INTRODUCTION
Background of the study
Vietnam has been through a rapid economic growth in the last three decades The characteristics of this rapid growth are the decline of the number living in poverty and the rising average income Since the 1990s, there has been nearly 30 million people overcoming the poverty line More specifically, the GDP per capita from 1990 to 2015 has increased from $100 to $2,300, respectively (Oxfam, 2017) In the last 30 years, the average of the economic growth has increased from 5-6 percent to 6.4 percent The rapid growth especially the increasing economic has several impacts on the Vietnamese On the one hand, it improves people‟s living standards However, it also causes the economic inequality as well as the uneven opportunity among people
Which means the equal distribution of income of the people has an important role in a society with high equality So now the challenge is that in the situation of the rapid economic growth how does Vietnam make solutions so that the distribution of income across Vietnam becomes much more equal
The rapid economic growth and the good policies in the last 30 years have significant contribute to poverty reduction However, the gap between the rich and the poor has been expanding seriously This gap has been causing many social problems and need to be solved as soon as possible So the Government need to issue new policies that ensure the poverty and the inequality will be controlled According to Saumik et al
(2016), while Vietnam experiencing the economic structural transformation as well as the poverty reduction, the growth is more beneficial for the rich than the poor This is realized as the returns to manufacturing and to agriculture increasing only for the top
10 th - 20 th percentiles In general, the economic inequality has been rising dramatically in the last twenty years
According to Oxfam (2017), in one day, the Vietnamese richest man earn more than the poorest earns in 10 years This man possessed assets worth $2.3bn which could be used to help 13 million poor people to get out of poverty According to the World Bank (2013), from 1992 to 2012, the Gini index has risen from 35.7 to 38.7, showing that the income inequality rose However, this kind of data may underestimate the serious impacts that inequality can have on Vietnam For example, the expenditures or the income of rich individuals may be under-reported in the household surveys, so the empirical measures of inequality may be biased
Since 2004, among the first four quintiles (the bottom 80 percent) there is a small difference in the income distribution However, in comparison between those quintiles with the richest quintiles (the top 20 percent), the income distribution has been widening significantly In other words, the benefit of growth has been distributed unequally in recent years This is consistent with the report conducted by Oxfam in
2016 The survey did depth-interview with 600 respondents from three provinces (Lao Cai, Nghe An, Dak Nong) The results showed that the income of the 20 percent of the richest households is 21 times higher than that of the 20 percent of the poorest households.There is one point suggesting that income at the province level is serious and has been increasing over time, especially in the remote areas where agriculture is the main source of income (Lam et al., 2016) Therefore, it is necessary to look into the income sources at province level to justify the income disparity.
Rationale of the study
It is revealed by the evidences in the research by Nguyen (2016) that reductions in poverty and dividends from growth have been spread unevenly across Vietnam, increasing income inequality between regions and to some extent within regions By region, the Red River Delta and the South East are considerably overrepresented in middle income groups, whereas the Mekong River Delta is overrepresented in the near- poor group The North West and Central Highlands are the two regions where most of the poor live According to VHLSS (2012), the South East has the highest monthly income per capita in the country (VND3,016,000 or $150), which is more than three times the average monthly income found in the North West region (VND999,000 or less than $50)
Using VHLSS data (2004–2014), the findings by McCaig &Brandt (2015) show that households in the South East (the richest region in Vietnam) have the highest income mobility of any region Compared with households in the Red River Delta (the reference group), households in the North East, South Central Coast, and Central Highlands are less likely to move up from the lowest quintile Households in the South East are more likely to move up from the lower 40 percent With downward mobility, households in the North Central Coast and Central Highlands are more likely to move down from the high-income quintiles
Such regional variation is also the product of ethnic factors in Vietnam (McCaig
&Brandt, 2015) Vietnam is an ethnically diverse country: there are 54 ethnic groups, in which the Kinh majority accounts for 85 percent of the population Kinh tend to live in delta areas, and have higher living standards than other ethnic minorities Hoa (Chinese) are also a rich group, and also live in delta areas Thus, Hoa are often grouped together with Kinh in studies on household welfare, although they may face ethnic discrimination in other areas
Income poverty is disproportionately higher among ethnic minority groups Members of ethnic minority groups make up less than 15 percent of the country‟s population but account for 70 percent of the extreme poor According to the 2014 survey conducted by the Ministry of Labor, Invalids and Social Affairs, the incidence of poverty among ethnic minorities was as high as 46.6 percent, compared to 9.9 percent for the Kinh and Hoa groups The gap in income mobility among ethnic groups is also large, and there are signs that this gap has been increasing over time Between 2010 and 2014, around
19 percent of ethnic minorities in the bottom quintile moved to a higher income quintile, while for Kinh and Hoa, this figure was 49 percent In addition, ethnic minorities are more likely to move down but less likely tomove up, compared with Kinh and Hoa It is revealed that both the absolute and relative income gap between Kinh/Hoa and other ethnic groups has increased over time The ratio of per capita income of Kinh/Hoa to that of other ethnic groups increased from 2.1 in 2004 to 2.3 in
The income disparity sourced from the ethnic and regional differences has led to the income inequality at the provincial level Therefore, it is meaningful to analyze the income sources at province level from 2008 – 2016 and how various factors affect them by using spatial analysis.
Objectives of the study
The overarching aims governing this current study is to obtain the insights into the current income distribution and to reduce the income disparity in Vietnam at the provincial level Therefore, the thesis‟s objective is to promoting income diversification by examining what economic and demographic variables affect the income sources among provinces in Viet Nam using spatial approach.
Research questions
The following research questions are derived in this current study:
(1) Is there the presence of spatial autocorrelation of income sources among provinces in Viet Nam?
(2) How do economic and demographic factors affect the income sources in Viet Nam?
Significance of the study
This study has several contributions to the literature Firstly, it is the first to identify the composition of sources of income in Vietnam and the contribution of various income sources to total income inequality with reference to the use of spatial analysis
Secondly, this study provides an analysis of long-term changes in income sources in Vietnam in the last ten years from 2006 to 2016 This research expects to provide the income inequality decomposition by income sources, based on the Vietnam Household Living Standard Surveys (VHLSS) carried out every two years, to reduce the errors that resulted from data aggregation process Lastly, the recommendations generated in this current study expect to make contributions to policy development to diversify the sources of income, contributing to minimize the income inequality in Vietnam.
