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Summary of PhD thesis in Economics: Analysis of inclusion in Vietnam economic growth during the period 2004-2016

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The overarching analytical thesis in economic growth in Vietnam; impacts of a number of factors on income inclusion in Vietnam in the period of 2004-2016; proposing some measures to improve the inclusion of income in Vietnam.

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INTRODUCTION

1 Necessity of research:

In the past few decades, the world has witnessed the increasing trend of

inequality in many countries Even though there are many recorded achievements in

terms of growth speed, poverty reduction, improved access to education, healthcare and

social security, few countries can neither ensure the benefits of growth are distributed

in an equal way nor guarantee the equal participation of people in the growth process

In many years, the correlated relationships among economic growth, poverty and the

increase in inequality has become the subject of concern and debate among researchers,

scholars and policymakers around the world

Significant economic growth is a crucial explanation for poverty reduction, but the

reality shows that this growth does not necessarily improve the general living standards of

everyone If the benefits of growth only served the minority of people in the society, it

would not be considered inclusive growth (Tirmazee and Haroon, 2015) Hausman and

Gavin (1996) stated that developing countries had an unequal distribution of income and

often recorded low inclusive growth This situation had been explained by many reasons

(Bigsten, 1983), and their governments always considered improving the inclusion of

economic growth as one of the top priority goals in their development policies Felipe

(2012) and Afzal (2007) agreed with the view that inclusive growth was the growth

achieved at the expense of reduced personal interests In other words, it promoted the

distribution of benefit coordination among all members of the society In some developed

countries, the inclusive growth goal has been achieved since the 1970s, but for developing

countries because high economic growth comes with great inequality, it is still the target of

growth to be achieved (Todaro, 1994)

Vietnam, like many other developing countries, has experienced substantial

changes and fluctuations of the economy in recent years Issues such as poverty, human

development, and inequality are issues of great concern In particular, growth and

income distribution have always been the hot topic of many studies, from the fact that

many developing countries have achieved impressive results in poverty reduction but

they could not solve the problem of reducing income inequality, meanwhile the trend

of inequality has even become wider Among those aspects of the new growth

perspective, the content of inclusive growth in income needs to be stressed, because of

the fact that in many countries, income growth goes hand in hand with income

inequality (Piketty, 2014) Many East Asian countries have reached miraculous

achievements in growth and distribution, but suffered from decline in equitable income

distribution (Zhuang, Kanbur and Lee, 2014; Jain-Chandra and et al., 2016)

2

Based on these facts, inclusive growth in income with both analysis of income growth and income distribution is the issue that needs deeper research Therefore, the

thesis focused on the topic: "Analysis of inclusion in Vietnam economic growth during the period 2004-2016", with the desire to contribute more research on this topic

with the context of Vietnam

2 Research purposes

2.1 General objectives:

Analyze the inclusion of economic growth in Vietnam through several dimensions during the period 2004 – 2016

Analyze the impact of several factors on income inclusiveness in Vietnam during the period 2004 – 2016

Propose some solutions to improve the income inclusiveness in Vietnam

2.2 Specific objectives:

theoretical basis of inclusive growth and the impact of related factors on this growth, with the focus on inclusive growth of income, (ii) measuring and analyzing inclusion of income and some non-income aspects of Vietnam during period 2004-2016, (iii) assessing the effect of related factors on inclusion of income Vietnam from 2004 to

2016, and (iv) suggesting some policies for Vietnam based on empirical results

3 Research Questions

The thesis focuses on answering the following research questions:

What is the situation of income growth and distribution in Vietnam during 2004 - 2016?

How is the inclusion of income and some non-income aspects in Vietnam? Which factors influence the inclusive growth of income in Vietnam?

Which policies are necessary to improve inclusive situation of income in Vietnam?

