From the couple of decades remittances have been playing an important role in the Nepalese economy. For people of rural areas even for the urban households, remittance is becoming the major source of livelihood. Therefore, this study considers remittance as a focus variable with an aim to assess the link between remittance and growth. Autoregressive distributed lag (ARDL) model is applied to examine the relationship between remittance and growth. All the variables included in the analysis became stationary after first difference. The result of bound test confirms that the variables are cointegrated. It means the variables have long run relationship. The empirical result reveals that one percent increase in remittance increases the GDP by 0.36 percent in the long run. Similarly, the gross fixed capital formation, secondary school enrolment and the trade openness and per capita GDP have positive relationship. It implies that one percent increase in capital, labor and trade openness increases the per capita GDP by 0.82 percent, 0.46 percent and 0.30 percent in the long run respectively.

With the application of Robust Regression Method, this paper attempts to estimate the production function for manufacturing industries of Nepal. In this endeavour, the production function for Furniture and Pharmaceutical industries have been estimated using cross-section data of the Census of Manufacturing Establishment (CME) 2011/2012. The coefficients of log-linear form of Cobb-Douglas (C-D) production function reveal that the selected manufacturing industries are operating with decreasing returns to scales. The labour coefficients of both industries are found to be statistically insignificant. Negative labour coefficient of Pharmaceutical Industry indicates capital intensive nature of the production and minimal contribution of labour inputs. Although positive and significant, capital coefficients indicate both industries were running with decreasing returns to capital inputs. Total Factor Productivity (TFP) representing the state of technology and factors other than labour and capital found to be instrumental and significant for both the industries.

The paper estimates and assesses the technical efficiency at individual and
aggregate levels and categorizes groups of banks at various ranges of efficiency.
The commercial and development banks established before 2005 in Nepal has been
considered as the population of the study and 20 banks are selected using
systematic random sampling. The 180 observations of nine year’s panel data from
FY 2006/07 to FY 2014/15 has been used. Stochastic Frontier Approach is used
taking three input variables i.e. capital, deposit and human resource cost, and one
output variable i.e. loans and advance of sampled banks for analysis. The study
found that the average technical efficiency (TE) by nature of banks provide
commercial banks as the more efficient than development banks. The joint venture
banks are the most efficient than other categories of banks. The average efficiency
of banks established inside the Kathmandu valley (Head Office located inside
Kathmandu) is lower than the average efficiency of banks established outside the
Kathmandu valley (Head Office located outside Kathmandu). Similarly, the banks
established after 1995 are found more efficient than the banks established before
1995. The study has important implications for the policymakers to take corrective
actions for improving the efficiency of the Nepalese banking sector with respect to
human resource policy, deposit collection policy and loan management policy.