Financial Inclusion of The Small and Marginal Farmers by the Banking Sector in Kerala

Financial inclusion for inclusive growth is central to the developmental philosophy of most of the nations over the past decade. It has been a priority for policy makers and regulators in financial sector development for improving access and usage of financial services to achieve comprehensive financial inclusion. The initiatives taken towards financial inclusion can promote a more effective and efficient process to achieve significant improvements in financial inclusion are to establish and achieve shared and sustainable development and growth. Realising this, an increasing number of countries are committing to promote financial inclusion, encouraged by the growing body of country level experiences (World Bank, 2012). Financial inclusion basically means, broad based growth through participation as well as sharing the benefits from the growth process along with the under privileged and marginal segments of the economy. Evidence suggests that it has substantial benefits for equitable and sustainable growth. Inclusive growth ensures that while economy grows rapidly, all segments of society are involved in this growth process, ensuring equal opportunities, devoid of any regional or sectoral disparitiesIt is widely acknowledged that the objective ofinclusive growth is accomplished through the process of financial inclusion. Financial inclusion envisages bringing everyone, irrespective of financial status, into the banking fold for the individual progress and development and thereby achieving comprehensive growth with equity

Factors Underlying Heterogeneous Individual Growth in Macrobrachium rosenbergii and the Effect of Size Heterogeneity on Economic Feasibility of Farming in Kuttanad ( Kerala )

School of Industrial Fisheries, Cochin University of Science and Technology

Regression models for bivariate survival data

Multivariate lifetime data arise in various forms including recurrent event data when individuals are followed to observe the sequence of occurrences of a certain type of event; correlated lifetime when an individual is followed for the occurrence of two or more types of events, or when distinct individuals have dependent event times. In most studies there are covariates such as treatments, group indicators, individual characteristics, or environmental conditions, whose relationship to lifetime is of interest. This leads to a consideration of regression models.The well known Cox proportional hazards model and its variations, using the marginal hazard functions employed for the analysis of multivariate survival data in literature are not sufficient to explain the complete dependence structure of pair of lifetimes on the covariate vector. Motivated by this, in Chapter 2, we introduced a bivariate proportional hazards model using vector hazard function of Johnson and Kotz (1975), in which the covariates under study have different effect on two components of the vector hazard function. The proposed model is useful in real life situations to study the dependence structure of pair of lifetimes on the covariate vector . The well known partial likelihood approach is used for the estimation of parameter vectors. We then introduced a bivariate proportional hazards model for gap times of recurrent events in Chapter 3. The model incorporates both marginal and joint dependence of the distribution of gap times on the covariate vector . In many fields of application, mean residual life function is considered superior concept than the hazard function. Motivated by this, in Chapter 4, we considered a new semi-parametric model, bivariate proportional mean residual life time model, to assess the relationship between mean residual life and covariates for gap time of recurrent events. The counting process approach is used for the inference procedures of the gap time of recurrent events. In many survival studies, the distribution of lifetime may depend on the distribution of censoring time. In Chapter 5, we introduced a proportional hazards model for duration times and developed inference procedures under dependent (informative) censoring. In Chapter 6, we introduced a bivariate proportional hazards model for competing risks data under right censoring. The asymptotic properties of the estimators of the parameters of different models developed in previous chapters, were studied. The proposed models were applied to various real life situations.

Risk Assessment of Rooftop- Collected Rainwater for Individual Household and Community Use in Central Kerala, India

Water quality of rooftop-collected rainwater is an issue of increased interest particularly in developing countries where the collected water is used as a source of drinking water. Bacteriological and chemical parameters of 25 samples of rooftop-harvested rainwater stored in ferrocement tanks were analyzed in the study described in this article. Except for the pH and lower dissolved oxygen levels, all other physicochemical parameters were within World Health Organization guidelines. Bacteriological results revealed that the rooftop-harvested rainwater stored in tanks does not often meet the bacteriological quality standards prescribed for drinking water. Fifty percent of samples of harvested rainwater for rural and urban community use and 20% of the samples for individual household use showed the presence of E. coli. Fecal coliform/fecal streptococci ratios revealed nonhuman animal sources of fecal pollution. Risk assessment of bacterial isolates from the harvested rainwater showed high resistance to ampicillin, erythromycin, penicillin, and vancomycin. Multiple antibiotic resistance (MAR) indexing of the isolates and elucidation of the resistance patterns revealed that 73% of the isolates exhibited MAR