Design of the study
There are five chapter included in this current study, including:
Chapter 1 – Introduction – presents the background and rationales of the current study
The research aims and objectives, research questions and design of the study are also generated in this chapter
Chapter 2 – Literature review – critically explores the theoretical fundamentals concerning the spatial analysis and income inequality and sources This chapter also looks in the previous literatures to identify the literature gaps
Chapter 3 – Methodology - presents research methodology The research method, data collection measures and how such models as Spatial Durbin Model (SDM, Spatial lag model (SLM), Spatial error model (SEM) are used for data analysis This chapter also discusses the validity and reliability of the research instruments
Chapter 4 – Findings and discussions – shows the results of data analysis and discusses the income sources of Vietnam with the provincial levels
Chapter 5 – Conclusion and recommendations – summarizes the whole study and research findings In addition, limitation of the thesis and suggestions for further research are also given out.
LITERATURE REVIEW
Spatial analysis
Spatial analysis or spatial statistics includes any of the formal techniques which study entities using their topological, geometric, or geographic properties Spatial analysis includes a variety of techniques, many still in their early development, using different analytic approaches and applied in fields as diverse as astronomy, with its studies of the placement of galaxies in the cosmos, to chip fabrication engineering, with its use of
"place and route" algorithms to build complex wiring structures In a more restricted sense, spatial analysis is the technique applied to structures at the human scale, most notably in the analysis of geographic data
Complex issues arise in spatial analysis, many of which are neither clearly defined nor completely resolved, but form the basis for current research The most fundamental of these is the problem of defining the spatial location of the entities being studied
More specifically, spatial autocorrelation can be defined as the coincidence of value similarity with location similarity (Anselin, 2003) There is positive spatial autocorrelation when high or low values of a random variable tend to cluster in space and there is negative spatial autocorrelation when geographical areas tend to be surrounded by neighbors with very dissimilar values There are at least three possible explanations One reason is that there is a simple spatial correlation relationship, showing what is causing an observation in one location also causes similar observations in nearby locations Another possibility is spatial causality, meaning that something at a given location directly influences it in nearby locations A third explanation is spatial interaction: the movement of people, goods or information creates apparent relationships between locations
Spatial heterogeneity means in turn that economic behavior is not stable across space and may generate characteristic spatial patterns of economic development under the form of spatial regimes: a cluster of forward States (rich regions, the core) being distinguished from a cluster of backward States (poor regions, the periphery) The methodology of exploratory spatial data analysis (ESDA) is applied to find the evidence of spatial autocorrelation and spatial heterogeneity The estimation of global spatial autocorrelation (Moran‟s I) and local spatial autocorrelation (LISA) will indicate how economic activities are located in India during the reform period 1993–
2004 Moreover, local spatial statistics confirms the existence of spatial heterogeneity and, consequently, raises an agenda behind the differential growth profile of forward States and backward States.
Income as an aspect of livelihoods
Although income from agricultural activities is the base of livelihood strategies for rural households in developing countries (Ashley, 2000; Dolan, 2004; Ellis, 1999;
Sandbrook, 2006), empirical evidence suggests that households regularly engage in nonagricultural activities as a source of income (Ashley, 2000; Ellis, 1998, 1999;
Hartter, 2007; Kaag et al., 2008; Lepper and Schroenn Goebel, 2010; Smith et al.,
2001) It has been found that high levels of non-agricultural income are often associated with higher levels of agricultural productivity and higher overall household income (Dolan, 2004; Ellis, 1999; Ellis and Bahiigwa, 2003; Evans and Ngau, 1991)
According to Ellis (1999: 2) livelihoods are defined as „the activities, the assets and the access that jointly determine the living gained by an individual or household‟ The concept of livelihoods was originally coined in the 1940s to describe people‟s strategies of making a living (Kaag et al., 2008) However, with the macroeconomic development literature of the 1980s and the pioneering literature of Robert Chambers, the livelihood approach transformed into its current meaning by including the complex dimension of poverty (Ahebwa, 2012; Brocklesby and Fisher, 2003; de Haan and Zoomers, 2005; Kaag et al., 2008)
In Vietnam, the majority of rural dwellers secure their livelihoods primarily through small-scale subsistence agriculture (Nguyen, 2004; Lam et al., 2016) Most Vietnamese households are dependent on small-scale agriculture activities for their earnings (GSO,
2016) Vietnamese households use their goods from their agricultural surpluses to sell in the local markets for cash generation Some other affluent households invest in large scale crops or livestock farming for commercial purposes Livestock is also used as savings for covering difficult periods or extraordinary expenditures for celebrations or holidays, such as the payment of dowries However, it is indicated by the previous studies in the sources of income in Vietnam that it is critical to expand the horizons of sources of income with the focus of non-agricultural sector (Nguyen, 2004; Hartter, 2007; Mackenzie, 2011; Lam et al., 2016) Drawing on the country‟s abundant resources, the Vietnamese government is stimulating the development of non- agriculture sectors to diversify the sources of incomes.
