The details

In this section, there is a closer examination of particular aspects of Canadian living standards. The phenomenal success of the economy in improving average real incomes and alleviating poverty does not reveal what has happened to certain groups and segments of society and the interesting details get washed out in the averages. Many questions remain unanswered: How has the standard of living changed for particular age cohorts? Have young families fared poorly in recent decades? What about the middle class? How unequally distributed are income and consumption? Have immigrants done as well as those born in Canada? Which provinces have done better than average in terms of improving living standards?

Age and income

Earnings from employment and overall income usually rise through the early part of one's career, reach a peak when we are in our late 40s or early 50s and decline fairly rapidly thereafter. There are obviously wide variations on this theme but this pattern is a broad average.

There is no accessible longitudinal database for Canada which would reveal the lifetime pattern of earnings or income for a sample of the population. However, a number of projects are beginning to build up panel data (which tracks the same group of households over time) to examine the dynamic aspects of income and demographic change. One such project, the Survey of Labour and Income Dynamics (SLID) conducted by Statistics Canada, has followed the progress of some 26,000 persons over the two year period from 1993 to 1994. In the report released in July of 1997 (Statistics Canada 1997), the study revealed that there was considerable movement up and down the income scale even over the short two-year period. In 1994, about one-third of the population were in an income quintile different from that they occupied in 1993. Most of those (78 percent) moved by only one quintile while the other 22 percent had made a more pronounced shift. One of the most interesting findings of the study was that changes within the family (especially marriage or separation) dominated as a cause of movement in or out of the low-income quintile: 41 percent of all persons who dropped below the low-income cut-off in 1994 underwent a change in family composition.

At this stage, we are too early in the empirical study of Canadian income dynamics to understand the long-term patterns of income changes. All we have currently are cross-sectional surveys that provide a good ``snapshot'' of Canadians and their incomes in a given year. If we examine the real earnings and real-income profile of families by age of family head for the years 1973, 1984, and 1994 (all in 1994 dollars), we get a rough proxy for the lifetime pattern. This is seen in figures 9 and 10.

What is noteworthy is that the profile for each year is remarkably similar. The 1994 profile is not markedly different from the pattern of the other two years. Indeed, young families in 1994 appear to be worse off than their counterparts in earlier decades. In general, the apparent lack of improvement in real family incomes is consistent with the earlier evidence. Average real-family income has not increased greatly since the mid-1970s.

A comparison of the economic circumstance of families in 1973 and 1994 by age cohort, in figure 11, demonstrates the changes more clearly than the previous graphs.

What stands out here is that very young families in 1994 are a fair bit worse off than very young families were 21 years earlier. In 1994, families headed by a 21-year-old have 30 percent less real income than their counterparts in 1973. As well, families headed by those between 22 and 24 years of age are about 15 percent worse off. It is also fair to say that families in 1994 headed by those in their late 20s have only marginally more real income than those in 1973. For those over 30, however, real incomes are consistently higher (by about 15 percent on average) than they were in 1973.

Some of the apparent lack of progress of young families can be attributed to the large increase since the 1970s in the number of families with only one parent. Between 1973 and 1994, the number of such families as a proportion of all families rose by more than 50 percent (drawn from Statscan 1974, 1995). The heads of these families, mostly younger females, are more likely to be out of the labour force and are more likely to be on social assistance than heads of other families. When single-parent families are excluded, the relative economic performance of young Canadian families since 1973 improves considerably.

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Nevertheless, it is still the case that families headed by someone under 25 years of age are materially worse off now than their counterparts two decades ago. Part of the explanation is undoubtedly economic restructuring and the lack of labour-market opportunities for the inexperienced and unskilled. However, we cannot ignore the role played by the under-reporting of income and the underground economy. As well, the increased numbers of young married people who are still in school and the work disincentive of some social programs may also help explain some of the decline in real income.

Earnings from employment

The major source of income for most non-retired individuals and families is earnings from employment. In 1994, earnings (which comprise wages, salaries, and net income from self-employment) made up 85 percent of average household income for households headed by someone under 65 (drawn from Statscan 1974, 1995). Although other sources of income have grown in importance over the years, earnings from employment remain the foundation of households' current and future living standard.

The dramatic rise in the number of women in the labour force in this century has fundamentally changed not only the labour market but family and society as well. Whether out of a desire for a better standard of living or the pursuit of personal fulfillment and independence, women--married women in particular--have increasingly embraced labour-market employment. In 1901, only 16 percent of women over 15 were employed. By 1941, participation by women in the labour force had risen to 23 percent (Gunderson and Riddell 1993: 98). The big increase, though, occurred in the 1960s and 1970s (see figure 12).

Between 1961 and 1981, the female participation rate in Canada increased by 70 percent to 52.3 percent. Over the same period, the male rate was declining modestly due, in part, to a higher participation in post-secondary education by young males and more early retirements. More recently, the female participation rate has levelled off at about 57 percent.

More females in the labour force has meant many more two-income families. Between 1961 and 1994, the proportion of families with two incomes more than doubled to about 60 percent of all husband-and-wife families.

Partly because of the increase in participation by women in the labour force, more attention has been focused on the disparity between earnings of men and women. Although the differential has declined steadily over time, by 1995, women who were in the labour force still earned only 65 percent of the earnings of men in the labour force. when one compares only full-time, full-year workers, the proportion rises to 73 percent. Labour economists have argued that the remaining discrepancy can be mainly attributed to three factors: education and experience; the crowding hypothesis, which suggests that men and women may tend to have intrinsically different preferences for particular activities and occupations; and discrimination. Morley Gunderson (1989), for example, has pointed out that once education levels have been accounted for, differences in occupational distribution explains much of the remaining gap between the earnings of men and women. He cites a variety of studies that show that within the ``same narrowly defined occupation, ratios of female/male earnings of 0.80 are common'' and ``within the same establishment ... ratios of female/male earnings of 0.90 and 0.95 and more are typical'' (Gunderson 1989: 51-52).

