Chapter 1 of this thesis analyzes the determinants of income inequality in Canada using
micro-level data from Canada’s censuses (1991, 1996, 2000, 2006, 2016). First, it is shown
that market-income inequality is higher than inequality based on other types of income
(annual wage, annual pre-tax income and annual income after-tax). Inequality is highly
driven by the gap between the income shares held by the top 1% income group compared
with other income percentiles. It is also explained by the large gap between income
percentile of the top 25% income group and the bottom 75% income group. The top 30%
income group held 60% of the population total income, while the bottom 30% income
group held under 9% of the population total income. Inequality is different by province
across Canada. From the findings, within-group inequality dominates between-group
inequality, regardless of whether groups are defined by education, occupation, gender,
age, language, marital status, or citizenship status. Second, analyzing the determinants
of inequality, the results suggest that they vary significantly across income groups. The results highlight the contribution of any explanatory factor to inequality and the proportion
of inequality explained by all observable characteristics. The largest part (between 64%
and 74%) of income inequality is not explained by individual observable characteristics.
Third, these determinants are modified by redistributive policies such as taxes and transfers.
Chapter 2 brings further light on income inequality dynamics by gender and inves tigates its determinants from static and dynamic points of view. Using Canada income
data, this research uses different measures of inequality to provide evidence on the
changes in inequality by gender from 1991 to 2016. In this study, unconditional quantile
regression based on the Re-entered Influence Function (RIF) is used to assess the impact
of individual characteristics on income quantiles. The contribution of each relevant
covariate on the Theil index by gender is documented by applying regression-based
decomposition of inequality. Finally, RIF-Oaxaca-Blinder decomposition is used to
investigate the composite and income structural effects on the changes in inequality
measures by gender. Results show that, before 2001, inequality was higher among
females than among males, and starting from 2001, the inverse process is observed.
The changes in the interquantile differences are not homogeneous along the income
distribution for both males and females. The pattern of the effects of covariates on
quantiles along the income distribution is gender specific. The findings provide evidence
that, in most cases, the income structural effect explains the higher part of inequality. dynamics by gender, even if the size of the impact differs by gender. Furthermore,
the composite effect counterbalances the income structural effect most of the time, even if, in some cases, they contribute to the change in inequality measures in the same direction.
Chapter 3 investigates the spillover effects of corporate tax across the provinces using
Canada’s corporate provincial aggregate data from 1981 to 2019. A dynamic panel model
is used to assess the incidence of tax competition within the country. The results show that
an increase of statutory taxes in other provinces has a positive effect on the corporate taxable
income of a specific province. The results provide the evidence of spillover effects of
corporate tax across provinces in Canada. This chapter supports the recommendations proposed
by Smart and Vaillancourt (2021) on formula allocation mechanism and by Boadway
and Tremblay (2016) on the modernization of business taxation mechanism in Canada.
| Identifer | oai:union.ndltd.org:uottawa.ca/oai:ruor.uottawa.ca:10393/45521 |
| Date | 05 October 2023 |
| Creators | Gninanfon, Medesse Armande |
| Contributors | Pongou, Roland |
| Publisher | Université d'Ottawa / University of Ottawa |
| Source Sets | Université d’Ottawa |
| Language | English |
| Detected Language | English |
| Type | Thesis |
| Format | application/pdf |
Page generated in 0.0024 seconds