the second row. A portion of the employment slowdown can be attributed to underlying
demographic trends with a reduced rate of growth in the population of labor force age
(15-64); but the bulk of the falloff has translated into higher unemployment and a decline
in the labor force participation rate.
The growth in output per worker (labor productivity) is reported in the third row
of the table. Much of the discussion in later sections focuses on this basic performance
measure. It provides a simple indicator of economic efficiency and it is the fundamental
determinant of improvements in real wages. It accounts for the majority of the slowing
of GDP growth, an average reduction in annual growth of 2.6 percentage points after
4 The assumption of constant factor shares may not be a serious limitation since they are normally quite stable in countries where the data are available. 5 The exclusion of the 1997-98 recession is consistent with the focus on longer-term growth rates. While the post-1998 recovery is implicitly included, the estimated trend growth rates are not significantly affected by excluding the 1998-99 change. Nor would the pre-crisis growth rate be substantially altered by the exclusion of the 1996-97 change.
5
1998. The decomposition of the changes in labor productivity, shown in the remaining
lines, indicates that all of the falloff in productivity growth can be attributed to a slower
accumulation of capital per worker. The contribution of improvements in educational
attainment of the workforce continued at the prior pace, and gains in TFP averaged 1.7
percent per year in both sub-periods. However, the average gain of only 0.9 percent per
year for the full two decades, shown in the first column highlights the magnitude of loss
in the intervening crisis period.
Within the above growth- accounting framework, Malaysia’s sustainable rate of
GDP growth would appear to be 6½-7 percent per year. A sustainable growth rate is
computed on the assumption that capital will grow in line with output. Thus, we assume
that the labor force will grow at two percent annually, slightly below the average of the
last decade, and that improvements in education can continue at past rates, yielding a
growth in the effective labor supply of 2½-3 percent per year. Second, the continuation
of past rates of improvements in TFP and a balancing rate of capital accumulation would
add the equivalent of another four percentage points of growth. However, as mentioned
earlier, the estimated labor share that we are using seems low relative to international
experience, and a higher estimate would lower the potential growth rate toward six
percent per year. Surprisingly, given Malaysia’s prior reputation for high rates of capital
accumulation, it is the current low rate of capital accumulation that emerges as the major
supply-side contributor to slower growth. This is most evident in the fall in the
investment rate from above 40 percent of GDP in 1995-97 to only about 20 percent in
recent years, below the rate needed to support a 6-7 percent growth of GDP.
Major Sectors.
The disaggregation of the growth accounts by major sector provides some
additional insights into the sources of the post-crisis slowdown and it highlights the
importance of the service-producing industries. The results for agriculture, industry and
services are shown in table 2. The agricultural sector includes forestry and fishing.
6
Industry includes mining, manufacturing and construction. The services sector is made
up of all the other industries.6
The importance of agriculture in the economy has steadily declined over time in
the face of faster growth in industry and services. Its share of GDP has fallen from 20
percent in 1987 to 7-8 percent today. However, as shown in the top panel of table 2, it
has been a consistent source of strong gains in labor productivity, as its share of total
employment has fallen even faster, from 31 percent in 1987 to 15 percent in 2007.
Historically, the gains in labor productivity were due to increased capital (mechanization)
per worker, but in recent years there have been significant gains in TFP.
The results for industry are shown in the middle panel of the table. Output growth
has slowed substantially, from an 11 percent annual rate before the financial crisis to 5.4
percent in 1998-2007. The crisis was a major shock to the sector as output fell by 11
percent in 1998 and employment declined by 5 percent. In subsequent years, however,
the pace of improvements in labor productivity has actually accelerated, with the result
that employment growth has fallen off from 8 percent per year in the pre-crisis period to
only a 1½ percent rate. Even with the generally low rate of capital formation, capital per
worker has increased in recent years and seems to be a major source of the improved
performance of labor productivity. TFP growth has remained strong, but at a lower rate
than before the crisis, 2.2 versus 3.4 percent per year.
The industry sector in Malaysia is dominated by the very strong performance of
manufacturing, which has been the focus of much of the discussion of Malaysia’s
development. Although, it is not central to this study, we report the results for
manufacturing, for comparative purposes in the addenda of table 2. In the pre-crisis
years, output expanded at an extraordinary 14 percent annual rate for a decade, and
employment grew at an eight percent rate. The result was very rapid gains in labor
productivity; and because the capital-labor ratio fell, the gains in TFP were even larger
than for labor productivity, 7.8 percent annually. Since the crisis, both output and 6 Malaysia, together with the United States and a few other countries, uses a definition of the major sectors that differs from standard practice by including public utilities within services, rather than goods. This study follows the Malaysian definitions.
7
employment growth have slowed dramatically with the result that labor productivity has
continued to grow in excess of five percent per year.
The services sector, as shown in the third panel of table 2, has been an area of
rapid growth, equal to that of industry. It too has suffered a substantial slowing of output
growth after 1998; but unlike the situation in the industry sector, employment growth has
remained strong. The offset has been a major moderation of growth in labor productivity,
from an incredible 6.4 percent per year in 1987-97 to 1.8 percent per year in 1998-2007.
The prior high rate is particularly surprising given services’ international reputation as a
sector of low productivity growth (Baumol, 1967). The productivity slowdown can be
attributed both to a reduced contribution of capital per worker and somewhat smaller
gains in TFP.
Given the difficulties of measuring service prices, it is possible that the rapid rate
of productivity improvement in services reflects an underestimation of price inflation.
Between the two benchmark years of 1987 and 2000, the annual rate of increase for the
services price deflator averages 3 percent compared with 3.8 percent for total GDP. In
2000-07 the differential is larger – a 1.4 percent inflation rate for services versus 3.5
percent for GDP. While the differential in the rate of price change is consistent with an
argument that the volume of services output is overstated, it is not large enough to
account for the large increase in measured productivity growth in the pre-crisis period.
However, the inflation differential has widened in the post-2000 data.
A second area of concern is centered on the low income share that we have
assigned to the labor input. The Malaysian national accounts do not include estimates of
labor compensation at the level of individual industries. Thus, we used the compensation
values reported in the 2000 I-O table. The estimates were multiplied by the ratio of total
employment to employees in each industry to account for the implicit labor contribution
of the self-employed and unpaid family workers. However, even with this adjustment the
average labor share was only 0.27 in industry and 0.41 in services. This is substantially
below the 50-70 percent share that is typically encountered in other countries. We
computed an alternative estimate from the wage and employment data of the household
income and expenditures survey. Those shares, however, were only about 20 percent
8
higher. We also examine the level of employee compensation reported in the distribution
and use of income accounts for 2000 to 2003. As shown in Appendix table 1, the
macroeconomic data are consistent with the I-O table in showing a low share of
compensation in national income.
The labor share matters for purpose of computing TFP because TFP is equal to
the difference between the growth in output and a weighted average of the inputs. If the
capital and labor inputs change at significantly different rates, the estimated
improvements in TFP will be sensitive to the relative factor income shares. To explore
the sensitivity of our conclusions, we recomputed the growth accounts using a range of
different values for the labor share, ranging from the current average of 0.375 for the total
economy up to 0.7. The values for the individual sectors were scaled up proportionately.
Those simulations are summarized in Appendix table 2. The result was a substantial
change in the pattern of TFP growth in agriculture, where there is a large difference in the
growth of employment (negative) and capital (positive): a larger labor share shifts the
weight to the slowly growing factor and increases the residual estimate of TFP. In
contrast, the alternative shares have modest impacts on the estimated TFP in industry and
services, where both employment and the capital stock have been expanding over time.
From the perspective of our focus on the service sector, the low share of compensation in
value added is a surprise, but it does not appear to have a critical effect on the
conclusions about productivity improvements.
Finally, improvements in the economy-wide average level of output per worker
result not only from increases in labor productivity within each sector, but from
movements in labor from low productivity sectors to those with higher productivity.
These reallocation effects are not fully captured in a discussion, like the above, that is
limited to productivity developments within each of the sectors. Their importance
depends both on the magnitude of differences in labor productivity across the sectors and
the extent of change in the distribution of employment.
Measures of the level of labor productivity in each of the three major sectors are
shown in the top panel of figure 2. The sector differences are relatively small in
Malaysia. Output per worker in industry has ranged between two and three times that of
9
agriculture, and the productivity of services lies between the other two. In 1987-97, the
productivity gap between industry and services narrowed substantially, but it has widened
again more recently. Each sector’s contribution to the economy-wide average
productivity can be represented by its share of total value added multiplied by its rate of
productivity growth. The difference between the growth of labor productivity at the level
of the total economy and the sum of the weighted sector contributions provides a
(residual) measure of the effects due to labor reallocation. Those results are shown in the
bottom panel of figure 2. The reallocation effect was very large in the rapid growth era
of 1987-97, adding about one percent per year, but it has had a negligible role since 1998
because the growth of employment in industry has slowed.
In summary, Malaysia has experienced a significant slowing of growth since the
1997-98 financial crisis. The slowdown is most evident in a reduction in the pace of
productivity improvements, but employment growth has also been reduced by about a
percentage point per year. Most of the slowdown in labor productivity can be attributed
to a reduced rate of overall capital accumulation which has never recovered to the pre-
1998 rates. For industry the moderation in the pace of economic growth is most evident
in a much-reduced rate of job creation, but the service-producing industries have had a
significant slowing of both employment creation and productivity growth. The services
sector includes a very diverse set of industries, however, and the next section is focused
on a more detailed examination of output, employment and productivity growth in those
industries.
II. Service-Producing Industries
The output of the services sector is currently equal to that of industry and its share
of total employment has steadily increased from 50 percent in 1998 to 57 percent in 2007.
As part of the conversion to the 1993 System of National Accounts (SNA93), the
Malaysian national accounts have a substantial increase in the number of service-
producing industries with published information on value added. The disadvantage is
that fully comparable data are only available beginning in 2000. However, we have used
additional information supplied by the Economic Policy Unit (EPU) and DOS to
10
construct consistent time series data covering 12 service-producing industries for the
period of 1987-2007. We have matched that with data on employment for the same
industries from the household-level Labor Force Survey. However, at the level of
individual industries, the employment data are erratic in terms of their year-to-year
changes, presumably because the respondents in the survey may not be knowledgeable
about the industry of employment for all of the household’s members. This is a particular
problem for measuring changes over short time periods, and in some cases we have
averaged annual data to reduce the volatility. Similarly it is evident that the detailed
output measures are less reliable for the years prior to 2000.
A summary overview of the 12 industries is provided in table 3. They vary
substantially in size, but the largest industries are trade and finance. Public
administration is a very small share of GDP – 3 percent – in Malaysia, but government
also accounts for 85 percent of value added in education and about 60 percent in health
care. In total, government services are about 6 percent of GDP. There may be some
error in the assignment of workers to specific industries on the basis of the household
survey, but the estimates of value added per worker generally seem reasonable.7 Value
added per worker is very high in public utilities and communications because they are
very capital intensive. The high estimate for finance is surprising, but seems to reflect
the extensive use of financial capital in the banking sector.8
The previously-noted rapid growth of output and labor productivity for the total
services sector is a very pervasive characteristic of the underlying industries. In the
majority of the industries, productivity gains account for more than half of the increase in
output. The performance seems particularly remarkable in areas like wholesale and retail
trade and hotels and restaurants where we would not have anticipated major changes in
efficiency. The gains in retail trade may be reflective of economies of scale as part of a
shift from small single-proprietor establishments to an emphasis on larger stores and 7 The industrial allocation of workers in the LFS is very similar to that reported by DOS in the 2000 input-output table, with the exception that the I-O table has a lower level of employment in wholesale and retail trade and a higher level in business services. This is not a surprise since the LFS is undoubtedly the primary source of information in compiling the employment estimates. 8 Relative to other countries, the labor share of value added in Malaysian banks – 23 percent – is unusually low.
11
malls. The high growth rates for the communications and finance industries are more
expected as reflective of the increased use of information and communications
technologies.
On the other hand, the low rate of improvement in business services is consistent
with much of the international discussion of measurement problems in service-producing
industries. They are often labor-intensive industries in which it is difficult to define a
unit of output for purposes of measuring service price changes (Griliches, 1992). Thus,
many statistical agencies deflate the nominal output with an input (wage) index; and,
unless the share of labor compensation in value added steadily declines, measured labor
productivity will show no growth. The use of an input price to deflate output is also
prevalent in the public sector because the outputs do not have market determined prices.
Therefore, the finding of persistent productivity improvements for public administration
(1.2), education (1.6), and health (2.6) is a bit puzzling.9 The health care industry has a
more substantial private sector component, and it is possible that the national accounts
division has some measure of heath care prices. Still, there is at least some suggestion
that the growth of real value added in the public component of the services sector is being
overstated.
Growth Accounts
For the seven major private service-producing industries, we have some rough
indicators of growth in the capital stock; and we can therefore separate the gains in labor
productivity between the contribution of increased physical capital, improved labor skills
(education) and TFP. Those more detailed growth accounts are shown in table 4 for the
full period of 1987-2007 and two subperiods of before and after the 1997-98 financial
crisis. For the full period, variations in the contributions of increased capital per worker
and education are relatively modest, and most of the cross-industry variations in labor
productivity growth can be traced to differences in rates of improvement in TFP. The
9 Some year-to-year variation in labor productivity can be expected because of changes in the composition of the workforce that are not incorporated in the wage index: for example, a shift toward more educated higher-skill workers. In addition, the 1993 SNA calls for the inclusion of a depreciation charge for physical capital in the measurement of public-sector value added. However, neither of these factors can account for the sustained growth in labor productivity.
12
gains in educational attainment are significant, but they are relatively modest compared
to the increases in other East-Asian economies.
The two sub-periods are initially most striking for the magnitude of the growth
slowdown after 1997-98. The decline is pervasive across all of the industries; and, except
for utilities and communications, they have post-1998 output growth rates that are about
half those of the earlier period. Furthermore, employment growth remains strong in the
second period, so that the slowing of output growth is concentrated in a reduced rate of
gain in labor productivity. The slowing of productivity is particularly pronounced for
utilities, trade, and communications. The deceleration in communications is puzzling
because it occurs during a period of rapid expansion of the mobile phone system in most
countries.10 Labor productivity within business services actually falls in the second
period, but that is largely the result of a strong surge of employment, rather than the
slackening of output growth.11 The LFS reports a strong and sustained surge in
employment for these industries, but the national accounts record an output slowdown
comparable to that for the other service-producing industries. The slowing of capital
accumulation is an important contributor to the reduced rate of gain in labor productivity
in several of the industries, and there are large cross-industry variations in the rate of TFP
increase.
