Monocentric Model of Real Estate Economics - Research Paper Example

REAL E ECONOMICS. School REAL E ECONOMICS. Introduction Rental values of commercial properties vary significantly, based on country, regions, cities or counties. The monocentric and polycentric models have been used in explaining the structure of rental rates and economic activities in an urban settlement. In this research, cities in England shall be analyzed, and the models used to describe the structure (Capello, 2014). The city of choice shall be Manchester City, in regard to the monocentric model. In the case of polycentric, London and the neighboring cities shall be analyzed. The researcher shall then relate the two cases and deduce the facts as well as other factors that may have affected the results. Monocentric Model Introduction This layout perceives a city as a pattern of settlement, which can be described using concentric regions. In this case, the epicentre represents the Central Business District (CBD). Here, any economic activity is highly regarded since the market is accessible to all. In order to understand the monocentric models, four primary factors are considered. They include; the fact that, the CBD acts as the core area of activities, where transport lines are connected to (Lin, 2014). Secondly, the people living in the CBD live in other cities, which surround the CBD, thus have to commute on a daily basis to the CBD. The third characteristic is the intercity transportation, where the goods obtained from the CBD are ferried to other cities, through common means of transport, such as rail and roads. Since the people here are in constant business, they exchange ideas and participate in a given trend of activities. As a result, they develop a culture, which further stratifies the layout of the monocentric city. Here, the forms of settlement are stratified and distinctively isolated to a given economic class. The land rates are expected to be highest in the CBD and reduce outwards. Here, the main occupants of the CBD include businesses and offices. These groups of tenants are willing to pay high rent, since they seek to position themselves strategically, in order to access the customers’ strategic locations (Hanushek, 2014). Case study In this research, the area selected is Manchester city, with all the cities around it. They include Oldham, Rockdale, Salford, Stockport, Tameside, Trafford and Wigan. The choice was based on the economic significance of the cities. In addition, the density of settlements and the accessibility of the areas. Then, the researcher opted to concentrate on the rateable values and area of the rented space (Madariaga, 2014). The combination of the two parameters enabled the use of rent value in pounds, per square foot. Data obtained from each city was analyzed and a graph of rent per square foot, was plotted. Then a trend line was used to depict the pattern of rents in relation to distance from Manchester city. The cities locations are as shown in figure 1. Table 2 shows the analyzed data, followed by figure 3 that shows the trend obtained. Figure 1. Map of great Manchester. City Rateable values in million pounds Area in thousand m2 Rateable Value psm Rateable Value psf Manchester 265 2,002 132.37 12.30 Oldham 14 205 68.29 6.34 Rockdale 14 175 80.00 7.43 Salford 54 535 100.93 9.38 Stockport 49 468 104.70 9.73 Tameside 10 157 63.69 5.92 Trafford 63 543 116.02 10.78 Wigan 18 234 76.92 7.15 Table 1. Figure 2. From the plot, the correlation coefficient was 0.054. Thus, there is a significant correlation between the parameters used. Also, the trend line depicts the expected theory. Discussion. In accordance with eh theoretical trend, the trend line depicts a decreasing rent per square ft. (PSF), as one moves outward from the CBD. Here, the assumption is that only the strategic location is affecting the rent psf (Wu, 2014). However, there are other factors that play a profound role in the distribution of focal points in a city. These factors are characteristically the cause of the non-smooth trend of the curve. The factors emerge from the fact that the growth of a city attracts myriad interests. As a result, there might emerge more than one focal point in a given region. Thus the uniformity may vary significantly. There are theories that describe these factors, such as thee bid rent theory. However, the monocentric layout still holds. Bid rent theory It explains the fact that the demand for a given rental space is subject to the bids placed by the interested parties. Here, the factors of production play a major part, in the determination of final value. A typical plot for a bid-rent curve, for a monocentric city, is characterized by four major regions. Thhhe regggion include the CBD, where offices dominate. Then, there is the manufacturing region, where the industries have been established (Capello, 2014). Here, the main factor that affects the distribution and rental values is the accessibility and the demand by the incomers. Then there is the residential area, where the people are working in the CBD, majorly reside. The next region is characterized by the agricultural land, where population density is much lower than the preceding regions. This trend may be represented as shown in figure 4. Regardless of availability of land, other factors such as transport cost, play a vital role in the determination of rental rates. As a result, the location may not be the core determinant of the rental rates. Such a case may be explained by virtue of the production plants in the rental space. For instance, the location of manufacturing plants may be based on the source of raw materials and the transport cost, thus, the pattern suggested by the monocentric curve shall be disturbed. In such a case, there shall emerge multiple focal points in a given city (Hanushek, 2014). Thus the rental value shall rely on the bid-rent theory. The location may interrupt