SOCIO-ECONOMIC STATUS OF MUSLIM MAJORITY DISTRICT OF KERALA: AN ANALYSIS

Similar documents
IJMIE Volume 2, Issue 3 ISSN:

The Trend and Pattern of Health Expenditure in India and Its Impact on the Health Sector

Assessing The Financial Literacy Level Among Women in India: An Empirical Study

BANKERS FAMILIARITY AND PREFERENCE TOWARDS FINANCIAL INCLUSION IN SIVAGANGA DISTRICT

NURSES PERCEPTION TOWARDS ESI SCHEME: A STUDY WITH REFERENCE TO SELECT HOSPITALS IN UDUPI DISTRICT

Financial Literacy and Financial Inclusion: A Case Study of Punjab

Chapter -V CONCLUSION. Importance of human resource for economic development was recognized by

Primax International Journal of Commerce and Management Research

Public Expenditure on Health and its impact on Health care Indicators in India

Micro Insurance opportunity for Growth. A Study with Reference to Kollam District, Kerala 1 Shaji. A.S, 2 Dr. R. Neelamegam

International Journal of Business and Administration Research Review, Vol. 3, Issue.12, Oct - Dec, Page 59

POLICYHOLDERS AWARENESS ON SBI LIFE INSURANCE PLANS IN COIMBATORE DISTRICT

A STUDY ON PERCEPTION OF INVESTOR S IN AN ASSET MANAGEMENT ORGANISATION

Standard Fireworks Rajaratnam,College for Women, Sivakasi,

Determining Tax Literacy of Salaried Individuals - An Empirical Analysis

Keywords: Financial services & Inclusive Financing, Awareness of Households towards Financial Services. I. INTRODUCTION

SERVICES OFFERED BY PUBLIC AND PRIVATE SECTOR BANKS - CUSTOMERS AWARENESS IN TIRUPUR DISTRICT

Social Sector Scenario of India after the Economic Reforms (T. Maheswari, Asst. Professor in Economics, Lady Doak College, Madurai, Tamil Nadu)

AWARENESS OF WOMEN BEEDI WORKERS ON GOVERNMENT SCHEMES RELATED TO THE BEEDI WORKERS Dr. P. Devi *1, Dr. I. Prem Rose Thayammal 2. India. Nadu, India.

CHAPTER III RESEARCH METHODOLOGY

MAHATMA GANDHI NATIONAL RURAL EMPLOYMENT GUARANTEE ACT (MGNREGA): A TOOL FOR EMPLOYMENT GENERATION

CHAPTER 6 DATA ANALYSIS AND INTERPRETATION

Sai Om Journal of Commerce & Management A Peer Reviewed International Journal

Saving and Investment Pattern of College Teachers

The Influence of Demographic Factors on the Investment Objectives of Retail Investors in the Nigerian Capital Market

ASSOCIATION BETWEEN LONG TERM ORIENTATION AND INVESTOR PREFERENCE TOWARDS DIFFERENT AVENUES

WOMEN ENTREPRENEURSHIP DEVELOPMENT THROUGH POVERTY ALLEVIATION SCHEMES: A CASE STUDY

IJBARR E- ISSN X ISSN ROLE OF PLANNING IN THE FINANCIAL DECISION MAKING OF INDIVIDUALS

Human Development Indices and Indicators: 2018 Statistical Update. Russian Federation

Correlation of Personal Factors on Unemployment, Severity of Poverty and Migration in the Northeastern Region of Thailand

Human Development Indices and Indicators: 2018 Statistical Update. Turkey

A Study on the Impact of Demonetization among the General Public in Coimbatore City

MOTIVATIONAL FACTORS AMONG TRIBAL WOMEN FOR JOINING SELF HELP GROUPS IN DHARMAPURI DISTRICT

POSTAL LIFE INSURANCE: ITS MARKET GROWTH AND POLICYHOLDERS SATISFACTION

International Journal of Business and Administration Research Review, Vol. 1, Issue.15, July - Sep, Page 34

Human Development Indices and Indicators: 2018 Statistical Update. Uzbekistan

Journal of Exclusive Management Science May Vol 6 Issue 05 ISSN

CHAPTER 5 DATA ANALYSIS AND HYPOTHESIS TESTING

Budgeting and Budgetary Control System: A study on Selected Indian Companies

www. epratrust.com Impact Factor : p- ISSN : e-issn : January 2015 Vol - 3 Issue- 1

