Journal of Global Resources
Volume 5 (02)
July 2019
ISSN: 2395-3160 (Print), 2455-2445 (Online)

Page 70-77

10
ROLE OF EDUCATION IN SOCIO-ECONOMIC DEVELOPMENT OF RURAL LIFE:
A STUDY OF MORILA VILLAGE, SUB-DIVISION SALUMBAR, DISTRICT UDAIPUR
Chandra Deo Ola
Research Investigator, Population Research Centre
Mohanlal Sukhadia University, Udaipur (Rajasthan), India
Email: cdola73@gmail.com
Abstract: This research paper examines the role of education in the socio-economic statusof the lives of Morila villagers of the Salumbar sub-division of Udaipur district. It is evident
from the results of observation and research that the socio-economic expansion of any
economy depends not only on the physical resources, but also on human resources that
reside in that particular area. The data collection for this study is done by a field survey. To
do this; an open and closed side questionnaire was designed. About one-third of the familiesof the total families of the village were interviewed. This study used both qualitative andquantitative approaches. Qualitative approach included in-depth interviews of adult men andwomen for their life histories focusing on food consumption pattern, medical or health care,and livelihood pattern was taken and analyzed. Though education is the most important andvaluable factor in the overall development of society, but the study of the village selected byme founds that primary education has less effect on the living conditions of rural residents.
With higher levels of education reached impact up to a level on socio-economic status andbehavior can be seen. It can be concluded that in the tribal region of Southern Rajasthan,education that gives some understanding about life is of matriculation level.
Key words: Education Level, Family, Resource, Development, Relationship, People
Introduction
Economic development of any country depends not only on material resources but also on
human resources. Developed human capital positively impacts on economic growth, politicalperseverance and social environment. Education is the most important variable, which plays
an important role in the development of human capital. Many empirical studies have shownthat the pace of economic development of developed countries could not be achieved
without the stock of human resources. In all stages of education, there is a central place forprimary education. In spite of this, primary school education provides basic principles tosociety. It can improve the quality of life, can develop industrial projects, which gives highfinancial rates of returns. Regarding measures to increase and improve elementary school
education and expenditure on the poorest population groups, in recent years, theGovernment of India has conducted a nationwide survey-DLHS-4; To overcome theimbalance in the social sector, India District Level Home and Facility Survey -4, 2011 (DLHS4). This survey provides rich information on the basic questions which were missing in theprevious home surveys conducted earlier. This study uses the figures of DLHS-4 to reexamine the education level using the Milcer-earning functional questions. And this is duelack of appropriate data in Indian studies with intent to fill the vacant space.
In this study, the first schools (class level) will estimate the work done according to
the given years and proceed from there to estimate the earnings. Thus there will be aperception of the rate of return for all school level. It is argued that different school years
provide different skills; therefore, we expand our analysis at the level of education, i.e.
primary, upper primary, secondary, senior secondary, graduate and PG to determine
increase in earnings with the additional year of schooling at different levels. The total literacy
rate in India's census 2011 was 72.98 percent; Males literacy 80.88 percent and female
literacy was 64.63 percent; in urban areas 84.11 percent and rural areas 66.77 percent. In
the village under study, literacy rate is 31.6 percent and of female it is 8.2 percent. According
to the report, "Between 1990 and 2015, the life expectancy of India increased by 10.4 years,
70the average of schooling increased by 3.3 years and school education increased by 4.1
years," . India's Gross National Income or GNI per capita increased 223.4 percent during thisperiod. This was mainly due to the adoption of India's market reforms, attracting investment
and dedicated more resources for social development in areas of health and education(United Nations Human Development Report 2016). Due to the low level of academic
achievement and the lack of technical and vocational education, there is the dominance ofless educated and inefficient labor in the Indian labor market. After 1990, there has been asignificant increase in the number of educational institutions and enrollments, but has notbeen reflected fully in the Indian labor market so far. This can happen because most
graduates and master degree programs insist on academic education only without
developing specific skills.
Review of Literature
Goodwin et al. 1984: viewed the primary factors affecting settlement patterns in rural areas of
the United States using factor analysis of survey responses from 1,156 households in
Oklahoma. Their results indicate that quality of services, age of home and availability ofservices; rural atmosphere and job and family considerations impact are most importantfactors. Von et al. 1992: studied that gender differences in education in Muslim developing
countries are related to the prevalence of Islam, but this decomposition model saysotherwise. Bhuyan et al. 1996: examined that the differential fertility in 16 contiguous villagesof both Savar and Dhamrai Upazila in Dhaka district, Bangladesh and find fertility between
working and nonworking women did not differ significantly. Deccache et al. 1997: reported
health promotion and health education have limited to evaluation of the effectiveness ofactions and programmes. Rath et al. 1998: reported that the impact of educational status,
income, indicate that a combination of these factors are associated with reduced fertility,
longer birth intervals, and lower levels of infant mortality. Dubois et al. 2003: described thesource and the scope of social inequalities in infant feeding practices. They examine theextent to which different recommendations are followed in different social groups andhighlight the main factors influencing the total adherence to these recommendations at the
population level.
Study Village Morila
This village is surrounded by forests and hills. About 200 years old, this village is located 9km away from Salumbar tehsil, sub-division office and block administration and Community
Health Center (CHC) city, Salumbar. But the people here moved out of the village andstarted living for pastoral and livelihood in the vicinity. The spread of the Morilla village is on
the banks of the Sarani River and the flow of the river is annual. However, due to being
situated at higher level than the lower elevation of the river, Morila village is not able tobenefit from the river for agricultural purpose. River water is used for self and animal drinking
and other domestic purposes. The total population in the village is 1554 and the number ofhouses is 314. The female population is 49.6 percent. The village literacy rate is 31.6
percent, and female literacy rate is 8.2 percent (Table 1).
Table 01: Literacy Rate of Morila Village
Census Parameter

