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Real Estate Prices In Inner And Outer London

Abstract

Understanding and predicting upcoming real estate house prices is a vital activity that forms the center for all strategic, tactical and operational planning decisions in management of real estate businesses. The political, environmental, sociological, technological, legal and economic factors in the market affect the consequent house prices; but the affect is greater in Inner London as compared to Outer London. In times of economic boom and political stability; Inner London is an attractive residence for professional and skilled individuals and families. Living in Inner London offers a close proximity to the large workplace; and a dwelling for like-minded professionals that work in similar markets, i.e. financial services. This study examines how best to model and forecast house prices through times series analysis to identify the accuracy of the forecasts and the smoothness of prices.

Chapter 1: Introduction

The macroeconomic or financial economics perspective emphasize housing as investment in an augmenting life-cycle model of consumerism, with minimal consideration to spatial issues; implying that houses and related facilities are crude human necessities that are utilized cost-effectively.

The urban economics perspective, places spatial issues at the centre, denoting human desire affect selection of houses and associated amenities. The current explanations given by mortgage banks for large house price increases is that the class of consumers who are not constrained in their access to credit are speculating and trading in this profitable market.

Illustration of housing as an asset, consumers only pay a high price if it implies that at the time of sale in the future a consumer will be prepared to pay a high price; this is the reason that price of housing should reflect the future. A fall in nominal interest rates leads to consumers capitalizing in the house market thereby causing large debts and high house prices.

1.1 Hidden Layers in House Sales Market

The presence of hidden layers in the housing framework of prices and consumption shields analysts against the casual explanation that house prices adjust in alignment to fundamental reasoning; the actual archetype is then based on bubble reasoning. The economic, socio-political situation of the free market guides investors and sequentially the real prices in the real estate market. An analysis of market efficiency leads to investors or consumer to speculate in housing; the most important determinants of long-run national and sub-national house prices are in consequence to; real interest rates, housing stock, demographic changes, credit availability, and tax structure.

1.2 Benefit of forecasting future house sales

Forecasting future house sales is one of the most important activities that form the basis for all strategic and planning decisions in effective operations of real estate businesses and the real estate market economies. The best model to forecast house sales is through a time series that contain both trend and seasonal variations. Sequentially, accurate forecasts of consumer or investor house sales can help improve real estate market operation especially for larger agencies that have a significant market share.

For profitable house sale operations, accurate demand forecasting is crucial in organizing and planning for consumers or investors; construction/renovation aspects, marketing and administration, as well as after-sales services. A poor forecast would result in either too much or too little customers, directly affecting the profitability of the brand and the competitive position of the organization.

1.3 Demographic Factors of UK House Market

Trends in demographic factors maintain demand, thus aiding in the explanation into the reasons housing has a good historical rate of return. The recent shift upwards of price trend into a new permanently higher level implies a shifting upwards in the trend of the original demographic factors. Whilst the trends keep adapting to economic scenarios, the position of the trends has not shifted radically. Realistically the demographic factors complimentary to house prices in the 1980s largely relaxed in the early 1990s. Recent studies by the IMF have suggested that the house-holds variable affects the long-term prices, and is not a significant issue in the short-term determination of prices.

1.5 The Nominal Interest Rate

UK mortgage banks are placing significant spotlight on nominal interest rate, however, no valid economy statistics report has determined that the nominal interest rate plays any role in the long-run determination of house prices. Essentially it is the real costs of housing that matter, though in the short-run real house prices do respond to changes in nominal interest rate.

Consumers purchase pricey houses by engaging in debts; the same initial monthly repayment is due; thus when nominal interest rates are 1% (all real rates remain the same) house prices augment, the percentage of lifetime income spent on housing increases and amount spent on other goods and services decreases, implying that just one or two per cent more interest can make a major variance to all consumption potentials.

1.6 Real Interest Rates

As market study and theory implies that at a low real interest rate, more customers borrow more money and house prices rise. Risk-averse consumers (credit unconstrained) base decision of amount of money to borrow on: 1) Real 2) After Tax 3) Expected and 4) Risk-Adjusted Rate of Interest.

1.7 Credit Constraints of House Buyers

The presence of credit constraints in the analysis designates inconsistencies that suggest (even without examining for market efficiency) that the clarification is attained from supplementary factors or hidden layers. Simplistic explanations of house prices do emphasize that it is the intensification of ‘lifetime utility’ that drive analysis and from this correct house prices are predictable.

1.8 GDP Growth and Expectations

At times that consumers are more optimistic about their economic prospects, increase in consumption of other goods and services in alignment with an increase in house prices occurs. House prices and the growth of debt-driven consumption are a result of unrealistic inference to recent unemployment and income patterns. The origins of growth matter; recent UK economic performance is based on consumption that is relatively based on high house prices; each time the housing market collapses, unemployment rises. Market study reveals that a large percentage of decrease in unemployment is from extension in government employment and from the housing market. Also, Long-term increases in the productivity of UK markets pulses into house prices.

Chapter 2: Literature Review

Precise forecasts of consumer real estate prices aide in improving real estate business operation, especially for agencies that have a significant market share. For cost-effective real estate operations, perfect price forecasting is decisive in organizing and planning purchasing, production, transportation, and labor force, as well as after-sales services. A pitiable forecast results in either too much or too little preparation, directly upsetting the prosperity of the agency chain and the competitive situation of the business.

2.4 Real Estate Investments

Real estate investments are categorized into: 1) private equity, 2) public equity, 3) private debt and 4) public debt. A choice of which one to invest in depends on the type of exposure required for a portfolio; to invest in income-producing properties or non-income-producing properties. Any leased property is income producing, and vacant properties are non-income producing. It is possible to earn a capital return on a non-income producing property, just as on an investment in a home. The foremost types of investment properties are offices, retails, industrials and multi-family residential properties. Real estate can produce income (like a bond) and appreciate (like equity).