Finally, the comparison of overall service-sector productivity growth with that of
the individual industries also incorporates a reallocation effect, as in the analysis of the
contributions of the major sectors to aggregate productivity change. A shift in the
composition of employment toward industries with above-average productivity levels
will raises the growth rate of labor productivity in the overall sector. The contributions of
each of the industries are reported in table 5. It is evident that large portions of the post-
1997 productivity growth slowdown can be traced to slower gains in trade and business
services; but, in addition, the contribution of reallocation effects falls sharply from a
10 The performance of telecommunications is examined in greater detail in a later section. 11 In the 2000 I-O table, DOS reports a level of employment in business services well-above that of the labor force survey. We do not know the reasons for the difference, and it may be that they transferred employment from other services – a large residual category in the LFS – to business services. The effects on the growth of employment are uncertain.
13
substantia1 1.1 percent per year in 1987-97 to only 0.1 percent in 1998-07. Thus, the
pattern of post-1998 growth, no longer favored the high productivity industries.
On balance, the disaggregated analysis suggests that the Malaysian service-
producing industries have performed well over the past two decades. While output
growth has slowed from the very high rates posted in the pre-crisis years, all of the
industries report continued strong gains in employment and labor productivity. And,
although the data on capital accumulation at the level of individual industries is quite
problematic, lower rates of capital accumulation appear to be contributing to the slowing
of labor productivity gains in several industries.
International Comparisons
An additional perspective on the performance of the services sector is provided by
an international comparison to other strong performers in Asia. Information on output
and employment are available at the level of the major service-producing industries for
Taiwan, South Korea, and Thailand.12 The first two are both higher-income countries
that should be useful benchmarks for Malaysia. Thailand is a neighboring country, but
with a lower level of GDP per capita.
We would like to compare both levels of productivity across countries as well as
their rates of change. International comparisons of productivity levels, however, are
difficult because of problems of converting measures reported in national currencies to
comparable units. The labor input can measured as the number of workers or working
hours, but both output and the capital input are normally defined in national currency
units. The comparison of rates of growth avoids these concerns by focusing on rates of
change.
One approach relies on commercial exchange rates to convert to common
currency units. This method is appropriate for comparing the values of goods that are
traded extensively in international markets where we could expect a cross-border
12 The data for Korea are taken from the STAN database of the OECD. The data for Taiwan are obtained from the web page of the national statistical bureau of the Republic of China (Taiwan): http://eng.stat.gov.tw/mp.asp?mp=5. Labor productivity for Thailand is available in NESDB and World Bank (2007).
14
equalization of prices. The vast majority of services, however, are exchanged across
borders in limited amounts or not at all. The comparison may still be interesting,
however, because the cost of services is a relevant consideration behind the location of
businesses that do engage in international business.
A second approach, employed in comparisons at the level of the aggregate
economy, uses Purchasing Power Parity (PPP) exchange rates that have been constructed
on the basis of a broad sample of individual products, matched across countries. Such
estimates are available for the aggregate GDP of most countries, but there are few
reliable estimates of the PPP exchange rate at the level of individual industries.13 PPP
exchange rates should vary widely across product groups and industries, depending in
part on their exposure to international trade. In addition, most of the underlying price
comparisons of the PPP are based on goods rather than service prices. Despite its
problems, the PPP exchange rate does provide a second basis of comparison and thus
some indication of the range of uncertainty in the exercise. We have used the PPP
estimates for 2005 that were recently released by the World Bank.
Table 6 shows productivity levels for the major service-producing industries for
the four countries measured in U.S. dollars and international PPP dollars. A simple
comparison of relative levels of development is provided by the measures of overall GDP
per capita that are reported at the bottom of the table using both PPP and commercial
exchange rates. Incomes in Malaysia are about two-thirds higher than those of Thailand
and half those of Korea and Taiwan using the PPP measures. The differences based on
commercial exchange rates are larger as Malaysia’s GDP per capita is about twice that of
Thailand and only a third of Korea and Taiwan.
Relative levels of labor productivity in services between Malaysia and Thailand
are generally consistent with the differences in overall GDP per capita; but Malaysia’s
productivity advantage is slightly less than that for GDP per capita. In contrast,
Malaysia’s services sector compares favorably with that of Korea – with levels of labor
productivity that are closer than suggested by the GDP per capita. The overall efficiency
13 The use of industry-specific PPPs is discussed and illustrated in O’Mahony and others (1996); but outside of the EU countries the PPPs generally lack sufficient industry detail.
15
of the Malaysian services sector is about two-thirds that of Korea based on PPP and 40
percent using commercial exchange rates. However, the comparison to Taiwan is
significantly less favorable (37% using PPP exchange rates). Interestingly, although
Korea and Taiwan have similar levels of GDP per capita measured in commercial
exchange rates, Taiwan has a much more efficient service sector – a level of value added
per worker about 40 percent higher with commercial exchange rates and 80 percent
higher using PPP.
Some of the industries within services are aggregated to make the comparisons
because Taiwan has not yet adopted the SNA93 industry classification. However, even
with aggregation, there is substantial variation in the structure of output per worker across
industries and countries. Relative to Thailand, Malaysia has a higher than average relative
productivity in trade and finance, but it is low in hotels and restaurants and public
services.
In the comparison of detailed service-producing industries with those of Korea
and Taiwan, the relative levels of labor productivity are comparable to the differences in
overall GDP for utilities, transportation and communications, and the miscellaneous
grouping of other services. Malaysia appears to do well in finance, and productivity
levels compare very favorably with those of Korea in trade, accommodations, and
business services. In contrast, productivity levels are unusually low for government
services. Since we do not have a market measure of the value of public services, the
result may only reflect a low relative level of compensation for workers in the public
sector in 2005. Measured labor productivity is notably low in Korea’s trade sector –
reflecting, perhaps, the reliance on a large number of small retail shops.
The comparison of recent growth rates of labor productivity within the service-
producing industries is shown in table 7. The annual rates of change in output,
employment and labor productivity are reported for eight comparable industries in
Malaysia, Korea, and Taiwan. Malaysia has the highest rate of growth of overall service-
sector output and productivity, but the differences vary across the industries. Malaysia
shows large gains in labor productivity for finance but lesser improvements in
transportation and communications relative to the other countries; and Malaysia and
16
Korea both report large increases in employment in business services that translate into
significant declines in productivity. Furthermore, the other countries do not report the
previously-discussed strong growth of productivity in public administration. Still, the
international comparison is consistent with the prior finding that the service-producing
industries have been a considerable source of strength for the Malaysian economy.
III. Selected Industries: Performance and Competitiveness
This section provides a more detailed analysis of five key service-producing
industries: airlines, banking, communications, land transport, and port facilities. All five
industries are important parts of the business infrastructure, providing logistics and other
forms of support to the rest of the economy – particularly manufacturing. These are also
industries where it is often feasible to construct measures of output based on various
physical indicators, circumventing the general lack of price deflators for services output.
Output can be defined directly in terms of physical units, such as passenger/ton
kilometers. Banking is a more challenging case because it is difficult to define a
meaningful measure of output; and at the international level, the definition of bank output
has been a subject of substantial debate. However, the banking system was at the center
of the 1997-98 financial crisis, and it is important to assess its performance since that
time.
A second major objective is to construct measures of output and productivity that
will facilitate international comparisons of productivity performance. The prior section
highlighted the wide range of uncertainty implied by the use of PPP or commercial
exchange rates. In the following analysis, a third method is employed in some industries
that relies on quantity indicators that can be directly compared across countries, thereby
avoiding the problem of currency conversions. This method is used for transportation
and telecommunications, industries where output can be defined in terms of ton-
kilometers (transport) and subscriber lines (communications). The problem is that the
output of only a few service-producing industries can be summarized with a simple count
of physical units.
17
Air Transportation
Passenger air transport in Malaysia is largely provided by the national carrier,
Malaysia Airlines, and Air Asia, a rapidly expanding low-cost regional carrier that began
operations in 2001. Malaysia Airlines reported weak financial results for several years,
but it has been through a recent restructuring and return to profitability. Air Asia has
grown very rapidly since its inception, and is now a major supplier in both Malaysia and
the region. About half of the total passenger traffic is out of the Kuala Lumpur Airport,
with Kota Kinabala, Kuching, and Penang being significant secondary ports. Kuala
Lumpur is not a major regional hub for air travel, however, and passenger traffic is about
half that of Bangkok and two-thirds that of Singapore. The result is a limited degree of
international competition.
Output and Productivity. We have been able to compile data on airline
operations covering the years of 1990-2007. In the early years, the data are drawn
straight from the annual reports of Malaysia Airlines; but, beginning in 2001, information
on the operations of AirAsia is also included. The measure of output is constructed as a
weighted average of the total number of passengers, passenger-ton kilometers, and
freight-ton kilometers. On the passenger side, the basic cost model assumes that costs
arise both as a function of the number of passenger embarkations and the distance that
they fly. We obtained the relative weights for passengers versus passenger-ton
kilometers from a dataset of 10 major U.S. airlines over the period of 1990-2006.
Because the U.S. market is largely deregulated, the pricing of the U.S. airlines should
reflect their costs. We estimated a statistical relationship between airline profits and the
number of passengers and passenger ton-kilometers. The results of that estimation led to
the assignment of a weight of 60 percent to the number of passengers and 40 percent to
passenger-ton kilometers. We believe that this measure, by accounting for both the fixed
and variable components of air travel, is a superior measure of industry output compared
to the normal reliance on passenger kilometers.
At a second stage, the shares of revenues from passengers and freight are used as
weights to combine the two components into a single output measure. The resulting
indicator is shown in figure 3 as an index with the 1990 value equal to 100. The figure
18
also shows the separate contributions of Malaysia Airlines and AirAsia to output growth
after 2000. Air traffic has grown substantially over the 17-year period, but the drop in
output of Malaysia Airlines between 2005 and 2007 is clearly evident. The airline scaled
back its operations by about 15 percent during this period.14 AirAsia now accounts for
about 30 percent of total output.15
Measures of productivity performance in the industry are constructed using the
same basic methodology as in the prior discussion of the performance of the major
industries. Total employment is drawn from the annual reports of the two airlines and
excludes airport services. A measure of the capital input is constructed from available
capacity ton kilometers (a common capacity concept in the industry) adjusted to exclude
the increase in the length of the average trip.16 Capacity increased by 75 percent between
1990 and 2007 with a particularly large jump in 2004 when both Malaysia Airlines and
AirAsia expanded their operations. The labor share of 0.45 was computed from recent
annual reports of Malaysian Air, but it excluded the loss-year of 2005: It is held constant
over the full period.
A summary of the productivity estimates is provided in table 8. Output expanded
at a 7.4 percent annual rate over the full period; but, as with other industries, there is a
substantial break in the growth rate at about 1999. Output growth averaged 8.8 percent
per year in 1990-99 and 5.8 percent in 1999-07. In addition, most of the post-1999
growth can be traced to the expansion of AirAsia. Output of Malaysia Airlines slowed to
a 1.2 percent annual rate after 1999.
Increases in employment have been quite modest for the full period with some
additional slowing of growth after 1999. Thus, most of the output growth has been the
result of increases in labor productivity. In the pre-1999 period, the gains were evenly
14 There is also a conversion of Malaysia Airlines from a fiscal year ending in March to a calendar year basis in 2005. The 9-month results for 2005 are raised by 75 percent: a simple adjustment that may exaggerate the peak level of output in that year. AirAsia operations are reported on a fiscal year ending in June. We averaged two fiscal years for purposes of combining with the Malaysia Airlines data. 15 AirAsia has no significant freight revenues. 16 In effect, an increase in the length of trips is categorized as an increase in TFP rather than the capital input.
19
split between increases in capital and improvements in TFP. Since 1999, all of the
increase in the capital contribution has come from the expansion of capacity at AirAsia,
and the overall TFP gains have slowed. Even so, the improvements in TFP may be
overstated, because the output measure does not incorporate any change in quality.
AirAsia is a discount airline with a much lower ratio of employees per passenger. Some
of that difference may represent a lower level of service, which is not reflected in the
output measure.
International Comparisons. At the international level, we have relied on data
obtained from individual company reports. In addition to Malaysia Airlines, we obtained
information for Thai Air, Singapore Air, and the average of a group of 10 major U.S.
airlines, covering the period of 1991-2007. Both Thai Air and Singapore Air are major
competitors of Malaysia Airlines in Southeast Asia, and the U.S. airlines provide a useful
international benchmark.
The output measures were constructed using the procedure outlined above to take
account of both embarkations and passenger-kilometers. In fact, the large differences in
the average length of flights among the international carriers originally highlighted the
importance of including the costs of embarkations. Second, the available data suggested
similar shares of labor compensation in total costs for the three Asian airlines, and we
used 0.45 for the labor share for those three. For the U.S. airlines, however, the average
labor share was 0.65.17 The capital input was again measured as available capacity in
tons.18 Furthermore, we have kept all of the data in level form with common units of
measurement across the comparison groups, rather than converting to indexes or rates of
change.
The comparison of labor productivity is shown in figure 4a. In all four cases,
labor productivity has improved substantially over the 15-year period; but Malaysia Air 17 It is not evident why the U.S. labor share is higher than that of the other airlines, but it was pervasive across all of the years for which we had data. It is consistent with the low profitability of U.S. airlines in a highly competitive domestic market. However, the choice of a specific value does not have a big effect on the estimates of TFP. We assumed constant returns to scale for air transport; thus, the weight assigned to capital is just one minus the labor share. 18 The conversion of the capacity measure from ton kilometers to tons had the largest impact on Singapore Air because it has longer flights than the other airlines.
20
and Thai Air lag behind the average of the U.S. carriers and Singapore Air. To some
extent this result is expected as the latter two airlines have lower average wage rates and
should make greater use of labor to improve service. There is however, some evidence
that the gap is increasing in recent years, as they have failed to match the gains of
Singapore Air and the United States carriers. In 2007, labor productivity for Malaysia
Airlines was only 40 percent of the average of the U.S. carriers.
The relative performance of capital productivity is summarized in figure 4b. Our
measure of output per unit of capital corresponds most closely to the industry concept of
load factor, or utilization of available seats. Again, the U.S. airlines are highest and have
been improving their performance over time. Meanwhile, Singapore Air has experienced
a deterioration in its utilization of capital and has been surpassed by Thai Air. Malaysia
Air appears to have the lowest rate of capital utilization. It is also notable that the range
of variation for capital productivity is less than for labor productivity: an outcome that
may reflect the fact that all of the airlines pay similar prices for the airplanes.
