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Construction industry play an important role in promoting the growth of economy in a county, with establish the building, infrastructure and factory its will stimulate other sector to expand. The construction activity is not only focusing in construction phase but it also include the pre-construction and after construction phase.
Construction can be defined as the activity of the creation of physical infrastructure, superstructure and related facilities, it’s also including maintenance and demolition of infrastructure, Installation of machinery or equipment after the original construction that require modification are also included (Ofori, 1990). The output of construction industry is differing from other industry output, it is not homogenous and each of them can be considered unique. It’s also very expensive because it including a very high cost and the structure are large, therefore the buyers and seller is not as many as other good. The output in construction industry are fixed in placed therefore it’s cannot be move to the place that have a demand, this cause the construction work need to be done in a certain location that have a demand on them.
Since 1950 Malaysia construction industry has establish and it has gone through very tough situation where they have lack of advance technology and during year 1982-1992 this industry performance become worst because of the world economic collapse especially at big country Europe, followed by Asian financial crisis at 1997-1998. But despite of many obstacles that have been trough, this industry has fast recover and now we can see that these industry has done many contribution towards making Malaysia a develop country at 2020. Figure 1.1 shows the growth and contribution to GDP of construction sector.
Malaysia had attained robust economic since 1980 and even in the figure show that the construction sector growth line declining to -14.0 percent at 1986 but the contribution towards GDP just show a little bit decline, it’s just decline only 0.3 percent from years 1985 their contribution was 5.2 percent and at 1986 was 4.8 percent(Economic Report : Various Issues).
In 1995 construction sector has achieve a very good performance ever achieved where their growth was 21.1 percent following with the growth of transfer properties of new and existing building was 15.8 percent and 34.1percent. For the residential component, the growth of transfer of new and existing building are 11.7 percent which are reached 156,915 units of houses with a total value of RM 15.8 billion. Loan offered by the banking system grew by 18.1 percent or RM 5.1 billion to RM33.1 billion at the end of 1995. Report from Bank Negara says that the statistic of individual loan that has been offered approved by the bank was increase by 38.1 percent. From this value 51.9 percent is for medium cost house, high cost is 36.1 percent and 12.0 percent for low cost. For non-resident component the report shows that the total transfer of commercial building grew by 10.1 percent to RM6.9 billion and the loan that has been approved by bank was RM40.2 billion.
In 1998 Malaysian face the worst economic recession, this is due to the Asian Financial crisis that result the meltdown of financial sector and affect all sector in Malaysia including construction industry. The growth of construction industry in that time sliding down from 10.6 percent in 1997 to -24.0 percent in 1998, due to the financial crisis that has paralyze the economy so government has done a fiscal policy to recover it back, however there still have a risk that could dampen the economic growth due to the external environment uncertainties which cloud prolog these crisis or make it more worst.
Construction Sector Growth and Malaysian Economic Trend (Constant Price) For Year 1980-Q1 2009
Source: CIDB (Construction Industry Development Board), Construction Growth
This due to lack of effort at the international level to tackle this crisis effectively, therefore government has continued its efforts to stimulate back the economic by implanting the National Economic Recovery Plan and this registering and impressive GDP growth of construction sector of 6.1 percent in 1999 and 8.3 percent in 2000.
Malaysia are well known with their open economic strategy and their performance very much depends on their partners such as Japan, United State and the European Union as their trading partner and this give Malaysian a goods economic performance during 2001, after the historical moment at 11 September 2001 where the terrorist attack on PWC cause the United State economy slipping down rapidly and followed by the multi-billion dollar corporate scandal. The uncertainties of the global economy after the tragedy and a declining in electronic industry led to decease in demand on our export causing Malaysia GDP growth increase very slow only 0.4 percent in 2001, this slow down the construction industry in Malaysia and their contribution declining every year from 2001 the contribution was 4.0 percent and decline to 3.0 percent in 2006.
From the figure 1.1 we can see the growth performance of construction industry fluctuated and it follow the trend of economic growth. If the economic in good condition the construction sector growth also will show the positive growth, even the trend are followed by the economic growth the construction share on GDP still low compared with other sector.
