Relationship Between Economic Growth And Its Determinants

After World War II, society experienced many changes due to economic growth. The reason for the rise in the economy is "… the developments in technology, methods of production, communication, and transportation..." (Background; lines 1-2). These changes "… led to far more goods and services for many people..." (Background; Lines 10-11).

Tulloch, et al. (2009) hypothesized that six underlying factors would be linked to residential mobility. The six factors are as follows: whether they are residing in time limited supported

In this study, I analyze how the economic restructuring affects income distribution in the gateway communities of the U.S. Lake States, relying on data from a number of different sources. Table 1 describes the data sources of public lands. In addition, various socioeconomic data are obtained from the 1990, 2000, and 2010 Decennial Census, and the 2005-2009 American Communities Survey (ACS). In order to measure income inequality for the study area, I use Gini coefficients based on sixteen income categories in each MCD during the periods.

For many decades, living out the American dream has meant living in the suburbs, surrounded by a white picket fence, with two and a half children, far from the noisy city. However, many people claim that in a couple years, the suburbs will be no more, and everyone will commence the migration back to the city. In order to understand this debatable topic, it is important to explore the rise of suburbs and what caused people to move out miles away from their place of work and center city in the first place.

In Burgesses model, the central town is surrounded by poor housing. The housing is low quality but there is short commuting time. The further one is away from the central business district, the better quality the housing becomes but the longer commuting time. This transition from low quality housing to longer commuting time occurs in the zone of transition. When people move further away from the center, they can afford both the better housing and the longer commuting. In this model, relative location effected both the housing and transportation

While the above test results demonstrate a strong negative relationship between geographic mobility and female households with no husband present, thus rejecting the null hypothesis that there is no relationship, one is not to assume this is a reliable reflection of the relationship between single motherhood and residential mobility. As the results show, only approximately 17 percent of the variability in geographic mobility of a state can be explained by female households with no husband present (r2= .166). An increase in the percent of female householders with no husband present only decreases the rate of geographic mobility by .27 percent (b= -.268).

Increasing populations additionally increase property value and tax, making it nearly impossible for local working-class families able to afford a home. Lack of job opportunities has caused a large portion of people to commute down to the resort on the Kohala Coast, approximately an hour drive, to work a minimum wage paid position. Many of the high paying jobs that are available are not held by people who have moved here for those positions, consequently, causing a sense of threat and creating a barrier between local people and “foreigners” since they see them coming over, taking their jobs and homes away, residing in resentment and frustration.

Second, I apply a spatial simultaneous equations model to control for spatial dependence. Third, I empirically focus on the U.S. Lake States region to analyze the effects of public lands on the population and employment growth. Finally, using U.S. census data from 1990-2010, I examine how the economic effects of public lands have changed between the periods of 1990-2000 and

First, the author had suggest a relatively wrong uncorrelated assumption between unemployment rate and business opportunities. The proportion of employed people out of the whole population of a region does not necessary create its that region competitive advantage in term of business attraction. In fact, the low employment rate can lead to high salary company have to pay payable due to the shortage of low job demand. The workers might changes their workplace once they are not satisfied with their salary. Second, the author does not mention any other sound advantages potentials that may benefit help companies gain prosperity, such as customer demand, demographic or rich resources…. Those factor may contribute largely to the overall atractiveness of the city. In a weak attempt to support the claim, the argument only describes the city as the industrial center of the region, and that the city has provided more than its share of the region’s manufacturing jobs. These elements is not enough to show clearly how city might help companies grow. Even in a subtle perspective, the reader still feel hard to imagine how helpful those elements is. And finally, the author does mention that the city is attempting to expand its economic base by

Metro workforce characteristics are able to account for the largest share of the variation in metro unemployment rates measured over complete business cycles. Characteristics more intrinsic to metro areas themselves account for much of this variation as well, though not as much as workforce characteristics. And moving costs are estimated to be high enough that some households will be unwilling to move away from high-unemployment metros.

Some early works suggest that home owners change their locations of residence less often than renters and, thus, home owners are immobile and less flexible. Nickell (1997) found that countries in which citizens are not shackled by the chain of permanent residence (flexible mobility) have relatively high employment rates. This point is also illustrated by Hughes and McCormick (1987), who examined links between housing policies, job mobility and unemployment in the UK. They found that UK housing policies, which seek to reduce spatial mobility, caused an inflexible, inefficient labor outcome in the UK

The theory of urban bias stems from the Urban Giantism problem. Todaro and Smith begin to describe the effects of Urban Giantism in Economic Development Ch. 7: Urbanization and Rural-Urban Migration: Theory and Policy. Here we can see contrasts between Urban Metropolitans in Developed

Economic growth is a necessary but not sufficient condition of economic development. There is no single definition that encompasses all the aspects of economic development. The most comprehensive definition perhaps of economic development is the one given by Todaro: ‘Development is not purely an economic phenomenon but rather a multi – dimensional process involving reorganization and re orientation of the entire economic and social system. Development is a process of improving the quality of all human lives with three equally important aspects. These are: 1.

Economic growth refers to the rate of increase in the total production of goods and services within an economy. Economic growth increases the productivity capacity of an economy, thereby allowing more wants to be satisfied. A growing economy increases employment opportunities, stimulates business enterprise and innovation. A sustained economic growth is fundamental to any nation wishing to raise its standard of living and provide a greater well being for all. Gross domestic product (GDP) is the monetary value of all final goods and services produced over a year. It is the total value of production within the economy. The total value of production is the total value of the final goods or services less the cost of

Globalization has combined with the sustained growth of urban areas in recent decades to strengthen urban-rural linkages, based on the increased integration of these areas, both spatially and functionally. Central to this process has been rural to urban migration. Nairobi, the capital city of Kenya, has an estimated population of 3.237 million (UN Habitat, 2014). Kenya has a population of 45.5 million, as estimated by the United Nations Population Fund (UNFPA, 2014). Nairobi, therefore, which has fully one-third of Kenya’s urban population, comprises some 8.4% of the country’s overall population. Between 2000 and 2010, Nairobi had an annual population growth rate of 3.80%, which is projected to rise to 4.23 and 4.36 annually during the 2010-2020 and 2020-2025 periods respectively (UN Habitat, 2014). Nairobi’s sustained growth, at least 40% of which can be attributed to rural-urban migration (Potts, 2009), has posed serious problems for the Kenyan government, which has been powerless to provide adequate housing, employment opportunities, and social services for the burgeoning urban population. This paper will consider the trend of rural to urban migration both generally and with particular regard to Kenya. The inability of the Kenyan and the Nairobian government to provide adequate support and services for this incoming population will then be considered, with especial reference to the shortage of affordable housing and the consequent development of informal