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Transforming Economy
The economic and industrial structure of U.S. cities changed dramatically in the 1970’s. Cities in the Northeast and Midwest lost many of their manufacturing industries while gaining service industries (e.g. finance and real estate). In contrast, Southern and Western or sunbelt cities typically experienced gains in both types of industries. These shifts in industry continued into the 1980’s. As a result the types of jobs available in cities (especially in the Northeast and Midwest) began to shift away from low skilled, well paying manufacturing jobs to service jobs which were either low skilled, low paying or high skilled, high paying. In other words, as the traditional manufacturing base in many Northeast and Midwest cities began to erode, the employment opportunities in these areas started to shift. Consequently, to obtain better paying jobs, training and education beyond high school grew in importance. Thus, what has evolved is a mismatch between types of jobs and the skills of the persons available in cities – better known as the spatial mismatch theory.
According to the spatial mismatch theory (Kasarda 1985, 1990), two major changes in the U.S. occurred that led to massive economic dislocation of low skilled workers with low educations in central cities. The first change is related to the transforming economy in urban areas of the Northeast and Midwest in the 1970’s and 1980’s. The economy changed from a manufacturing/ industry based economy to a high tech/service sector based economy. In the manufacturing economy many low skilled jobs with sufficient income were readily available. Thus, a worker did not have to have any education beyond a high school diploma (if that) to easily support a family. But, with the movement of many manufacturing industries to the suburbs, the American South and West, and to less developed countries, urban areas in the Northeast and Midwest lost many low skilled jobs that paid an adequate wage.
Subsequently, as previously mentioned, two types of jobs were created. The first type created were high wage jobs in high tech fields such as insurance, real estate, finance, and other highly skilled service areas requiring a college degree. In contrast, the second type of jobs created were low wage jobs in the service sector (i.e., retail, fast food) requiring very little education. Along with the transformation of the economy from manufacturing to the high tech/service sector economy and the movement out of many blue collar jobs, there has been an increase in the number of persons with low education in central cities, particularly young black males (Wilson 1987). Thus, this transformation has lead to a spatial mismatch. The education levels of many persons in urban areas no longer match the required skill levels in the jobs available. Most low educated persons do not have the resources to relocate to areas where the low skilled manufacturing jobs have moved or even to commute to those jobs in situations when movement was to the suburbs (Choke and Shumway 1991).
Change in the economic and industrial structure of cities in the United States and changes in the political structure (Wilson, 1979) led to changes in the composition of persons in cities. According to Wilson (1987, 1991), with changes in employment opportunities working and middle classes moved out of central cities leaving the lower class behind (especially the black lower class) with no well paying jobs, opportunities, or positive role models. This movement eventually led to the formation of an urban underclass (or ghetto poor) in U.S. cities, especially in the Northeast and the Midwest. In addition to the importance of class segregation, Massey and Denton (1993) stressed the importance residential segregation played in the formation of the primarily black urban underclass.
Thus what has emerged is a large group of people living in the central city with education levels that do not match the jobs available. With the shift in the economy of the Northeast and Midwest from manufacturing to service, the unemployment levels have increased and employment dislocation has resulted.
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Employment Dislocation
While employment dislocation leads to joblessness among many inner city residents, it can also lead to the creation of an urban underclass. Definitions of the underclass vary but most are closely linked to areas of high poverty (Ricketts and Sawhill 1988). Initially the term underclass was defined primarily in terms of income. But in the 1980’s the term took on behavioral and moral overtones referring to the underclass as persons residing in areas with high crime rates, high premarital pregnancy rates, high unemployment rates, and high welfare dependency rates (Auletta 1982; Wilson 1991; Jargowsky and Bane 1990). The term urban underclass today is used to represent the segments of the urban poor that have deviant social behaviors and most of these people are minorities (Jargowsky and Bane 1990).
Joblessness itself is not as much of a problem as the problems it can cause and the role conflicts it produces. Traditionally, in two parent families the male has played the role of the breadwinner while the female stayed home, raised the children, and ran the household. It has been suggested that when men have no job or they are not the principle breadwinner in the family they lose status. They can no longer assume the breadwinner role and as a result, divorce and separation are more likely (Farley 1988). “The central factor in this situation is the inability of black males to meet the normative responsibilities of husband and father.” (Staples 1985). In addition, especially among blacks, high unemployment rates among young males make them less desirable partners for marriage (Wilson 1987; Lichter et al. 1992; South and Lloyd 1992). Finally, Testa et al. (1993) found that regardless of race, employed fathers were two times as likely to marry the mother of their first child than unemployed fathers.
