jaya latentvar models examples

8/6/2019 Jaya Latentvar Models Examples

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Multivariate Analysis MSE 2010 1

Krishnakumar (JHD, 2007)

A SEM is estimated using national (aggregate) data.

Based on the availability of data, three fundamentalcapability dimensions namely knowledge (education),

health and political freedom, are considered.

Data relate to a cross section of middle and low incomecountries across the world for the year 2000 (or the year

closest to it i.e. 1999 or 1998 for a few variables).


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Possible exogenous variables (observed)

For the structural part

x1: Government Effectiveness

x2: Regulatory Quality

x3: Population using improved water sources (%)x4: Cellular mobile subscribers (per 1000 people)

x5: Public expenditure on health ({\%} of GDP)

x6: Total debt service (% of GDP)

x7: Density (persons per sq.km.)

x8: Political Stability

x9: Population Growth Rate (Annual %)

x10: Urban Population Growth Rate (Annual %)x11: Youth Bulge (Pop. Aged 0-14 as a % of Total)

x12: Physicians (per 100,000 people)

x13: Press Freedom

x14: Democracy - Autocracy Index

x15: Total fertility rate (per woman)

x16: Foreign direct investment (PPP USD)

x17: Gross fixed capital formation (PPP USD)x18: Trade (PPP USD)

For the measurement part

w1: Control of Corruption

w2: Rule of Law

w3: Population with access to essential drugs (%)

w4: Population using adequate sanitation facilities (%)

w5: Public expenditure on education (% of GDP)


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Measurement Model

Dependentvariable

Explanatoryvariable

Political

Rights

Civil

Liberties

Voice

and

Accountability

Adult

Literacyrate

Combined

Enrolment

Ratio

Life

Expectancy

Infantmortality

Knowledgecapability

- - - 1

(0)

0.71

(0.06)

- -

Healthcapability

- - - - - 1

(0)

-3.87

(0.34)

Politicalfreedomcapability

1

(0)

0.66

(0.04)

0.40

(0.02)

- - - -

Access to

essentialdrugs

- - - - - 0.04

(0.03)

-0.10

(0.09)

Public

spending oneducation

- - - 1.72

(0.82)

1.58

(0.83)

- -

R2 0.92 0.88 0.95 0.83 0.87 0.80 0.97


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Results of the Measurement Model:

The coefficient of knowledge is positiveand highly significant for adult literacy rate

and combined primary, secondary andtertiary gross enrolment ratio.

The situation is similar for life expectancyat birth and infant mortality rate asindicators for health (the second one witha negative health coefficient) and thefour political freedom indicators.


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Structural ModelDependent variable

Explanatory variable

Knowledgecapability

Health capability Political freedom capability

Knowledge capability - - 0.01

(0.00)

Health capability 1.37

(0.27)

- -

Political freedom capability 0.28

(0.31)

Control of corruption - - 0.61

(0.18)

Access to adequate sanitation - 0.07

(0.02)

-

Population density -0.03

(0.01)

Youth bulge -64.39

(30.55)

Press Freedom 0.08

(0.01)

Fertility rate -4.00

(0.48)

R2 0.82 0.80 0.89


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Results of the Structural Model:

These results confirm the interdependent nature

of the three dimensions.

The positive and significant impact of health oneducation shows that better health is definitely

an asset for better performance in education,

which is in turn an important factor in achieving

political rights. Furthermore, greater political freedom leads to

better health status thus completing the loop.


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The results also show the importance of certain

supply side (exogenous) factors.

The population with access to essential drugs

has a significant positive impact on lifeexpectancy at birth whereas it has a negative

though not significant effect on the infant

mortality rate.

Public expenditure on education has a positiveand significant effect on adult literacy rate and

combined primary, secondary and tertiary gross

enrolment ratio.


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Krishnakumar (JHD, 2007) Percentage of population using improved water

sources and number of physicians per 100000people have a positive and significant effect onhealth whereas fertility has a negative effect asexpected.

