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My presentation attempts to explain recent boom-bust cycles in the US from the perspective of the Austrian School of Economics. Austrian Business Cycle theory (ABCT), though long considered to be on the fringe of economic thought, has recently experienced a surge in popularity. I walk through a series of business cycles in America including the “dot-com” bubble of the 1990s, the housing market bubble in the 2000s, and the current financial crisis, all with ABCT in mind.
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In this presentation, I examine recent shifts in the demographics of workers in Durham, including the development of a “creative class,” and what implications these shifts have for policy makers in the Bull City. Specifically, the literature in this area proposes that monetary incentives have a limited effect on the locational decisions of the creative class, and the presence of other factors that attract them, such as cultural amenities or a diverse, open and creative milieu (Florida 2002) may justify alternative forms of investments in a city.
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Durham’s recent revival of its downtown’s economic and social activity can be used as a model for other cities with similar post-industrial disinvestment. Besides being relevant for analogous American cities, Durham’s redevelopment strategies are even more pertinent for post-Soviet cities that are still undergoing industrial downsizing and could learn to prevent further urban degeneration.
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In the attached presentation, I examine this question through a case study of environmental justice and the toxic release inventory in North Carolina.
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The idea behind this paper is to create a model that will predict the optimal place for a business to locate. In order to ensure long run viability, a firm must understand the idea of optimal business location. In the designing of a strategy, it is important to not only evaluate the present market environment but to also account for possible future change. This paper will demonstrate the core ideas behind a comprehensive location model that will predict the optimal location for a business. The effectiveness of the model will be evaluated by using past data in Durham, North Carolina to predict current retail development and to see if the trend recognized would be able to correctly identify the location choices of firms. Further analysis will show what this foretells for Durham’s future retail locations.
The remainder of the paper can be found here.
A presentation on this topic can also be found here.
1. Chi S.C., Kao S.S., Kuo R.J., “A decision support system for selecting convenience store location through integration of fuzzy AHP and artificial neural network.” Elsevier Science B.V., June 15, 2001.
2. Craig Samuel, Ghosh Avijit. “Formulating Retail Location Strategy in a Changing Environment.” The Journal of Marketing, Vol. 47, No. 3, 1983. pp 56-68.
3. Glaeser, Edward L., Rosenthal, Stuart S., Strange, William C., “Urban Economics and Entrepreneurship.” National Bureau of Economic Research. Working Paper 15536.
4. Huff, David L., “A Programmed Solution for Approximating an Optimum Retail Location.” Land Economics Vol. 42 No. 3, Aug. 1966. pp 293-303.
Brazil is one of the fastest growing economies in the world. The country has established itself as the 8th largest economic power in the world with a GDP of around 1.6 trillion dollars, almost 4 times bigger than its economy in 1970. These facts bring up the question of how the country’s population and cities responded to this growth. Through 3 studies I try to answer these questions and explain a little better the impact of the growth into Brazilian’s economy, cities and population.
The main conclusions from the study are that migration within a country may well largely offset regional advantages derived from market and supplier access, in which case wage disparities would be the result of diversity in individual, industry and firm characteristics, but labor mobility has not arbitraged away all cross-regional wages differences in Brazil. They also state “market access and supplier access have a positive and significant impact on wages.
From these analyzes we can see that even the benefit of economic growth in a developing country like Brazil might have its negatives impacts on some portion of the population. To control such effects policies decisions can be taken and many different scenarios must be taken into consideration.
 International Monetary Fund http://www.imf.org/external/index.htm
2 Tolosa, HamiltonC.. “Causes of Urban Poverty in Brazil.” Pergamon Press. Available at <World Development, 1978, vol 6, No. 9/10 , pp 1087-1101>.
3 Da Mata, D; Deichmann, U; Henderson, J.V.; Lall, S.V.; Wang, H.G. “Determinants of city growth in Brazil.” ScienceDirect. Available at <www.sciencedirect.com>.
4 Fally, Thibault; Paillacar, Rodrigo; Terra, Cristina. “Economic geography and wages in Brazil: evidence from micro-data.” Journal of Development Economics. Available at <www.elseiver.com/locate/devec>.
Unlike in the United States, China’s suburbanization and urban sprawl was nonexistent until 1978, the year which marked the beginning of China’s gaige kaifang or economic reform and open-door policy. Prior to 1978, land was public property so that no market forces were involved in these transfers. The government strictly limited the rural-to-urban migration and in general, China had limited capital to invest in urban development projects (Zhang, 2000). Most Chinese cities are best characterized by the monocentric city model as most cities are still undersized, meaning they have not reached their peak agglomeration size (Pan and Zhang, 2002). Furthermore, the Chinese population is almost completely homogenous so that the “flight from blight” theory does not apply and public transportation is still the main mode of transportation although cars are becoming increasingly popular with the nouvelle rich in China.
Urban sprawl in China is mainly a product of low-density urbanization. Higher income residents actually stay in the central city, where the environment and public services are better while those who cannot afford the higher housing costs are forced to live in the suburban fringes in poorly constructed low density area. The spatial area of the cities grows faster than the population, resulting in the same low density sprawl found in the United States. Encroachment of farmland and open space is similarly a problem. The two primary forms of Chinese-style urban sprawl are overdeveloped development zones and underdeveloped semi-urbanized villages. They are the result of China’s institutional environment on the urban fringe.
