Entreprenuership, Technical Progress and Economic Growth: A Quantitative Analysis of Hong Kong,

Transcription

1 Entreprenuership, Technical Progress and Economic Growth: A Quantitative Analysis of Hong Kong, Jonathan Cheng Research Master with Training This thesis is submitted for the degree of Research Master with Training of Murdoch University 2017

2 ABSTRACT Studies within the economics discipline have consistently treated productivity growth or total factor productivity (TFP) as the critical factor in generating economic growth (Solow, 1956, 1957; Swan, 1956; Jorgenson and Griliches, 1967; Harcourt, 2006; Taylor, 2007). The rationale and importance of technological progress in driving long-run aggregate output growth can be explained through the mechanism of the Solow (1956) Swan (1956) growth model. Utilising the Solow (1956) and Swan (1956) growth framework, the primary aim of this dissertation is to quantify the impact of technological progress, in the form of total factor productivity (TFP) growth, on Hong Kong s aggregate output growth over the years The bulk of studies on estimating TFP growth on Hong Kong covered the period between the 1960s and the 1980s. Very little has been done after that. Hence, an update of Hong Kong s TFP growth is long overdue. Above all, Hong Kong s contemporary production structure resembles very little that of the 1960s-1980s period, where the bulk of the literature on Hong Kong s TFP growth tends to be concentrated. Examining Hong Kong s contemporary production structure, especially through the period , will make a useful and meaningful contribution to the current stock of knowledge about the economic growth of Hong Kong. Over the period , on average, TFP contributed annually around 41.1 per cent to aggregate output growth. Based on the Solow-Swan growth framework, Hong Kong s aggregate output for the period was productivity driven and

3 as such is sustainable. Although on an averaged basis TFP s contribution to output growth was positive and significant, however on a year-to-year basis, TFP growth was found to be highly cyclical. A possible explanation to the cyclical nature of Hong Kong s TFP growth can be found in the real business cycles analysis in that economic downturns are periods of technological regress (Mankiw, 1989; Prescott, 1986). During the period , the estimated average elasticity of TFP growth with respect to aggregate output for Hong Kong, shows that for every one per cent increase in TFP growth resulted in 0.49 per cent increase in GDP growth. While the Solow-Swan growth model postulates that technological progress as captured by TFP growth is the engine to sustainable economic growth, it does not provide a formal explanation on how technological progress comes about. Instead, technological progress is estimated from a residual, and hence it is treated exogenously. The real business cycles theory can only explains the relationship between the residual (TFP) and aggregate output growth. What is driving TFP growth has yet to be explained. The analysis found in Chapter Four suggests that human capital accumulation in the form of entrepreneurship could be driving Hong Kong s TFP growth.

4 Table of Contents Chapter One: Study Overview 1.0 Introduction Structure of Dissertation 4 Chapter Two: Growth Framework: Solow-Swan Growth Analysis 2.0 Introduction The Solow-Swan Growth Model The Dynamics of the Model Technical Progress and Output Growth the Swan s Way Total Productivity and Economic Growth Conclusion 27 Chapter Three: TFP Growth, Hong Kong, Introduction Methodological Framework for Estimating TFP Growth Sources of Hong Kong s Economic Growth, Real Business Cycles Theory Conclusion 42 Chapter Four: Entrepreneurs and Productivity Growth 4.0 Introduction Human Capital Accumulation, Entrepreneurship and TFP Growth Entrepreneurial Spirit: A Possible Driver of TFP Growth 49

5 4.3 The Impact of Entrepreneurial Spirit on TFP Growth Adjusting the Value of β to Re-measure TFP Growth Conclusion 80 Chapter Five: Concluding Remarks 5.0 Summary Policy Implications Future Research 85 References 89 Appendix 1 95

6 List of Figures 2.1 Dynamics of the Solow-Swan Growth Model Technical Progress and Output Growth the Swan s Way TFP and Output Growth, US, TFP and Output Growth, Hong Kong, Technology Branch and Next Generation of Technology A Random Step Function of Output Growth The Effort and Wage relationship: The Solow Condition 74

7 List of Tables 2.1 TFP Growth in Selected Countries and Regions, Annual Growth of Total Factor Productivity of Selected Countries, Accumulation and Assimilation of Factor Inputs Annual Growths of Real Output (y), Real Capital (k), and Labour (l), Hong Kong, , Per cent Different values for selected countries Average Annual Growth in Real Output (y), Capital contribution (k), and Labour contribution (l), Hong Kong, , Per cent TFP Growth Rates, Hong Kong, , Per cent Annual Growths of Real Output (y), Capital Contribution (k), Labour Contribution (l), and TFP, Hong Kong, , Per cent TFP Growth Estimates on Selected Countries Coefficient of and β and TFP growth for Malaysia, , Annual Average Efficiency Wages and Elasticity Values (e) of Full-Time Government Employees in Selected Countries β values and TFP growth, Hong Kong, α values and TFP growth, Hong Kong,

8 CHAPTER ONE STUDY OVERVIEW 1.0 Introduction Hong Kong is one of the world s fastest growing economies in the post-war period. Over the years , real output grew at an annual rate of 8.85 per cent and real labour productivity grew at a yearly rate of 6.03 per cent (Gapinski, 1997). In terms of economic growth performance, Hong Kong easily bested the US. The comparable rate of 3.28 per cent for the US provides some magnitude to that accomplishment (Gapinski, 1997). From 1991 to 2015 real output growth averaged 5.88 per cent per year which nearly doubled that of the US over the same period. Even more miraculous (Gapinski, 1997; World Bank, 1993) is that Hong Kong has achieved per capita income levels of the OECD countries in a time span of less than 40 years compared to 80 years or more for the UK, US, France and Germany to achieve such growth (Nelson and Pack, 1999). The United Nations (1997) reported that for the period , Hong Kong was catching up with the OECD countries per capita income at rate of more than 3 per cent per year. What is also worth mentioning is that the rapid economic transformation from a dying city as described by an American journalist visiting Hong Kong in 1951 (cited in Ho, 1992, p.5) to an economic miracle (World Bank, 1993; Gapinski, 1997) was achieved without planning or even premeditation (Chen, 1979, p.333). The government played a very small role in the economic development of Hong Kong and the entire experience of rapid industrialization represented a series of 1

9 successful self-adjustments to changes in the internal and external economic environment (Chen, 1979, p.333). Quantifying and decomposing Hong Kong s long-run economic growth performance is important and meaningful because it enables us to understand the processes of economic growth in East Asia. This is important especially when considering the fact that, income disparities between the developed and developing countries have widened considerably, producing a ratio of 60:1 in the 1990s (United Nations, 1997). Some 25 years later, there is little sign that this trend will reverse in the near future. Are the benefits of higher income, and therefore living standards, found only in advanced economies? Is there anything that poor and backward countries could do to improve their citizens living standards? In the last 40 years of the last millennium, a small group of initially poor, economically and technologically backward countries in East Asia managed to break away from this persistent trend. As Taylor (2007, p.1) puts it the growth performance in these countries not only exceeded those with comparable income levels in 1960 but outperformed virtually all the countries in the world Why have only a small group of countries managed to grow at such a rapid pace while most of the developing countries around the world have either stagnated or gone backward? In the last 30 years or so witnessed a large and rapid expansion of the development and growth literature with huge desire to find the determinants of economic growth in this part of the world (Taylor, 2007, p.2). A strong reason for many of these studies is that once they have found the key determinants in driving 2

10 the East Asia growth miracle, they can then be applied to poor and developing countries, and in the process narrowing the income disparities gap. The main aim of this small dissertation is to estimate the sources of economic growth of Hong Kong covering the period The neoclassical growth analysis will be employed to decompose Hong Kong s economic growth into three components. The first is due to the growth of labour input, the second is due to the growth of capital input, and the third is due to technological progress as captured by an increase in both the productivity of capital and labour, which is also known as total factor productivity (TFP). The neoclassical growth model was originally developed by the independent works of Solow (1956) and Swan (1956), and due to the similarities in their approach, it is appropriate to refer to the neoclassical growth framework as a Solow-Swan growth model. Solow (1957) tested the model (1956) on the U.S. and found that technological progress or TFP growth accounted for seven-eighths of the U.S. growth per worker over the first half of the twentieth century. Since then, the Solow-Swan growth model has become the standard and most widely used approach to quantify or measure the contribution of technological progress to output growth. The Solow-Swan model not only provides a razor-edge measurement method for technological progress (Denison, 1962, 1967; Harcourt, 2006; Taylor, 2007) but of more importance, the model demonstrates that technological progress (as captured by TFP) is the engine of long-run sustainable growth (Solow, 1956; Swan 1956; Denison, 1962, 1967). 3

11 1.1 Structure of dissertation This dissertation consists of 5 chapters and one appendix. The information in the appendix provides the macroeconomic data on real GDP, real capital stock, and employment (over the period) that are required in the formulation of the research methodology adopted in this dissertation. Chapter One provides the main aim of the dissertation and the justification for using the Solow-Swan model to quantify the economic growth of Hong Kong. A bulk of studies on estimating TFP growth on Hong Kong covered the period between the 1960s and the 1980s. Very little has been done after that. Hence, an update of Hong Kong s TFP growth is long overdue. Above all, Hong Kong s contemporary production structure differs that of the period, where the bulk of the literature on Hong Kong s TFP growth tends to be concentrated. Examining Hong Kong s contemporary production structure, especially the period , will make a useful and meaningful contribution to the current stock of knowledge about the economic growth of Hong Kong. Chapter Two presents a brief overview of the Solow-Swan growth model to form the theoretical basis for the estimations of TFP growth found in Chapter Three. This is then followed by a brief survey of TFP growth in selected East Asian economies to give some comparisons against Hong Kong s growth performance. Using the macroeconomic data found in Appendix One, Chapter Three details the empirical model and quantifies the sources of economic growth in Hong Kong for the period

12 In Chapter Three, the relationship between TFP and sustainable long run economic growth is explored and measured. But, what drives TFP growth in Hong Kong over the period has yet to be explained. To put it in another way, the neoclassical model has the engine, but has left its driver out. This elusive treatment of technological progress had led critics (Harcourt, 1972, 2006; Kaldor, 1957; Romer, 1986, Robinson, 1965, 1978, 1980; Taylor, 2007) to question the robustness of the explanatory power of the neoclassical growth framework. This dissatisfaction culminated in a new idea, which came to be known as endogenous growth or new growth theory (Solow, 1994, 2000; Harcourt, 2006; Taylor, 2007). This new growth paradigm outlines the mechanism that captures the evolution of technological progress. Accordingly, this new approach provides a theory to explain the evolution of technological progress (Solow, 1994; 2000). The central feature of this approach is that technological progress can be driven by innovations, new consumer goods (Aghion and Howitt, 1992, 1998), human capital accumulation (Lucas, 1988), and research and development (Romer, 1990). The main analysis found in Chapter Four suggests that human capital accumulation in the form of entrepreneurship could be driving Hong Kong s TFP growth. Finally, Chapter Five provides a summary of the findings with reference to relevant theories, policy implications, and some suggestions for future research. 5