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Considerable attention has also been focused on earnings polarization. Briefly, earnings are more polarized if there are more earners (or a greater proportion of total earnings) in the top and/or bottom groupings of the income distribution and fewer in the middle. Increasing polarization of earnings, if it exists, would be evidence of a growing dual labour market and would raise concerns about a shrinking middle class. In a recent study entitled Are We Becoming Two Societies? Income Polarization and the Myth of the Declining Middle Class, Charles Beach and George Slotsve (1996) point out that men's earnings have indeed become more polarized over the past two decades. Women's earnings, in contrast, have not become more polarized. However, the data used by Beach and Slotsve is for ``all earners.'' Given the increasing prevalence of part-time and part-year work, it may well be that rising polarization of male earnings is due, in large part, to greater disparities in hours worked rather than in the rate of earnings themselves.

For example, if we examine the earnings of all household heads (of either sex) who reported any earnings in 1994, we see in figure 13(a) that both polarization indexes drift up over the period. Polarization indexes are measures of the percentage of income flowing to recipients with either very high or very low income. For example, Polarization Index 1 (P1) is the percent of all earnings above 1.5 times the median earnings and below 0.5 times the median earnings and Polarization Index 2 (P2) is the percent of earnings above 1.75 times the median earnings and below 0.25 times median. Between 1973 and 1994, P1 increased by 26 percent and P2 by 34 percent. However, a large portion of the increase is due to an increase in the number of part-time and part-year workers, a circumstance that naturally tends to increase the inequality of earnings. Thus, in figure 13(b), which tracks P1 and P2 just for the earnings of household heads who were full-time, full-year workers, we see that both polarization indexes are much lower and both show a much more moderate upward drift: 16 percent in the case of P1 and 15 percent in the case of P2.

Beach and Slotsve's most important conclusion, that family incomes have not become more polarized and that the middle class, defined in purely relative terms, has not declined over the past two decades, needs emphasis. This result contradicts a widespread view in the popular press regarding a supposedly rising disparity between the rich and the poor (relatively speaking) in Canadian society. Beach and Slotsve point to pooling of incomes within families, the equalizing effect of government transfers (see below page 32-34), and the offsetting effects of the trends in the earnings of men and women as largely responsible for the fact that polarization of family incomes has not increased. Evidence presented later in this report (see p. 32) supports the conclusion that the middle class in Canada is not declining. Evidence presented already suggests that more Canadians than ever before enjoy a middle-class living standard (or better).

Education and earnings

There is ample evidence that investments in human capital (i.e., education and training) pays off in terms of higher expected lifetime earnings. In general, the greater the level of formal education, the greater the earnings and the evidence suggests that this is more true now than it was in the early 1970s.

Table 3 shows the average earnings of all men and women5 who worked and reported positive earnings, in current dollars, for the years 1973 and 1994. The direct relationship between earnings and the level of formal education is clearly borne out in the table. In several cases, especially with male earners, there is a bit of ``slippage'' in the category some post-secondary education. This is somewhat anomalous and may be partly explained by people who are still in school, either as full-time or part-time students.

A university degree has always conferred its economic benefits, but the evidence in table 3 shows that the margin of advantage over those with certificates or diplomas has grown substantially for married persons since 1973. The margin of advantage over high-school graduates has increased more modestly but for both married and single persons between 1973 and 1994.

Table 4 shows the average earnings of full-time workers alone. Because of the increasing prevalence of part-time work in Canadian society, this table gives us a somewhat fairer comparison. The anomaly in the category some post-secondary education shows up again, but only in 1994. As well, the growing margin of advantage for university graduates over college graduates (and to a lesser extent, over high-school graduates) again prevails for married persons. While broad averages never tell the complete story, these tables reveal a clear connection between the level of formal education and earnings. In general, the more schooling you have, the higher will be your material standard of living.6

Finally, the advantages of more formal schooling are not limited to the earnings while employed but extend to the probability of being employed. In table 5, unemployment rates by education level show a clear inverse pattern despite the long-term upward drift in all rates over the decades.

The poor, the rich, and the middle class

It has become common to measure the rich, the poor, and the middle class in purely relative terms. The rich are most often identified as those individuals or families in the top 10 percent or 5 percent of the income or wealth distribution. The poor are identified as those in the bottom 10 percent or 20 percent or else those whose income falls below half the average or median income of society. The middle class, by default, is what is left after rich and poor have been categorized or, simply and literally, some middle-income grouping such as the middle 60 percent or middle 80 percent of the income distribution.

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It is difficult to argue too strenuously against such relative measures, especially when they are used in a casual manner, and it is the case that we tend to judge our current economic situation at any point in time in relation to how most others around us are doing. Without doubt, relative measures are of great interest. But they miss so much!

The enormous growth in living standards in this century, lifting rich and poor alike, registers nary a ripple on relative gauges. The fact that people today are far better off materially than their grandparents were is entirely neglected by relative measures unless there is some change in the way incomes are distributed. More and more Canadians are enjoying a middle-class standard of living than ever before but, according to some studies using relative measures, the middle class is shrinking. When it comes to the very important task of measuring genuine economic progress, relative benchmarks are of little value.

To see an illustration of this point, imagine a society in which there is modest but steady economic growth such that there is an across-the-board increase of all incomes in real terms over time. In figure 14, the entire distribution of income can be represented by a thin rectangle. We start with the income distribution D1. Over a period of time, the distribution grows to D2 and later on to D3.

The whole distribution is moving up over time. Everyone's real income is improving but, unless there is some change in inequality of income--that is, some change in people's relative positions--relative measures cannot acknowledge what has happened. Relative poverty will be the same in each period yet many who were previously poor are now much better off. While we should continue to track relative measures to determine if inequality is changing, we clearly need absolute measures to inform us about any real progress in the standard of living. We need measures such as average real family income, inflation-adjusted levels of household consumption, proportions of households owning certain facilities and, perhaps most important, a poverty line connected to the costs of necessities.

A basic-needs poverty line

The development of a basic-needs poverty line is founded on the premise that poverty is, largely, a problem of real deprivation of necessities. People are poor when they are ill-housed and ill-clothed, when they and their children are hungry, and when they cannot afford essential medical care. Lacking basic needs embodies what it means to be living in poverty in a way that relative deprivation can never do.