Levels of total factor productivity, efficiency in the combined use of capital and
labor, are exhibited in figure 4c. The U.S. airlines show a strong gain in TFP since 2001,
which was a crisis year for the industry with record rates of reported losses. After
approaching U.S. rates of efficiency in 2000/01, the TFP of Singapore Air has remained
relatively constant. Overall, Malaysia Airlines and Thai Air have very similar rates of
productivity performance that are substantially below the levels achieved by Singapore
Air and the U.S. airlines.
Finally, productivity, or efficiency in the use of the various inputs is only one of
the determinants of airline profitability. While the airlines should have similar costs for
fuel and other purchased inputs, they will vary in their labor costs, and the competition
that they face will have a significant effect on the revenues that they can obtain per unit
of output. Average wage cost per employee in 2006 for Malaysia Airlines and Thai Air
were less than half those of Singapore Air and only a third of the U.S. airlines.
Surprisingly, average wage costs of Malaysia Airlines were slightly below those of Thai
Air. On the revenues side, we find that Singapore Air had the highest revenue per unit of
21
passenger output, followed closely by Thai Air (figure 5). Malaysia Airlines had the
lowest revenue yield.
In summary, Malaysia Airlines operates with levels of efficiency substantially
below the largest international carriers, as does Thai Air. Much of the difference lies in
the area of labor productivity where it may be sensible to have a lower rate, given the
wage rate differences. Importantly, our comparisons suffer from the lack of any measure
of the quality of the air travel. For example, U.S. airlines have gained efficiency in terms
of passengers flown per employee, but the recent gains have been accompanied by
deterioration in many quality indicators.19 There are some international measures of
airline quality, but they tend to be subjective or apply only to specific classes of service.
The most prominent ranks both Malaysia Air and Singapore Air as top 5-star airlines,
Thai Air is a 4-star, and most major U.S. airlines are 3-star. In addition, KLIA airport is
a 4-star airport, one of four and only below Singapore, one of three 5-star airports.20 We
are unaware, however, of any objective measure of the quality of service for international
airlines.
Commercial Banks
Commercial banking has undergone rapid change in both the regulatory
environment and technology over the past quarter century. The innovations in
information and communications technologies (ICT) have found broad applications in the
development of electronic payment systems. Many Asian countries, including Malaysia,
have reorganized their banking systems in the aftermath of the financial crisis, altering
competitive relationships. There is an interest in understanding the implications of these
changes for the productivity and efficiency of the financial system. At the same time,
banking has been unusual among service-producing industries in the extent of research on
methods of measuring output and efficiency.
19 A report on various indicators of quality covering U.S. airlines, including measures such as on-time performance, rates of lost baggage, flight cancellations, and customer complaints, is available at: http://www.aqr.aero/index.htm. 20 Available at: http://www.skytraxresearch.com/General/ranking.htm.
22
Malaysia has maintained a relatively closed market in banking services, limiting
foreign ownership to 30 percent of equity and tightly controlling the number of their
branch banks (including ATMS), which are critical to the competition for deposit funds.
At the same time, the domestic industry has been consolidated into six major banking
groups. These restrictions are reflected in an unusually high profit margin and low share
of labor payments in value added. In practice, the supervisory authorities have focused
on prudential regulation, not the promotion of competition.
Measuring Output. There are two main conceptual approaches to measuring the
output of banking institutions. Under the production approach, the institutions are
viewed as producing services – processing loans and payment instructions for account
holders. Thus, only physical quantities, such as labor and capital, and their costs are
included as inputs into the production function. Under the alternative of an
intermediation model, institutions are viewed as intermediating funds between depositors
and borrowers, and the input of funds (deposits) and their costs are included since they
are part of the raw material that is being transformed in the intermediation process. Our
analysis of the productivity of Malaysian banks emphasizes the production framework
because it is more closely related to the literature on productivity performance in the
nonfinancial sectors of the economy. However, many of the studies of individual banks’
performance in terms of profit and cost efficiency have utilized the intermediation
framework. With the intermediation approach, it is common to emphasize the spread
between asset returns and deposit costs; but it can become difficult to distinguish between
differences in efficiency and productivity. Financial firms can be highly profitable either
because they are efficient or because they operate in markets with limited competition
and thus high margins.
The measurement of banking output is also complicated by the practice of not
explicitly charging for all of the individual services provided to account holders. Instead,
they often pay depositors a rate of interest on deposits lower than they could otherwise
earn on the funds. Thus, neither the fees nor the deposit rate is reflective of the value of
the services provided. The national accounts are adjusted to include an imputed value of
the un-priced services, but there are no accurate measures of transactions prices that
could be used to convert to a measure of the real value of banking output.
23
Within the production function framework there have been two primary
suggestions for measuring bank output. The first assumes that the flow of services is
proportional to the value of deposit and loan accounts. We can use the nominal value of
deposits and loans since such information is regularly collected by the regulatory
agencies. The nominal stocks of deposits and loans, which are readily available from
balance sheet reports of the banking system, are deflated by a broad measure of price
inflation (the GDP price deflator), and combined together into a single output index.21
While banks do not maintain accounting records of the division of costs between deposit
and loan operations, surveys of U.S. banks and interviews with individual banks in other
countries suggest that costs are roughly equal for the two sides of the banks’ operations.
More persons are often employed on the deposit side, but the costs per employee are
typically higher for the lending operations. In addition, the relative weights are not
particularly critical at the level of the total industry because deposits and loans grow at
similar rates.
The second approach to measuring bank output focuses on transactions rather
than the value of accounts. Physical measures of the number of deposit and loan
accounts, check clearing, ATM transactions, and credit card transactions are combined to
construct an overall index of bank output. This follows the methodology developed by
the U.S. Bureau of Labor Statistics and used to measure output in the U.S. national
accounts. In this case, the weights play a larger role because the individual transactions
series can grow at substantially different rates – reliance of checks has been reduced as
customers shift to electronic account management and cash payments are being replaced
by greater reliance on consumer credit and debit cards.22 The current methodology also
ignores the growth of other bank services, such as financial investment counseling.
As shown in figure 6, the two alternative measures of bank output yield similar
estimates of the growth in banking services in Malaysia over the period of 1996-06. The
21 The definition of the banking industry in Malaysia includes commercial banks, Islamic banks, and finance companies. 22 The weights for the individual indicators are based on a functional cost survey of U.S. banks that was last conducted in 1999 (Board of Governors of the Federal Reserve, 2000).
24
final index of output growth is based on an average of the two measures, and the deposit/
loan measure is used to extend the index back to 1990.
Productivity Analysis. We would expect banking to be an industry of
considerable gains in productivity because it is a primary user of the new information
technologies.23 The measures of productivity performance are constructed using the
same basic methodology as in the prior sections and summarized in appendix A. The
estimate of labor input is based on total employment in the industry with a quality
adjustment that reflects the increased educational attainment of the workforce. In the
absence of any other information, we assume that hours per employee have not changed
significantly over the past two decades. The capital stock is based on balance-sheet
reports of the book value of fixed assets. The book value is adjusted to current prices and
then converted to a constant-price measure using the capital goods price deflator of the
national accounts.24 The labor and capital inputs are combined into an overall index of
growth in the inputs using the shares of value added paid to labor versus operating profits
and depreciation. As mentioned above, operating profits are very high in the Malaysian
banking industry, and we have used a labor share that averages only 23 percent of value
added. Total factor productivity (TFP) is measured as the growth in the output measure
less the increase in the index of the combined inputs.
A summary table of the sources of growth in the Malaysian banking industry is
shown in table 9 for the period of 1990 to 2006. First, the industry has expanded very
rapidly over the past 16 years, but there has been a pronounced slowing since the
financial crisis of 1997-98. Real output has increased at a seven percent average annual
rate since 1997 compared with a 15 percent rate in 1990-97. Nearly all of the growth has
been the result of improvement in labor productivity since employment growth has
23 In the United States, government estimates for commercial banking indicate that labor productivity has risen at a relatively modest 2.2 percent per year over 1987-2005. 24 Measures of the capital stock are available only as book values as recorded on bank balance sheets. The adjustment from book to current nominal values is a function of the rate of inflation, and our adjustment is based on the ratio of current to book value observed in the United States. Both countries have had relatively similar paths of inflation over the last two decades, although the rate of capital good inflation in Malaysia has averaged about one percent annually above that of the United States.
25
averaged only about one percent per year. While banks employ workers with above
average levels of education, their educational attainment has remained largely unchanged
over the full period. Increases in physical capital – presumably IT – have accounted for
more than half of the output gains. Another third of the gains have come from
improvements in TFP. The contributions of capital and TFP have both slowed in the
most recent period, but the overall gains in labor productivity and TFP remain
impressive.
The contribution of capital investments to the productivity growth of the banking
industry is surprisingly large. The result is driven by a relatively high share of income
accruing to capital in the Malaysian banking industry. The labor share, shown in the
income and expenditure reports of Bank Negara, is only 20-25 percent of estimated value
added compared to 40-50 percent in most other countries. One possible explanation is
that regulation and restrictions on entry have created monopoly rents in the industry,
because the return to own capital is very high. The annual report of one of Malaysia’s
largest banks shows the same low share of labor compensation in net income.
Furthermore, although the national accounts do not publish separate information on
commercial banks, the 2000 I-O table reports a labor share of 27 percent.
International Comparisons. Cross-border banking studies have been quite
uncommon; and those that have been done focus on the performance of individual banks
rather than national banking industries. In addition, most of the studies emphasize
efficiency in terms of cost minimization or profit maximization rather that attempting to
derive formal estimates of productivity. Frontier analysis, for example, is a means of
quantifying the relative ranking of individual firms by their performance on a set of
efficiency concepts. A variety of parametric and non-parametric techniques have been
used in this regard. The basic objective is to measure banks’ performance relative to a
best practice frontier of the best-performing firms in the sample. While the techniques
have been frequently applied in studies of domestic bank performance (Berger and
Humphrey, 1997), there are relatively few examples of cross-border comparisons.
One of the first studies to focus on Asian banks was undertaken by Karim (2001),
who compared the cost efficiency of 155 banks in four southeast Asian economies
26
(Indonesia, Malaysia, the Philippines, and Thailand) over the pre-crisis period of 1989-
96. He used a model based on the intermediation approach to measuring bank output and
concluded that Thai and Malaysian banks were the most efficient and those of the
Philippines and Indonesia were the least efficient.
A second study by Nguyen and Williams (2005) included Korean banks and
spanned the 1990-2002 period, including the years of financial crisis. While their study
emphasized the relative performance of banks with different ownership structures, they
found that Malaysian and Korean banks were the most efficient overall and those of the
Philippines and Thailand were the least efficient. A third study by Brown and Skully
(2006) focused on a singe post-crisis year, 2004, and included banks from a wider
number of Asian countries. Banks in Singapore, Australia, and Hong Kong were the
most efficient, and Malaysian banks were ranked only 10th out of 12 countries,
outperforming only the banks of the Philippines and Thailand.25
These studies used a common data source and converted all the financial data of
the individual banks from national currencies to U.S. dollars using the commercial
exchange rate. However, as discussed in a prior section, cross-national comparisons of
productivity require that output and the inputs be measured in comparable units. The
labor input can be measured as the number of workers or working hours, but both output
and the capital input are normally defined in national currency units. The use of
commercial exchange rates is appropriate only if the products are traded extensively in
international markets where we could expect a cross-border equalization of prices. That
assumption seems particularly inappropriate for banking services, which trade across
borders in limited amounts or not at all. As a result, the reliance on commercial exchange
rates raises significant questions about the interpretation of the existing international
comparisons. Alternatively, the comparison could be based on PPPs; but, while it is
conceptually possible to construct a PPP measure for financial services using cross-
border surveys of the cost of a set of standard financial transactions, specific examples
25 There have been two other recent studies of bank performance in Malaysia, though they do not focus on cross-border comparisons, Mathews and Ismael (2006) and Rosita Suhaimi (2007).
27
are largely limited to the EU countries (O’Mahony and others, 1996). Thus, the PPP
comparison is limited to the use of the aggregate PPP exchange rates.
The third method uses physical quantity indicators that can be defined without
reference to national currency values. We use this method for transportation and
telecommunications, industries where output can be defined in terms of ton-kilometers
(transport) and subscriber lines (communications). However, the output of only a few
service-producing industries can be summarized with a simple count of physical units.26
For example, the method can be applied in banking only for the transactions-based
concept of output.
Our cross-border comparisons of banking output use the physical indicators
method only for Malaysia and Thailand because they are the only countries for which we
had access to matching information for the components of the transactions-based measure
of output.27 We find that the per capita use of banking services in Malaysia in 2005 was
about double that of Thailand, as would be expected from its higher level of income; but
labor productivity within the banking industry is virtually identical in the two countries.
For other countries, we could obtain information only on the level of deposits and loans
per employee. Those countries included Singapore, the United States, and Korea. The
data were converted to U.S. dollars on the basis of both commercial exchange rates and
the 2005 PPPs. The average level of deposits/loans per employee in Malaysia is about
half that of the United States and Korea using commercial exchange rates, but only about
10 percent below on the basis of PPPs. Singapore has a relatively low level of measured
productivity; but the comparison may be distorted by its role as an international banking
center, so that the magnitude of bank services is not well-represented by the volume of
deposits and loans.
26 This method is used in Baily and Zitzewitz (2001) to measure productivity in banking and other service industries for seven OECD countries. 27 Information for Thailand is available as part of a report on Measuring Output in Services, authored by the National Economic and Social Development Board and the World Bank (2008). Although a similar methodology is used for the measure of banking output in the U.S. national accounts, the United States does not currently produce estimates of the number of deposit and loan accounts.
28
It may be possible to extend the transactions measures of bank productivity to
other countries. Many central banks now produce annual reports on their payment
systems that provide information on the use of checks, credit/debit cards and other
electronic transactions, but measures of the total number of deposit and loan accounts are
not generally available in their publications.
Telecommunications
Malaysia’s telecommunications industry has gone through a dramatic revolution
over the past two decades. In the early 1990s, telephone subscribers represented only
about ten percent of the population; but with the introduction of mobile phone service,
the penetration rate (subscribers per 100 inhabitants) has soared to 92 percent in 2006
(ITU 2008). Nearly all of this growth has been the result of the expansion of mobile
services, and the fixed-line penetration rate is still only about 18 percent. Mobile
communications require a much less expensive infrastructure to provide basic service.
Within a decade, Malaysia has been able to upgrade its telecommunications to a level
approaching that of higher income countries, but at a fraction of the cost.
The basic regulatory structure was established with the 1998 Communications and
Multimedia Act. One of the major policy objectives is the extension of coverage to
remote areas – universal service – which is funded with a tax of 6 percent on telecomm
services. The tax offers some advantages over the distorting effects of imposing a system
of cross-subsidies. Regulations still sharply restrict foreign equity participation in the
industry.