AWARENESS OF FINANCIAL INCLUSION ON TRIBAL PEOPLE IN DHARMAPURI DISTRICT

CUSTOMER AWARENESS REGARDING BANKING SERVICES

A Comparative Study of Life Insurance Corporation of India and Bajaj Allianz Life Insurance Co.Ltd. on Customer Satisfaction

Himachal Pradesh District Governance Index

A STUDY ON LEVEL OF AWARENESS & PERCEPTION ABOUT MICRO HEALTH INSURANCE SCHEMES IN DAKSHINA KANNADA DISTRICT, KARNATAKA

Demographic Influences on Rural Investors Savings and Investment Behavior: a Study of Rural investor in the kangra district of Himachal Pradesh

SECTION - 13: DEVELOPMENT INDICATORS FOR CIRDAP AND SAARC COUNTRIES

PERCEIVED FINANCIAL LITERACY AND SAVINGS BEHAVIOR OF IT PROFESSIONALS IN KERALA

Education and Employment Status of Dalit women

Investment Pattern of Working Women in Dindigul District

A Study on Policy Holder s Satisfaction towards Life Insurance Corporation of India (LIC) with Special Reference to Coimbatore City

A study on investor perception towards investment in capital market with special reference to Coimbatore City

EXECUTIVE SUMMARY OF THE DEVELOPMENT GAPS AND PRIORITIES FOR THE MULTI-SECTOR PLAN

SECTION - 13: DEVELOPMENT INDICATORS FOR CIRDAP AND SAARC COUNTRIES

INVESTORS ATTITUDE TOWARDS RISK AND RETURN CONTENT IN EQUITY AND DERIVATIVES

Human Development Indices and Indicators: 2018 Statistical Update. Brazil

Human Development Indices and Indicators: 2018 Statistical Update. Costa Rica

Methodology and Tools for Supporting the Formulation of Evidence-based Policies in Response to the Challenge of Population Ageing in Malawi

Human Development Indices and Indicators: 2018 Statistical Update. Switzerland

Human Development Indices and Indicators: 2018 Statistical Update. Congo

Human Development Indices and Indicators: 2018 Statistical Update. Argentina

Human Development Indices and Indicators: 2018 Statistical Update. Belgium

Introduction. 1.1 Introduction

Lecture 19: Trends in Death and Birth Rates Slide 1 Rise and fall in the growth rate of India is the result of systematic changes in death and birth

AWARENESS OF FINANCIAL PRODUCTS AMONG RURAL HOUSEHOLDS IN SRIKAKULAM DISTRICT, ANDHRA PRADESH

Human Development Indices and Indicators: 2018 Statistical Update. Peru

Impact of Microfinance on Indebtedness to Informal Sources among Clients of Microfinance Models in Palakkad

1. Introduction. M. Yasodha 1, Dr. G. Ravindran 2

Financial Risk Tolerance and the influence of Socio-demographic Characteristics of Retail Investors

A STUDY ON STATUS OF AWARENESS AMONG MUTUAL FUND INVESTORS IN TAMILNADU

BASELINE SURVEY OF MINORITY CONCENTRATION DISTRICT. Executive Summary of Leh District (Jammu and Kashmir)

INTRODUCTION. The banking sector plays an important role in efficient functioning of the economy of the

INITIATIVES OF KERALA TOWARDS FINANCIAL INCLUSION

Role of Independent Variables on Investment Decision of Equity Retail Investors

Appendix 2 Basic Check List


A Comparative Study of Life Insurance Corporation of India and Bajaj Allianz Life Insurance Co. Ltd. on Customer Satisfaction

CHAPTER-VI PERCEPTIONAL ANALYSIS OF CHIT MEMBERS AND THE MANAGERIAL STAFF

SATISFACTION OF WORKING WOMEN POLICYHOLDERS ON THE SERVICES OF LIC

Eswatini (Kingdom of)