In other research (Sarlo 1996 and, especially, Sarlo 1994), I have attempted to construct a poverty line based on basic needs that can be used to tell Canadians whether any progress has been made in reducing poverty. Essentially, a person's poverty line in a given year would be the total cost of acquiring nutritious food, adequate shelter (apartment accommodation in Canada) including the standard set of facilities and furnishings and household supplies, transportation, clothing, and health care (including personal hygiene costs, necessary medications, eye and dental care and, of course, the standard range of preventive and emergency care). Appropriately, these costs vary by particular circumstance, size of family, size of city and even sex, to some extent. Additional items such as restaurant meals, vacations, home computers, and leather jackets are not included, not because the poor should not have these items but because we are, after all, trying to measure how many of our fellow citizens cannot afford even basic necessities. I have suggested the use of a ``social comfort line'' set, quite arbitrarily, at twice the poverty line, which might help to inform us about the extent of ``social deprivation.''

My own calculations result in approximate average 1997 poverty lines for Canada by family size of: 1--$7,500; 2--$10,500; 3--$13,500; 4--$17,000; and 5 or more--$20,000.

A person or family whose true income is less than the poverty line is likely to be deprived of some basic need unless additional help is available. Of course, reported income is not always the same as true income and so the use of reported incomes tends to overstate, to some extent, the real level of poverty. However, there is no easy and reliable way to discover ``true income.'' As with most studies, my estimates of poverty in Canada are based on reported income despite its flaws. In 1994, the latest year for which reported income microdata are available, roughly 1.1 million Canadians or about 4 percent of the population were poor according to the basic-needs definition of poverty. More importantly, the rate of basic-needs poverty has declined dramatically over the past 40 years, as we saw in figure 5. In 1951, roughly one in three Canadians had insufficient income to cover all the necessities. In 1994, only one in 25 endured this kind of deprivation. This is remarkable progress!

The use of a purely relative line such as a measure set at half the average income adjusted for family size, however, shows very little progress in reducing poverty. The Canadian Council on Social Development (CCSD) has for many years used this measure (half the average income) because their view is that poverty is solely a relative phenomenon. As figure 15 shows, the relative poverty rate using the CCSD line in 1994 is essentially the same as it was in 1973. This is a period over which absolute poverty in Canada roughly halved!

The simple reason for the apparent lack of progress is that relative lines do not measure poverty at all. They measure inequality. Even the well-known Low-Income Cut-Off (LICO), developed in the 1960s by Statistics Canada to indicate the number of Canadians who were likely to be living in ``straightened circumstances'' completely fails to record the phenomenal reduction in real poverty in this country. It fails because it is also a relative measure, intimately connected to the average spending of Canadians, despite its reference to basic necessities. Jenny Poduluk, the statistician most responsible for LICO, estimated that about 29 percent of Canadians were ``low income'' in 1961 (Poduluk 1968: 187, 194). Statistics Canada, continuing to track the incidence of ``low income'' found that the rate (using latest ``revised'' lines) was 20.6 percent in 1971, 15.3 percent in 1981, and 17.4 percent in 1995 (CCSD 1979: 24, table 13; National Council of Welfare 1995: 10, table 2). This very modest decline using the LICO measure completely misses the extraordinary improvement in the lot of those living at the bottom of the income distribution. By comparison, in 1961 basic-needs poverty was 5 times as common as it is today. LICO, when used as a poverty line, simply does not tell us the real story.

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A major advantage of basic-needs poverty lines is that they represent a constant standard by which to measure progress. That standard--the cost of a fixed list of necessities--is the same through time even though the costs vary over time.7 We cannot measure change adequately if our gauge is also changing. As we saw in figure 14, even as the income distributions are moving up over time, the poverty standard was constant and rising living standards lifted many households above the poverty line. An ever smaller portion of the population is poor if we have solid, across-the-board economic growth like that in Canada over the past four decades.

Using the absolute approach

If an absolute approach to measuring poverty is useful in informing us about changes in poverty (and I strongly believe that it is) does it have any relevance in tracking changes in the rich and the middle class? If we consider only income, can we, for instance, develop a concept of ``rich'' that means being far removed from the poverty line? Is someone or some family rich if they can afford much more than those living at the poverty line? If we are inclined to answer these questions affirmatively, then it is possible to construct a framework connected to the poverty line to categorize rich, middle-class, and poor.

For example, a person or family having an income of 10 times the poverty line might be regarded as sufficiently far removed from poverty to be rich. There might be a tendency to label such a threshold as a relative measure. However, because the poverty line is absolute (based, as it is, on the costs of a fixed list of needs) a ``rich'' cut-off which is a multiple of the poverty line is also absolute. A change in the distribution of income will not affect the rich threshold but a change in the real cost of food or apartment accommodation will do so. If one were to use the ``10'' factor in establishing a ``rich'' cut-off (i.e., to be rich is to have 10 times or more income as someone at the poverty line), the approximate values for 1997 by family size would be: 1--$75,000; 2--$105,000; 3--$135,000; 4--$170,000; and 5 or more--$200,000.

These values would certainly correspond to most notions of ``richness'' measured by income in 1997. Filling out the structure, the ``near poor'' would be those living above the poverty line but at, or below, the social-comfort line set at twice the poverty line and the ``near rich'', those between 6 and 10 times the poverty lines. These selections are entirely arbitrary but no more arbitrary than poverty lines that are set at half the mean or median income, or than a definition of the ``rich'' as the highest 10 percent of incomes. It is clear that one cannot avoid arbitrariness in the study of the various income-groupings and there are no ``natural'' thresholds. Nevertheless, the basic-needs poverty line is about as close as we can get to a ``natural'' threshold in the social sciences. It is important to select reasonable thresholds and stick to them in tracking change over time.