Real estate is tangible, thus requires constant management. There is an increased ability to influence the performance of a single investment as compared to other asset classes. Some of the benefits of adding real estate to a portfolio include: diversification, yield enhancement, risk reduction and inflation-hedging capabilities. However, real estate also has high transaction costs, can be difficult to acquire and it is challenging to measure its relative performance.

Buying real estate requires considerable positive intuition to ensure that the investment is beneficial. To determine the value of a property (other than actually selling it) is to have it appraised by an accredited appraiser.

2.5 Private or Public Markets

In the planning of real estate investments, a first tasks is to decide what kind of exposure to the real estate market is appropriate for the situation. Different exposures produce varying levels of risk and return. The choice also influences the means by which real estate is acquired. The first type of market is the private market.

In the private market; involves purchasing a direct interest in one or more real estate properties; own and operate the piece of real estate through a property manager or by-self, and receive the rent payments and value changes from that investment. Participation in this market is also possible by purchasing properties with any number of partners, known as a pool or syndicate.

Alternatively, participating in the public market is purchasing a share or unit in a publicly traded real estate company. Purchase of a real estate security institutes investing in a company that owns real estate and manages it on behalf of the shareholders/unit-holders of the company. As a result, overall exposure to the real estate market is more indirect. A real estate security usually pays a dividend or distribution in order to send the rent payments that it receives from tenants to its shareholders/unit-holders. Any price appreciation or depreciation in the assets owned by the company is reflected in its share or unit price.

2.6 Equity and Debt Investments

In addition to choosing the market, another decision is whether to invest in debt or equity. An investment in debt; lending funds to an owner or purchaser of real estate; receive periodic interest payments from the owner and a security charge against the property in the form of a mortgage. At the end of the mortgage term, the bank (conventionally) obtains back the balance of the mortgage principal. This type of real estate investing is quite like that of bonds.

An equity investment represents a residual interest in the property. An equity investor is effectively the owner of the property; situated to gain reasonably if the property value increases or if rent for the building increases. However, in the event of tribulation (i.e. all tenants vacate and it is not possible to make the mortgage payment) then the mortgagee (has a priority interest in the property), may foreclose and the investor must forfeit the equity position to satisfy security. In that sense, the risks of an equity position in real estate is much like that of owning stock. The choice of whether to invest in equity or debt depends upon the investor’s risk tolerance and return expectations.

2.7 Types of Real Estate

Real estate investments have one or more tangible real estate properties underlying each investment; in an investment it is important to consider the characteristics of the principal real estate because the performance of those properties will impact the performance of the investment. One of the most important criteria (aside from location) is the type of property.

The primary properties are; residential homes, shopping malls, warehouses, office towers or a combination of any of these. Each type of real estate has a different set of drivers influencing its performance.

There are four types of income-producing real estate: 1) offices, 2) retail, 3) industrial and 4) leased residential. There are many other less common types as well; hotels, mini-storage, parking lots and seniors care housing.

Non-income-producing investments, such as houses, vacation properties or vacant commercial buildings, are as beneficial as income-producing investments. If investing in equity in a non-income producing property, there is no income from rent, so all of the return is through capital appreciation. If investing in debt secured by non-income-producing real estate; the borrower's personal income must be sufficient to cover the mortgage payments, because there is no tenant income to secure the payments.

Office Property

Offices are the desired investment for frequent real estate owners, on average, the largest and highest profile property type due to typical location in town centers and expansive business office parks. The demand for office space is attached to companies' requirement for office workers, and the standard space per office worker. The typical office worker is involved in things like finance, accounting, insurance, real estate, services, management and administration. As these "white-collar" jobs grow, there is greater demand for office spaces.

Returns from office properties can be highly variable because the market tends to be sensitive to economic performance. One obstacle is that office buildings have high operating costs, so if a tenant is lost, it can have a substantial impact on the returns for the property. Nonetheless, in times of prosperity, offices tend to perform exceptionally sound, because demand for space causes rental rates to increase and an extended time period is required to build an office tower to relieve the pressure on the market and rents.

Retail Property

There is a ample variety of retail properties, ranging from large enclosed shopping malls to single tenant buildings in pedestrian zones. At the present time, the Supremacy Center format is in favor, with retailers occupying larger premises than in the enclosed mall format, and having greater visibility and access from adjacent roadways.

Recurrent retail properties have an anchor, which is a large, well-known retailer that acts as a draw to the center. If a retail property has a food store as an anchor, it is said to be food-anchored or grocery-anchored; such anchors would typically enhance the fundamentals of a property and make it more desirable for investment.

Often, a retail center has one or more ancillary multi-bay buildings containing smaller tenants. One of these small units is termed a commercial retail unit (CRU). The demand for retail space has many drivers. Among them are: location, visibility, population density, population growth and relative income levels.

From an economic perspective, retails tend to perform best in growing economies and when retail sales growth is high. Returns from Retails tend to be more stable than Offices, in part because retail leases are generally longer and retailers are less inclined to relocate as compared to office tenants.

Industrial Property

Industrials are often considered the simpler of the average real estate investor; require smaller average investments, are less management intensive and have lower operating costs. There are varying types of industrials depending on the use of the building (i.e. warehousing, manufacturing, research and development, or distribution).

Important factors to consider in an industrial property are functionality (i.e. ceiling height), location relative to major transport routes (including rail or sea), building configuration, loading and the degree of specialization in the space (such as whether it has cranes or freezers). For some uses, the presence of outdoor or covered yard space is important.