From figure 1.2 show that share of Malaysia sector to GDP from year 2000-2008, the highest share is services sector followed by manufacturing and construction sector are in the lowest rank in share of GDP. Government had allocate a lot of money to stimulate the construction sector, during year 2000 government had allocate RM18 billion under 2000 budget in this sector and from that show an increment in construction growth from 0.4 percent at 2000 to 3.3 at year 2001.
Figure 1.2 and table 1.3 shows the differential of what happen in construction sector in Malaysia. As we can see the share of construction sector to economic GDP is very low compared to other sector but based on government Malaysia Plan show that the project awarded increasing every year. During 8th Malaysian Plan the total value of project awarded is RM256.27 billion plus with additional government stimulus package at year 2000, during 9th Malaysian Plan the total value of project awarded are RM380 billion which are higher from before. This shows that the important of construction sector in promoting the sustainable growth for nation and by the implementation of infrastructure in private or government sector it create a strong linkage with other sector.
There is no doubt to say that construction sector was the initial point to the development of country and it’s also contributed to other sector. The share of these sector to the economy are evaluated by taking the construction value added that usually expressed as a percentage of GDP, based on World Bank the share of construction sector in GDP is differ between developing and develop country.
This observation had been done by Turin and Strassman(1974) where they state that their share of construction sector toward GDP in develop country is between five to eight percent and for developing country is between three to five percent. Other researcher such as Miles (1984) and Wells (1985) get the similar result. But after 1980s the share of these sector in GDP are higher than what they are observe especially in newly industrial country such as Korea and Singapore.
Based on Bon (1994) the share of construction sector in GDP of economic development is based on three stages first stage is LDC (Least Develop Country), second stage is NIC (Newly Industrial Country) and third stage is AIC (Advanced Industrial Country). This stage show the inverted U-shape, the most rapid construction activity is on the LDC stage where the government still need to fulfill the basic infrastructure and the share of construction sector in GDP is low in the advanced economic.
Based on above we can say that Malaysia are in developing country where it’s on their way to reaching the advanced economic, suppose to be the share of construction sector is high compared to other sector but what we observe is the share is low every year and its seems that these sector giving a small contribution to economic
The construction sector in Malaysia gave a lot of positive impact on economic development. With an established a new infrastructure such as roads and skyscrapers it can turn on economic activity in a particular area. The pace of the construction sector in Malaysia can be seen in the year 1965 with a production output of RM801million and in 2003 a total of RM7.52 billion (economic report-current issue). With the increase in construction projects, it will provide substantial employment opportunities so it the government needs to bring in foreign workers to work with the construction.
Announcement of the budget every year give a lot of stress on the construction of a new infrastructure and today we can see many construction projects that is being carried out, especially after the announcement of the 2012 budget. From the government budget in 2012 government spend more budget in improving and repairing of infrastructure such as the implementation of the People’s Housing 1 Malaysia (PRIMA) and the government has allocated RM 443 million for the construction of 15,000 houses under the People’s Housing Programmed (PHP). (Budget 2012)
Even though more and more construction projects, but report from Bank Negara Malaysia showed that the contribution of construction sector to national GDP is small compared to other sectors and the percentage is not stable, on Bank Negara annual report 2011 growth in the construction sector in 2011 grew at a slower rate of 3.5 % over the previous year of 5.1% was due to slower activity in the field of civil engineering and non-residential sub-sector after the completion of maintenance projects and the upgrading and construction of major highways in the second stimulus package. Based on what was stated above it we can see that construction industry play a major role in contributing to the GDP, but when the government present the summary of each sector it show that construction industry remain low in percentage of GDP.
This study aims to assess the relationship between construction sector and economic growth in Malaysia. Specifically this study is to evaluate the long run and short run relationship between construction sector and economic growth in Malaysia.
The Significance of Study
We hope through this research reader can get a full view of the real growth of construction sector by providing the new relevant determinant in measuring construction growth. Since Malaysia under developing country the construction sector is important toward sustainable development and by examine the relationship between construction sector and economic growth we can see how strong these sector in developing country. From this study also can give information to other researcher to study more about the construction sector.
In this chapter we will discuss about previous study on construction activity and economic growth, we also look what kind of variable and method they use. Based on my reading most of study tends to focus on linkage between construction sector and economic growth by taking these two indicators as a variable. Early study mostly looked at the simple correlation between these two variable by letting the construction investment as an explanatory variable for cross-section of developing country, Akintoye and Skitmore(1994).
