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Nature of Price of Houses in Eight Major Australian Cities - Assignment Example

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The paper "Nature of Price of Houses in Eight Major Australian Cities" is a great example of a finance and accounting assignment. Canberra has the closest and least relationship with Brisbane and Darwin respectively as indicated by a high percentage of the coefficient of correlation. This implies that some cities experience the movement of house prices in the same direction…
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Unit name Problem Analysis and Statistics COLT3 2013 GROUP ASSIGNMENT Unit number 8732 Name of tutor   Tutorial day and time   Group Number/Name Group Member 1 (name, ID and signature): Group Member 2 (name, ID and signature): Group Member 3 (name, ID and signature): Group Member 4 (name, ID and signature): Due date Friday January 10th2014 11:55pm Table of Contents Table of Contents ii List of Figures/ Tables List of figures iii Executive Summary iv Background Knowledge v Analysis vi Question 1: Canberra House Movement Compared with Other Cities vi Question 2: Trend Demonstrated by Cumulative Index and Median House Prices x Question 4: Recommendations xv Summary and Conclusion xvii Recommendation for further research xvii Limitations of Data xvii List of Figures/ Tables List of figures Figure 1: Canberra and Melbourne Error: Reference source not found Figure 2: Canberra and Sydney Error: Reference source not found Figure 3: Canberra and Brisbane Error: Reference source not found Figure 4: Canberra and Adelaide Error: Reference source not found Figure 5: Canberra and Perth Error: Reference source not found Figure 6: Canberra and Hobart Error: Reference source not found Figure 7: Canberra and Darwin Error: Reference source not found Figure 8: Line chart of cumulative index Error: Reference source not found Figure 9: Line chart of median house prices Error: Reference source not found Table 1: Percentage increase in house prices for eight cities Error: Reference source not found Table 2: Dollar increase in median house price Error: Reference source not found Table 3: Median Multiple of eight cities Error: Reference source not found Executive Summary Canberra has the closest and least relationship with Brisbane and Darwin respectively as indicated by high percentage of coefficient of correlation. This implies that some cities experience movement of house prices in the same direction. By assessing house price indices for the eight cities, it was apparent that between Mar 2002 and Sept 2013, Darwin recorded the highest percentage increase in house prices while Sydney was the least. In terms of median house prices, Darwin as well led in median house price increase. Through an analysis of median multiple of the eight cities, it is obvious that all cities had a rating that exceeded 3.0. This offered enough evidence that no cities are affordable to buyers in Australia. Introduction The objective of this report is to offer an insight into nature of price of houses in eight major cities comprising of Canberra, Sydney Melbourne, Brisbane, Adelaide, Perth, Hobart, and Darwin. The first section covers general information regarding price of houses in Australia. This will be followed by an in-depth analysis of the relationship between movement of house price in Canberra and other major cities. Percentage change in house prices will be used to understand this movement. Thirdly, the report will examine trends for the eight cities in terms of house price indices and median house prices. To enhance the discussion, various statistical tools will be deployed. Before drawing recommendations, a newspaper article will be analysed with a view of pointing out whether the writer offered a balanced opinion. Background Knowledge According to Demographia (2013), Detroit emerged as the most affordable major market with a 1.5 Median Multiple rating. The survey further confirmed that Atlanta was the second most affordable. Looking at affordable markets in different countries presented by Demographia Australia, New Zealand, and United Kingdom did not have affordable markets. Nonetheless, United States, Canada, and Ireland had some affordable markets. Some of the factors that contributed to unaffordable markets in Australia include rising population with stagnating housing supply, and the global financial crisis. However, there has been reprieve in Australia credited to rising incomes and stagnating house prices. Despite such an improvement, Australia market still report extremely high level of unaffordability. Analysis Question 1: Canberra House Movement Compared with Other Cities The provided data of Australian House Price was deployed to compare changes in houses prices between Canberra and other Australian capital cities. a) In relation to the cities of Sydney, Melbourne, Brisbane, Adelaide, Perth, Hobart and Darwin, regression analysis was conducted as follows: i. Regression equations: ii. Line fit plot: Figure 1: Canberra and Melbourne In order to determine whether the line fit plot is a good fit, randomness of residual plot is examined. A plot of residual against actual data of Melbourne shown in appendix 1 is a random pattern thus is a line of best fit. Figure 2: Canberra and Sydney A plot of residual and actual Sydney price in appendix 1 gives a random plot. This confirms that the line is the best fit. Figure 3: Canberra and Brisbane A plot of residual against actual data