INTRODUCTION
Empirical studies indicate that the structural transformation process is closely linked to the economic growth of developed nations Kuznets (1971) in "Economics of Nations" identifies six key characteristics common to all developed countries during their economic growth, with one being a high rate of structural transformation within the economy Additionally, Chenery (1979) contributes to this understanding by further exploring the relationship between structural changes and economic development.
Structural Change and Development Policy analyzes the post-World War II development patterns in several developing countries, highlighting key characteristics of their development processes A significant feature identified is the transition from agricultural to industrial production, marking a crucial shift in their economic landscape.
Asian developing countries, particularly Vietnam, have experienced significant structural transformation over the past two decades, contributing to sustainable economic growth This ongoing development process highlights their crucial role in the global economy, making it essential to analyze the factors driving this transformation in these nations.
This paper aims to achieve three key objectives: first, to analyze the structural transformation processes of several Asian developing countries, including China, India, Indonesia, Korea, Malaysia, Nepal, the Philippines, Sri Lanka, Thailand, and Vietnam, from 1985 to 2010; second, to compare labor productivity between Vietnam and Malaysia, as well as Thailand and the Philippines; and third, to identify strategies for enhancing Vietnam's structural transformation process Consequently, the research focuses on three main questions: how does the structural transformation process manifest in Asian developing countries, is this process homogeneous across these nations, and what are the specific differences in structural transformation among them?
The structural transformation process refers to the shifts between different sectors of an economy, including agriculture, industry, and services, as influenced by development indicators like GDP and GDP per capita The agriculture sector encompasses activities such as forestry, fishing, hunting, and farming, while the industrial sector includes mining, quarrying, manufacturing, and construction This article will analyze the transformation processes and labor productivity in Vietnam, Malaysia, Thailand, and the Philippines, with detailed insights provided in chapter four.
The article progresses through several key chapters: Chapter two reviews relevant literature, focusing on theories and empirical studies of structural transformation in both the global context and Vietnam Chapter three outlines the dataset and research methodology employed Chapter four analyzes the structural transformation processes in Asian developing countries, comparing Vietnam's labor productivity with that of Malaysia, Thailand, and the Philippines Finally, chapter five presents the main conclusions, policy implications, and limitations derived from the findings in chapter four.
LITERATURE REVIEW
Theoretical review
According to Begg et al (1995), Gross Domestic Product (GDP) can be measured by the formulation:
Where: gdp i is GDP of a country in year i va ij is value added of sector j in year i j includes three sectors of an economy: agriculture, industry and service
Solow (1962) uses the Cobb-Douglas production function to form up Solow growth model q = A k α (2)
A is multifactor of productivity or technology progress of an economy k is capital per capita of an economy q is output per capita of an economy
Equation (2) illustrates that output per capita will experience significant growth when there are changes in productivity, efficiency, or technology within the economy A market economy naturally reallocates resources from less efficient sectors to more efficient ones, thus reinforcing the model's relevance to this research on structural transformation discussed in the subsequent sections of this chapter.
In 1955, Lewis introduced the two-sector labour surplus model, which describes an underdeveloped economy divided into traditional and modern sectors The traditional sector experiences a surplus of labour, while a gradual transfer of this labour to the modern sector occurs, leading to employment expansion until the surplus is fully absorbed This model serves as a foundational theory for understanding structural transformation, highlighting that economic growth can arise from the expansion of the modern sector and industries without diminishing agricultural output.
Ernst Engel developed Engel's Law in the nineteenth century, which posits that as household income rises, the percentage of income allocated to food decreases This phenomenon helps explain the diminishing share of agriculture in total production as GDP per capita increases Additionally, advancements in agricultural productivity driven by technological changes facilitate labor force liberalization, enabling workers to transition into non-agricultural sectors such as industry and services.
Kuznets (1971) identifies a two-phase structural transformation process in developed countries In the initial phase, the economy predominantly allocates resources to the agriculture sector As development progresses, there is a shift in resource allocation from agriculture to the industrial and service sectors In the second phase, resources are further re-allocated from both agriculture and industry to the service sector.
