This report was first published by the MEI’s Taxation Series.
A concern for social mobility—the ability to earn more than one’s parents and climb up the socio-economic ladder—is shared among people from across the political spectrum in liberal democracies. The idea that one’s socio-economic position should not be fixed by dint of birth finds little to no opposition. However, debates emerge when the time comes to measure social mobility and to determine which policies promote it.
The goal of the present Economic Note is to provide a provincial ranking of barriers to social mobility in order to help guide policymakers regarding the actions they can take to promote such mobility. A longer, more complete Technical Annex, including a literature review, is available on the MEI’s website.
Main Barriers to Social Mobility
Natural barriers
Without oversimplification, arguments over social mobility can be conceptualized around the idea of the heritability of inequalities. On the one hand, those who are wealthy now inherit a key advantage that could allow them to access a greater pool of socio-economic opportunities. Such potential transmission implies that inequality is transmitted between generations—a “structural reproduction” of inequality.(1) The emphasis on “structural” invokes social factors that are more “natural” in the sense that these are barriers to mobility that policymakers only have an indirect—often unintentional—effect on. One can think of differences in parental investment—choices that parents make to improve the skills, education, and experience of their children—or the stability of family life.
Artificial barriers
On the other hand, and more importantly from a public policy standpoint, there are “artificial” barriers to mobility that come from government actions that policymakers have direct control over.(2) These include laws and policies that reduce the returns to working, saving, and training to acquire new skills. Artificial barriers are the byproducts of government intervention in the economy. They raise the cost of investing in one’s children (sometimes in a regressive manner), depress the returns to these investments (again, sometimes regressively), and reduce earnings in adulthood.
For example, tightly regulated credit markets limit the ability to raise funds to invest in children (for post-secondary studies, for instance). This favours the better-off, as they can use their own savings to make these investments. Another example is occupational licensing, which restricts entry through expensive courses, lengthy apprenticeships, minimum hour requirements, and registration fees. By limiting supply, it raises incumbent incomes while lowering expected returns for new players, especially those at the bottom. Labour market regulations that deter hiring, and high marginal tax rates that reduce after-tax returns to schooling, similarly discourage skill acquisition.(3)
Artificial barriers are the byproducts of government intervention. They raise the cost of investing in one’s children and reduce earnings in adulthood.
Sometimes, the barriers are unforeseen consequences of other regulations. Such regulations may, for example, raise the price of key goods like childcare, housing, transport, and food. This has a disproportionate impact on poorer households’ budgets, reducing the resources they have left for human capital investments.(4)
There is a large literature tying economic freedom—the degree to which the government adopts pro-market policies—to greater income mobility.(5) Economic freedom also has an indirect effect on mobility. It fuels faster economic growth, promotes higher incomes, and encourages innovation, all of which creates new pathways for upward mobility.
This works largely through specialization: open, competitive markets let people and firms focus on what they do best, and this specialization deepens economic dynamism and multiplies the number of pathways to move up in the world. Economic dynamism variables thus act as a proxy for the “creation of new pathways” (knocking down some existing barriers, both artificial and real).(6)
However, the most obvious artificial barrier is tied to the provision of schooling. Education policy can create barriers if the government’s mission to provide universal schooling has great variation in quality—especially if this is correlated with existing income distributions. For example, public school assignments trap poor families in underperforming, low-quality schools. Such policies reinforce existing barriers by making it very difficult to escape a bad school.
Open, competitive markets let people and firms focus on what they do best, and this specialization multiplies the number of pathways to move up in the world.
It is also important to note that these barriers affect people differently across their lives. For example, artificial barriers hurt mobility by limiting one’s ability to secure a high-paying job. However, they also hurt by reducing the resources available to one’s parents to make investments. Sometimes the effect is confined to childhood.
For instance, childhood poverty—accompanied by limited parental investments—shapes the trajectory of upward mobility early on. Its impact is front-loaded, determining who moves ahead during childhood itself. Table 1 sorts examples of socio-economic indicators by type and by when they matter.
The Index and Its Results
The variables listed in Table 1 are useful for our purposes because it is from them that we can create a provincial ranking of the barriers to mobility. To create this ranking, we used standard index numbers (explained in the Annex). Summarized simply, the approach consists in picking different variables and setting a minimum and maximum for each.
If a province reaches the maximum for a given variable, then it obtains a score of 100 for that variable. If it is at or below the minimum, it obtains a score of zero. Anything between the minimum and maximum is linearly contained between 0 and 100. (If, for a given variable, “less is better,” such as for childhood poverty, then it is the minimum that gets the score of 100.(7)) All the scores for the different variables having been standardized on the same scale from 0 to 100, we can average the scores to provide a total score, according to which we rank the provinces, with higher scores implying better environments for social mobility.
The variables we used for artificial barriers are: occupational licensing, business regulation, minimum wage intensity (relative to market wages), approval delays in construction, land-use regulation, tax rates (across multiple types of taxes), and the degree of property rights protection. For artificial barriers affecting dynamism (i.e., the addition of new pathways for social mobility), we used: business entry, firm growth, construction activity, labour force participation, interprovincial migration, and incarceration rates.
Alberta offers the most propitious setup for income mobility, whereas Quebec offers the least propitious one.
For natural barriers, we used: the share of single-earner families, children born to single parents, school competition, school quality, parental involvement, poverty rates, income inequality, share of income donated to charity, share of taxpayers making charitable donations, and average volunteering hours (the last three are related to social networks).
We produced an aggregate score and then decomposed it into its “natural” and “artificial” barriers. When computing the aggregate score, however, we added an important parameter. Indexes that average across indicators risk masking imbalances, as high scores in some areas can offset severe weaknesses, like persistent childhood poverty. Because many determinants of mobility—education, income, family stability, social capital, and institutions—reinforce one another, unevenness matters. Balanced environments reduce the chance that one weak link undermines progress.(8) As such, we introduced a penalty (explained in the Annex) that affects provinces with greater imbalance across the barriers to social mobility.
Figure 1 illustrates our results. In the Annex, we show that the index is highly correlated with measures of social mobility (i.e., actual outcomes). As such, our index of the determinants of social mobility correspond to actually observed patterns of social mobility. In terms of the aggregate index, Alberta offers the most propitious setup for income mobility, which is to say, the lowest overall barriers, whereas Quebec offers the least propitious one. The ranking is similar with respect to artificial barriers as well.
However, there are some notable differences with respect to natural barriers. For example, some Atlantic provinces like Nova Scotia have relatively low artificial barriers to mobility (i.e., higher scores on the index) but high natural barriers to mobility (lower scores on the index). Another stark example is Ontario, which scores poorly with respect to artificial barriers but ranks second best with respect to natural barriers.
In every province, there is room for improvement. Our analysis provides policymakers with information about policies they could deploy to promote social mobility in both the short run and the long run. Below is a briefing note about each province and where improvements could be most easily secured.
Download the technical and methodological annex.
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