Data

Census Parameter

Data

Total Population

1554

Scheduled Tribes Population %99.5 (1546)

Total No of Houses

314

Scheduled Caste Population %0.1 (1)

Female Population %49.6 (771)

Working Population %58.9

Total Literacy rate %31.6 (491)Child(0-6) Population

343

Female Literacy rate

8.2 (127)

Girl Child(0-6) Population %Male Literacy rate

23.4 (364)

Geographical Area (in Hectare)71

48.7 (167)501.7

Theoretical Model and Methodology
Human capital model developed by Becker (1964) and Minor (1974) is used to findrelationship between the socio-economic status of the people of Morila village at different
levels of school education for this study. In the mathematical version, the equation can be
expressed as:
In SESt = ß0 + ß1Edut + €t
(1)
In SES represents socio economic status. The nomenclature of SES is given under:
FS = Size of family, FI = Family income, HS = Structure of the house (1 for pakka and
0 for otherwise), RN = Number of rooms, EW = Women education (1 if they like it,0otherwise), HW = Women health facility (1 if they visit the doctor, 0 otherwise), F P =Family planning (1 if they use contraceptives, 0 otherwise), V = Vaccination (1 if yes,
0 otherwise),PA = Production per acre, ND = Diet (1 if they take egg, meat or milk
daily, 0 otherwise), and Edu= Education level represents of like: Primary, Middle,
Secondary, Senior Secondary and above and €t error term.
In order to find the returns to education at different level of education, we estimate
equation:
In SESt = ß0 + ß1 E1+ ß2 E2+ ß3 E3 + ß4 E4 + ß5 E5+ €t(2)
Where E1 = Primary education, where ß1 = 1 if 0 < Education≤ 5
E2 = Primary education, where ß2 = 1 if 5 < Education≤ 8
E3 = Primary education, where ß3 = 1 if 8 < Education≤ 10
E4 = Primary education, where ß4 = 1 if 10 < Education≤ 12
E5 = Primary education, where ß5 = 1 if 12 < Education≤ higher education
The coefficients associated with E1, E2, E3, E4 and E5 in equation (2) show anincrease in socio-economic status of people of Morila village with one year increasein education at particular levels. The returns to education can be computed at eachlevel as:Return to Primary = 5ß5E1 + ß2E2+ ß3E3 + ß4E4 + ß5E5
Returns to Middle = 5ß1 +3ß2, Returns to Secondary = 5ß5 + 3ß2 + 2ß3
Returns to Senior Secondary = 5ß1 + 3ß2 + 2ß3 + 2ß4
Returns to higher education = 5ß1 + 3ß2 +2ß3 + 2ß4 + 2ß5
The data used in this study has been collected from Morila village of Salumbar SubDivision, District Udaipur. The data collection for this study is done by a field survey. To dothis, an open and closed side questionnaire was designed. In this study, about one-third of
the families (95 households) of the total families of the village were interviewed. To measuredifferences and inequalities, a dummy variable question has been used, which takes value 1
for yes and 0 for no. The main source of gathering information about the change in lifestylewith the level of education is an interview, for which about 24 short questions were set in thequestionnaire. This questionnaire was based on two parts, one part measures educational
levels and in the last section some practical questions were asked for qualitative
measurements, including decision power, type of communication, and assessment of womeneducation, family planning and the most important child care and include10 different related
questions. In case of respondents, their activities like diet, immunization and medicines havebeen included. Out of 63 families living in kachcha houses, 23 live in one-room houses and
14 live in 2 room houses. They do not have toilets, kitchens, stores and cattle shed forlivestock. Approximately 24 percent of the village's population lives in one room, 8 percent