Human Development Indices and Indicators: 2018 Statistical Update. Paraguay

Human Development Indices and Indicators: 2018 Statistical Update. Dominica

BASEL III AND STRENGTHENING OF INDIAN BANKING SECTOR

e-issn : p- ISSN : Impact Factor : www. epratrust.com September 2014 Vol - 2 Issue- 9

CHAPTER.5 PENSION, SOCIAL SECURITY SCHEMES AND THE ELDERLY

Human Development Indices and Indicators: 2018 Statistical Update. Nigeria

Data Profile of Sagar District

INTERNATIONAL JOURNAL OF MANAGEMENT (IJM)

A COMPARATIVE STUDY ON FINANCIAL HEALTH OF ICICI BANK AND AXIS BANK

HUMAN GEOGRAPHY. By Brett Lucas

Analysis of Deposits and Advances of Selected Private Sector Commercial Banks

The Role Of Micro Finance In Women s Empowerment (An Empirical Study In Chittoor Rural Shg s) In A.P.

ROLE OF MUTUAL FUND IN THE RURAL HOUSEHOLDS (SCHEME PREFERENCE AND PERIOD OF INVESTMENT)

EFFECT OF CORPORATE SOCIAL RESPOSIBILITY ON FINANCIAL PERFORMANCE OF SELECTED INDIAN COMMERCIAL BANKS- AN ANALYSIS

Amol Khandare, Planning Department, Govt. of Maharashtra

A Study of Investors Attitude towards Mutual Fund

A Study on Opinion of Working People towards Share Market Investment with Reference to Tiruchirapalli District

DECENTRALISATION OF GOVERNANCE IN KERALA AN OVERVIEW. Prof. T.Raghavan. Kerala Institute of Local Administration

Indian Research Journal of Extension Education Special Issue (Volume I), January,

INFLUENCE OF LOANS AND ADVANCES SCHEMES IN DETERMINING THE SERVICE QUALITY OF BANKS A STUDY WITH SPECIAL REFERENCE TO CANARA BANK IN SIVAKASI

Transcription:

SOCIO-ECONOMIC STATUS OF MUSLIM MAJORITY DISTRICT OF KERALA: AN ANALYSIS Dr. Ibrahim Cholakkal, Assistant Professor of Economics, E.M.E.A. College of Arts and Science, Kondotti (Affiliated to University of Calicut), Kumminiparamba Po, Malappuram District, Kerala State, ABSTRACT This paper is based on the study conducted as part of the doctoral research, which led to Doctor of Philosophy in Economics. As Kerala State is characterized by the so-called health paradox (Low mortality with high morbidity) and paradoxical development (high social development with low economic development). It is interested to examine the socio-economic status of households in Malappuram-a socially backward and Muslim majority district of Kerala. This study tried to examine the socio-economic status of households among different communities, income groups and education groups in particular and the socio-economic status of households of Malappuram district in general. The application of statistical tools revealed that there is no significant difference in socio-economic status between urban (non-coastal) and rural (coastal) areas. But, significant difference in socio-economic status is discovered among different communities, education groups and income groups. Keywords: Socio-economic status index, per capita monthly income, education and Community. 1. Introduction The social development of Kerala, particularly in the areas of education and health, despite not having appropriate economic development, received both countrywide and universal attention. The State has achieved an admirable position among the states in the country in education indicators such as literacy rate, top enrolment of students, higher percentage of girls, SC and ST students in schools and colleges even in outmost regions, low dropout rate among students (Salim 1997). Even though the state's expenditure on education is on a downward trend, the per capita expenditure on education in Kerala is still one of the highest among other Indian states. The literacy rate of Kerala is still comparable with most developed countries of the world. It was only 47.18 per cent in 1951, and it has nearly doubled as 93.91 per cent in 2011 (Census-2011). The male-female literacy gap was 21.92 per cent in 1951 and has came down to 4.04 per cent in 2011. Kerala has made an admirable achievement in the area of healthcare and immunization. The so-called 'gulf boom' experienced by the state since the 1970s has resulted to the emergence of private nursing homes in Ayurveda and Allopathic medical systems. The services of doctors and hospitals were well spread all over the state. The wide network of rural dispensaries, community health centres, taluk hospitals, district hospitals, research and medical college hospitals and the private and co-operative hospitals provide healthcare services to people (Gangadharan 2007). Generally, Kerala people are more health conscious and hence the state stands first among the Indian states in the provision of hospitals and hospital beds. The 2011 Census report remarks that, the Crude Death Rate of Kerala was 18 per thousand in 1951 and it has came down to 7.32 in 2011(Economic Review 2012). The Infant Mortality Rate in Kerala was 153 per thousand live births in 1951 and it came down to 7.53 in 2011. The life expectancy at birth in Kerala was 39.9 years in 1951 and it has improved to 74 years in 2014 (Kerala Economic Review 2014). Hence, the health status of Kerala state is comparable even with the health status of the developed countries. Meanwhile, the morbidity structure of Kerala provides a different picture. The health sector of Kerala is characterized by the co-existence of low mortality and high morbidity. The morbidity rate in the state is twice the all India average in the rural areas and over 50 percent higher than the countrywide average in the urban areas. 143