of Brisbane in appendix 1 does not give a pattern. The random plot confirms that the line plot is the best fit. Figure 4: Canberra and Adelaide Adelaide residual plot in appendix 1 is random hence is the best fit. Figure 5: Canberra and Perth Perth residual plot in appendix 1 is random thus is the best fit. Figure 6: Canberra and Hobart A plot of Hobart residual in appendix 1 gives a random pattern. This is an indicator of a line of best fit. Figure 7: Canberra and Darwin The line is not the best fit because Darwin residual plot in appendix 1 does not give a random pattern. iii. Correlation coefficient: The excel output of correlation is shown in appendix 2. iv. Coefficient of determination The model explains 55.69% of variability of observed data. It indicates that the model explains only 57.37% of variability of observed data. It indicates that the model explains only 68.61% of variability of observed data. It indicates that the model explains only 16.87 % of variability of observed data. It indicates that the model explains only 50.56% of variability of observed data. It indicates that the model explains only 3.37% of variability of observed data. b) The increase in Brisbane city housing price has the closet relationship with the increase in Canberra pricing. c) The increase in Darwin city housing price has the least relationship with the increase in Canberra house price. d) Estimating housing price increases in Canberra after a 5% increase in house price of: Canberra and Brisbane: Canberra and Darwin: e) Reliability of values obtained above is determined by looking at coefficient of determination. In the case of Canberra and Brisbane, coefficient of determination is 0.6861. It indicates that 68.61% of changes in one variable have been explained by changes in the other related variable. The percentage is large enough hence the reliability is high. In the second case of Darwin, the reliability as indicated by coefficient of determination is very low at 0.0337. It shows that the model only explains 3.37% of variability in response data. Question 2: Trend Demonstrated by Cumulative Index and Median House Prices a) Cumulative index i. Line chart showing index for each city from mar 2002 to Sept 2013 Figure 8: Line chart of cumulative index ii. Total percentage increase in house prices for the cities Table 1: Percentage increase in house prices for eight cities Mar-02 Sep-13 Total increase In percentage Sydney 1.000 1.689488 0.689 69% Melbourne 1.000 2.204408 1.204 120% Brisbane 1.000 2.430741 1.431 143% Adelaide 1.000 2.236796 1.237 124% Perth 1.000 2.867962 1.868 187% Hobart 1.000 2.64809 1.648 165% Darwin 1.000 3.041853 2.042 204% Canberra 1.000 2.176945 1.177 118% b) Median house prices i. Line chart for median house prices Figure 9: Line chart of median house prices ii. Total dollar increase in the median house price for each city Table 2: Dollar increase in median house price Territory Total Increase Sydney 240.0 Melbourne 239.0 Brisbane 260.0 Adelaide 229.5 Perth 338.0 Hobart 221.7 Darwin 385.0 Canberra 285.0 Question 3: Analysis of Newspaper Article Major premises: A survey conducted by Demographia on International Housing Affordability indicates that Australia is overpriced among 337 markets in seven countries that were analyzed. By looking at the major cities, Sydney is ranked third after Hong Kong and Vancouver. Sydney was experiencing rising population while supply was too low. The ranking based on Median Multiple shows that Sydney scores the highest amongst the biggest cities in Australia. Supply in Australia has been stagnant while the price of houses keeps increasing. Major subconclusions A House price in China is more expensive as compared with Australia. The rationale is the competitive Hong Kong Market. Affordability is improving because of an improvement in incomes coupled with stagnating price of houses. Main conclusion Compared with other cities in Australia, Sydney is classified as severely unaffordable. This conclusion was reached after considering the Median Multiple that placed Sydney as the most unaffordable city. Evaluating the argument and truth claims The argument that Sydney is severely unaffordable is true when the methodology of Median Multiple is taken into consideration. The other premise that supports the conclusion is that Sydney was experiencing rising population while supply was too low. Additionally, house supply in Australia was stagnating while prices rose. This ultimately leads to unaffordability. The arguer’s claims are consistent throughout the article. However, more data is required to reach a conclusion that Sydney is severely unaffordable. The writer presented both sides of the argument hence it is a balanced piece of work. Unsupported claims Survey conducted by Demographia International Housing Affordability claims that Australia housing is overpriced out of 337 markets. The rating based on Median Multiple further indicates that Sydney is unaffordable. Refuting the argument Since the goal was to develop a decision as to whether Sydney was severely unaffordable, it was imperative for the researcher to assess the internal market in Australia instead of bringing into perspective markets in different countries. Concisely, markets in different countries vary in line with their own structural framework. Secondly, Sydney, Melbourne, Adelaide, Perth, and Brisbane have a Median Multiple rating that exceeds 5.1 hence classified as severely unaffordable. It is therefore incorrect for the writer to assert that Sydney