live in two-room houses and 3 percent live in three-room houses. The source of drinking
water is the hand pump and river channels.
Results
Two types of quantitative and qualitative results were found in the study. Of the total 95
respondents, 53 were men and 42 were women. Of them, 82 were married and 13 were
single. 67 respondents were associated with the unorganized sector, 15 were working informal sector and 13 were not having any jobs. Table 2 shows that the age of 34
respondents is between 18-30 years and the age of 19 respondents is between the age of
31-40 years and the age of 17 respondents is between the age of 41-50 and the age of 13
respondents, between the age of 51-60 years, while only 8 respondents are over 60 years ofage. Table shows that out of 100 interviewed respondents, 49.5 percent were uneducated72and 50.5 percent were educated. Within 50.5 percent educated respondents, 20.0 percent
were educated till primary level, 16.8 percent higher primary, 8.4 percent secondary, 4.3
percent college education, while 1 percent were post graduate respondents.
Table 02: List of Different Age Group and Educational Level of Respondents#
Age Group
Percentage of
Number
Education Level(Year’s)
Education Level
1.
18-30
34
No Schooling
49.5
2.
31-40
19
Primary
20.0
3.
41-50
17
Middle
16.8
4.
51-60
13
Secondary
08.4
Above (Senior Secondary, College
5.
61-70
08
05.3
and University educated)
Source: Computed on the basis of primary survey data.

Table 3 describes the relationship between education level and monthly income. In
the 2nd column of this table, average responsive income is calculated. Positive relationshipexists between education level and average income of respondents. Excluding the case of
matriculated people, the average income increases with increasing educational levels. In thethird column of the table, the average family income is calculated. It shows a relation that the
average family income increases with an increase in education level. Per capita income
calculated in fourth column, shows positive relationship with education level.

1.

Table 03: Distribution of Income in Respondents
Education
Average Respondent's
Average Family
Level
Monthly Income (Rs.)
Monthly Income (Rs.)
No Schooling
3350.00
4520.25

2.

Primary4725.505694.00

2665

3.

Middle5485.00

10441.00

2460

4.

Secondary

5250.00

10120.00

3180

5.

Above

9200.00

12312.00

3200#

Per Capita
Income (Rs.)
2150

Source: Computed on the basis of primary survey data.

Table 4 shows the relationship between the level of education and the use of various
types of communication devices. Relationship between the level of education and the use of
television has been discussed. Interestingly, there is a positive relationship between the twovariables, i.e., with increase in the education level, the demand for TV sets has also
increased. The main reason for this increase is awareness about world issues, national
issues and the desired programs. This is also the case with telephone use. With the increasein education level, the use of telephone increases. In case of telephone use, the only
exception is in the matriculation group, this may be due to sample error because only 5
matriculated respondents were interviewed between 100 samples. In the fourth column, therelationship level is presented between the use of radio and education. While the last column
shows the relationship between the education level and the reading newspaper. A positive
relationship exists between the education level and the reading of newspaper.