Malappuram district is the only Muslim-majority district in Kerala (Beevi 2012), is economically and socially backward. It has 14 th rank (last rank) in per capita income and 9 th rank in literacy rate according to the 2011 census. The education and health amenities in terms of infrastructure and services provided by the public sector in Malappuram district are not adequate due to the district's large population size. However, the presence of private sector in providing education and health facilities enhanced the education and health status of the district to an extent. 2. Statement of the Research Problem Kerala has received worldwide attention to its noteworthy achievements in the social sector, mainly in the area of education and health. Improvement in education is generally observed as a positive symbol of wellbeing of the people. But, today Kerala is affected by several diseases and epidemics that are prevented in several countries of the world. The incidence of lifestyle diseases and communicable diseases are more in the state today than that of the past. The health situation of Kerala is characterised by the health paradox low mortality and high morbidity (Navaneethan et al. 2006). The research problem is, what is the status of socio-economic situations of people in Malappuram district?, since this district is backward in Per capita income, literacy and in the provision of health amenities. 3. Objectives of the Study 1. To examine the socio-economic status of households in Malappuram district 2. To inspect the variations in socio-economic status of households among different income groups. 3. To identify the variations in socio-economic status of households among different education groups. 4. To analyse the socio-economic status of households of different communities. 4. Hypotheses 1. There is no significant variation in socio-economic status of households among different income groups. 2. There is no significant variation in socio-economic status of households among different education groups. 3. There is no significant association between socio-economic status of households and communities. 5. Sources of Data The study was designed with the information drawn from secondary as well as primary sources of data. 5.1. Secondary data The secondary data were collected from Economic Reviews of various years of the Kerala State Planning Board, Census Reports, Economic Surveys, Human Development Reports, Sample Registration System Reports, National Family Health Survey Reports, Reproductive and Child Health Reports, National Rural Health Mission (NRHM) Reports and Surveys of Ministry of Human Resource Development (MHRD). Research dissertations, books, journals, periodicals and electronic database such as INFLIBNET and Google Scholar were also used. The secondary data used are pooled in nature, which is the mixture of time series and cross section data. 5.2. Primary data and Sample Design Primary data were collected from 400 households with planned schedule from Malappuram, which is one of the low HDI districts of Kerala (HDR, Kerala 2005). For the study, 2 municipalities and 2 panchayaths were purposively selected. To represent urban as well as non-coastal households, Perinthalmanna municipality and Angadippuram grama panchayath were selected. To represent rural as well as coastal households, Ponnani municipality and Tanur panchayath were chosen. From each Panchayath and municipality 5 wards were randomly selected. From each randomly selected ward, 20 households were randomly surveyed. The total sample consists of 400 households. The primary data used for the study are cross section in nature, which is the data on one or more variables collected at the same point of time. 6. Methodology The study is descriptive and analytical in nature. For the analysis of the objectives, a socio-economic status index was constructed based on the variables; per capita monthly income, average year of education of the households, size of households and method of disposal of wastewater. The construction of socio-economic index is according to the general formula applied for the construction of Human Development Index by the United Nations Development Programme (UNDP). The index was standardized by the formula 144