Background of ethnicity and income structure in Vietnam
2.3.1 Ethnic geographical distribution in Vietnam
Vietnam has 54 officially recognized ethnic groups, with more than 85% of the population made up of Kinh people The rest of the population, 15%, is distributed among 53 ethnic minorities Most of these ethnic groups, however, have a few thousand people each According to the General Statstisitics Office Vietnam (GSO,
2015), of the ethnic minority group, the most numerous are the Tay (1.9%), Thai (1.8%), Muong (1.5%), Kho Me (1.5%), H‟Mong (1.2%) and Nung (1.1%) Most ethnic minority groups reside in mountainous areas, while the Kinh and Chinese are found in the lowland areas in Red River delta, Central Coast and Mekong Delta By comparison, the minority groups are primarily located in the East and West Northern mountains, in the Central Highlands, and in the North Central Coast
2.3.2 Poverty distribution by ethnicity in Vietnam
Since the economic reform introduced in 1986, known as Doi Moi, both majority and minority ethnic groups have experienced an improvement in living standards, which has been reflected in increasing average expenditure per capita, falling fertility rate and household size, and declining in the level of malnutrition (Epprecht, Müller, & Minot,
2011) However, Vietnam‟s ethnic minority groups lagged behind the Kinh ethnic majority Initially, early in the last decade, the ethnic minority groups achieved a significant success in poverty reduction, e.g poverty rates fell from 75.2% in 1998 to 50.3% in 2008 Nevertheless, ethnic minorities have increasingly accounted for most of the poor in Vietnam Although they contributed only 15% of Vietnam‟s total population, ethnic minorities accounted for about half of the poor and 68% of the extremely poor (Kozel, 2014) Poverty rates among ethnic minorities average between four and seven times higher than that of the Kinh people The malnutrition rate of children from ethnic minority households is also considerably higher than among children from ethnic majority households Vietnam‟s poverty map shows that the majority of the poor live in the upland regions, whereas the better off households are found in Vietnam‟s urban centres along the coast There existed an increasing disparity between the ethnic majority and ethnic minorities among income percentiles in Vietnam from 1998 to 2010 In 1993, the ethnic minority was 1.6 times poorer than the ethnic majority This gap increased to 2.4 times in 1998, 4.5 times in 2004 and 5.1 times in 2010 The proportion of the poor from Vietnam‟s ethnic minorities in 2010 was considerably higher than in 1998
2.3.3 Changes in Vietnam’s income structure in Vietnam
Income structure in Vietnam has changed over time The proportion of income from agriculture has declined, while wage income has contributed to an increasing share of total household income in 2000s as well as in the previous decade In rural areas, crop income and agricultural side-line income remained two main sources of household income, but together they contributed one third of total household income for top ten percentile income households However, income from cultivation declined sharply by half compared with its level a decade ago (Benjamin et al., 2017; McCaig, Benjamin,
& Brandt, 2009) The proportion of income from wages in rural areas increased faster than in urban areas
The share of wage income of the bottom-income household group increased faster than that of the top-income households In the meantime, in urban areas, changes in income structure have not been as fast as in rural areas in 2000s However, wages had already become the main income source of urban households since the 1990s The share of agricultural side-line income in total household income has remained stable at a small share in urban areas during the 2000s The top income quartile households experienced a faster increase in income than the other quartiles The income share from remittances and other income sources in 2000s has moderately decreased compared to the 1990s
There was also a shift in the employment structure among ethnic minorities toward wages in nonfarm employment and nonfarm self-employment in the early 2000s (Pham
& Bui, 2010) However, the ethnic minorities still received a smaller amount of their income from non-agricultural wages and nonfarm businesses In the meantime, the ethnic majority received a higher portion of their income from wages (Cuong, 2012;
The main income source for the ethnic majority was from wage employment, whereas for the ethnic minority, the main source was crop income Poorer ethnic minority households had a larger proportion of their total income from crops (Cuong, 2012) In terms of employment, in 2006 agriculture accounted for 30% of ethnic majority employment, but made up 55% of ethnic minority employment (Kozel, 2014) There was a significant rise in income share from wages, while the level of income from the agricultural sector has declined However, the change toward wage-earning employment of ethnic minorities was slower than those of the ethnic majority There are several studies on income inequality between ethnicities in Vietnam (Benjamin et al, 2017; Kozel, 2014; Cuong, 2012; Baulch, Pham, and Reilly, 2012; Baulch, 2011;
Epprecht et al 2011; World Bank, 2009; Van de Walle and Gunewardena, 2001)
However, most of them focused on various characteristics to explain the widening income or income inequality gap Although ethnic minorities have made significant progress in improving living standards, health and education in recent years, this group still lag behind the ethnic majority in terms of household per capita expenditure and income The absolute gap between the ethnic majority and ethnic minorities widened dramatically in the 2000s (Benjamin et al., 2017) The main causes of the disparity between the ethnic groups are differences in educational attainment, residential area, accessibility to public services and household assets (Cuong, 2012; Dang, 2012;
Tuyen, 2016; van de Walle & Gunewardena, 2001; World Bank, 2009) Furthermore, Benjamin et al (2017) and Cuong (2012) find that the main contributors to the widening income gap are the ethnic minority‟s lower wages and lower non-farm business income In addition, the income structure of the ethnic majority people has shifted from the agricultural sector to non-agricultural sectors more quickly than that of the ethnic minority This income source disparity is also the drivers of the larger income gap between ethnic minority groups (Cuong, 2012).
Previous studies
Concerns about increasing income inequality with reference to the sources of income have become the areas of focus in many researches which investigating the income issues in the world and Vietnam Dabla-Norris et al (2015) have investigated the factors influencing the increasing inequality worldwide It is realized that the issue of income equality under the effects of sources of income has become alarming in not only such developed countries as the US, European countries, Japan and Korea, etc but in developing and poor nations as well (Dabla-Norris et al., 2015; Furrer, 2016)
The findings by Milanovic (2013) have revealed that the effects generated by the trend of globalization provide benefits for those with middle and high income levels rather than those with the low level By using the data obtained between 1988 and 2008, he concluded that while those who have the top 1% income experienced a 70% increase in their income over the given period, their poor counterparts hardly enjoyed any increase in their income Oxfam (2017) emphasized that the top 1% rich people are those who own the majority of global wealth These findings are also supported by the researches concerning the expanding income inequality in such others countries in BRICS by Berg (2015) and Haldane et al (2015) Additionally, these researches identified that among the most powerful factors influencing the income inequality, the source of income have significant impacts on income inequality
For the past decades, owing to the stable and skyrocketing economic development Vietnam has experienced the significant increase in the amount of average income per capita, contributing to the poverty reduction However, the studies by McCaig et al
(2009) and Kozel (2014) indicates that despite the economic development and income increase, the income gap in Vietnam has been continuously widened These scholars provide the evidences with different measures to indicate that there is a rise in the absolute income gap between the top and bottom income groups in Vietnam Oxfam
(2017) also reported that the daily income of the top 1% is at least ten times more than the annual income of the top 5% bottom in Vietnam The difference between the income level of rural and urban households has also witnessed the same pattern
Consequently, the income disparity has remained as one of the most problematic issues in Vietnam Kozel (2014) also attempts to prove that the increasing income gap across the country is significantly attributed to the sources of income which are different province by province and region by region in Vietnam Therefore, it is critical that the policymakers and scholars look into income sources as a significant and meaningful factor to the income inequality in Vietnam
In Vietnam, the income gap is regarded as one of the most challenging barriers to the attempts to obtain the sustainable development of the Government Despite the reduction of the poverty rate to less than 10%, the income inequality has still lowered the progress as the whole (Kozel, 2014) It is planned by the Government that the development policies will target to earn a 2% decrease per year in the poverty rate (Gibson, 2016) Dealing with the inequality requires the investigation into sources of income in Vietnam
According to Abdulai, A., & CroleRees, A (2001): “the income of agricultural households is affected by various factors such as land, the level of education, the number of labors” The research titled Effect of Resources on Incomes of Agricultural Households in Thanh Hoa Province: A Case Study at Tho Xuan and Ha Trung Districts by Chu Thi Kim Loan & Nguyen Van Huong (2015) also points out that sources like the scale of production (lands, farms), the The research by Nguyen & Tran (2018) concerning the effects of various income sources on income inequality also points out that They also revealed that among the sources of income wages and non-agriculture incomes are the most influencing drivers of income gap in Vietnam Their counterpart from agricultural activities were also relatively evenly distributed The research findings also imply significant changes in the structure of incomes in Vietnam with a shift from agriculture reliance to non-agriculture reliance economy Therefore, it can be concluded that the income sources have significant impacts on the income equality
However, in all the studies concerning this issue there has been no significant research concerning the spatial analysis of income sources in Viet Nam at province level especially after Viet Nam‟s signing WTO in 2006 This study will focus on the income sources based on different economic and demographic variables at the province level and will explain the influence of those variables on the income sources using these variables.
