productivity research papers

Amani Elnasri University of New South Wales - Australian School of Business - School of EconomicsKevin J. Fox University of New South Wales - Australian School of Business - School of Economics February 2014 UNSW Australian School of Business Research Paper No. 2014-08 Abstract:      This paper examines the impact of investment in research and innovation on Australian market sector productivity. While previous studies have largely focused on a narrow class of private sector intangible assets as a source of productivity gains, this paper shows that there is a broad range of other business sector intangible assets that can significantly affect productivity. Moreover, the paper pays special attention to the role played by public support for research and innovation in the economy. The empirical results suggest that there are significant spillovers to productivity from public sector R&D spending on research agencies and higher education. No evidence is found for productivity spillovers from indirect public support for the business enterprise sector, civil sector or defence R&D. These findings could have implications for government innovation policy as they provide insights into possible productivity gains from government funding reallocations. Number of Pages in PDF File: 49 Keywords: Productivity, Innovation, Intangible assets, Public support JEL Classification: O3, O4 , H4 working papers series Suggested CitationElnasri, Amani and Fox, Kevin J., The Contribution of Research and Innovation to Productivity and Economic Growth (February 2014). UNSW Australian School of Business Research Paper No. 2014-08. Available at SSRN: or.
Skip to Content DPRPD DPRPD Working Papers Working Papers Giandrea, Michael D. The Impact of Hours Flexibility on Career Employment, Bridge Jobs, and the Timing of Retirement, with Kevin E. Cahill and Joseph F. Quinn, 2014) U.S. Bureau of Labor Statistics Working Paper No. 472. Are Gender Differences Emerging in the Retirement Patterns of the Early Boomers?, with Kevin E. Cahill and Joseph F. Quinn, 2013) U.S. Bureau of Labor Statistics Working Paper No. 468. New Evidence on Self-Employment Transitions Among Older Americans with Career Jobs, with Kevin E. Cahill and Joseph F. Quinn, (2013) U.S. Bureau of Labor Statistics Working Paper No. 463. The Relationship between Work Decisions and Location Later in life, with Kevin E. Cahill and Joseph F. Quinn, (2012) U.S. Bureau of Labor Statistics Working Paper No. 458. Employment Patterns and Determinants Among Older Individuals with a History of Short-Duration Jobs, with Kevin E. Cahill and Joseph F. Quinn, (2009) U.S. Bureau of Labor Statistics Working Paper No. 440. How Does Occupational Status Impact Bridge Job Prevalence?, with Kevin E. Cahill and Joseph F. Quinn, (2011) U.S. Bureau of Labor Statistics Working Paper No. 447. Self Employment Among Older American Workers, (with Kevin E. Cahill and Joseph F. Quinn). BLS Working Paper No. 418, 2008. An Update on Bridge Jobs: The HRS War Babies, (with Kevin E. Cahill and Joseph F. Quinn). BLS Working Paper No. 407, 2008. A Micro-level Analysis of Recent Increases in Labor Force Participation among Older Workers, (with Kevin E. Cahill and Joseph F. Quinn). BLS Working Paper No. 400, 2006. Industry Competition and Total Factor Productivity Growth, BLS Working Paper No. 399, 2006. Are Traditional Retirements a Thing of the Past? New Evidence on Retirement Patterns and Bridge Jobs, (with Kevin E. Cahill and Joseph F. Quinn). BLS Working Paper No. 384, 2005. Publications by.
NBER Working Paper No. 6696 Issued in August 1998 NBER Program(s):   PR This paper studies the links between productivity, innovation and research at th level. We introduce three new features: (i) A structural model that explains pro by innovation output, and innovation output by research investment; (ii) New dat manufacturing firms, including the number of European patents and the percentage sales, as well as firm-level demand pull and technology push indicators; (iii) E which correct for selectivity and simultaneity biases and take into account the features of the available data: only a small proportion of firms engage in resea apply for patents; productivity, innovation and research are endogenously determ investment and capital are truncated variables, patents are count data and innov We find that using the more widespread methods, and the more usual data and mode may lead to sensibly different estimates. We find in particular that simultaneit with selectivity, and that both sources of biases must be taken into account tog results are consistent with many of the stylized facts of the empirical literatu of engaging in research (R&D) for a firm increases with its size (number of empl share and diversification, and with the demand pull and technology push indicato capital intensity) of a firm engaged in research increases with the same variabl research capital being strictly proportional to size). The firm innovation outpu patent numbers or innovative sales, rises with its research effort and with the indicators, either directly or indirectly through their effects on research. Fin correlates positively with an higher innovation output, even when controlling fo the skill composition of labor as well as for physical capital intensity.    (1836 K) Machine-readable bibliographic record - MARC, RIS, BibTeX Document Object Identifier (DOI): 10.3386/w6696 Published.