The cross tabulation, sub-divided bar diagram, Chi Square and ANOVA were used to analyze the variation in socio-economic status among different communities, income and education classes. 7. Socio economic Status of the Sample Households - An Analysis The distribution of sample households based on socio economic status (table 1) shows that, 36.5 percent have low-level socio economic status, 36.75 percent have medium and 26.75 percent households have a high-level socio economic status. The classification based on coastal and non-coastal shows that there is no significant disparity socio-economic status. Table 1: Distribution of Households based on Socio Economic Status Socio-economic Status Non coastal Coastal Number Percent Number Percent Number Percent Low 73 36.5 73 36.5 146 36.5 Medium 75 37.5 72 36 147 36.75 High 52 26 55 27.5 107 26.75 200 100 200 100 400 100 Source: Sample Survey 2014 8. Occupation and Socio economic Status The distribution of households on occupation of head of households and socio economic status reveals that, 80 percent government employed head of households have high socio economic status (table 2) and among the head of households with the occupation coolie, it is only 17 percent. Table 2: Distribution of Households by Occupation of Head of Households and Socio Economic Status Occupation of Head of household Socio economic status Low Medium High No. Percent Number Percent Number Percent Number Percent Self employed 17 30 28 49 12 21 57 14.25 Business 4 10.25 15 38.46 20 51.28 39 9.75 Govt. employees 0 0 3 20 12 80 15 3.75 Coolie 48 44 42 38.5 19 17.43 109 27.25 NRIs 27 39.7 22 32.35 19 27.94 68 17 Housewife and unemployed 50 44.64 37 33 25 22.32 112 28 146 -- 147 -- 107 -- 400 100 Source; Sample survey 2014 9. Income Versus Socio economic Status Table 3 illustrates the distribution of households based on socio economic index and level of per capita monthly income. Table 3: Distribution of Households on Socio Economic Status and Per capita Monthly Income Level of Per Capita Monthly Income Level of Socio Economic Status Low Medium High No. Percent No. Percent No. Percent Number Percent Low 132 65 68 33.5 3 1.5 203 50.75 Medium 14 13 66 61 28 26 108 27 Source Sample survey 2014 High 0 0 13 14.6 76 85.4 89 22.25 146 36.5 147 36.75 107 25.75 400 100 145

In the sample area, 50.75 percent (203 households) have low-level per capita income. Out of them, 65 percent (132) have lowlevel socio economic status, 33.5 percent (68) have Medium socio economic status and 1.5 percent (3) has high socio economic status. Out of total sample households, 108 (27%) have medium level per capita monthly income. Out of them, 14 (13%) have low-level socio economics status, 66(61%) come under the medium level in socio economic status and 28(26%) enjoys high social economic status. And among 89 (22.25%) households with high level of per capita monthly income, no households are in low socio-economic status group while 13 (14.6%) and 76(85.4%) are in medium and high level socio economic status respectively. This illustration shows that the socio economic status is high where the per capita monthly income is high and vice versa. 10. Size of Households Versus Socio economic Status The distribution of households according to socio economic status and size of households (table. 4) confirms that among small size family, 33.5 percent have high socio-economic status. It is only 22.56 percent among medium size family and 0 percent among large size family. It proves that socio economic status and size of family is inversely correlated. Size of Household Table: 4: Distribution of households on size of households and socio economic status Socio Economic Status Low Percent Medium Percent High Percent Percent Small 56 26.8 83 39.7 70 33.5 209 52.25 Medium 70 42.68 57 34.76 37 22.56 164 41 Large 20 74 7 26 0 0 27 6.75 All types 146 36.5 147 36.75 107 26.75 400 100 Source: Sample survey 2014 11. Education Versus Socio economic Status of Households Education is a prime criterion of socio economic status of households. Therefore, it will be positively associated with the socio economic status. The socio economic status among the households with different education level exhibits that 66 percent of plus two level educated households, 89 percent of graduate level educated households and 100 percent post graduate level educated households have high level of socio economic status in the study area (Fig.1). At the same time, only 1.4 percent of primary level educated households and 23 percent of high school level educated households have high socio economic status. Figure 1: Percentage Distribution of Households on Socio Economic Status and Level of Education 100% 90% 80% 70% 60% 50% 40% 30% 20% 10% 0% 43 56 Source: Sample Survey result 2014 1 23 41 36 66 30 4 11 0 0 primary High school Plus two Graduation Post graduation The figure 1 exhibits that as level of education of households improved, the socio-economic status of households were also improved. 89 100 High Medium Low 146