Utilizing this framework for income subdivisions and Statistics Canada microdata files (only available since 1973), figure 16 displays the percentages in each grouping for selected years over the past two decades. The sharp reduction in poverty is notable. The incidence of poverty in Canada has roughly halved over the past two decades and, clearly, most of the decline occurred in the 1970s. Equally impressive is the rise in the proportion of rich and near rich. Both categories have more than doubled between 1973 and 1994. The proportion of near poor is about the same but the size of the middle class, using this absolute framework, is down by about 7 percent. This, however, should not be viewed as bad news since living standards increased solidly during part of this period and fewer Canadians are now living in poverty. The modest decline in the size of the middle class is due, in aggregate, to movement into the higher categories and not to movement downwards.

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Figure 16 is an important graph. It displays the real improvement in the economic circumstances of Canadian households in the 21 years for which the required data is available. Clearly, given the indirect evidence from earlier periods, more dramatic absolute improvements occurred in the 1950s and 1960s. When these are put together, it is clear that many more people can now enjoy the ``good'' life that was available to only a tiny group earlier this century. This graph gives us a more accurate picture of what has happened to Canadian living standards than any relative measure could. That there has been no perceptible progress since 1988 is a cause for concern.

Poverty among children

The existence of children living in poverty is particularly disturbing because they have no control over their situation; they are unwitting victims of parental misfortune or mismanagement. Concern about child poverty has increased in recent years after various reports using relative measures pointed out that about one in 5 children in Canada lived in poverty. In 1989, the House of Commons passed an (all party) resolution to end poverty among children by the year 2000. Various social-welfare groups continue to issue reports and make claims that poverty among children in Canada is, if anything, getting worse.

The statistical evidence of real living standards and ``basic-needs'' poverty, however, does not support the view that poverty among children has become a crisis in Canada. Indeed, all of the evidence presented thus far in this report points to improving living standards and conditions for most families since the end of World War II. On average, children today are significantly better off than their parents were as children but averages can mask a lot of interesting detail. What are the specific numbers and proportions of poor children in Canada over the period for which we have reliable data?

Tables 6a, 6b, and 6c display a breakdown by age and family-size of estimated poverty among children for the years 1973, 1984, and 1994. The most noteworthy value for each year is the overall child-poverty rate at the bottom of each subsection. This rate has declined from 9.06 percent in 1973 to 5.61 percent in 1994, a decrease of 38 percent. This decline pretty much matches the rate of change in the overall poverty rate over the period. This reduction in measured poverty among children occurred despite the sharp increase in single parenting and the increasing unreliability of reported income, especially at the bottom end.

What is particularly noteworthy in the table is that children in families of only two persons are much more vulnerable to poverty than children in larger families. Indeed, they face at least twice the risk of being poor as all other children. This confirms what is already well-known: single parents face major difficulties. They are most often young, female, not well educated, and must raise a child alone often with no assistance of any kind from the child's father. We might expect that this combination increases the risks of poverty. Also notable is that the very youngest children face the highest risk of poverty over the whole period. This, again, is not surprising. The youngest children are likely to have the youngest parents and poverty is, in large part, a problem of youth. Every study of poverty, regardless of the particular definition used, shows that poverty rates decline sharply as household heads move out of their twenties. This pattern is consistent whether the household heads are single or married.

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It would be a mistake, however, to use this statistical evidence to dismiss the problem of poverty among children. If there are only about 400,000 children in Canada deprived of basic needs, that is 400,000 too many. It is clear that there are still children in Canada who go to bed hungry and who are ill-housed. Part of the problem may be solved by an improving job market but much of the problem has little to do with money and much to do with parents failing to take their responsibilities seriously.

My earlier research (especially Sarlo 1994) has examined the issue of the adequacy of social assistance benefits. In general, welfare recipients with dependent children receive sufficient income (counting all federal and provincial tax credits and benefits) to cover basic needs. In other words, the various provincial social-assistance programs fulfill the mandate of the Canada Assistance Act to provide income to meet the cost of basic requirements of a single person or a family when all other financial resources have been exhausted. Over the past two decades, social-assistance benefits, like earnings and family incomes, have just barely kept pace with the cost of living. However, new tax credits and benefits (the child tax benefit in particular) have boosted the real incomes of recipients in the 1990s. For example, the average annual benefit for a family of four (two adults and two children) in Canada in 1973 was about $3,900. The amounts to roughly $14,700 in 1996 dollars. Currently, the average income of this category of recipients is about $18,000.

The concern, more and more, is that there is a far larger problem in society involving children that has nothing at all to do with low incomes. There are now more than one million children of divorced parents. The proportion of families with only one parent has doubled in just over one generation. The stress of family break-up and the absence of one parent is particularly difficult for children. The Canadian Council on Social Development noted in their recent report (1996) on the progress of Canada's children that the rate of violent offences by youths 12 to 17 years old more than doubled between 1986 and 1992. They also report that choices made by parents are having a profoundly damaging effect on children: one quarter of mothers reported that they smoked during their pregnancy; 20 percent admitted to consuming some alcohol while pregnant; despite the overwhelming evidence of the health advantages of breast-feeding, about half of all newborns are not breast fed at all or are breast-fed for less than one month. And recent evidence from Toronto reveals that the number of babies born to drug-addicted mothers is up sharply (Toronto Star 1997). I think that experts on children would agree that some degree of material deprivation is far less damaging than abuse and neglect. The problem of ``poverty'' among children is not, for the most part, a problem of lack of income.

Inequality

Social scientists have long had a keen interest in inequality. Statistical measures of inequality of income and wealth were developed almost as soon as we had reliable data on income and wealth. There is a natural human tendency to compare one's material well-being with that of others. There is also a very human tendency to resent significant differences in income and wealth and, as many wits have observed, that resentment is far greater towards those above us than those below. This inequality of income and wealth is widely regarded as a problem and any increase in inequality, therefore, is felt to be a major problem. Why is this so? What is it about significant differentials between people that presents a problem? Is it a problem by itself or is it a symptom of a problem?

Socialists frequently make the claim that inequality of income or wealth is bad and that it is the result of unfair distribution under capitalism. But, it is a rare socialist who wishes to impose perfect equality on all persons or families. Perfect equality, you see, means that extra effort, diligence, productivity, or saving cannot be rewarded and, worse, that laziness and irresponsibility cannot be punished. Rather, socialists tend to focus on the problem of ``too much'' inequality and actively promote ``redistribution.'' High and rising inequality, they claim, ``erodes the social glue'' that fastens society together. But ``erosion of the social glue'' is merely a euphemism for resentment.