Malaysia’s traditional fixed-line service, voice and internet, is dominated by
Telekom Malaysia (TM), which faces little domestic competition. Mobile services are
largely provided by three companies: Maxis, Celcom (a subsidiary of TM), and DiGi.28
The penetration rate for internet dialup accounts is about 15 percent (MCMC, 2008), but
28 In 2006, 41% of mobile phones subscribers were served by Maxis, 34% by Celcom, and 26 % by DiGi. About 80 percent are prepaid accounts.
29
the poor fixed-line coverage limits the penetration rate of broadband in 2007 to only 5
percent of the population (15% of households).29
Data. The telecommunications industry is not separately identified in most
countries’ national accounts where it is combined with postal services and
broadcasting.30 Most of the data for this report were obtained from the International
Telecommunications Union (ITU). However, the country submissions to the ITU are
often incomplete and inconsistent in their coverage. We selected a group of comparator
countries, mostly from East Asia, and supplemented the ITU data with information from
national sources. The basic period of comparison is 1990-2006.31
The growing diversity of telecommunication services also complicates the
computation of a meaningful measure of output. Previously, the choice was between the
number of subscribers and total number of minutes, but current measures of output need
to reflect both fixed and mobile services and the growing importance of the internet and
broadband. This study is limited to statistics on the number of fixed and mobile
subscribers because information on internet and broadband usage is very incomplete in
the ITU data set. Thus, the output measure does not adjust for the intensity of subscriber
use. This may not be a major problem for the historical data; but, with the expansion of
networks to incorporate internet and broadband usage, a more sophisticated measure of
output will be increasingly important for evaluating future performance of the industry.
Since mobile and fixed line subscriptions are growing at dramatically different
rates, it is also important to compute a measure of overall output using up-to-date revenue
29 In comparison, the penetration rate of broadband is 50 percent in Singapore, and 30 percent in Korea and Taiwan (ITU 2008). The estimate for Malaysia is from the web site of the Malaysian Communications and Multimedia Commission (MCMC) at: http://www.skmm.gov.my/index.asp. 30 In the ISIC system, telecommunications are in group 642 with broadcasting. Post and courier services are included in 641. Together, they comprise division 64. The national accounts of many countries continue to combine communications and transportation, despite the dissimilarities of the underlying technological trends. 31 The Department of Statistics has also conducted a series of annual ‘censuses’ of the industry, but variations in the number of firms suggest that they are actually surveys that vary in the proportion of the industry that they cover. As a result they do not appear to provide reliable measures of the change in the industry over time. The ITU data only cover the fixed and mobile service providers, but the coverage is more consistent over time.
30
weights to combine the two types of service. The output index is constructed as a
chained Tornquist index: two-year average shares of revenue are used as the weights to
combine the annual changes in the number of fixed and mobile subscribers. In addition,
we have information from the ITU on the number of employees in the
telecommunications industry, and we constructed a measure of the capital stock by
cumulating ITU data on investment outlays.32
Analysis. As shown in figure 7, Malaysia’s market for telephone services has
expanded at a rapid pace over the last decade. Starting from a very low penetration rate
of 9 percent of the population in 1990, telephone usage has soared to reach over 90
percent of the population by the end of 2006. Yet, that growth is largely due to the
expansion of the mobile network, and fixed-line phone usage still represents only about
20 percent of the population, compared to 50 percent in high-income countries. The data
for the other countries illustrates that the growth of the mobile phone system has been a
common phenomenon of many emerging markets. For example, Thailand’s growth has
been even more rapid in 2000-06 with annual rates of increase in excess of 30 percent.
The impact is less evident for high-income countries, such as the United States, that had
elaborate pre-existing fixed-line systems.
There are, however, large differences in revenue per subscriber, as shown in the
second panel of table 10, which reflect difference in price and utilization of phone
services. For example, Korea has the highest level of realized revenues in 2006 primarily
because it offers a wide range of broadband and other services. In contrast, Thailand
operates more of a bare-bones system limited to basic phone service, and prices have
been driven down by intense competition. Malaysia is an intermediate case with revenue
per subscriber in between Thailand and Singapore. After an initial phase in which simple
mobile connections greatly reduced the average cost of phone usage, many countries
32 Each country’s investment series was converted to U.S. dollars of 2000, using the commercial exchange rate and the price deflator for communications investment in the U.S. national accounts. We have used this methodology of computing values in U.S. dollars because large portions of telecommunications equipment are purchased internationally and should reflect common international prices. The capital stock was computed with a geometric rate of depreciation of 12.5 percent. The initial stock in 1990 was computed as the depreciated sum of investment in prior years back to 1976.
31
have begun a process of introducing new services and are experiencing rising revenues
per subscriber. That is not yet evident in Malaysia.
Estimates of labor productivity, shown in the third panel of table 10, illustrate an
important feature of the mobile technology, its low cost relative to fixed-line service.
Thus, labor productivity in Thailand and Malaysia has soared well above that of the
United States. Since the fixed-line system had not progressed as far in the emerging-
market economies, they were able to leap over the older technology and construct
networks that are lower cost than those of the high-income countries.
The wireless systems are also less capital intensive as shown in the fourth panel.
Output per unit of capital has risen in both Thailand and Malaysia in recent years and is
well above that of the higher-income countries.33 However, the output measure does not
capture the greater utilization of telephone services in some countries. Thus, an
alternative measure of capital intensity is to focus on revenue per unit of capital, shown in
the last panel of the table. Malaysia and Thailand have a high number of subscriber lines
per unit of capital, but revenues per line are less than those of other countries. As a
result, revenue per unit of capital in both countries is well below Korea and Singapore,
but they still compare favorable with the Australia and the United States.
There has been less dramatic change in the area of internet usage. Narrowband
(dial-up) service, which is too slow to accommodate many internet services, has leveled
out at about four million subscribers – a population penetration rate of about 15 percent.
As mentioned above, broadband subscriptions have only recently reached one million. It
remains to be seen if the mobile technology will be able to provide the full range of
internet and broadband services that are becoming critical parts of the future
communications infrastructure. At present it is largely a voice-based system. Malaysia
seems particularly handicapped by the lack of a fixed-line infrastructure to support the
expansion of broadband services to residences. New technologies are emerging that may
enable high-volume data transmission over wireless systems, but they are not yet
33 Capital productivity is measured as output per unit of capital where the latter is measured in U.S. dollars of 2000. Output is a revenue-share weighted average of the number of fixed and mobile subscribers.
32
employed on a wide basis. A high-capacity fiber-optic backbone network is in place to
serve the more urban areas of the country, but less has been done to extend the network to
residences, perhaps due to a lack of strong demand.
Telecomm Prices. There is a shortage of reliable information on the pricing of
telecommunication services. Because there are variations in the structure of telephone
plans across countries, the comparisons of single elements of the service are frequently
misleading. Average revenue per minute provides a very rough guide; and, at .08 USD
per minute, Malaysia is higher priced than Thailand (.03), the same as Singapore, but less
than Korea (.12) and Taiwan (.11).34 However, a measure of revenue per minute fails to
reflect the wide range of services offered in some telecomm plans. For example, the
earlier comparison of data from the ITU indicated that Korean telecoms received annual
revenues of 700 USD per subscriber compared to 270 USD in Malaysia; but the usage
and range of services may be quite different in the two countries
A more meaningful analysis is provided by comparisons of standardized bundles
of services, as is done in OECD (2007, Chapter 7). The OECD analysis compares
equivalent services across its member countries. That same analysis is not available for
Malaysia but we have combined the detailed specification of the bundles of services used
in the OECD analysis with information on prices from the public web sites of the two
major mobile providers in Malaysia (Celcom and Maxis) and Telecom Malaysia for
fixed-line service.35 We have limited our comparisons to a medium level of usage for
both mobile and fixed-line service.
Comparisons of telecom prices are reported for Malaysia, Korea, and Mexico and
the average of the OECD in table 11 using both commercial and PPP exchange rates.
Korea is normally ranked near the top of all countries in telecomm technology, its
availability and its price. Mexico, in contrast, is comparable to Malaysia in terms of GDP
per capita. Both mobile and fixed line services are less costly in Malaysia compared to
34 These estimates are drawn from Merrill Lynch, 2007. Global Wireless Matrix 1Q07. 35 The detailed specifications of the OECD bundles are from OECD (2006). The information on broadband prices is from the OECD Broadband Portal. The OECD telecom price measures are for October 2007, whereas the information on telecom prices in Malaysia was collected in July, 2008.
33
the two OECD countries using commercial exchange rates; however, prices are similar to
those of Mexico and considerably higher than in Korea if we use PPP exchange rates.
The data on broadband prices are averages of broadband services in each country, but the
actual speeds are not standardized. Thus, it is more useful to compare on the basis of
megabits per second. Average broadband service prices in Malaysia are only slightly
higher than the OECD average, but the average transmission speed is much less. Thus
the effective price is far higher than that for Korea and the OECD average; but again, it is
comparable to that of Mexico.
In summary, the Malaysian telecommunications industry has been a major source
of growth over the past decade, and it has succeeded in providing a dramatic expansion of
telephone service to the general population. Improvements in the technology of mobile
phone service have enabled emerging-market countries to catch up with the high-income
countries in the provision of basic phone service. In future years, it will be equally
important to build the broadband network required both as a vital infrastructure for the
general economy and as a mechanism for delivering an increasingly wide range of
consumer services. Information on revenues from broadband services is limited, but
without a major expansion of the fixed-line system, Malaysia is likely to lag behind
comparator countries in this important submarket.
Land Transport
Land transport is a major element of the logistics system. Both trucking and
railroads are important to moving products between business centers and to and from
ports. The 2006 census of land transport estimated total value added at RM 3 billion.36 It
is dominated by road haulage with 79 percent of the total, and railroads and buses
represent 8 and 13 percent respectively. We have constructed estimates of productivity
performance for both railroads and trucking (road haulage). Since there is one dominant
company, the data for railroads are readily available, but it represents a relatively small
proportion of total land transport. Similar data, however, are not available for trucking.
However, DOS has long conducted surveys of the industry that included the three
36 Although the reference is to a census, the national accounts report a larger estimate of GDP (value added) in land transport (RM3.7 billion in 2005.
34
categories (road haulage, bus, and rail), but variations in the proportion of the enterprises
that were covered makes the interpretation of the annual changes problematic.
Railroads. The rail transport system in Malaysia is largely comprised of Keretapi
Tanah Melayu Berhad (KTMB), a publicly-owned enterprise that was corporatized in
1992. Other significant rail providers are Express Rail Link Sdn Bhd, a private company
operating the high-speed railway link between Kuala Lumpur and the KL International
Airport; and RapidKL, a government owned company under the Ministry of Finance that
operates two light rail lines in the Kuala Lumpur area. The KTMB rail system has three
distinct components: KTM Inter-city, a passenger railway service transporting passengers
between cities and towns in peninsular Malaysia; KTM Komuter, an electrified commuter
train system primarily serving the Kuala Lumpur metropolitan area; and a dedicated
series of freight train services.
The only publicly available statistics on the performance of the rail transport
industry in Malaysia are those supplied by KTMB (identical data are reported as well on
the Ministry of Transport’s website). Since the operations of KTMB constitute a
substantial majority of all rail transport operations in Malaysia, an analysis of this data
should reflect the broader performance of the industry in general. Annual data are
available for the period 1996 to 2007. The measure of output used is a weighted average
of the passenger-ton kilometers of the commuter and intercity systems, and the ton-
kilometers of freight service. The weights used to combine the three measures into a
single output estimate are the shares of revenue attributed to each business unit as
provided by KTMB. This measure of output is shown in figure 8 as an index measure
with 1996 equal to 100, for KTMB as a whole as well as the separate sectors of
commuter, intercity, and freight. What is clearly evident from the figure is the strong
growth exhibited by the commuter rail sector, which has averaged 13 percent per year
over the period 1996 to 2007. Output in the inter-city and freight sectors, on the other
hand, both declined somewhat during the period at an annual rate of 0.4 percent. Thus,
our combined measure of KTMB output shows negligible growth in the early years of the
period, and then substantial gains beginning in 2003, once the commuter sector had
grown to represent a significant portion of the total.
35
The measure of capital input is constructed by combining annual inventories of
locomotives, passenger coaches, and freight wagons, weighted by estimates of the
average purchase prices for each asset type over 2000-06. The measure of total
employment was supplied by KTMB. Since the railroad operated at a loss over the
period, it is not feasible to use factor shares to measure the relative contribution of each
capital and labor to production. Instead, we employed an estimate of the factor
proportions drawn from U.S. experience – a labor share of 0.62 that is held constant over
the period.37 Finally, estimates of the educational attainment of the work force are taken
from data provided by DOS at the industry level of total land transport.
A summary of the estimates of productivity for the rail transport industry is
provided in table 12. As indicated above, real output growth is positive in the 1996 to
2007 period as a whole, but growth in the latter years, 2000 to 2007, is considerably
higher, 5.5 percent annually. In contrast, employment growth is negative in the early
years and constant after 2000. Therefore, the bulk of the growth in output can be
attributed to gains in labor productivity. There have been positive but negligible
contributions from capital during the period, and moderate gains in human capital
improvements due to educational attainment. Ultimately, the preponderance of the
growth in output can be traced to increases in TFP, an average growth of 3.3 percent
annually over the full period of 1996-2007 and 4.7 percent annually after 2000. The
efficiency gains are consistent with efforts to eliminate excess capacity, and a more
intensive use of resources in the commuter segment.
Road Haulage. Over the past decade, the structure of the road haulage
industry has been significantly altered by a major expansion of competition (Jamaluddin,
2003). In the early 1990s, for example, container haulage was limited to five large firms
who formed an association and carved up the market among themselves. The rapid
growth of the economy and demand for containerization services lead to congestion at the
ports and delivery delays. The Government responded by sharply increasing the number
of firms that were permitted to haul containers. It is currently estimated that there are as 37 As a government corporation, KTMB has not operated with a clear profit objective. Since the U.S. industry is private and competitive, we assume that the factor shares are reflective of a technology similar to that in Malaysia.
36
many as 70 road haulage firms with authority to handle containers. In addition, KTMB
has emerged as a major transporter of containers. The entry of new firms effectively
eliminated the prior oligopoly, but the overall haulage industry remains subject to
regulation by the Commercial Vehicle Licensing Board (CVLB), which controls entry
through a licensing system and establishes ceiling levels for tariffs.