13 CHAPTER TWO GROWTH FRAMEWORK: SOLOW- SWAN GROWTH ANALYSIS Productivity isn t everything, but in the long-run it is almost everything. (Krugman,1997, p.11.) It s Technology, Stupid. (Easterly, 2002, p.51.) 2.0 Introduction There seems to be a general consensus that technological progress is the key to longrun sustainable economic growth (Solow 1956, 1957, 1994, 2000; Swan 1956; Kaldor 1960; Romer 1986; Lucas 1988; Krugman, 1997; Easterly, 2002; Harcourt 2006; Taylor 2007). In fact, mainstream economists would find it difficult not to agree with the view that technological progress is the key to per capita income growth of the OECD economies since the industrial revolution (Romer 1986). The relationship between technological progress and long-run sustainable growth has its origin as far back as in the writings of Adam Smith (1776). In explaining the European Class struggles, Karl Marx (1867) argued that the rise of the capitalist class was primarily propelled by capitalist investments into new technology to produce more output. The central proposition of the Solow-Swan growth model is that positive and long run growth of output per capita hinges on technological progress. Solow (1956) and Swan (1956) postulated that without technological progress, economic growth would 6

14 cease as a result of diminishing returns to factor inputs (capital and labour). When the economy finally arrives at its steady state growth path, output per worker is determined primarily by the rate of technological progress. The rationale and importance of technological progress in driving long-run aggregate output growth can be explained through the mechanism of the Solow (1956) Swan (1956) growth model. 2.1 The Solow-Swan Growth Model The logic of the Solow (1956) and Swan (1956) growth model can be captured by a standard Cobb-Douglas production function of the following type: Y t = F(A t,k t L t ) (2.1) Where Y is the aggregate level of output, K is capital stock, L is labour, and A the level of technology. In the process of empirical accounting or estimation (which will be conducted in Chapter Three), technological progress A, is captured by total factor productivity (TFP) growth. Consequently, the higher the value of A, the higher is the effectiveness of labour and capital in producing output Y, while t represents a single point in time. The production function stated in Equation (2.1), is constructed based on the following assumptions (Taylor 2007, pp.10-13): 7

15 1. Both labour and technology are assumed to grow at constant rates where growth of labour is denoted as n and technology as g. L t = L 0 (1+n) t (2.2) A t = A 0 (1+g) t (2.3) 2. The increase in capital (K) and labour (L) will yield positive increases in output (Y); marginal products are assumed to be positive and denoted as: F κ, F l > 0 (2.4) 3. However, the continued increase in capital (K) and labour (L) will lead to a decline in output (Y); marginal productivities of capital (K) and labour (L) are diminishing: F κκ, F ll < 0 (2.5) 4. There are constant returns to scale where the doubling of factor inputs will produce double the output. πy t = F(πK t, πa t L t ) π > 0 (2.6) 8

16 By setting π = 1/AL, equation (2.6) can also be expressed in per capita format: Y/AL = F(K/AL,1) =f(k/al) (2.7) 5. A constant portion of (Y) is consumed while the remaining amount is saved and devoted to investment denoted as a constant (s). One unit of (Y) devoted to investment will yield one unit of new capital, while existing capital depreciates at a rate denoted by δ. Accordingly, the rate of change in capital stock/investment ( ) is given as: Kᵗ = dk dᵗ = sy δkᵗ (2.8) 2.2 The Dynamics of the Model The relationship between output per effective worker and capital per effective worker, is derived by dividing Equation (2.8) on both sides by AL. Hence (Taylor 2007, p.11): Kᵗ Aᵗ Lᵗ = syᵗ Aᵗ Lᵗ δkᵗ Aᵗ Lᵗ (2.9) By substituting expression Y t A t L t with (2.7), gives: 9

17 Kᵗ Kᵗ Kᵗ Aᵗ Lᵗ =sf( Aᵗ Lᵗ ) δ( Aᵗ Lᵗ ) (2.10) By writing Kᵗ Aᵗ Lᵗ as k t, f( Kᵗ Aᵗ Lᵗ )=k t,and using equations (2.2) and (2.3) where the growth rates of labour and technology are n and g respectively, the expression δ( Kᵗ ) will become (δ+n+g)k. Thereafter, Equation (2.10) can then be rewritten as: Aᵗ Lᵗ k t = sf(k t ) - (n + g + δ)k t (2.11) Equation (2.11) specifies the rates of change of capital stock per unit of effective labour, which is depicted in Figure

18 Figure 2.1 Dynamics of the Solow-Swan Growth Model Source: Taylor 2007, p.12. As shown in Figure 2.1, the capital to effective labour ratio will increase when sf(k) exceeds (n+g+δ)k, and decrease when sf(k) falls below (n+g+δ)k (Taylor 2007). This is so, because the marginal product of capital will exceed that of (n+g+δ)k when the capital to labour ratio is small (Taylor 2007). The capital to labour ratio will increase when the marginal product of capital falls below (n+g+δ)k (Taylor 2007). As a result, capital per worker rises when k is initially less than k*, and falls when k exceeds k* (Taylor 2007). There is concavity in the model, where successive increases in capital per worker will eventually lead to a decline in returns on capital (Solow, 1956). And since the accumulation rate is fixed, new investment is merely sufficient to equip new workers 11

19 and replace depreciated capital stock (Solow, 1956). Once at the steady state, there will be no growth in per capita capital stock, as the steady state rate of growth of capital and output would be identical to the rate of population growth or labour force (Solow, 1956). Hence, the capital to effective labour ratio is constant at the steady state k* (Solow, 1956). This means that the economy will eventually converge to the steady state path, regardless of the starting point, where each variable in the model will grow at a constant rate (Taylor 2007). As such, the shape of the sf(k) curve satisfies the Inada conditions 1 (Taylor 2007). In order to increase further output growth, the savings rate (s) may be increased, which is reflected in a shift of the investment curve from sf(k) to s 1 f(k) as shown in Figure 2.1. As a result, s 1 f(k) now exceeds (n+g+δ)k, where the capital to labour ratio will continue to increase until it reaches the new steady state point at k 1 *, where s 1 f(k)= (n+g+δ)k. This intrinsically means that permanent increases in the savings rate (s) will merely produce level effects (Taylor 2007). The increase in output per worker by raising the savings rate (s) will only result in a temporary increase in the growth rate of output per worker as the economy makes the transition from one steady state to another (Solow, 1956). Thus, sustained increases in output can only be achieved by increasing the rate of change in technological progress. 1 Inada (1963) imposed the technological restrictions that f '(k) as k 0 and f '(k) 0 as k. 12

20 2.3 Technical Progress and Output Growth, Swan s Way Swan (1956) provided another approach in explaining the relationship between technological progress, A, and output growth, Y (Harcourt 2006) as illustrated in Figure 2.2. Figure 2.2 Technical Progress and Output Growth, Swan s Way Source: Harcourt 2006, p.111. Swan's economy wide aggregate production function is written as follows (Harcourt 2006): Y = K α L β (2.12) 13

21 Where Y is output, K is capital and L is labour. In order to avoid complexities associated with the measurement or aggregation of capital, Swan (1956) adopted an all-purpose commodity model, much like "corn is to seed corn, corn as output" (Harcourt 2006, p. 111). As with Solow s production function, Swan s production function also exhibited constant returns to scale in that α + β = 1, whereby β can be derived from 1 α. In addition, markets are assumed to operate under perfect competition, in that r (the return to capital) equals the marginal product of capital and ω (the real wage) equals the marginal product of labour (Harcourt 2006). As summarized by Harcourt (2006, p.111): δy δk = αkα-1 L (2.13) But Y K = Kα-1 L 1-α (2.14) So that δy = α Y (= r) (2.15) δk K The share of profits in national income is thus given as: rk = α Y K K Y Y = α (2.16) 14

22 Likewise, it may also be shown as: ω = β Y K = (1 - α) Y L (2.17) And the wage share is given by: β = (1 - α) (2.18) Through logarithmic differentiation of the production function stated in Equation (2.12), the relative contributions of the growth of capital and labour to the growth of output is obtain (Harcourt 2006): 1. δy = α 1 δk + β 1 δl Y δt K δt L δt (2.19) Or y = α 1 K + βƪ = α sy K + βƪ (2.20) Where y is the rate of growth of output, sy K the rate of growth of capital and ƪ is the rate of growth of labour. 15

23 As shown in Figure 2.2, the vertical axis depicts the rates of growth, while on the horizontal axis the output-capital ratio, Y. K sy is the growth line of capital, showing K the corresponding value of the rate of growth of capital for any given values of Y,K and s (Harcourt 2006). The resulting contribution to the growth of output is given by α s Y, which also shows K the value of r at any rate of growth and value of K/Y. 0B, the horizontal line starting from B on the vertical axis, is the exogenously given rate of growth of labour (Harcourt 2006). The (constant) contribution to the growth of output of the growth of labour (βƪ) is added to the contribution line of the growth of capital to give the rate of growth of output associated with each value of Y (see line yin Figure 2.2) (Harcourt K 2006). Given α + β = 1, when labour and capital grow at the same rate, so too does output, so that all three lines intersect at the value of Y shown in Figure 2.2, K (Y) 1. As shown K in Figure 2.2, output grows faster than capital (and slower than labour) towards the left of the intersection, while the ordering of growth rates is reversed towards the right of the intersection (Harcourt 2006). Due to the substitution possibilities between capital and labour and changes in relative factor prices brought about by cost-minimizing and profit maximization production techniques, the values of the capital-labour and capital-output ratios will also change (Harcourt 2006, p.113), such that it will always lead the economy towards equilibrium, where the rates of growth 16

24 of output, capital and labour, intersects each other, in a similar manner as the steady state equilibrium proposed by Solow (1956), as shown earlier in Figure 2.1. Swan (1956), offers an explanation (similar to Solow (1956)) on the process of substitution between labour and capital intensive technique in his model as depicted in Figure 2.2. When Y is momentarily above K (Y) 1, capital would be growing faster K than output (and labour slower). In this instance, output-capital ratio would be falling (with Y rising) (Harcourt 2006). This implies that r (the rate of return to capital) is L falling and ω (the real wage) is rising, inducing a choice of a more capital and less labour-intensive technique (Harcourt 2006). 2.4 Total Factor Productivity and Economic Growth During empirical accounting or estimation, technological progress in the Solow- Swan model can be captured by TFP. Briefly, output growth can be driven either by increasing factor inputs (capital and labour), or by increasing the productivity of both (total) capital and labour (hence, TFP). In other words, it is possible to increase a country s GDP growth rates either by employing more capital and labour (an accumulation process) or use the capital and labour more efficiently (assimilation process). Since both approaches increase output, does it matter which one to use? According to the Solow-Swan model, it does matters, especially in the long run. Whether a country can get onto the path of sustained growth is very dependent upon which production approach it takes. The production approach that is based on employing more capital and labour will not be sustainable in the long run as this type 17

25 of production approach is subject to the constraint of diminishing returns. On the other hand, the effective usage of capital and labour will avoid diminishing returns. This is because technological progress, which is derived from an increase in the productivity of both labour and capital, is not subject to the constraints of diminishing returns. A positive TFP growth suggests that growth is productivity or technologically driven, and this type of growth is sustainable in the long run. A minimum or negative TFP growth will suggest an accumulation (capital and labour) process, and therefore is not sustainable. Intuitively, TFP growth figures provide a rough measure of the economy s capacity to escape the constraint of diminishing returns. As such, it can be a useful tool for monitoring the state of the economy. If TFP is found to be negative, policy makers can initiate incentives to increase the activities that are associated with the advancement of technological progress such as, human capital accumulation, R&D, or the expansion of the education system in the manner suggested by the new or endogenous growth theories (which will be discussed in detail in Chapter Four). Young (1994) reported that TFP in Hong Kong grew on average 2.5 per cent per year over the period The World Bank (1993) estimations of TFP growth various countries are shown in Table