Multi-Family Residential Property

Multi-Family residential property delivers stable returns, regardless of the economic cycle, people always need a place to live. The result is that in normal markets, residential occupancy tends to stay reasonably high. Another factor contributing to the stability of residential property is that the loss of a single tenant has a minimal impact on the substructure.

Commercial property types portray tenant leases either net or partially net, meaning that most operating expenses can be passed along to tenants. However, residential properties normally do not have this feature, meaning that the risk of increases in building operating costs is borne by the property owner for the duration of the lease.

A positive aspect of residential properties is that; government-insured financing may be available. At the cost of a small premium, insured financing lowers the interest rate on mortgages, enhancing potential returns from the investment.

2.8 Characteristics of Real Estate Investments

One of the beneficial features of real estate is that it produces relatively consistent total returns that are a hybrid of income and capital growth. In that sense, real estate has a coupon-paying bond-like component in that it pays a regular, steady income stream, and it has a stock-like component in that its value has a propensity to fluctuate. And, like all securities that the investor has a long position in, prefers the value to go increase.

The income return from real estate is directly linked to the rent payments received from tenants, minus the costs of operating the property and outgoing mortgage/financing payments. If too many tenants are lost, the owner does not have sufficient rents paid by the other tenants to cover the building operating costs. The ability to keep the building full depends on the strength of the leasing market; the supply and demand for space similar to the owner’s space to lease.

In weaker markets with oversupply of vacancies or poor demand, the investor has to charge less rent to maintain the building full than in a strong leasing market. Evidently, if the rents are lower, income returns are lower.

Capital appreciation of a property is determined by having the property appraised. An appraiser uses actual sale transactions that have occurred and other pieces of market data to estimate what the property would be worth if it were to be sold. If the appraiser declares that the property would sell for more than purchased for, then the owner has achieved a positive capital return.

Because the appraiser uses past transactions in judging values, capital returns are directly linked to the performance of the investment sales market. The investment sales market is affected largely by the supply and demand of investment product.

The majority of the volatility in real estate returns comes from the capital appreciation component of returns. Income returns tend to be fairly stable, and capital returns fluctuate more. The volatility of total returns distinguishes someplace in between.

2.9 Other Characteristics of Real Estate Investments

Other characteristics that make real estate unique as compared to other investment alternatives are as follows:

No fixed maturity

Unlike a bond which has a fixed maturity date, an equity real estate investment does not normally mature. In Europe, it is not uncommon for investors to hold property for over 100 years. This attribute of real estate allows an owner to buy a property, execute a business plan, then dispose of the property whenever appropriate. An exception to this characteristic is an investment in fixed-term debt; by definition a mortgage would have a fixed maturity.

Tangible

Real estate is real; it is possible to visit the investment, speak with tenants, and obtain speculation. As a result, the investor holds a certain degree of physical control over the investment, dissimilar to a stock or bond.

Requires Management

Real estate is tangible and requires to be managed; tenant complaints are addressed, landscaping is handled, and renovation is required after passing of several or more years.

Inefficient Markets

An inefficient market indentifies that information asymmetry exists among participants in the market, allowing greater profits to be made by those with special information, expertise or resources. In contrast, public stock markets are much more efficient; information is efficiently circulated amongst market participants, and those with material non-public information are not permitted to trade upon the information. In the real estate markets, information is vital, and facilitates an investor to identify profit opportunities that otherwise would not be visible.

High Transaction Costs

Private market real estate has high purchase costs and sale costs. On purchases, there are real estate agent-related commissions, lawyers' fees, engineers' fees and many other costs that can raise the effective purchase price sound beyond the price the seller will essentially collect. On sales, a substantial brokerage fee is usually required for the property to be properly exposed to the market. Because of the high costs of “trading? real estate, longer holding periods are common and speculative trading is rarer than for stocks.

Lower Liquidity

With the exception of real estate securities, no public exchange exists for the trading of real estate. This makes real estate more difficult to sell because deals must be privately brokered. There can be a substantial lag between the time the owner decides to sell a property and when it actually is sold.

Underlying Tenant Quality

When assessing an income-producing property, an important consideration is the quality of the underlying tenancy. This is important because when investing in the property, there are two acquisitions: the physical real estate and the income flow from the tenants. If the tenants are likely to default on the monthly obligation, the risk of the investment is greater.

Variability among Regions

Location is one of the important aspects of real estate investments; a piece of real estate can perform very differently amongst, regions, cities, towns. These regional differences need to be considered when making an investment, because the investors selection of which market to invest in has as large an impact on resultant returns.