4 Research Subject and Research Scope

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Research subjects: Inclusive growth or the integrated concept between growth

and distribution of dimensions in Vietnam’s economic growth

Research scope

Scope of content: Among the aspects / indicators of inclusive growth, this study

focused on evaluating the income aspect

Scope of timing: In the period 2004-2016

Scope of space:

The analysis of inclusive growth situation in this study was carried out all over

Vietnam, including urban, rural areas and ethinicity, and some aspects were done in

specific provinces and cities in Vietnam The panel data regression conducted in this

research for quantitative analysis model was based on provinces and cities scope

5 Research methods

The thesis used two main research methods:

Household Living Standards Survey (VHLSS), General Statistic Officer (GSO) and

other sources, the research measured the inclusive growth index of income and some

other non-income aspects in Vietnam This index was calculated for the whole country,

including urban - rural areas and ethnicity Only two indicators namely income and

education level were calculated with the scope of provinces and cities in Vietnam during

2004-2016 The social opportunity function method of Ali and Son (2007) was applied

in this study with non-monetary indicators and was developed for income indicators

with the social mobility function by Anand et al (2013) (Specific information of the

method would be presented in the main content of the thesis)

Quantitative research method

- The research made an estimate about impact of factors on inclusive growth of

income in Vietnam Data used in the study are from the Vietnam Household Living

Standards Survey (VHLSS) from 2004 to 2016 and secondary data were collected from

other sources VHLSS data was collected every two years and in even years, namely

2004, 2006, 2008, 2010, 2012, 2014 and 2016 (Because this survey was only conducted

in even years in research phase) Other data were taken by year from sources such as

General Statistics Office, Provincial Statistical Offices, Ministry of Finance, Provincial

Department of Finance and Vietnam Chamber of Commerce and Industry (VCCI)

4

- The estimation methods used in the thesis include: The study applied Panel data regression model based on fixed estimation and random estimation methods, and performed tests to select appropriate models In addition, to test whether spatial correlation exists among provinces and cities, Panel data regression model with spatial factors was also conducted besides necessary tests to choose which spatial model is the most suitable

6 Research structure

Besides introduction, references and appendices parts, the structure of the thesis comprises of 4 chapters, as follows:

Chapter 1: Theoretical framework of inclusive growth

Chapter 2: Research overview of inclusive growth

Chapter 3: The situation of inclusive growth in Vietnam during 2004-2016

Chapter 4: Impact estimation of factors on inclusive growth in income in

Vietnam during 2004-2016

Chapter 5: Policy recommendations

CHAPTER 1 THEORETICAL FRAMEWORK OF INCLUSIVE GROWTH

1.1 Concepts and research content of inclusive growth

1.1.1 Some concepts of inclusive growth

Acemoglu, Robinson and Johnson (2004) are the first group of authors who introduced this growth concept They argued that the reason many countries have high and sustainable growth was they had harmonious political and economic systems, in which the achievements and benefits from economic growth were fairly equitably allocated among regions, economic sectors and social groups In contrast, in countries with no growth or less sustainable growth, the reason originated inharmonious political system

Afterwards, major international organizations such as the Asian Development Bank (ADB), the World Bank (WB), the Europe 2020 Strategy, the Organization for Economic Co-operation and Development (OECD), the United Nations Development Program (UNDP) and the World Economic Forum (WEF) also presented concepts of inclusive growth The main contents in the inclusive growth concepts of the aforementioned organizations are: Inclusive growth is multi-dimensional growth,

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associated with equality of opportunities, which are created for everyone, not any

specific person The two inseparable components of inclusive growth are pace and

pattern of indicators/aspects of economic growth The common feature in most

international organizations’ concepts of inclusive growth is that it refers to both income

and non-income aspects, as well as the process and outcome of growth The process here

indicates all opportunities in the economy that individuals, irrespective of their

circumstances and status, can get access to, while the outcome of growth means the

equal distribution of growth results to everyone - leave no one behind

In addition to international organizations, there are also a number of independent

authors giving the concept of inclusive growth

Based on different views of concepts of inclusive growth by international

organizations and independent authors, in this thesis, inclusive growth is considered as

a narrow meaning in which economic growth must go hand in hand with social equality

(poverty reduction and inequality contraction), enhancing residents’ competents through

improving access to education, health and other basic living conditions

1.1.2 The pillars (content) of inclusive growth

The research conducted by Asian Development Bank (ADB) looked into

inclusive growth under five perspectives: (i) income poverty, multidimensional poverty

and inequality, (ii) creation of opportunities, (iii) access to opportunities, ( iv) social

safety nets, and (v) institutions and governance

The African Development Bank (AfDB) study focused on five aspects of

inclusive growth namely: economics, politics, society, environment and space Among

them, economics and society are the two most crucial fields Specifically, economic

refers to growth and employment while society is a combination of factors such as

health, education, social safety nets and gender

The World Economic Forum (2015) suggested inclusive growth to be analyzed with

seven contents: Education and skills development, Employment and labor compensation,