DOS has conducted surveys of the transportation industry extending back into the
1970s. Many of the surveys were intended to be censuses in that they included all of the
firms that were known to be active at the time of the survey. The survey collects much of
the information that we need to compute measures of productivity. It obtains data on
value added, employment, compensation and the value of fixed assets. The most
significant gap is information on either freight rates or physical measures of freight
moved, similar to the ton-kilometers data from the railroad. The survey covers a broad
definition of the industry that extends much beyond the large firms that are involved in
the movement of containers.
The breadth of the industry definition contributes to the most serious shortfall of
the survey: the difficulty of maintaining a consistent level of coverage over time. The
basic sample frame is constructed in large measure from the licensing information of the
CVLB, but the completeness of the survey sample obviously varies from year-to-year,
and in the 2000-03 period the survey excluded small firms with annual revenues below
RM500,000.38 Since both 1998 and 2005 are years with complete censuses, we used data
on the size distribution of firms in those years to compute adjustment ratios, which we
interpolated and used to adjust the reported data of 2000, 2002, and 2003.39
The estimates of output, employment and the capital stock are shown in index
form in table 13. Lacking a direct measure of output, we deflated the estimate of value
38 As a consequence, the number of surveyed firms declines from 6,442 in 1998 to only 1,070 in 2000. Although the 2005 survey (for 2004 activities) is reported as a complete census, it had problems covering the small firms, and the number of surveyed firms is only 2,271, more than double the number surveyed in 2004, but less than half the number for 2006. 39 We had the data to compute the adjustment ratios for years prior to 1998 as a test of the reasonableness of the methodology. The ratio varied substantially across the years and across the various categories (output, employment, capital assets). This suggests that the RM500,000 cutoff is too large to provide a reliable means of inferring the missing portion of the distribution.
37
added with the price deflator for land transport from the national accounts. Similarly, the
estimates of the book value of assets from the survey were deflated with the price deflator
for fixed capital formation from the national accounts. In the years in which no survey
data are available, the reported values are simply an average of the prior and subsequent
years’ surveys.
The excessive year-to-year variability, which we believe is due to variation in the
survey’s coverage, is evident in the annual changes. Some of the volatility cancels out in
a focus on ratios such as output per worker or output per unit of capital. However, there
is a very large reported change in capital assets between the 1990 and 1991 surveys,
which could represent a definitional change; and the data for 2004 seem much different
than those of the surrounding years.
A summary set of growth accounts are shown in table 14. The variability in the
survey coverage may be less of a problem over longer time periods, leading us to focus
on the two periods before and after the 1997-98 crisis. As with other industries, there is a
marked moderation of output growth after 1997, slowing from an average of 8.3 percent
per year in 1990-1997 to a 3.6 percent average in 1998-2005. Since employment growth
slows more modestly, there is a large deceleration of the gains in labor productivity.40
The large jump in the reported capital stock between 1990 and 1991 is a major reason for
the very large rise in the capital-labor ratio in the first sub-period, and the offset is a large
reported decline in TFP growth, -3.7 percent annually. If the 1990-91 observation is
excluded, the negative change in TFP would be cut to -1.7 percent per year in the first
period. In contrast, TFP is essentially constant after 1998.
On balance, the estimates of recent productivity change seem reasonable since we
would expect improvement in labor productivity to be limited largely to reliance on
larger trucks. However, variations in the survey coverage create significant uncertainties
and we have no direct measure of fares or ton-kilometers. In addition, nothing is known
about the frequency of backhauls with partial or empty loads. The survey combines
operations of commercial haulers ( “A” licenses) and those who carry their own goods
40 The adjustment for educational quality is based on the increase in years-of-schooling reported in the LFS for total transportation.
38
(“C” licenses); and there is no identification by type of primary haulage, such as
containers.41
Seaports
Seaports are the primary interface between maritime and inland transportation of
goods and passengers. Malaysia’s port operations appear to perform well when judged
by various international standards. The Global Competiveness Report ranks Malaysia’s
ports as 13th in the world, surpassed only by Singapore and Hong Kong in East Asia. In
addition, tonnage moved through the country’s ports has been growing at an 11 percent
rate (2000-07), nearly double that of Singapore, and far above that of Taiwan and Korea.
Container traffic is expanding even more rapidly, and the percent of general cargo that is
containerized is comparable to that of Singapore, at 80-90 percent. About half of the
containerized freight is composed of trans-shipments reflecting the consolidation of
freight from other ports in Malaysia and its development as a regional hub.
Annual data are available from the census surveys for nine port authorities
covering only the period of 2000 to 2005. The major ports have been privatized, and the
surveyed ports account for about three-fourths of total cargo movement. The surveys
report employment, compensation, revenues, and the book value of the capital stock. In
addition, surveys of cargo handling and stevedoring firms are available back to 1991; but,
as with road haulage, the coverage of the industry has varied over the years and it is not
evident that the survey results can be adjusted to be representative of the industry as a
whole. The inclusion of cargo handling may also extend beyond the port activities, and
primary activities of the surveyed firms are sometimes shifted between cargo handling
and other transportation industries. As a result, we have limited the analysis of
productivity performance to port operations alone. Finally, the data on the volume of
cargo moved through the ports provides an independent physical indicator of output.42
41 Information is available on container shipments by rail, and they account for more than half of KTMB’s freight revenue. 42 We have adjusted the data to limit the measure of tonnage throughput to the nine surveyed ports.
39
With the available information, we have constructed a growth account for port
operations that allocates the growth in output over the 2000-05 period among the
contributions of employment, capital and TFP. We have two potential measures of
output: the total throughput of cargo which rose by 49 percent over the 5 years, and a
deflated estimate of value added from the survey which indicates a growth of 122
percent.43 The discrepancy can be traced largely to an extraordinary 92 percent rise
nominal value added between the surveys of 2000 and 2002. In subsequent years the
growth rates of the two measures are quite comparable. Furthermore, the surge in value
added between 2000 and 2002 is largely concentrated in capital income, as reflected in
the doubling of the gross return on assets. The source of the large change is puzzling
because the same nine firms are surveyed in both years. In any case, we have based the
estimate of output growth on the measure of cargo throughput and use the measures of
employment and capital assets from the survey.
The resulting measures of output, employment, and capital asset are shown in
table 15 together with the productivity measures for 2000-05. Even with the more
conservative measure based on cargo throughput; output has expanded at a rapid pace of
eight percent annually. That growth has been evenly split between increases in
employment and labor productivity. Interestingly, capital per worker appears to have
declined over the period, implying a substantial increase in capacity utilization. The
result has been a very strong five percent annual rate of improvement in TFP.
The lack of reliable information on stevedoring is a major shortcoming of the
productivity estimates. Despite their variability, the DOS surveys of cargo handling and
stevedoring indicated levels of employment nearly equal to that of port authorities alone.
Thus, we do not know the extent to which some stevedore employment is missing from
the port authority measures.
A 2003 study by the Australian Productivity Commission undertook an
international comparison study that defined the industry by limiting port activities to
43 The survey estimate of nominal value added was converted to constant prices using the price index for port operation in the national accounts.
40
container stevedoring, but it included information on both the use of cranes and handling
charges. Port Klang and Singapore were included in that study with data for 1997 and
2002. Productivity levels at Port Klang, as measured by the number of cranes handled
per crane hour, were generally comparable to those of Australia, but somewhat below
those of East Asia, the United States, and Europe. On the other hand, port charges were
below those of most other large container ports. The study did not obtain information on
the labor utilization at Port Klang.
The Australian study is becoming dated, but it provides a useful framework in
indicating the data that needs to be collected to provide a more systematic evaluation of
the efficiency of port operations. It is the type of study that could be performed quite
easily within Malaysia in order to compare the performance of the country’s major
container ports. However, by not having an explicit framework for counting the labor
requirements, it would remain an incomplete assessment of productivity performance.
IV. External Trade in Services
Malaysia is a signatory to the General Agreement on Trade in Services (GATS).
The GATS presents Malaysia’s service industries with both opportunities and challenges.
Greater foreign involvement can expand competition and stimulate a faster rate of
improvement in the efficiency and competitiveness of the domestic service-producing
firms to the benefit of the users of those services. Those firms will, in turn, enjoy greater
access to regional and global markets; but they will also have to adapt to a more open
domestic market, and the agreement imposes a requirement for greater transparency of
rules and regulations.
Malaysia has sought to promote exports of business services through a variety of
measures such as the creation of the Multimedia Super Corridor with its provision of
high-quality broadband communication resources and the development of a workforce
proficient in English and technical skills. It also has a substantial tourism industry.
However, Malaysia has been very cautious in the easing on restrictions of foreign
participation in the domestic services industries, because of concerns that the domestic
producers would not be able to compete. A 2004 World Bank study indicated that
41
Malaysia had a relatively high level of barriers to foreign FDI in services. For example,
the tax-equivalent value of restrictions on foreign banks was estimated at 36 percent. The
report of approvals of foreign direct investment in 2007 indicated an RM11 billion
foreign investment in services ($3.1 billion) that represented only about one sixth of the
RM65 billion ($19 billion) of approved domestic investment projects in services. In
comparison, foreign projects in manufacturing were RM33 billion out of a total of RM60
billion.44 However, the 2007 FDI in services did represent an 80 percent increase over
the value reported for 2006.
To date, however, the liberalization of markets in services has had relatively little
effect on Malaysia’s services trade. As shares of GDP, both exports and imports have
declined by modest amounts, and the trade balance in services was a -1.3 percent of GDP
in 2006 compared to a -3.1 percent in 2000 (table 16). Exports of services represented
14.5 percent of GDP in 2006 and imports were 15.7 percent. The largest source of
growth on the export side was for travel services (tourism), and it has grown substantially
faster than imports. Transportation has long been the major source of the deficit in
services trade, and that imbalance has grown over time. Interestingly, the category of
computer and business services has declined substantially on both the export and import
side of the accounts. That is one the subsectors that is targeted for expansion in the third
industrial master plan.
Singapore provides an interesting neighboring comparison because services trade
is such a large and important part of the economy. A comparison of the two countries’
services trade for 2006 is shown in table 17. Singapore also has a deficit in transportation
services, and it is not a major tourist destination. Furthermore, it stands out with a large
deficit in royalties and fees. Singapore does extremely well, however, in the area of
computer and business services, where exports represent 17 percent of GDP; and the
overall services trade surplus is the equivalent of 8 percent of the GDP. It is a strong
example of the extent to which many services can now be traded internationally.
Malaysia’s trade in business services is only a fourth that of Singapore.
44 Data available at http://www.mida.gov.my/beta/view.php?cat=13&scat=1524
42
V. Educational Attainment.
For many of the top-performing East Asian economies, improvements in the
educational attainment and skill of the workforce have played a critical role in sustaining
economic growth and ensuring wide-spread distribution of its benefits. Advanced levels
of education are particularly important for service-producing industries because many
require a highly skilled labor force. That is particularly true for finance, health care, and
the education sector itself: all industries where more than half of the workforce had a
tertiary education in 2007. Various international comparisons place Malaysia in the
middle of the East Asian countries with respect to the average years of educational
attainment – slightly below Singapore and Taiwan, but higher than Thailand.
Education conditions both the type of work that individuals can perform and their
proficiency in any particular occupation. Its contribution to productivity can be inferred
from information on the income accruing to individuals of differing levels of education.
Estimates of these private returns to education are obtained from empirical studies of the
relationship between earnings and educational attainment. However, the private return to
education may overstate the contribution to productivity if the educational process simply
sorts people who differ in their native abilities, thereby providing a convenient indicator
or signal of hard-to-observe personal characteristics (Spence, 1973). If the latter process
dominates, estimates of the private return would overstate the contribution to aggregate
productivity. On the other hand, a case can also be made that the aggregate productivity
gains exceed the private returns because an educated workforce accelerates innovation
and facilitates introduction into the production process.
Examples of empirical estimates of the private returns to education are widely
available; and a survey by Psacharopoulos and Patrinos (2002) reports a range of returns
between 7 and 12 percent for a large number of country studies. Those studies typically
use micro survey data to estimate the impact of years of schooling on wage rates.
We used data from four years (1995, 1999, 2002, and 2004), of the Malaysian
Household Income and Expenditure Surveys to explore the relationship between
education and earnings in Malaysia. The surveys provide information on both wages and
self-employment income, and the usable sample size varied between 40 and 70 thousand
43
observations. Regressions were estimated for each survey in which the log of the
monthly earnings was related to age, age2, gender, and years of schooling.
The regression results for wage and salary income of employees are reported in
18(a).45 The coefficient on years-of-schooling is virtually identical in all four surveys,
implying a very stable estimated return to education of about 10 percent per year-of-
schooling. A second formulation used a set of categorical variables to represent the
various levels of education, dropping the assumption of a linear relationship with years of
schooling (table 18b). The coefficient estimates were again very stable over time; and,
therefore, only the results for 2004 are reported in the table. The estimated return is
slightly lower than in the version based on years of schooling, particularly for those with
only elementary schooling. Workers with a college diploma education earn a premium of
about 60 percent above those who have completed a secondary education. However, the
largest incremental return per year of schooling accrues to those who complete the
secondary level and to post-graduate studies.
These estimates of the private return to education are very much in line with the
results for other countries. However, because of the potential role of sorting in
overstating the contribution of education, we have chosen to use a slightly lower, more
conservative estimate in constructing an index of labor quality for the growth accounts
reported in prior sections. The specific formulation, shown in appendix A, assumes that
each year of schooling raises individuals’ productivity by a constant 7 percent.46
Questions have also been raised about the quality of the education that students
receive. Malaysia participated in the 1999 and 2003 Trends in International Mathematics
and Science Study (TIMMS) for 8th graders. In 1999, its scores were 21st out 38
countries in mathematics and 27th in science. In 2003, its performance improved and its
rank improved to 10th out of 45 in mathematics and 20th in science. The scores are about
average for the Asian countries: above Indonesia, the Philippines, and Thailand, but
below Korea, Singapore, and Taiwan. The tests suggest that the primary and tertiary 45 The results for wage and salary income are emphasized because the wage data is believe to be more accurate than reported self-employment income; but the results were very similar for all measures of reported income. 46 See Bosworth and Collins (2003) for a further discussion.
44
schools perform well. However, only 20 percent of the workforce has a tertiary level of
education; and Malaysia has only two universities that appear in international rankings
while significant numbers of college students attend overseas institutions—primarily in
Australia and the United Kingdom. Malaysia is also an important destination for students
from developing countries.
VI. Service-Sector Statistics
In recent years, DOS has undertaken a major expansion of its statistics on the
service-producing industries. This is particularly true for the national accounts where the
degree of detail on value added has been greatly expanded to provide published estimates
for a large number of industries. However, fully comparable data are available only 2000
and later years, making it difficult to provide an appropriate historical context for some
recent developments. In addition, information on other aspects of the sector’s
development is still limited – especially in comparison with the information available for
goods-producing industries.