Chapter 3: Methodology

Chapter 4: Results

4.1 Time Series Analysis on Outer London House Prices

Year

Price in GBP

Moving Average

Centered Average

Seasonal Variation

Seasonal Variation Multiplicative Model

Q1 1996

£59,562.61

Q2 1996

£57,936.38

60,272.93

Q3 1996

£61,673.3

60,781.26

60,527.1

+1146.21

101.8937

Q4 1996

£61,919.44

62,772.85

61,777.05

+142.386

100.2305

Q1 1997

£61,595.91

64,795.35

63,784.1

-2188.191

96.56938

Q2 1997

£65,902.75

66,635.37

65,715.36

+187.39

100.2852

Q3 1997

£69,763.31

69,295.36

67,965.36

+1797.95

102.6454

Q4 1997

£69,279.5

72,263.94

70,779.65

-1500.149

97.88054

Q1 1998

£72,235.88

74,293.44

73,278.69

-1042.808

98.57693

Q2 1998

£77,777.06

76,726.72

75,510.08

+2266.98

103.0022

Q3 1998

£77,881.31

78,337.86

77,532.29

+349.02

100.4502

Q4 1998

£79,012.63

80,102.67

79,220.27

-207.6362

99.7379

Q1 1999

£78,680.44

83,818.49

81,960.58

-3280.139

95.99791

Q2 1999

£84,836.31

87,573.55

85,696.02

-859.7063

98.9968

Q3 1999

£92,744.56

92,198.75

89,886.15

+2858.41

103.18

Q4 1999

£94,032.88

97,293.15

94,745.95

-713.0687

99.24739

Q1 2000

£97,181.25

102,118.4

99,705.75

-2524.503

97.46805

Q2 2000

£105,213.9

105,675.6

103,897

+1316.93

101.2675

Q3 2000

£112,045.4

109,839.4

107,757.5

+4287.92

103.9792

Q4 2000

£108,261.8

113,161.1

111,500.3

-3238.45

97.09557

Q1 2001

£113,836.4

117,186.4

115,173.8

-1337.363

98.83883

Q2 2001

£118,500.9

123,428.2

120,307.3

-1806.388

98.49852

Q3 2001

£128,146.5

129,337.5

126,382.9

+1763.65

101.3955

Q4 2001

£133,228.9

136,672.2

133,004.8

+224.063

100.1685

Q1 2002

£137,473.8

145,696.3

141,184.2

-3710.4

97.37194

Q2 2002

£147,839.4

154,509.1

150,102.7

-2263.275

98.49218

Q3 2002

£164,242.9

163,239.4

158,874.3

+5368.64

103.3792

Q4 2002

£168,480.3

170,033.3

166,636.4

+1843.92

101.1066

Q1 2003

£172,395.1

174,140.6

172,087

+308.138

100.1791

Q2 2003

£175,015

178,801.1

176,470.9

-1455.85

99.17502

Q3 2003

£180,672

182,642.6

180,721.8

-49.825

99.97243

Q4 2003

£187,122.3

187,052.4

184,847.5

+2274.84

101.2307

Q1 2004

£187,760.9

192,088.1

189,570.3

-1809.35

99.04555

Q2 2004

£192,654.3

195,588.1

193,838.1

-1183.788

99.38929

Q3 2004

£200,815

198,330.8

196,959.4

+3855.56

101.9575

Q4 2004

£201,122

201,343.5

199,837.2

+1284.84

100.6429

Q1 2005

£198,732

203,390.8

202,367.1

-3635.138

98.20369

Q2 2005

£204,705

204,844.2

204,117.5

+587.5

100.2878

Q3 2005

£209,004.1

207,249.2

206,046.7

+2957.38

101.4353

Q4 2005

£206,935.8

209,719.3

208,484.3

-1548.45

99.25728

Q1 2006

£208,352

213,557.2

211,638.3

-3286.25

98.44723

Q2 2006

£214,585.2

218,996.8

216,277

-1691.825

99.21775

Q3 2006

£224,355.9

225,475.7

222,236.2

+2119.66

100.9538

Q4 2006

£228,694.2

232,444.5

228,960.1

-265.8625

99.88388

Q1 2007

£234,267.3

240,032.5

236,238.5

-1971.2

99.16559

Q2 2007

£242,460.5

246,276.9

243,154.7

-694.2125

99.7145

Q3 2007

£254,708.1

250,051.8

248,164.4

+6543.75

102.6369

Q4 2007

£253,671.7

251,542

250,796.9

+2874.83

101.1463

Q1 2008

£249,366.9

246,086.1

248,814

+552.887

100.2222

Q2 2008

£248,421.1

236,546.4

241,316.2

-7104.88

102.9442

Q3 2008

£232,884.6

226,903.8

231,725.1

+1159.5

100.5004

Q4 2008

£215,512.9

218,310.7

222,607.2

-7094.337

96.81307

Q1 2009

£210,796.7

216,358.6

217,334.6

-6537.9

96.99178

Q2 2009

£214,048.4

N/A

N/A

N/A

N/A

Q3 2009

£225,076.2

N/A

N/A

N/A

N/A

Q4 2009

N/A

N/A

N/A

N/A

N/A

Q1 2010

N/A

N/A

N/A

N/A

N/A

Average

2,177.91

