Idea Transcript
TITLE
Senior Entrepreneurship: Empirical Evidence of the Effect of Aging on Entrepreneurial Intent AUTHORS
Marc Duhamel, Universite du Quebec a Trois-Rivieres, CA Murat Erogul, Thompson Rivers University, CA Nathan Greidanus, Unviersity of Manitoba, CA Etienne St-Jean, Universite du Quebec a Trois-Rivieres, CA
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Senior Entrepreneurship: Empirical Evidence of the Effect of Aging on Entrepreneurial Intent There is a common belief that entrepreneurship is a young man’s game (Lévesque & Minniti, 2006). As individuals age, the relative returns of entrepreneurship are reduced and it is less likely that people in older demographics become entrepreneurs (Lévesque & Minniti, 2011; Parker, 2009; Tervo, 2015). At the same time, there are increasing numbers of people entering these older demographic ranges (e.g. ageing baby boomers, increased life expectancy) and increasing opportunities and incentives for people in more senior age ranges to consider entrepreneurship (insufficient pension income, chance to leverage accumulated social and human capital (Henley, 2007; Singh and DeNoble, 2003 ; Weber and Schaper, 2004 ). Despite the increasing salience and opportunities, there remains a paucity of research investigating the interaction of age and entrepreneurship. The current paper aims to fill this gap by investigating how aging influences both entrepreneurial intention1 and the relationship of entrepreneurial attitudes on intentions. Le´vesque and Minniti, (2006) build on Becker’s theory of time allocation (Becker, 1965 ), to show that after a threshold age is reached, an individual willingness to invest time in starting new firms declines. Levesque and Minnit’s (2006) model of employment status choice includes age, risk aversion and wealth, are shown to be important determinants of an individual’s choice of whether or not to become an entrepreneur. Based on these considerations we investigate the formation of entrepreneurial intentions in seniors over the age of 55 by adapting Levesque and Minniti’s (2006) model. We estimate the link between age, selecting a dimension of background variables (e.g. gender, household income, employment status, education attainment, and regional factors) in relation to entrepreneurial intention. We use age both as a predictor and moderator to measure cognitive and physical functions and abilities such as the perception of opportunity, skills, prior experience and fear of failure. The contribution of this article is threefold. First, we develop theoretical hypotheses of the formation of entrepreneurial intentions by examining age as both a predictor of entrepreneurial intent and moderator of an individual’s perception of entrepreneurial opportunities, failure or necessary skills within the framework of the TPB. Second, using a unique dataset of over 8,000 individuals from the Canadian Global Entrepreneurship Monitor, of which more than a third of the observations on entrepreneurial intent are from individuals over the age of 55 years old, we provide empirical evidence of a robust negative nonlinear relationship between an individual’s age and entrepreneurial intentions 01 1 We operationalize entrepreneurial intention as the expectation of an individual to start a new business including any type of self-employment, alone or with others, within the next three years.
ICSB 2016: Senior Entrepreneurship 2 and weak statistical evidence for a moderating influence of age on an individual’s perception of his or her entrepreneurial skills. Thirdly, as argued by Lévesque and Minitti (2006), these findings are important to policy makers around the globe.2 An aging population can not only drag an economy’s labour productivity and economic growth potential and squeeze its fiscal capacity but also bog down a country’s engine of growth (e.g. Zhang, 2008). Background Literature In terms of defining “senior” entrepreneurs, the extant literature losely defines the category as people aged approximately 50-55 years and older starting a business (e.g., Lorrain and Raymond, 1991; Curran and Blackburn, 2001; Hart et al., 2004; Kautonen et al., 2008; Harms, et al., 2014; Jarnefelt, 2011), which is in line with definitions of aged (senior) workers (Tervo, 2015). In the current paper, we avoid subjective discrete categorizations of senior entrepreneurs and prefer to focus on the relationship between entrepreneurial intention and age. Previous research at the intersection of ageing and entrepreneurial intentions has focussed on the initial phase of becoming an entrepreneur (Shapero and Sokol, 1982; Amit and Muller, 1995; van Praag and van Ophem, 1995). For example, older individuals like others can be both ‘pulled’ and ‘pushed’ to self-employment and other entrepreneurial activities (e.g. Harms et al., 2014; Dyer, 1994), with the effect of age on the probability of engaging in some form of entrepreneurship following an inverse Ushape. That is, the probability of an individual becoming an entrepreneur increases with age up to a certain point (usually between 35 and 44 years) and decreases thereafter (Le´vesque and Minniti, 2006; Parker, 2009) while the opportunity to do so increases (Blanchflower, et al. 2001 ; van Praag and van Ophem, 1995). Others suggest that the role of the socio-cultural perception of the economic potential of aging people to be a factor that may influence their enterprising propensities (Weber and Schaper, 2004; Kautonen, et al., 2008; Kautonen, et al., 2011). Drawing on the extant literature we develop and test a model that uses age both as a predictor and moderator of the relationship between cognitive indicators and intention. We assume the interaction of time on age moderates the perceived level and cost of reward as well as the perceived value of opportunity (i.e., push/pull), fear of failure and ability (i.e., knowledge and skills) affects the strength of entrepreneurial intention. 01 2 For a recent example see the Australian Productivity Commission report « An ageing Australia : Preparing for the Future » (Australia, 2013). Also, see Beach (2008) and Auerbach et al. (1989) for earlier discussions of the consequence of aging for Canada, Japan, Germany, Sweden and the United-States. See Feyer (2007) for cross country empirical evidence of the effects of aging on aggregate productivity growth.