METHOD AND METHODOLOGY
Method and methodology
The major difference between spatial econometrics and standard econometrics is that spatial econometrics requires diffrent sets of information It relates to the observed values of the variables and it also relates to the particular location where the variables are observed This means spatial regression takes into account the spatial correlation
This study uses Moran I‟s test to test the presence of spatial autocorrelation of the income sources among provinces If this index is significant at 5% then applying spatial model is necessary The Moran I‟s test takes the form like this:
Ho: no spatial correlation among provinces H1: there is spatial correlation among provinces
Xi : Observed variable at the province i
Xj : Observed variable at the province j
Wij : spatial weight matrix between two provinces
In this thesis, spatial weight matrix (Spatial contiguity weights) indicating whether spatial units share a boundary or not is used to summarize the spatial relation among 63 spatial units (provinces) The spatial weight matrix contains 63 columns and 63 rows associated with 63 provinces in Viet Nam: n𝑤 𝑛 𝑤 11 ⋯ 𝑤 𝑛1
𝑤 1𝑛 ⋯ 𝑤 𝑛𝑛 (1) and has the standard form as following:
0, 𝑏𝑛𝑑(𝑖)𝑏𝑛𝑑(𝑗) = (2) Where: i, j: provinces taken into consideration bnd: boundary
The weight matrix receives the value as 1 when these two provinces share the border and as 0 otherwise
Besides the OLS, this paper also runs three other spatial models which are Spatial Durbin Model, Spatial lag model and spatial error model and then compares between them to choose the best model for analyzing
The Spatial Durbin model takes the form:
X: a matrix of non-stochastic regressors β (1), β (2), ρ: parameters to be estimated
W: the weight matrix exogenously given
WY: the spatially lagged variable of Y WX: the spatially lagged variable of X The spatial lag model takes the form:
U: stochastic disturbances β, ρ: parameters to be estimated W: the weight matrix exogenously given WY: the spatially lagged variable of Y The spatial error model takes the form:
X: a matrix of non-stochastic regressors U: stochastic disturbances, β: parameters to be estimated
Wu: the weight matrix of stochastic disturbances
Finally this paper uses the software QGIS for drawing maps to see the changing rate of income sources across provinces as well as the main regions.
Data collection
Dependent data : Per capita monthly income at current prices by income sources and by provinces (deflated by CPI with year 2008 as base year)
Per capita monthly income is calculated by dividing the household‟s total income by the number of family members then dividing by 12 months This income includes: income from wages; income from agriculture, forestry and fishery (after tax); income from non-agricultural, forestry and fishery (after tax); and the last is other income sources such as donations, gratuities, savings interest, etc Items which are not taken into account in the income include savings, debt collection, asset sale, debt financing, transfers, capital from joint ventures, associates in production and business
- Immigration and migration rate: a Immigration rate:
The number of people from another territorial unit (original place) immigrating to a territorial unit during the study period (usually one year) on average per 1000 inhabitants of that territorial unit
Ptb : average population b Migration rate:
The number of people from a territorial unit migrating to other territorial unit during the study period (usually one year) on average per 1000 inhabitants of that territorial unit
Ptb : average population (calculated until midyear)
- Percentage of workers aged 15 and over who are working in a trained economy by province
- The percentage of working population aged 15 and over working in the total population by province
- Sex ratio of population by provinces: reflects the number of males over 100 females
- Registered capital for FDI projects (mill.USD)
All the explanatory variables are collected from the Population and Household investigation conducted every 10 years, and from Population change survey and Labor force survey conducted every year.
