Proceedings of 7th Annual American Business Research Conference

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Proceedings of 7th Annual American Business Research Conference
23 - 24 July 2015, Sheraton LaGuardia East Hotel, New York, USA, ISBN: 978-1-922069-79-5
An Empirical Study on the Impact of Technology Change on
Income Distribution in U.S. States
Ashraf Eid
This paper adds to the R&D literature by focusing on the social considerations of R&D
investment and investigates the impact of technological changes on poverty and
unemployment rates in 50 U.S. states plus the District of Columbia during the period
1987-2013. We use two measures of technological changes: first, R&D performed by the
federal government, industrial, and academic sectors in each state and, second, the
number of patents granted by the United States Patent and Trade Mark Office (USPTO)
for each state. Results of the multilevel mixed-effects model suggest a positive and
significant relationship between regional R&D expenditure performed by the industrial
sector and both unemployment and poverty rates. Results did not change when using the
aggregate R&D expenditure instead of the disaggregated R&D figures. On the contrary,
the number of patent grants, the second measure of technological changes, is found to
be negatively related to both poverty and unemployment rates. This contradictory result
could be explained as follows: technological changes do not benefit the poor and
unemployed people until a successful R&D investment is granted a patent which usually
takes few years. This means that there is a time lag between technology improvement
operations, through R&D activities, and the observed benefits for the poor and
unemployed people. The main conclusion of this paper could be summarized in the
following statement: while regional R&D activities divert resources away from poverty and
unemployment programs in the short run, their long run effect, after firms are granted
patents, is found to be in favor of poor and unemployed people.
Keywords: Technology Change, Research and Development, Poverty, Unemployment,
Mixed-Effect Model.
JEL Classification: O33, I32, C23.
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Dr. Ashraf Eid, Assistant Professor of Economics, Finance and Economics Department, College of
Business and Economics, Qatar University, Email: [email protected]
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