This dissertation explores the performance of manufacturers of exportables using macro- and micro-level data. Empirical analysis has been carried out at industry level to estimate technical efficiencies using Stochastic Frontier Analysis as well as Data Envelopment Analysis. Stochastic Frontier Analysis is used to estimate Translog as well as Cobb-Douglass production frontier. The Data Envelopment Analysis technique is used under the assumptions of Constant Returns to Scale and Variable Returns to Scale. The key findings indicate that technical efficiency of manufacturing industries is in general low, and there is an ample room for improvement. Industries showing high technical efficiency include Tobacco Products, Refined Petroleum Products, Carpets & Rugs, and Meat & Meat Products. Industries showing low technical efficiency include Refractory Ceramic Products, Electricity Distribution. & Control apparatus, Fish & Fish Products, Basic Precious Metals, and Aluminum & its Products. Exporting industries are not found to be significantly more efficient than other industries. This indicates an ample scope for higher exports by improving technical efficiency. Improvements in entrepreneurial skills are recommended to increase technical efficiencies. Firm-level analyses are performed on a sample of manufacturers of exporting goods to determine firm-specific characteristics of export performance as well as those of market and client oriented technology adoption. Ordinary Least Squares and Logit/Probit regression techniques have been employed in these analyses. The analyses show that FDI as well as investment in market/client-oriented technologies will increase the export performance at firm level. Facilitation of domestic testing labs is needed to meet certification needs of exporters at low cost to boost their export potential. Industrial clusters need to be developed and strengthened, with a focus on export-oriented industries. Entrepreneurial/managerial skills are needed to be enhanced to improve export performance.