Empirical studies
In his 2008 analysis, Bah examines the structural transformation of nine developed countries—Australia, Canada, France, Germany, Italy, Japan, Sweden, the United Kingdom, and the United States—over the period from 1870 to 2000 The study reveals two key findings: first, developed nations exhibit a homogeneous process of structural transformation, and second, this transformation is characterized by well-defined patterns across these countries.
This empirical study, discussed in chapters four and five, aligns with Simon Kuznets' theoretical framework, which indicates that agriculture declines during both the first and second phases of development In contrast, the industrial sector experiences growth in the first phase but sees a decline in the second phase The service sector, however, consistently grows throughout both phases The transition from the first to the second phase occurs when GDP per capita reaches $8,100 Notably, all developed countries are currently situated in the second phase of development.
Bah (2009) highlights that while structural transformation positively influences economic growth, the Total Factor Productivity (TFP) of individual sectors is also crucial Utilizing panel data on sector employment shares and GDP per capita from the US, as a representative of developed countries, alongside Korea, Cameroon, and Brazil, which represent developing nations, the study spans from 1950 to present.
In a 2000 study analyzing sectoral productivity across developed and developing countries, it was found that developing nations exhibit the lowest productivity in agriculture compared to the US, followed by services and manufacturing sectors.
Hoang Kieu Trang (1998) analyzes structural change of Vietnam during 1980-
In 1997, a study highlighted that the growth rate of Vietnam's non-agricultural sector outpaced the overall GDP growth rate Additionally, the structural shift characterized by a decline in agriculture and a rise in industry and services contributed positively to the nation's economic growth.
Dekle and Vandenbroucke (2006) examine the influence of structural transformation on China's economic growth from 1978 to 2003, focusing on three key sectors: agriculture, private non-agriculture, and public non-agriculture Utilizing employment and GDP data by sector, the study identifies three primary drivers of China's growth during this period: high productivity in the private non-agriculture sector, the movement of labor from agriculture to non-agriculture, and the reallocation of labor within the non-agriculture sector.
Duarte & Restuccia (2010) analyze how sectoral labor productivity and labor reallocation contribute to structural transformation Their findings reveal significant disparities in sectoral labor productivity among countries, particularly pronounced between developed and developing nations in agriculture and services, while differences in industry are comparatively smaller Over time, the productivity gaps have notably decreased in agriculture and industry, yet the service sector continues to show minimal progress in bridging these disparities.
Conceptual framework
Structural transformation within an economy is driven by three key factors: technological change, investment, and capital accumulation, both physical and human These elements significantly enhance sectoral productivity, leading to continuous growth As sectors absorb these advancements, disparities in productivity levels—such as labor surplus and low productivity in agriculture—result in varied structural transformations across countries, typically shifting resources from low to high productivity sectors This reallocation of resources plays a crucial role in the transformation process, contributing to a nation's overall development and economic growth This paper will explore the relationship between structural transformation and GDP per capita growth in Asian developing countries, drawing insights from Kuznets' findings on developed nations.
Figure 1: Conceptual framework – structural transformation and growth
Source: author’s creation base on theoretical review and empirical studies
RESEARCH METHOLODOGY
Data
This research utilizes data sourced from the World Bank's World Development Indicators and Global Development Finance, covering a 26-year period from 1985 to 2010 The study focuses on 10 Asian developing countries—Vietnam, China, India, Indonesia, Korea, Malaysia, the Philippines, Sri Lanka, Nepal, and Thailand—resulting in a comprehensive panel dataset comprising 260 observations.
Research methodology
This study employs descriptive statistics and econometric techniques to analyze the structural transformation and growth patterns of developing Asian countries By utilizing polynomial functions, it examines the relationship between sectoral output shares—namely agriculture, industry, and services—and the logarithm of GDP per capita across these nations The findings aim to clarify whether these countries experience a similar structural transformation process.