While political scientists and historians would urge us not to underestimate the power of resentment, we need a stronger basis for scholarly concern about inequality. Inequality of opportunity rather than unequal outcomes is a possible basis. This is particularly true when the barriers to opportunity are based on economically irrelevant considerations such as sex and race. In many societies in the West, however, the most compelling determinants of opportunity are intrinsic to the individual; that is to say, we value intelligence and other personal characteristics. And these key characteristics, some heritable, some not, are simply not equally distributed. Thus, even if everyone starts the ``race'' in the same position, not everyone will finish first. Even assuming equal opportunity (that itself has a variety of meanings), intrinsic personal characteristics ensure unequal outcomes.

At the other extreme, libertarians tend not to be concerned with inequality unless the income or the wealth have been acquired through force or fraud. You have a fundamental right to any property received via consensual contract or gift. This means that million-dollar contracts to baseball players, movie stars or bank presidents are on the same moral footing as any other voluntary transaction. In a free society, with few exceptions you may not interfere with the contracts of others and they may not interfere with yours. While libertarians encourage compassion and charitable giving, it is morally wrong to compel someone to give their rightly acquired property to others. Thus, for libertarians, the result of free and voluntary contracting and, as well, gifts and charitable giving will be the final distribution of income. The resulting degree of inequality may be a matter of interest but not of policy.

Canadian society in recent decades has been governed by ideas somewhere between the ideals of Socialists and Libertarians. Governments at all levels have a wide variety of tools and powers to interfere with the prevailing distribution of income. Ideally, they redistribute from the well-off to the less well-off. However, reputable economic studies suggest that much state redistribution involves the shuffling of monies between middle-class families (see, e.g., Horry and Walker 1994). Nevertheless, governments in Canada do have an impact on the final distribution of income.

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The data on inequality

What are the facts of inequality in Canada? Are incomes more equally or less equally distributed than before? How are earnings and consumption distributed? Is the gap between the rich and the poor growing?

The most common indicator of financial inequality is the distribution of income by quintile shares. As the name suggests, quintile shares show the percentage of income (or other financial variable) that is received by each quintile or 20 percent of the population once incomes have been ranked from top to bottom. Table 7 displays the quintile shares of total household incomes for Canada since 1951.

What is noteworthy here is the remarkable stability of quintile shares over this long period of time. The bottom 20 percent of the population in terms of household incomes receive roughly the same proportion of overall income as they did in the early 1950s, that is, about 4.5 percent. The top 20 percent is up slightly, but the ratio of the top to the bottom quintile shares has actually declined somewhat over the years.

There is often an initial inclination to condemn the apparent yawning gap between the top and bottom shares. Surely it is unfair that the top 20 percent of households receive 9 times the income of the bottom 20 percent? The economics of the life-cycle pattern examined earlier, however, explains much of the observed inequality. Even if everyone had the same lifetime income, because income rises with age, that is, with increased experience and responsibility, there would exist substantial income inequality at any point in time. In one simulation, I showed that such a pattern would result in the bottom quintile receiving 9.2 percent of income and the top, 31.6 percent (Sarlo 1996: 216).

Some people have higher incomes than others because they command a valued skill or hold jobs with greater responsibility. Professionals (architects, lawyers, doctors, engineers, and professors) earn more than those working in less skilled jobs (clerks, secretaries, truck drivers, and salesclerks). Skill differentials may account for much of the remaining observed inequality. It must be noted, however, that the earnings differential, say, between professionals and other occupations on an annual basis is much higher than the lifetime differential. This is because the professional typically works (and earns) fewer years than the non-professional. In most cases, professional occupations require substantial education and training--what economists term ``investment in human capital''--and professionals will, therefore, have a number of years of foregone income during the investment phase. As well, in many cases a large debt-load accrues to professionals, further reducing the apparent living standard differential.

Finally, not everyone is employed. Those who are retired, some of the disabled and some students are not in the labour force. Others are involuntarily unemployed. They want a job but cannot find one. On the high end, there are a small number of ``superstars'' (typically in the sports, entertainment, and business) earning enormous incomes. Both phenomena serve to stretch out the distribution of income and increase measured inequality. However, it needs to be emphasized that age and skill are capable of explaining most of the inequality in incomes.

The point has been frequently made that, if not for government transfers, measured inequality would have increased. On one level, this is clearly true. If unemployment benefits run out, for example, then welfare will often provide more income than the next best alternative--at least for the current period and this obviously means less inequality than might have prevailed. However, for someone who can work, the transfer may delay entry into employment and this may, over time, result in less income to the household. If this happens, then transfers end up increasing inequality. The more generous the transfers, the more likely it is that this moral hazard (i.e., the tendency to relax one's own efforts because of the security provided externally) will adversely affect inequality.

The Gini coefficient is another, very common, indicator of inequality. It is a measure that lies between 0 (perfect equality) and 1 (one person has all the income, everyone else has nothing). It is a very convenient measure because of its easy interpretation. The following series of graphs tracks the Gini coefficients for key variables over the period for which detailed information is available (1973-1994). Figure 17 displays the trend in inequality for total earnings of families, unattached individuals and all households; figure 18, for earnings only of households with positive earnings; figure 19 for total income and figure 20 for after-tax income.

In the real world, people constantly shift their income across time. Students borrow against expected future income. Pensioners enjoy income saved during prime earning years. In addition, the State provides income transfers to people for a variety of reasons. Income, for a large number of Canadians, is much different from earnings. This is an important point. Not every household has earnings: students, seniors, and people on welfare will often have zero earnings, though not zero income. So we expect substantial inequality of earnings on that count alone. As well, total earnings are pre-tax, which further enhances the degree of inequality. So, in figure 17, we observe fairly high Gini coefficients at the beginning of the period, as expected. Then, the Gini coefficient trends upward over the next two decades, with a particularly sharp rise during the recession of the early 1980s. This evidence is consistent with the polarization results for the earnings of household heads in figure 13(a) and 13(b). Familiar economic explanations like the trend towards part-time work, structural economic change (especially, a reduction in the number of high-paying, lower-skilled manufacturing jobs), and the increasing generosity of social programs--all of which increase the number and proportion of households with little or no earnings--help explain much of the upward trend.