Measures of the economic performance of the service sector are under-
represented in the statistical systems of many countries. The bias in favor of agriculture
and industry has been due in part to difficulties of defining and measuring the intangible
output of some service-producing industries. Attitudes toward the production of services
were also strongly influenced in the early stages of industrialization and growth by the
need to increase the production of food and other material necessities of life.
Furthermore, only goods could be traded internationally and used to finance the purchase
of advanced capital equipment and other products that were unavailable in the domestic
economy. Few services were tradable across national borders.
National statistical agencies have had to change, however, as it becomes
increasingly evident that services have emerged as a leading source of growth in
employment and incomes. In this regard, Malaysia is no different. As discussed above,
the services sector has been the primary source of growth in new jobs. The need for an
expansion of services statistics has also been recognized by the formation of the Task
Force on Service Statistics which has compiled a compendium of available statistics and
future needs.
45
From the perspective of this study’s focus on the economic performance of the
service-producing industries, several data priorities have emerged. Reflecting the study’s
emphasis on a growth accounting framework, the data issues can be grouped into three
categories of: (1) the measurement of services output, (2) capital accumulation, and (3)
industry-level employment.
Service-industry Output. The expansion of the published national accounts data
on value-added in service-producing industries has been made possible by the
enlargement of an underlying set of industry surveys. The surveys are undertaken by the
Services Statistics Division of DOS. In most instances, they are biennial and are
advertised as censuses in that they cover all establishments that are known to be active at
the time of the survey. However, in past years some surveys have incorporated a size
limitation, excluding for example firms with sales below RM500,000. The surveys are
designed to collect key information on the operations of establishments, such as revenues,
expenses, employment and capital assets. They comprise the basic source data for the
estimates of industry value added in the national accounts. Separate smaller surveys,
often limited to major firms, are used by the National Accounts Division to interpolate
and extrapolated the estimates for years in which the surveys are not available.
It seems evident from a comparison of the results from successive “censuses,”
however, that they are often unreliable indicators of rates of change. In some industries
there are implausible large changes in the number of reporting establishments and the
magnitude of key characteristics, such as their value added, employment and capital
assets.47 As a result, the surveys are underutilized as a source of information on basic
economic trends. The fundamental problem is a lack of a reliable business registry or list
of active establishments on which the ‘census’ or a sample survey can be based.48 As a
consequence, the census results appear to reflect year-to-year variations in the success of
the survey division in identifying all of the relevant enterprises and convincing them to 47 The inconsistencies were noted in the earlier section on road haulage, but they also evident in other service industries which were not the focus of the study 48 The census of the distributive industries is an exception in being based on geographical enumeration block of the population and housing census. The census also provides the sampling frame for stratified sampling in subsequent years. The challenge is in maintaining an accurate registry in industries of rapid entry and exit.
46
participate. Without a business registry, it is not possible to fully incorporate modern
sampling procedures and to correct for nonresponse. The frequent use of censuses is also
unnecessarily burdensome of small enterprises who could be well-represented by random
sampling techniques. The surveys also need to place a greater emphasis on time-
consistent estimates; perhaps by providing a separate tabulation of changes in the
statistics for those firms that appear in two consecutive surveys.
Second, the statistical system collects very little information on service prices,
particularly for business services. The Producer Price Index is limited to goods, and the
Consumer Price Index captures only services provided to households. DOS publishes
price deflators for the expanded list of service-producing industries since 2000; but
without more information on the source and method of estimation, it is not possible to
evaluate their quality.
Investment and the Capital Stock. Perhaps most striking, DOS produces no public
statistics on the composition of fixed investment by either industry or type of capital.
With no information on the composition of investment, it is also impossible to construct
measures of the capital stock by industry. This is a major gap in any effort to evaluate
the productivity performance of individual industries. In this study, we have used some
measures of the capital stock prepared by the Malaysian Productivity Corporation, but
those estimates are very tentative and based on very little direct measurement. A
considerable portion of the required information is provided in the service-industry
censuses, but because of the variation in coverage the time-series estimates of the capital
stock are problematic. In addition, most enterprises report the capital assets on a book
value basis, which is difficult to adjust for price changes.
It is possible to collect information on capital expenditures through establishment-
level censuses and surveys, but it is difficult to fully integrate such information with the
fixed investment data of the national accounts, which are normally obtained from the
producers of capital equipment, external trade statistics, and construction permits.
Alternatively, many national statistical offices construct periodic capital transactions
matrices that convert information on investment by type to investment by industry. The
required information is similar to that compiled for the input-output accounts. For
47
example, the last I-O table for Malaysia is for 2000, and estimates of investment at the
industrial level were prepared as part of that exercise. In addition, the service-industry
surveys do provide information on capital expenditures by major type. However, no
published data are available from the national accounts on aggregate investment outlays
by type (such as transportation, machinery and equipment, and structures) that could be
used to complete the transactions matrix. The construction and publication of data on
capital expenditures and stocks is a current project of DOS, but a completion data is
unknown.
Industry-level employment. The statistics on employment at the level of detailed
service-producing industries are also limited. The labor force survey is based on a large
(nearly 100 thousand households) and well-designed household sample that uses
geographical enumeration and appears to be highly reliable for aggregate measures of
labor market performance. However, a household-level survey cannot be expected to
provide reliable information on the industrial composition of employment below the level
of major sectors. The survey respondents simply do not have sufficient knowledge of the
industrial classification of all employed members of the household. Thus, statistical
agencies are ultimately required to develop enterprise or establishment-level surveys to
follow employment and output trends at the level of detailed industries. That is already
being done in Malaysia for manufacturing enterprises.
Assuming that the problem of constructing a reliable sampling frame is resolved,
the existing service-industry survey would satisfy a large portion of the requirement for
employment data at the detailed industry level. At present, employment information is
collected only for the last pay period of the reference year; however, employment at a
higher frequency, if deemed important, should not impose a large burden on respondents.
The surveys would also be the appropriate means for collecting information on employee
compensation and wage rates. Such data would make it possible to publish information
on the division of value added between payments to workers and the return to capital.
In conclusion, a reasonable objective of the expansion of data on service-
producing industries would be the ultimate production of an industry data base
comparable to the Structural Analysis (STAN) database of the member countries of the
48
OECD. The industry data would be integrated with the national accounts and provide
industry-level data on gross output, purchased inputs, value added, prices, employment,
labor compensation, capital stock, exports, and imports. Such a database provides much
of the information needed to inform national policymakers and to assist in the setting of
policy goals and priorities. Within the OECD, the STAN database is used to analyze
industrial structure and the evolution of industrial performance (e.g. import penetration,
investment per employee, export market shares). A comparable dataset for Malaysia
would greatly expand policymakers’ ability to benchmark the performance of Malaysian
industries to those of other countries. As discussed above, DOS currently produces much
of the basic information required to construct the database through its surveys of goods
and service-producing industries.
VII. Policy Implications
Malaysia’s service industries have performed well over the past decade, both with
respect to creating jobs and raising efficiency (productivity). In the international
comparisons, for example, most service industries have significantly narrowed the gap
between their efficiency and that of the comparator countries of Korea and Taiwan. In
addition, according to the World Bank’s Doing Business Project, Malaysia has also done
well in creating a favorable business environment. In 2008, it was ranked 24th among
178 countries in terms of the ease of doing business.
External Trade in Services. A major surprise of this study has been the lack of
any significant growth in international trade in business services. Despite some
liberalization measures, the importance of both exports and imports of business services
declined over the period of 2000-2005. Given its location and the example of
neighboring Singapore, we would expect Malaysia to perform well as a regional center
for business services. The major opportunity for expansion of output and employment in
the services sector lies in the growth of external trade in services and greater interactions
between Malaysian service-producing firms and the international market. A recent study
by the World Bank (World Bank, 2004) suggested that, despite Malaysia’s participation
in the GATS, the regulatory barriers to trade in business services and the distributive
industries remain relatively high. The high ranking in the Doing Business project is
49
largely due the ease of obtaining credit and a high level of investor protection. Malaysia
does not rank high in the ease of starting a business or dealing with licensing and other
regulatory requirements. At the same time, this study suggests that the efficiency of the
service industries have progressed to the point that they can compete effectively in
international markets, and would benefit from the enhanced competition and knowledge
transfers. In addition, Malaysia has a relatively strong financial services industry, and
MSC Malaysia provides it with a communications network capable of supporting an
expanded business services industry. Thus, it has much of the infrastructure to compete
effectively on a global basis. We conclude that services trade would benefit significantly
from a liberalization of the regulatory system to expand competition and a reduction of
the barriers to foreign firms’ involvement in service-producing industries.
University Education. A significant expansion of business services will be
conditional on an increased supply of university graduates with strong English language
skills, an area of historic strength for Malaysia. There are, however, some concerns about
the erosion of quality in the university system. A recent study by McKinsey Global
Institute concluded that only 20-35 percent of Malaysian university graduates had the
appropriate skills to work for international business firms that are engaged in the off-
shoring of business services. The most frequent concerns were the lack of appropriate
language skills and the quality of the technical degrees. In addition, none of Malaysia’s
universities rank amount the top universities in global rankings. The professional
qualifications of university faculty are low, with very low incidence of PhD level
degrees. Tertiary education enrollment and graduations rates have risen substantially in
recent years, but they remain far below those of the comparator countries of Korea,
Singapore and Taiwan; and they have been consistently below those of Thailand.
Malaysia universities face a major challenge of simultaneously increasing graduation
rates and raising their academic standards.
In addition to providing a more qualified workforce, the university system
occupies a critical link in countries’ research and development systems. Malaysia’s R&D
expenditures have grown in recent years, but they remain below the levels of the above
comparator countries measured as a percent of GDP. Thus, a program to strengthen the
50
university system needs to address the development of the R&D network as well as
tertiary education.
Competition Policy. We noted earlier that many service industries operate with
relatively high shares of capital income. Those high profit margins could be indicative of
weak levels of competition in finance and some other service industries. In the past,
many service industries have been sheltered from foreign competition by provisions for
FDI that were less liberal than those available to foreign manufacturing firms. Foreign
commercial presence is largely confined to joint ventures in which combined foreign
ownership cannot normally exceed 30 per cent. Moreover, there are tight restrictions on
the involvement of non-citizens in professional services and the recognition of overseas
professional qualification. In this study, we find that Malaysia service industries have
achieved reasonable levels of efficiency, and that concerns about the inability of infant
firms to compete seem misplaced. A vigorous competitive environment can spur
additional efficiency gains and penetration into international markets.
51
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55
Appendix A: Growth Accounting
Modern productivity analysis, following from the contribution of Solow (1957), begins with a concept of an aggregate production function that relates output to the contribution of the factor inputs, capital and labor, and a Hicks-neutral shift in the production function:
(1) ( )tttt LKFAQ ,= . By combining the notion of a production function with the assumption of
competitive markets where the factors are paid their marginal products, it is possible to derive a simple index number formulation that relates the growth in output to increases in the factor inputs and a residual shift term that is identified with TFP:
(2) TFPLdvKdvQd lk ln)ln()ln(ln Δ++= , where vk and vl are the shares of capital and labor income, respectively. The use of income share weights is critical in that it makes it possible to avoid imposing restrictions on the possible functional forms of the production function. In empirical applications, the factor shares are replaced by average between period shares in a Tornqvist discrete time approximation. Thus vk is replaced by (vkt + vkt-1)/2. 49
As discussed more fully below, it is often difficult to obtain meaningful time series estimates of factor income shares. Thus, many studies adopt a more restricted Cobb-Douglas production function in which the contribution of each factor is assumed to be constant:
(3) . ( )γαα −= 1( ttt LKAQAgain, A represents TFP and γ measures the extent of returns to scale. In this restricted formulation, the sk and sl of equation (2) are replaced with constants and many studies have simply assumed returns to scale of unity.50
Quality Adjustment. It has also become quite standard to adjust the factor inputs, particularly labor, to reflect changes in quality. There are two common approaches that have been used. The first seeks to cross-classify the workforce by a number of differentiating characteristics, such as education, age, occupation and gender. This information is combined with data on wage rates to compute each subgroup’s share of total compensation, vi. An adjusted measure of the labor input is then computed as
(4) ii
i LdvLd lnln * ∑= This is a very data intensive process and some analysts object that the wage differentials may measure factors other than productivity differences, such as gender or age discrimination.
The alternative is to use a simple index of educational attainment to adjust for skill differences. For example, an index of the form:
49 The only restriction on the production function is the assumption of constant returns-to-scale. A summary of the literature is provided in Hulten (2001), and a detailed manual that elaborates on the major issues is available in OECD (2001). 50 This may not be a very important restriction, since income shares seldom show strong trend changes in those countries where they can be estimated with reasonable precision.
56
(5) LeL as=*
assumes that each year of schooling, s, raises the average worker’s productivity by a constant percentage, a. This formulation also has a ready parallel with a vast number of empirical studies that have used “Mincer regressions” to measure the relationship between wage rates and years of schooling. These studies have been carried out around the world with typical findings on the return to education in the range of 7 to 12 percent.51
The Department of Statistics provided estimates from the Labor Force Survey (LFS) of the number of employed persons by educational attainment (at the level of no education, primary, secondary, tertiary) cross-tabulated by industry. The Household Income and Expenditure Surveys (Years 1995, 1997, 1999, 2002, 2004) provides additional detail on average years of schooling within the broad categorical measures of attainment. We combined the information from the two sources to convert the measures of attainment by level of attainment to years of schooling. Finally, to aggregate the industry estimates to the sectoral level of agriculture, industry, and services, we took the weighted average of the years of schooling measure for each industry, using the share of sector employment in that industry as the weights.
A quality adjustment can also be made to the capital input, although in most cases it should more properly be identified as reflecting changes in the composition of the capital services. Neoclassical investment theory clarifies the distinction between the capital stock and capital services. The rental price of capital services is give by
(6) , kks
k PPiP •−+= )( δ where i represents the nominal rate of return, δ the rate of depreciation, and the rate of price change. This formulation makes it clear that the flow of capital services will vary with difference in the rate of capital asset depreciation. Assuming that the real rate of return is constant across asset classes, the capital services term can be used to aggregate across capital with different rates of depreciation. The essential difference is that the aggregate of the capital stock is constructed using purchase prices as the relevant weights, while the aggregate of capital services is weighted by the rental prices. The growing importance of short-lived, high-tech capital has made this issue of compositional changes in the capital stock more important. Unfortunately, most countries do not have sufficiently detailed information – particularly at the level of individual industries – to make these compositional adjustments. Thus, it is common to use a simple estimate of the capital stock as the index of capital services.
kP
Income Shares. The empirical application of the above framework encounters one additional complication. The use of income shares assumes that total value added is composed of labor and capital income, but the national accounts are based on classifying income among three categories of wages, capital, and mixed income. The last category refers to the self-employed and family businesses in which the income is a combination of returns to capital and labor. It is a particularly important component of national income in developing countries because of the large role of the agricultural sector, but also because family run businesses, with large numbers of unpaid relatives, are common in
51 Summaries of many of these international studies are available in Psacharopoulos and Patrinos (2002).
57
many service-producing industries, such as trade, restaurants and personal services. Thus, a means must be found to partition the mixed income into its capital and labor constituents.