the trend, thus causing a spiky trend in the plots. Case study: Manchester City. The case of Manchester City is based on the rental values as projected by Collier (2014). In this case, the factors to be considered include the demand for offices, in Manchester city. In relation to the regions around the city, it emerges that the bid-rent curve is depicted by the general trend line as well as the correlation coefficient (Lin, 2014). In order to investigate the effect of location on the prices, the researcher assumes a straight direction from Manchester to York. Here, the office rates as projected by Collier (20140 are recorded. Then, the values are used to plot a curve, where the general trend is observed. The results are as shown in figure 5. City Rental values (pounds per square ft.) Manchester 31 Huddersfield 13 Halifax OOt 16 Wakefield 16 Leeds 27 YORK OOT 13.75 York 15 Table 2 shows the values of offices per square feet, in different cities from Manchester city. Figure 6 shows the cities and the direction considered, from Manchester City. Figure 7 shows the trend of office rental prices for different cities, in relation to the price in Manchester city. Analysis. From the above plot, it is evident that the trend obtained is consistent with that from the bid-rent theory. Although the curve is not smooth, the nature is similar and the factors to be considered have not been exhausted. As a result, the factors that affect the rates of offices obey the bid-rent curve. Leeds city is the odd one out, since the rent is above the trend line. The reason for the exemption is suggested to be the establishment of opulent international firms in the city. This town acts as a supportive city to the other vast neighbors, such as Manchester and London. In the case of correlation, the value of R 2 is 0.1474, implying that although the correlation is weak, it is reliable and acceptable. The office rent for other cities such as shuddersfiled appears to be the lowest. This is because of the accessibility and the nature of transport system from the other surrounding cities. Therefore, there are few bids. Thus, the rent is low. Here, the assumptions include the terrain of the land, the serene, location of affiliate industries and the nature of the transport lines. It has also been assumed that the form of transport would affect the rental values in a similar way. Limitations of the monocentric theory emerge due to the assumptions made. In this case, it is evident that the modern cities may be affected by more factors, other than the transport systems from the CBD. Another limitation is the over-generalized approach, which also assumes the existence of other activities in the region. However, the theory still provides a foundation for analysis of rental trends in a city. Polycentric City. The polycentric model is a modification of the monocentric model. Here, it has been suggested that despite the fact that a city starts from one focal point, there comes a time when the city expands, and there emerge other economic activities around the city. In this case, there emerges the need to offer the services outside the CBD. As a result, the De-urbanization of the CBD is experienced and, consequently, the emergence of other small cities around the CBD, whose growth rate greatly exceeds that of the CBD. AS a result, the model perceives a large city as a multi-nucleated region, where the cities might be known to specialize in given activities. In some cases, there are cities that are known for sports, recreation, and hospitality among other activities (Hanushek, 2014). The polycentric model allow the vastness since the growth may assume any direction from the focal point. This explains why most vast metropolitans have been structured in a polycentric manner. In this case, the cities that form the focal points may be based on the service industry, manufacturing centers, a logistics hub, technological centers, recreation, or tourist centers. The result is the variable land values, based on the specific economic activities (Wu, 2014). The bid-rent theory also applies to the polycentric city. Here, the major factors considered include the demand, in relation to the activities. For instance, the rental rates may be high in a given building, simply because other international organizations, have acquired offices in the same building. Another example may be the demand for hospitality and accommodation rooms around an airport. These factors lead to the emergence of a unique trend, whose general curve may be represented as shown in figure 7. Figure 7 shows the bid-rent plot for a polycentric city. Case study: London. Having been established in 43 AD, London has experienced various changes. It grew from an ancient city to the modern metropolitan. Due to the location and the preference by the incoming bidders, the city emerged as the Capital city of England. Then, the vast growth from its CBD led to the development of other cities around it. These cities led to the shift from monocentric to a polycentric model. The result is the establishment of many cities around a big city, which are comparatively similar in characteristics. Here, the other cities are perceived as other focal points. The nature of each focal point is determined by the economic activity and accessibility via various transport lines (Lin, 2014) (Hanushek, 2014). The choice of London for the case study is motivated by the fact that London, being a vast metropolitan city, forms the heart of the development of the other cities. The analysis of rental rates in these cities, in relation to London, should give substantial results, in regard to the establishment of each city. Here, the cities analyzed are as shown in Table 3. The rent in pounds, per square ft. (PSF), for the city was plotted against the cities location. The Inner London was assumed to be the reference point. The trend emerges as shown in figure 8. Inner London 