- Zhang, Tingwei. (2000). Land market forces and government’s role in sprawl: The case of China, Cities, Volume 17, Issue 2, April 2000, Pages 123-135.
- Qi, Lei and Lu, Bin. (2008). Urban sprawl: A case study of Shenzhen, China. 44th ISOCARP Congress 2008.
- Deng, F. Frederic and Huang, Youqin. (2004). Uneven land reform and urban sprawl in China: The case of Beijing, Progress in Planning 3-2004, pp. 211–236.
- Cheng, J., Masser, I. (2003). Urban growth pattern modeling: a case study of Wuhan City, PR China. Landscape and Urban Planning, Volume 62, Issue 4, 25 February 2003, Pages 199-217.
- Fang, Jiang, Shenghe, Liu and Hong, Yuan. (2007). “Measuring urban sprawl in Beijing with geo-spatial indices”, Journal of Geographical Sciences, 17, 469-478.
- Yu, Xi Jun and Ng, C. N. (2007). “Spatial and temporal dynamics of urban sprawl next term along two previous term urban next term–rural transects: A case study of Guangzhou, China.” Landscape and Urban Planning, 79, 96-109.
- Nechyba, Thomas and Walsh, Randall. (2004). “Urban Sprawl.” Journal of Economic Perspectives – Volume 18, Number 4, Fall 2004, pgs 177-200).
- Pan, Z., Zhang, F., (2002). Urban productivity in China. Urban Studies 39 (12), 2267–2281.
- Yeh, Ago and Li, X. (1999). Economic development and agricultural land loss in the Pearl River Delta, China. Habitat International 23 1999, pp. 373–390.
Plantinga and Bernell (2007) found what they expected to find: lower sprawl is correlated with lower BMI while higher BMI is correlated with the choice to reside in a county with higher sprawl. In other words, BMI and choice in residential density are actually endogenously determined. However, when you take away the endogeneity, there is still a relationship between BMI and sprawl. This goes along with the notion that those with lower BMI tend to care more about their health and fitness, hence choosing an area that is easily accessible by walking and biking. The converse is true where a person with higher BMI might be averse to exercise, so this individual will choose a more sprawling area that is more suitable for traveling by car. The infrastructure available in the densely populated communities encourages individuals to be more active since it is more difficult to travel by car whereas sparse communities will require residents to drive. The infrastructure differences leads to significant changes in BMI, most likely through behavioral changes. According to their estimate, an individual who moves from Geauga County to New York City would lose approximately 18 pounds or a 2.83 unit decrease in BMI over a two year period. This is a dramatic decrease, despite how unlikely a person is to move from Ohio to New York City. These findings should play an important role in policy making, such as including dense mixed use communities that encourage more physical activity.
Nechyba, Thomas J., and Randall P. Walsh. “Urban Sprawl.” Journal of Economic Perspectives 18.4 (2004): 177-200.
Edward Glaeser and Giacomo Ponzetto, 2007, “Did the death of distance hurt Detroit and help New York?” Cambridge, MA: NBER working paper 13710.
Andrew Plantinga and Stephanie Bernell, 2007, “The association between urban sprawl and obesity: is it a two-way street?” Journal of Regional Science 47(5): 857-879.
England in the early 20th century experienced a rapidly changing national landscape. While historically its capitol, London, was the only sizeable urban area in the country, the industrial revolution brought with it the rapid rise of industrial hubs such as Birmingham, Manchester, and Liverpool. Then a combination of agricultural decline, rising tax and death duties, and the death of heirs during the First World War resulted in the breakup and sale of large land estates all over the country, effectively ending the era of country life encouraged by intellectuals from Adam Smith to Jane Austen. Due to the greatly increased supply, the middle and working classes were able to buy land for the first time, leading to rapid development of previously empty areas. Thus, English officials in the inter-war period were faced with the problem of a rapidly shrinking supply of undeveloped land combined with explosive urban and population growth. Their solution: the green belt.
Amati, Marco and Makoto Yokohari. “Temporal Changes and Local Variations in the Functions of London’s Green Belt.” Landscape and Urban Planning 75 (2006): 125–142.
Local Planning Authority Green Belt Statistics. Office of the Deputy Prime Minister, 2010. <http://www.odpm.gov.uk/>. Accessed 10 Oct. 2010.
In this 2010 study published by the Journal of Housing Economics, the effect of imputed wealth upon 5 European countries was examined. The countries studied were Germany, Belgium, Greece, Italy, and the United Kingdom. To clarify, imputed wealth is defined as the value of living in a house that someone owns would value the space if they were instead a renter. The findings in the study point to incorrect rankings of wealth and equality in these nations because imputed wealth is typically not a factor in studying these qualities.
For a detailed analysis, please continue here
Source: “Distributional Effects of Imputed Rents in Five European Countries.” Joachim R. Frick, Markus M. Grabka, Timothy M Smeeding, Panos Tsakloglou. Journal of Housing Economics Volume 19, Issue 3, September 2010, Pages 167-179.