#
1.
2.
3.
4.
5.

Table 04: Source of Communication by Different Educational Levels(in percent)Education Level
TV
Phone
Radio
News Papers
No Schooling
75
14
43
4
Primary
92
15
38
23
Middle100506225Secondary
80
40
40
20
Above
92
70
62
62

Source: Computed on the basis of primary survey data.

73Respondents' behavior about decision making with different education levels has
been seen and it’s seen that there is increased participation in decision-making with anincrease in education level. One of the reasons for this change in behavior is the fact that theeducated person is of more liberal and open mind. People think that decision by their family
participation will be more positive and better for everyone. That's why they acknowledge theimportance of their family members, such as; wives, children and parents. 69 percent of
uneducated people do not include their families in decision making; perhaps they feel
humiliated to take any kind of opinion from their families. 38 percent of primary, 49 percent
higher primary, 45 percent secondary and 29 percent of highly educated people do notinclude their families in decision-making activity.
Table 5 shows the relationship between education level and, education of women,
family planning and the role of immunization. The second column of the table shows thepercentage of choice for women education, that is how many people like to educate theirdaughters. This attitude appears very much from the table, i.e. as the respondents climb theeducational ladder, they have more generous behavior towards women education.
Sophistication, liberal outlook, broad vision can be one of the reasons for such an attitude.
Table 05: Use of Family Planning and Health Care Activities(in percent)#Education Level

1.
2.
3.
4.
5.

No SchoolingPrimary
MiddleSecondary
Above

Liking of Women
Education
48.2
57.0
87.5
96.0
98.0

Women's
Health Facility
62.4
74.5
81.0
95.0
100.0

FamilyPlanning
51.0
82.0
82.1
75.4
67.0

Vaccination
25.0
51.2
62.0
78.5
94.0

Source: Computed on the basis of primary survey data.

The 3rdcolumn gives the availability of female healthcare facilities. Relationship is
once again positive, i.e. increase in education level increases awareness of women's health.
The fourth column of the table shows the relationship between the use of education level andcontraceptives. Column shows positive relationships between the level of education and therole of family planning. Like the use of contraceptives, only 51 percent uneducatedrespondents use it, while 75 percent of higher and 67 percent of lower educated people likeit. Here is a very interesting situation with the primary and middle education group. Here is avery interesting situation with primary and middle education groups. The 82 percent of theseage groups recognize the importance of family planning. So, it is clear that 5 to 8 years ofschooling has a more positive effect on the use of contraceptive activities. The last column
discusses relations between vaccination courses with different education levels. With theacquisition of more education, the person is more aware of the importance of immunization.
Table 6 shows the daily diet of respondents' children. Generally, young children getmilk, eggs, and fruits, vegetables in their daily diet while they need corn, wheat and rice. As
people climb the education ladder they become more aware of this daily diet chart. In theentire table, it clearly shows that the use of milk, eggs, fruits, maize and wheat increases with
the increase in the level of education.

#

Table 06: Daily Diets Taken by Different Educational Group
Education Level
Milk Eggs Fruit Vegetables Meet Rice Wheat Maize

1.

No Schooling

45

28

26

40

30

97

100

100

2.

Primary (1-5)

75

33

33

42

58

100

100

85

3.

Middle (6-8)

62

50

37

45

75

100

100

65

4.

Secondary (9-10)

75

75

50

60

75

100

100

62

5.

Above

90

80

40

55

90

100

100

72

Source: Computed on the basis of primary survey data.

74

The most important fact is that maize and wheat are being used by almost all
members of all education groups. The reason may be that these two-maize and wheat
because of social, economic and geographical causes has become a major part of the diet ofthe people of the region.
Table 7 describes the different types of hygiene used by respondents related todifferent education levels. 70.5 percent of uneducated respondents get government
sanitation service and it is almost identical to upper primary education persons. This is betterfor primary and upper primary education groups, for example 81.25 percent and 70 percent,and this availability of sanitation facility increases with the recipients of college and university
education, i.e. 92.3 percent.
Table 07: Use of Different types of Sanitation Facilities
#
1.
2.
3.
4.
5.

Education Level
No SchoolingPrimary
MiddleSecondary
Above

Govt. Provisions
70.50
81.25
70.00
80.00
92.30

Village Community
19.60
18.75
30.00
20.00
76.00

Own
7.80
0
0
0
0

(in percent)
Any Other
1.9
0
0
0
0

Source: Computed on the basis of primary survey data.