For each sector, I estimate by the following equation: gdp it gdp it gdp va i 1 log( it ) 2 log( it ) 2 3 log( it ) 3 (3)
Where: va it is the sectoral output share of GDP for country i (i=1~10) in period t
i is fixed affect of country i
is coefficients of log( gdp it ) gdp it is GDP per capita of country i in period t
it is the error term
According to Nguyen Trong Hoai (2006), polynomial functions effectively represent the long-run average trend between dependent and independent variables Given that the structural transformation process requires a long-term analysis to capture the relationship between sectoral output share and the log of GDP per capita, a polynomial function is chosen for this analysis The degree of the polynomial function is determined by the goodness of fit, starting with a linear polynomial and incrementally increasing the degree until the change in R-squared is less than 0.01 This approach aims to simplify the model to the lowest degree while maintaining the highest possible goodness of fit.
EMPIRICAL ANALYSIS OF STRUCTRUAL
Overview of economic growth of Asian developing countries in period
Figure 2 below show the economic growth in GDP of ten Asian developing countries
P hi lli pp in es
Figure 2: Average GDP growth of Asian developing counties, 1985-2010 (%)
Source: Author draw base on data from World Bank, 2012
Based on the economic growth rates, the countries can be divided into three groups The first is very rapid GDP growth group above 7% annually during 1985-
In 2010, China was the only country to achieve an impressive average annual growth rate of 10.0% Following China, Vietnam led a second group of nations with a solid growth rate of 6.8%, while India, Malaysia, Thailand, and Indonesia recorded annual growth rates of 6.4%, 6.1%, 5.9%, and 5.6%, respectively A third group of countries, including Sri Lanka, Nepal, and the Philippines, maintained moderate annual growth rates of 4.9%, 4.5%, and 3.7%.
According to GDP growth data, Figure 3 and Table 1 illustrate the GDP per capita and growth rates for ten developing Asian countries Notably, China achieved the highest average annual GDP per capita growth rate of 9.0% from 1985 onwards.
Between 1985 and 2010, China led the way with significant economic growth, while Korea and Vietnam followed closely with average annual growth rates of 5.3% and 5.1%, respectively Other countries such as India, Thailand, Sri Lanka, Indonesia, Malaysia, Nepal, and the Philippines experienced varying GDP per capita growth rates, averaging 4.5%, 4.4%, 3.8%, 3.7%, 3.4%, 2.2%, and 1.3%.
Ph ill ip pi ne s
Figure 3: GDP per capita 1985 and 2010 (current, US$)
Source: Author draw base on data from World Bank, 2012
Table 1: Average GDP per capita growth 1985-2010 (%)
GDP per capita of Asian developing countries
VNM CHN IND THA IDN NPL PAK PHL LKA
GDP per capita of Malaysia and Korea
Figure 4: GDP per capita of Asian developing countries 1985-2010
Source: Author draw base on data from World Bank, 2012
Experimental study result of structural transformation Asian developing
4.2.1 Result of statistics descriptive model
This section analyzes the structural transformation process of ten Asian developing countries over time using descriptive statistics The findings are illustrated in Figure 5, highlighting key trends and developments in these nations' economic structures.
Figure 5: Structural transformation of Asian developing countries 1985 and
Source: Author draw base on data from World Bank, 2012
The economic structural transformation of Asian developing countries from 1985 to 2010 reveals several key insights: (1) GDP per capita varies significantly among countries at different development levels; (2) the starting and ending points of sectoral shares in GDP—namely agriculture, industry, and services—differ due to these varying development levels; (3) geographical location, natural resources, technology, and economic policies contribute to divergent paths of economic transformation; (4) despite differences in starting points and growth rates, the agricultural sector's share generally declined across all countries as GDP per capita increased; and (5) while most countries experienced an increase in the industrial sector's GDP share, some saw a decrease, and the service sector's share rose in most countries, with notable exceptions like Thailand, Vietnam, and Indonesia during specific periods.