Asset building and entrepreneurship, Financial intermediation of real economy investment,

Corruption and rents, Basic services and infrastructure, Fiscal transfer These were also the

seven principal pillars of inclusive growth analysis given in the study of Sammans et al

(2015)

There were several other studies focused on analyzing the income and labor pillars

of inclusive growth In this group, there were studies by Anand et al (2013) and Hann and

Thorat (2013) looking at the aspect of income in inclusive growth Meanwhile, Hausman,

6 Rodrik and Velasco (2005), Ramos et al (2013) all conducted study about employment, labor and income

However, since inclusive growth is a multidimensional concept, the pillars (main content) in previous research about this topic are also very diverse From literature review

of empirical studies, it is possible to summarize some of the key areas of growth including: (i) economic growth, (ii) poverty and inequality, (iii) employment, (iv) education, healthcare and demographic issues, (v) environment, (vi) gender / gender inequality, (vi) space, (vii) social safety nets and (viii) infrastructure

1.2 Inclusive growth measurement methods

1.2.1 Concentration curve and concentration index method

The concentration curve was developed by Kakwani (1977) based on the cumulative percentage of the measurement variable (vertical axis) compared to the cumulative percentage of the population (horizontal axis), households are arranged in ascending order in average income, beginning with the lowest and ending with the highest income per capita households The concentration curve showed the cumulative percentage of measurement variables taken by the percentage of households with lowest income per capita

From the concentration curve, Kakwani (1977) calculated the concentration index to measure the level of socioeconomic inequality The concentration index can be stated as follows:

In which is the measure of inequality, µ is its mean, and = is the ranking order of the household in its distributionbased on the average income, with i = 1 for households with the lowest average income, and i = N for households with the highest average income

1.2.2 Social opportunity function method

The social opportunity function method, first developed by Ali and Son (2007), applied to non-monetary indicators Afterwards, Anand et al (2013) developed this idea for monetary indicators into the social mobility curve method

The measurement method of inclusive growth reflects the increase in the social opportunity function, depending on two factors: (i) the average opportunity created; (ii) and how to allocate opportunities among households in the economy Households with average income increase, and ȳp is the average opportunity taken by p percent of the lowest-income

(Kakwani, 1977, 1980) (1)

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7 households (in which p fluctuates between 0 and 100 and ȳ is the average opportunity

available for the population), then ȳ will be equal to ȳ when p equals 100 (that means

including the whole population) Because ȳ varies with p, we can draw a curve for each

value of p This is the curve that focuses overall opportunity when households are arranged

in ascending order in average income The index represents the area below the opportunity

curve, and is expressed mathematically as follows:

ȳ*= ȳ ȳ* is opportunity index (2)

To consider the issue of equality in opportunity distribution, we can develop and

calculate the Equality of Opportunity Index (EOI) index as follows:

With the same principle, Anand et al developed the social opportunity function

method to calculate the social mobility index for income criteria (also called the social

mobility function method)

1.2.3 The composite index method

The composite index method is a method of calculating inclusive development

index based on the indices of individual indicators and assigning weights to those

indicators The aggregate index is built on a scale of 0 to 10, according to the degree of

achievement of each country in each of these measurement dimensions with criteria

The higher the score is, the greater the inclusion that country had in that component

indicator

1.3 Theoretical foundation for inclusive growth determinants

1.3.1 Theoretical foundation of growth determinants

Some of the theories of growth mentioned in this section are classical theories of

Adam Smith (1776), David Ricardo and Karl Marx; theories of Keynesianism, including

Harrod-Domar theory which focused on the role of capital in economic growth;

Neoclassical theories, represented by the Slow Swan theory (1956) stated that, besides

capital, labor and technology also affected growth Finally, there are endogenous growth

model in Arrow and Romer theory with emphasis on human capital’s effect on a nation's

economic growth In addition, the role of population growth was also mentioned in a

variety of theories, including Thomas Malthus's population theory explaining the impact

of the population on income per capita

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1.3.2 Theoretical foundation for the determinants of income inequality or income distribution

