Test 3

  • June 2020
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Trent Berger A plethora of reasons exist as to why U.S. Internal migration rates have generally fallen sharply from the mid 1970’s to the mid 2000’s. To begin, a few demographic trends in the U.S. should be identified. First, in the late 1960s the U.S. population shifted from the baby boom to the baby bust, were fertility rates declined drastically from the record rates of the mid 1940’s to the mid 1960’s.1 Second there has been a rise in divorce rates and the entry of women in the labor force.2 Also of significance is the GI bill, which helped spur home construction post WWII and subsequently increase the rate of home ownership. All of these above trends factor as to why U.S. internal migration rates generally have dropped over the last 30 years. The push-pull theory of migration holds that the decision to migrate is determined by the pros and cons of the origin vs. the pros and cons of the destination along with the intervening variable in between.3 The introduction of the GI bill post WWII made home ownership much more obtainable and helped lead a rise in the construction and marketplace for suburban housing. As the U.S. population became more likely to own a home, this increased the attractiveness of the current destination, reducing the chances of migration. Not only that, but owning a home poses a significant obstacle or intervening variable in moving. The potential migrant will have to not only invest time and money into selling a home, but likely will own more possessions, adding cost expenses to moving, all of which poses additional hassles.

1

Kent, M.M and Mather, M (2002). What Drives U.S. Population Growth? Population Bulletin 57(3), 340. 2 Suzanne M. Bianchi and Lynne M. Casper, “American Families,” Population Bulletin 55(4), 5-39. 3 Lee, E. S. (1966). A Theory of Migration. Demography, 3, 47-57.

Along those lines, the equilibrium perspective held migration occurs less for jobs and more for quality of life factors, such as housing and labor balance.4 However, if a person in their current location (Ohio) owns a home assessed at $100,000, then despite the warmer climate of California, the burden of losing the stability and equity of their Ohio home along with the prohibitive costs of home ownership in California may lead to the person not migrating to the generally assumed more attractive destination. Similarly not only does the cost of moving and home ownership inhibit migration, but the question of employment arises. Taking the Ohio example, a person there might live in a place with generally lower wages and employment opportunities than say New York City. However, given the cost to move and obtain new housing, the salary in Ohio might actually be higher when adjusted for cost of living. The potential migrant might take years, depending on the profession, to make up for the moving costs. Furthermore, while employment rates might be better in a place such as New York City vs. Ohio, potential migrants from Ohio might not necessarily have more opportunities to get work. If they have been a longtime resident of their current location, chances are they have connections and a strong ability to network for work as opposed to a foreign location with few contacts. These factors of housing and networking also represent another inhibitor of migration, liquidity constraints. One crucial component of Ravenstein’s theory was that migration itself is a highly selective process.5 Specifically, that the rate of migration varies across different ages and characteristics of people. For instance, persons who are younger and more educated are more likely to migrate. This cohort is less likely to be tied down to a community via 4

Hunt, G. L. (1993). Equilibrium and Disequilibrium in Migration Modeling. Regional Studies, 27, 341341. 5 Lee, E. S. (1966). A Theory of Migration. Demography, 3, 47-57.

children in school or home ownership. They also might be more opportunities for employment elsewhere, particularly if they went away to college. However, referring to fertility rates, the U.S. is an aging population.6 Young and educated people could be just as mobile today as they were in the mid 1970s. The proportion of young people in the population however, as shown on the age composition pyramid, is less significant today than in the past.7 Increasingly people in their senior years are occupying a greater share of the population. David Plane’s research showed that the elderly are less likely to move than other age cohorts, a significant for why net migration is dropping.8 Life Course Theory corroborates David Plane’s findings.9 Life Course Theory holds that the importance of time, context, process, and meaning on family life.10 It states that depending upon were people are at during these various time stages of life, this will influence and explain their behavior. One example is age-graded trajectories, like migration. A relatively young adult moving away to go to school is seen as being the norm, while teenage and elderly migration would be viewed as an off-age transition. Even more telling about life course theory is the principle of linked lives. The women’s’ rights movement gave way to more freedom and the ability of more woman to have sustainable careers. Family life has shifted from having the male husband as the bread winner with a stay home mom to both being in the labor force.11 While the male

6

Kent, M.M and Mather, M (2002). What Drives U.S. Population Growth? Population Bulletin 57(3), 340. 7 See above 8 Plane, D. A., Henrie, C. J. & Perry, M. J. (2005). Migration Up and Down the Urban Hierarchy and Across the Life Course. Proceedings of the National Academy of Sciences, 102, 15313-15318.

9

Marriage and Family Encyclopedia. (n.d.). Life Course Theory - Historical Development, Key Principles And Concepts, Selected Research Applications. Retrieved November 19, 2009 from http://family.jrank.org/pages/1074/Life-Course-Theory.html. 10 See above 11 Suzanne M. Bianchi and Lynne M. Casper, “American Families,” Population Bulletin 55(4), 5-39.

might still be the bread winner in terms of income, having both partners in the labor force adds a constraint to migration. A more attractive employment opportunity may exist for one partner in another destination, but finding suitable jobs for both partners in a new location poses an additional hurdle that can explain migration decreases.