29.89 Camden 32.34 City of London 27.96 Hackney 17.87 Hammersmith and Fulham 22.16 Haringey 9.22 Islington 21.26 Kensington and Chelsea 33.71 Lambeth 18.35 Lewisham 6.86 Newham 11.13 Southwark 22.46 Tower Hamlets 20.79 Wandsworth 14.38 Westminster 45.20 Outer London 11.62 Barking and Dagenham 10.12 Barnet 10.96 Bexley 7.38 Brent 11.40 Bromley 9.76 Croydon 10.89 Ealing 11.35 Enfield 10.12 Greenwich 8.99 Harrow 10.78 Havering 11.46 Hillingdon 12.45 Hounslow 12.78 Kingston upon Thames 13.13 Merton 14.67 Redbridge 10.12 Richmond upon Thames 17.03 Sutton 7.98 Waltham Forest 10.12 Figure 8 shows the trend for rent, from inner London to Waltham Forest. Analysis According to the results obtained in figure 8. It emerges that the location of the cities from the CBD does not, necessarily, lead to a downward, smooth curve. Instead, there are peaky points in different cities, such as the case fo Ellington, Westminister, and Richmond. Here, the cities act as focal points, from where the downward trend resumes. It is evident that the correlation coefficient depicts a weak relationship. This is because the factors considered are not the sole determinants of the pattern. Therefore, it can be deduced that despite the location of a city, the primary factors may lead to a variation in the rental rates. Here, it is assumed that other factors such as the season, government interest, and affiliated factors do not affect the rental rates. The trend line depicts a downward movement. Thus, the results are consistent and similar to those provided in the typical model. Therefore, the researcher concludes that the analysis conducted is an accurate reflection of the bid-rent theory, for a polycentric city (Capello, 2014). Central place theory. According to Christaller, a region city and the manufacturing plants offers a circlet of satellite cities. They store their goods in warehouses since they are meant for distribution and to the local markets and the retail distributors, in a hexagonal wreath of cities around the production point. The difference between the monocentric and the central place theory is the fact that the Central place theory ( CPT) does not consider a specified area as the CBD, but rather the economic activity in a given location. As a result, there might emerge numerous cities in a region, regardless of the location of the CBD. The model may be represented as shown in figure 9. Figure 9 shows the emergence of a cluster of cities around a given production hub, according to the CPT. As shown in the figure 9, there are four aspects in every the urban settlement. They include the regional cities, the satellite cities, towns that act as distribution centers (Wu, 2014). An analysis based on the central place theory shall be conducted, based on London and the neighbouring cities. Taking the floor space as the variable to be tested against the location of the cities, it will be prudent to consider the cities around London. The facts obtained from the data may be plotted as shown in figure 10. Table 10 shows the floor space in the cities. City floor space m^2 Inner London 20963 Camden 2137 City of London 5000 Hackney 546 Hammersmith and Fulham 763 Haringey 141 Islington 1455 Kensington and Chelsea 485 Lambeth 633 Lewisham 149 Newham 242 Southwark 1270 Tower Hamlets 2458 Wandsworth 310 Westminster 5373 Outer London 5693 Barking and Dagenham 101 Barnet 356 Bexley 151 Brent 277 Bromley 295 Croydon 640 Ealing 442 Enfield 202 Greenwich 155 Harrow 224 Havering 154 Hillingdon 664 Hounslow 756 Kingston upon Thames 290 Merton 266 Redbridge 156 Richmond upon Thames 300 Sutton 163 Waltham Forest 101 Table 10. Figure 10 shows the plot of the floor space against the location of the cities. Analysis. The above plot shows that the regional city is inner London. The floor space shows the level of development as well as the rateable values. Here East London emerges to be the regional city. Then, there are other satellite cities, such as Newham. Then, there is the satellite city of Westminister. The other cities are typically, small towns, which act as distribution centers, for goods produced in London. It emerges that the theory depicts the trend in the region, despite the changes that have occurred in the city since the time of establishment. If a general trend line was to be made, it would show a downward trend, which implies that the analysis is true (Hanushek, 2014). Although this theory has been proven true, there are various limitations, since the theory assumes a given perspective towards production while the world economic activities are changing rapidly. Also, it assumes that the terrain of the land is uniform. It, therefore, assumes the fact that rivers, lakes, mountains and other natural features, dictate the type of trend to be assumed by a given region. Conclusion In this research, the focus of study has been the models and theories that explain the urban settlement. Here, the area of focus has been the cities in England. The researcher has demonstrated the concentric, polycentric and the central place theories.The three theories depict a similar trend since they are based on comparatively similar parameters. However, there are variations, depending n the assumptions made in each of the theories. The researcher, therefore, concludess that the analysis was a success. References Capello, R., 2014. Regional economics. s.l.: Routledge.. Hanushek, E. A. &. Y. K. .., 2014. Land-use Controls, Fiscal Zoning, and the Local Provision of Education.. Public Finance Review, Issue 1091142114524618. Lin, E. S. P. S. K. &. Y. C. M., 2014. Housing Market and Agglomeration of Rent-Seeking Activities.. Madariaga, R. M. J. C. &. O. R., 2014. Income, distance, and amenities. An empirical analysis. Empirical Economics,. s.l.:s.n. Wu, S. M. S. Y. &. H. E. C., 2014. Industrial land price and its impact on urban growth. A Chinese case study. Land Use Policy, Volume 36 , pp. 199-209. Read More