Figure 18 examines the trend in the Gini coefficient for the earnings of those households that had positive earnings. It is an interesting question whether earnings themselves are less equally distributed--as would be the case if bottom-end jobs simply paid less than before--or whether much of the increase in measured inequality is due to the fact that fewer households have any earnings at all. By removing those households with earnings of zero or less, we focus attention on the issue of the distribution of the earnings themselves as distinct from any demographic or labour-market changes. The first thing we notice is that the variable ``positive earnings only'' has Gini coefficients that are far lower than was the case with total earnings. It makes sense that there would be much greater equality if those without any earnings are excluded. However, the Gini coefficient still rises over the period and most of that rise occurred during the recession of the period from 1982 to 1983. So, it appears that at least some of the rise in earnings inequality is due, not to the fact that more households are without earnings, but to the fact that earnings themselves are less equally distributed. It may be that rising inequality of earnings is due, in large part, to increasing polarization of hours of work as more part-time work and short-term contracts appear simultaneously with more overtime in existing jobs. One common explanation is that the economics of hiring tends to work against new full-time jobs and in favour of more intense work in existing jobs.

Click Here to View Figure 17

Click Here to View Figure 18

Figures 19 and 20 show the trend in inequality for total income and after-tax income respectively. It is no surprise that after-tax incomes would be more equally distributed than pre-tax incomes. A progressive tax system with exemptions for the very poor tends to be equalizing. It is noteworthy that the Gini coefficients for total family incomes and after-tax incomes are essentially trendless over the period. For unattached individuals, the trend is clearly down. Most of the decline in inequality for single people occurred during the 1970s, undoubtedly showing the impact of improved supplementary pensions for poor seniors. Overall, total pre-tax income and after-tax income of Canadian households are not more unequally distributed than was the case in the 1970s. This result conforms to the evidence provided by many others, including Beach and Slotsve (1996).

Does any of this evidence support the claim often heard that the gap between the rich and the poor is growing? It might, but only in a very simple-minded way. If everyone's income is growing at the same rate, then everyone remains in the same relative position so there is no change in the standard inequality measures. However, the absolute gap between the rich (however defined) and the poor (however defined) will increase. Indeed, the incomes of the poor could grow substantially faster than the incomes of the rich and the absolute gap would still rise.

Click Here to View Figure 19

Click Here to View Figure 20

However, in a more meaningful sense, the gap between rich and poor is not increasing at all. Some evidence for this has already been provided. Table 1, for example, shows that the average income of the bottom quintile of households has grown faster since 1973 than the average income of the top quintile. More importantly, the dramatic decline in real poverty since the 1950s (figure 5) tells us that many fewer Canadians, proportionately, are poverty stricken. This information, combined with evidence in figure 16 revealing that, while the number of rich has increased by almost two percentage points since 1973, the number of poor declined by four percentage points, clearly demonstrates that proportionately fewer people in Canada are either rich or poor. Reduced polarization of the population, in this sense, suggests a lower and not a greater gap between rich and poor.

Click Here to View Table 8a

Click Here to View Table 8b

Click Here to View Table 9

The best evidence contradicting the claim that the gap between the rich and the poor is growing, however, comes from an examination of the way people live--that is to say, from the consumption and the facilities that most contribute to their actual standard of living. More and more, people at the bottom of the income distribution enjoy the amenities and facilities associated with those who are well-off. For example, the clear distinction between wealth and poverty once signified by ownership of an automobile has all but disappeared. By and large, in our mass-consumption society, there is greater commonality than ever before in terms of dress, entertainment (especially television), housing, and food consumption.

Along these lines, it is noteworthy that the ownership of key household facilities has increased by more in the bottom quintile than in the top quintile. In table 8b, we observe that, for eight important household items, the average percentage increase in ownership for the lowest quintile since 1980 has generally been much higher than the increase for the top quintile (table 8a shows the percent of the bottom and top quintiles that owned the facilities in selected years).

Examination of consumption trends by quintile tells a similar story. In table 9, the average level of current consumption by income quintile is given for the years 1948, 1969, 1978, 1982, 1986, and 1992. These are the years that Statistics Canada conducted the national family expenditure (FAMEX) survey and these data are derived from the published FAMEX tables. Roughly speaking and on average, the consumption level of households in the top quintile was 4 times that of those in the bottom quintile and this ratio has remained quite stable over the period. This is not a large differential and is particularly small when compared to the ratio between the largest and smallest incomes (a ratio of 9.3 currently). Since households that are better off are also larger, the bottom half of the table shows the quintile distribution of consumption on a per-capita basis.

In this part of the table, we notice that the ratio between the top quintile and the bottom quintile is less than two! On a per-capita basis, the average top quintile household lives about twice as well as the average bottom quintile household. While per-capita consumption omits scale economies and these calculations ignore wealth (a household's net worth), it is still rather remarkable that there is such a small difference between the top quintile's and the bottom quintile's average per-capita consumption.

Finally, the most recent FAMEX survey (1992) provides some interesting comparisons between quintiles for key consumption items. In figures 21(a) to (h), direct comparisons of average spending by quintiles is made for food, shelter, clothing, personal care (such items as make-up, shampoo, toothpaste, haircuts), education, recreation, tobacco and alcohol, and personal taxes; figure 21(i) shows overall consumption.

Click Here to View Figures 21a, b, c, d, e, f, g, h, i

Average per-capita consumption of basic necessities such as food and shelter is surprisingly equal across quintiles. Average household per-capita spending on food (which includes spending at restaurants) by those in the top income quintile is only 48 percent more than those in the bottom quintile. With shelter, the per-capita cost differential among the first four quintiles is negligible. This reflects, to a large extent I believe, the economies of scale in shelter as families get larger and the positive correlation between income and household size. Spending on personal care, on a per-capita basis, is also not highly unequal.