The study between construction industry and economic growth has been done by many researchers and mostly the result show that there has a strong relationship between construction industry and economic growth. In Malaysia there are few researcher focuses on the relationship between construction sector and economic growth, for example a study done by Khan, R.A., Noor, A. and M. Faris, K. (2010) was to examine the linkage between construction sector and economic growth.. By using Engel Granger econometric approach they found that there is strong causal bi-directional relationship between construction output and aggregate economy during the period 2000-2010. They also has run co-integration test to see whether these variable are co-integrate in the long-run or not, as they expect these variable are co-integrated in long-run.
Similar method also has been used by Lopes, J., Nunes, A. and Balsa, C. (2011) but their data are larger than Malaysian study. Their study was focus on Cape Verde because these country are classified as low-middle income country and its influence them to make a research on construction industry, by taking construction gross value added and gross domestic product (GDP) as variable they found that there was a weak uni-directional relation in long-run between GDP and construction output. For the short-run and medium-run the result didn’t show any effects of the construction growth on GDP growth, they state that there was a problem in collecting data because lack of disaggregate data on subsectors of the construction industry, due to this problem its complicate the analysis.
From the Cape Verde cases in show that the trend of construction growth are following the general economic situation because of the income level in that country furthermore this country were new in newly industrial country(NIC) stages and there are lot of improvement need to be done to boost the construction sector and economic growth. The relationship between construction industry and economic growth in India show different result compared with Cape Verde even though they are in the same stage of NIC. This study done by Mallick, H. and Mahalik, M.K. (2008), by using real growth rate, construction sector growth, total capital and other relevant variable that might influence the economic growth they find out that the impact of construction sector was low or blurred, but once they drop the capital stock variable the construction sector emerges as significant determinant of GDP. Other variable that are include which is interest rate and non-food bank credit give no significance role in GDP.
What we found from the Indian case the author use Auto Regressive Distribution Lag (ARDL) approach to examine the short-run con-integration and the result show that construction sector and capital stock were significantly influence the economic growth, moreover the construction sector growth rate are higher than capital stock growth rate.
Other findings done by James M. W. Wong, Chiang, Y.H. and Thomas, S.NG.(2008) show that construction output especially infrastructure sector will lead to economic growth of Hong Kong but not vice versa. They also find the construction sector had change the Hong Kong economic from newly industrializing country (NIC) to advance industrialize country (AIS). This shows that construction activity can influence the economic growth by providing a physical capital to other sector.
Ramachandra (2006) state that the construction in capital formation causes GDP and not vice versa in Sri Lanka cases, this result same with the James M. W. Wong, Chiang, Y.H. and Thomas, S.NG.(2008) studies, but the authors also try to use policy archetypes and input-output analysis. The result shows that there has significance link between economic growth, policy regime and construction growth. Slow economic growth and construction growth occur when policies are under interventionist cluster, for non-interventionist it could contributed to high performance in economy and construction sector. For input-output analysis it shows that construction sector has significance backward and forward linkages with other forty-eight sector. Ofori(1990) state that the construction sector actually provides a backward and forward linkage to the other economic sector, this show that construction industry play a crucial role to boost the growth of other sector.
Mostly early previous study only concentrates at the simple correlation between construction sector and economic growth, most of them found a positive correlation between these two variables. By moving step forward Chang, T. and Nieh, C.C,(2004) make a study in Taiwan using four variable. Using Johansen (1988)and Johansen and Juselius (1990) approach for co-integration they found that real GDP, real investment in construction activity, real government expenditure and real private consumption expenditure are co-integrated with vector one. Other result by using Granger-causality test shows that the existence of unidirectional causality running from construction activity to economic growth.
Similar finding with Khan, R.A,(2006), their research arise from problem face in Pakistan where the construction share to GDP was very low compared with other sector but its share of the employment labor force was larger. Based on Field, B. and Ofori, G. (1988) the construction industry is regarded as essential and highly visible contributor to the process of growth but if we look again in Pakistan cases it seem contradict with that. Using Granger-causality test its shows that there is strong causal relationship between economic growth and construction sector of Pakistan, the construction flow precedes GDP while GDP doesn’t precede construction flow. This classified as uni-directional causal relationship between construction sector and economic growth. The author also concludes that the aggregate economy of Pakistan is influenced by the construction activity.