All other respondents who don’t get government sanitation service use one generated
by the village community, but about 10 percent of uneducated people use their own sourceor one generated from any other source. It is clear from the table that as education levels
increase there is less dependence on the village community and more reliance on
government sanitation services.
Table 08: Estimation of Child Care Facilities
#
1.
2.
3.
4.
5.

Education Level
No SchoolingPrimary
MiddleMatricAbove

Doctor
29.00
92.80
75.00
75.00
90.00

Hakims
12.50
0
12.50
0
10.00

Dispensary
60.40
21.42
75.00
25.00
20.00

Devra
16.60
7.10
0
0
0

(in percent)House Tips
25.0
7.14
0
0
0

Source: Computed on the basis of primary survey data.

Table 8 describes the relationship between education level and child care activities.
In the second column of the table it has been discussed that how many people at different
education level seek advice from doctors for the care of children. Only 29 percent of
uneducated people consult doctors and this ratio increases with the increase in the educationlevel and it is highest in the primary education group where the ratio is 92.80 percent.
In the third column, the role of the hakim is discussed. 12.50 percent uneducated andthose educated till middle school respondents consult the hakim during the illness. The fourthcolumn shows that 60 percent of uneducated people get medicines without the fullinvestigation and examination of their child. This tendency has decreased with the increasein education level and there is a very interesting situation in column 5th, which shows that
16.60 percent of uneducated people and 7.10 percent of primary educated people believe in
Mataji and Bharuji Deora (traditional deities of worship) instead of the doctor. And similarly incolumn 6, it is clear that only uneducated and primary educated people rely on traditional
household methods of treatment of diseases. No other section is interested in Mataji, BharujiDeora and traditional methods. Therefore, it is clear that, with the spread of education,
people depend more on doctors and modern medical facilities than traditional deities andhousehold treatments.

75

Table 09: Regression and Logistic Model’s Result of SES
Ordinary Least Squares (OLS) Regression
Independent
Intercept
E1
E2
E3
E4
Variables
FS
2.37
0.21
0.42
0.37
0.46