99.9445%

4.2 Time Series Analysis on Inner London House Prices

Year

Price in GBP

Moving Average

Centered Average

Seasonal Variation

Seasonal Variation Multiplicative Model

Q1 1996

£148,896.8

Q2 1996

£142,925.9

147,341.9

Q3 1996

£149,826.8

147,512.5

147,427.2

2,399.612

101.6277

Q4 1996

£147,718.2

154,229.6

150,871

-3,152.8

97.91027

Q1 1997

£149,578.9

163,204.5

158,717

-9,138.13

94.2425

Q2 1997

£169,794.3

171,798.4

167,501.5

2,292.85

101.3689

Q3 1997

£185,726.6

182,167.5

176,982.9

8,743.675

104.9404

Q4 1997

£182,093.8

189,947.1

186,057.3

-3,963.48

97.86976

Q1 1998

£191,055.1

194,649.2

192,298.1

-1,243.02

99.35359

Q2 1998

£200,912.9

195,698.1

195,173.6

5,739.3

102.9406

Q3 1998

£204,534.8

199,057.7

197,377.9

7,156.925

103.626

Q4 1998

£186,289.4

203,921.1

201,489.4

-15,200

92.45617

Q1 1999

£204,493.7

214,261.3

209,091.2

-4,597.52

97.80119

Q2 1999

£220,366.6

231,982.3

223,121.8

-2,755.21

98.76515

Q3 1999

£245,895.6

248,538.2

240,260.3

5,635.337

102.3455

Q4 1999

£257,173.3

263,644.1

256,091.1

1,082.162

100.4226

Q1 2000

£270,717.4

273,068.9

268,356.5

2,360.925

100.8798

Q2 2000

£280,789.9

282,179.8

277,624.4

3,165.55

101.1402

Q3 2000

£283,595

288,329.1

285,254.5

-1,659.46

99.41825

Q4 2000

£293,616.9

292,479.6

290,404.3

3,212.563

101.1062

Q1 2001

£295,314.7

301,948

297,213.8

-1,899.08

99.36104

Q2 2001

£297,391.6

302,959.7

302,453.9

-5,062.26

98.32627

Q3 2001

£321,468.8

307,248.3

305,104

16,364.8

105.3637

Q4 2001

£297,663.8

321,073.8

314,161

-16,497.2

94.7488

Q1 2002

£312,468.9

328,782.1

324,927.9

-12,459

96.1656

Q2 2002

£352,693.6

341,841

335,311.6

17,382.04

105.1838

Q3 2002

£352,302.1

346,899.1

344,370.1

7,932.025

102.3033

Q4 2002

£349,899.5

346,678.6

346,788.9

3,110.65

100.897

Q1 2003

£332,701.3

347,625.3

347,152

-14,450.7

95.83737

Q2 2003

£351,811.4

350,678.9

349,152.1

2,659.3

100.7616

Q3 2003

£356,089.1

358,687.6

354,683.2

1,405.862

100.3964

Q4 2003

£362,113.7

369,487.9

364,087.8

-1,974.05

99.45781

Q1 2004

£364,736.2

381,333.6

375,410.8

-10,674.6

97.15656

Q2 2004

£395,012.6

381,712.7

381,523.2

13,489.44

103.5357

Q3 2004

£403,472

390,406.4

386,059.6

17,412.45

104.5103

Q4 2004

£363,630

395,557

392,981.7

-29,351.7

92.53103

Q1 2005

£399,511

403,120

399,338.5

172.525

100.0432

Q2 2005

£415,615

413,411.6

408,265.8

7,349.25

101.8001

Q3 2005

£433,723.8

421,405.6

417,408.6

16,315.25

103.9087

Q4 2005

£404,796.4

431,011.5

426,208.5

-21,412.1

94.97614

Q1 2006

£431,487

441,305.4

436,158.4

-4,671.41

98.92896

Q2 2006

£454,038.7

450,973.4

446,139.4

7,899.35

101.7706

Q3 2006

£474,899.3

466,815.3

458,894.3

16,004.98

103.4877

Q4 2006

£443,468.4

485,594.8

476,205.1

-32,736.7

93.12551

Q1 2007

£494,854.8

510,784.7

498,189.8

-3,334.95

99.33059

Q2 2007

£529,156.8

533,983

522,383.8

6,772.975

101.2966

Q3 2007

£575,658.7

556,445.9

545,214.4

30,444.27

105.5839

Q4 2007

£536,261.6

566,853.2

561,649.5

-25,387.9

95.47975

Q1 2008

£584,706.4

568,963.1

567,908.2

16,798.24

102.9579

Q2 2008

£570,786.1

558,468.3

563,715.7

7,070.388

101.2542

Q3 2008

£584,098.4

553,527

555,997.6

28,100.76

105.0541

Q4 2008

£494,282.3

531,454.4

542,490.7

-48,208.4

91.11351

Q1 2009

£564,941.1

528,003.7

529,729.1

35,212.05

106.6472

Q2 2009

£482,495.8

N/A

N/A,

N/A

N/A

Q3 2009

£570,295.6

N/A

N/A

N/A

N/A

Q4 2009

N/A

N/A

N/A

N/A

N/A

Q1 2010

N/A

N/A

N/A

N/A

N/A

Average

11,049.32

100.0296%