Finally, press freedom and control of corruptionhave a significant and positive effect on politicalfreedom, the effects of regulatory quality,government effectiveness and political stability

not being significant. Lack of corruption definitelyimplies more freedom and the more thecollective voice in terms of press freedom thebetter the political rights atmosphere.


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Finally, the relevance of political, demographic,socio-economic and environmental factors in thedetermination of capabilities is also confirmed byour results.

The democracy-autocracy index has an important

positive effect on education (that is a moredemocratic regime seems to favour higherachievement in education).

Population growth rate and population density havean important negative effect on education. This can

be explained by the increased pressure exerted bya higher growth rate and density of population, onexisting educational services and governmentresources thereby affecting the overall achievementin this field.


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A key message of this paper is that a better social and

political environment not only implies a better conversion

of capabilities into achievements but also enhances the

capabilities themselves. This emphasizes the powerful

role that a State can and should play in terms of

providing better infrastructure and governance.

The paper also constructs capability indices from the

latent variable scores and ranks countries according to

them.

These rankings are compared with those obtained with

the commonly used HDI or GDP per capita.


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Argentina 1 10 2 3 7 15

Hungary 2 1 1 1 2 3

Slovakia 3 4 3 5 1 6

Chile 4 5 7 6 3 10Uruguay 5 3 8 2 4 5

Costa Rica 6 2 5 15 5 1

Mexico 7 18 9 17 16 23

Panama 8 7 17 12 11 9

Bulgaria 9 8 13 4 6 11

Romania 10 11 21 7 12 13

Colombia 11 24 11 13 17 34

Mauritius 12 6 6 32 8 2

Venezuela 13 20 20 24 14 27Thailand 14 15 15 20 18 18

Brazil 15 16 10 16 19 19

Philippines 16 13 27 8 20 16

Kazakhstan 17 36 18 10 37 44

Peru 18 25 23 9 28 28

Jamaica 19 9 29 33 10 8

Turkey 20 29 14 27 30 37

Sri Lanka 21 19 32 14 9 31Paraguay 22 22 22 22 15 32Dominican Republic 23 12 12 10 13 14

Uzbekistan 24 43 38 28 32 53

China 25 38 28 19 23 52

Iran 26 34 18 29 29 45

Jordan 27 26 26 35 25 29

Country rankhdi rankhhat rgdpn ry*1 ry*2 ry*3


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Kyrgyzstan 28 33 36 25 34 38

Guyana 29 14 24 18 33 7

Algeria 30 42 16 37 36 50

South Africa 31 17 4 23 40 4

Syrian Arab Republic 32 41 33 36 21 54Vietnam 33 40 41 26 22 55

Indonesia 34 27 34 21 27 33

Bolivia 35 23 39 31 41 12

Egypt 36 32 30 30 26 41

Honduras 37 21 35 34 24 22

Guatemala 38 28 25 39 35 26

Morocco 39 31 31 45 31 35

Zimbabwe 40 46 37 38 43 47

Ghana 41 30 40 43 39 24Cambodia 42 47 46 40 47 39

Kenya 43 45 51 41 42 43

Pakistan 44 51 44 47 46 51

Togo 45 48 47 46 44 42

Bangladesh 46 37 48 50 38 30

Madagascar 47 35 53 44 48 21

Mauritania 48 53 44 54 54 40

Zambia 49 49 55 42 51 36

Senegal 50 44 49 49 45 25Benin 51 39 52 48 50 17

Guinea 52 55 43 53 52 48

Gambia 53 52 41 51 49 49

Mali 54 50 54 55 55 20

Chad 55 54 50 52 53 46

Country rankhdi rankhhat rgdpn ry*1 ry*2 ry*3


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Multivariate Analysis MSE 2010 14Access to electricity

Access to radio, TV,

phone

LivingConditions

Capability

Schooling for

Age

(SAGE)