12. Socio-economic Status among Different Communities The socio-economic status of different communities shows that, among Christina community, 30.76 percent households have low socio-economic status, it is 42 percent and 32.5% among Hindu, and Muslim communities respectively (table 5). Among Christian community, 34.62 percent households have medium socio-economic status while it is 28 percent and 44.5 percent among Hindu and Muslim communities respectively. Christian community has high percentage of households with high socio-economic status, ie., 34.62 percent while it is 30 percent and 23 percent among Hindu and Muslim communities respectively. Table.5: Community versus Socio-economic status Socio-economic Status Community Low % Medium % High % Christian 8 30.76 9 34.62 9 34.62 26 Hindu 73 42 49 28 52 30 174 Muslim 65 32.5 89 44.5 46 23 200 146 36.5 147 36.75 107 26.75 400 Source: Sample survey 2014 Our null hypothesis is no significant association in socio economic status of households among different communities. The value of chi square is 11.615 Degree of freedom is 4 5% level of significance is 0.020 Since the significance value is less than 0.05, we rejected the null hypothesis. And it is concluded that there is significant association among communities in socio-economic status. 13. Variation in Socio-economic Index Values between Different Income and Education Groups The variation in socio-economic index value among different per capita monthly income groups and education groups were examined by applying the Analysis of Variance (ANOVA). The result shows in tables 6 and 7. Table. 6: ANOVA table showing the Significance of Socio-economic Index according to Per capita Income Level of Households Index Source of variation Sum of squares D.f Socio- Economic index Between groups 12.772 2 With in groups 7.109 397 19.881 399 Mean squares 6.386 0.018 F Significance 356.612 0.000 Source: Developed from sample data From the ANOVA table, it is clear that in the case of socio-economic index, the variation between groups when households are classified on the basis of per capita monthly income are highly significant since the level of significance is less than 0.05 and we rejected the H 0. Table. 7: ANOVA table of Socio-economic Index versus Education Level of Households Index Source of variation Sum of squares D.f Mean squares F Significance Between groups 10.065 4 Socio- With in groups 9.816 395 2.516 101.264 0.000 Economic 0.025 index 19.881 399 Source: Developed from sample data 147

The ANOVA table shows that, in the case of socio-economic index, the variation between groups when households are classified based on education level are highly significant as the level of significance is less than 0.05 and we rejected the H 0. 14. Conclusion Malappuram district is the most populous district with least work participation rate. There is no significant difference in socio-economic status between coastal and non-coastal areas. The socio-economic status is high among government employees compared any other occupational groups. The socio-economic status is high among the households whose per capita monthly income is high. The socio-economic status is high among the small size households compared to large size households. The level of education of households and socio-economic status are directly related. Among the post-graduated households, 100 percent have high socioeconomic status. The high socio-economic status is more in percentage among Christian community households compared to Hindu and Muslim communities. The ANOVA result clearly shows that, in socio-economic index, the variation between groups when households are classified based on per capita income and education are highly significant. The Chi Square result reveals that there is significant association between socio-economic index and community. References: 1. Beevi Haseena (2012), Health Status of Muslim Women in Kerala PhD Thesis submitted to Mahatma Gandhi University in 2012. 2. Census of India (2011), Provisional Population totals-kerala Series 33, Ministry of Home affairs Government of India. 3. Gangadharan.K. (2007), Health for all, Kerala Perspective, Article, Kerala Calling January 2007 4. Government of Kerala, Economic Review (2011), State Planning Board, Thiruvananthapuram 5. Government of Kerala, Economic Review (2012), State Planning Board, Thiruvananthapuram 6. Government of Kerala, Economic Review (2014), State Planning Board, Thiruvananthapuram 7. Kerala Human Development Report (2005). CDS Thiruvananthapuram. 8. Navaneethan et.al., (2006), Pattern and Determinants of Morbidity in Kerala. Paper presented at International Conference on Emerging Population Issues in Asia Pacific Region, 2006. 9. Salim Abdul (1997), Sameeksha, Annual Magazine, E.M.E.A. College Kondotti. ********* 148