V. GROWTH ACCOUNTINGANDTHE MEDIUM-TERM OUTLOOKIN THAILAND1
1. Thailand has gradually recovered from the crisis; however, recent GDP growth rates remain well below the average recorded in previous decades (Text Figure). As noted in Chapters II and III, a prerequisite for the restoration of robust economic growth is an acceleration of bank and corporate debt restructuring. This chapter goes beyond this, to examine the role of total factor productivity (TFP) and supporting policies to enhance economic growth. The chapter uses a growth accounting framework to examine Thailand’s growth performance before and after the crisis. It draws implications for the medium-term outlook, with a view to establishing the conditions necessary for Thailand to return to growth rates of at least 5-6 percent.
2. A principal finding is that, in the future, economic growth would have to be driven by higher TFP growth. The high growth rates of the pre-crisis period were driven by capital accumulation, rather than TFP growth. Indeed, TFP growth slowed during the 1990s. As capital accumulation is expected to remain modest in the medium term, economic growth will have to be increasingly driven by higher TFP growth and, to a lesser extent, employment growth. A pick-up in TFP growth, in turn, will require maintenance of an open trade and investment regime, as well as investments in human capital.
B. Growth Accounting and Methodology
3. TFP measures the efficiency of a given set of input factors (normally capital and labor) in generating output. Alternatively, it can be thought of as the level of technological development in the economy; a given amount of factor input will generate more or less output depending on the technological capacity. TFP is an important concept in the economic growth literature, because output growth (per capita) is typically regarded as more sustainable if driven by improvements in TFP rather than capital accumulation; a given rate of capital accumulation will gradually lead to lower rates of output growth as diminishing returns set in.2
4. TFP growth can be measured empirically as the difference between growth in output and growth in labor and capital, for given estimates of the technological factor shares.3 Different ways of measuring factor shares have been proposed in the literature. The most common ones are “the national income approach” and “the regression approach.” However, both approaches suffer from several methodological shortcomings. For example, the national income approach implicitly assumes that capital and labor markets are perfectly competitive and that the income accruing to each factor is always equal to the value of its marginal product. The regression approach typically assumes that the factor shares are constant over time and the growth rates of the input factors are exogenous. In both cases, the assumptions are often violated in practice, yielding biased estimates of the factor shares and, therefore, the TFP growth rates. Instead, an alternative approach—based on Sarel (1997)—is used in this chapter. The approach basically derives the aggregate capital share by taking the weighted average of the capital shares in different sectors (agriculture, manufacturing, construction, etc), with the weights equal to the sectors’ proportion of Thailand’s GDP. The capital shares for the various sectors are assumed to be equal to what has been found in a large sample of other countries, where data availability has allowed for a thorough estimation of the factor shares (see Appendix for further details).4 Thus, the aggregate capital share varies as the composition of GDP changes, yielding an annual time-series of this parameter. The TFP growth rate in Thailand was then estimated for each year by subtracting capital and labor growth, weighted by their respective factor shares, from output growth.5
Growth in Output, Factor Inputs, and TFP, 1981–2000
5. The high rate of output growth during the 1980s and early 1990s was mainly driven by capital accumulation and, to a lesser extent, TFP growth. The Text Figure plots Thailand’s annual growth rates of output, factor inputs, and TFP for 1981–2000. It can be noted that the high annual GDP growth rates (averaging about 8 percent) between 1981–96 were largely explained by high rates of capital accumulation. In fact, Thailand experienced an investment boom during the first half of the 1990s such that its investment rate (as a share of GDP) was nearly the highest in Asia (Text Table). The high rates of investment led to a sharp increase in the capital-output ratio, and to a declining trend in the marginal product of capital (Text Figure).6 Taken together, these findings are indicative of a degree of “over-investment” in Thailand in the period before the Asian crisis.7 In addition to the high rates of capital accumulation, output growth was also explained by a relatively robust rate of TFP growth (averaging nearly 4 percent per year), possibly reflecting factors such as a high degree of openness to trade and foreign investment (see further discussion below). The findings are similar to what has been found in several other studies.8 In particular, Sarel (1997) compares the growth performance of several Asian countries, and shows that Thailand’s accumulation of capital was substantially higher than in other Asian countries in the early 1990s, although its capital-output ratio was on average somewhat lower than elsewhere.9 He also finds that TFP growth played a role in explaining Thailand’s high output growth between 1978–96, in line with other countries in the region.
