The new growth theory drops two central assumptions of the Solow model, (i) that technological change is exogenous, and (ii) that the same technological opportunities are available in all countries. In addition, the assumption of decreasing returns to a narrow concept of capital (including only physical capital) is replaced by the assumption of constant returns to a broad measure of capital (including also human capital and infrastructure). New growth models treat technology and knowledge as economic goods in an attempt to understand the determinants of long-term growth based on learning-by-doing or investment in human capital and new technologies.
Contrary to the standard neoclassical models and that by Arrow (1962), there are invention costs in the creation of new technology, and there are adoption costs associated in particular with creating the human capital required to use a new technology. Adoption costs have a direct component in the form of investment outlays for schooling, on-the-job training, etc., as well as an indirect component, such as in the form of foregone output. Endogenous growth models can be distinguished according to whether they emphasize invention costs or adoption costs.
New growth models differ as to what mechanism is employed to end organize the impact of technical progress on growth. The mechanisms in early models (Romer, 1986; Lucas, 1988) are dynamic externalities at the aggregate level, i.e. technology is endogenously provided as a side-effect of private investment decisions. Romer (1986) assumes that the stock of knowledge of a firm increases in proportion to the firm's expenditure on research and development, while spillovers from these private investments increase public knowledge. In the absence of an effective patent market, the stock of knowledge is like a public good. Even though Romer's model is similar to Arrow's, technological change is to end organize, since in his model long-term growth is driven primarily by the creation of new knowledge by forward-looking, profit-maximizing, private agents. The investment which creates new knowledge displays diminishing returns. But, given the knowledge spillovers due, for example, to the inadequacy of patent protection, the production of goods from new knowledge exhibits increasing returns. Since new knowledge is produced from investment with diminishing returns, each profit-maximizing private agent who invests in knowledge creation - and hence incurs invention costs - faces an optimal upper limit to his investment. Thus,
technical change should be responsive, endogenously, to policy, such as tax and fiscal incentives.
The model by Lucas (1988) is also similar to Arrow's (1962). However, the spillover effects which increase the level of technology stem from investment in human capital rather than in physical capital. The model focuses on general skills and in particular those which cannot be separated from the worker who has acquired them.
Knowledge grows with the time spent on education and the efficiency with which this time is translated into human capital. This efficiency is associated with different factors depending on whether education is understood as schooling or as learning-by doing.
Regarding schooling, efficiency increases with the quality of schooling which, in turn, improves with increased general knowledge. Here, the mechanism of raising long-term growth is learning or doing rather than learning-by-doing. Differences in long-term growth are the result of different rates of human capital accumulation, stemming from differences in countries' time allocation decisions. Regarding learning-by-doing, efficiency is associated with the type of process workers are engaged in: "one might think of some activities as carrying with them a high rate of skill acquisition and others, routine or traditional ones, as associated with a low rate. If so, the mix of goods a society produces will affect its overall rate of human capital accumulation and growth" (Lucas, 1993). A country's initial comparative advantage determines the goods it produces, and hence its rate of human capital accumulation and growth.
Neo-Schumpeterian growth models employ temporary monopoly profits, which motivate the discovery of new technology, as the mechanism to end organize the impact of technological progress on growth. This branch of new growth models introduces conditions of imperfect competition at the micro-level of production, emphasizing the
importance of temporary monopoly power as a motivating force for the intentional investment of resources by profit-seeking firms or entrepreneurs in the innovative process. In these models, growth depends on the incentives to invest in improving technology. It is also important to note that the appropriability of (new) knowledge is related to lead times over rival inventors and imitators rather than to effective patent protection. The models are based on the assumption that there are invention but no adoption costs. The invention costs are fixed-cost expenditures which occur, for example, through the need to conduct research and development for the invention of new designs; the inventors sell these designs to producers of goods that are new (Romer, 1990, and Grossman and Helpman, 1991) or of superior quality (Grossman and Helpman, 1991). The competitive equilibrium solution of the neoclassical model cannot be sustained where such fixed costs are important because, if this is the case, decentralized market valuations of the economic efficiency of an investment project diverge from valuations at the aggregate level. As a result, no such investment will take place if at least part of the expenditure cannot be recovered through monopoly profits.
