Discrimination and Disparities Page 6
All this happened too fast for such sweeping policy reversals in non-profit organizations to have been due to changing personnel in the role of decision-makers. In many, if not most, cases the same decision-makers who had discriminated against blacks were now instituting preferential policies favoring blacks. In neither case was the policy necessarily due to the personal beliefs, biases or values of the individual decision-makers, nor was the change necessarily due to “road to Damascus” conversions of personal views occurring among innumerable decision-makers at the same time.
UNINTENDED CONSEQUENCES
In addition to laws and policies directly concerned with Discrimination II, other laws and policies with very different purposes can also change the amount and impact of adverse consequences on groups defined by race, sex or other characteristics. In short, unintended consequences can affect outcomes as readily as intended consequences, and sometimes even more so. Minimum wage laws and building restrictions are two examples among others.
Minimum Wage Laws
Although minimum wage laws in the United States apply without regard to race, that does not mean that their impact is the same on blacks and whites alike. Where rates of pay are determined, not by supply and demand in a free market, but are imposed by minimum wage laws, that can affect the cost of Discrimination II to the discriminator.
A wage rate set above where it would be set by supply and demand in a freely competitive market tends to have at least two consequences: (1) an increase in the number of job applicants, due to the higher wage rate, and (2) a decrease in the number of workers actually hired, due to labor’s having been made more expensive. In this situation, the resulting chronic surplus of job applicants beyond the number of jobs available reduces the cost of refusing to hire qualified job applicants from particular groups, so long as the number of qualified job applicants refused employment is not greater than the number of surplus qualified applicants.
When, for example, the number of qualified black job applicants refused employment can be easily replaced by otherwise surplus qualified white or other job applicants, that reduces the cost of Discrimination II to the discriminating employer to virtually zero. On the most basic economic principles, such a situation makes racial or other discrimination far more affordable by employers, and therefore more sustainable, than in a situation where wage rates are determined by supply and demand in a free, competitive market.
In the latter case, where supply and demand leave no chronic surplus or chronic shortage of labor, qualified black job applicants turned away have to be replaced by attracting additional other qualified job applicants from other groups by offering higher pay than what that pay would be by supply and demand in a freely competitive and non-discriminatory labor market. In other words, Discrimination II has costs in a free market, greater than its costs when a minimum wage law creates a chronic surplus of job applicants.
Empirical evidence is consistent with this hypothesis. The prevailing national minimum wage law in the United States is the Fair Labor Standards Act of 1938. However, high rates of inflation that began in the 1940s put virtually all money wages above the level specified in that Act, so that for all practical purposes, there was no minimum wage in effect a decade after the law was passed. As economist George J. Stigler pointed out in 1946, “The minimum wage provisions of the Fair Labor Standards act of 1938 have been repealed by inflation.”37
As of 1948, during this period of no effective minimum wage law, the unemployment rates of both black and white teenagers were just a fraction of what they would become in later years, as minimum wage rates began rising in the 1950s to catch up, and then keep up, with inflation in later years.
What is particularly striking, however, is that there was no significant difference between the unemployment rates of black and white teenagers in 1948. The unemployment rate for black 16-year-old and 17-year-old males was 9.4 percent. For their white counterparts, the unemployment rate was 10.2 percent. For 18-year-old males and 19-year-old males, the unemployment rate was 9.4 percent for whites and 10.5 percent for blacks. In short, there was no significant racial difference in unemployment rates for teenage males in 1948,38 when there was no effective minimum wage.
After the effectiveness of the minimum wage law was restored by recurring minimum wage increases in later years, not only did teenage unemployment rates as a whole rise to multiples of what they had been in 1948, black teenage male unemployment rates became much higher than the unemployment rates for white teenage males—usually at least twice as high for most years from 1967 on into the twenty-first century.39
Labor force participation rates tell much the same story. As of 1955, labor force participation rates were virtually the same for black and white males, aged 16 and 17. For 18-year-old and 19-year-old males, blacks had a slightly higher labor force participation rate than whites, as was also true of males aged 20 to 24. But this pattern changed drastically, as minimum wage rates rose over the years.
In the mid-1950s, black labor force participation rates for 16-year-old and 17-year-old males began falling below that of their white counterparts, and the gap grew wider in succeeding decades. For males aged 18 and 19, the same racial reversal in labor force participation rates occurred a decade later, in the mid-1960s. For males aged 20 to 24, that same racial reversal occurred at the beginning of the next decade, in 1970.
The magnitude of the racial difference in labor force participation rates among males, after the racial reversal, followed the same pattern, being greatest for the 16-year-olds and 17-year-olds, less for males aged 18 and 19, and least for males aged 20 to 24.40
These labor force participation patterns shed additional light on the basis for racial differences in employment. If the primary reason for that racial difference in labor force participation rates was racism, there was no reason for such reversals, and especially reversals in different years and with different magnitudes for different age groups.
