Australian House Price Index Forecasting Economics Essay

Prediction is the method of detecting informations of variables in the past and in the present and doing illations and anticipations about the expected values of those variables in the hereafter. One of the variables whose informations is observed over clip by the ABS is the house monetary values, which can be used to explicate a lodging monetary value index for the observation period.

House monetary value index is a step used in measurement of the monetary value of residential lodging ( Wikipedia ) . It is a step used by the authorities and the private sector to be able to detect the tendency and behaviour of the residential house monetary values and be able to find the factors that have caused alterations in the monetary values. It besides assists in calculating methods to find what the hereafter of house monetary values look like so as to find how investings are made in the lodging sector.

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A good sum-up of the steps of the house monetary values is given by the lodging monetary value indices provided by the ABS ( Australian Bureau of Statistics ) , which are fundamentally meant for usage in authorities economic sciences, planning and budgeting. However, they are besides provided to other stakeholders for usage in their ain planning and analysis so as to better on the sector of residential lodging. ( Wheelwright, 1998 ) .

The ABS normally collects and releases informations on the chief colony countries and the countries within the largest Numberss of residential houses, which include the 8 capital metropoliss of Australia, viz. Sydney, Melbourne, Brisbane, Perth, Adelaide, Hobart and Darwin.

in this survey, the informations used was for the leaden agencies of all the metropoliss supplying an overview of the state ‘s public presentation in footings of the lodging monetary value index.

Methodology and justification

There are many methods that are used in the preparation of the lodging monetary value index ( HPI ) . The method used to explicate the HPI in this survey is the hedonistic theoretical account of lodging monetary value index. This method is efficient since it considers the informations collected for the specific period and gives a HPI which can be used to compare with other clip periods.

There are many calculating methods that can be used in calculating the monetary values of the houses in the hereafter utilizing the observed informations from past house monetary values and from the HPI gotten from the informations.

There are two chief types of methods of calculating that can be used to give prognosiss of the lodging monetary value index. This includes qualitative and quantitative methods. In this survey, qualitative methods will be used since at that place seems to be a systematic tendency in the alterations of the lodging monetary value index. ( Putra, 2009 ) .

The pick of the method to utilize depends on many facets including phase of development rhythm, variables involved, desired truth, minimal tolerance degree of mistake and the sum of informations available. ( Putra, 2009 ) .

Short-run methods are used for strategic planning. The most appropriate methods for short-run prediction of the lodging monetary value index are the different quantitative methods such as causal and clip series analysis. The causal method carries cheques for correlativity between the dependant and independent variable thought to be doing alterations in it. A arrested development analysis can be used to give the tendency and prognosiss. ( Hyndman, 2009 ) .

In this survey, the clip series analysis method is used. This method gives really dependable and accurate estimations and it considers past informations in its analysis. Merely from looking at the past behaviour of a variable can we be able to look into on its tendency and presume it follows the same tendency in the close future hence doing really feasible and accurate prognosiss for the values of the variable.

In specific, we will utilize the exponential smoothing method of clip series analysis. This method is really convenient since it does non necessitate so much informations and provides really dependable prognosiss with minimal mistake. It besides involves simplified prediction computations and involves self-correcting mechanisms to cut down the mistake. This method has a disadvantage of being inaccurate when there is consistent form in the information being used. ( Dash, 2003 )

The most appropriate method for Long-term prediction of monetary values is the judgment attack of prediction in which uses merely human judgement from experts and the does non needfully depend on informations from the past history to do decisions and prognosiss. This method is more preferred since it is difficult to state what alterations will hold taken topographic point in the long-run period in Australia ‘s residential lodging.

Consequences and reading

From the informations obtained from ABS, the following tabular array of Housing monetary value index was obtained. It shows the per centum quarterly monetary value indexes for the old ages 2005-2009.

Table 1: Percentage means difference in House monetary value indices for the 8 metropoliss, Australia.



Price index













































% alteration over a one-fourth

Beginning: Australian Bureau of Statistics ( ABS )

Graph 1: The graph demoing the per centum difference in House monetary value indices for the 8 metropoliss, Australia:

The Regression Model for the clip series demoing how the HPI alterations with clip was calculated utilizing SPSS statistical package and the following tabular array was generated to give the arrested development theoretical account. In this chart, there is a celebrated tendency of addition in the Housing Price Index from the twelvemonth 2005 to stop of the twelvemonth 2007. Then there is a sudden lessening in the twelvemonth 2008 with the lowest HPI being noted in that twelvemonth. Actually, the HPI is -2.6, the lowest of all time noted HPI in the clip frame.

Observed Trend and its reading

From the informations above, a tendency can be noted of the form of the house monetary values in Australia. There seems to be a general addition in the house monetary values except for the monetary values of the houses in 2008 where there was the greatest bead in the house monetary values of all time seen for many old ages in Australia.

The arrested development theoretical account besides forecasts an addition and sum up it by demoing that in every following one-fourth, there is an addition in the HPI of ( 1.316 + 0.02 * Previous HPI ) hence a general addition in HPI is expected. Hence, for an addition of one unit in clip, there is an addition of 0.020 in the Future HPI if all factors are held changeless.