Level of

Education

Basic services

conditions

Water coverage

Habitability

conditions

Dwelling

conditions

Knowledge

Capability

Social investment

Number of

classrooms

Belongs to the urban

area

Number of individuals

Age

Number of siblings aged

7-14

To be poor

To be indigenous

Number of female/male

adults

Number of schools

Presence of a school

%of agricultural

population in the

active population

Belongs to maincities

Parental education

Use of medical

services

Literacy

Gender

Working status

Number of siblings

# of siblings aged 7-14

enrolled

Number of children

Male household head

Belongs to the urban

area

To be the oldest

Monthly per

capita expenditure

Belongs to main cities

Krishnakumar and

Ballon (2007, WD)

Basic Capabilities for

Bolivian Children


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Structural Model

oeff.Sta ar .

oeff.Sig if. oeff.

Sta ar .

oeff.Sig if.

y1*

Kno ledge capabil ity - - - 0.078 0.129 ***y2 iving conditions capability 0.124 0.075 *** - - -

x9 Father's level o education 0.074 0.160 ***

x10 other's level o education 0.141 0.171 *** 0.067 0.134 ***

x14 elongs to main cities 0.109 0.044 *** 0.128 0.085 ***

x11 se o medical services 0.170 0.023 * ***

x1 umber o schools 0.001 0.200 *** ***

x2 umber o classrooms 0.000 -0.273 *** ***

x4 gricultural population/ -0.045 -0.016

x12 onthly per capita expenditure 1.275 0.457 ***

R2 0.065 0.441

***,* denote signi icance at 1 and 10 levels respect ively.

ivi g co itio s

ca a ility equatio

y2*

Varia le

o le ge ca a ility

equatio

y1*


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Knowledge Measurement Model

Standardized

coefficientSignificance

Standardized


Standardized


y1*

Knowledge capability 0.609 - 0.599 *** 0.655 ***

w7 Number of siblings -0.106 *** -0.029 ** -0.068 *

w8 Number of siblings aged 7-14 -0.091 *** -0.045 *** -0.027 ***

w9 Number of siblings aged 7-14 enrolled 0.453 *** 0.166 *** 0.189 ***

w1 Age 0.534 *** 0.447 *** -0.156 ***

w4 Being indigenous -0.041 * -0.029 *** -0.082 ***

w2 Male 0.046 * -0.033 *** -0.028 ***

w14 Male household head -0.228 *** -0.097 *** -0.111 ***

w3 Working status -0.039 *** -0.017 *

R2 0.759 0.567 0.507

***,**,* denote significance at 1%, 5% and 10% levels respectively.

Sage

y3

Variable

Literacy Level of Education

y2y1


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Living Conditions Measurement Model

Standardized

Coefficient Significance

Standardized


Standardized


y2*

Living conditions capability 0.532 - 0.546 *** 0.532 ***

w4 Being indigenous -0.031 ***

w5 Being poor -0.052 *** -0.112 *** -0.065 ***

w14 Male household head -0.048 *** -0.050 *** -0.031 ***

w11 Number of female adults 0.036 *** 0.028 ** 0.076 ***

w13 Number of children -0.080 *** -0.233 *** -0.078 ***

w15 Urban 0.278 *** -0.076 *** 0.436 ***

R2 0.500 0.446 0.695

***,** denote significance at 1% and 5% levels respectively.

Variable

Basic Services

y6y4 y5

Dwelling Habitability


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Normalised Capability Scores

Knowledge Living Conditions


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Some Capability Determinants


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Department rankings

Department ank ank ank ank

(alphabetical order) EduAchiev. Knowledge LC.Achiev. LC.Cap Education LivCond

A1 C1 A2 C2 C1-A1 C2-A2

Beni 8 6 9 8 -2 -1Chuquisaca 3 4 7 5 1 -2

Cochabamba 4 3 4 2 -1 -2

La Paz 7 5 3 3 -2 0

Oruro 2 2 5 4 0 -1

Pando 5 6 8 6 1 -2

Potos 9 5 6 7 -4 1

Santa Cruz 1 1 1 1 0 0

Tarija 6 5 2 3 -1 1

Differences

jaya latentvar models examples

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