Capital-Output Ratio and Marginal Product of Capital
|Thailand In 1998||2.3||12.7|
6. The collapse of output growth during the Asian crisis (1997–2000) is reflected in a substantial slowdown of capital accumulation and negative TFP growth. The capital-output ratio peaked in 1998, as the slowdown in output growth was more pronounced than the slowdown in capital growth. As a consequence, Thailand’s marginal product of capital continued to decline, and by 1998 was lower than the 1991–96 average for several other Asian countries (see earlier Text Table). However, a trend-break in the capital-output ratio and marginal product of capital is evident in 1998, possibly pointing to a reversal of the overinvestment that took place during the 1990s. Indeed, Thailand’s investment rate was lower than in most other Asian countries during 1997–2000. Meanwhile, TFP growth is estimated to have been negative during this period. This may seem odd, as it is unclear why the overall technological level would deteriorate in the economy. The result is, however, partly explained by a business cycle phenomenon, as explained below.
7. Taking into account the cyclical pattern of output growth, indications are that the slowdown in TFP growth in fact began in the early 1990s, and has held up reasonably well in recent years. It is likely that measured TFP growth is affected by the business cycle in the short-run. For example, if firms find it difficult to adjust the capital stock swiftly—firms rarely scrap capital in the face of a short-term downturn—aggregate data would indicate higher rates of TFP growth during booms and lower rates during recessions.10 To address this problem, effectively arising from changes in capacity utilization, the TFP growth rates were recalculated using the potential (rather than actual) rate of output growth (Text Figure).11 The results now indicate that TFP growth began slowing in the early 1990s, and has since remained at about 2 percent per year (see Text Table). Thus, even after controlling for the business cycle element, it is clear that TFP growth was about 1½ percentage points lower per year during the 1990s compared to the 1980s. This indicates that the exceptionally high investment rates during the early 1990s were offset by a substantial reduction in the efficiency by which additional capital (and labor) was used. This lower rate of efficiency gain has continued in recent years. Thus, the negative TFP growth rate that was derived above by using actual GDP is likely less accurate and largely driven by the sharp drop in actual output during 1997–98.
Actual and Potential CDF Growth
|TFP based on actual GDP||3.8||4.0||−1.7|
|TFP based on potential GDP||3.4||2.2||2.3|
8. The large capital accumulation in the 1980s and early 1990s reflected increases in both “dwellings” and “machinery and equipment”. The pre-crisis investment boom was accompanied by a sharp rise in credit (both by banks and finance companies) to the real estate sector. Construction of residential and office property increased sharply, although demand seemed to be lagging as vacancy rates rose.12 This development was also reflected in high growth rates of the capital stock classified as “ownership of dwelling.” However, the high growth in the aggregate capital stock was not driven exclusively by an increase in dwellings. Accumulation of other types of capital—defined as “machinery and equipment”—was also very rapid, growing on average by about 9 percent per year between 1981–96 (Text Table). As a consequence, even after excluding dwellings from the measure of the capital stock, the capital-output ratio rose while the marginal product of capital fell in the early 1990 (see Text Figures on next page).13
|Total net capital||8.2||11.8||2.0|
|Machinery and Equipment||7.0||12.1||2.5|
|Share of dwelling in total capital||22.5||25.7||23.8|
Marginal Product of Capital
9. The evolution of TFP growth in Thailand is similar to developments elsewhere in the region. A number of studies have estimated TFP growth rates in several Asian countries. As noted earlier, the studies differ with regard to methodology, data, and estimation technique, and the results are therefore not easily comparable. Nevertheless, it is interesting to note that three different studies covering various (albeit overlapping) time periods show that TFP growth has slowed in Thailand during the last two decades; a result which is consistent with the findings in the current study (Text Table). Also, the estimated level and pattern of the TFP growth rate in Thailand is fairly similar to what has been found in other countries.14
|Study: Sample period:||Collins and Bosworth|
|Lee et al.|
|Thailand, current study 1/||3.1||2.1||1.9|
Based on potential GDP.
Based on potential GDP.
D. Medium-term Outlook
10. Over the medium term, high rates of economic growth would be expected to be driven by TFP growth. As factor accumulation—especially capital—is likely to be limited in the medium-term, high rates of output growth ought to be driven by high TFP growth. For example, in the staff’s medium-term projection (see the staff report), the GDP growth rate is projected at 5-6 percent while gross investment grows by 8-9 percent. However, most of the investment is expected to simply replace depreciated capital and the net capital accumulation is projected to be much lower (about 2-3 percent). Likewise, employment growth is projected to be positive but modest (about 2 percent). Taken together, this implies that annual output growth of 5-6 percent would require TFP growth of about 3-4 percent per year.