In this study, we utilize a polynomial function to model the structural transformation process across various sectors, as detailed in Chapter Three The equation is represented as \( va_{it} = \alpha_i + \beta_1 \log(gdp_{it}) + \beta_2 \log(gdp_{it})^2 + \beta_3 \log(gdp_{it})^3 + + \epsilon \), where \( va_{it} \) denotes the sectoral output share of GDP for country \( i \) (where \( i \) ranges from 1 to 10) during period \( t \).
i is fixed affect of country i
is coefficients of log( gdp it ) gdp it is GDP per capita of country i in period t
it is the error term
In the agricultural sector, a linear polynomial regression model was applied, yielding an R-square of 0.76 A subsequent fit using a quadratic polynomial improved the R-square to 0.83, indicating that the relationship between agricultural output share and the log of GDP per capita is best represented by a quadratic model Higher degree polynomials did not significantly enhance the fit For the industrial sector, a third-degree polynomial was the best fit, but with a lower R-square of 0.47 compared to agriculture Similarly, the relationship between the service sector's output share and the log of GDP per capita was also modeled with a third-degree polynomial, resulting in an R-square of 0.33, which is lower than both agriculture and industry The regression results for developing countries in Asia are summarized in Table 2.
Table 2: Summary Regression Result for Asia Developing Countries
* Significant at 10%; ** Significant at 5%; *** Significant at 1%; **** Significant at 0.1%
Note: This table reports the fixed effect regression of equaltion (5) of each sector The data consist of 260 obersvations including 10 countries with 26 observations per country The P- value is in parentheses
Source: Author’s calculation using panel data from World Bank, 2012
To estimate the fixed effect (αᵢ) for each country, I employ the Least Square Dummy Variables (LSDV) estimator model The average fixed effect across all ten countries, denoted as α, is derived from the regression results presented in Table 2, with values of 2.29 for agriculture, 26.78 for industry, and -91.19 for services Each country's fixed effect, αᵢ, is calculated as αᵢ = αᵢ - α, representing the fixed effect deviation from the mean for that country According to Bah (2008), analyzing the coefficient distribution, including these fixed effect deviations, aids in assessing the heterogeneity among countries As shown in Table 3, the fixed effect deviation from the mean is 3.92 for agriculture, while it stands at 6.83 for industry and 5.21 for services.
After conducting regression analysis, I utilized Stata to create scatter plots that illustrate the output share of each sector in relation to the log of GDP per capita, enabling an examination of sectoral transformation and each country's contributions Figure 6 presents the scatter plot comparing the output share of agriculture with the log of GDP per capita, featuring a fitted curve along with lower and upper bounds marked at two standard deviations of the forecasted values.
Table 3: Fixed Effect Deviation from the Mean
This table presents the variations in the average fixed effects across all countries compared to the fixed effects specific to each individual country The average fixed effect for all countries is derived from regression equation (3) for each sector, while the fixed effect for each country is calculated using Least Squares Dummy Variable (LSDV) estimation.
Source: Author’s calculation using panel data from World Bank, 2012
Figure 6: Scatter chart of agriculture output share and Log of GDP per capita
Source: Author’s calculation and draw from Stata
The agricultural transformation process in countries tends to decline as GDP per capita increases Notably, when GDP per capita reaches approximately US$ 6,600 (log of GDP per capita at 8.8 or higher), the agricultural sector's share stabilizes at around 7% This indicates three key points: first, an increase in GDP per capita correlates with a decrease in the agricultural share; second, when the agricultural share falls to US$ 6,600, Asian developing countries transition from the first to the second phase of structural transformation, as outlined by Kuznets; and third, during this transition, maintaining an average agricultural share of 7% is crucial for ensuring national food security.
Figure 7: Scatter chart of industry output share and Log GDP per capita
Source: Author’s calculation and draw from Stata
Figure 7 illustrates the relationship between the sectoral output share of industry and the logarithm of GDP per capita, highlighting key trends: (1) The share of industry rises with the log of GDP per capita, reaching a peak of 45% at approximately US$ 6,600, after which it gradually declines as GDP per capita continues to increase This indicates a structural transformation shift at the US$ 6,600 threshold, similar to trends observed in the agricultural sector; (2) The industrial share among countries varies significantly, with Nepal consistently below the fitted curve, while China, Vietnam, and Indonesia often exceed it Conversely, countries like Sri Lanka, India, and the Philippines show a stable industrial share relative to GDP per capita, with the Philippines exhibiting a declining trend.