There is substantial inequality in spending on clothing. The average per-capita expenditure of those in the top income quintile is three times that of those in the bottom quintile. Undoubtedly, the additional spending on clothing in the higher quintiles reflects both quality and quantity. Per-capita spending for both recreation and education is quite unequal: the ratio between the average per-capita spending on these items by the top quintile and the bottom quintile is about 3.7. This is not surprising, especially in the case of education, which is unlike most other commodities in that most households spend zero on education, not having dependents in private schools or attending post-secondary institutions. If we look just at those households that spent some positive amount on education in 1992, then the ratio between per-capita spending on education by the top and bottom quintiles is approximately one.

Average per-capita expenditure on tobacco and alcohol is remarkably equal across income quintiles. These values are absolute expenditures and not proportions of income. Clearly, these items have a consistent attraction across the board, with little regard to income. Not surprising at all is the per-capita spending on personal taxes. With a progressive tax system, we expect huge differentials in taxes paid. The average per-capita spending on personal taxes by the top income quintile is about 50 times the average spent by the bottom income quintile. Figure 21(i) presents the quintile distribution of overall average per-capita consumption in 1992.

Immigrants

Canada has benefited enormously from immigration over the years. It has brought to this country hard-working people eager for a fresh start. It has helped to fill the sparsely populated land mass of Canada and helped to give us the critical accumulation needed to be an important economic entity. Most of all, immigration has brought to Canada a wide diversity of ethnic groups enriching the cultural fabric of society. Heterogeneity is one of our most prized characteristics.

How have immigrants fared in Canada? How do they compare to those who were born here in income, level of education, and jobless rates? Are they more or less likely to be poor? Overall, how do the living standards of new Canadians compare to native-born Canadians?

Let us begin with poverty. Figure 22 displays the poverty and near-poverty rates of immigrants (dashed line) and the Canadian-born (solid line) over the period 1973 to 1994. For most of the period, immigrants had lower poverty and near-poverty rates.

From 1973 to 1988, immigrants were less likely than non-immigrants to have reported incomes below the poverty line and less likely to have reported incomes below twice the poverty line. Since 1988, however, poverty rates for immigrants have moved above, and near-poverty rates have become equal to, the corresponding rates for the Canadian-born. This may reflect stricter regulations for immigrants and refugees as far as employment is concerned. More broadly, it suggests that immigrants, when compared to those born in Canada, are seen to be having a more difficult time than they used to.8 Despite this, it is important to emphasize that throughout the 1970s and 1980s, immigrants were less likely to be poor than other Canadians. They had to overcome the language barrier in most cases and make significant adjustments to Canadian conventions and customs. As well, many faced discrimination. Their superior ability to avoid poverty is all the more remarkable.

What other evidence is available regarding the relative performance of immigrants is fairly consistent with this result. For example, immigrants are better educated than those born in Canada; they have higher incomes; their families are much less likely to be headed by a single woman. And, their incomes are higher even when we control for education level. These and other data are displayed in table 10.

As with the poverty data, the rate of unemployment is an area of concern. Where once immigrants had a substantially lower unemployment rate than other Canadians, now their rate is higher. This change in circumstance has no easy explanation. Nevertheless, overall, immigrants to Canada continue to have an enviable record of success.

The elderly

The current cohort of Canada's senior citizens is better off than seniors at any other time in the past. Rapidly rising living standards and enhanced public supplementary pensions for low-income seniors have greatly improved the lot of those over 65 years of age. Seniors are not only better-off financially but are also living longer, have better health-care facilities available, and are generally more active than ever before.

Click Here to View Figure 22

Click Here to View Table 10

Click Here to View Figure 23

In 1994, seniors had higher real incomes at every age level than their counterparts in 1973. Figure 23 shows the changes in the real incomes by age of households headed by a senior--both families and unattached individuals--from 1973 to 1994: the average senior household is roughly 40 percent better off in terms of real incomes than it was two decades earlier. This far outstrips the typical gain for non-seniors (see figure 11). This relative gain can be seen more directly in figure 24, which shows the trend in average household income from 1973 to 1994 for seniors and non-seniors.

The life-cycle hypothesis of income and consumption predicts that seniors' incomes will be lower than that of non-seniors. Most seniors are not employed and have no earnings. They typically live on pensions, part of which will have been generated by their own past savings. Their consumption is typically reduced, most having no mortgage payments and no children at home. It is easy to see in figure 24 that, while the gap in incomes is, as expected, still substantial, it has declined markedly over two decades. In 1973, seniors had, on average, one-half the income of non-seniors. By 1994, the ratio had risen to almost two-thirds.

Consistent with these data, the poverty rate for seniors has decreased dramatically over the period. As we see in figure 25, the senior's poverty rate was actually above that for non-seniors in the 1970s. However, by 1981, the senior's rate had dipped below that for non-seniors and is now almost insignificant. Canada's means-tested supplementary public pensions and the welfare system (as a last resort) virtually guarantees that no elderly person will be living in poverty.

Click Here to View Figure 24

Click Here to View Figure 25

Click Here to View Table 11

Click Here to View Table 12

The net effect of the many influences on seniors' incomes has tended to be equalizing over the period from 1973 to 1994. Indeed, as seniors' incomes have become somewhat more compressed, the incomes of non-seniors has become somewhat more dispersed. Table 11 displays the Gini coefficients for total household income for both seniors and non-seniors.

In terms of household facilities, the standard of living of Canada's seniors is quite comparable to non-seniors. For a number of key items, such as colour television, cable television, air conditioning and freezers, ownership by seniors is equal to, or greater than, that for all households (see table 12). It is understandable, partly because of restricted income but mainly because those of the seniors' generation are unfamiliar with the technology, that facilities such as automobiles, home computers and even video cassette recorders are somewhat less common in the households of seniors.

Seniors' overall consumption, on a per-capita basis, is comparable to that of non-seniors, although the composition is different. As we see in table 13, in the most recent (1992) family expenditure survey the total per-capita consumption by households headed by seniors was found to be about 96 percent that of all households. That percentage is about the same as it was in 1969 but is higher than was the case in 1978 and 1986.