In this chapter researcher tells the type of data used, source of data, the model used and the scope of the study. Explanation of the econometric method used is important so that researchers can give an initial overview of what is to be analyzed. The data obtained should also be listed in order to show the variables that will be used. In this study researchers using secondary data because the study need to refer back the trend of growth in construction sector and also including some other variable, by using the secondary data it will facilitate the researcher to see how the construction sector in the past and will assist researchers to estimate the state will come through the econometric analysis
Data Collection and Sample
This research is using a time series data and the data range is 30 years from year 1980 to 2010. Some of the data is not available because there are not survey had been conducted during that year and to fix the data we take the average value from the past year and the next year of the current years.
Data collection is important to conducts an analysis, the source of data gathered as below:
Department of Statistic, Malaysia. Construction Sector.
Department of Statistic, Malaysia. Services Sector.
Department of Statistic, Malaysia. Manufacturing Sector.
Economic Planning Unit. Latest Economic indicators.
Economic Planning Unit. National Account.
2.3 Model Specifications
To see a relationship between construction sector and economic growth the researcher will use a co-integration test to see whether this variable has a long run relationship or vice versa in case of Malaysia. Thus the basic model could be written as;
α : Intercept term SCgr : Growth in services sector
GDPgr : Growth of Malaysian economy POP : Population
CSgr : Growth in construction sector EX : Export
MSgr : Growth in manufacturing sector
The error term is donates ast which is the other variable that are not included in this model are explained in error term. Economic growth in Malaysia (GPD) are set as independent variable, in this model we use growth in manufacturing and services sector because their share in GDP is the most highest compared with other sector. By including this sector we can make comparison on how strong their relationship in GDP compared with construction sector. This model also includes a control variable which is population and export that effect the Malaysia GDP.
The purpose we added many variable other than construction sector growth because we want to how far the construction sector influence the economic growth compared to other variable. This kind of concept has been done by Mallick, H. and Mahalik, M.K. (2008), and Chang, T. and Nieh, C.C,(2004) but their variable are choose based on their role in economic growth at their country.
In this chapter the researcher use autoregressive distribution lag (ARDL) framework by Pesaran and Shin (1995, 1999). Based on Pesaran et al. (2001) there has a three validation in using bound test, first is the relationship of variable can be measure by using OLS when the order in ARDL model has been recognized. Second is the mixture of I(0) and I(1) variable are allowed in bound test as a regressor. Third is this approach is applicable for small sample size (Pesaran et al., 2001). Compared with conventional approach by Johansen (1998) and Johansen and Juselius (1990), the ARDL approach gives a lot of advantage. The equations use in ARDL approach as below.
From the above equation the first part with β1, β2, β3 and β4 represents the long-run relationship and the parameters ρ1, ρ2, ρ3 and ρ4 represent the short-run relationship with sign is first difference operator and n is optimal lag length. The above model will be estimated using the ARDL bound test to test the cointegration between construction sector and economic growth. The bound test is based on Wald of F-statistic, this test has non-standard distribution. There are two set of critical values to test for cointegration introduce by Pesaran. For the lower critical bound it assume all the variable are I(0), means that there are no cointegration among variables, while the upper bound assume that all variables are I(1) this indicate that there is a presence of cointegration among the variable. The hypothesis of the model as below;
H0: β1 = β2 = β3 = β4 = β5 = β6 = 0 ( no cointegration among the variable)
H1: β1 ≠ β2 ≠ β3 ≠ β4 ≠ β5 ≠ β6 ≠ 0 ( cointegration exist among the variable)
To test the existence of long-run relationship in null hypothesis so the F-test is used. We can reject the null hypothesis if the estimated test statistic exceeds the upper critical value and if the test statistic is below the lower critical value we cannot reject the null hypothesis. Unit root test must be conduct firstly before we use the ARDL co integration approach, the popular unit root test is Augmented Dickey-Fuller test (ADF) (Dickey and Fuller, 1979). Even though in ARDL approach is allow using a mixture of stationary of variable but is necessary to check the stationary of the series to ensure the relationship.
After test for the long-run co integration has been conducted we need to test for the short-run relationship. ARDL error correction model are use to evaluate the relationship in short-run and to evaluate the speed of adjustment between construction sector and economic growth.
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