4.3 Time Series Analysis on Number of House Sales Transactions in the UK

Year

Number of Transactions

Moving Average

Centered Average

Seasonal Variation

Seasonal Variation Multiplicative Model

Q1 1990

344

Q2 1990

360

349.5

Q3 1990

349

342

345.75

3.25

100.94

Q4 1990

345

333

337.5

7.5

102.2222

Q1 1991

314

334

333.5

-19.5

94.15292

Q2 1991

324

326.5

330.25

-6.25

98.10749

Q3 1991

353

307

316.75

36.25

111.4444

Q4 1991

315

292.25

299.625

15.375

105.1314

Q1 1992

236

295.75

294

-58

80.27211

Q2 1992

265

284

289.875

-24.875

91.41871

Q3 1992

367

284.75

284.375

82.625

129.0549

Q4 1992

268

288.25

286.5

-18.5

93.54276

Q1 1993

239

283.25

285.75

-46.75

83.63955

Q2 1993

279

299

291.125

-12.125

95.83512

Q3 1993

347

314

306.5

40.5

113.2137

Q4 1993

331

322.25

318.125

12.875

104.0472

Q1 1994

299

321.75

322

-23

92.85714

Q2 1994

312

318.75

320.25

-8.25

97.42389

Q3 1994

345

315

316.875

28.125

108.8757

Q4 1994

319

307

311

8

102.5723

Q1 1995

284

295.25

301.125

-17.125

94.31299

Q2 1995

280

283.5

289.375

-9.375

96.76026

Q3 1995

298

277.75

280.625

17.375

106.1915

Q4 1995

272

278.75

278.25

-6.25

97.75382

Q1 1996

261

288.75

283.75

-22.75

91.98238

Q2 1996

284

310.75

299.75

-15.75

94.74562

Q3 1996

338

326.5

318.625

19.375

106.0808

Q4 1996

360

343.25

334.875

25.125

107.5028

Q1 1997

324

355.5

349.375

-25.375

92.73703

Q2 1997

351

359.75

357.625

-6.625

98.1475

Q3 1997

387

358

358.875

28.125

107.837

Q4 1997

377

349.5

353.75

23.25

106.5724

Q1 1998

317

347

348.25

-31.25

91.02656

Q2 1998

317

336.5

341.75

-24.75

92.75786

Q3 1998

377

336.25

336.375

40.625

112.0773

Q4 1998

335

342.5

339.375

-4.375

98.71087

Q1 1999

316

351.75

347.125

-31.125

91.03349

Q2 1999

342

367.25

359.5

-17.5

95.13213

Q3 1999

414

380

373.625

40.375

110.8063

Q4 1999

397

381.5

380.75

16.25

104.2679

Q1 2000

367

372.75

377.125

-10.125

97.31521

Q2 2000

348

358.25

365.5

-17.5

95.21204

Q3 2000

379

348.25

353.25

25.75

107.2895

Q4 2000

339

348

348.125

-9.125

97.37882

Q1 2001

327

352.25

350.125

-23.125

93.39522

Q2 2001

347

364.25

358.25

-11.25

96.85973

Q3 2001

396

368

366.125

29.875

108.1598

Q4 2001

387

380

374

13

103.4759

Q1 2002

342

395.25

387.625

-45.625

88.2296

Q2 2002

395

396.5

395.875

-0.875

99.77897

Q3 2002

457

396

396.25

60.75

115.3312

Q4 2002

392

373.75

384.875

7.125

101.8513

Q1 2003

340

349

361.375

-21.375

94.08509

Q2 2003

306

336

342.5

-36.5

89.34307

Q3 2003

358

362.75

349.375

8.625

102.4687

Q4 2003

340

399.25

381

-41

89.23885

Q1 2004

447

433.25

416.25

30.75

107.3874

Q2 2004

452

447.75

440.5

11.5

99.99119

Q3 2004

494

411

429.375

64.625

115.0509

Q4 2004

398

385.5

398.25

-0.25

99.93723

Q1 2005

300

373.25

379.375

-79.375

79.07743

Q2 2005

350

380.75

377

-27

99.85423

Q3 2005

445

403.5

392.125

52.875

113.4842

Q4 2005

428

422.5

413

15

103.632

Q1 2006

391

432.75

427.625

-36.625

91.43525

Q2 2006

426

444.25

438.5

-12.5

99.96777

Q3 2006

486

453

448.625

37.375

108.331

Q4 2006

474

458.25

455.625

18.375

104.0329

Q1 2007

426

459.25

458.75

-32.75

92.86104

Q2 2007

447

448.5

453.875

-6.875

100.0919

Q3 2007

490

N/A

N/A

N/A

N/A

Q4 2007

431

N/A

N/A

N/A

N/A

Average

24.44118

99.9445%

4.3 Regression Number of Transactions in the UK and Inner London House Prices

Year Ended

Number of Transactions UK (X)

Median Inner London House Prices (Y)

