Using the rich micro data set of the World Bank Investment Climate Survey, this paper examines the determinants of productivity among manufacturing firms in the context of a least developed country, Tanzania. In particular it seeks to evaluate the importance of technological variables - such as R&D, education and training, innovation, foreign ownership, licensing and ISO certification - and institutional variables – such as access to credit, health of the workforce, regulation and business support services. Among the technological variables, R&D, and innovations in the form of new products or processes fail to produce any significant impact, and only foreign ownership, ISO certification and high education of the management appear to affect productivity. Some of the institutional variables on the contrary are highly significant and robust to different specifications of the model. As such, formal credit constraints, administrative burdens related to regulations and a lack of business support services seem to depress productivity, while membership of a business association produces the opposite effect. The results of a quantile regression further indicate that the educational level of the managers and access to formal credit are significant for the less productive firms only, whereas for the more productive firms it is having an ISO certification or being a member of a business association that are the significant determinants.
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Paper provided by United Nations University, Maastricht Economic and social Research and training centre on Innovation and Technology in its series UNU-MERIT Working Paper Series with number
037.
Find related papers by JEL classification: O12 - Economic Development, Technological Change, and Growth - - Economic Development - - - Microeconomic Analyses of Economic Development D24 - Microeconomics - - Production and Organizations - - - Production; Capital and Total Factor Productivity; Capacity C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models
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