11. The growth rate of the capital stock would likely be lower than output growth in order to generate a pick-up in the marginal product of capital in the medium term. Given the indications of over-investment during the 1990s, it is likely that firms would accumulate relatively modest amounts of capital in the medium term, and focus instead on improving the efficiency of their operations (e.g., through corporate restructuring). This would also result in a decline in the capital-output ratio. For example, a gradual increase in the net capital stock of 2-3 percent per year together with annual output growth of about 5-6 percent would imply that the capital-output ratio would fall back to its average 1991-96 level within five years. Such an increase in the net capital stock together with an annual depreciation rate of about 6 percent (which is close to the average rate of depreciation during the last five years) translates into a growth rate of gross fixed capital formation of about 8-9 percent in the medium-term.15
Unemployment and Participation Rates
12. Thailand’s labor market is relatively flexible and unemployment has traditionally been low.16 However, as the crisis hit Thailand in 1997, the labor market was adversely affected and employment fell. This was especially pronounced in the construction sector, which shed 1.2 million jobs during 1997–99. As a result, the official unemployment rate rose from 1.7 percent in 1995 to 4.4 percent in 1998 (Text Figure). Moreover, the participation rate—defined as the ratio of the labor force to population aged 13 and above—fell in the second half of the 1990s, indicating that the more difficult labor market conditions discouraged people from participating in the formal labor market.17 Also, a degree of labor hoarding became evident, as the share of “underemployed” workers rose in 1997–98.18 These trends have been partly reversed during the last two years as the economy began to recover. Employment grew by about 2 percent in 1999 and 2000, respectively, and the official unemployment rate fell to 3.6 percent by 2000. The participation rate, however, has remained well below pre-crisis levels.
13. As the economy continues to recover, a gradual pick-up in employment could be expected in the medium-term. Although employment opportunities in the construction sector would be expected to remain constrained in the near future, it is likely that demand for labor in the manufacturing sector and, in particular, the service sector would pick up as economic activity improves. Likewise, it is possible that the overall participation rate will increase, as workers who left the labor force during the crisis—for schooling and retraining—return to work, but also reflecting demographic factors; the share of the population below the age of 13 has been on a declining trend since the early 1980s, which is likely to be conducive to a higher participation rate in the medium term.19 Taken together, these factors suggest that labor input would grow by nearly 2 percent per year during the coming years, compared with an annual population growth rate of about 1 percent (which is equal to its average growth rate during the past five years). This would also imply that the unemployment rate would fall by 1-1½ percentage points.
14. A robust rate of TFP growth would be crucial to reach high rates of output growth in the medium-term. Given the possibility of low rates of capital and employment growth, a substantial improvement in the efficiency of the factor inputs will be essential to reach GDP growth rates that are closer to the pre-crisis rates. For example, capital growth of about 3 percent coupled with employment growth of 2 percent would imply that TFP would need to grow by more than 3 percent for GDP growth to reach 5-6 percent. This example illustrates the importance of understanding the factors that would drive TFP growth.
E. Determinants of TFP Growth
15. Ample theoretical and empirical literature indicates that TFP and output growth are positively associated with trade openness as well as human capital indicators. In the case of Thailand, it is also possible that TFP growth could be stimulated by reaping further benefits in the areas of information technology (IT) and research and development (R&D).
16. There are several channels through which an open trade and investment regime could benefit productivity growth. For example, trade facilitates technology transfers from abroad, provides incentives for domestic firms to innovate, and puts pressure on firms to enhance efficiency owing to foreign competition. Indeed, a number of cross-country studies have found a positive empirical relationship between various ‘openness-indicators’ and output growth.20 In particular, Coe et. al. (1997) and Edwards (1998) show that TFP growth is higher in more open economies.