Logistic Regression
E5

E1

E2

E3

E4

E5

R2

R1
-

0.41

-

-

-

-

-

94%

FI

2.42

0.44

0.52

0.62

0.76

0.71

-

-

-

-

-

95%

-

HS

2.49

-

-

-

-

-

0.22

0.36

0.42

0.47

1.03

-

76%

RN

4.79

1.04

1.49

2.21

3.03

3.31

-

-

-

-

-

91%

-

EW

2.81

-

-

-

-

-

0.11

0.17

0.61

0.83

1.02

-

73%

HW

2.85

-

-

-

-

-

0.14

0.26

0.85

1.16

1.21

-

72%

FP

2.72

-

-

-

-

-

0.81

0.34

0.98

1.34

1.76

-

74%

PA

2.09

2.19

1.36

1.42

1.79

1.65

-

-

-

-

-

87%

-

ND

2.12

-

-

-

-

-

0.86

0.43

0.71

0.68

0.65

-

86%

Logistic model (or logit model) is a statistical model that is usually taken to apply to abinary dependent variable. More formally, a logistic model is one where the log-odds of theprobability of an event are a linear combination of independent or predictor variables.
The current study shows that family size decisions are dominated by village
traditions. In this regard, all coefficient of education is unimportant. The importance of first
three levels of education- uneducated, primary and upper primary is less, whereas the othertwo levels have a significant effect on the per capita income and income of the family.
However, all coefficients give positive signals. For composite home equation, the logistic
model is used. The first three levels of education have insignificant effect on the structure of
the house, whereas the last two equations have a positive and significant effect. Because,
more educated people do generate more income.
The relationship between the living room and the level of education is measured by atleast class regression. The results show that at only higher level, education has a positiveand significant effect on the number of living rooms in households. In the case of womeneducation, women's health and family planning, the results show that there is a positive andsignificant impact of education; health and family planning instead of low level of education.
As the education level of the head of the family increases, the education standard of otherfamily members also increases. Use of new technology, access to new crop varieties or
sophisticated equipment is the result of education. Diet equation shows significant andpositive results at all levels of education. This can be due to the cultural, social environment
and the pure food items of the village.
Suggestions
Education must be able to motivate young people to prepare for the transition from school towork by participating in society before they leave school. Education should help young
people learn from society so they can develop a vision of the direction they may wish to takeonce they leave school and enter the workforce. Approaches to non-formal and informal
education each have a different dynamic. Formal education is compulsory for the first nine
years of the education system, while non-formal education is purely voluntary and informal
learning is influenced by parents and culture. These approaches to education may pullstudents in different directions. However, they may also work together in a powerful way.
Conclusion
This study shows that the role of primary education on rural life is insignificant. This isbecause the educational system in Rajasthan especially in rural areas is inadequate toachieve its goals. However, partly in the agricultural sector it has some significance. Thisimplies that primary schooling increases the income of the farmer and is the reason forpoverty reduction. Similarly, primary education produces good understanding of diet.
However, a significant conclusion has been drawn in this study that only 10 years ofschooling has a positive and significant effect on all the variables. It can be concluded that in
the tribal region of Southern Rajasthan, education that gives some understanding about life
is of matriculation level. It shows that the authorities should pay proper attention towards
76primary and secondary basic and skill based education and higher education, which enables
individuals to become a productive agent of the economy.
References
1. Ansari, Z., T. Barbetti, N. J. Carson, M. J. Auckland, F. Cicuttini et al. (2003) The
Victorian ambulatory care sensitive conditions study: Rural and urban perspectives. Soz
Praventivmed., Volume 48(1), pp. 33-43.
2. Barro, Robert J., and Jong Wha Lee (2013) “A New Data Set of Educational Attainment
in the World, 1950–2010.” Journal of Development Economics, 104 (September): 184–
198.
3. Becker G. 1964: Human Capital. 2nd edition. Columbia University Press, New York
4. Bhuyan, K. C. et al. (1996) Fertility differentials according to females' education,
employment and family planning adoption in rural Bangladesh. Nufusbil Derg, Volume
17-18, pp. 21-39.
5. Caldwell (1979) Education as a factor in mortality decline: An examination of Nigeria
data. Population Studies, Volume 33.
6. Deccache, A. et al. 1997: Evaluating quality and effectiveness in the promotion of health:Approaches and methods of public health and social sciences. Promot Educ, Volume4(2), pp. 10-5.
7. Dubois, L., M. Girard et al (2003) Longitudinal Study of Child Development in Quebec(LSCDQ 1998-2002). Social inequalities in infant feeding during the first year of life.
Public Health Nutr., Volume 6(8), pp. 773-83.
8. Fane, G. (1975) Education and the managerial efficiency of farmers. Review of
Economics and Statistics, Volume 57(4).
9. Goodwin et al., editors 1984: Disaggregating Models of Fluctuating Growth", in Nonlinear Models of Fluctuating Growth.
10. Gopaldas, T., P. S. Christian, R. D. Abbi, S. Gujral et al 1990: Does growth monitoring
work as it ought to in countries of low literacy? J. Trop Pediatr., Volume 36(6), pp. 322327.
11. Lucarelli, P. et al. (2002) Raising the bar for health and safety in child care. Pediatr Nurs.,
Volume 28(3), pp. 239-41, 291.
12. Mincer, J.1974: Schooling, experience and earnings, National Bureau of Eco. Research,
New York.
13. Psacharopoulos, George (1994) “Returns to Investment in Education: A Global Update”.
World Development, 22 (9): 1325–1343.
14. Stewart, Frances, and Séverine Deneulin (2002) “Amartya Sen’s Contribution to
Development Thinking”. Studies in Comparative International Development, 37 (2): 61–
70.
15. Von Urff, W. et al (1992) Comments on "Human Capital Accumulation in Post Green
Revolution Rural Pakistan: a Progress Report". Pak Dev Rev. Volume 31 (4 Pt 1), pp.
488-490.
16. Wirakartakusumah, M. D. et al (1998) The impacts of health, education, family planningand electrification programs on fertility, mortality and child schooling in East Java,
Indonesia. Majalah Demografi Indones., Volume 15(29), pp. 37-73.

77