Page 236 - Contributed Paper Session (CPS) - Volume 8

CPS2265 Siti Salwani Ismail et al.

5. Data
The data for this study was drawn from three main sources: Economic
Census / Survey of Real Estate Services, Central Bank of Malaysia Statistical
Bulletin and statistical compilation by National Property Information Centre
which is available in its website. For the purpose of analysis, a time series of 5
years data from year 2010 to year 2015 was used. The data extracted were
gross output of real estate subsector, base lending rate, loan applied for
residential property and average price house in Malaysia. In order to reduce
the volatility, all variables were converting to log linear form (for example using
ln output of real estate subsector instead of actual value of output of real
estate subsector).

6. Model
In order to develop the regression model for factors affecting the gross
output value of real estate subsector in Malaysia, multiple regression function
was used.
The regression function was shown in Equation 1.

= + + +

(1)

Where Y is the dependent variable, X2 and X3 the explanatory variables (or
regressors), e the residual term and i the ith observation; in case there are time
series, the subscript t will denote the t observation.
th
For this study, the function of gross output value for real estate subsector
was given in Equation (2).

O = f (LA, BLR, APH) (2)
Following variables are used throughout the model:
O = Gross output of real estate subsector
LA = Loan approved

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