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Family Structure Changes
Divorce and separation lead to family structure changes. The decline of the two parent household has occurred in conjunction with the growth of female-headed households. There are two major problems with female-headed households: Females earn less money than males (even for the same job with same skills), and females are more likely to work in lower wage jobs (female sex-typical occupations).
Racial differences are an important factor in family structure today. This is in contrast to the past. Prior to 1950, blacks and whites had similar percentages of ever-married persons. But since the 1950’s and more significantly since the 1960’s the racial gap in marriage patterns has grown (Wilson 1987). Black women today are more likely to either delay marriage or postpone it indefinitely. In addition, while black marital fertility, along with white marital fertility, has dropped since the baby boom of the 1950’s and early 1960’s black nonmarital fertility has not (Wilson 1987). Thus, this has led to an increase in never-married or female-headed families.
The economic transformation of the 1970’s led to shifts in the economy from a manufacturing base to a service base. With this shift much employment dislocation took place as the skills of workers became mismatched with the jobs available (especially the high paying jobs). Many men were unable to fulfill their “bread-winner role” and the result was the tremendous increase in female-headed families. This link between economic changes and the growth of the female-headed family is the main focus of this paper. The link is important because of the potentially harmful effects female-headed families can have on children in terms of poverty.
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Data and Methods
This study uses data from the Urban Underclass Database developed by Kasarda at the University of North Carolina. The database contains data from 1960-1990 compiled from various sources on the largest 100 cities (in 1980) by population size in the United States. This analysis uses data originally from the Summary Tape Files of the U.S. Census. City is the unit of analysis. It refers to the central city only and not the surrounding suburbs.
The first analysis will be primarily descriptive. It will focus on the transformation of the economy section of Figure 1. Industry variables are created to measure the economic situation of a city. They are designed to represent the changing economy of the U.S. from 1970 to 1990. Industry is divided into four categories: Manufacturing, low income service, high income service, and agriculture. Each represents the percentage of industries in that category. Manufacturing industries are industries in construction, manufacturing, and transportation, communication, or utilities. Low income service industries are industries in person services, retail trade, business services, and health services. In contrast, high income service industries include: wholesale trade; education services; finance, insurance, or real estate; public administration, and other professional services. Finally, agriculture industries are agricultural and mining industries. Agriculture industries are not included in the analysis because of their lack of importance in urban areas.
Because the family represents a more primary unit than the household, families will be used in this study instead of households. The family is defined as “the entire group of (2 or more) persons in a household who are related by blood, marriages or adoption.” In contrast, a household is defined as “all persons who occupy a housing unit [in separate living quarters].” (Shryock and Siegal 1976). Measures for percent married couple families and percent female-headed families with children under age 16 are included in the analysis. Percent female-headed is the dependent variable while percent married couple is only included in the descriptive statistics.
Race is an important determinant of family structure. Black families are much more likely to be female-headed than white families. In addition, despite the Civil Rights legislation of the 1960’s, blacks are still likely to face discrimination in the work place. As a result, the analyses includes variables for percent black and percent Hispanic (only in descriptive statistics) in each city.
Three measures are used to control for common indicators of female-headed families. They are area poverty, less than high school education. and sex ratio. Area poverty is measured by calculating the proportion of persons in poverty. This controls for the overall poverty level in a city and should be highly correlated with female-headed families. The percentage of persons aged 25 and over that have less than a high school education was also included. This is an indicator the percentage of persons with low education levels and indicates persons that would not make good marriage partners. The percentage of persons without a high school education is expected to have a positive effect on the percentage of female-headed families. Finally, sex ratio or the number of males to every 100 females was calculated to control for the number of males to females aged 15 to 59 available in each city. Presumably the more males there are available the fewer female-headed families there will be. It should be noted that the sex ratio is a fairly crude measure of available males because we are assuming than all males are available marriage partners and this is not always the case.
The 100 cities are classified by region. This is important because the changes in the economic structure differ greatly by region. The four regions used are Northeast, Midwest, South, and West. The census definition of a region was used to assign cities to regions. South is used as the reference category.