FINDINGS AND DISCUSSIONS
Area of Study
According to GSO (2016), there are total 64 provinces in Vietnam with Hanoi and Ho Chi Minh as the socio-economic centers Currently, the 64 provinces in Vietnam are grouped into eight regions depending their geographic features, including:
The region of Northwest in Vietnam, consists of six provinces including Hoa Binh Lao Cai, Lai Chau, Yen Bai, Son La and Dien Bien which are located in the mountainous northwestern areas of Vietnam With the population of 4.5 million people, these Northwest provinces are recorded as the poorest provinces in Vietnam with the income majorly sourced from agricultural activities
The Northeast Vietnam consists of such provinces as Bac Giang, Bac Kan, Cao Bang,
Ha Giang, Lang Son, Phu Tho, Quang Ninh, Thai Nguyen, and Tuyen Quang which are located in the north of the Red River Delta With the population of more than 8.5 million people and economic and geographic advantages, this region is regarded as one of the regions taking the most important role in the development of Vietnam Owing to the abundance of natural resources, these Northeast provinces have developed such industries as mining or mineral processing industries Additionally, the favorable geographic conditions also support the development of agriculture and forestry sectors
(3) Red River Delta Red River Delta consists 11 provinces located in the South of the Northern area of the country, including Bac Ninh, Ha Nam, Ha Noi, Hai Duong, Hai Phong, Hung Yen,
Nam Đinh, Ninh Binh, Thai Binh, Vinh Phuc with the population of more than 19 million people This region is featured with many advantages for economic development including:
(i) Geographic advantages: the location of Hanoi as the economic, cultural and political center of Vietnam; and 6 centrally controlled municipal provinces with dynamic economy including Ha Noi, Hai Phong, Hai Duong, Hung Yen, Bac Ninh and Vinh Phuc;
(ii) Transportation advantages: a wide ranges of transportation infrastructure with good conditions and known as the gate of the whole country;
(iii) Natural resources: diversified ecology with abundant sources of natural resources
With these advantages, this region is recorded as the region with the second highest income region in Vietnam
North Central Coast is one of key economic regions in Vietnam which is adjacent to Red River Delta in the North of the country Such provinces in this region include Ha Tinh, Nghe An, Quang Binh, Quang Trị, Thanh Hoa, and Thua Thien Hue The income of these provinces depends on the mining and building material industry, livestock, perennial industrial crops and rice intensification
South Central Coast consists of 8 provinces which are located in the coastal central part of Vietnam, including Binh Dinh, Binh Thuan, Da Nang, Khanh Hoa, Ninh Thuan, Phu Yen, Quang Nam, and Quang Ngai These provinces are features as agriculture reliance provinces with the majority of income sourced from agriculture, forestry and fishery
In recent years, under the economic innovation, there is a significant change in the income source of this region with the increasing portion of income from tourism
Central Highlands, Tay Nguyen, consists of five mountainous inland provinces which are located at the South-central Vietnam, including Đac Lak, Đak Nong, Gia Lai, Kon Tum, and Lam Dong With the specific geographic and social features, this region is regarded as one of the most disadvantageous regions in Vietnam The major sources of income in these provinces consist of agriculture and forestry
There are six provinces in the Southeast in Vietnam, including Ba Ria–Vung Tau, Binh Duong, Binh Phuoc, Dong Nai, Ho Chi Minh City, and Tay Ninh This region is ranked at the first place with income level in Vietnam This region has led the country with exports, foreign direct investment, GDP, and other socio-economic sectors for years Such provinces as Dong Nai, Binh Duong and Ho Chi Minh City are provinces attracting a large amount of FDI, contributing to the development of industry and services of the region There are many manufacturing industrial zones in this area located in Binh Duong, Dong Nai and Ho Chi Minh City The income of this area is sourced from industry
Mekong River Delta which is located at the Southwest of Vietnam, contains 13 provinces, including An Giang, Ben Tre, Bac Lieu, Ca Mau, Can Tho, Dong Thap, Hau Giang, Kien Giang, Long An, Soc Trang, Tien Giang, Tra Vinh, and Vinh Long The strengths of this region consist of rice farming, fruit planting, and tourism
Besides the geographic characteristics, the provinces in each region are also featured by the targeted economic sectors which are regarded as the major sources of incomes
It is reported by GSO (2018) that the Total Factor Productivity (TFP) accounted for 43.50% of the national GDP growth This contribution has experienced an increasing trend since 2008 The average contribution of TFP to the GDP growth of Vietnam in the given period 2008-2016 is recorded at 33.58% which rose to 43.29% during the past three years 2016-2018 The labor productivity of Vietnam has also witnessed a significant increase from only US$1623 per worker in 2008 to US$3827 in 2016, reaching the peak of US$ 4512 per worker as the end of 2018 (GSO, 2018) The reasons attributed to the stable increase of labor productivity in Vietnam since 2008 include the added labor force and rising employment rate
Particularly, the efficiency of national economies is significantly boosted by the additional new productive capacities It is reported that there is a fall in the records of average incremental capital output ratio (ICOR) since 2008, decreasing from 6.2 during the given period 2008-2016 to 6.17 during the last three years
4.1.3 Production of agriculture, forestry and fishery
According to a report by the Ministry of Agriculture and Rural Development (MARD,
2018), despite the great transformation in the economy structure with the shift from agriculture to industry and service the agricultural sector has still maintained their important role to the national economic growth During 2008-2016, the report by GSO
(2018) reveals that GDP of the sector of agriculture, forestry and fishery experienced an average increase of 3.63% which expanded by 3.86% during 2016-2018 The trade of agriculture, forestry and fishery also witnessed an average surplus of US$8.72 billion during the given period 2008-2016, with the average exports of US$40.02 billion (Oxfam, 2018) The top goods of exports in this sector include wood, shrimp, fruits and vegetables, coffee and cashew nuts with the exports value from more than US$3.5 billion to US$8.8 billion
In term of the production structure, under the effects of market economy, there are significantly effective and positive changes in the sector of agriculture, forestry and fishery The development of new effective production models with the incorporation of innovative technologies has not only boosted the productivity but also quality of agricultural production The report by MARD (2016) reveals that over the period of 2008-2016 the crop productivity enjoyed a five-time increase
Descriptive statistics
This section represents the descriptive data which are analyzed with the use of different models such as OLS, SDM, SEM and SLM
Table 1 – 25 shows a comparison of Spatial regression models and OLS regression model concerning income in total and breakdowns in different sources such as agriculture, non-agriculture, wages, and other sources during 2008-2016
X1: Percentage of workers aged 15 and over who are working in a trained economy by province
X5: Number of farms X6: Sex ratio of population by provinces
X2: Immigration rate X3: Migration rate X4:The percentage of working population aged 15 and over working in the total population by province
X7: the number of FDI projects licensed
X8: Registered capital (mil USD) Lag X1, X2, X3, X4, X5, X6, X7, X8:
Spatially lagged variable of the observed variables
The results show that twenty four out of twenty-five have the Moran I‟s test is significant at 5% which means there is a necessity to use the spatial models to analyze the income sources among provinces And most of the regressions, SDM show the much more effectiveness than other models
