Entrepreneurship, Innovation, and Aging: A Conceptual Framework and Empirical Evaluation

Entrepreneurship, Innovation, and Aging: A Conceptual Framework and Empirical Evaluation

Jenifer Paola Garza Puentes, Sherine El Hag
Copyright: © 2020 |Pages: 13
DOI: 10.4018/978-1-7998-2019-2.ch016
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The entrepreneurship processes is an important process in the development and mature economies. The Schumpeterian logic of the classic entrepreneurship analyses and considers an evident relation between the rates of innovation and a positive effect on economic growth. The technological progress is another factor to consider in the entrepreneurship procedure. It especially affects the business innovation process and the personal innovation process of the entrepreneur. Both innovation and technology, apparently, are not characteristics of old entrepreneurs. For this reason, in this chapter, the authors sought to contribute to the literature by explicitly connecting the age structure with innovative results as measured by technological progress.
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Our conceptual framework builds upon the contribution of Lancia & Parolo (2012), where an aging society confronts a trade-off dilemma between human capital accumulation and innovation policy. We also rely on Ang & Madsen (2015), who find that aging in OECD countries does not necessarily decelerate technological progress as highly educated individuals tend to have longer stays in the working population.

Key Terms in this Chapter

Per Capita Income: It measures the average income earned per person in a specified area and year.

Density Function: It is a function used in Statistics for finding probabilities associated with a continuous random variable.

Ordinary Least Squares: It is an econometric method that minimizes the sum of vertical distances between the responses observed in the sample and the model responses.

Higher Education: Also called as tertiary or post-secondary education, it represents levels 6,7 and 8 of the 2011 version of the International Standard Classification of Education structure.

Heteroskedasticity: It occurs when the variance of the errors is not constant in all the observations made

Labor Force Participation: It is defined by the section of the working population between 18 and 64 years of age who are currently employed or are seeking employment.

Log-Log Regression: It is a regression model where the outcome and at least one predictor are log-transformed.

The Breusch-Pagan Test: It is a statistical test used for testing heteroscedasticity of errors in linear regressions.

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