26 Table 2.1: TFP Growth in Selected Countries and Regions, Country/Region TFP Growth ( ) Hong Kong Indonesia Japan South Korea Malaysia Singapore Taiwan Thailand Latin America Sub-Saharan Africa Source: World Bank, The Solow-Swan growth model has been extremely popular in examining the growth process of the developed countries, but the same could not be said for the developing world. Although from time to time, books and academic journal articles using the Solow-Swan approach did surface to explain economic growth in East Asia, the numbers have remained small. It was only in the mid-1990s that interests in quantifying the impact of technological progress on the growth of East Asia began to intensify (Taylor, 2007). Spurred on by the publication of the World Bank s (1993) The East Asian Miracle, economists began to take the East Asia growth performance more seriously. The question which begs to be asked Why did it take economists so long to gain an interest in quantifying the impact of technological progress on the East Asia growth performance? Perhaps it made little sense in carrying out empirical studies to find what was thought to be the obvious, that the development gap is simply a technological gap. If this small group of initially economically and technologically backward countries were able to converge to the per capita income of the developed nations, it was only because they were able to 19

27 narrow the technological gap and hence close the development gap (Taylor, 2007). Prior to the publications of two influential works by Kim and Lau (1994), and Young (1992, 1994), it was often though that technological progress had played a big part in driving the rapid growth of the East Asian economies. When Young (1992) presented his findings to the European Economic Association in 1993, his conclusion, that growth in this part of the world was an accumulation process, was not well received. It is not hard to see this. A visitor to, for instance, Singapore will see a modern and sophisticated city-state with infrastructures that rival many European cities. Young (1995) published a follow-up paper that carefully scrutinised the data. The findings of the reworked version were similar to the previous findings in that technological progress played little role in the East Asian growth miracle. It was Paul Krugman s (1994) interpretations of Kim and Lau (1994) and Young (1992, 1994) findings that caused a big stir in this part of the World. The Myth of Asia s Miracle particularly upset senior leaders of the small city state, especially with the analogy Lee Kuan Yew s Singapore is an economic twin of the growth of Stalin s Soviet Union (Krugman, 1994, p. 66), and the miracle turns out to have been based on perspiration rather than inspiration: Singapore grew through a mobilization of resources that would have done Stalin proud (Krugman, 1994, pp ). A special conference was even organised to counter Krugman s (1994) claims. At the national conference on growth and development in ASEAN in December 1995, the then Prime Minister of Singapore, Dr. Goh Chok Tong publicly repudiated Krugman s view (Wilson, 2000). 20

28 What Krugman (1994) claimed was that there had been no economic miracle in East Asia. Instead, he attributed the region s growth experience to heavy investment and a big shift in labour from farms to factories rather than from productivity gains based on technological advancement or organisational change. Krugman (1994) indicated that once inputs are exhausted, and capital-to-labour ratios rise towards the developed economies levels, diminishing returns will set in and growth will decelerate sharply. He argued that it is unrealistic to expect these countries, which are already investing per cent of their GDP, to be able to further raise their rate of investment. In addition, he argued that most of the East Asian economies already have highly educated and high quality labour forces. This, in turn limits the scope for further improvement in these areas. Under such circumstances, without technical progress, eventually decreasing returns to investment will set in and the growth potential of these economies will be limited. As with Easterly and Fischer (1995), Krugman (1994) pointed out that the Soviet economy would inevitably run into diminishing returns due to the massive accumulation of capital not accompanied by technological progress: The newly industrializing countries of Asia, like the Soviet Union of the 1950s, have achieved rapid growth in large part through an astonishing mobilization of resources. Once one accounts for the role of rapidly growing inputs in these countries growth, one finds little left to explain. Asian growth, like that of the Soviet Union in its high-growth era, seems to be driven by extraordinary 21

29 growth in inputs like labor and capital rather than by gains in efficiency (p.40). Young (1994) conducted a comprehensive study based on a sample of 118 countries during , and reported that the East Asian TFP performance was not as spectacular as indicated by the World Bank (1993). Table 2.2 shows that in the TFP league, Hong Kong ranked sixth, Taiwan twenty-first, South Korea twenty-fourth, Malaysia thirty-eighth and Singapore sixty-third. Table 2.2: Annual Growth of Total Factor Productivity of Selected Countries, Egypt Guinea Turkey Pakistan South Korea Netherlands Botswana Iran Ethiopia Congo Burma Austria Malta Mauritius Australia Hong Kong China Spain Syria Denmark Kenya Zimbabwe Israel France Gabon Greece Liberia Tunisia Japan Paraguay Cameroon Luxembourg Honduras Lesotho Yugoslavia Portugal Uganda Tanzania USA Cyprus Colombia Belgium Thailand Sweden Canada Bangladesh Malaysia Algeria Iceland Malawi Cent. Af. Rep Italy Brazil India Norway Panama Singapore Finland United Kingdom Sri Lanka Taiwan W. Germany Fiji Ecuador Mali Switzerland 0.0 Note: Only the top 66 countries are presented out of the 118 countries. Source: Young, 1994, p

30 It is interesting to note that Young (1994) ranked Bangladesh higher than Taiwan, South Korea, Japan and Singapore. A subsequent study conducted by Young (1995) supported his 1994 findings of significantly lower TFP growth values in many East Asian economies relative to those in the industrialised economies. TFP growth in Singapore, for example, was estimated to be 0.2 per cent for Young s findings are consistent with studies conducted by Yuan (1983, 1985) and Kim and Lau (1994). Yuan (1983) reported virtually no TFP growth for the average of 28 manufacturing industries in Singapore between 1970 and 1979; in fact, TFP growth was negative for 17 of them. In a subsequent application of the growth accounting approach, Yuan (1985) indicated that almost all of Singapore s output growth in could be explained in terms of an increase in the quantities of factor inputs with negligible contribution from TFP growth. Kim and Lau (1994) presented several reasons for the lack of measured growth in productive efficiency over time for the Newly Industrialised Countries (NICs) in the post-war period. One of them is that R&D and indigenous technology played minor roles in their growth process. There is also the possibility that new technology that are embodied in capital goods could not be diffused effectively into the economic system as the East Asian NICs have limited capacity, in terms of human capital, to harness the embodied technological progress. Furthermore, the capital equipment that was installed in plants and factories is likely to be standardised, and as such, would have limited opportunities for indigenous improvements. They went on to argue that the managerial methods, institutional environment and supporting infrastructure lagged behind, so the NICs were unable to gain the full potential 23

31 productivity of foreign capital goods. As such, the poor human resource endowment may have reduced the potential gains in technical progress. The findings and conclusions drawn from the studies conducted by Kim and Lau (1994), Krugman (1994), and Young (1994, 1995) have led to the interpretations and the reinterpretations of the relationship between TFP and long run economic growth, resulting in the development of competing views the accumulationists and the assimilationists in the interpretation of the results generated from TFP estimates. Table 2.3 summarises the basic principles of accumulation and assimilation theories. 24

32 Table 2.3: Accumulation and Assimilation of Factor Inputs Accumulation Theories Measurement - rate of factor accumulation. Rapid economic development is caused by high investment rates, whereby the bulk of the share of increased output per worker is Explained by increases in physical and human capital per worker. Little attention is paid to firms as their behaviour is basically determined by the external environment. Accumulation of human capital is treated as an increase in the quality or effectiveness of labour. Economies in which the stocks of physical and human capital are rising rapidly are expected to show a steep rise in manufacturing exports. There would also be a shift in comparative advantage towards sectors that employ these inputs intensively. Therefore, there is nothing commendable about a surge in manufacturing exports. Assimilation Theories Measurement - rate of total factor productivity. Rapid economic development is linked to entrepreneurship, innovation and learning. New technologies from advanced nations also have to be adopted. Although investment in human and physical capital are pre-requisites, they are not sufficient. Entrepreneurial firms and their ability to learn rapidly are critical factors behind the success of South Korea,Singapore, Taiwan and China. Sharply rising educational attainment means that well-educated managers, engineers and workers have comparative advantage in terms of new opportunities and effective learning of new production techniques. Accumulation of human capital is an important factor for successful entrepreneurship. In order to compete effectively in world markets,firms require not only government support but must also acquire factors such as the necessary learning, entrepreneurship and innovation. Exports stimulate learning in two ways: (1) Being forced to compete in world markets will make managers and Engineers of firms pay close attention to best practice; and (2) The increase in exports is usually with US and Japanese firms which provide assistance in order to achieve their demanded high standards. Source: Nelson and Pack, 1999 (cited in Taylor, 2007, pp.28-29). 25

33 The assimilationists challenged Krugman s (1994) analysis on a number of grounds. They argued that the decomposition of growth in output is difficult because technical progress is embodied in new capital. Accordingly, the effects of technical progress cannot be separated from the expansion of capital inputs. Technological progress can only take place through the introduction of new machines i.e. through an increase in capital inputs. In fact, this type of rationale had been put forward in the 1960s by Kaldor. According to Kaldor (cited in Taylor, 2007, p.32), In a world in which technology is embodied in capital equipment and where both the improvement of knowledge and production of new capital goods are continuous, it is impossible to isolate the productivity growth which is due to capital accumulation as such from the productivity growth which is due to improvements in technical knowledge. There is no such thing as a set of blueprints which reflect a given state of knowledge the knowledge required for making of, say, the Concorde only evolved in the process of designing or developing the aeroplane; the costs of obtaining the necessary new knowledge is causally indistinguishable from the other elements of investment. According to Taylor (2007), even replacement investment is associated with technical progress. This is because, when a machine is being replaced by a new one the latter is likely to be technologically more advanced and not simply a new copy of the old one. On this basis, decreasing returns are unlikely to occur because the higher the rate of investment, the greater would be the turnover of machines and the greater would be the technical progress. This in turn would lead to greater learning by doing activities, thereby increasing technological progress (Arrow, 1962). 26

34 2.5 Conclusion This chapter has highlighted the key role of technological progress in driving long run sustainable aggregate output growth. The mechanics of the Solow-Swan growth analysis demonstrated that the only way in which to escape the constraint of diminishing returns to factor inputs is through higher productivity growth of both labour and capital. This short survey of the Solow-Swan growth model not only reinforced the importance of technological progress in driving higher aggregate output, it has also provides the theoretical basis for examining the growth process of Hong Kong covering the period Quantifying and decomposing the economic growth of Hong Kong starts in the next chapter. 27

35 CHAPTER THREE TFP GROWTH, HONG KONG, Introduction Hong Kong s real output grew at an annual rate of 8.85 per cent over the years , and 5.88 per cent annually over the period. Although Hong Kong s output growth has somewhat declined in the later period, it is still miraculous particularly when compared to the averaged annual growth rates of the combined 15 European Union countries plus the US of 1.65 per cent over the same period. This chapter has two aims. The first is to measure TFP growth of Hong Kong for the period based on the Solow-Swan growth analysis found in Chapter Two. In doing so, it will help us to understand the means by which Hong Kong is able to converge to the per capita income of the rich countries in Europe and North America in just 35 years or so (Taylor, 2007). The second is to explain Hong Kong s output fluctuations utilising the real business cycle theory. The macroeconomic data used for quantifying Hong Kong s TFP growth are found in Appendix Methodological Framework for Estimating TFP Growth The estimations of TFP growth for Hong Kong takes the following constant returns to scale production function: 28