17. The relatively robust rates of TFP growth in Thailand in the past appear to be, in part, a consequence of its open trade and investment regime. Thailand’s openness, as measured by the ratios of exports plus imports to GDP and foreign investment to GDP, are higher than in many other Asian countries, although not quite as high as in Singapore and Malaysia (Text Table).21 A simple time-series chart suggests that TFP growth in Thailand is positively correlated with changes in openness (defined as exports plus imports of goods and services as a share of GDP) until 1996. Moreover, Tinakorn and Sussangkarn (1998) shows that this relationship is statistically significant in Thailand for the period 1980–95, even after controlling for other factors that are important for productivity growth.22
18. Skills development is another key factor in generating high and sustainable output growth. The importance of the human capital stock in explaining economic growth is well established.23 The fact that this aspect is not taken into account in the simple growth accounting exercise above could be viewed as a shortcoming of such an exercise. More precisely, to the extent that improvements in TFP are explained by a more skilled employment base rather than more efficient use of factor inputs, the TFP growth rates would be overestimated while labor inputs would be underestimated. A number of studies therefore adjust the labor data (by, for example, the number of years of schooling) to account for improvements in the quality of labor. However, an alternative view is to argue that a more educated labor force will lead to improved technology, and higher TFP growth rates therefore would be explained by skills development.
TFP Growth and Openness
19. Although Thailand has a strong foundation in basic education, there is scope for improvement in the area of higher education. The human capital stock has been enhanced in Thailand during the past decades, as schooling and training has become more widespread.24 For example, Tinakorn and Sussangkarn (1998) construct an index of labor quality, and show that this index has improved almost continuously in every sector since 1980. Consequently, after adjusting labor data for this quality improvement, they find that the contribution of TFP growth to output growth is about 0.8 percentage points lower per year between 1980–95, while ‘effective’ labor growth is correspondingly higher. Nevertheless, enrollment rates at the secondary and tertiary levels are lower in Thailand than in several other Asian countries, with particular gaps in the areas of science and technology (Text Table). Improvements in these areas could help stimulate output and TFP growth in the medium term.
|Gross Enrollment Rates in 1997 (in percent)|
|Gross rate||Gross rate||Share in technology 2/|
|Lower middle income countries 1/||64||22||…|
As of 1995. Technology enrollment include natural science engineering, ant maths/computing.
As of 1995. Technology enrollment include natural science engineering, ant maths/computing.
Information technology and R&D
20. TFP growth could possibly be enhanced in Thailand by further adoption of information and communication related technology (ICT). It has been argued that the high rates of output growth in the U.S. during the last decade is in part explained by the very rapid growth in the use of computers and information technology (see Oliner and Sichel (2000)). Likewise, a recent study by Lee and Khatri (2001) notes that the high output growth in Asia in the early 1990s is to a large extent attributed to strong ICT-related exports. Investment in ICT activities has also contributed to a degree of capital deepening, although the impact on TFP growth has been relatively modest thus far.25 The study also shows that Thailand compares poorly with other Asian countries with regard to investment in ICT (Text Table) and other IT-indicators, such as computer penetration and e-commerce. Government initiatives to develop a comprehensive information technology framework are now underway, with the aim of facilitating access and diffusion of information technology in all segments of the society. The implementation of this framework could enhance the overall technological capacity of the Thai economy in the medium term.
|Non-ICT capital stock||ICT capital stock||Non-ICT capital stock||ICT capital stock|
|Taiwan Province of China||1.26||Korea||0.13||Taiwan Province of China||1.39||Korea||0.14|
|Philippines||1.23||Taiwan Province of China||0.09||Philippines||1.29||Taiwan Province of China||0.11|
|Hong Kong||0.97||Thailand||0.04||Hong Kong||1.02||Thailand||0.04|
21. Thailand is also lagging behind other countries in indicators of technology-related capabilities, such as expenditures on R&D activities, number of researchers per capita, and international patenting. For example, it is estimated that the total amount of expenditure on R&D as a share of GDP was about 0.1 percent in Thailand in 1995, compared with about 3 percent in Korea, while the number of researchers per 10,0000 population was about 2, compared to 30 in Korea (see Arnold et. al., 2000).26
22. Economic growth will need to be driven by TFP growth rather than accumulation of capital and labor in the medium term. This contrasts with the composition of output growth during the past two decades, which was largely explained by capital accumulation. The need of TFP-led output growth underscores the importance of maintaining an environment that is conducive to efficiency gains and technological development. Factors that appear crucial in contributing to such a development include: preserving an open trade and investment regime, further emphasis on education and skills development, the implementation of initiatives to stimulate R&D activities, and the adoption and diffusion of information technology.
Arnoldet al. 2000 “Enhancing Policy and Institutional Support for Industrial Technology Development in Thailand,” Draft Report World Bank.