Factors affecting income inequality are usually divided into 5 groups, namely: economic development, demographics, politics, culture and environment, and macroeconomic factors Each group consists of different representative elements So far,

a number of studies have chosen to analyze the one or some of these factors

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9 with income inequality However, the findings of those studies revealed different impacts

of differenr factors on income inequality The relationship is either positive or negative,

while many factors did not show clear impact on income inequality Among those

aforementioned factors, consistent results from past research were shown in: positive

effects of technological progress, inequality in education and foreign investment on

income inequality Meanwhile, financial development level affected income inequality

negatively Additionally, some factors were researched by many scholars, although the

impact might be heterogeneous, including GDP per capita, economic restructuring,

education levels and spending, inflation, and unemployment

CHAPTER 2

RESEARCH OVERVIEW OF INCLUSIVE GROWTH

2.1 Foreign research

2.1.1 Research conducted for multi-country sample

The full version of the thesis includes an overview of studies in which the

dependent variable reflects inclusive growth in income, income per capita and income

inequality measurement However, this summary only focuses on research with

inclusive growth in income as dependent variable conducted for multi-country sample

Specifically, studies in this group included research by Anand et al (2013), Jalles

and Mello (2019), Doumbia (2018), Javed et al (2018), Aoyagi and Ganelli (2015), Sen

(2014), Ravi et al (2013) Although all of them focused mostly on the income aspect of

inclusive growth, these studies still varied widely in the selection of measurement

variables for dependent and independent variables The main independent variables used

were: GDP per capita, inflation, human development indicators such as education and

healthcare, institutions and governance, investment, trade openness and government

spending

2.1.2 Research conducted within one country

There was some research conducted in one nation with inclusive growth of

income as the dependent variable, such as:

Studies of Arabiyat et al (2019), Munir et al (2018), Khan et al (2016), Pukuh

and Widyasthika (2017), Oluseye and Gabriel (2017) The common point of these

studies is that the dependent variable - inclusive growth of income was measured by the

social mobility curve as proposed in Anand et al (2013) The independent variables

mostly used in these studies were: GDP per capita, inflation, population growth,

government spending, trade openness, and money supply growth

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2.1.3 Other research on inclusive growth

Besides inclusive growth studies using quantitative analysis, there were some other studies also investigated this topic but only stopped at analyzing the situation of growth on one or some aspects The number of these studies is much higher than the quantitative analysis research Some following studies can be stated as example: Yuwa (2014), Schmid (2014), Habito (2009), Ganesh and Ravi (2009), Osmani (2008), Fernando (2008), Norman et al (2007), Afzal ( 2007), Afzal and Jazhong (2007), Afzal and Xianbin (2004) and Bolt (2004) The main content analyzed in these researches was: economic growth, poverty, employment, institutions and infrastructure

2.2 Domestic research

Inclusive growth is a relatively new concept in Vietnam, so there has not much research done on this topic Some studies in this group include: Le Kim Sa (2014), Pham Minh Thai and Vu Thi Minh Ngoc (2014), Nguyen Duc Thanh and Pham Van Dai (2014), Do Son Tung and Ma Ngoc Nga (2014), Le Kim Sa (2008) The content of inclusive growth studies in Vietnam mainly analyzed the labor market of one or several enterprises in a certain industry, thereby made policy recommendations to improve the inclusion for that market

Based on the overview of overseas empirical studies, together with domestic research analyzing inclusive growth, the thesis found a big gap of inclusive growth in income, especially from household perspectives Furthermore, no studies in Vietnam have conducted quantitative analysis to investigate the impact of factors on inclusive growth in income in Vietnam

2.3 Research framework

The thesis was conducted by following several steps: (i) identifying research objectives, (ii) reviewing the research materials, (iii) developing analytical framework, (iv) collecting, analyzing and processing data, (v) doing research findings and (vi) making policy recommendations

Regarding the content of inclusive growth, this study analyzed six main groups: (i) economic growth, (ii) poverty and inequality, (iii) employment, (iv) education and health care, (v) space and (vi) infrastructure Within each group, one or more indicators would selected for analysis

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11 Regarding quantitative analysis, the thesis developed analytical framework as

follows:

Figure 1: Quantitative analysis framework of the research

CHAPTER 3 THE SITUATION OF INCLUSIVE GROWTH IN VIETNAM

DURING THE 2004-2016 PERIOD

3.1 Situation of inclusive growth of income

3.1.1 Situation of economic growth and income distribution

In general, Vietnam's economic growth in the past three decades since the

Renovation implementation has achieved great results As a result, the proportion of

poor households has decreased significantly, GDP per capita increased (In average,

