Factors Affecting Human Development Index (HDI) in Vietnam

Factors affecting Human Development Index (HDI) in Vietnam

Lecturer: Dao Thanh Binh Student: Tran Thi Thanh Loan

Tran Vu Tien Pham Tra My

Vu Tuyet Nhung Ho THi Minh Phuong

Ngo Thi Bich Hanh Vu Thai Duy

Bui Hai Ngoc Dinh Duy Quang

Tutorial: 4 BA-06

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Overview

Introduction

Model specification

Data graph

Results

Conclusions and suggestions

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Introduction

HDI: a summary measure of human development

HDI measures three basic dimensions of human development:

- a long and healthy life, as measured by life expectancy at birth

- knowledge, as measured by the adult literacy rate

- standard of living, as measured by GDP per capita

HDI has had a significant impact on drawing the attention of governments, corporations and international organizations to aspects of development that focus on the expansion of choices and freedoms, not just income.

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Model specificationHDI = β1 + β2* GDP + β3*EDU + β4*LIE + u

HDI: dependent variable

GDP (Gross Domestic Product): dependent variable

- Y = C + I + G + NX

- GDP per capita = Y/ Population

Educational attainment (EDU): dependent variable

- represented by the literacy rate

- considered as a crucial measure of a region's human capital since literacy increases job opportunities and access to higher education.

Life expectancy (LIE): dependent variable

- the average number of years a human has before death

- an important measure in its own right and can be a proxy measure for many other issues such as healthcare, wealth, opportunities, and education

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Data graph

HDI

Vietnam HDI through 1995-2006

0.709

0.704

0.539

0.540

0.557

0.560

0.664

0.671

0.682

0.688

0.688

0.691

0.000

0.100

0.200

0.300

0.400

0.500

0.600

0.700

0.800

1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006

Year

HDI

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Data graph

GDP per capital

Vietnam GDP index during 1995-2006

0.550

0.540

0.520

0.510

0.500

0.490

0.4700.470

0.1800.180

0.110

0.170

0.000

0.100

0.200

0.300

0.400

0.500

0.600

1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006

Year

Bil

lion

of

doll

ars

GDP

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Data graph

Educational attainment

Vietnam Education index 1995-2006

0.810

0.8200.820

0.830

0.8400.840

0.830

0.820

0.810

0.800

0.790

0.780

0.750

0.760

0.770

0.780

0.790

0.800

0.810

0.820

0.830

0.840

0.850

Year

Percen

t

literacy index

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Data graph

Life expectancy

Vietnam Life Expectancy index 1995-2006

0.760

0.760

0.730

0.730

0.7200.710

0.710

0.710

0.6900.680

0.6800.670

0.620

0.640

0.660

0.680

0.700

0.720

0.740

0.760

0.780

1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006

Year

yea

rs

LE

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Data graph

Year HDI GDP Literacy Life expectancy

1995 0.539 0.17 0.78 0.67

1996 0.540 0.11 0.79 0.68

1997 0.557 0.18 0.80 0.68

1998 0.560 0.18 0.81 0.69

1999 0.664 0.47 0.82 0.71

2000 0.671 0.47 0.83 0.71

2001 0.682 0.49 0.84 0.71

2002 0.668 0.50 0.84 0.72

2003 0.668 0.51 0.83 0.73

2004 0.691 0.52 0.82 0.73

2005 0.704 0.54 0.82 0.76

2006 0.709 0.55 0.81 0.76

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Results

Eview result table

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Results

Functional test

- Log – linear function:

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Results

- Lin – log function:

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Results

- Log – log function:

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Results

C.V1 (linear-linear) = 0.0044/0.6410= 0.0068

C.V2 (log-linear) =0.0069 /0.4502= 0.0153

C.V2 (linear- log) = 0.01/0.6410=0.0156

C.V2 (log- log) = 0.0158/0.4502 = 0.035

=>best model linear-linear:

HDI =-0.021 + 0.3214* GDP + 0.384* EDU + 0.3144* LIE

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Results

Errors in the model:

- Multicolinearity:

+ happens when there is a functional relationship among independent variables.

+ all coefficients are significant

=> don’t need to worry about this error

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Results

- Heteroscedasticity: to check this error, Park-test is used

lnu^2 = β1 + β2*EDU

^Lne_sp= 22.0571 -42.157*EDU

H0 : β2 = 0 Heteroscedascity does not exist.

H1 : β2 ≠ 0 Heteroscedascity exists

From the table, P-value of β2> 0.05

=> β2 is not significant at 0.05

=> do not reject H0

=> there is no heteroscedascity

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Results

- Autocorrelation: to check this error, use The Breusch-Godfrey (BG) test

H0 : no autocorrelation

H1: autocorrelation exists

BG-statistic: 1.204509 < X 2p=1 = 3.84146

(α=0.05).

=> do not reject H0

=> no autocorrelation

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Results

Discussion

^HDI= - 0.021 + 0.3214 * GDP + 0.384 * EDU + 0.3144 * LIE

+ β2, β3 and β4 at 5% level of significance, their P-value are all < 0.05

=> GDP, EDU, LIE have significant impact on HDI Index

+ R2 = 0.996975 => more than 99% of the variation of HDI index can be explained by GDP, LIE, EDI indexes

=> very high level of fit between the regression line and the data provided.

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Conclusions and suggestions

Conclusions:

With the lowest CV, linear_linear was the best model

All the coefficients are significant shows a significant impact of EDU, LIE, and GDP indexes on HDI index

With positive sign of coefficients, there is a positive relationship between HDI indexes and the other three listed indexes.

Suggestions:

Invest more in education

Provide more health care service with good quality

Apply suitable economic development strategy to increase GDP

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