The addition in the monetary values can be attributed to many variables which include old alterations in the monetary values and macroeconomic variables. For the old alterations in the monetary values, a big monetary value addition in the past leads to a comparatively lower monetary value addition or a lessening in the monetary value. Besides, a little addition in the past monetary values leads to a comparatively larger addition in the monetary value in the current one-fourth. Similarly, a lessening in the monetary value in one one-fourth has the same consequence in the monetary value index of the following one-fourth as that of an addition.

The macroeconomic variables include rising prices rate, population growing, involvement rates, involvement rates, GDP, household income among others. Surveies have shown that population growing has the largest consequence on the house monetary value index since an addition in the population increases the demand for more houses, with the consequence of increasing the monetary value. This may explicate the continuously increasing monetary values of the houses since it is good known that the population of Australia has been increasing quickly.

Surveies have besides shown that there has been an addition in the GDP over the past old ages, which has besides had a comparatively big consequence on the HPI. Unemployment and involvement rates have the least consequence on the HPI, though their consequence is important in the overall HPI of the state. ( Lange, 2005 )


Prediction is a method used both traditionally and by scientists to do anticipations for future happenings of events, or for future expected values of variables in the steps being investigated. Traditionally, prediction was done for things like conditions and expected crops though most of the methods used were merely through personal judgement and observation. The same methods are used for some facets in daily life and still work good and accurately, particularly for short-run informations.

Scientific methods nevertheless are more accurate and dependable and are more preferred in the current personal businesss and occurrences in the daily life. Both scientific and traditional methods are used in calculating in finance and accounting Fieldss. They help investors to foretell the hereafter of their concerns and cognize what to make and where to put. They are therefore able to do more dependable and helpful determinations to put in the countries that are more profitable. On the other side, prediction may assist one to seek and avoid or set the factors that may impact the tendency of a concern or an investing.

In the lodging sector, prediction may assist in look intoing the old tendency of the lodging monetary value index and finding which metropoliss to put in and by how much. If the analysis shows that the lodging monetary value index is high, so investors must strike a balance between supply of residential houses and the current and future demand in the market.

The smoothing method of clip series analysis is a dependable scientific method that can be used to give really dependable and accurate prognosiss into the hereafter. It is a really convenient method that uses informations from the old observations to give the prognosiss, look intoing on the presence of tendency. This method is more dependable for short-run prediction where the tendency is non expected to change excessively much.

Table 2: Arrested development Model Table.


Unstandardized Coefficients

Standardized Coefficients




Std. Mistake



( Constant )











a Dependent Variable: HPI

The expression for the exponential smoothing theoretical account of prediction is

F t+1 = i?? D T + ( i??-1 ) F T + C


Ft+1 is the forecasted Housing Price Index for the t+1 period ( following one-fourth )

i?? is the Smoothing invariable,

Ft is the current clip Housing Price Index, and

C is the general invariable ( tendency ) .

The arrested development theoretical account for the House Price Index is given by:

Future HPI = 0.020 Time + 1.316

The analysis shows that for every addition of one unit in clip, there is an addition of 0.20 in the Housing Price Index, all else held invariable.

Therefore the prognosiss for the subsequent quarters are:

December 2009:

HPI 20 = 0.020 HPI 19 + 1.316

0.020 ( 4.42 ) + 1.316


March 2010:

HPI 21 = 0.020 HPI 20 + 1.316

0.020 ( 4.42 ) + 1.316


June 2010:

HPI 22 = 0.020 HPI 21 + 1.316

0.020 ( 4.42 ) + 1.316


September 2010:

HPI 23 = 0.020 HPI 22 + 1.316

0.020 ( 4.42 ) + 1.316


The prognosis for the December 2020 would necessitate usage of opinion attack where observations are made of the current lodging monetary value index and expertness applied in gauging the hereafter HPI. If the tendency does no change excessively much, and presuming the HPI, maintains a changeless lessening or addition, so lets presume a HPI of 1 in the old one-fourth. Then, the expected HPI for the last one-fourth of 2020 would be around:

HPI 64 = 0.020 HPI 63 + 1.316

0.020 ( 1 ) + 1.316



From the analysis affecting the informations obtained from the Australia Bureau of Statistics, there has been noted that in the past few old ages, more specifically organize the twelvemonth 2005-2009 there has been an addition in the tendency of the Housing Price Index. The HPI has continually increased between the quarters with few beads in the HPI noted in some quarters. The HPI is a step that is affected by many factors, both internally and externally.

Population addition has been attributed to the addition in the HPI as the greatest subscriber of the addition. This is because the increased population increases the demand for more lodging and therefore the supply goes down doing an inv=crease in the HPI. Besides, an addition in the GDP would intend that more people can afford to purchase their ain residential premises therefore increasing the HPI. A rise in the involvement rates has a big consequence on the monetary value of the houses due to a rise ion the cost of building of the houses doing an addition in the monetary value of the houses themselves. Unemployment would connote that

In the Year 2008 up to the 3rd one-fourth there is a great lessening in the Housing monetary value index. This may be explained by the high competition in the Housing traders and existent estate investors, which may hold increased the supply of houses high above the demand by the possible and available clients who could hold been able to purchase the residential houses.



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