36 Y t = A t K t Lt β + β = 1 (3.1) where Y is the aggregate real output, K is capital stock, L is labour and A indicates productivity or TFP. α, is a parameter with a value between 0 and 1, equal to capital s share of the value of output. β is the labour s share of the value of output. As discussed in Chapter Two, the Solow-Swan growth model is a constant returns to scale type of production function, requiring + β = 1. Hence, the value of β can be derived from 1 -. The aggregate output, Y, is the gross domestic product deflated by the price index (1990=100). In this analysis, capital stock (K) is constructed by taking into account the sum of capital stock from all existing vintages following Taylor (2007, p. 189) specifications: t I i δ i / P i (3.2) i=1 where I denotes gross domestic investment, t represents the age of the oldest vintage, δ is depreciation, and P is the price index. Capital K, in this context is derived from Equation (3.2), weighted by the 1990 price index, and is derived from the sum of public and private investments. An annual depreciation rate (δ) of 4 per cent (Inland 29

37 Revenue Department, Hong Kong) is applied to take into account the depreciation of physical capital. Labour, L, is the number employed in the Hong Kong economy. Table 3.1 shows the annual growth rates (in per cent) of real output, y, real capital, k (derived from equation (2)), and labour, l, for the aggregate economy of Hong Kong for the period

38 Table 3.1: Annual Growths of Real Output (y), Real Capital (k), and Labour (l), Hong Kong, , Per cent Year y k l Average Sources: Census and Statistics Department Hong Kong SAR, Hong Kong in Figures, various issues. 31

39 By taking logs and differentiating with respect to time, output growth can be derived from equation (3.1) as shown below:... y t = a t + αk t + (1 α)l t (3.3) ^ Once an estimate of is provided,, then TFP, â t, is estimated as follows:. ^. ^. â t = y t αk t (1 α)l t (3.4) Prior to substituting the growth rates data found in Table 3.1 into equation (3.3), the accounting of TFP, would, in the first instance, require the coefficients of and β. Once a value for is available, it is just the matter of subtracting the value from 1 to get the β value. For instance, if has a value of 0.3 then β is 0.7 (1- ). Estimates in the literature have found a value for of 0.3 for industrialised economies (Maddison, 1987), and 0.4 for the newly industrialised economies in East Asia (Kim and Lau, 1995; Collins and Bosworth, 1996; Harrison, 1996, and Taylor, 2007). The explanation of why developing countries have higher value is linked to the logic that the capital stock is smaller in these economies so the output elasticity should be higher as postulated by the hypothesis of diminishing returns (Taylor, 2007). Past studies on TFP show that the value of employed for different countries ranged from 0.29 to These estimates are presented in Table

40 Table 3.2: Different values for selected countries OECD Countries, France 0.40 Canada 0.44 Germany 0.39 Italy 0.39 Japan 0.39 Netherlands 0.45 UK 0.38 US 0.40 G-7 Countries, Canada 0.45 France 0.42 Germany 0.40 Italy 0.38 Japan 0.42 UK 0.39 US 0.41 Latin American Countries, Argentina 0.54 Brazil 0.45 Chile 0.52 Colombia 0.63 Mexico 0.69 Peru 0.66 Venezuela 0.55 East Asian Countries, Hong Kong 0.37 Singapore 0.53 Korea 0.32 Taiwan 0.29 Source: Taylor, 2007, p.194. In this analysis the value of 0.49 is derived from averaging all the countries found in Table 3.2. Given that has a value of 0.49, labour s shares of output, β, is 0.51 (derived from 1- ). The growth rates of y, k, and l found in Table 3.1, and together with the and β values of 0.49 and 0.51 respectively are then substituted into Equation (3.3), as shown in Table 3.3. Table 3.3: Average Annual Growth in Real Output (y), Capital contribution (k), and Labour contribution (l), Hong Kong, , Per cent y k ( =0.49) (β =0.51) l Average (5.66 X 0.49) 0.69 (1.34 x 0.51) 33

41 Capital, k, as in Table 3.3 is derived from multiplying the averaged annual growth rates of real capital (k) of 5.66 per cent (Table 3.1) with the value of 0.49, which is equal to 2.77 per cent. Labour s contribution (l) is derived from multiplying 0.51 (β) with the averaged annual growth rates of labour (l) of 1.34 per cent (Table 3.1), which is equal to 0.69 per cent. Table 3.3 shows the annual average real GDP (y) growth rates of 5.88 per cent. Out of that, capital (k) contributed 2.77 per cent, and labour (l) contributed 0.69 per cent to that output (y) growth. The next step is to estimate TFP growth in Hong Kong for the period using Equation (3.4). 3.2 Sources of Hong Kong s Economic Growth, Table 3.4 summaries Hong Kong s annual averaged TFP growth rates over the period. Table 3.4: TFP Growth Rates, Hong Kong, , Per cent Average Percentage. y 5.88 (100). k ( =0.49) 2.77 (47.1). (β =0.51) l TFP 0.69 (11.8) (â) 2.42 (41.1) 34

42 Table 3.4 shows that over the period , TFP grew at an annual rate of 2.42 per cent (i.e., = 2.42), which is consistent with prior estimations of TFP growth in Hong Kong (as discussed in the previous chapter). In that 5.88 per cent average annual real GDP growth, TFP contributed 41.1 per cent or nearly half to that output growth. Capital (k) accumulation constituted a slightly larger contribution to output growth than TFP. The individual years of the decompositions of Hong Kong s economic growth for the period are given in Table

43 Table 3.5: Annual Growths of Real Output (y), Capital Contribution (k), Labour Contribution (l), and TFP, Hong Kong, , Per cent. y Year TFP (â) Average k. l As shown in Table 3.5, on average, TFP played a major role in driving Hong Kong s output growth over the period Based on the Solow-Swan growth framework, output growth is productivity driven and as such growth is sustainable. However, the data in Table 3.5 also shows that output fluctuated over the period despite the fact that, on average, TFP growth was positive and substantive. This should not be based on the growth propositions put forward by the neoclassical 36

44 growth analysis discussed in Chapter Two. What is driving these fluctuations? The next section is the first attempt to explain Hong Kong s output fluctuations based on the real business cycles theory. 3.3 Real Business Cycles Theory Mankiw (1989, p. 79) wrote: The debate over the source and propagation of economic fluctuations rages as fiercely today as it did 50 years ago in the aftermath of Keynes s The General Theory and in the mist of the Great Depression. The Real business cycles theory is the latest theoretical construct developed to shed further light on aggregate output fluctuations. Accordingly, the primary determinant of aggregate output (GDP) fluctuations is linked to random technological shocks. The logic is that technological progress does not evolve with a smooth exponential growth rate but is rather, somewhat unpredictable and random. This unpredictable characteristic would explain the cyclical fluctuations of aggregate output. As Prescott (1986, p.9) pointed out: Given the value of the changing production possibility set, it would be puzzling if the economy did not display these large fluctuations in output and employment. 37

45 Prescott (1986) provided some empirical evidence on the importance of random technological shocks for the United States economy. He used the Solow residuals (TFP) as measurements to capture technological progress and found that TFP growth was cyclical as TFP fell, aggregate output also fell, and vice versa. Mankiw (1989) plotted aggregate output (GDP) against TFP (Solow residual) growth covering the period 1948 to mid-1980s as shown in Figure

46 Figure 3.1 TFP and Output Growth, US, Source: Mankiw 1989, p

47 Like Prescott (1986), Mankiw (1989) also found substantial fluctuations in TFP. Figure 3.1 shows that TFP growth trend is highly cyclical. For the period 1948 to 1985, there seemed to be a direct relationship between TFP and GDP growth. A fall in TFP saw a fall in GDP, and a rise in TFP was followed by a rise in GDP. As Mankiw (1989, 84) pointed out "If the Solow residual is a valid measure of the change in the available production technology, then recessions are periods of technological regress." Prescott s (1986) and Mankiw (1989) empirical testing will be replicated for the first time on Hong Kong covering the period The TFP and output growth trends are shown Figure

48 Per cent per year Figure 3.2: TFP and Output Growth, Hong Kong, Output Growth Solow Residual (TFP) Figure 3.2 shows that TFP growth in Hong Kong over the period was also highly cyclical in nature. In every year in which TFP fell, GDP also fell replicating the US pattern of growth (Figure 3.1). The magnitude of the relationship between TFP and output growth can be quantified by working out the elasticity of TFP with respect to output (y). The elasticity (E) concept is basically a mechanism that is used to measure the responsiveness of a change (Δ) in one variable on another variable (Marshall, 41

49 1920). It will determine how much a change in one variable (TFP) affects the change in another variable (output, y). To determine how much change in TFP contributes to output growth (y), the following equation is utilised: E = Δ log TFP/ Δlog y (3.5) Where: log = logarithms. The data are converted into logarithms, which is the conventional approach of measuring elasticity (Taylor & Taylor, 2011). y = Real GDP growth rates, and TFP is total factor productivity growth rates. The E value explains the magnitude and direction of the relationship between TFP and output (y). Covering the period, and using Equation (3.5), the elasticity (E) of TFP with respect to output growth (Y) is estimated to be approximately This suggests that for every 1 per cent annual increased in TFP growth, GDP grew annually by per cent over the period. 3.4 Conclusion The findings of this chapter suggest that there were substantial fluctuations in Hong Kong s TFP growth, which in turn, drove the fluctuations in GDP growth 42

50 over period. The estimated elasticity coefficients (E) of TFP growth with respect to real GDP growth suggests that, on average, for the period , every 1 per cent increase in TFP resulted in per cent increase in real GDP growth. Following the propositions put forward by Prescott (1986) and Plosser (1989), economic downturn or recessions in Hong Kong can therefore be explained by technological regressions. Although the Solow-Swan growth model postulates that technological progress as captured by TFP is the engine for sustainable economic growth, however it does not provide a formal explanation on how technological progress comes about. Instead, technological progress is estimated from a residual as shown in equation (3.4). Hence, it is treated as exogenous, meaning that technological progress is driven exclusively from outside the model. The real business cycles theory can only explain what is driving fluctuations in aggregate output. Accordingly, substantial fluctuations in the rate of technological change will result in substantial fluctuations in output. In the Hong Kong case, it seems that TFP plays a significant role in the production of output growth as well as explaining the fluctuations of output growth from 1991 to But, the findings of this chapter have yet to pin down what drives TFP growth in Hong Kong in the first place. It is possible that human capital accumulation in the form of entrepreneurship could be driving Hong Kong s TFP growth. The next chapter will explore this. 43

51 CHAPTER FOUR ENTREPRENEURS AND PRODUCTIVITY GROWTH Give a man a fish, and you feed him for a day. Teach a man to fish, and you feed him for a lifetime. (Chinese proverb) 4.0 Introduction The elusive treatment of technological progress led critics to question the robustness of the explanatory power of the neoclassical growth framework (Harcourt, 1972, 2006; Kaldor, 1957; Robinson, 1965, 1978, 1980; Romer, 1986, Taylor, 2007). This dissatisfaction culminated in a new idea, which came to be known as endogenous growth or new growth theory. This new growth paradigm outlines the mechanism that captures the evolution of technological progress. Accordingly, this new approach provides a theory to explain the evolution of technological progress (Solow, 1994, 2000). The central feature of this new approach is that technological progress can be driven by innovations, new consumer goods (Aghion and Howitt, 1992), human capital accumulation (Lucas, 1988), and research and development (Romer, 1990). The recent resurgence of the importance of human capital accumulation in the determination of economic growth (Lucas, 1988; Romer, 1986, 1990; Barro, 1989, 44