Vietnam's income per capita for the whole period 2004-2016 doubled, based on

purchasing power parity in 2011) Vietnam has been one of the countries with high

economic growth rate in the region In addition, the economic structure was also shifting

in line with the trend of developing economies towards increasing the proportion of

industry and services, reducing the proportion of agriculture

Income inclusive growth Human

resources

Labor quality Education level

Years of schooling Healthcare

Macro factors

Inflation

Crisis

GRDP

FDI

Institutions and policies

Ratio of trained labor to total labor

Provincial Competitiveness Index Budget spending

12 However, while the poverty rate dropped, fluctuations recorded in the distribution

of the poor across the country The majority of poor people came from rural areas Whereas, if based on regional criteria, most poor people originated from the Midlands and Northern Mountains (in 2010 and 2016)

Some indicators reflecting the income inequality used were Gini, income between 20% of the richest population and 20% of the poorest population in the country, based on urban-rural areas and ethnicity showed different fluctuations Considering both criteria, inequality in urban areas reduced and recorded more volatile than in rural areas, ethnic minorities group (including Hoa and non-Kinh people) also followed the same pattern compared to Kinh people The average growth rate of income in both urban and rural areas decreased more in the last years of the study period, this rate was highest in the period 2010-2012 in all six geographical regions The proportion of income in industry and services was still small, wages and salaries constituted the largest part in urban areas’ income, while in rural areas income mainly came from agricultural activities

3.1.2 Inclusive growth of income in Vietnam

Inclusive growth of income improved over all years throughout the study period, regardless of the scope of analysis However, this improvement was mainly explained

by the improvement in average income, which did not come from more equal income distribution 2010 was the year witnessing the most unequal household income distribution in Vietnam, while the most equal distribution time was 2006 In terms of provinces and cities, there were also some notable changes coming from all three indicators: income growth, equality growth and inclusive growth

3.2 The inclusive growth situation of some non-income indicators

3.2.1 Education, healthcare, labor and employment

Education: The thesis analyzed the rate of joining school at the right age in all educational levels, by urban-rural area and by sex; and the highest number of schooling years of the member with the longest study time in the household to calculate the opportunity index The results indicated that the rate of joining school at the right age was lower with the higher levels of education, this rate in urban areas was higher than

in rural areas, and also the rate recorded in females was higher than males Regarding the criteria of the longest time of schooling (by year), the equality was higher in urban areas than in rural areas and the same pattern shown among Kinh people compared to other ethnic groups

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13 However, in all criteria, the opportunity index reflecting the inclusion of access

to educational opportunities (measured by years of schooling) improved

Healthcare: Opportunity of accessing to healthcare was analyzed through access

to health insurance and free health checks for citizens Considering this opportunity, in

all criteria, inclusion increased over the years, except for the period 2006-2008

Labor and employment: The labor force participation rate and the percentage of

trained workers were higher in both males and females

3.2.2 Some other non-income indicators

In this section, the study investigated the ability to access social security through

the social insurance access rate in 5 income groups and access to basic living conditions

such as electricity, water and sanitation The rate of social insurance coverage decreased

gradually according to 5 income groups, with large disparities among groups In each

group, this rate reduced during 2006-2010, but improved over the rest of the time In

addition, regarding inclusion of the three basic types of access, the opportunity to access

electrical grid was highest, followed by sanitation and finally tap water

3.3 Some constraints to inclusive growth in Vietnam

Despite many achievements in growth and poverty reduction, inclusive growth

in Vietnam has been facing many challenges and limitations One of them can be stated

such as (i) uneven growth, (ii) low employment and labor productivity, (iii) large gaps

in asset holdings and access to opportunities in life

CHAPTER 4

ESTIMATION OF FACTORS AFFECTING INCOME INCLUSIVE

GROWTH IN VIETNAM

4.1 Model specification

4.1.1 Model building

The thesis built an econometric model to analyze the impact of factors on

inclusive growth of income for provinces and cities of Vietnam as follows:

4.1.2 Estimation method

The thesis applied the Panel data regression estimation method: conducted with

fixed / random effects estimator and spatial estimator

14 Using Hausman test, the research chooses between two fixed and random effects models

The spatial estimation method was used when there was suspicion of the spatial relationship among entities According to Le Gallo et al (2003), in measuring economic relationships, ignoring spatial correlation may lead to biased and unreliable estimates This was also the spatial autocorrelation shown in several studies such as Paraguas and Kami (2005) or Higazi et al (2013)