To examine the second hypothesis, that by 1980, employment dislocation was an important source of growth in female-headed families, two indicators of employment dislocation are included. The first measure is the male unemployment rate, which is used to represent unemployment. The male unemployment is defined as the percentage of male workers age 16 and over that are unemployed. Male unemployment should have a positive effect on female-headed families because unemployed males generally do not make good marriage partners.
Along with increasing unemployment levels the changes in types of jobs available in urban areas has also led to underemployment. Underemployment is indicated by a measure of part-year male workers. That is, the percentage of male workers age 16 or older that were employed less that 26 weeks in the year preceding the census. This variable should also have a positive effect on the percentage of female-headed families.
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Results and Discussion
To best understand the effects changes in the economy have had on family structure both descriptive statistics and multivariate regression models were calculated. The descriptive statistics for selected area characteristics at the city level are listed in Table 1. Descriptive statistics for industry by decade are listed in Table 2. These are calculated for all cities and by region. Table 3 contains regression models by decade, while Table 4 contains regression results for a stacked data file.
Table 1 provides a descriptive picture of the characteristics of the largest 100 cities in 1980 by decade. As expected the statistics illustrate the change in family structure that occurred in the 1970’s and 1980’s. During each decade the percentage of families that were female-headed with children grew while the percentage of families that were married couple families declined. By 1990, female-headed families with children made up 17.24 percent of all families while married couple families fell to 67.02 percent of all families.
In addition to the growth of female-headed families, poverty rates and the minority population increased from 1970 to 1990. Poverty increased from 14.8 percent in 1970 to 18.5 percent in 1990. While both the black and the Hispanic populations also increased, the gap between them in percentage of the overall population declined slightly. Contrary to expectation, the percentage of persons with less than a high school education declined in the two decades. The percentage with less than a high school education dropped tremendously from 1970 to 1990 (46.10 to 25.97 percent). This decline is probably a function of examining the city as a whole and not just areas with high numbers of female-headed families.
As expectedly both the overall unemployment and the male unemployment rates increased with the largest gains coming in the 1970’s. The unemployment rate almost doubled from 4.67 to 7.22 in this decade. The growth was somewhat smaller in the 1980’s. Finally, in terms of underemployment, the percentage of male workers 16 and over that worked part-time also grew.
Clearly family structure has changed significantly in cities in the last two decades with families becoming more female-headed. At the same time, cities are experiencing higher unemployment rates and more part-year employment, along with increases in both their poverty and minority populations. In the next section the patterns of change in the economic structure will be examined.
Table 2 examines the changing economic structure by region and for the country as a whole. While the percentages differ, the overall patterns are the same for all regions. During the last two decades each region experienced a decline in their manufacturing industries and a growth in both their low and high income service industries. The decline in manufacturing jobs was especially great in the Northeast (where 39.7 percent of all jobs in 1970 and 27.9 percent of all jobs in 1990 were in manufacturing industries) and in the Midwest (40.1 to 29.4 percent). In contrast, in the West, manufacturing jobs only declined from 29.5 to 26.6 percent in the same time period. In contrast to declines in manufacturing jobs, all regions experienced an increase in service industries. This includes both low skilled, low wage and high skilled, high wage jobs. The largest increases in both types of service industries were in cities of the Northeast and Midwest.
It is apparent that in the last two decades large cities in the U.S. have undergone a transformation of their economies. Manufacturing industries are declining while service industries are increasing. This transformation is particularly pronounced in the Northeast and Midwest where unemployment rates have doubled. The results of Table 2 indicate support for the first hypothesis, suggesting that the transformation of the economy in 1970’s and 1980’s led to employment dislocation or increased unemployment in urban areas. Given the support found for the first hypothesis, the next part of the model or the second hypothesis needs to be examined. The second hypothesis, or after 1980, employment dislocation has led, in part, to dramatic changes in family structure is examined in Tables 3 and 4.
Table 3 contains separate OLS regression models for 1970, 1980, and 1990. For each decade both the percent poor and the percent black in a city had a significant positive effect on the percentage of female-headed families. This was expected since these variables tend to be highly correlated. Areas with high poverty rates tend to have large numbers of female-headed families. In addition, the location of the city by region was also important in determining the percentage of female-headed families. With the exception of the West in 1970, each dummy variable for region was significant suggesting that cities in the Northeast, Midwest, and West all are more likely to have female-headed families than cities in the South. This was particularly true for cities in the Northeast, which by 1990 were 3.33 times as likely as cities in the South to have female-headed families.