52 1997; Mankiw, Romer and Weil, 1992; Taylor, 2007) reflects the increasing recognition of its importance in explaining economic growth. Solow (2000), for instance, pointed out that research on the role of human capital in economic growth should have high priority (p.154). In fact, human capital accumulation has long been stressed as a prerequisite and/or concomitant for economic growth (Nelson and Phelps, 1966). The aim of this chapter is to trace the impact of human capital in the form of entrepreneurship on TFP growth in Hong Kong. 4.1 Human Capital Accumulation, Entrepreneurship and TFP Growth In the economic development and growth literature the bulk of the focus on human capital tends to be on formal education. For instance, Snodgrass (1980, p.252) pointed out that Education is primarily a process of human capital formation (in italic). Through the accumulation of economically useful learning, a resource is built up which can be used in the labour market to earn higher returns for the individual and make larger contributions to society. In a cross-country empirical study consisting 67 countries (aimed at finding the determinants of economic growth), Barro (1997) reported a significant positive effect on growth from the years of schooling at secondary and higher level. An extra year of upper-level schooling contributed to increase the growth rate by a substantial 1.2 percentage points per year. 45

53 Denison (1964) reported that improvements in the quality of the labour force through additional education contributed 23 per cent to the US growth rates in Barro (1991, 1997) and Benhabib and Spiegel (1994) found education to be correlated with the growth rate of per capita GDP across different countries. Lau, Jamison and Louat (1991) estimated that one additional year of education in East Asia contributed over 3 per cent to real GDP. The World Bank (1999) reported that education is the key to competing successfully in world markets. It is also possible that, in addition to formal education, human capital accumulation can be driven by entrepreneurial spirit. The reason being that entrepreneurs respond spontaneously to economic and social condition contingency far outweighs containment, resulting in radical innovation (Courvisanos, 2007). Courvisanos (2007, p.47) went on to argue: Human actions by agents at this end are strongly influenced by what John Maynard Keynes (1936, p. 137) calls animal spirits in an environment where containment is relatively weak. Society encourages the spontaneous urge to action (Keynes 1936, p.144) of entrepreneurs. Innovation as a process is complex and not well understood because it is deeply rooted in the uncertainty of the future world, from which emerge new products, processes, movements, organisations and sources of raw material. All that is known is that innovation brings change and something new emerges, which 46

54 cannot be modelled. As a result, it is often portrayed as exogenous, as in the residuals of the Solow-Swan growth model (as discussed in Chapter Two). It is possible that entrepreneurship - especially in the entrepreneur economy (Keynes, 1936, p. 150) like Hong Kong - could affect the labour variable, L, in the Solow-Swan growth model. The higher the effectiveness of labour input - where entrepreneurs are compelled to make sound and risky investment decisions - the higher will be the TFP value, and therefore the greater the level of output (a simple experiment will be conducted in the later part of this chapter to determine this). On the other hand, increasing ordinary labour, L, will only have a level effect but not a growth effect. This is supported by the empirical findings of Mankiw, Romer, and Weil (1992), who found that more investment in human capital is conducive to growth but a more rapid expansion in population is not. According to Kirzner (1973), in a capitalist society, the opportunity that human agents are alert to is monetary profit. Kirzner (1973, pp.39-41) argued that the role of the entrepreneurs arises out of their alertness to hitherto unnoticed opportunities in that they proceed through their alertness to discover and exploit situations in which they are able to sell for high prices that which they can buy for low prices. Alertness implies that the actor possesses a superior perception of economic opportunity. As Kirzner (1985, p. 162) elaborated, entrepreneurial process consisted of: the social integration of the innumerable scraps of existing information that are present in scattered form throughout society.yet the same entrepreneurial spirit that stimulates the 47

55 discovery in the market of the value of information now existing throughout the market also tends to stimulate the discovery or creation of entirely new information concerning ways to anticipate or to satisfy consumer preferences. The entrepreneurial process at this second level is what drives the capitalist system toward higher and higher standards of achievement. New entrepreneurs are more likely to take high risks in order to pursue higher gains by taking advantage of new technological advancement as well as ensure a continuation of that progress. There are a number of studies conducted suggesting that successful entrepreneurs are more likely to take risks when it comes to developing new innovative products with commercial applications. In fact, Carland and Carland (2015) determined that potential entrepreneurship could be predicted by using three variables risk-taking propensity, innovation, and achievement. Accordingly, entrepreneurs who are more willing to take risks are, typically, more successful than their cautious or risk averse peers. In an entrepreneur economy like Hong Kong, enhancement of innovation has become the quintessential feature of commercial, political, economic and business life. Fu-Lai Yu(1998, p.898) wrote; Hong Kong s economic success is mainly attributable to the dynamics of adaptive entrepreneurs who are alert to opportunities and exploit them. Through their efforts, the tiny economy has been able to catch up with the economically more advanced economies. 48

56 Fu-Lai Yu (1998) also pointed out that Hong Kong s manufacturers have encountered extremely volatile economic conditions but have tackled these problems by being alert to business opportunities, making quick decisions, acting promptly, and maintaining a high degree of flexibility and adaptability (p.899). Fu-Lai (1998) went on to argue that virtually without any government support in research and development, the technological level of Hong Kong s manufacturing industry has lagged behind that of South Korea and Taiwan. Yet, Hong Kong s entrepreneurs have survived and prospered largely by being alert to new opportunities. 4.2 Entrepreneurial Spirit: A Possible Driver of TFP Growth In order to shed further light on the impact of entrepreneurs on TFP growth, it is helpful and appropriate to provide a brief overview of some of the economic rationales put forward by Schumpeter (1934), Lucas (1988), Romer (1990), Aghion and Howitt (1998). In doing so, the analysis would not only be more complete but would also add further rigour to the analysis found in this chapter. Schumpeter (1934) postulated that knowledge accumulation needed to drive innovation is facilitated by entrepreneurship. In his creative destruction analysis, technological progress is primarily driven by entrepreneurs, who are constantly seeking improvements and changes, and progress to enhance their profit margins during the production of goods and services. He stated that competition is not 49

57 simply about prices but also about better production techniques (innovation). Schumpeter (1934) viewed growth as a dynamic process, occurring intermittently over time. The introduction of a new innovation or new production technique by one entrepreneur would affect the production structures of other entrepreneurs through the spillover of knowledge. This would facilitate other entrepreneurs in their decisions about their own production frontiers. As time progresses, the pace of spillover and diffusion would slacken and so would growth. In order to sustain long run growth, incentives must be provided to stimulate the accumulation of knowledge - in the form of better linkages between investment and other areas of the economy needed to drive technological progress. According to Schumpeter (1943), this creative destruction - whereby a new invention is created and put to market for consumption and peaked (matured) in the later part of the product cycle and then declined - would kick start a new phase in business investment to produce new products. This may explain why aggregate output growth fluctuates over time as proposed by the arguments found in the real business cycles analysis. In the Hong Kong case, the relationship between TFP and real GDP growth, over the period, was found to be cyclical. In every year in which TFP fell, output also fell (Figure 3.2 in Chapter Three). Following Schumpeter s creative destruction analysis, and if TFP is driven by creative destruction, then recessions in Hong Kong can be seen as periods of technological regress brought about by mature product cycles. Schumpeter (1934) argued that it is the innovative entrepreneurs that are largely responsible for driving economic development. Schumpeter (1934) wrote that 50

58 there are five overarching types of entrepreneurial innovations that could bring about significant economic change and development: 1) An entrepreneur has the capacity to develop and launch a new product based on the existing or pre-established product. 2) An entrepreneur has the ability to apply new methods of production to produce a new product or to improve an existing product. The new methods must be unique and not a mere replica of an established practice within the industry. Otherwise, they will not spark change. 3) An entrepreneur could prompt economic development through exploiting new markets and expanding an industry into a new branch or direction. 4) Economic growth could be driven by entrepreneurs finding new, better and less costly methods of acquiring raw materials and/ or unfinished products (goods). 5) Economic growth could be driven by the formation of a new industry structure. For instance, the destruction, creation, or restructuring of an industry monopoly could bring about quick and radical change and development. 51

59 Schumpeter (1939) maintained that it is innovation that is the real catalyst for creative destruction and entrepreneurs are directly responsible for this function of change. Accordingly, true entrepreneurs are individuals who exploit market opportunity through technical and / or organizational innovation. An important implication of Schumpeter s creative destruction analysis as summarised by the above 5 points is that it would lead to the accumulation of new technology and new innovation. New technology is an ongoing step-bystep transformation from a simple production process to a highly sophisticated one. This gradual evolutionary process has been happening for the last 200 years, but it has been accelerated by the discoveries of key technological breakthroughs such as, electronic valves, transistors and silicon chips. This cumulative process cannot come about if capital is treated as a static phenomenon. Increasing capital investment will mean that there is an unbroken continuum in the evolution of technological progress. Above all, cumulative accumulation of embodied technology is the basis for the next generation of technology. This could be clarified by a simple technology branch representation. Branches make sub-branches. Each sub-branch in turn makes further smaller branches, and so on, as shown in Figure

60 Figure 4.1: Technology Branch and Next Generation of Technology New Technology New Technology New Technology Current Technology The above technology branch starts with a single technology, and over time, evolves into various sub-branches and even smaller branches. A classic example is the electronic valve. It was originally created (by an innovative entrepreneur) to demonstrate that it is possible to transfer electrons in a vacuum from one point to another point. Through trial and error, entrepreneurs learn how to control the flow of a current in a vacuum valve (hence, the name valve). Over time and more trial and error later, they learnt how to use a vacuum valve to switch the current on and off in a systematic sequence. This was the birth of the digital revolution. This switching sequence in electronic valves has contributed to other innovations. There are the telecommunication and information technology industries, which spurred other hosts of new industries along the way. The wireless radio was invented. We have television. Humans set foot on the moon, and so on. This switching sequence (digital as now known) essentially drives our lives every second, from a simple electronic watch to the computer which is used to write this 53

61 small dissertation. Prior to the electronic valve, it would be practically impossible to make digital electronic computers, and all the other electronic consumable goods. This switching sequence is not confined to the manufacturing sector. It has propelled the rapid expansion of the service sectors (e.g. tourism, banking, financial and insurance) which otherwise would not have been possible. The basic switching principle has not changed since it was discovered over 100 years ago. What have changed are the manufacturing techniques that started from glass vacuum valves to metal and plastic transistors, and to silicon based chips as a result of trial and error, experimentation and refinement, and so forth. Today s silicon chips perform the same function as the vacuum valves, but what differentiates them is that one vacuum valve performs one on and off (switching) function, while a silicon chip performs more than a million switching functions. For instance, the very old generation of Pentium III chip performs approximately 23 million switching functions (or 23 million valves in the older days). Who knows what the next generation of switching technology will be based on? From one small beginning, the valves have generated not only countless varieties of new technologies and industries, but they have also changed the production structures of the global communities, and in the process, generated millions of employment opportunities. These technological branches will continue to grow as long as the entrepreneurial spirit continues to grow. In this sense, diminishing returns to capital will not take place because embodied capital produces new generation technologies. Diminishing returns will only come about if the entrepreneurial spirit and capital are static. But as 200 hundred years of progress has demonstrated, the entrepreneurial spirit and capital are extremely dynamic. 54