The thesis created the spatial matrix according to distance and conducted necessary tests to select the appropriate spatial model After finishing the tests, the selected spatial model was the Spatial Autoregressive Model with Auto Regressive disturbances In addition, the construction of different matrix types also tested the robustness check of the model The results indicated that there was not much difference when selecting different types of matrices to make estimates In other words, the robustness of the model was confirmed

4.2 Data sources, data descriptions and variables used in the estimation model

4.2.1 Data sources

4.2.1.1 Characteristic of provincial data

According to the government decision, from the beginning of August 2018, all

Ha Tay, Me Linh district of Vinh Phuc province, and 4 communes of Luong Son district, Hoa Binh province were merged into Hanoi Therefore, for data consistency, all data of

Me Linh district in Vinh Phuc province and data of 4 communes in Hoa Binh province before 2010 was be calculated as Hanoi data

The dependent variable is the inclusive growth of income, which was calculated

as the social mobility index according to the social mobility function method of Anand

et al (2013), using data of average household income in VHLSS

Independent variable: The data for the independent variable used the secondary data source from the General Statistics Office, the Statistical Office of provinces, the Ministry of Finance, the provincial Department of Finance, and Vietnam Chamber of Commerce and Industry (VCCI) Only the inclusion index of education as independent variable was calculated from the data in VHLSS by using of the social opportunity function method of Ali and Son (2007)

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15 All independent variables in the model were: GRDP per capita in the first period,

inflation, dummy variable (shown for crisis factor), the ratio of investment to GRDP,

Foreign Direct Investment (FDI), the ratio of trained labor to total labor, the inclusion

index of education, the human resources for health per capita, the provincial

competitiveness index (PCI), and local budget expenditures

4.2.2.2 Expected sign of the variables

Based on the overview of past research in chapter 2, the signs of variables were

expected as follows:

Variables with positive expectation: GRDP per capita in the first period, the ratio

of investment to GRDP, the ratio of trained labor to total labor, the inclusion index of

education, the provincial competitiveness index (PCI), the human resources for health

per capita

Variables with negative expectation: Inflation

Variables with unclear expectation: The dummy variable for crisis, local budget

expenditures, Foreign Direct Investment (FDI)

4.3 Model results

4.3.1.1 Descriptive statistics and correlation matrix among variables

The table showing descriptive statistics and correlation among variables was

presented in the full text of the thesis

4.3.2 Estimating the fixed and random effect model

The Hausman test results showed that the value Prob> chi2 = 0.0000, therefore

the fixed effects estimation model was selected

The specific estimation results were as follows

Table 1: Test results of FE model and RE model without space factor

VARIABLES

(1)

FE

(2)

RE

lgdppop2004 0.29*** 0.32***

(0.07) (0.04)

(0.14) (0.12)

(0.04) (0.03)

16

(0.01) (0.01)

lchins

ledu

labor_tyle

lyte2

Constant

(0.08) 0.06***

(0.01) 0.32***

(0.10) 1.36***

(0.24) -0.05**

(0.02) -1.32***

(0.40)

(0.08) 0.06***

(0.01) 0.25***

(0.09) 0.99***

(0.22) -0.10***

(0.02) -1.71***

(0.37)

Hausman test Prob>chi2 = 0.0000 Standard errors in parentheses

*** p<0.01, ** p<0.05, * p<0.1 Positive effects were shown in variables: GDP per capita in the first period, the ratio of investment to GDP, the ratio of trained labor to total labor, the inclusion index

of education, the provincial competitiveness index (PCI), local budget expenditures Negative effects were presented in variables: Inflation, the human resources for health per capita, FDI

Both positive and negative effects recorded in: Dummy variable shown crisis

The thesis conducted heteroskedasticity test, multi-collinearity test, and test for time fixed effects The results proved that there was heteroskedasticity in the fixed effects model, no multi-collinearity among variables in the model, and the model was affected by time factors

4.3.3 Estimating spatial models

The study built a sequence of steps to select the appropriate spatial model

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steps: (i) performed Hausman test to choose between fixed or random effects models, (ii)

Verified the choice of spatial matrix type

(i) estimating without effect from LeSega and Pace (2009), and (ii) estimating with effect

from LeSega and Pace (2009)

In this section, the study conducted some tests including: Hausman test for Spatial