The simplest means of splitting mixed income between its labor and capital components is to assume that the self-employed and unpaid family workers earn the same wage as employees in the same industry. However, the adjustment can yield implausible outcomes in which the imputed wage exceeds the total income payment. An alternative is to average the wage rate assumption with an assumption that the business earns the same rate of return on capital as in the corporate sector of the economy, but this approach requires a larger amount of data on the capital stock and returns than is available in most countries.
The difficulties of obtaining plausible income shares in the presence of a large mixed-income component often leads to the alternative of assuming fixed exogenous shares. As mentioned above, the assumption comes at the cost, however, of being based on a more restricted formulation of the production function.
58
Figure 1. Malaysia's GDP Growth: Actual and Trend, 1987-2007
Source: National Accounts and calculations as explained in text.
Table 1. Sources of Growth, Total Economy: 1987-2007Annual percentage rate of change
1987-2007 1987-1997 1998-2007Output 6.8 9.4 5.7Employment 2.7 3.7 2.0Output per worker 3.7 5.5 2.9Contribution of:
Capital 2.5 3.4 1.0Education 0.3 0.3 0.3Land 0.0 0.0 -0.1Factor Productivity 0.9 1.7 1.6
Source: National Accounts and calculations as explained in text.
0
100
200
300
400
500
600
1985 1990 1995 2000 2005
2000
pric
es
9.4 % trend1987-97
5.7 % trend1998-07
Table 2. Sources of Economic Growth by Major Sector, 1987-2007Annual percentage rate of change
1987-2007 1987-1997 1998-2007
Output 1.9 1.1 3.3Employment -1.0 -2.2 -0.8Output per worker 2.8 3.3 3.9
Contribution of:Capital 1.5 2.3 1.0Education 0.3 0.2 0.4Land 0.6 1.2 0.2Factor Productivity 0.4 -0.4 2.3
Output 7.2 11.0 5.4Employment 4.3 8.1 1.4Output per worker 2.6 2.7 3.6
Contribution of:Capital 0.4 -0.9 1.2Education 0.2 0.2 0.2Land 0.0 0.0 0.0Factor Productivity 2.0 3.4 2.2
Output 8.1 10.8 6.2Employment 3.6 4.1 3.3Output per worker 3.9 6.4 1.8
Contribution of:Capital 1.0 1.7 0.2Education 0.3 0.3 0.3Land 0.0 0.0 0.0Factor Productivity 2.5 4.4 1.3
Addenda: Manufacturing1987-2007 1987-1997 1998-2007
Output 9.2 13.9 6.9Employment 4.1 8.0 1.0Output per worker 4.7 5.4 5.5
Contribution of:Capital -0.6 -2.4 0.8Education 0.2 0.2 0.2Land 0.0 0.0 0.0Factor Productivity 5.1 7.8 4.5
Note: Labor shares used in these calculations are as follows: Total Economy (.38), Agriculture (.45), Industry (.27), Services (.41), and Manufacturing (.28)
Agriculture
Industry
Services
Source: Department of Statistics and calculations as explained in the text.
Figure 2. Sector Contribution to Overall Growth in Labor Productivity
A. Output per Worker: Major Sectors
0
20
40
60
80
1985 1990 1995 2000 2005
Thou
sand
s of
200
0 R
m
Industry
Agriculture
Services
B. Sector Contributions to Output per Worker
0
1
2
3
4
5
6
1987-2007 1987-1997 1998-2007
Ann
ual P
erce
nt G
row
th
ReallocationServicesIndustryAgriculture
Table 3. Output and Productivity of the Major Service-Producing Industries: Malaysia, 1987-2007Percents unless otherwise indicated
Level
Output Employment
Utilities: Electricity, Gas, and Water 3.0 0.5 215.6 9.0 2.7 6.1Wholesale and Retail Trade 11.2 15.0 28.7 8.9 3.6 5.1Hotels and Restaurants 2.2 6.4 13.5 8.6 3.9 4.5Transportation and Storage 3.9 4.0 37.4 5.4 3.9 1.4Communications 3.1 0.7 174.7 12.4 4.0 8.1Finance 9.2 2.5 141.7 11.7 4.5 6.9Real Estate and Business Services** 4.4 2.8 60.3 8.1 7.5 0.6Public Administration, Defense, Social Security 3.0 6.8 16.8 3.8 2.5 1.2Education 3.1 5.4 22.2 5.9 4.2 1.6Health Services 1.1 1.6 26.7 7.2 4.5 2.6Other Sevices 1.3 5.6 9.2 6.7 3.1 3.5Total Services** 45.5 51.3 34.1 8.2 3.9 4.2Source: Author's calculations as explained in text.* Measured in ('000) RM per worker** Real Estate & Business Activities and Total Services both exclude owner-occupied dwellings
Output per worker
Annual Growth RateShare of
EmploymentShare of
GDPOutput per
worker*
Table 4. Sources of Growth: Seven Service-Producing Industries, 1987-2007Annual percentage rate of change
Utilities: Electricity, Gas,
& WaterWholesale & Retail Trade
Hotels & Restaurants
Transportation & Storage
Commun-ications
Finance and Insurance
Real Estate & Business Activities*
Total Services*
Labor Share 0.09 0.30 0.62 0.51 0.18 0.23 0.34 0.55
1987-2007Output 9.0 8.9 8.6 5.4 12.4 11.7 8.1 8.2Employment 2.7 3.6 3.9 3.9 4.0 4.5 7.5 3.9Output per worker 6.1 5.1 4.5 1.4 8.1 6.9 0.6 4.2Contribution of:
Capital 3.3 1.3 0.6 0.7 1.0 0.5 -1.5 0.7Education 0.1 0.2 0.5 0.5 0.1 0.2 0.1 0.4Factor Productivity 2.6 3.5 3.4 0.3 6.8 6.2 1.9 3.0
1987-1997Output 11.0 13.1 12.2 8.2 15.8 16.4 11.5 10.8Employment 3.6 4.1 3.5 5.5 4.0 6.6 6.3 4.1Output per worker 7.2 8.7 8.4 2.5 11.4 9.2 4.9 6.4Contribution of:
Capital 5.0 2.9 1.8 0.5 2.0 -0.3 -0.1 1.4Education 0.1 0.2 0.5 0.4 0.1 0.1 0.3 0.4Factor Productivity 2.1 5.4 6.0 1.6 9.1 9.4 4.7 4.6
1998-2007*Output 6.7 5.6 6.3 3.5 9.4 7.2 6.8 6.3Employment 3.8 3.5 4.0 3.1 3.9 1.9 10.5 3.8Output per worker 2.8 2.1 2.2 0.4 5.3 5.1 -3.3 2.4Contribution of:
Capital -0.3 -0.5 -0.5 0.5 0.1 1.6 -3.9 0.0Education 0.1 0.2 0.5 0.5 0.1 0.2 0.0 0.4Factor Productivity 3.0 2.4 2.2 -0.5 5.1 3.2 0.6 2.0
Source: Author's calculations as explained in text.*Reported values are averages of 1998-2006 and 1999-2007.* Note: Real Estate & Business Activities and Total Services both exclude owner-occupied dwellings
Table 5 : Industry Contributions to Growth in Output per Worker, Servicespercent
1987-2007 1987-1997 1998-2007*
Utilities: Electricity, Gas, and Water 0.3 0.4 0.2Wholesale and Retail Trade 1.1 1.8 0.5Hotels and Restaurants 0.2 0.4 0.1Transportation and Storage 0.2 0.3 0.0Communications 0.3 0.4 0.3Finance 0.8 1.0 1.0Real Estate and Business Services** 0.1 0.5 -0.3Public Administration and Defense 0.2 0.0 0.2Education 0.2 0.1 0.2Health Services 0.1 0.1 0.1Other Services 0.1 0.2 0.1
Reallocation Effect 0.7 1.1 0.1Total Services** 4.2 6.4 2.4Source: Authors' calculations as explained in text.*Reported values are averages of 1998-2006 and 1999-2007
Contribution
** Note: Real Estate & Business Activities and Total Services both exclude owner-occupied dwellings
Thousands of dollars
IndustryPPP $ per
workerUS $ per worker
PPP $ per worker
US $ per worker
Utilities: Electricity, Gas, and Water 149 67 130 51Wholesale and Retail Trade 20 9 12 5Hotels and Restaurants 10 4 9 4Transport, Storage, Communications 39 17 30 12Finance 105 47 52 21Real Estate and Business Services* 27 12 19 8Public Admin, Education, and Health 15 7 17 7Other Sevices 7 3 18 7Total Services 24 11 17 7
GDP per Capita 11 5 7 3
PPP $ per worker
US $ per worker
PPP $ per worker
US $ per worker
Utilities: Electricity, Gas, and Water 300 231 270 162Wholesale and Retail Trade 17 13 61 37Hotels and Restaurants 12 9 20 12Transport, Storage, Communications 47 36 76 46Finance 103 79 153 92Real Estate and Business Services* 25 19 50 30Public Admin, Education, and Health 46 36 76 46Other Sevices 15 12 36 21Total Services 32 24 64 38
GDP per Capita 21 16 26 16
* This category excludes owner-occupied housing for Malaysia, Taiwan, and Thailand and all of real estate for Korea.
Taiwan
Table 6. Labor Productivity Levels by Industry: Malaysia Thailand, Korea, and Taiwan: 2005
ThailandMalaysia
Korea
Sources: Malaysia: authors calculations as explained in text; Thailand: National Accounts and Labor Force Surveys; Korea: OECD ; Taiwan: National Accounts. Data on PPP taken from World Bank. "2005 International Comparison Project, Preliminary Results" (December, 2007),
Table 7. Sources of Growth in Services Industries for Malaysia, Korea, and Taiwan: 1998-2006Annual percentage rate of change
Output EmploymentOutput per
worker Output EmploymentOutput per
worker
Utilities: Electricity, Gas, and Water 6.8 5.3 1.4 5.9 n.a. n.a.Wholesale and Retail Trade 5.1 3.4 1.6 2.8 3.7 -0.8Hotels and Restaurants 5.7 4.0 1.7 4.4 6.4 -1.9Transport, Storage & Communications 5.9 3.1 2.7 6.0 1.8 4.1Finance 6.8 1.2 5.6 -0.3 0.8 -1.1Real Estate and Business Activities 6.1 10.8 -4.3 4.1 5.2 -1.0Public Admin, Education, and Health 6.4 3.3 3.0 3.4 2.0 1.4Other Sevices 3.6 1.6 2.0 8.0 6.6 1.4Total Services 6.0 3.7 2.2 3.8 3.8 0.0
Output EmploymentOutput per
worker Output EmploymentOutput per
worker
Utilities: Electricity, Gas, and Water 7.4 2.8 4.5 3.3 -0.4 3.7Wholesale and Retail Trade 4.3 -0.4 4.6 4.3 0.6 3.6Hotels and Restaurants 4.8 2.0 2.7 3.5 4.6 -1.0Transport, Storage & Communications 9.6 3.0 6.4 5.5 0.3 5.2Finance 5.1 0.2 4.9 3.1 1.8 1.2Real Estate and Business Activities 4.8 9.0 -3.8 5.4 5.3 0.1Public Admin, Education, and Health 2.7 4.2 -1.4 2.5 2.6 -0.1Other Sevices 5.3 7.6 -2.1 4.9 2.6 2.2Total Services 5.0 3.1 1.9 3.8 2.1 1.7Sources: Table 5 and authors' calculations * Years for Thailand are 1998-2005, and total services excludes utilities.** Years for Taiwan are 1999-2006
Malaysia
Korea Taiwan*
Thailand*
Figure 3. Indexes of Output: Malaysian Passenger Airlines, 1990-071990 - 2007
Source: See below
Table 8. Sources of Growth in Air Transport: Malaysia 1990-2007annual rates of change
1990-2007 1990-1999 1999-2007Real Output Growth 7.4 8.8 5.9Contribution of:
Labor 1.3 1.6 1.0Employment 0.9 1.4 0.3Quality 0.4 0.2 0.7
Capital 3.4 3.6 3.3TFP 2.5 3.4 1.5
Source: Data are compiled from annual reports of Malaysia Airlines and AirAsia. Output is a weighted average of passengers, passenger revenue kilometers and freight-ton kilometers. Employment is number of employees from company reports. The measure of capital inputs is the total ton-kilometers of available capacity.
100
150
200
250
300
350
1990 1992 1994 1996 1998 2000 2002 2004 2006
Inde
x 19
90 =
100
output - MAS
output - MAS & AXM
Figure 4a. Relative Labor Productivity for Selected Airlines, 1991-2007United States 1991 = 100
Source: Calculations based on airline financial and operating reports.
Figure 4b. Relative Capital Productivity of Selected Airlines, 1991-2007United States 1991 = 100
Source: Calculations based on airline financial and operating reports.
Figure 4c. Relative Total Factor Productivity of Selected Airlines, 1991-2007United States 1991 = 100
Source: Calculations based on airline financial and operating reports.
25
50
75
100
125
150
175
1991 1994 1997 2000 2003 2006
United States
Malaysia
Thai Air
Singapore
25
50
75
100
125
150
175
1991 1994 1997 2000 2003 2006
Singapore
MalaysiaThai Air
United States
25
50
75
100
125
150
175
1991 1994 1997 2000 2003 2006
United States
Singapore
Malaysia
Thai Air
Figure 5. Passenger Revenue per Unit of Passenger OutputU.S. Dollars
Note: As explained in the text, passenger output is a weighted average of passengers enplaned and 1000 passenger-km flown.
Source: Calculations based on airline financial and operating reports.
108
133
158
123
0
25
50
75
100
125
150
175
200
Thailand Singapore Malaysia U.S.
Figure 6. Measures of Banking Output, Malaysia 1990-2006
Source: Authors' calculations as explained in text.