YX

Q1 1996

261

£148,896.8

38862064.8

68121

22170257050

Q2 1996

284

£142,925.9

40590955.6

80656

20427812891

Q3 1996

338

£149,826.8

50641458.4

114244

22448069998

Q4 1996

360

£147,718.2

53178552

129600

21820666611

Q1 1997

324

£149,578.9

48463563.6

104976

22373847325

Q2 1997

351

£169,794.3

59597799.3

123201

28830104312

Q3 1997

387

£185,726.6

71876194.2

149769

34494369948

Q4 1997

377

£182,093.8

68649362.6

142129

33158151998

Q1 1998

317

£191,055.1

60564466.7

100489

36502051236

Q2 1998

317

£200,912.9

63689389.3

100489

40365993386

Q3 1998

377

£204,534.8

77109619.6

142129

41834484411

Q4 1998

335

£186,289.4

62406949

112225

34703740552

Q1 1999

316

£204,493.7

64620009.2

99856

41817673340

Q2 1999

342

£220,366.6

75365377.2

116964

48561438396

Q3 1999

414

£245,895.6

101800778.4

171396

60464646099

Q4 1999

397

£257,173.3

102097800.1

157609

66138106233

Q1 2000

367

£270,717.4

99353285.8

134689

73287910663

Q2 2000

348

£280,789.9

97714885.2

121104

78842967942

Q3 2000

379

£283,595

107482505

143641

80426124025

Q4 2000

339

£293,616.9

99536129.1

114921

86210883966

Q1 2001

327

£295,314.7

96567906.9

106929

87210772036

Q2 2001

347

£297,391.6

103194885.2

120409

88441763751

Q3 2001

396

£321,468.8

127301644.8

156816

1.03342E+11

Q4 2001

387

£297,663.8

115195890.6

149769

88603737830

Q1 2002

342

£312,468.9

106864363.8

116964

97636813467

Q2 2002

395

£352,693.6

139313972

156025

1.24393E+11

Q3 2002

457

£352,302.1

161002059.7

208849

1.24117E+11

Q4 2002

392

£349,899.5

137160604

153664

1.2243E+11

Q1 2003

340

£332,701.3

113118442

115600

1.1069E+11

Q2 2003

306

£351,811.4

107654288.4

93636

1.23771E+11

Q3 2003

358

£356,089.1

127479897.8

128164

1.26799E+11

Q4 2003

340

£362,113.7

123118658

115600

1.31126E+11

Q1 2004

447

£364,736.2

163037081.4

199809

1.33032E+11

Q2 2004

452

£395,012.6

178545695.2

204304

1.56035E+11

Q3 2004

494

£403,472

199315168

244036

1.6279E+11

Q4 2004

398

£363,630

144724740

158404

1.32227E+11

Q1 2005

300

£399,511

119853300

90000

1.59609E+11

Q2 2005

350

£415,615

145465250

122500

1.72736E+11

Q3 2005

445

£433,723.8

193007091

198025

1.88116E+11

Q4 2005

428

£404,796.4

173252859.2

183184

1.6386E+11

Q1 2006

391

£431,487

168711417

152881

1.86181E+11

Q2 2006

426

£454,038.7

193420486.2

181476

2.06151E+11

Q3 2006

486

£474,899.3

230801059.8

236196

2.25529E+11

Q4 2006

474

£443,468.4

210204021.6

224676

1.96664E+11

Q1 2007

426

£494,854.8

210808144.8

181476

2.44881E+11

Q2 2007

447

£529,156.8

236533089.6

199809

2.80007E+11

Q3 2007

490

£575,658.7

282072763

240100

3.31383E+11

Q4 2007

431

£536,261.6

231128749.6

185761

2.87577E+11

SUM

18,202

£15,218,243

5,982,454,675

7,053,270

5.45022E+12

Regression Line

b = 1,401.870047 a = -214,554.0571 y = -214,554 + 1,401.87x

Correlation Coefficient

n = 48, ∑XY = 5,982,454,675 ∑X = 18,202 ∑Y = 15,218,243 ∑X² = 7,053,270

∑Y² = 5,450,220,000,000 Therefore; r = 0.6886964582

Coefficient of Determination r² = 0.4743028115

4.4 Regression Number of Transactions in the UK and Outer London House Prices

Year Ended

Number of Transactions UK (X)

Median Outer London House Prices (Y)

YX

Q1 1996

261

£59,562.61

15545841.21

68121

3547704510

Q2 1996

284

£57,936.38

16453931.92

80656

3356624128

Q3 1996

338

£61,673.3

20845575.4

114244

3803595933

Q4 1996

360

£61,919.44

22290998.4

129600

3834017050

Q1 1997

324

£61,595.91

19957074.84

104976

3794056129

Q2 1997

351

£65,902.75

23131865.25

123201

4343172458

Q3 1997

387

£69,763.31

26998400.97

149769

4866919422

Q4 1997

377

£69,279.5

26118371.5

142129

4799649120

Q1 1998

317

£72,235.88

22898773.96

100489

5218022359

Q2 1998

317

£77,777.06

24655328.02

100489

6049271062

Q3 1998

377

£77,881.31

29361253.87

142129

6065498447

Q4 1998

335

£79,012.63

26469231.05

112225

6242995700

Q1 1999

316

£78,680.44

24863019.04

99856

6190611639

Q2 1999

342

£84,836.31

29014018.02

116964

7197199494

Q3 1999

414

£92,744.56

38396247.84

171396

8601553410

Q4 1999

397

£94,032.88

37331053.36

157609

8842182521

Q1 2000

367

£97,181.25

35665518.75

134689

9444195352

Q2 2000

348

£105,213.9

36614437.2

121104

11069964753

Q3 2000

379

£112,045.4

42465206.6

143641

12554171661

Q4 2000

339

£108,261.8

36700750.2

114921

11720617339

Q1 2001

327

£113,836.4

37224502.8

106929

12958725965

Q2 2001

347

£118,500.9

41119812.3

120409

14042463301

Q3 2001

396

£128,146.5

50746014

156816

16421525462

Q4 2001

387

£133,228.9

51559584.3

149769

17749939795

Q1 2002

342

£137,473.8

47016039.6

116964

18899045686

Q2 2002

395

£147,839.4

58396563

156025

21856488192

Q3 2002

457

£164,242.9

75059005.3

208849

26975730200

Q4 2002

392

£168,480.3

66044277.6

153664

28385611488

Q1 2003

340

£172,395.1

58614334

115600

29720070504

Q2 2003

306

£175,015

53554590

93636

30630250225

Q3 2003

358

£180,672

64680576

128164

32642371584

Q4 2003

340

£187,122.3

63621582

115600

35014755157

Q1 2004

447

£187,760.9

83929122.3

199809

35254155569

Q2 2004

452

£192,654.3

87079743.6

204304

37115679308

Q3 2004

494

£200,815

99202610

244036

40326664225

Q4 2004

398

£201,122

80046556

158404

40450058884

Q1 2005

300

£198,732

59619600

90000

39494407824

Q2 2005

350

£204,705

71646750

122500

41904137025

Q3 2005

445

£209,004.1

93006824.5

198025

43682713817

Q4 2005

428

£206,935.8

88568522.4

183184

42822425322

Q1 2006

391

£208,352

81465632

152881

43410555904

Q2 2006

426

£214,585.2

91413295.2

181476

46046808059

Q3 2006

486

£224,355.9

109036967.4

236196

50335569865

Q4 2006

474

£228,694.2

108401050.8

224676

52301037114

Q1 2007

426

£234,267.3

99797869.8

181476

54881167849

Q2 2007

447

£242,460.5

108379843.5

199809

58787094060

Q3 2007

490

£254,708.1

124806969

240100

64876216206

Q4 2007

431

£253,671.7

109332502.7

185761

64349331381

SUM

18,202

£6,877,314

2,719,147,638

7,053,270

1.17288E+12

Regression Line

b = 736.8998122 a = -136,161.1746 y = -136,161.2 + 736.9 x

Correlation Coefficient

n = 48, ∑XY = 2,719,147,638 ∑X = 18,202 ∑Y = 6,877,314 ∑X² = 7,053,270

∑Y² = 1,172,880,000,000 Therefore; r = 0.6610921139

Coefficient of Determination r² = 0.4370427831

4.4 Regression Number of Transactions in the UK and Outer London House Prices

Year Ended

Median Inner London House Prices

Median Outer London House Prices (Y)

