This study focuses on total factor productivity growth and its decomposition of commercial banks in Sri Lanka. For this purpose, two state banks , Bank of Ceylon and Peoples' bank and four private banks, namely, Commercial bank, Seylan bank, Hatton National Bank and Sampath were selected over the period [2009][2010][2011][2012]. By using Data envelopment analysis (DEA) total factor productivity and its components were measured in terms of efficiency change, technical efficiency change, pure efficiency change and scale change. The data related to interest income and amount of loans which were considered as two outputs and amount of deposits, total assets, number of staff and interest expenses considered as four inputs were collected from annual reports of Colombo Stock Exchange (CSE) in Sri Lanka and were analyzed on the assumption of output oriented method with constant returns to scale. It was found that, all six banks operate averagely at 87.2 percent of overall efficiency and it reveals the less performance of the banks. This less performance was achieved due to the less progress in technical change than efficiency change and the finding highlights that technical change has been the main constraint to achieve a high level of total factor productivity of commercial banks in Sri Lanka. Among the private banks, Seylan bank has the highest efficiency of 1.033 than other banks and among the state banks, Peoples' bank have the values of 0.773than Bank of Ceylon. The overall results concluded that comparatively selected private banks are more efficient than state banks in the study period in Sri Lanka.

This study investigates the impact of socio-economic characteristics of the farmers and its impact on their loans resettlement behavior in the People's Bank, Puttalam branch in Sri Lanka. Secondary data were collected from the bank officials and the data were analyzed with 100 applicants who are cultivating paddy as a major crop and other field crops during the Maha and Yala season 2011/2012. This study was analyzed using descriptive statistics, Tobit model and in addition to that elasticity of the loan repayment ratio also measured. The estimated Tobit regression model indicated that family members and secondary education were significantly positive influence on the farmers' repayment behavior while loan disbursement has negative influence on their behavior in Sri Lanka. Other independent variables namely gender, age, civil status, major crops, income and higher level of education of the beneficiaries were not statistically significant influence on the farmers' behavior in the above bank branch in Sri Lanka. The elasticity of the loan repayment performance for the variables also were calculated at the mean values and according to that number of family members, size of loans and secondary education were statistically significant. The overall results revealed that, the bank managers should considered the above characters of the borrowers to increase the probability of repayment ratio and thus it will help them to improve the efficiency of lending decision of the bank loans in future.

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Technical efficiency means the effectiveness which a given set of inputs used to produce a given output and it helps to produce the maximum output using minimum quantity of inputs for any firm or farm products. The objectives of this study are to estimate the Hicks -Moorsteen index and examine the impact of demographic, economic, farming and environmental characteristics on total factor productive efficiency index. Further, this study evaluate the overall performance of paddy farmers (n= 200) and identify the factors affecting the efficiency using twostage Data Envelopment Analysis (DEA) during 2019/2020 period in Mullaitivu district of Sri Lanka. Hicks -Moorsteen index showed that among the components of the index, 94% of the highest mean value was attained in Input Oriented Technical Efficiency (ITE) followed by 93% of efficiency was attained in Output Oriented Scale Efficiency (OSE). Tobit regression results suggested that education, availability of training and destroy the crops whether the crops were damaged by environmental factors were significantly affecting the Hicks -Moorsteen index. Further, results of two stage input-oriented DEA revealed that on average the overall technical efficiency of paddy farms was nearly 42%, scale efficiency was nearly 45% and variable returns to scale technical efficiency was nearly 93%. The Tobit regression results showed that, education, land ownership, amount of savings, loan size, land quality and farm income were positively impact on overall technical efficiency while experience, ownership of land, amount of savings and destroy the crops whether the crops were damaged by environmental factors significantly affected on technical efficiency. Conversely, scale efficiency of paddy farming mostly influenced by education, land ownership, saving amount, loan size, quality of land and farm. The paper concludes that both input oriented technical efficiency and output oriented scale efficiency need to be improved further as well as scale efficiency mostly affected by economic and farming characteristics in the study.

The objective of the study is to examine the factors which determine the credit worthiness and loan repayment performance among the small-holder farmers in Vavuniya district in Sri Lanka. A sample of 113 small -holder agricultural loan borrowers from five villages who get the loans from SANASA TCCS served as the respondents in the study. A set of structured questionnaire was used to collect the primary data from the respondents who lives in the five villages located in Marukkarambali GS division in Vavuniya district, Sri Lanka during the period of 2018/2019. The dependent variable is the credit worthiness measured as binary variables where it takes as one for defaulters and zero for non -defaulters and the selected demographic characters, farming characters and farmers' attributes were taken as explanatory variables in the study. To identify the above characters on the credit worthiness of the farmers' descriptive statistics, and binary probit model were employed. The results of the descriptive statistics revealed that, 43.4% of the respondents belonged to the defaulters while 56.6% of them belonged to the non -defaulters in the study. Estimated results of the probit model suggest that among the demographic characteristics, age of the farmers, levels of education, number of family members positively influenced the loan repayment performance of smallholder farmers, while among farming characters, income, farm size, land ownership, farming experience, off-farm activities, purpose of loan and possibility of crop failure were positively impact on credit worthiness and repayment performance at different significant levels. On the other hand, knowledge about the loan and responsible guarantors were the major factors of farmers' attributes influencing the repayment performance in the study. The overall findings of the study may help to the farmers as well as to the micro finance institutions to predict the repayment behaviour of the new loan applicants and to make the decision to grant loans in future.