The determinants of terrace housing rates in malaysia

1. THE DETERMINANTS
OF TERRACE
HOUSING RATES IN
MALAYSIA
1st Presenter: ASMA LIYANA JA’AFAR
2014838744
2nd Presenter: SYAHIRAH AMIRA MD. DIN
2014223624
3rd Presenter: AMIRUL NIZAM MOKHTAR
2014604954

2. OUTLINES 1.0
 INTRODUCTION
Problem Statements
RQ & RO
Significance of Study
Limitation of Study
Scopes of Study
Definition of Terms
 LITERATURE
 METHODOLOGY
 DISCUSSION

3. INTRODUCTION
 Average housing prices in Malaysia increases up to 20% per
year after year 2007 (Tze San Ong,2013).
 Terrace housing industry is very salient beneficial to Malaysia
especially in the process of becoming a developed country
(Jarad, 2010).
 Government identifies that terrace housing is a basic need for
every citizen.
 Housing scheme (PR1MA).

4. Malaysia’s Property Market
Slowing
Global Property Guide. (2014, June 15). Malaysia's Property
Market Slowing. Retrieved from Global Property Guide:
http://www.globalpropertyguide.com/Asia/malaysia/Price-
History
Malaysia’s nationwide house
prices rose to RM276,668
Nominal (red line): Excludes
macroeconomic factors
Real (blue line): Includes
macroeconomic factors

5. PROBLEM STATEMENTS
 Rapid economic development has resulted in an increasing
demand in Malaysia.
 The price of house increasing dramatically, which has affected
the decision making for house buyers.
 This is a worrying trend for lenders and brings out a big issue. (Tze
San Ong, 2013)
 Been a major problem for Malaysian middle-class incomers.
 Average monthly household income increase to RM5,900 from
RM5,000 in 2012. (Malay Mail Online, 2014)
 Median household income for 2014 is RM4,258 compared to
2012, RM3,626. (Malay Mail Online, 2014)

6. Affordability of Middle-Income
Earner & Average House Prices
Dr W. N. Azriyati, A. P. (2009). Affordability Compared to Mean
Housing Price For Current Middle Income Home Owners. A Study
on Affordable Housing Within The Middle Income Households in
The Major Cities and Towns in Malaysia, 15.
Aidila, C. (2011, May 12). Rising House Prices Create
Homeless Generation. Retrieved from Malaysia Kini:
www.malaysiakini.com/news/163963

7. RESEARCH QUESTIONS &
RESEARCH OBJECTIVES
RESEARCH QUESTIONS
• Does terrace housing rates in
Malaysia increase when Foreign
Direct Investment (FDI) increases?
• Does increase in inflation rate
influenced the increased of
terrace housing rates in
Malaysia?
• When population growth rates
increase, does terrace housing
rate in Malaysia increases?
RESEARCH OBJECTIVES
• To identify the relationship
between Foreign Direct
Investment (FDI) with terrace
housing rates in Malaysia.
• To examine the relationship
between inflation rate with
terrace housing rates in Malaysia.
• To study the relationship between
population growth rates with
terrace housing rates in Malaysia.

8. SIGNIFICANCE OF STUDY
Researchers & Academicians
Government policy
Banking sector

9. LIMITATION OF STUDY
 Availability of data
Data is available but the components are
comprehensive. Some data collected were not properly
in quarterly basis.

10. SCOPE OF STUDY
 Identify the determinants of housing rates in Malaysia
using four theories.
 Selected macroeconomic variables.
 Secondary data (BNM, MIDA, DOSM & World Bank).
 Quarterly basis (30 data).
 Period Q3 2006 – Q4 2013.