YX

Q1 1996

£148,896.8

£59,562.61

8868682029

22170257050

3547704510

Q2 1996

£142,925.9

£57,936.38

8280609254

20427812891

3356624128

Q3 1996

£149,826.8

£61,673.3

9240313184

22448069998

3803595933

Q4 1996

£147,718.2

£61,919.44

9146628222

21820666611

3834017050

Q1 1997

£149,578.9

£61,595.91

9213448462

22373847325

3794056129

Q2 1997

£169,794.3

£65,902.75

11189911304

28830104312

4343172458

Q3 1997

£185,726.6

£69,763.31

12956902371

34494369948

4866919422

Q4 1997

£182,093.8

£69,279.5

12615367417

33158151998

4799649120

Q1 1998

£191,055.1

£72,235.88

13801033277

36502051236

5218022359

Q2 1998

£200,912.9

£77,777.06

15626414678

40365993386

6049271062

Q3 1998

£204,534.8

£77,881.31

15929438165

41834484411

6065498447

Q4 1998

£186,289.4

£79,012.63

14719215435

34703740552

6242995700

Q1 1999

£204,493.7

£78,680.44

16089654293

41817673340

6190611639

Q2 1999

£220,366.6

£84,836.31

18695089191

48561438396

7197199494

Q3 1999

£245,895.6

£92,744.56

22805479228

60464646099

8601553410

Q4 1999

£257,173.3

£94,032.88

24182746058

66138106233

8842182521

Q1 2000

£270,717.4

£97,181.25

26308655329

73287910663

9444195352

Q2 2000

£280,789.9

£105,213.9

29543000460

78842967942

11069964753

Q3 2000

£283,595

£112,045.4

31775515213

80426124025

12554171661

Q4 2000

£293,616.9

£108,261.8

31787494104

86210883966

11720617339

Q1 2001

£295,314.7

£113,836.4

33617562315

87210772036

12958725965

Q2 2001

£297,391.6

£118,500.9

35241172252

88441763751

14042463301

Q3 2001

£321,468.8

£128,146.5

41195101579

1.03342E+11

16421525462

Q4 2001

£297,663.8

£133,228.9

39657420644

88603737830

17749939795

Q1 2002

£312,468.9

£137,473.8

42956287065

97636813467

18899045686

Q2 2002

£352,693.6

£147,839.4

52142010208

1.24393E+11

21856488192

Q3 2002

£352,302.1

£164,242.9

57863118580

1.24117E+11

26975730200

Q4 2002

£349,899.5

£168,480.3

58951172730

1.2243E+11

28385611488

Q1 2003

£332,701.3

£172,395.1

57356073884

1.1069E+11

29720070504

Q2 2003

£351,811.4

£175,015

61572272171

1.23771E+11

30630250225

Q3 2003

£356,089.1

£180,672

64335329875

1.26799E+11

32642371584

Q4 2003

£362,113.7

£187,122.3

67759548406

1.31126E+11

35014755157

Q1 2004

£364,736.2

£187,760.9

68483197175

1.33032E+11

35254155569

Q2 2004

£395,012.6

£192,654.3

76100875944

1.56035E+11

37115679308

Q3 2004

£403,472

£200,815

81023229680

1.6279E+11

40326664225

Q4 2004

£363,630

£201,122

73133992860

1.32227E+11

40450058884

Q1 2005

£399,511

£198,732

79395620052

1.59609E+11

39494407824

Q2 2005

£415,615

£204,705

85078468575

1.72736E+11

41904137025

Q3 2005

£433,723.8

£209,004.1

90650052468

1.88116E+11

43682713817

Q4 2005

£404,796.4

£206,935.8

83766866871

1.6386E+11

42822425322

Q1 2006

£431,487

£208,352

89901179424

1.86181E+11

43410555904

Q2 2006

£454,038.7

£214,585.2

97429985247

2.06151E+11

46046808059

Q3 2006

£474,899.3

£224,355.9

1.06546E+11

2.25529E+11

50335569865

Q4 2006

£443,468.4

£228,694.2

1.01419E+11

1.96664E+11

52301037114

Q1 2007

£494,854.8

£234,267.3

1.15928E+11

2.44881E+11

54881167849

Q2 2007

£529,156.8

£242,460.5

1.283E+11

2.80007E+11

58787094060

Q3 2007

£575,658.7

£254,708.1

1.46625E+11

3.31383E+11

64876216206

Q4 2007

£536,261.6

£253,671.7

1.36034E+11

2.87577E+11

64349331381

Q1 2008

£584,706.4

£249,366.9

1.45806E+11

3.41882E+11

62183850816

Q2 2008

£570,786.1

£248,421.1

1.41795E+11

3.25797E+11

61713042925

Q3 2008

£584,098.4

£232,884.6

1.36028E+11

3.41171E+11

54235236917

Q4 2008

£494,282.3

£215,512.9

1.06524E+11

2.44315E+11

46445810066

Q1 2009

£564,941.1

£210,796.7

1.19088E+11

3.19158E+11

44435248731

Q2 2009

£482,495.8

£214,048.4

1.03277E+11

2.32802E+11

45816717543

Q3 2009

£570,295.6

£225,076.2

1.2836E+11

3.25237E+11

50659295806

SUM

£19,069,848

£8,473,421

3.39612E+12

7.58058E+12

1.53837E+12

Regression Line

b = 736.8998122 a = -136,161.1746 y = -136,161.2 + 736.9 x

Correlation Coefficient

n = 55, ∑XY = 3,396,120,000,000 ∑X = 19,069,848 ∑Y = 8,473,421

∑X² = 7,580,580,000,000 ∑Y² = 1,538,370,000,000

Therefore; r = 0.4730322188

Coefficient of Determination r² = 0.22375948

Chapter 5: Conclusion & Recommendations

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