The approach focusing on invention emphasizes ideas which can be used by many workers once they are created, i.e. disembodied human capital, through a research and development effort by a small subset of educated workers. Policies that raise the incentive of this group of workers to innovate consciously raises the question of long-term growth. Romer (1990) explains that the basic difference between ordinary tangible goods, such as capital and knowledge, is that the latter is a nontrivial and partially non-excludable good. The feature of non-rivalry means that knowledge can be used in more than one place at any one time, while the feature of non-excludability means that the creators or owners of knowledge can exclude others from making unauthorized use of
it only with difficulty. Knowledge may be considered a partially non-excludable good because one type of knowledge, namely product-specific information, can be protected through patents, while more general technical information which may allow for subsequent inventions cannot be hidden from rival innovators and is much more difficult to appropriate. Technological spillovers associated with the latter feature maintain investment incentives endogenously and allow successive inventions to use fewer resources than their predecessors because, contrary to inputs of capital and labor, it is not necessary to replicate non-rival inputs. The resulting fall in the real cost of invention counteracts the falling marginal product of investment. "In short, the process of knowledge accumulation generates endogenously the productivity gains that sustain growth in the long run" (Grossman and Helpman, 1991).
A third class of new growth models distinguishes human capital from technology as well as different types of each. They include both invention and adoption costs but focus on the latter. Young (1993) and similarly Lucas (1993) criticize the discussed models of invention and models of learning as focusing on two extreme cases of the process of accumulation of human capital. In particular, Young (1993) points to the unrealistic assumption in the learning approach "that the potential productivity gains from learning are essentially unbounded", since making this assumption does not allow
"explaining the recurring pattern of technological improvement and stagnation apparent in pre-modern history". This approach also implies the assumption that, contrary to the invention approach, new technologies are not considered to attain their full production potential at the moment of their invention but that they initially are broadly inferior to the older technologies they seek to replace. This means that these models add a complementarity element of innovation to the Schumpeterian emphasis on substitution.
Young concentrates on the interaction of factors emphasized in the learning and invention approach, starting from the basic assumption that the potential of "learning in the production of any particular good, using any particular process, is in fact finite and bounded. When a new technical process is first invented, rapid learning occurs as, by virtue of experience, the productive potential of that process is explored. After some time, however, the inherent (physical) limit on the productivity of technology will be approached and learning will slow and, perhaps, ultimately stop. In the absence of the introduction of new technical processes, it is unlikely that learning-by-doing can be sustained" (Young, 1993). This means that Young emphasizes the existence of a technology ladder in the production of goods ordered by increasing technical sophistication, with the result that countries have to combine efforts at learning-by-doing and innovation in order to fully exhaust their potential in human capital accumulation.
The consideration that, in the absence of further invention, learning is bounded has important implications for diversification. If the potential for learning-induced productivity improvements in each good is finite and bounded, then the potential maximum accumulation of knowledge in an economy is determined by the number and variety of activities as well as by the level of technology mastered by the labor force, compared to that required to exhaust fully the learning potential incorporated in the production of a given set of goods. Accordingly, if an economy continues to produce the same narrow range of goods, its learning-induced productivity improvements are likely to peter out. It also means that neither the presence of state-of-the-art technology nor a highly skilled labor force alone is sufficient for the full exhaustion of an
economy's learning potential, but that the introduction of new technologies and the commensurate up-grading of skill-related knowledge must go hand in hand.
IV. Policy Applications of Growth Theory
The above model provides the basic framework for considering endogenous growth in a general equilibrium framework. However, given the broad nature of the results there is still little information for policymakers. A number of models have been developed along the above lines to deal with more specific policy and empirical issues.
Many of these issues have also been of concern to developing countries.
A. Human Capital and Education
Development economists have long been concerned with human capital formation. Endogenous growth model, such as Lucas (1988), allow for significant effects of human capital accumulation on economic growth. Lucas (1988) presents a growth model in which output is generated via a production function of the form
𝑌 = 𝐴𝐾!(𝑙ℎ𝐿)"#!
where Y, A, and K are as usually defined and 0 < α < 1, where L is defined as the proportion of total labor time spent working, and h is what Lucas calls the stock of
‘human capital.’