11. DEFINITION OF TERMS
• Labour in various specialty in construction, material
costs, and investment which can influence the
property rates.
Foreign Direct Investment (FDI)
• Immediate increase in price of such “store of value”
real assets that directly influence the housing rate.
Inflation rate
• Indicates that the demand for the housing is high
when the population is increases.
Population growth rate

12. OUTLINES 2.0
 INTRODUCTION
 LITERATURE
Literature Review
Underpinning Theories
Research Framework
Hypothesis Statement
 METHODOLOGY
 DISCUSSION

13. LITERATURE
REVIEW

14. FOREIGN DIRECT INVESTMENT
(FDI)
 When the developer runs FDI, it will affect the cost incurred to be
increased and this will lead to upturn of property price which will
be a major problem to the purchaser (MacDonald, 2010).
Another studies conducted by David (2010) found something
more which stated that when the developer used foreign
investment on workers at low-cost property building, it is not really
appropriate as trade barriers for investment exist as uncertainty.
These correlation drawback between FDI and workers which
increase the housing price is called the shadow house price.
Wang (2013), in the other hand found the extra finding of the
impact of FDI on house price was greater than that of house price
on FDI.

15. INFLATION RATE
 An increase in the expected rate of inflation causes an immediate
increased in the relative price of such "store of value" real assets
(Felstein, 1983). So, when cost of building increase, of course the
developer will tend to charge higher price for their terrace housing
property to the purchaser. The research done by Piazzesi and
Schneider (2009) made an extension from the previous study which
commended that higher the expected inflation tends to lead to an
increase in the price-dividend ration on houses. Another finding
from McBride (2013) supported this variable which indicated that
when inflation is high, the cost of buying a home increases as
lenders raise interest rates to curb inflation. As the dollar loses some
of its purchasing power with a rise in inflation, any savings have to
put aside for a down payment loses value as well.

16. POPULATION GROWTH RATE
 According to Ley (2010) and Ong (2013), agreed that housing prices are
related to the population. A study done stated that an increase in the
population in Malaysia increases the housing demand and therefore
increases the housing price. If there is a greater demand than a supply for
housing, it will affect the housing price too. When there are fewer houses in
the market, people are willing to spend more money to buy a house. This will
cause the housing price to increase. Another study conducted by The
finding by Swann (2013) go beyond the previous research by indicated that
the overall direction of population growth and housing increase is however
jointly upward, and population remains a major determinant of housing
requirement. This is strengthen by Pettinger (2014), emphasized that if supply
of housing fails to meet the growth in the number of households, it will
increase the cost of living, house prices and the cost of renting. This shortfall
is causing an increase in long-term house prices, reducing affordability.

17. UNDERPINNING THEORIES
 Demand and Supply Theory (Marshall, 1890)
This theory is used to determine the price of market product or services .
Quantity demanded is the amount of the good that buyers are willing to
purchase and quantity supply is the amount that sellers are willing to sell in
the market.
 Maslow Hierarchy of Needs (Maslow, 1943)
This theory represented the human’s physiological needs as the base of
a triangle to show that meeting these needs are the most important in our
lives; shelter or house is one of the requirements for addressing the
physiological needs.
 Quantity Theory of Money (Fisher, 1867)
The quantity theory of money states that there is a direct relationship
between the quantity of money in an economy and the level of prices of
goods and services sold.
 FDI Macro-Micro Level Theory (Hymer, 1976)
The macro-level FDI theories give the macroeconomic factors that
determine the FDI and micro-level theories discuss the motivation of FDI
associated with the firm level.

18. RESEARCH FRAMEWORK
Foreign Direct Investment
(FDI)
Inflation Rate
Population Growth Rate
Terrace Housing
Rate
INDEPENDENT VARIABLES DEPENDENT VARIABLE

19. HYPOTHESIS STATEMENTS
 Foreign Direct Investment (FDI)
H1: If FDI is high, then the terrace housing rates in Malaysia will
increase.
 Inflation rate
H1: If inflation rate is high, then the terrace housing rates in
Malaysia will increase.
 Population growth rate
H1: If population growth rate is high, then the terrace housing
rates in Malaysia will increase.