BarroR. andJ-W.Lee1994 “Sources of Economic Growth,” Carnegie-Rochester Conference Series on Public Policy Vol. 401–46.
Ben-DavidD.1993 “Equalizing Exchange: Trade Liberalization and Income Convergence,” Quarterly Journal of Economics Vol. 108(3)653–680.
CoeD. T.E.Helpman andA. W.Hoffinaister1997 “North-South R&D Spillovers,” Economic Journal Vol. 107134–149.
CoeD. T. andR.Moghadam1993 “Capital and Trade as Engines of Growth in France,” International Monetary Fund Staff Papers Vol. 40542–566.
CollinsS. andB.Bosworth1996 “Economic Growth in East Asia: Accumulation versus Assimilation,” Brookings Papers on Economic Activity Vol. 2135–191.
DollarD.1992 “Outward-Oriented Developing Economies Real Do Grow More Rapidly: Evidence from 95 LDCs, 1976-85,” Economic Development and Cultural Change Vol. 40523–544.
EdwardsS.1998 “Openness, Productivity and Growth: What Do We Really Know?” Economic Journal Vol. 108383–398.
FelipeJ.1999 “Total Factor Productivity Growth in East Asia: A Critical Survey,” The Journal of Development Studies Vol. 351–41.
JonssonG. andA.Subramanian2001 “Dynamic Gains from Trade: Evidence from South Africa,” international Monetary Fund Staff Papers forthcoming.
LeeI. H. andY.Khatri2001 “The Role of the New Economy in Asia,” International Monetary Fund mimeo forthcoming.
OlinerS. andD.Sichel2000 “The Resurgence of Growth in the late 1990s: Is Information Technology the Story?” Federal Reserve Board Working PaperFebruary.
RodriguezD. andF.Rodrik1999 “Trade Policy and Economic Growth: A Skeptic's Guide to the Cross-National Evidence,” NBER Working Paper No. 7081 National Bureau of Economic Research.
SachsJ. andA.Warner1995 “Economic Reform and the Process of Global Integration,” Brookings Papers on Economic Activity Vol. 11–118.
SarelM.1997 “Growth and Productivity in ASEAN Countries,” Working Paper WP/97/97 International Monetary Fund.
SiamwallaA.2000 “Anatomy of the Thai Economic Crisis,” in Thailand Beyond the Crisis byP.Warr (editor) Routledge, Londonforthcoming.
TinakornP. andC.Sussangkarn1998 “Total Factor Productivity Growth in Thailand: 1980-95,” manuscriptThailand Development Research Institute.
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1. The simplest growth accounting exercise starts with a Cobb-Douglas production function:
where Y, K, and L denote output, capital, and labor, respectively, A refers to the technological or TFP level, and the parameters a and (1-α) are the technological factor shares. In growth terms, expression (1) translates to:$$$
where ΔY/Y, ΔK/K, and ΔL/L, denote growth in output, capital, and labor, respectively, while ΔA/A, is the technological progress or, put differently, TFP growth. In the empirical analysis, TFP growth is calculated residually given observations of, Y, K, L, and an estimation of the parameter α.
2. The marginal product of capital can be derived from expression (1) as dY/dK = αY/K. Thus, given an estimate of α, it is easy to empirically calculate the marginal product of capital at any point in time.
3. Different methods for estimating the capital share, α, have been proposed, including the national income approach and the regression approach. However, both approaches suffer from statistical shortcomings, and an alternative approach introduced by Sarel (1997) is used in the current paper. This approach uses detailed data on the compensation for the use of capital inputs for nine different economic activities for 26 countries (one-digit ISIC classification). The average of the sample is then defined as the typical capital share in the specific activity. The aggregate value of the capital share is derived by weighing the sector-specific capital shares by their respective share in GDP. The estimated capital shares in the different sectors are: (i) agriculture, 0.275, (ii) mining and quarrying, 0.601, (iii) manufacturing, 0.308, (iv) utilities, 0.538, (v) construction, 0.189, (vi) commerce, 0.232, (vii) transport and communication, 0.320, (viii) financial and business services, 0.604, and (ix) government and other services, 0.081.
4. When estimating the marginal productivity of ‘dwelling’ and ‘machinery and equipment’, respectively, the following production function is used
i.e., the capital stock is decomposed into dwelling, KD, and machinery, KM, respectively, where β denotes the factor share of KD. In the empirical analysis, β is assumed to 0.26, which is equal to the average share of dwelling in total capital between 1980–2000.