While seniors spend about the same, per person, as households in general, they tend to spend more on food and shelter and less on other items, especially clothing, tobacco and alcohol, and recreation. This compositional difference is not surprising: the extra spending by seniors on food and shelter has to do largely, I think, with economies of scale in living. Food preparation for smaller units (mainly one- and two-person households) will be somewhat more expensive per person than for larger units as small households are less able to take advantage of volume purchasing, ``family packs,'' and the lower price per unit of larger-sized items. As well, seniors' households are composed almost exclusively of adults, whereas many other households have young children who will consume less food than adults. Finally, some seniors may have special diets that require additional expenditures. While spending on food includes food purchased at restaurants, it is the case that seniors' households spend about 40 percent less per capita at restaurants than households in general (Statscan 1992). The economies of scale regarding shelter are clear: the additional or marginal cost of housing declines dramatically after the first person is housed (see table 13).

Regional living standards

It is now well known that some regions of Canada are performing less well economically than others. The Maritimes and Quebec have, in many respects, ``underperformed'' relative to the rest of Canada. As table 14 reveals, there are, indeed, significant differences in the economic performance of Canada's 5 regions.

Average incomes (family incomes in 1961 and total household incomes afterwards) have consistently been lowest in the Maritimes and highest in Ontario. Since the early 1980s, the average incomes in the Prairies have moved up relative to incomes in other regions, due largely to the oil boom in Alberta. However, average income is not a good indicator of relative living standards for regions because it ignores differences in living costs. It is clear that costs--especially the cost of shelter--varies considerably across the nation. The cost differential is sufficiently significant that the same family could enjoy a higher living standard on, say, an income of $30,000 in a small rural or seaboard community than on an income of $40,000 in a large expensive city. Thus, while the change in a region's average income over time is of some interest--we note that average income in the Maritimes has been growing somewhat faster than average incomes in Ontario in recent decades--the level of income and the relative rankings do not indicate very much by themselves.

Click Here to View Tables 13a & 13b

Click Here to View Table 14

The unemployment rate is an indicator of importance. The Maritimes have had an unemployment rate that is chronically higher than other regions in Canada. It is a relatively depressed area in which economic growth and job creation proceeds more slowly than in the rest of Canada. The poverty rates and the relative population growth confirm this conclusion. For example, since 1961 the population of the Maritimes has grown less than half as fast as the overall Canadian average and the population of Quebec, about two-thirds as fast. The poverty rates, again using my own basic-needs poverty lines that explicitly take regional cost differences into account, tell a particularly meaningful story. In the 1960s and 1970s, the Maritimes have the highest poverty rates in the country by a fair margin, consistent with its relatively depressed status. Despite continuing slow growth and high unemployment, however, poverty in the Maritimes has fallen more quickly than in other regions, to the point where the Maritimes no longer have the highest incidence of poverty but now rank after British Columbia, where very expensive housing in recent years has resulted in high poverty lines and correspondingly high poverty rates. The low poverty rate in the province of Quebec is also puzzling given its relatively high unemployment rates, although substantially lower housing costs in Quebec resulting in lower poverty lines may help explain this outcome.

Figure 26 displays real household consumption for selected years over the post-war period. Again, one must not associate a region's ranking or actual level of average consumption with its underlying standard of living. In regions where costs are lower, consumption levels will naturally tend to be lower, ceteris paribus. Thus wage levels, incomes, and consumption levels do not inform us directly about living standards. What is noteworthy here is that the general pattern of real consumption in the regions follows closely the overall Canadian trend shown in figure 8; that is, strong improvements up to 1978 and modest, if any, change there-after. No region has been immune from the relative stagnation in living standards since the 1970s.

Wealth

Wealth or a household's net worth plays an important role in determining material living standards. The ownership of financial and non-financial assets (ownership net of debt, of course) bestows benefits that cannot be captured in income or consumption patterns. We may reasonably argue, for example, that owning a home, having $50,000 in a mutual fund, and having a good pension plan gives a household a higher standard of living than not having those assets even if income and consumption are the same. The benefit of wealth may be largely psychic: one ``feels better off'' having assets such as a home and a good pension plan than not having them. While wealth is not a major determinant of the standard of living as it omits any consideration of what and how much people consume from day to day, it is certainly a component.

The life-cycle hypothesis suggests that wealth will have a pattern strongly influenced by age and will be even more unequally distributed than income. We also expect that the ratio of financial wealth to non-financial wealth would increase with age. In a major study of wealth in Canada (Oja 1987: 16), Statistics Canada found that between 1970 and 1984, real household wealth almost doubled. Oja concluded:

Click Here to View Figure 26

Click Here to View Figure 27

Wealth holdings conform to a predictable pattern based on the life-cycle hypothesis of saving; that is, the youngest age group holds the least wealth, the middle-aged group holds the most and the wealth of the elderly lies between these two extremes, reflecting some depletion of savings after retirement. This pattern seems firmly established and has been observed in all Canadian data (1987:16).

Regrettably, there is no reliable, detailed, and continuous data on household net worth. Statistics Canada's surveys on the wealth of Canadians are very occasional and none have been conducted in recent years. The National Accounts provide an aggregate estimate of net worth on an annual basis, which is a second-best source of information. The major problem, of course, is that these data allow no examination of distributional aspects of wealth. Figure 27 tracks the net worth of Canadian persons and unincorporated businesses on a per-capita basis and in real (1994) dollars drawn from the National Balance Sheet Accounts. About 90 percent to 95 percent of total Canadian net worth comes from persons and unincorporated businesses. Corporations, governments, and other institutions account for the rest. The major assets composing the wealth of persons and unincorporated businesses are currently, in order of importance: homes and land; cash and deposits (including Guaranteed Investment Certificates); life insurance and pensions; shares (equities); and durable goods. On a real per-capita basis, net worth has increased only modestly (16 percent) since 1979, a picture consistent with other evidence (income, consumption, poverty rates, etc.,) of the relative lack of economic progress in recent years.

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Last Modified: Wednesday, October 20, 1999.