20. OUTLINES 3.0
 INTRODUCTION
 LITERATURE
 METHODOLOGY
Research design
Data collection method
Regression Flows
Unit Root Test
Normality Test
Auto-Correlation Test
Multicollinearity Test
Correlation Test
Multiple Regression – Findings
 DISCUSSION

21. RESEARCH DESIGN
Purpose of study – Causal study/Hypothesis testing
Type of investigation - Correlation
Study setting – Non-contrived
Time horizon - Longitudinal
Unit of analysis - Macro economy

22. DATA COLLECTION METHOD
Secondary data
Retrieved from Bank
Negara Malaysia,
Department of Statistics
Malaysia, MIDA & World
Bank
Using 30 data start from
Quarter 3, 2006 until
Quarter 4, 2013
Journals retrieved from
Emerald, UiTM Ez Access
and Google Scholar

23. Regression Flows
Secondary Data Collected
Unit Root Test
Multiple Regression
Analysis
• F-test
• R-squared
• Significant Level
Correlation Test
Multicollinearity Test
Normality Test
Auto-Correlation Test
Controlling
Variables

24. Unit Root Test
 A condition with a constant mean, constant variance,
and constant auto-covariances for each given lag.
Variables
5% Significant at
Level (intercept)
5% Significant at
1st Difference
(intercept)
Housing Price
Indicator (Y)
0.7609 0.0000
Foreign Direct
Investment (X1)
0.3212 0.0003
Inflation Rate
(X2)
0.4133 0.0128
Population
Growth Rate
(X3)
0.3731 0.0001
 The data has no unit root

25. Normality Test
 Determine whether error term is normally distributed
 The error term is normally distributed > 5%

26. Auto-Correlation Test
 To investigate whether there is a serial independence
for the error term
Breusch-Godfrey Serial Correlation LM Test:
F-statistic 3.986378 Prob. F(2,23) 0.0326
Obs*R-
squared
7.464945
Prob. Chi-
Square(2)
0.0239
 Error term is serially independent > 5%

27. Multicollinearity Test
 Whether independent variables are highly correlated
with each other or not
Independent Variables
Centered Variation
Inflation Factor
Foreign Direct Investment
(X1)
1.224135
Inflation Rate (X2) 1.233808
Population Growth Rate
(X3)
1.051758
 There is no multicollinearity problem < 10 value

28. Correlation Test
 If there exists any linear relationship or correlation of
the dependent variable with any of the independent
variable
 There is a correlation < 5%
P-Value of T- Statistic
Foreign
Direct
Investment
(X1)
Inflation
Rate (X2)
Population
Growth
Rate (X3)
Housing
Price
Indicator
(Y)
0.420155 0.020211 0.733684

29. Multiple Regression - Findings
Variable Coefficient Std. Error t-Statistic Prob.
C 31.39395 4.859412 6.460443 0.0000
Foreign Direct
Investment
0.839862 0.285685 2.939816 0.0070
Inflation Rate -0.186718 0.316382 -0.590168 0.5604
Population Growth
Rate
-15.95356 2.784843 -5.728710 0.0000
R-squared 0.661821
Prob. F-statistic 0.000004
 Most Significant : Population
Growth Rate
Independent
Variables
Hypothesis Findings
Relationship with
DV
Foreign Direct
Investment
If FDI is high, then the terrace
housing rates in Malaysia will
increase
Significant at
5%
Confidence
level
Directly
Proportional
Inflation Rate
If inflation rate is high, then
the terrace housing rates in
Malaysia will increase
Not Significant
at 5%
Confidence
level
-
Population
Growth Rate
If population growth rate is
high, then the terrace
housing rates in Malaysia will
increase
Significant at
5%
Confidence
level
Inversely Related

30. OUTLINES 4.0
 INTRODUCTION
 LITERATURE
 METHODOLOGY
 DISCUSSION

31. DISCUSSION
 For future research undertakings, we recommend that the
researcher:
 To use panel data, varies in term of geographical area (etc
urban/rural).
 To use data period on yearly basis (widen the spurious
regression).
 Using currency value instead of rate of percentage for
dependent variable.