62 Perhaps Karl Marx was correct when he wrote that capital accumulation is technological progress. In the popular press, Karl Marx is often associated with the evil side of communism. Yet, he is very much a growth theorist (Nelson, 1996, p.7). Marx viewed capital accumulation as the key for capitalists to expand their production capacity. As pointed out by Solow, 2000, p.xxiii, Nobel Lecture, December 8, 1987); the effectiveness of innovation in increasing output would be paced by the rate of gross investment. A policy to increase investment would thus lead not only to higher capital intensity, which might not matter much, but also to a faster transfer of new technology into actual production, which would. Schumpeter (1934) indicated that it is more appropriate to view economic development as a historical, on going process of structural changes that are primarily driven by entrepreneurial innovation. Schumpeter s creative destruction analysis is formalised recently by Aghion and Howitt (1998). In the Aghion and Howitt (1998) model creative destruction is captured by the notion that successful R&D may render technology invented by previous R&D unprofitable. Profits acquired from successful innovations are viewed to be temporary, thereby affecting the entrepreneurs R&D spending decisions. It will be in the interests of entrepreneurs to pursue further innovation in order to capture the temporary monopolistic profits until it has been replaced by the next innovation. In doing so, technological progress (TFP) will continue to 55

63 rise. The Aghion and Howitt (1998) formal model is summarised below (Taylor, 2007, pp ): In Aghion and Howitt s (1998) framework, output depends on the input of an intermediate good, x: y = AF(x) (4.1) Function F is positive with diminishing marginal product. Technological progress is derived from the invention of a new variety of intermediate good which replaces the old one, and in the process raises the technological parameter, A, by a constant factor of γ>1: A Φ + 1 / A Φ (4.2) where Φ denotes the ith innovation. Labour is assumed to be fixed but has competing usages. It can either be utilised for the production of intermediate goods, x, or it can be employed in R&D, n. Hence: L = x + n (4.3) 56

64 The amount of n being employed in R&D would generate an amount of innovations at a random Poisson arrival rate of λn, where λ > 0 (a parameter capturing the productivity of R&D). The amount of labour being devoted to R&D is derived from: w Φ = λp Φ + 1 (4.4) where w Φ is the wage paid to the Φth innovation, and p Φ + 1 is the discount rate or expected payoff of the (Φ + 1)th innovation. The value of p Φ + 1, is determined by: r p Φ + 1 = π Φ + 1 λn Φ + 1 p Φ + 1 (4.5) The expected income or rate of profit (being generated by the (Φ+1)th innovation), rp Φ+1, is equal to the profit flow, π Φ+1, minus the expected loss, p Φ+1, that will be incurred by an entrepreneur when the (Φ+1)th innovation is being replaced by a new invention. The Schumpeterian effect can then be captured by: 57

65 P Φ+1 = π Φ+1 / (r + λn Φ+1 ) (4.6) The technically detailed mechanism for tracing the flows of both profit, π Φ+1, and labour, x, can be found in Aghion and Howitt (1998). Briefly, the arbitrage in relation to flows of profit, π Φ, and flows of demand for labour in the production of intermediate goods, x Φ, is where: both the allocation of labor between research and manufacturing and the productivity-adjusted wage rate remain constant over time, so that wages, profit, and final output are all scaled up by the same γ > 1 each time a new innovation occurs (Aghion and Howitt, 1998, p. 57). In a steady-state, the flow of final output produced during the interval period between the Φth and the Φ+1th innovation is: y Φ = A Φ = A Φ (L-ñ) (4.7) where denotes the steady-state equilibrium. This implies that: 58

66 y Φ + 1 = γy Φ (4.8) Since the flow of output does not occur in time but in a continuous sequence of innovations, and in order to trace the rate of growth of output, it is necessary to trace the evolution of final output in real time, φ. Using equation (4.8), and taking logs, the final output ln y (φ) increases by an amount equal to ln γ each time a new innovation occurs. Since the real time interval between two successive innovations is random, the time path of the log of final output ln y (φ) will also be a random step function as shown in Figure

67 Figure 4.2: A Random Step Function of Output Growth ln y (φ) ln y 4 ln γ ln y 3 ln γ ln y 2 ln γ ln y 1 0 Φ = 1 Φ = 2 Φ = 3 φ Source: Aghion and Howitt, 1998, p.60 (cited in Taylor, 2007, p.45). Accordingly, the size of each step is equal to ln γ >0 and the time interval between each step is exponentially distributed with parameter λñ. Taking a unit-time interval between φ and φ+1: ln y (φ+1) = ln y (φ) + (ln γ) ν (φ) (4.9) where ν(φ) is the number of innovations between φ and φ+1. 60

68 The Poisson distribution of ν(φ) is with parameter λñ, so: V[ln y (φ+1)-ln y (φ)] = λñ ln γ (4.10) In the steady state, average growth rate is given by: g = λñ ln γ (4.11) Based on equation (4.11), the expected rate of growth is proportional to ñ. This endogenous rate of growth will depend on anything that will help to increase ñ. Increases in labour, L, will increase ñ and thereby g. Increases in the size of innovation γ and/or in the productivity of R&D, λ, will also foster growth, directly by increasing the factor λ lnγ, and indirectly through increasing ñ. The random nature of new and successive innovations in Aghion and Howitt (1998) growth analysis provides a possible explanation for the TFP growth fluctuations experienced by Hong Kong during period (discussed in Chapter Three). Furthermore, increases in labour quality, L, in a manner suggested by Aghion and Howitt (1998), will increase ñ and thereby g. Thus, opening up the possibility of entrepreneurship in improving the quality of labour, which in turn drives higher TFP growth. 61

69 Lucas (1988) proposed that it is the quality of human capital that drives the level of productivity, which in turn drives growth rates. Lucas s analysis of human capital is as follows (Taylor, 2007, pp.51-53): Y = K α (uhl) 1-α (4.12) where H is current human capital stock, u denotes fraction of labour time being allocated to the production of consumer goods, and K denotes physical capital stock, which evolves overtime according to the neoclassical production function. 2 Since human capital, H, is the driver of technological progress, the evolution of H is given as: H= H ε δ (1-u), ε = 1 (4.13) where 1-u is the share of labour being utilised in the production of consumer goods, 3 and ε denotes knowledge intensity. If u = 1, no effort is made to increase human capital accumulation as all of the society s labour force is devoted to the production of intermediate goods. Hence, there is no accumulation of human capital. If u = 0, then H will grow at the maximum rate δ. In between, there are no diminishing returns to the stock H. This, 2 Lucas (1988) model is consistent with the Solow-Swan growth model, as outlined in Chapter Two, except for the (1-u) term. 3 This implies that a society can determine the efficiency of the forthcoming generation of workers by making a choice between present consumption of consumer goods and future investment in educational activities. 62

70 according to Lucas (1988), is because a given percentage increase in H would require the same effort no matter what level of H has already been attained. Hence, technological progress is dependent upon the term 1-u, which is the amount of resources being devoted to the accumulation of human capital. Based on such a rationale, the growth rate of an economy can then be summarised as: g = ψ (1-u*) (4.14) Where u* is the optimal allocation of individuals time between production and education. As discussed earlier, in addition to formal education, human capital accumulation could also come from entrepreneurship in the manner suggested by Schmpeter (1934). Following the logic put forward by Lucas (1988), a society can determine the speed and the magnitude of technological progress (TFP) by making a choice between present consumption of consumer goods and future investments by entrepreneurs on new innovations leading to the production of new types of consumer goods. If no effort is made to induce entrepreneurs to invest in new innovation, there will be no advancement in technology. This is because the current consumer goods may have already reached the peak (matured) of their product cycle resulting in the decline in both the production size and the demand size. This is in line with the notion of diminishing returns as discussed in Chapter Two. If, on the other hand, more effort is being devoted to induce entrepreneurs to invest in new production techniques, then technological progress (TFP) will grow at the maximum rate - as it would kick start a new phase in the production of new 63

71 consumer goods. This process will continue to expand in a manner similar to the technology branch representation (Figure 4.1). The endogenous growth model of Romer (1990), where he stresses the importance of the quality of human capital, can be expressed with the Cobb- Douglas production function of the type below (Taylor, 2007, pp.52-53): A Y = H Y L xi 1- -, α + β > 1 (4.15) i = 1 where Y is final aggregate output, L is stock of ordinary labour, H is human capital being accumulated through formal education and on-job training, and xi is an index of the different types of capital goods employed in the production of final output. Because the integer i (different varieties of goods) is treated as a continuous variable, equation (4.15) can be replaced with an integral as shown below: A Y = H L xi 1- - di (4.16) 0 Since each good is assumed to have the same production cost and marginal productivity, xi is substituted with X to get: 64

72 A Y = H L X 1- - di 0 A = X 1- - di 0 = A X 1- - (4.17) Equation (4.15) can now be written as: Y = H Y L AX 1- - (4.18) The rest of Romer s (1990) analysis is devoted to the construction of a market structure which makes H A constant and positive. It will not be pursued in this brief overview. Human capital H is assumed to be constant but is allocated according to the preference between the production of final output H Y, and the production of new varieties of capital H A. Hence: H Y + H A = H (4.19) The evolution of A is constructed as shown below:. A = H A A (4.20) where is a productivity parameter. 65

73 Equation (4.19) specifies that endogenous growth is derived from the rate of growth in output which is proportional to the amount of human capital allocated to research in discovering new varieties of capital goods. According to Romer (1990), the key to growth is that A is linear in A. In short, only the stock of human capital, and not that of labour, affects the growth rate. This is consistent with the empirical findings of Mankiw, Romer, and Weil (1992), who found that more investment in human capital is conducive to growth but a more rapid expansion in population is not. In the Hong Kong case, virtually all the R&D is conducted without any government support (Fu-Lai Yu, 1988) but driven by entrepreneurs who are alert to new opportunities and exploit them. According to Fu-Lai Yu (1998) and Chau (1993), entrepreneurship in Hong Kong is not only confined to the manufacturing sector, but also operates in the tertiary sector (retailing, transport, finance, and real estate). Fu-Lai Yu (1988) and Chau (1993) reported that the shift from one sector to another in Hong Kong could be explained consistently by the dynamic operations of entrepreneurship. When entrepreneurs in Hong Kong perceive that other activities such as finance or service in the tertiary sector have higher growth potentials than the manufacturing sector, they will attempt to arbitrage. There have been three major phases of structural changes in Hong Kong in the last 50 years or so. The first phase occurred in the 1950s and the 1960s, during which there was a shift of resources from agricultural to manufacturing. The second 66