People who are black at age 16 remain black as they get older, so there is no basis for racists to change their treatment of blacks in such patterns as black workers age. But, if the real reason for these patterns was that the work experience and job skills of younger black workers made them less in demand than older black workers with more work experience and/or more job skills, then a rising minimum wage rate prices the younger blacks out of jobs first and to the greatest extent.
Unfortunately, when minimum wage laws reduce the employment prospects of inexperienced and unskilled black teenagers, that reduces their labor force participation, and therefore reduces their rate of acquisition of work experience and job skills. Whatever the degree of racism, it cannot explain age differences in employment among young black males, who do not change race as they grow older.
This pattern of virtually no difference in unemployment rates between black and white teenagers when wages were determined by supply and demand in a free market, but with large and enduring racial differences in unemployment rates when minimum wage laws became effective again, also fits the economic principle that a chronic surplus of job applicants reduces the cost of discrimination to the employer.
This pattern establishes correlation between increased minimum wage rates and changing racial differences in unemployment among teenagers. If this does not conclusively prove causation, it does at least establish a remarkably persistent coincidence.
Alternative explanations for these changing patterns of racial differences—such as racism, poverty or inferior education among blacks—cannot establish even correlation with changing employment outcomes over the years, because all those things were worse in the first half of the twentieth century, when the unemployment rate among black teenagers in 1948 was far lower and not significantly different from the unemployment rate among white teenagers.
Building Restrictions
Severe restrictions on building homes or other structures swept through various parts of the United States during the 1970s, in the name of preserving “open spa
ce,” “saving farmland,” “protecting the environment,” “historical preservation,” and other politically attractive slogans. But, however they were characterized, what such laws and policies did in practice was forbid, or drastically reduce, the building of either housing or other structures. Coastal California, including the entire peninsula from San Francisco to San Jose, was one of the largest regions where severe building-restriction laws and policies arose and prevailed.
The predictable effect of restricting the building of housing, as the population was growing, was a rise in housing prices, when the supply of housing was not allowed to rise as the demand rose. California home prices were very similar to those in the rest of the country before this wave of building restrictions swept across the coastal regions of the state in the 1970s. But, afterward, San Francisco Bay Area home prices rose to more than three times the national average.41
In Palo Alto, adjacent to Stanford University, home prices nearly quadrupled during the 1970s, not because more expensive homes were being built—for there were no new homes built in Palo Alto during that decade. Existing homes simply skyrocketed in price.42 By the early twenty-first century, the top ten areas in the United States with the biggest home price increases over the previous five years were all in California.43
The racial impact of these housing restrictions was more pronounced than many racially explicit restrictions. By 2005, the black population of San Francisco was reduced to less than half of what it had been in 1970, even though the total population of the city as a whole was growing.44 In an even shorter span of time, between the 1990 and 2000 censuses, three other California counties—Los Angeles County, San Mateo County, and Alameda County—had their black populations decline by more than ten thousand people each, despite increases in the general population in each of those counties.45
By contrast, Harlem was a predominantly white community as late as 1910, and there were openly proclaimed and organized efforts by white landlords and realtors to prevent blacks from moving into Harlem.46 But, like the organized white efforts to suppress black earnings in the postbellum South, the mere presence of such organized efforts was no evidence or proof that they achieved their goal. To call such explicitly racist efforts in Harlem unsuccessful would be an understatement.
Those white landlords and realtors in Harlem who held out while others began to rent to blacks, found themselves losing white tenants who moved out of the neighborhood as blacks moved in, leaving the holdouts’ buildings with many vacancies, representing lost rent.47 The collapse of these organized efforts to keep out blacks is hardly surprising under these conditions.
No such economic consequences inhibited those residents and their elected officials in later years who restricted the building of housing in San Francisco and other coastal California communities through the political process, driving up home prices and rents to levels that many blacks could not afford. On the contrary, such restrictions on new building increased the market value of the existing homes of residents in those communities and permitted higher rents to be charged by landlords in a market with severe housing shortages.
Attitudes and beliefs, however strongly held or loudly proclaimed, do not automatically translate into end results—into “what emerges”—especially when there are costs to be borne by discriminators themselves.
It may well be that the racial attitudes and beliefs held by white landlords and realtors in early twentieth-century Harlem were more hostile to blacks than the attitudes and beliefs of white residents and officials in late twentieth-century San Francisco and other coastal California areas. But, in terms of end results, the actions of the former failed to keep blacks out of Harlem, while the actions of the latter drove out of San Francisco half the blacks already living in that city. Costs matter.
* As a personal note, some years ago an elderly relative was crossing a busy thoroughfare alone in the Bronx, when she lost consciousness and fell to the ground in a high-crime neighborhood. People on the sidewalk rushed out into the street, to direct traffic around her. One of the women in the group took charge of her purse and returned it after my unconscious relative revived. Not a cent was missing from the purse.