The production function can be rewritten in per-capita terms as 𝑌 = 𝐴𝐾!(𝑙ℎ𝐿)"#!
which is a constant returns to scale production function in K and 𝑙ℎ.
Capital accumulation proceeds via the usual differential equation, 𝑘 = 𝑦 − 𝑐(𝜗 + 𝛿)𝑘
while ℎ accumulates according to
ℎ̇ = ∅ℎ(1 − 𝑒) ℎ̇
ℎ= ∅(1 − 𝑒)
B. Government Spending and Taxation
Development economists have also been interested in the effects of government spending, taxation, and related distortions in developing countries. Romer (1986) is that capital taxation (or subsidization) may have significant growth effects in the endogenous growth models whereas it would only have level effects in the Slow model.
It would be important for policymakers to understand the relative importance of these effects for long-term growth. Also, factors such as political instability and property rights may have effect similar to capital taxation by increasing the uncertainty associated with investment decisions.
C. Trade Policy
Given the success stories of the East Asian countries, development economist has been interested in the links between foreign trade and economic growth. Many developing countries have significant trade distortions through tariff of quota barriers which generate inefficient allocation of investment and rent-seeking behavior. Because trade distortions would have only level effects in the Solow model the discussion has moved to the relationship between trade policy and productivity growth. A number of recent studies explore these issues within models of endogenous growth. Romer (1990a) notes a general implication of endogenous growth theories is that through
increasing the scale of spillovers or available technologies openness trade should increase growth. Further research a suggested modification to this result.
It appears that even in very aggregative models that few strong conclusions can be drawn concerning the relationship between growth and trade policy. A major difficulty with these models is that it is hard explain difference in growth rates among countries when they are open to trade. One could explain differences between countries open to race and those completely closed but this does not seem satisfying as a complete theory of growth differentials between countries.
D. Financial Markets
Development economists have also been concerned about the role of financial factors in development. It has been argued by McKinnon (1973) and Shaw (1973) that financial repression (particularly depressed interest rates) slow growth through retarding savings and promoting inefficient investment allocation. Recent studies have addressed the issue of financial markets and growth. Rather than focusing on the relationship between savings and interest rates (which is theoretically ambiguous) they focus on firm behavior in a risky environment with financially constraints.
Chapter 3: Research Method
I. Data
To determine the sources of economic growth affecting the real gross domestic product (RGDP) in Thailand, this study is based on secondary data in annual time-series and data covering the period 2007 to 2018. The major data source for macroeconomic variables in this study from the Office of the National Economic and Social Development Council and World Bank's World Development Indicators 2018. An effort has been made to fill missing values by using alternative sources like the Bank of Thailand.
II. Research Framework
Sources of economic growth are relevant to expenditures, industries sectors, labor productivity, and technological progress. The research framework is summarized as follows:
(Independent Variables) Economic Growth in
Thailand
III. Variables
As explained in the previous section, a number of real gross domestic product (RGDP) was used as a proxy for increasing the economy's ability to produce goods and services. Sources of economic growth to explain the real gross domestic product is first defined by expenditure.
Sources of GDP growth by expenditures, we can calculate by 𝐺𝐷𝑃 = 𝐶 + 𝐺 + 𝐼 + 𝑋 − 𝑀 I is gross fixed capital formation
X-M is net exports; calculate as total exports minus total imports All these activities contribute to the GDP of a country.
Continuing of another sector of GDP. Sources of GDP growth from industry sector.
Sources of GDP Growth by industry we can calculate from 𝐺𝐷𝑃 = 𝐴 + 𝐼 + 𝑆
Continuing of other sources of GDP. Sources of GDP growth from input.