Coefficients OLS SDM SEM SLM
Table 1: A comparison of Spatial regression models and OLS regression model (Year
2008, dependent variable: total income (Mill VND))
In the table 1, Moran I‟s test is significant at 5% so it is necessary to use spatial models and the AIC of SDM is the smallest so SDM is used for analyzing in this case
Source: Developed by the researcher lag x1 -1.8657E+01** lag x2 5.2421E-03 lag x3 6.5552E+00 lag x4 1.5363E+01* lag x5 3.5E-02*** lag x6 4.7212E+00 lag x7 1.3224E+00** lag x8 -1.9076E-03
The percentage of workers aged 15 and over in the trained economy, the immigration rate, the migration rate had positive impact on the total income
However the FDI Projects licensed had negative effect on the total income This could be explained by the economic crisis, the enterprises were affected, people‟s job transformed from agricultural to non – agricultural activities but it took quite a long time for them to equip necessary skills The authorities‟ acting to attract FDI projects affecting the domestic companies
The total income had negative effect on that of the observed province
The percentage of their trained labor force had competitive impact on the household‟s total income of the observed province The more percentage at the neighboring provinces, the less income in the observed unit Because they can attract and make a good deal with the companies
The percentage of working population aged 15 and over in the economy, the number of farms and the FDI licensed projects had negative effects on the total income of the observed unit This means the more untrained workers, especially working in agricultural sector, the more income people at the province observed got
Coefficients OLS SDM SEM SLM
-5.3487e-03* lag x1 7.0129E-01 lag x2 -7.7203E-01 lag x3 9.6291e+00 lag x4 3.4064E+00 lag x5 1.5439e-02** lag x6 5.7059E+00 lag x7 -2.8746E-02 lag x8 -1.0914e-02 *
Coefficients OLS SDM SEM SLM
Source: developed by the researcher
Table 2: A comparison of Spatial regression models and OLS regression model Year:
2008 Dependent variable: Income from Agric (million VND)
In this model, the Moran I test is significant at 5% The AIC of SLM is the smallest so SLM is used for analyzing
Rho is significant at 5% which means the income from Agric was affected positively by that at the neighboring provinces This indicates quite perfect market in the Agric sector which is a good sign
The more labor force in the trained economy and the more registered capital the less income from this source This could be explained that the trained labor force focused mainly on the non-farm business and the FDI projects were for manufacturing, services sector This is an unbalancing situation that can be solved by appropriate policies
The more rate of immigration, number of farms and number of men over 100 females the more income from this source Based on the interpretation above we can conclude that some of the immigrants were not in the trained labor force and the males contributed more on increasing income from Agric
Coefficients OLS SDM SEM SLM
X8 (Registered capital) 5.30E-03 4.9135E-03 4.8574E-03 0.0053402 lag x1 -7.1378E-01 lag x2 4.0635E+00 lag x3 1.0544E+00 lag x4 6.1940E+00 lag x5 1.8561e-02*** lag x6 9.2653e+00 lag x7 5.5782e-01* lag x8 -5.1885E-03
Coefficients OLS SDM SEM SLM
Source: Developed by the researcher
Table 3: A comparison of Spatial regression models and OLS regression model Year:
2008 Dependent variable: Income from Nonagric (million VND)
In the table 3, the Moran I test is significant at 5% and the AIC of SDM is the smallest, so this model is used for analyzing
The more number of trained labor force, the immigration rate and the migration rate the more income from this source The skilled labor mostly worked in the Nonagric sector which lies at the higher position than the previous one in the value chain reflecting higher income Comparing the two parameters of the variable immigration between Nonagric and Agric sector, we can see that most of the immigrants to provinces were white-collars The migrants seemed to be unskilled workers to their original provinces but better workers to provinces where they moved to, this reflects the different level gaps among provinces
The more number of farms and the number of licensed FDI projects the more income from this Nonagric at the observed province This indicates that the Agric sector was the foundation of the Nonagric sector and the licensed FDI mostly focused on the Nonagric activities
Coefficients OLS SDM SEM SLM
X8 (Registered capital) -2.9033E-03 9.3468E-04 -2.9033E-03 -5.5771E-04 lag x1 -1.0638e+01* lag x2 1.4922E+00 lag x3 5.0559E+00 lag x4 2.9238E+00 lag x5 1.3369e-02* lag x6 -1.3652E+00
Coefficients OLS SDM SEM SLM lag x7 5.7806e-01 (.) lag x8 5.0756E-03
Source: Developed by the researcher
Table 4: A comparison of Spatial regression models and OLS regression model ,Year:
2008 Dependent variable: Income from Wages (million VND)
In the table 4, the Moran I test is significant at 5% and the AIC of SDM is the smallest, so this model is used for analyzing
Rho is significant at 5% and has positive value which means the income from wages of the examining province was influenced in the same way by that of the neighboring provinces If considering the wage as a good then the non-farm business was quite a perfect market which is a good signal for the country
The more number of trained labor force, the immigration rate the more income from this source The majority of people who receive wages and immigrants were well trained This implies the different levels of people in different provinces
At the neighboring provinces, the more trained labor force in the neighboring provinces the less income from wages in the observed province This situation could be explained clearly by the fact that provinces that had many skilled workers attracted more investments The other factor also reflects this situation is the number of farms The more number of farms the more income from wages in the observed province
Coefficients OLS SDM SEM SLM
Source: Developed by the researcher
Table 5: A comparison of Spatial regression models and OLS regression model Year:
2008 Dependent variable: Income from Other sources (million VND)
The Moran I test is not significant at 5% so spatial models are not used OLS is used
The income from other sources was affected positively by the trained labor force, the immigration rate, migration rate and affected negatively by the sex ratio This indicates that the more education they had, the more income from other sources they got
Coefficients OLS SDM SEM SLM
3.36E-02 5.0003e-02* 8.1177e-02*** 2.0245E-02 lag x1 -3.4288e+01*** lag x2 -6.8089E+00 lag x3 -4.0014E+00 lag x4 -3.2590E+00 lag x5 1.1792E-02
Coefficients OLS SDM SEM SLM lag x6 -8.8032E+00 lag x7 2.7635e+00*** lag x8 -1.5747e-01**
Source: Developed by the researcher
Table 6: A comparison of Spatial regression models and OLS regression model Year:
2010 Dependent variable: Total income (million VND)
The Moran I test is significant at 5% and the AIC of SDM is the smallest so SDM is used for analyzing
Rho is significant at 5% and has the positive value which means the total income of the observed province was affected positively by that of the neighboring provinces
The trained labor force, the immigration rate, the number of farms and the registered capital had positive effect on the total income
Changes in income sources in Vietnam 2008-2016
Figure 1 demonstrates the total income of Vietnam from 2008 to 2016
Figure 1: The changing rate of total income between 2008 and 2016
Figure 1 reveals that the provinces in Red River Delta and Southeast regions are those with the highest levels of income while the Northwest and North Central Coasts provinces are recorded with the lowest levels of income This income pattern is similar from 2008-2016
Figure 2 shows the changing rate of income from wages between 2008 and 2016
Figure 2: The changing rate of income from wages between 2008 and 2016