Durbin Model, test for spatial dependence of dependent variables, test for selecting

suitable spatial model Specifically, there were tests between Spatial Autoregressive

Regression (SAR) and Spatial Durbin model (SDM) (consequently chose SDM model),

between the Spatial Error model (SEM) and SDM (consequently chose SDM model),

between SAC, SDM and Generalised Spatial Panel Random Effects Model (GSPRE)

(with the result of selecting SAC model)

The results of estimating the SAC spatial model were presented with two

methods, with or without effects according to LeSega and Pace (2009) These two

authors pointed out that there could only be direct and indirect effects in the spatial

estimation model Accordingly, the direct effect was used to measure the change in

effect of the independent variable on dependent one in the same city, while the indirect

effect was the cross-space effect used to measure the change in effect of one city’s

independent variable on another city’s dependent variable The total effect was the

combined effect of the direct and indirect effects

The estimated results of spatial models without considering the effects according

to LeSega and Pace (2009): The results were quite similar to the estimation model

presented above (without considering spatial factors)

Table 2: Test results of estimating SAC spatial model

lgdppop2004 0.09**

(0.04)

(0.07)

(0.03)

18 (0.00)

(0.00)

(0.01)

(0.06) labor_tyle 0.63***

(0.13)

(0.01)

(0.04)

(0.09)

(0.00) Observations 441

Number of mun 63 Standard errors in parentheses

*** p<0.01, ** p<0.05, * p<0.1

Results of estimating spatial model when considering effects from LeSega and Pace (2009)

The estimation results showed that in all three cases with the direct, indirect and total effects, the sign of the coefficients and statistical significance of the variables were the same as the expected original model This implied that among the variables selected

in the model had direct, indirect and total effects when spatial factors were considered

in the model In other words, there exists both direct and indirect effects of independent variables on one city and other nearby cities presented

Table 3: Results of direct, indirect and total effects

VARIABLES EFF LR-

DIRECT

LR- INDIRECT

LR- Total

lgdppop2004 0.09** 0.11** 0.20*** 0.32***

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19

i_gdp

lcpi1

(0.04) 0.19***

(0.07)

- 0.10***

(0.03)

(0.05) 0.22***

(0.08) -0.12***

(0.03)

(0.08) 0.40***

(0.15) -0.22***

(0.05)

(0.12) 0.62***

(0.23)

- 0.34***

(0.07)

(0.00) (0.00) (0.01) (0.01)

lchins

ledu

labor_tyle

lyte2

(0.00) 0.02***

(0.01) 0.23***

(0.06) 0.63***

(0.13)

- 0.05***

(0.01)

(0.00) 0.03***

(0.01) 0.28***

(0.07) 0.76***

(0.15) -0.06***

(0.02)

(0.01) 0.05***

(0.01) 0.51***

(0.14) 1.37***

(0.32) -0.11***

(0.03)

(0.01) 0.08***

(0.02) 0.79***

(0.20) 2.13***

(0.45)

- 0.18***

(0.05)

rho

lambda

sigma2_e

0.70***

(0.04)

- 0.60***

(0.09) 0.01***

(0.00)

Number of

mun

Standard errors in parentheses

*** p<0.01, ** p<0.05, * p<0.1 Column (1) was the result of estimating spatial model without considering the

effects from LeSega and Pace (2009)

20 Columns (2), (3) and (4) were the test results when considering the direct indirect and total effects (considering effects from LeSega and Pace (2009)

4.3.4 Testing the impact of the crisis on income inclusiveness

Due to the fact that there was a global financial crisis during the research period, and this crisis was the time Vietnam witnessed two years of 2-digit inflation rate Therefore, the thesis estimated of the crisis impact on income inclusiveness with two dummy variables, 2007 and 2011, with a spatial estimation model The results showed that the two dummy variables representing the crisis were statistically significant, suggesting that the crisis had influence on income inclusiveness However, the sign of the 2007 crisis was negative while it was positive for the 2011 crisis variable

Table 4: Test the impact of crisis on income inclusiveness

lgdppop2004 0.104*** 0.0987***

(0.0381) (0.0371)

(0.0741) (0.0749)

(0.0351) (0.0269)

(0.00261) (0.00250)

(0.00282) (0.00305)

(0.00599) (0.00542)

(0.0595) (0.0587) labor_tyle 0.583*** 0.595***

(0.137) (0.135)

(0.0133) (0.0132)

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