Table 9. Sources of Growth in Malaysia's Banking Industry, 1990-2006Annual percentage rates of change
Component 1990-2006 1990-1997 1997-2006
Real Output Growth 10.5 14.9 7.1
Contribution of:Labor 1.2 1.5 1.0
(11.3) (9.9) (13.3)Employment 1.1 1.5 0.8
Quality 0.1 0.0 0.2
Capital 5.9 8.5 4.0(56.3) (56.8) (55.3)
TFP 3.1 4.4 2.1(29.6) (29.5) (29.4)
Addenda:Output per worker 9.3 13.2 6.3Source: Bank Negara Malaysia and calculations as explained in text.Note: Percentage contributions to the total are in parentheses
20
60
100
140
180
1990 1994 1998 2002 2006
Inde
x, 2
000
= 10
0
Deposit/Loan
Transactions
Figure 7. Fixed and Mobile Telecommunications Penetration Rate by Country, 1990 - 2006Subscribers per 100 population
Source: ITU 2008
0
20
40
60
80
100
120
140
160
180
Fixed Mobile
Australia Korea Singapore Malaysia Thailand Taiwan United States
1990 2006 1990 2006 1990 2006 1990 2006 1990 2006 1990 2006 1990 2006
Table 10. Summary Statistics of Telecommunications Industry by Country
Australia Korea Malaysia Singapore Thailand TaiwanUnited States
1990 46.7 30.8 9.4 36.3 2.5 31.4 56.91995 61.7 45.4 21.6 49.2 8.2 46.6 72.62000 97.2 114.6 41.9 116.8 14.1 137.0 107.32006 145.8 133.6 92.3 151.7 73.9 165.6 134.5
1990 980.0 379.9 569.1 956.6 754.6 509.5 946.51995 999.7 524.8 589.8 1464.2 650.9 550.2 903.52000 637.1 393.7 398.5 665.7 374.1 315.8 969.42006 904.0 983.3 314.9 614.0 119.1 307.7 725.2
1990 4.8 6.7 2.7 5.2 4.0 6.1 10.21995 7.0 10.5 7.3 14.2 8.1 10.9 12.52000 9.2 38.0 19.7 28.3 11.0 35.2 13.52006 13.8 34.9 40.1 36.8 55.0 49.0 20.4
1990 47.3 38.7 43.7 65.5 66.1 51.1 57.41995 52.3 40.1 42.7 53.6 68.1 47.9 55.72000 52.0 80.6 67.6 84.3 75.5 108.3 44.12006 42.0 65.9 104.2 89.5 218.1 101.1 45.1
1990 0.88 0.53 0.54 1.31 0.93 0.74 0.831995 0.96 0.65 0.52 1.50 0.84 0.67 0.802000 0.65 0.63 0.54 1.16 0.54 0.68 0.762006 0.84 1.24 0.78 1.20 0.57 0.63 0.67
Source: ITU 2008
Revenue per Unit of capital
Penetration Rate (subscribers per 100 population)
Output per Employee
Revenue per Subscriber (U.S. dollars)
Output per Unit of Capital
Table 11. Prices of Telecom Services in Malaysia and the OECD, 2007-8*
Item Malaysia Korea MexicoOECD
Average
Mobile Phone Monthly Rate 18.02 24.91 23.87 33.95
Fixed Phone Monthly Rate 27.53 32.29 43.02 48.18
Broadband Avg Monthly Rate 28.61 37.81 49.81 52.40
Broadband per Mbit/second 26.70 5.54 44.08 20.69
Mobile Phone Monthly Rate 40.28 27.37 36.17 34.04
Fixed Phone Monthly Rate 61.54 35.48 65.18 49.00
Broadband Avg Monthly Rate 63.95 40.65 72.20 48.09
Broadband per Mbit/second 59.69 5.96 63.89 19.16
*The OECD data apply to October 2007 and Malaysia data are reported in July 2008
U.S. dollars
US PPP
Source: Malaysia: Authors' calculations based on operators' websites. Korea and Mexico: OECD Communications Outlook 2007 and OECD Broadband Portal.
Figure 8. Contributions to Growth in Rail Output, 1996 - 2007
Source: See below
1996-2007 2000-2007
Real Output Growth 2.46 5.45Contribution of
Labor -0.66 0.54Employment -1.14 0.08Quality 0.49 0.46
Capital 0.16 0.18TFP 2.98 4.70
Source: Ministry of Transport & Department of Statistics
Table 12. Sources of Growth: Rail Transport, 1996-2007
60
70
80
90
100
110
120
130
140
1996 1998 2000 2002 2004 2006
Inde
x: 1
996
= 10
0Freight
Freight + Inter-city
Total
Inter-City
Freight Commuter
Index values, 1990 = 100
Output Capital EmploymentOutput per
WorkerCapital per
Worker TFP1990 100 100 100 100 100 1001991 114 155 114 100 136 851992 119 172 117 102 148 831993 138 209 121 114 174 851994 151 248 124 122 200 851995 164 302 126 130 239 821996 176 347 128 137 270 811997 174 368 129 135 285 771998 164 365 129 127 282 721999 178 385 128 139 301 762000 181 356 127 143 281 812001 169 359 117 145 307 792002 152 353 107 142 330 742003 161 379 116 139 327 722004 167 345 107 156 321 822005 210 480 154 136 312 72
Table 14. Sources of Growth: Road Haulage, 1990-2005
1990-2005 1990-1997 1998-2005
Output 4.5 7.4 3.6Employment 2.9 3.7 2.5Output per worker 2.1 4.4 1.0
Contribution of:Capital 3.9 7.9 0.7Education 0.4 0.5 0.3Factor Productivity -2.2 -3.7 0.0
Source: Table 13 and authors' calculations.
Table 13. Statistics of Road Haulage, 1990-2005
Source: Department of Statistics, Transport and Communications Services Statistics , various years, and authors' calculations
Table 15. Output and Productivity Growth, Port Operations, 2000-2005
Cargo Throughput
Employ-ment Capital
Output per Worker
Output per Capital TFP
2000 1.00 1.00 1.00 1.00 1.00 1.002001 1.07 1.06 1.00 1.01 1.07 1.112003 1.19 1.11 0.99 1.07 1.20 1.272004 1.28 1.23 1.06 1.03 1.20 1.282005 1.42 1.24 1.03 1.15 1.38 1.48
2000-2005Output 8.3Employment 4.5Output per worker 3.6
Contribution of:Capital -1.0Education 0.1Factor Productivity 4.6
Source: Ministry of Tranportation, Department of Statistics, Transport and Communications Services Statistics , various years, and authors' calculations
Table 16. Services Trade by Type: Malaysia, 1996-2006Millions U.S. Dollars
1996-2006
GDP (Millions Current USD)
Credit 15,136 15.0 13,941 15.4 21,831 14.5 3.7
Transportation services 2,822 2.8 2,802 3.1 4,228 2.8 4.1Travel services 4,477 4.4 5,011 5.5 10,427 6.9 8.8Other services 7,836 7.8 6,127 6.8 7,177 4.8 -0.9
Communications 181 0.2 641 0.4Construction 314 0.3 1,041 0.7Royalties and licence fees 18 0.0 26 0.0Finance and insurance 0 0.0 316 0.3 364 0.2Computer and business services 7,667 7.6 5,136 5.7 4,131 2.7 -6.0Other services 169 0.2 162 0.2 973 0.6 19.1
Debit -17,573 -17.4 -16,747 -18.5 -23,720 -15.7 3.0
Transportation services -5,433 -5.4 -5,890 -6.5 -9,577 -6.4 5.8Travel services -2,569 -2.5 -2,075 -2.3 -4,020 -2.7 4.6Other services -9,571 -9.5 -8,783 -9.7 -10,123 -6.7 0.6
Communications -231 -0.3 -653 -0.4Construction -1,091 -1.2 -1,314 -0.9Royalties and licence fees -546 -0.6 -1,052 -0.7Finance and insurance 0 0.0 -464 -0.5 -735 -0.5Computer and business services -9,404 -9.3 -6,236 -6.9 -4,714 -3.1 -6.7Other services -167 -0.2 -215 -0.2 -1,656 -1.1 25.8
Trade Balance -2,437.2 -2.4 -2,806.9 -3.1 -1,889.4 -1.3
Source: IMF Balance of Payments Statistics
Millions USD
Share of GDP
Millions USD
Avg Annual % Change
Share of GDP
Millions USD
Share of GDP
1996 2006
150,672100,850
2000
90,320
Table 17. Services Trade by Type: Malaysia and Singapore, 2006 Millions U.S. Dollars
GDP (Millions Current USD)
Millions USD Share of GDP Millions USD Share of GDP
Credit 21,831 14.5 59,076 44.7
Transportation services 4,228 2.8 20,975 15.9Travel services 10,427 6.9 7,069 5.3Other services 7,177 4.8 31,032 23.5
Communications 641 0.4 614 0.5Construction 1,041 0.7 666 0.5Royalties and licence fees 26 0.0 730 0.6Finance and insurance 364 0.2 5,530 4.2Computer and business services 4,131 2.7 23,177 17.5Other services 973 0.6 315 0.2
Debit -23,720 -15.7 -61,929 -46.9
Transportation services -9,577 -6.4 -22,947 -17.4Travel services -4,020 -2.7 -10,384 -7.9Other services -10,123 -6.7 -28,598 -21.6
Communications -653 -0.4 -979 -0.7Construction -1,314 -0.9 -262 -0.2Royalties and licence fees -1,052 -0.7 -10,470 -7.9Finance and insurance -735 -0.5 -4,054 -3.1Computer and other services -4,714 -3.1 -12,345 -9.3Other services -1,656 -1.1 -488 -0.4
Source: IMF Balance of Payments Statistics
Malaysia Singapore
150,672 132,158
Table 18(a). Regression Estimates of Determinants of Wages and Salary Earnings
2004 2002 1999 1995
Years of Schooling 0.098 0.104 0.102 0.101(144.9) (136.1) (130.0) (130.4)
Age 0.095 0.104 0.104 0.101(63.9) (64.9) (63.8) (66.3)
Age Squared -0.001 -0.001 -0.001 -0.001(-49.3) (-50.7) (-49.6) (-52.2)
Female -0.274 -0.297 -0.277 -0.293(-44.9) (-46.1) (-43.5) (-46.6)
Constant 6.270 6.019 6.028 5.956(234.0) (206.8) (209.0) (220.0)
adj_R2 0.393 0.381 0.389 0.381Observations 49,628 47,320 43,474 45,881Source: See text. Numbers in parentheses are t-statistics.Dependent variable is measured in logarithms.
Table 18(b). Coefficients on Levels of Schooling Certification, 2004
Schooling Certificate Coefficient YearsAverage Return
Incremental Return
Primary School 0.253 6 0.042 0.042(23.2)
Lower Secondary 0.531 9 0.059 0.093(42.6)
Upper Secondary-V 0.783 11 0.071 0.126(23.1)
Upper Secondary 0.802 11 0.073 0.136(69.3)
Post-Secondary 0.965 13 0.074 0.082(52.3)
College 1.302 17 0.077 0.084(88.3)
Post-Graduate 1.691 19 0.089 0.195(110.9)
Source: See text. Numbers in parentheses are t-statistics.Average return is coefficient value divided by years of schooling.Incremental return is change in the coefficient divided by change in years of schooling
Table A1. Alternative Measures of Employee Compensation, 2000-2003Rm million
2000 2001 2002 2003Value Added, GDP 356,401 355,138 349,723 374,802 415,065Gross National Income 326,844 324,722 349,762 392,177
Compensation of Employees 99,138 95,588 108,165 105,682 112,706Wages and Salaries 81,350 92,817 89,019 95,121Employers' Social Contributions 14,238 15,347 16,663 17,586
Unadjusted Labor Share 0.278 0.269 0.309 0.282 0.272
Adjusted Compensation* 133,515 128,734 145,672 142,328 151,788Adjusted Labor Share of GDP 0.375 0.362 0.417 0.380 0.366
Households and Non-Profit Serving HouseholdsGross National Income 163,807 173,540 177,974 201,071Disposable Income 140,889 160,357 155,191 176,508Adjusted 153,930 175,974 172,858 194,814
Ratio of Compensation to Disposable Income 0.678 0.675 0.681 0.639
Source: Distribution and Use of Income Accounts and Capital Account, Department of Statistics,2007
Distribution and Use of Income Accounts2000 I-O Table
*The compensation adjustment accounts for the labor income of the self-employed and non-wage workers. The adjustment factor from the 2000 I-O Table is applied to remaining years.
Table A2. Contributions to Labor Productivity, Alternative Factor Shares
1987-2007 1987-1997 1998-2007 1987-2007 1987-1997 1998-2007
Labor Share 0.375Capital 2.5 3.4 1.0 1.5 2.3 1.0Education 0.3 0.3 0.3 0.3 0.2 0.4Factor Productivity 0.9 1.7 1.6 0.4 -0.4 2.3
Labor Share 0.5Capital 1.9 2.7 0.8 0.7 1.1 0.5Education 0.4 0.5 0.4 0.4 0.3 0.5Factor Productivity 1.3 2.3 1.7 1.1 0.7 2.7
Labor Share 0.6Capital 1.5 2.1 0.6 0.1 0.2 0.1Education 0.5 0.5 0.5 0.5 0.3 0.6Factor Productivity 1.6 2.8 1.8 1.6 1.6 3.0
Labor Share 0.7Capital 1.1 1.5 0.5 -0.5 -0.7 -0.3Education 0.6 0.6 0.6 0.5 0.4 0.7Factor Productivity 1.9 3.3 1.9 2.2 2.4 3.4
1987-2007 1987-1997 1998-2007 1987-2007 1987-1997 1998-2007
Labor Share 0.375Capital 0.4 -0.9 1.2 1.0 1.7 0.2Education 0.2 0.2 0.2 0.3 0.3 0.3Factor Productivity 2.0 3.4 2.2 2.5 4.4 1.3
Labor Share 0.5Capital 0.4 -0.8 1.1 0.8 1.3 0.2Education 0.3 0.3 0.2 0.4 0.3 0.4Factor Productivity 1.9 3.2 2.3 2.7 4.7 1.2
Labor Share 0.6Capital 0.3 -0.7 1.0 0.6 1.0 0.1Education 0.3 0.3 0.3 0.4 0.4 0.5Factor Productivity 1.9 3.1 2.4 2.8 4.9 1.2
Labor Share 0.7Capital 0.3 -0.6 0.8 0.4 0.7 0.1Education 0.4 0.4 0.3 0.5 0.5 0.5Factor Productivity 1.9 2.9 2.4 2.9 5.2 1.2
Note: Values for contributions from land are omitted
Total Economy Agriculture
Industry Services