Provinces with darker color in Red River Delta and Northeast regions represent the larger changing rate of income from wages These provinces have the same common things such as being attractive to FDI, having good policies for development and the rate of urbanization is fast
The changing rate of income from Agriculture, Forestry, fishery between 2008 and
Figure 3: The changing rate of income from Agriculture, Forestry, Fishery between
Some provinces in the North (Hanoi, Hai Phong), North Central (Ha Tinh, Quang Binh), South Central Coast (Binh Dinh, Phu Yen, Khanh Hoa, Daklak), South East, Mekong deltal river experience the high changing of income in term of agriculture, fishery and forestry The common thing of these provinces is that they are located next to the beach, some of them are concentrated along the two largest plains of the country (Red river and Mekong Delta river) which provide them great nature (the weather, soil, etc), some of them apply the advanced technology such as Soc Trang province
Figure 4 shows the changing rate of income from Non-Agriculture, Non-Forestry, Non- fishery between 2008 and 2016
Figure 4: The changing rate of income from Non-Agriculture, Non-Forestry, Non- fishery between 2008 and 2016 Provinces from North-west, North center and South-east of Viet Nam experience a high changing rate of income from non –agriculture, non-fishery, non-forestry
The common thing among these provinces is that they are concentrated quite near the two largest plains, and thus, they can focus on the activities which do not directly create products from agriculture, fishery and forestry
Lastly, Figure 5 demonstrates the changing rate of income from other sources between
Figure 5: The changing rate of income from other sources between 2008 and 2016 Other income is classified as income from gifts, savings, etc The rate of changing income from others is larger at poor provinces.
Discussions
There was a transition in income sources at the provincial level during the given period in this current study Firstly, it is proven that there is in comparison to income sourced from non-agricultural activities, income from agricultural activities tend to significantly shrank during 2008-2016 With reference to the four income categories including agriculture, non-agriculture, wages and others, the income generated from wages is ranked with the highest proportion which is followed by non-agriculture, agriculture and other sectors It is calculated that the contribution of wages to the total income in Vietnam has drastically increased from less than 31% in 2008 to 46% in
2016 Despite the rapid and significant increase in the proportion of income sourced from wages, this portion is relatively smaller than that of those countries in the same group The report by ILO (2016) on the global wages shows that in developing countries more than 60% of the national income is attributed to wages and salary
Owing to FID investments into such provinces as Hanoi, Bac Ninh, Quang Ninh, Vinh Phuc, Dong Nai, Binh Duong, and Ho Chi Minh City, many people are employed by manufacturing firms in the industrial zones in these provinces The employment from these industrial zones has boosted the income amount generated from wages and salary Other provinces also enjoyed a small increase in the income sourced from wages and salaries
Following wages and salary, incomes sources from non-agriculture sectors such as manufacturing or real estates are the second largest source for the total income in Vietnam During 2008 and 2016, incomes from non-agriculture activities accounted for more than 20% of the total income In contrast, incomes from other sources has experienced a downward trend during the given period The contributing portion of this sector decreased from 19% to 12% during 2008-2016 These findings regarding the sources of income in Vietnam during the period indicate that there is a shift in the income structure of Vietnam from a heavily agricultural reliance country to a less agricultural reliance country It is also realized that such centrally controlled municipal provinces as Hanoi, Ho Chi Minh City, Quang Ninh, Hai Phong, etc present an upward trend in the income amount sourced from non-agriculture sectors such as manufacturing or services while such provinces as Da Nang, Khanh Hoa, Quang Ninh, Kien Giang, Phu Yen, etc have shifted their income structure from agriculture reliance to tourism and service reliance
Changes in income structure vary across provinces There is a significant fall in the amount of income generated from agriculture activities in such high-income provinces as Red Delta River and Southeast provinces in Vietnam Contrastively, the poor provinces still present a heavy reliance on agricultural activities for income generation
In other words, the incomes sourced from wages and salaries, non-agriculture activities and other sectors account for the smaller portions in the income structure In the provincial level, while such provinces in Red River Delta as Ninh Binh, Thai Binh, Hai Duong have decreased their income dependence on agriculture sector (from 43.6% in
2008 to 18.9% in 2016) other provinces as An Giang, Ca Mau, Dong Thap, Long An, Soc Trang, Tien Giang, Tra Vinh, and Vinh Long still maintain the significant contribution of agriculture to the total provincial income
In summary, there is a rapid and constant increase in the contribution of incomes generated by wages in all provinces in Vietnam Despite the faster growth rate in the incomes by wages in poorer provinces of Vietnam, the contribution of wages to the total income in these provinces is still much lower than that of rich provinces
Additionally, although the declining contribution to the provincial and national income, agriculture has still maintained their important role in income generation of all provinces in Vietnam
The analysis indicates the following findings: i The total income of one province has spatial correlation by that of the neighboring provinces The total income is mostly affected positively by the trained labor force, the immigration, the farms And the trained labor force has competitive effect among provinces due to the negative value of parameter of the variable spatially lagged percentage of workers aged 15 and over who are working in a trained economy by provinces The more man over 100 females, working labor force, immigration rate of the neighboring provinces, the less total income in the observed province From 2008 –
2010, the more FDI projects licensed in neighboring provinces the more total income in the observed province ii Income from wages of one province has positive spatial correlation by that of the neighboring provinces The trained labor force and the immigration rate play an important role and have competitive effect among provinces The number of farms of the neighboring provinces have positive effect on the observed unit From 2008 to
2010 the FDI projects has positive effects among provinces but later in 2014 it has competitive effect (when the market is more stable than the crisis time) iii Income from Agriculture, Forestry, Fishery activities: in the crisis period 2008 to 2010, this variable is affected by that of neighboring province (when people focused more on agriculture) The trained labor force plays negative role for this variable but the variables number of farms, sex ration have direct effect From the year 2012, there is spatial correlation of farms among provinces (sharing knowledge, creating jobs serving farming, etc) The more immigration rate in the neighboring provinces the more income from Agricultura (because there will be more land for farming) iv Income from Non-Agriculture, Non-Forestry, Non-Fishery activities is basically affected by that of neighboring provinces in the year 2010 – 2012 The trained and the immigration rate still play an important role and have competitive effect The number of man as well as the number of farms have directly negative effect v Income from other sources: the more trained labor force, registered capital, FDI projects licensed (has positive spatial effect) The more income from other sources
The more man over 100 females (including from neighboring provinces) and working labor force the less income from other sources.