is the only city that is severely unaffordable. Since all these cities were rated above 5.1, they are severely unaffordable. Inductive reasoning The argument starts with the fact that prices will rise with a growing population and a constant supply of houses. This situation eventually leads to severe state of unaffordability. Sydney has a growing population with an under supply of houses. The conclusion therefore is that Sydney faces severe unaffordable housing status. Results A condition of rising population and a constant housing supply leads to a high price. Sydney is highly populated hence it is expected that price of houses is high. Secondly, application of Median Multiple to deduce affordability of houses across Australia indicates that Sydney is the most expensive among the major cities. Question 4: Recommendations Darwin experiences surging price of houses and should be avoided by a potential purchaser. By assessing house price indices and median house prices for the eight cities, it was apparent that between Mar 2002 and Sept 2013, Darwin recorded the highest percentage increase in house prices while Sydney was the least. In terms of median house prices, Darwin registered the highest increase in median house price. Conversely, Hobart was the least in median house price increase. Looking at movement of house price, Canberra has the closest relationship with Brisbane but the least relationship with Darwin. Concisely a 5% increase in price of house in Brisbane culminates into a 4.0521 increase in price in Canberra. On the other hand, a 5% increase in price of house in Darwin leads to 2.322 increases in price in Canberra. This sends a message that some cities experience similar movement in price. In a research by Nicholls (2013), Sydney, Melbourne, Adelaide, Perth, and Brisbane have a Median Multiple rating that exceeds 5.1 hence these cities are classified as severely unaffordable. However, by looking at the value of rating, Brisbane has the least value of 5.8 hence a buyer can choose this option. Moreover, Annual Demographia International Housing Affordability Survey 2013 clearly shows that all major cities in Australian market are overpriced and unaffordable. The only option that is available to a homeowner is to buy from other places apart from major markets. In calculating Median Multiple, median house price is divided by gross before tax annual median household income of the eight cities. This formula was employed in finding Median Multiple of eight cities consequently giving the following: Table 3: Median Multiple of eight cities Territory City Gross median income per week Gross median income per annum (52 weeks) Median House Price median multiple Tasmania Hobart 1,312 68,224 291,500 4.27 South Australia Adelaide 1,308 68,016 335,000 4.93 Victoria Melbourne 1,568 81,536 370,000 4.54 Western Australia Perth 1,695 88,140 455,000 5.16 Northern Territory Darwin 1,969 102,388 400,000 3.91 Queensland Brisbane 1,534 79,768 390,000 4.89 New South Wales Sydney 1,726 89,752 500,000 5.57 Australia Canberra 1,612 83,824 447,000 5.33 According to the table above, Sydney has the highest median multiple of 5.57. This falls under the classification of severely unaffordable. On the contrary, Darwin has the least rating at 3.91, which is moderately unaffordable. The other remaining cities satisfy the conditions of seriously unaffordable and severely unaffordable. Taking into account these rating, all cities are unaffordable and a house buyer should consider other towns. Summary and Conclusion Canberra has the closest and least relationship with Brisbane and Darwin respectively as indicated by coefficient of correlation. This implies that some cities experience house prices that move in the same direction. By assessing house price indices and median house prices for the eight cities, it was apparent that between Mar 2002 and Sept 2013, Darwin recorded the highest percentage increase in house prices while Sydney was the least. In terms of median house prices, Darwin recorded high median house price increase. Through an analysis of Median Multiple of the eight cities, it was obvious that all cities had a rating that exceeded 3.0. This offered enough evidence that no cities are affordable to buyers. Recommendation for further research There is need to investigate impact of globalization on price of house in the eight cities. The advent of information communication technology has opened way for cross boarder movement of investment funds. It is therefore necessary to carry out a research to understand whether opening up the boarders have contributed to the present high price of houses in Australia. Limitations of Data The data used in this report are historical. This means that several events must have taken place thus the data might not give an accurate outlook of housing situation in the cities under consideration. Secondly, the data fails to take note of the small metropolitans. It therefore appears to be overgeneralization. References Demographia. (2013). Ninth Annual Demographia International Housing Affordability Survey: 2013 Ratings for Metropolitan Markets. Retrieved from http://www.demographia.com/dhi.pdf. Nicholls, S. (2013, Jan 29). Sydney house prices 'severely unaffordable. News.domain. Retrieved from http://news.domain.com.au/domain/real-estate-news/sydney-house-prices-severely- unaffordable-20130121-2d39f.html. Appendices Appendix 1: Residual plots Appendix 2: Correlation coefficient Read More
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