Figure 8: Scatter chart of service output share and Log GDP per capita
Source: Author’s calculation and draw from Stata
The service sector exhibits the lowest goodness of fit among the three sectors, with an R-square value of 0.33, indicating a distinct transformation process As illustrated in Figure 8, the relationship between service output share and the logarithm of GDP per capita unfolds in three key periods In the first period, with a log GDP per capita below 7.0, the share of services rises alongside GDP per capita During the second period, ranging from a log GDP per capita of 7.0 to 8.8 (approximately US$ 1,100 - 6,600), the service share stabilizes at around 48%, reflecting a slowdown in agriculture's share while industry absorbs this reduction The third period, characterized by a log GDP per capita exceeding 8.8 (over US$ 6,600), marks a transition in the service sector as it shifts from the first to the second phase of structural transformation Country-specific analyses reveal that China, Indonesia, and Malaysia's service sectors fall below the fitted curve, while Sri Lanka and India are positioned above it Notably, Vietnam's service sector has shifted downwards from above to below the fitted curve as GDP per capita surpasses 6, whereas the Philippines' service sector has moved upward from below the curve.
Figure 9: Structural transformation of Asian developing Countries
Source: Author’s calculation and draw from Stata
Figure 9 which is a combination of figures 6, 7, and 8 shows us the structural transformation of Asian developing countries
4.2.3 Structural transformation and labor productivity of Vietnam and a comparison with Malaysia, Thailand and the Philippines
Although Vietnam maintained a relatively high GDP per capita growth and stability at 5.11% in the period 1985-2010 (Malaysia 3.38%, Thailand 4.41%, the
Philippines 1.33%), but GDP per capita of Vietnam is still lower than Malaysia, Thailand and the Philippines
A gri cul ture s ha re ( % G D P )
Ind us tr y sha re ( % G D P )
S er vi ce s ha re ( % G D P )
Firgure 10 displays that although the process of economic structural transformation also took place in Vietnam and other countries, but the share of agriculture of Vietnam is always at a higher level than others and the share of the service sector of Vietnam is always lower than other countries The highlight of Vietnam in the industry is from the lowest point of all countries, the share of Vietnam's industry has continued to increase, surpassing the Philippines and very close to Thailand
Despite a decline in the percentage of agricultural workers in Vietnam from 70% in 1996 to 51% in 2009, this figure remains significant when compared to the agriculture sector's contribution to the GDP, which stood at 21% in 2009.
S e c to ra l E m p lo y m e n t s h a re V ie tn a m
Figure 11: Sectoral employment share of Vietnan 1996-2009
Source: Author’s calculation and draw from data of World Bank, 2012
% E m p lo ym en t in A g ri cu lt u re s ec to r
% E m p lo ym en t in In d u st ry s ec to r
% E m p lo ym en t in S er vi ce s ec to r
Figure 12: Sectoral employment share of Vietnam, Malaysia, Thailand and the Philippines
Vietnam's industrial sector has shown significant growth, with its labor rate surpassing that of the Philippines and closely approaching Thailand's In contrast, the service sector in Vietnam lags behind, consistently maintaining a lower labor rate compared to Malaysia, Thailand, and the Philippines This trend reflects the broader shifts in GDP share across these countries.
A comparative analysis of sectoral labor productivity among Vietnam, Malaysia, Thailand, and the Philippines reveals that Vietnam lags behind in all three sectors In 2009, Vietnam's labor productivity in the industrial sector was only US$ 3,892 per person per year, significantly lower than Malaysia's US$ 26,637, Thailand's US$ 15,144, and the Philippines' US$ 9,671 This trend continues in the service sector, where Vietnam also shows diminished productivity compared to its regional counterparts Overall, the findings indicate that Vietnam's labor productivity is less effective than that of Malaysia, Thailand, and the Philippines across all sectors.