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Method Our data is drawn from individual responses of the Canadian Global Entrepreneurship Monitor (GEM) Adult Population Survey (APS) for the periods of 2013-2015 (n=8918). The Canadian GEM is a population weighted sample based survey of entrepreneurial aspirations, attitudes and activities. While in most countries data is sampled from the standard labour force population (i.e. 18-65 years range), the Canadian sample offers three years of data that includes individuals 18-99 year olds and offers unique insight into senior entrepreneurs, in particular the 55 years and older category (34% of our sample is over 55 and 18% over 65). We model entrepreneurial intentions, as measured by a positive binary response (yi = 1) to the question ‘Are you, alone or with others, expecting to start a new business, including any type of selfemployment, within the next three years?’ The perception variables, xi, include the individual’s perception of entrepreneurial opportunities in the region, the respondents perceived required knowledge, skills and experience to start a new business and the respondent’s perception whether the fear of failure would prevent him or her from starting a business. Results and Discussion As shown in table I, descriptive statistics reveal that individuals in the young group category (18-55) are 2.5 times more likely to intend to start a new business over the next three years period than the 55+ seniors and 5 times more likely than the 65+ seniors. All other aspects of entrepreneurial perceptions and attitudes also show a decreasing pattern with age but not as marked as the stated intention to start a new business. Pairwise Student’s t-test reject the null hypothesis of no differences between the means of each group (at the 5 percent degree of statistical significance) except for the knowledge, skills, and experience between the young and 55 years old and over seniors. INSERT TALBE I HERE To investigate more deeply the factors that could explain why seniors display less intent to start a new business, we controlled for other potential determinant of entrepreneurial intentions. First, we add three variables that measure an individual’s perception of new business opportunities (opport), of his or her knowledge, skills and experience to start a business (suskill), and his or her attitudes towards the risks of failure in starting a new business (fearfail). Second, we add socio-demographic variables that control for an individual’s gender (female), household income (hhinc), household size (hhsize), experience in owning a business (anybusow), current work status (categorical gemwork, omitting full-time employed
ICSB 2016: Senior Entrepreneurship 4 as the base category), and highest educational attainment (categorical careduc, omitting no education as the base category). All these data originate from the Canadian GEM microdata set. Third, we merge these data with a series of regional environment factors that may influence the perception of the economic climate of an individual. These yearly regional data are collected from Statistics Canada CANSIM dataset for the corresponding years the GEM survey was collected. We match these variables with each individual’s by region for each year to control for the population size (pop), employment growth (emp_g), the unemployment rate of the 15 years and over population (UNEMP15plus), and the share of the population of age 55 years old and over of the individual’s region. Table II shows that results for the effect of the age of an individual on their intent to start a new business is robust across the different specifications once controlling for individual perceptions, individual characteristics and year and regional dummies. We can reject Base Model I at the 5 % level of significance but all other models cannot be rejected. They show a statistically significant monotonically decreasing nonlinear relationship between age and entrepreneurial intentions.3 The estimated average marginal effect of age over the entire sample for Base Model V is -0.004 and is statistically significant at the 1 % level. To illustrate the nonlinearity of the relationship between the probability of intent of starting a new business with age, Figure I below shows the estimated marginal effect at different individual’s age. It is monotonically decreasing and confirms the main hypothesis. INSERT TABLE I AND FIGURE I HERE Estimates for individual perceptions concerning entrepreneurial opportunities and skills are also robust and statistically significant across the different specifications with the expected sign. Both factors have a statistically significant positive effect on the probability of an individual to intend to start a new business. Only the perceived fear of failure is not statistically significant although the negative sign is as expected. Table II reports probit ML estimates of the Base Model V with the addition of an interaction of each individual perception variable and age. Also, the estimated average marginal effect of the age of an individual is -0.004 and is statistically significant at the 1 % level. However, the results suggest that the age of a person does not influence his or her perception of entrepreneurial opportunities, its fear of 01 3 As in Tornikoski et al. (2012), other estimations results not reported here show that a second order polynomial relationship between entrepreneurial intentions and age are not statistically significant while a first order polynomial is.
ICSB 2016: Senior Entrepreneurship failure or its skills level at the 5 % level of significance. Only the negative relationship between the
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perception of an individual’s necessary knowledge, skills and experience and his or her age is marginally statistically significant at the 10 % level of significance. This provides weak statistical evidence that as individuals get older, their perception of possessing the necessary knowledge, skills, and experience to start a new business is decreasing. The above findings fill an important gap in our understanding of the influence of age, specifically older age, on entrepreneurial intention. We suggest future research that examines our findings in the different economies identified by GEM, for example, comparing the aging effect on entrepreneurial intent in innovation-driven economies in relation to factor-driven economies and efficiency-driven economies. This is important as scholars could compare environments with different retirement and benefits systems, which are likely to shape the levels of “opportunity” and “necessitybased” older entrepreneurship. Moreover, we suggest that qualitative research is needed to develop a deeper understanding about the role of age-related barriers and influences for older entrepreneurship and more quantitative research is necessary to create generalizations about the impact of age on entrepreneurship. To our knowledge, there exists only two quantitative studies (Kautonen 2012; Kautonen, Tornikoski, and Kibler 2011) that specifically address age-related norms in the entrepreneurial context and no studies using GEM related data.
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ICSB 2016: Senior Entrepreneurship 11 Table I Entrepreneurial intentions and perceptions, by age group
ICSB 2016: Senior Entrepreneurship 12 Table II
ICSB 2016: Senior Entrepreneurship 13 Figure I