CONCLUSION AND RECOMMENATIONS
Conclusion
The investigation into the income in Vietnam during 2008-2016 indicates that in this period Vietnam has experienced a significant improvement in the average level of income per capital, contributing to the progress of reduction poverty of the country
Despite the improvement, there is an inherent problem raising the concerns of the policymakers due to their impacts which is the income disparity The research by Kozel (2014) indicates that there is hardly any improvement in income inequality in Vietnam for the ten-year period This income disparity mainly results from the less diversity of income sources and the distribution of income across the provinces in Vietnam Consequently, the challenge to diversify the sources of income been becoming an important issue for researchers and policymakers
This study uses the spatial analysis method to investigate the current situation of income sources among provinces in Vietnam; and to explore the influencing factors as economic and demographic variables affect the income sources among provinces in Viet Nam during the given period of 2008-2016
The analysis indicates the following findings:
(i) Over the period of study, there are some significant changes in the structure of income in provinces across Vietnam There is a sharp rise in the contribution of income generated by wages to the total income in all provinces in Vietnam This source of income accounts for nearly a half of the total income in the provinces with high income in such areas as Southeast and Red River Delta regions and 40% for other provinces
However, the provinces with lower total income experienced a faster growth rate than their counterparts, richer provinces
(ii) Among all the four sources of income, the sector of non-agriculture is ranked as the second largest source of income for rich provinces in Vietnam Contrastively, this source only represents about 14% of the total income generated in poorer provinces
The portion of income generated from agricultural cultivation is much higher than incomes from other sources in the poorer provinces In such rich provinces, the portion of income generated from agricultural activities has experienced a stable and constant decrease during the given period
(iii) The expanding income generated by wages and salary has increasingly expanded the income disparity in Vietnam during 2008- 2016 However, there is an increasingly even distribution in wages generated from wages because of the increasing amount of wages in the households with the low income levels
(iv) Incomes by wages and non-agriculture sectors are the major and powerful drivers to the changes in the total in the provinces in Vietnam Although the share of agricultural activities to the total income of both groups of provinces has decreased, however, these sources of income are also the important contribution to the income disparity in Vietnamese provinces While in the rich provinces incomes from wages account for the larger portion, it is contrastive with the poorer counterparts with the large contribution of agricultural activities
It is realized that although the decreasing contribution of agricultural activities to the total income the promotion measures to this sector also boost the income for those with the lowest levels of income distribution, contributing to the shrinking income gap among the provinces in Vietnam The reason is that although the income generated from the agricultural sector takes the role as the source of income disparity in Vietnam, agricultural activities are the major sources for the poorer households in Vietnam
According to Tuyen (2015), although there are arguments regarding the effectiveness of increase in agricultural income to income disparity reduction, the research findings support that the income sourced from the improvement in agricultural productivity can significantly improve the income levels of households in poor provinces in Vietnam
It is also recommended that in order to facilitate the shift in the income structure of Vietnam from agriculture reliance to non-agriculture reliance economy, the Vietnamese Government should develop the policies to enhance the industries and service sectors in Vietnam These policies can improve the income sources from wages and other sources in both rich and poor provinces in Vietnam
The Government should issue social protection policies to the citizens especially to the working people In order to do this, the Government should
(i) Provide information and encourage workers to notice on any measures taken or envisaged related to wages among the working people as well as the officials so that they can raise their awareness of the 2012 Labor Code‟s provisions;
(ii) Apply necessary solutions to enforce Article 91 of the Labor Code 2012 so that the minimum wage as well as the minimum living standards of workers and their families are assured;
(iii) Make sure all companies to pay increased wages in line with government legislation, to encourage worker representation in decision making, and to build freedom in company policy;
(iv) Commit to promote accountability of trade unions and Corporate Social Responsibility (CSR).
Limitations
It is acknowledged by the researcher that there are some limitations inherent in the current study There are some measurement errors presented in the calculations of incomes sourced from agriculture incomes or self-employment incomes (McCaig et al.,
2015) which leads to the concerns of research validity and reliability The CPI deflators by space could be used instead of CIP yearly This limitation is significantly meaningful because in this current research income from these sources presents a high portion of the national and provincial income The measurement errors can potentially devalue the effects of other sources in this study Moreover, the given period of study is only conducted with the data during 2008-2016 due to the limited access to the data in the most recent year 2017 and 2018 It can devalue the significance and contributions of this current study.
Suggestions for the further studies
It is identified that sources of income are of the most powerful influencing factors for income inequality in Vietnam This current study has looked into the distribution of income sources at the provincial level in Vietnam However, the influencing factors to income sources and distribution are not thoroughly investigated Therefore, it is recommended that the scholars can explore and evaluate more other factors which influence mostly the sources of income in Vietnam and to which extent these factors impact the sources and distribution of income Additionally, the sources of income in poorer provinces can also be a topic of interest in research Lastly, it is suggested that the further studies should investigate the impacts of sources of income on poverty and income inequality in Vietnam
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