Labor productivity in agriculture sector
Figure 13: Labor productivity in agriculture sector of Vietnam, Malaysia, Thailand and the Philippines
Source: Author’s calculation and draw from data of World Bank, 2012
Labor productivity in industry sector
Figure 14: Labor productivity in industry sector of Vietnam, Malaysia,
Source: Author’s calculation and draw from data of World Bank, 2012
Labor productivity in service sector
Figure 15: Labor productivity in service sector of Vietnam, Malaysia, Thailand and the Philippines
Source: Author’s calculation and draw from data of World Bank, 2012
Vietnam's agricultural, industrial, and service sectors are less efficient compared to those of Malaysia, Thailand, and the Philippines Among these sectors, the service sector is the least effective, generating an average of US$ 2,636 per person annually In contrast, the industrial sector demonstrates the highest efficiency, with an average output of US$ 3,892 per person per year.
Table 4: Sectoral labor productivity of Vietnam (US$ per person per year)
Source: Author’s calculation from data of World Bank, 2012
Sectoral labor productivity of Vietnam
Figure 16: Sectoral labor productivity of Vietnam
Source: Author’s calculation and draw from data of World Bank, 2012
CONCLUSIONS AND RECOMMENDATIONS
Conclusions
Most Asian developing countries, with the exception of Korea and Malaysia, are currently in the initial phase of structural transformation As GDP per capita rises, the agriculture sector typically experiences a decline, while the industry sector shows growth Additionally, the service sector also expands in response to increasing GDP per capita.
The transition to the second phase of structural transformation occurs when GDP per capita reaches $6,600, at which point the contributions of agriculture, industry, and services are approximately 7%, 45%, and 48%, respectively.
(3) Asian developing countries including Vietnam are not all followed the same process and are not homogeneity of structural transformation;
Vietnam has the highest agricultural contribution to GDP among Malaysia, Thailand, and the Philippines, while its share of services in GDP remains the lowest among these four nations.
Vietnam has a significantly higher labor distribution rate in the agricultural sector compared to Malaysia, Thailand, and the Philippines, while conversely, its labor rate in the services sector is notably lower than that of these neighboring countries.
Labor productivity across all three sectors in Vietnam—agriculture, services, and industry—falls short compared to Malaysia, Thailand, and the Philippines Among these, the agricultural sector exhibits the lowest efficiency, followed by the service and industrial sectors.
Recommendations
Basing on the findings of this research, I would like to propose the following
Vietnam's agriculture sector holds a significant share of the country's GDP and employs a large portion of the workforce; however, labor productivity in this sector is notably low To enhance agricultural efficiency, the government should prioritize rural development initiatives, including the selection of superior crop and livestock varieties This strategy aims to boost productivity in agriculture, ultimately facilitating the transition of labor from agriculture to the more efficient industrial and service sectors.
Vietnam's industrial sector has made significant progress, prompting the government to focus on sustaining its growth It is essential to continue implementing policies that promote industrialization, modernization, and equitization to enhance the industry's performance relative to other countries.
Vietnam's service sector remains underdeveloped compared to other ASEAN countries, prompting the government to expand the service market and diversify its offerings to enhance competitiveness and growth.
Vietnam has a high agricultural labor rate, with a low percentage of workers in the service sector, resulting in overall sector performance lagging behind other countries To address this, the government should develop policies that promote labor restructuring across sectors and enhance vocational education initiatives, focusing on human capital investment to boost labor productivity in Vietnam.
To enhance productivity across all sectors, particularly in agriculture and services, the Vietnamese government should encourage enterprises to focus on and invest in new technologies, given the country's low GDP per capita.
The share of employment in agriculture is expected to decline, while the industrial and service sectors will see an increase in job opportunities Consequently, it is essential for the government to implement effective migration and urban development policies to adapt to these changing employment trends.