74 phase began in the late 1970s, and the direction has been towards the development of the financial services. The third phase came in the 1980s, which saw a massive shift of resources towards property development (real estate sector). According to Chau (1993), it was in the property market that the mentality of merchant entrepreneurs found their fullest expression. Land in the Territory is a scare resource. Because of its physical attributes, land in Hong Kong can only be increased through reclamation. Therefore, land has to be used more intensively, by either moving to higher value uses or by constructing multi-storey buildings. This is made apparent by a classic acquisition conducted by Cheung Kong holding Ltd. Li Ka-Shing, the managing director of Cheung Kong Holding Ltd, saw that the supply of land in Hong Kong was limited, whereas population growth was unlimited. As a consequence he reduced his manufacturing business and moved into property development. In the 1980s, he perceived that the land owned by the British firm, Green Island Cement Co., possessed considerable development potential, for it is located in Hung Hom, the city center. If the land is to be developed into a residential estate it will yield a huge profit. After acquiring a 25 per cent stake in Green Island and entering the managing board of the company in the 1980s, Li successfully converted the land in Hung Hom into a gigantic residential estate, namely Whampao Gardens. The change in use of the land and its subsequent rise in value was not automatic, but was made possible by entrepreneurial insight. Ventures and output productions in Hong Kong are still concentrated in technologically simple areas such as banking, insurance, retail clothing franchises, rather than sophisticated technological schemes 67 (Census and Statistics

75 Department, Hong Kong SAR, various issues). Some manufacturers in Hong Kong still explore profit opportunities in certain low value-added products, which many foreign firms do not consider to be worthwhile. Other entrepreneurs have shifted towards the tertiary sector, or moved to other low costs countries, using unsophisticated technology. This is how Hong Kong has maintained its impressive economic growth despite the fact that its export composition has remained at a relatively low value of added activities, with labour-intensive and technologically simple goods continuing to make up by far the largest share. As such, it is possible that entrepreneurship is driving technological progress (TFP) in Hong Kong. 4.3 The Impact of Entrepreneurial Spirit on TFP Growth The models discussed earlier have highlighted the importance of human capital accumulation in driving technological progress, which in turn drives output growth. In a case study of TFP growth in Malaysia, covering the period , Taylor (2007) reported that when human capital is factored into the estimation of TFP growth, TFP was found to be higher on the production function with human capital (of 3.5 per cent per year) as compared to the standard production function (of 2.5 per cent per year). It is possible that entrepreneurs in Hong Kong play a pivotal role in improving the quality of human capital in a manner suggested by Schumpeter (1934), Aghion and Howitt (1998), Lucas (1988), and Romer (1990). In order to provide some measure of the extent to 68

76 which human capital accumulation could impact on TFP growth, a simple experiment is conducted using the following production function (Taylor, 2007): Y t = A t K t α HL t β (4.21) The above production function and specifications, with exception of labour (L), are similar to the one used to estimate TFP growth in the previous chapter. Here, labour (L) includes a quality component, H, in the form of human capital ( H L). The reason being that in an entrepreneur economy like Hong Kong human capital accumulation could be driven largely by entrepreneurs seeking new opportunities and new production methods to gain more monetary profits. H, in this case, is a proxy for entrepreneurial spirit (the capacity to make productive investments in order to generate new innovations). One major difficulty in estimating TFP growth accurately is linked to the problem that the α values can bias TFP growth estimations either upward or downward depending on the size of the α values. According to Collins and Bosworth (1996), Dowling and Summers (1998), Harberger (1996), Sarel (1996), and Taylor (2007), TFP is highly sensitive to the sampling period, the assumed size of the capital share of output,. According to Taylor (2007), one possible implication of estimating TFP with a high value is that it can bias TFP growth downwards. Chen (1997) reported that the inappropriate choice of would explain why many studies reported a small 69

77 TFP value in East Asia. Sarel (1996) conducted a sensitivity exercise of TFP growth on Hong Kong, Korea, Taiwan and Singapore by applying the values of 0.25 and He found that the TFP growth in these countries was estimated to be 3.7 per cent based on a capital share,, of 0.25 in comparison to a TFP growth of 2 per cent based on an value of Dowling and Summers (1998) reinforced the view that TFP estimation is highly sensitive to the size of. Using Summers-Heston ( ) data, with a capital share,, of 0.4, TFP growth for Korea was estimated to be 2.6 per cent, 2.8 per cent for Singapore and 2.5 per cent for Taiwan, while a capital share,, of 0.30 produced TFP growth of 3.5 per cent, 3.5 per cent and 3.3 per cent respectively, as shown in Table 4.1. Table 4.1: TFP Growth Estimates on Selected Countries Nehru-Dhareshwar capital stock, World Bank output Capital share Sample period China Korea Malaysia Singapore Taiwan Thailand King-Levine capital stock, Summers-Heston output Capital share Sample period China Korea Malaysia Singapore Taiwan Thailand n.a n.a n.a Source: Dowling and Summers, 1998, pp There is very little explanation why this is so, other than that TFP growth is very sensitive to the size of the values. This part of the literature has not been explored fully and this gap in the literature should be given a priority in the 70

78 economic growth research agenda. This is because accurate TFP growth estimations require the determination of correct values. In this model, H does not impact directly upon TFP, but through, β, which is the coefficient of labour. It is possible that the value of β will be higher due to improvements in labour quality being brought about by the desire to succeed in business ventures, which in turn drives new innovations and new products, leading to higher TFP. In his earlier analysis, Schumpeter (1912), detailed several forces behind entrepreneurship. Accordingly, an entrepreneur might simply be motivated by an overarching desire to achieve something. Or, be motivated by the sheer joy and personal satisfaction that results in creating a new product, good, service or technology. For some, entrepreneurship is a way of exercising their energy and ingenuity. Another reason how one might be prompted to become an entrepreneur is an insatiable desire to establish for themselves their own kingdom. Schumpeter (1912) believed that the modern man often tried to obtain a sense of power and prestige through entrepreneurship, and compared this endeavour to the medieval lord. As Schumpeter (1912) pointed out, it was no longer acceptable to gain power and prestige through marriage alliances and physical battle. Therefore, these innate needs had to be met another way. In the modern context, one of the ways these needs could be met was through entrepreneurship with the desire for monetary and positional gain. 71

79 Taylor (2007) reported that the annual average TFP growth in Malaysia for the period increases as the β values increases as shown in Table 4.2. Table 4.2 Coefficient of and β and TFP growth for Malaysia, , Annual Average Method β TFP Standard production function Production function with human capital Product function with openness (trade) Source: Taylor, 2007, pp According to Taylor (2007) the increased β value from 0.45 to 0.61 was linked to the improvement in labour quality through a learning-by-doing process (Arrow, 1962). Taylor (2007, p.197) explains: Workers with a basic education (primary) can absorb and diffuse the embodied technological progress at a faster rate than their counterparts who lack a basic education. As workers learn how to operate machinery more effectively, their productivity level will increase, leading to higher labour wages and a higher share of output. Accordingly, capital will become cheaper (thereby lowering the value ), which in turn will stimulate additional capital accumulation, leading to additional employment and learning-by-doing activities and hence a higher labour share of output. The relationship between higher wages and productivity has also been analysed in detail in the efficiency wage literature (Solow, 1979; Akerlof, 1982; Yellen, 1984; Akerlof and Yellen, 1986, 1990; Taylor and Taylor, 2011). The propositions put 72

80 forward by many of the efficiency wage models are consistent with the need to allocate a larger share of the output to labour if higher productivity is to be gained. The efficiency wage analysis argues that there is a cost associated with paying lower wages. Higher wages may raise the productivity of labour. The central idea is that if firms cannot monitor their workers effort perfectly, they may pay more than the market-clearing rate to minimise shirking brought about by moral hazard and adverse selection. Wages higher than the minimum at which people are willing to work will not only increase the queue for the job but, more importantly people will increase their effort level while doing their job. According to the efficiency wage analysis, effort (E) per worker (i) is given by: E i = e (w i /w e, u) (4.22) Where W i is internal wage (wage inside the firm), W e is the market wage or the expected prevailing wage outside, and U is unemployment. If the firm s output depends on the total effort, E i N i, the firm chooses wages and employment to maximise profits, π i : π i = R i (E i N i ) W i N i = R(E i N i ) (W i /E i )E i N i (4.23) Where R is revenue, N is employment. 73

81 Equation (4.23) says that in order to maximise profit, a firm would first choose wages that would minimise the cost per unit of effort (W i /E i ). Once the firm has done that, it would then choose the number of workers that would maximise profit. Hence to minimise (W i /E i ), wages must be raised so long as effort rises faster than wages. The firm will always find it worthwhile to raise the wage so long as 1 per cent rise in wages brings forth a more than 1 per cent rise in effort. But, once this ceases to be the case, the firm will stop raising wages. In equilibrium, which is also known as the Solow condition, W* i is the efficiency wage as shown in Figure 4.3. Figure 4.3: The Effort and Wage relationship: The Solow Condition Effort E i = e(w i ) W i * W i Source: Layard, Nickell and Jackman, 1991, p.152. Hence, the maximum or optimum amount of wages that should be paid to be the employees is W i * to produce the maximum amount of effort, E i *. W i * is therefore 74

82 the efficiency wage a wage that could increase the employee s productivity by extracting the maximum amount of effort. Several studies have reported a significant relationship between efficiency wages and employees effort (Kruger and Summer, 1988; Katz and Summer,1989; Wadhawani and Wall, 1991). The classic example of this relationship is drawn from the 1914 Ford Motor Company case. In 1914, the Ford Motor Company decided to pay Ford workers $5, which was approximately double the wage that was previously paid to them. The result was an increase in the workers productivity by about 55 percent (Raff and Summer, 1987). Studies carried out by Kohli (1988), Huang, Hallam and Paterno (1998) and Goldsmith, Veum and William (2000) found positive relationship between efficiency wages and employees effort. For instance, Goldsmith, Veum and William (2000) reported that receiving an efficiency wage enhances a person s effort and that persons providing greater effort earn higher wages (p.351). Huang, Hallam and Paterno (1998) surveyed 18 manufacturing firms in the US, covering the period from 1986 to 1991, and found that paying efficiency wages did increase the workers productivity. Similarly, Kohli (1988) reported a wage accelerated effect amongst the workers in manufacturing industries in the US where the effort of employees depended on the rate of wage change. In an empirical study of 15 selected countries, Taylor and Taylor (2011) reported that the full-time government employees in these countries are paid the efficiency wage, in that the efficiency wage ratio (public/private) of the public sector workforce has a mean value of 1.02 across the 15 countries as shown in Table

83 This suggests that government wages in most countries, such as Australia, New Zealand, Taiwan and Japan, were slightly above the market rate. Table 4.3 Efficiency Wages and Elasticity Values (e) of Full-Time Government Employees in Selected Countries Source: Taylor and Taylor, 2011, p. 77. The second column in Table 4.3 shows the elasticity of effort with respect to wages (e). It was estimated to have a mean value of 0.24 for the respondents across the 15 countries. This suggests that a rise in government wages by 0.24 per cent is associated with a one per cent rise in the effort levels of government workers, and vice versa. This positive relationship between wages and effort, as 76

84 shown in the positive values in the elasticity of effort with respect to wages, e, is consistent with efficiency wage literature. In a capitalist and lassie faire economy like Hong Kong (and together with the earlier analysis of the entrepreneurial spirit), it is reasonable to view β as a reward or return given to Labour ( H L) for their contribution to the production of output. The higher the β value, the higher would be the reward and vice versa. 4.4 Adjusting the Value of β to Re-measure TFP Growth Equation (3.4) and the data found in Table 3.1 (Chapter Three) are again utilised to estimate TFP growth for the period In this section, the and β coefficients values are recalibrated to take into account the effects of human capital as suggested by various authors (Lucas, 1988; Romer, 1986, 1990; Barro, 1989, 1997; Mankiw, Romer and Weil, 1992; Taylor, 2007; Keynes, 1936; Fu- Lai,1998; Chau, 1993; Kirzner, 1973; Courvisanos, 2007; Schumpeter, 1912, 1934,1939). As mentioned in the previous chapter, is equal to capital s share of the value of output (Y), and β is the labour s share of the value of output (Y). It is possible that TFP growth will be higher when the β value is increased. Increases in the β value i.e. increases in the labour s share of output can be driven by the nature and characteristics of the entrepreneurial spirits or as Keynes (1936) called animal spirits. 77

