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Analyze the impact of deindustrialization on a global and regional scale and the role of technology in deindustrialization

Dissertation : Analyze the impact of deindustrialization on a global and regional scale and the role of technology in deindustrialization. Recherche parmi 237 000+ dissertations

Par   •  14 Octobre 2017  •  Dissertation  •  3 892 Mots (16 Pages)  •  387 Vues

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Clea Bonnet, 1SIA                                                                                                                                     05/09/17

Analyze the impact of deindustrialization on a global and regional scale and the role of technology in deindustrialization

Since the 1970s, developed countries have been witnessing the demise of their heavy and manufacturing industries and the subsequent growth of their service sector. Deindustrialization is defined as the process of social and economic change caused by the removal and/or reduction of industrial activity or capacity in a region or economy. This essay will analyze the global and regional impacts of the deindustrialization which has been sweeping across the developed world as well as the role technology plays in this process. Firstly, it will be shown how the retraction of the industrial sector and the expansion of the service sector have led to a global market shift with the manufacturing work force diminishing in MEDCs and growing in LEDCs and the increase of the former’s service work force. Secondly, how the regional job market has been affected as a result of an uneven deindustrialization and/or the relocation of industries into another, more profitable region. Moreover, this essay will focus on the social and economic deprivation facing deindustrialized regions and the way this may affect internal migration flows. It will be shown that although short-term and sectorial unemployment may rise, long-term unemployment will remain relatively unchanged and how deindustrialization may encourage a change in regional/national governments and union policies. Finally, the role of technology in deindustrialization will be studied.

With the global shift of manufacturing industries from developed countries to lower wage economies, the global job market has witnessed the relocation of the manufacturing work force. Indeed, less economically developed countries (LEDCs) are becoming increasingly attractive to manufacturing industries as they offer lower cost locations (cheaper land and/or smaller relative distance to materials for production), an unregulated, cheaper and more abundant work force capable of working longer hours for lower wages and generally looser laws and regulations regarding pollution and other environmental concerns.  Consequently, the manufacturing work force of these countries increases at the expense of those left-behind by the departure of industrial employers in developed nations. An example of this would be the brand Levis’, whose story embodies that of the “American Dream”.  Today, the flag brand of American culture imports 99% of their products, which they produce in a number of developing countries, such as China or Bangladesh. In 1999, the company announced it would be closing down half of its 22 US based plants (more of which have closed since), slashing 5,900 jobs, or 33% of its total North American work force (US and Canada combined), in an attempt to compete more effectively with rivals who largely make their products overseas, where labor costs are cheaper. Overall, the more economically developed countries’ (MEDCs) share of global manufacturing products and work force is decreasing as they gradually filter down to LEDCs.

Similarly, the manufacturing work force has, in some cases, seen a more regional shift. Admittedly, this displacement seems more prominent in regions where statism, a political system in which the state has substantial centralized control over social and economic affairs, applies. In these cases, significant differences in wages, Worker Union leverage etc. may manifest themselves, rendering a region much more industrially profitable than another, in the same way LEDCs compare to MEDCs. For instance, the heavily unionized Midwest and Northeast US states have seen their manufacturing job market drop as industries relocate to the Southeast and Southwest states, where “right-to-work” laws restrict the Unions’ influence and the high supply of workers diminishes their value, lowering wages. The previously named “Steel Belt”, former industrial heartland of the United States is now commonly referred to as the “Rust Belt” following the transfer of surviving manufacturing industries to the west.

Moreover, regions facing deindustrialization are often prone to a downward spiral of deprivation which furthers the depression of local economy. The departure or decline of industries central to a region’s economy generates the reverse effect of Myrdal’s model: the driving industry shuts down and collateral firms move away. House prices drop, the local economy grows depressed and the region, without necessary funds, becomes unattractive to prospective inhabitants. In Oldham, designated as “the most deprived area of the United Kingdom”, the local economy has suffered tremendously from the decline of the English textile industry. Indeed, the former boomtown of the Industrial Revolution, recognized as “one of the most important centers of cotton and textile industries in England” up to the mid-20th century, saw its last cotton mill close down in 1998. It has since failed to recuperate and, in an article written by one of its inhabitants, it is said: “The facilities available for just 50p are world class. But not many children get the chance to use it, as parents cannot afford even the 50p fee”, demonstrating how poor its population has become.

As previously mentioned, regions whose economy relies heavily on a declining or departing industry suffer severe economic and social consequences as a result of deindustrialization. The inhabitants of such regions are faced with the decision of remaining in the increasingly deprived region or migrating to a more dynamic region, whose economy generally centers on newer, more profitable industries such as technology. The poster image for this type of migration is Detroit. Previously a center of industrial production and a cultural hotspot, the city suffered from the relocation of its industries during the 1980s and 1990s. As jobs disappeared, its inhabitants moved away: from 1980 to 2012, its population decreased from 1,200,000 to 700,000. What remains of Detroit’s population suffers from high unemployment, crime and poverty rates. Hence, deindustrialization encourages regional migration. For those who fail to move away, long-term unemployment and deprivation isolates them from mainstream society, enclosing them in “islands of deprivation”.

Although the industrial labor and job market decreases with deindustrialization, it is commonly accepted that the later does not result in long-term higher unemployment rates. Indeed, jobs lost in the industrial sector are often compensated for by the creation of new jobs in the growing service sector. Indeed, as technology advances, manufacturing becomes cheaper and consumers are left with more disposable income. When these individuals have met their material needs and desires, they turn to services to increase their quality of life. Therefore, as deindustrialization progresses, the service sector grows, creating more job opportunities. From 1980 to 2011, the US manufacturing employment dropped from 30 to 18%, while the service sector employment rose from 65 to 80%. The German job market evolved in a similar fashion: its manufacturing employment decreased from 42 to 23% and its service sector employment rose from 52 to 72%. Similar fluctuations have been noticed in the United Kingdom. However, it is important to note that unemployment amongst low-skill workers has risen as these individuals often find the transition from heavy industry/manufacturing to service and skilled manufacturing difficult.  Overall, long-term unemployment has not significantly increased as a result of deindustrialization. However, worker groups (low-skill, skilled…) have seen employment and unemployment rates drastically change.


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