* A study of employment in government-regulated public utility monopolies, back when that included all telephone companies, pointed out that little worker recruitment was necessary to fill their jobs because, in large cities, “applicants often number in the thousands for a few hundred openings.” Bernard E. Anderson, Negro Employment in Public Utilities: A Study of Racial Policies in the Electric Power, Gas, and Telephone Industries (Philadelphia: Industrial Research Unit, Wharton School of Finance and Commerce, University of Pennsylvania, 1970), p. 157. Generous pay and benefits also allowed such companies to cherry-pick the enlarged applicant pool for whatever kinds of personalities or other characteristics would make for a more congenial and manageable workforce.
* As a personal note, the first time I encountered a white professor at a white university with a black secretary, it was Milton Friedman at the University of Chicago in 1960–four years before the Civil Rights Act of 1964.
Chapter 3
SORTING and UNSORTING PEOPLE
Much empirical evidence suggests that human beings do not interact randomly—nor as frequently or as intensely—with all other human beings as with selected sub-sets of people like themselves. In short, people sort themselves out, both in where they choose to live and with whom they choose to interact most often and most closely. It is worth examining some of that empirical evidence as to self-sorting, before going on to consider the consequences of third-party sorting or unsorting of other people. The crucial point here is that, when people spontaneously sort themselves, the results are seldom even or random, and are often quite skewed.
RESIDENTIAL SORTING AND UNSORTING
Where people live has, at various times and places, been decided either by the people themselves or by others who imposed various restrictions through a variety of institutional devices, ranging from government laws and policies to many private formal and informal means, ranging from restrictive covenants to homeowners’ associations to outright violence against individuals or groups who have sought to live in neighborhoods where they were not welcome.
Residential and Social Self-Sorting
Immigrants have seldom immigrated evenly or randomly from their country of origin. Nor have they settled evenly or randomly in the country they reached. For example, two provinces in mid-nineteenth-century Spain, containing 6 percent of the Spanish population, supplied 67 percent of the Spanish immigrants to Argentina. Moreover, these immigrants tended to live clustered together in particular neighborhoods in Buenos Aires.1
Similarly skewed patterns of settlement have been common around the world, among other immigrants moving from their country of origin to their country of settlement. During the era of mass emigration from Italy, for example, Italian immigrants in Australia, Brazil, Canada, Argentina and the United States not only tended to cluster together in predominantly Italian neighborhoods but, more specifically, within those neighborhoods people from Genoa, Naples or Sicily clustered together with other people from those same respective places in Italy.2
During that same era, the massive immigration of Eastern European Jews to America was concentrated in New York’s Lower East Side. But within those Jewish neighborhoods, Hungarian Jews were largely clustered in their own enclaves, as were Jews from Romania, Russia and other places in Eastern Europe.
German Jews, who had lived in their own enclave on the Lower East Side decades before the mass arrival of Eastern European Jews, were already leaving that neighborhood as they rose socioeconomically, and were increasingly locating in other parts of New York as the Eastern European Jews arrived. Such spatial and social separation between German Jews and Eastern European Jews was common, both in New York3 and in Chicago.4
Lebanese immigrants to Sierra Leone in Africa or Columbia in South America likewise settled in enclaves of other Lebanese from
the same parts of Lebanon and of the same religion, with Catholic Lebanese from particular places in Lebanon settling together and separate from enclaves of Orthodox Christians from Lebanon or Lebanese Shiite Muslims.5
German immigrants who settled in nineteenth-century New York not only settled in an area of Manhattan called Kleindeutschland (little Germany), Hessians clustered in one part of Kleindeutschland, while Prussians clustered in another.6
People tend to sort themselves out, not only in their residential patterns but also in their social interactions. Twentieth-century Japanese immigrants to Brazil not only settled in Japanese enclaves, most Okinawan immigrants in Brazil married other Okinawans, rather than marrying Japanese from other parts of Japan, much less marrying members of the Brazilian population at large.7
It was much the same story among German immigrants in nineteenth-century New York, where most Bavarians married other Bavarians, and most Prussians married other Prussians. Among the Irish immigrants as well, most nineteenth-century marriages that took place in New York’s Irish enclaves were marriages between people from the same county in Ireland.8
In the Australian city of Griffith, in the years from 1920 to 1933, 90 percent of Italian men who had emigrated from Venice and gotten married in Australia married Italian women who had also emigrated from Venice. Another five percent married Italian women from other parts of Italy, the same percentage as married “British-Australian” women.9
However striking these patterns may be statistically, they are not patterns that most people are made aware of by seeing them with the naked eye, as is the case with differences between black neighborhoods and white neighborhoods in the United States. As a result, black-white residential separations have been seen and treated as if they were unique, as well as being inconsistent with prevailing background assumptions of equal or random outcomes in the absence of discriminatory impositions.