All of the above is not to say that U.S. Internal Migration, defined as moving from one county to another county, is not occurring. Ravenstein stated that most migration occurs within short distances.12 Furthermore he theorized that when migration does occur, with people moving from B to A, this sets off a series of chain migrations with people moving from C to B, D to C, and so fourth.13 Not only that, but migration from one location, A-B, sets up a counter streaming network that can relay employment and other opportunities between both places setting up B-A reverse migration.14 Thus, a series of intra-county movements from the older, denser urban cluster to the rural hinterland might be occurring but not officially recognized. David Plane validated step-migration theory that migration is occurring but moreso with migrants moving down from densely populated metropolitan areas to lesser populated regions along the hinterlands in a counter urbanism movement.15 His research showed high rates of net out-migration for the age cohorts of 10-14 and 15-19 to smaller metropolitan and non CBSA communities.16 However, the same research showed a rebound effect with 20-24 and 25-29 cohorts moving back up the urban hierarchy before

12

Lee, E. S. (1966). A Theory of Migration. Demography, 3, 47-57. See above 14 See above 15 Plane, D. A., Henrie, C. J. & Perry, M. J. (2005). Migration Up and Down the Urban Hierarchy and Across the Life Course. Proceedings of the National Academy of Sciences, 102, 15313-15318. 16 See above 13

the 30-34 and 35-39 cohorts moved back down the urban hierarchy.17 Also noteworthy, David Plane’s results found those cohorts for ages 75 and up show the lowest rates of mobility.18 As was already discussed, this cohort makes up an increasingly larger share of the U.S. population. Thus, migration is occurring. However, this is done in a dynamic, counterbalanced fashion were cohorts leaving metro areas (15-19, 30-39) are replaced at the same time by other cohorts (immigrants and 20-24 year olds) which along with the increasingly aging elderly population, more than offset overall migration rates.

Given these explanations, several implications exist for the future. Many older, industrial communities in the rustbelt and northeast have long feared that Internal Migration is to their disadvantage due to the loss of young, productive workers (braindrain) and a diminished tax base and economy. After reviewing the Internal Migration rates of the past 30 years and understanding the theories behind such movements, this might indicate the rustbelt and northeast has less to fear. Perhaps as the disequilibrium theory states, people have migrated from the rustbelt to the sunbelt in search of employment but that such behavior has been saturated. The benefits of moving to warmer climate with an expanding economy, the return of the investment, are being diminished. Overall wages relative to cost of living in the destination has declined; opportunities for employment are not much better that at the origin. Perhaps as well migration is occurring from northeast states like Connecticut, were young adults move away for college and to get established in their careers. 17

See above Plane, D. A., Henrie, C. J. & Perry, M. J. (2005). Migration Up and Down the Urban Hierarchy and Across the Life Course. Proceedings of the National Academy of Sciences, 102, 15313-15318. 18

However, once they enter the next life stage, in their young 30s seeking good schools and affordable housing, they return to Connecticut. All of this suggests that certain policies, such as merit scholarships and home ownerships, might have made staying at the origin location attractive enough to offset the amenities and other benefits of the destination as holds the push-pull theory. In this case, areas with a history of out-migration such as the rustbelt might focus on scholarships, home ownerships, and marketing a lower cost of living to retain residents and return those who have already left. Just as these patterns can provide hope for industrial regions, they also can serve as a warning for trendy spots like California. In the 90s for the first time California, long the dream spot for migrants, actually experienced a heavy stream of out-migration.19 Factors such as pollution, over-crowding, and prohibitive housing were cited as reasons.20 Should disasters like hurricanes, poor schools, and bad infrastructure not be fixed, it isn’t inconceivable other long held sunspots in the sunbelt, Texas and Florida for example, might also see a reversal of migration patterns. This suggests the attractiveness of a warm climate might not be enough to sustain current migration trends in perpetuity, and thus sunbelt destinations should not take for granted the need to wisely invest in capital improvements to maintain their relative desirability in the future.

19

Plane, D. A., Henrie, C. J. & Perry, M. J. (2005). Migration Up and Down the Urban Hierarchy and Across the Life Course. Proceedings of the National Academy of Sciences, 102, 15313-15318. 20 See above

References Hunt, G. L. (1993). Equilibrium and Disequilibrium in Migration Modeling. Regional Studies, 27, 341-341. Kent, M.M and Mather, M (2002). What Drives U.S. Population Growth? Population Bulletin 57(3), 3-40. Lee, E. S. (1966). A Theory of Migration. Demography, 3, 47-57. Marriage and Family Encyclopedia. (n.d.). Life Course Theory - Historical Development, Key Principles And Concepts, Selected Research Applications. Retrieved November 19, 2009 from http://family.jrank.org/pages/1074/Life-Course-Theory.html. Plane, D. A., Henrie, C. J. & Perry, M. J. (2005). Migration Up and Down the Urban Hierarchy and Across the Life Course. Proceedings of the National Academy of Sciences, 102, 15313-15318. Suzanne M. Bianchi and Lynne M. Casper, “American Families,” Population Bulletin 55(4), 5-39.

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