Prepared by Gunnar Jonsson.
Indeed, per capita output growth is exclusively driven by TFP growth in the simplest neoclassical growth model (assuming that population growth equals employment growth).
See the Appendix for a more complete description of the growth accounting framework and the methodology for estimating the factor shares.
Sarel (1997) shows that the estimated capital shares in a specific sector do not vary with the level of income.
The labor share was defined as one minus the capital share. All data is from the National Economic and Social Development Board (NESDB).
The marginal product of capital is calculated as the capital share divided by the capital output ratio (see Appendix for details).
Tinakorn and Sussangkarn (1998) also find empirical evidence of a degree of pre-crisis over-investment in Thailand. In particular, they show that there exists a non-linear relationship between productivity and capital growth, implying that the capital accumulation exhibited diminishing returns.
See, for example, Young (1994, 1995), Collins and Bosworth (1997), Sarel (1997), and Felipe (1999). Owing to differences in methodology, estimation technique, data, and sample period, the results in these studies differ with regard to the estimated rates of TFP growth. However, the general conclusion is that capital accumulation explained a substantial part of East Asia’s exceptional growth performance during the 1980s and early 1990s.
The differences between the numbers for the capital-output ratio and marginal product of capital in the figure and the table above are due to different data sources and estimates of Thailand’s capital stock. The Text Table is based on Sarel (1997), who derives capital stock data from investment flows using Penn World Tables, while the Text Figure uses actual capital stock data as published by the NESDB.
Alternatively, a cyclical element in the measure of TFP growth could appear if the labor market is inflexible, and the firms engage in some labor hoarding behavior.
The potential GDP series was extracted from the actual GDP series by using a Hodrick-Prescott (HP) filter (with the smoothing parameter set to 100). The resulting series indicate that potential GDP dropped from nearly 8 percent in the 1980s to about 3 percent in 2000. A potential GDP growth rate of about 4 percent during the second half of the 1990s is consistent with the observation that, during the same period, capacity utilization in the manufacturing sector fell by 20 percentage points while manufacturing production grew at a modest rate.
See IMF (1999), Thailand—Selected Issues, SM/99/304 (Chapters I and III).
See Appendix for a description of the assumptions underlying the calculations of the marginal product of different kinds of capital.
The main exception seems to be the Philippines, where the evolution of TFP growth is the opposite of the other countries.
It is possible that firms might increase the rate of capital scrapping in the coming years as a response to the previous over-investment. As a result, the depreciation rate could rise, implying that a given amount of gross fixed capital formation will generate a relatively smaller increase in the net capital stock.
The official unemployment rate was, on average, 2½ percent during 1991–95. However, this figure excludes the seasonally unemployed, who typically account for another 2½ percent of the labor force. The seasonally unemployment rate has remained fairly stable during the 1990s at around 2 percent per year, although it temporarily increased to 2.7 percent in 1998.
The participation rate was on average 74½ percent in 1991–95, compared with 69 percent in 1996–2000.
The definition of ‘underemployed’ is divided into the ‘severely underemployed’ defined as working less than 20 hours a week, and ‘moderately underemployed’ defined as working 20–34 hours per week. See Siamwalla (2000) for further discussions.
The share of the population below age 13 has fallen from 34 percent in 1980 to 29 percent in 1990 to 26 percent in 2000.
See, for example, Dollar (1992), Sachs and Warner (1995) and Ben-David (1993). Rodriguez and Rodrik (1999) have noted, however, that a more relevant question is whether liberal trade policy is good for growth, rather than whether openness—defined in terms of trade outcomes—is positively related to growth, and that the empirical evidence for the former proposition is less convincing.
It can be noted, however, that Thailand’s simple average tariff rate is higher than in several other Asian countries, although its effective rate is much lower, in part owing to a complex system of rebates and exemptions.
A similar positive relationship between openness and TFP growth have been found also for some other economies using time-series data; see, for example, Coe and Moghadam (1993) and Jonsson and Subramanian (2001).
However, the primary enrollment rate has fallen somewhat during the 1990s.
ICT-export is defined as computer and communication equipment and electronic components, while ICT-investment is defined as investment in telecommunication, computer hardware, and computer software.
A more recent study by the National Science and Technology Development Agency indicates that R&D expenditures had doubled by 1999 (i.e., it increased to 0.2 percent of GDP), which still, however, is much lower than in many other countries in Asia.