85 In the previous TFP calculation (Chapter Three) was given a value of 0.49, resulting in a 2.42 per cent TFP growth for the period In the following section, both the and β values are recalibrated with different values. The β values that are used to estimate TFP growth are found in Table 4.4, while the estimations using the values are found Table 4.5. Table 4.4: β values and TFP growth, Hong Kong, y (Annual Average %) k (Annual Average %) l (Annual Average %) β TFP growth (Annual Average %) As show in Table 4.4, each time the value of β is increased, TFP growth increases. For instance, a β = 0.60 would result in a 2.82 per cent TFP growth. Increasing to β = 0.70 increases TFP growth to 3.24 per cent, despite the same amount of output (Y), capital (K), and labour (L) being used in all the calculations, as shown in Table 4.4. The simple experiment demonstrates that TFP is highly sensitive to the size of β. Next, a similar experiment on the coefficient of capital, α, is conducted to see its impact on TFP growth. The aim is to see whether an increase in resources devoted to physical capital actually boost higher TFP growth. The α value is increased from 0.49 to 0.80 as shown in Table

86 Table 4.5: α values and TFP growth, Hong Kong, y (Annual Average %) k (Annual Average%) α l (Annual Average %) TFP (Annual Average %) The results in Table 4.3 show that as the α value becomes higher, TFP growth on the other hand, becomes lower. This is opposite to the labour estimate. The increasing β value is consistent with the proposition that entrepreneurship increases the quality of human capital as discussed earlier. Each time the value of β is increased, TFP growth increases. The results from Table 4.4 and Table 4.5 suggest that increasing labour quality is far more important than just increasing capital. This is consistent with the rationale of the Solow-Swan growth model. In the Solow-Swan growth framework capital investment is not the key to growth. Growth can only come from the labour component that is actively initiating technical change (Swan, 1956). The higher the value of β, the higher is TFP growth as compared to the higher the value of α, the lower is TFP growth. This may explain why, in the last 50 years or so, the massive investments in physical capital in many developing countries made possible by foreign aid did not work as intended. As Easterly (2002, p. 44), correctly pointed out: The aid-financed investment fetish has led us astray on our quest for growth for fifty years. The model should finally be laid to rest. We should eliminate the notion of the financing gap altogether, with its spurious precision on how much aid a country needs. We should not attempt to estimate how much 79

87 investment a country needs for a given target growth rate, because there is no stable short-run link between investment and growth. We should not attempt to estimate how much aid a country needs for a given growth rate, because there is no economic model that addresses that question. In short, increasing the size of resources devoted to capital is not enough for long run output growth, and may not be productive if the desire to further improve the productivity of the economy is not accommodated by dynamic entrepreneurial spirit. 4.5 Conclusion The analyses and findings of this chapter suggest that entrepreneurship is a strong potential driver of TFP growth. In the propositions and models put forward by Aghion and Howitt (1998), Lucas (1988), Romer (1990) Keynes (1936), Fu-Lai Yu (1998), Chau (1993) Kirzner (1973) Courvisanos (2007) Schumpeter (1912, 1934,1939), entrepreneurial spirit could affect the labour variable, L, in the Solow- Swan growth framework. Accordingly, the higher the effectiveness of labour input (and in this case - entrepreneurs are able to explore new opportunities), the higher will be TFP growth. The results in Table 4.4 suggest that as the quality of human capital increases (as proxied by increases in the β values), TFP growth also increases. In an entrepreneurial economy like Hong Kong, enhancements in new ways of producing goods and services has become an essential feature of commercial, 80

88 political and economic life. This special human capital quality is quintessential in driving higher TFP growth, which in turn drives higher output growth. A final remark by Fu-Lai Yu (1998, p ) sums up the pivotal role of entrepreneurial spirit in economic growth: any policy recommendation on economic development should be based on analysis that incorporates entrepreneurship, the engine of economic growth Whether a developing nation can catch up with economically more advanced countries depends on whether it can promote entrepreneurship to identify and exploit these opportunities. 81

89 Chapter Five Concluding Remarks 5.0 Summary This dissertation has examined the contributions to economic growth in Hong Kong made by increases in the quantity and quality of labour and capital inputs. It found that TFP growth is a major determinant of economic growth in Hong Kong. Over the period, TFP grew at an annual average rate of 2.42 per cent. Based on the Solow-Swan growth model (as discussed in Chapter Two), output growth in Hong Kong is therefore sustainable. However, the findings in Chapter Three also show that output fluctuated over the period despite the positive and substantial TFP growth figure. In Chapter Three, the relationship between TFP and output growth has been quantified. TFP growth in Hong Kong over the period was found to be highly cyclical. In every year that TFP growth fell, GDP growth also fell. The elasticity of TFP with respect to output growth was estimated to be around 0.49, suggesting that for every 1 per cent annual increased in TFP growth, GDP grew annually by 0.49 per cent over the period. The real business cycles theory can only explain the relationship between TFP growth and aggregate output growth. What drives TFP growth in Hong Kong over the period has yet to be explained. The analyses and findings found in Chapter Four highlights the possibility that human capital in the form of entrepreneurship could be one such factor driving TFP growth in Hong Kong. 82

90 5.1 Policy Implications Having quantified and explained the important role of entrepreneurship in driving the economic growth of Hong Kong, some implications and lessons can now be drawn. Firstly, increasing the size of resources devoted to physical capital is not enough for long run output growth, and may not be productive if the desire to further improve the productivity of an economy is not accommodated by policy to enhance entrepreneurial spirit. Entrepreneurs in Hong Kong not only play a key role in driving TFP growth, they are also responsible for driving structural changes involving the inter-sectoral shift of resources. The shift from one sector to another in Hong Kong could be explained consistently by the dynamic operations of entrepreneurship. When entrepreneurs in Hong Kong perceive that other activities such as finance or service in the tertiary sector have higher growth potentials than the manufacturing sector, they resort to arbitrage and gravitate to the sector that has the highest returns. Secondly, dynamic entrepreneurial spirit is the key to competing successfully in the world markets through new innovations. According to Schumpeter (1939), entrepreneurs are individuals who exploit new market opportunities through new technical innovations. As long as the entrepreneurial spirit is nurtured properly and continues to grow, diminishing returns to output production, in the manner suggested by the Solow-Swan growth analysis (Chapter Two), will not take place. This is because the introduction of a new innovation or a new production 83

91 technique by one entrepreneur would affect the production structures of other entrepreneurs through the spillover of knowledge. This, in turn, would facilitate and speed up the discoveries of new and better production techniques by other entrepreneurs so as to stay competitive in the world markets. Finally, if the development gap is simply a technological gap, and if Hong Kong, an initially economically and technologically backward economy, was able to converge to the per capita income of the developed nations in a time span of just 35 years, it was because entrepreneurs in Hong Kong were able to narrow the technological gap and hence closed the development gap. The crucial point is that whether poor countries or latecomers can converge to the per capita income of the rich nations, hinges on whether they can successfully develop a dynamic entrepreneurship so as to exploit world market opportunities. As pointed out by Fu-Lai Yu (1998, pp ): in the dynamic world development process, market opportunities, the result of the creative power of entrepreneurs, will never be exhausted. Whether a developing nation can catch up economically more advanced countries depends on whether it can promote entrepreneurship to identify and exploit these opportunities. 84

92 5.2 Future Research Economic growth is a complex process. It is not entirely confined to the advancement of technological progress as indicated by the Solow-Swan growth analysis (Chapter Two) and the endogenous growth theories (Chapter Three). There are many other factors that could affect the growth process. Based on the findings of this dissertation, further research is needed in the following areas: 1. Better proxies are needed for the estimation of TFP growth. The findings in Chapters Three and Four highlighted the sensitivity of TFP estimates to the values of both α and β. One major difficulty in estimating TFP growth accurately is linked to the problem that the α values can bias TFP growth estimations either upward or downward depending on the size of the α values. According to Taylor (2007), and the findings in Chapter Four, estimating TFP with a high α value will bias TFP growth downwards. Chen (1997) reported that the inappropriate choice of α would explain why many studies reported a small TFP value in East Asia. Very few explanations are available for why this is so, other than that TFP growth is very sensitive to the size of the α and β values. According to the findings of this dissertation, each time the value of β is increased, TFP growth increases. A possible explanation why is this so is linked to the quality component of human capital. The higher the β value, the higher would be the quality of human capital, and as such the higher would be their returns or rewards (as reflected by the larger β value), and vice versa. The opposite happened with the size of the α value. As the α value becomes higher, TFP 85

93 growth becomes lower. In the Hong Kong case, increasing the quality of human capital is far more important than increasing physical capital. By and large, this part of the literature has not been explored fully and this gap in the literature should be given a priority in the economic growth research agenda. This is because accurate TFP growth estimations required the determination of correct and β values. 2. The role of aggregate demand in driving productivity growth. One limitation so far of the rationales and models used in this dissertation is that they focused exclusively on the supply side of production. This type of analysis is not entirely satisfactory in fully understanding the growth process, because the decision made to the production of goods and services cannot be made or explained independently from the growth of effective demand (Casaratto, 1991). Although, the real business cycles analysis (Chapter Three), does provides some empirical evidence on the relationship between technological progress and output growth, it is also highly likely that output fluctuations may not be entirely due to the random nature of technological progress. According to Mankiw (1989) and Hall (1987), the Solow residual (TFP) need not be interpreted as evidence regarding exogenous technological disturbances, but rather by demand shocks. As pointed out by Mankiw (1989, p.84): The standard explanation of cyclical productivity is that it reflects labor hoarding and other off the production behavior. Productivity appears to fall in a recession 86

94 because firms keep unnecessary and underutilized labor. In a boom the hoarded laborers begin to put out greater effort; output increases without a large increase in measured labor input. Furthermore, Brouwer and Kleinknecht (1999) reported that growth of effective demand stimulates innovation. As Taylor (2007, p.210) observed: further research on the relationship between aggregate demand and innovations could shed new light on technological progress. Fluctuations in aggregate demand will not only have effects on short-run production and employment, but they can also enhance or hamper innovation. A final remark by Solow (2000, p. 184) sums up the pivotal role of aggregate demand on economic growth: So why should it be important to incorporate a serious demand side in models of economic growth, apart from analytical tidiness? For one thing, observed growth paths are not smooth. They are punctuated by recessions, large and small, and periods of excess demand. How do these macroeconomic fluctuations affect the growth path itself? There are obvious ways: Rates of investment, and therefore the evolution of capital stocks, are affected by short-run fluctuations. 87

95 Finally, the issues raised in this small dissertation formed only a narrow and confined view of what is thought to be driving economic growth. It is hoped that its findings will provide one more step to the very long quest of how to place poor countries on the path to sustainable economic growth. 88

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102 APPENDIX ONE The primary aim of Appendix One is to provide the macroeconomics data on aggregate output growth (Y), capital stock (K), and employment (L) that are required in the formulation of the research methodology adopted in Chapters 3 and 4 of this dissertation. 95

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