A. Increase in employment B. Increase in labor productivity
Sources of GDP Growth from input we can calculate from
𝐺𝐷𝑃 = 𝐸𝑚𝑝𝑙𝑜𝑦𝑒𝑑 𝑙𝑎𝑏𝑜𝑟 𝑓𝑜𝑟𝑐𝑒 × 𝐿𝑎𝑏𝑜𝑟 𝑝𝑟𝑜𝑑𝑢𝑐𝑡𝑖𝑣𝑖𝑡𝑦 𝐺𝐷𝑃 = 𝐿 × 𝐿𝑎𝑏𝑜𝑟 𝑃𝑟𝑜𝑑𝑢𝑐𝑡𝑖𝑣𝑖𝑡𝑦
If we want to calculate technologies progress, we can use:
𝑦 = 𝐴 ∙ 𝑒$%∙ 𝐾! ∙ 𝐿&
log 𝑦 = log 𝐴 + 𝑔𝑡 + 𝛼 log 𝐾 + 𝛽 log 𝐿
log 𝑦 = log 𝐴 + 𝑔𝑡 + 0.25 log 𝐾 + 0.75 log 𝐿 log 𝑦 − (0.25 log 𝑘 + 0.75 log 𝐿) = log 𝐴 + 𝑔𝑡
where, K is Physical capital L is Labor forces
The above relation will be estimate with regression analysis. The coefficients of the explanatory variables are expected to take the following signs: the direction of the relationship between sources of economic growth and real gross domestic product (RGDP).
IV. Methodology
This research is study in a source of economic growth that affecting real gross domestic product in Thailand by use multiple regression analysis. At the model formation stage, the relationship between the dependent variable and the independent variable must be explained by logic. Based on logic used, it is predicted that the relationship between the independent variables and the dependent variables is related.
This study has chosen to use research data as multiple regression analysis which an analysis of relationships between more than one independent variable and one dependent. In general, the multiple regression equation of Y on X1, X2, …, Xk is given by:
𝑌' = 𝛽( + 𝛽"𝑋"'+ 𝛽)𝑋)'+. . . +𝛽*𝑋*'+ 𝜖', 𝑖 = 1, . . , 𝑛
where,
Y is the expected value of Y for a given X value β0 is the Y intercept of the regression line
β1 is the parameter associated with X1 (measures the change in y with respect to x1, holding other factors fixed) and so on…
ε is a random variable called the error term.
By show the result of analysis in 3 parts as following:
A. The appropriateness of the multiple regression model as a whole can be tested by the F-test in the ANOVA table. A significant F indicates a linear relationship between Y and at least one of the X’s.
B. Once a multiple regression equation has been constructed, one can check how good it is (in terms of predictive ability) by examining the coefficient of determination (𝑅2!). 𝑅2! always lies between 0 and 1.
C. A related question is whether the independent variables individually influence the dependent variable significantly. Statistically, it is equivalent to testing the null hypothesis that the relevant regression coefficient is zero.
This can be done using t-test. If the t-test of a regression coefficient is significant, it indicates that the variable in question influences Y significantly while controlling for other independent explanatory variables.
Chapter 4: Major Findings
This study examines the effects of sources on economic growth in Thailand.
The construction of the study is discussed, including the later chapters for concluding remarks and references. As part of the methodology, the previous chapter argued for the selection of estimation equations and preparation of the variables for the model.
This chapter has the estimation results of the specified equations. The supply side model estimation is presented as two sections: public investment finance and national production function.
Economic growths by expenditures comprise equations relating to the sources of Thailand’s revenue. Since Thailand revenue is come from expenditures, the
estimates primarily focus on these sources. Expenditures is represented by a series of estimable equations, while other sources such as private consumption, government consumption, gross fixed capital formation and net export of goods & service are represented with identity equations.
The three broad categories including the agricultural sector, the manufacturing sector and the service sector an estimation of economic growth in Thailand. The agricultural sector is extraction of raw materials-mining, fishing and agriculture. The manufacturing concerned with producing finished goods, e.g. factories making toys, car, food, and clothes. The service sector concerned with offering intangible goods and service to consumers. This includes retail, tourism, banking, entertainment and I.T.
services.
Third, growth accounting measures the contribution of increase in labor inputs estimate and identity equation were calculating from labor productivity. Thus, a country’s growth can be broken down by accounting for what percentage of economic growth comes from labor.
Finally, estimated and identity equations were combined by input of technological changes. The technological progress is the main driver of long-run economic growth. Because of other input factor constant, the additional output obtained when adding one extra unit input of capital or labor will eventually decline, according to the law of diminishing return. Therefore, the driver of long-run growth has to be technological progress.
The four sector values beyond the analysis and thus provides an economic policy model. A discussion of the nature and the outcomes of this research follow.
I. Sources of Thailand’s Economic Growth
As noted, the research methodology in sources of Thailand’s economic growth
As noted, the research methodology in sources of Thailand’s economic growth