Abstract Construction sector and construction activities are considered to be one of the major sources of economic growth, development and economic activities. Construction and engineering services industry play an important role in the economic uplift and development of the country.
Don't use plagiarized sources. Get Your Custom Essay on
Impact of the Construction Industry to Its Nation
just from $13,9 / page
It supplements the foreign exchange earnings derived from trade in construction material and engineering services. Unfortunately construction sector is one of the most neglected sectors in Kenya. Although the construction sector has only a 2. 3 percent share in GDP, its share of the employed labor force was disproportionately large at 6. 1 percent in FY07. The construction sector is estimated to have grown by 17. 2 percent in 2006-07 as against 5. 7 percent of last year.
The higher demand for construction workers is also reflected in a continued double-digit rise in their wages since FY05. Their wages increased by 11. 1 percent in FY07. Keywords: Construction Sector, GDP, Causal Relationship, Co-integration. 1. Introduction The construction industry plays an essential role in the socio economic development of a country. The activities of the industry have great significance to the achievement of national socio-economic development goals of providing infrastructure, sanctuary and employment.
It includes hospitals, schools, townships, offices, houses and other buildings; urban infrastructure (including water supply, sewerage, 280 drainage); highways, roads, ports, railways, airports; power systems; irrigation and agriculture systems; telecommunications etc. It deals with all economic activities directed to the creation, renovation, repair or extension of fixed assets in the form of buildings, land improvements of an engineering nature. Besides, the construction industry generates substantial employment and provides a growth impetus to other sectors through backward nd forward linkages. It is, essential therefore, that, this vital activity is nurtured for the healthy growth of the economy. The main purpose of this study is to see whether growth in construction industry actually caused the economic increase or, alternatively, did economic expansion strongly contribute to construction growth instead? 1. 1 Global Distribution of Construction Output and Employment: Globally, construction industry is regarded as one of the largest fragmented industry. An estimate of annual global construction output is probably closer to U.
S $ 4. 5 trillion in 20041. The construction industry is also a prime source of employment generation offering job opportunities to millions of unskilled, semi-skilled and skilled work force. Global picture of construction output and employment in developing and developed countries can be seen in table -1 below. It can be seen from the table-1 that total construction output worldwide was estimated at just over $3,000 billion in 1998. Output is heavily concentrated (77 per cent) in the high income countries (Western Europe, North America, Japan and Australasia).
The contribution of low and middle income countries was only 23 % of total world construction output (ILO Geneva2001). The data in employment situation table 2 tells a rather different story so far as employment is concerned. It can be seen that there was an excess of 111 million construction workers worldwide in 1998 and most of them were in the low- and middle-income countries. The distribution of construction employment is, in fact, almost the exact reverse of the distribution of output. The high-income countries produce 77 per cent of global construction output with 26 per cent of total employment.
The rest of the world (comprising low- and middle-income countries) produces only 23 per cent of output but has 74 per cent of employment (ILO Geneva2001). ------------------------------------------------ 1 Source: Engineering News Record, USA 281 1. 2 Construction Industry in Kenya; The housing and construction sector in Kenya plays an important role in developing aggregate economy and reducing unemployment. It provides substantial employment opportunities as it contributes through a higher multiplier effect with a host of beneficial forward and backward linkage in the economy.
The sector through linkages affects about 40 building material industries, support investment and growth climate and helps reduce poverty by generating income opportunities for poor household. It provides jobs to about 5. 5 per cent of the total employed labor force or to 2. 43 million persons, (2. 41 million male and 0. 2 million female) during 2003- 04 (Economic Survey 2004-05) Unfortunately the construction sector is one of the most neglected sectors in Kenya. It is at low ebb, which can be judged from the fact that per capita consumption of cement in Kenya is one of the lowest among the developing countries. 2.
Literature Review: Construction in any country is a complex sector of the economy, which involves a broad range of stakeholders and has wide ranging linkages with other areas of activity such as manufacturing and the use of materials, energy, finance, labor and equipment. The contribution of construction industry in the aggregate economy of a country has been addressed by a number of researchers and valuable literature available on the linkage between construction sector and other sectors of the economy. Several researchers conclude that the construction sector has strong linkages with other sectors of the national economy.
Hirschman (1958) first defined the concept of ‘linkage’ in his work The Strategy of Economic Development. He emphasized the significance of ‘unbalanced’ growth among supporting sectors of the economy as opposed to a balanced development of all interrelated economic activities (Lean, 2001). Park (1989) has confirmed that the construction industry generates one of the highest multiplier effects through its extensive backward and forward linkages with other sectors of the economy. It is stated that the importance of the construction industry stems from its strong linkages with other sectors of the economy (World Bank, 1984).
However, interdependence between the construction sector and other economic sectors is not static (Bon, 1988; Bon, 1992). Strout (1958) provided a comparative inter-sectoral analysis of employment effects with an emphasis on the construction. Ball (1965) and Ball (1981) addressed the employment effects of the construction sector as a whole. Many studies (Fox, 1976; Bon and Pietroforte, 1993; Pietroforte and Bon, 1995) use the strong direct and total linkage indicator to explain the leading role of the construction sector in the national economy. . 1 Construction Industry and National Economy: Construction activities and its output is an integral part of a country’s national economy and industrial development. The construction industry is often seen as a driver of economic growth especially in developing countries. The industry can mobilize and effectively utilize local human and material resources in the development and maintenance of housing and infrastructure to promote local employment and improve economic efficiency.
Field and Ofori (1988) stated that the construction makes a noticeable contribution to the economic output of a country; it generates employment and incomes for the people and therefore the effects of changes in the construction industry on the economy occur at all levels and in virtually all aspects of life. This implies that construction has a strong linkage with many economic activities, and whatever happens to the industry will directly and indirectly influence other industries and ultimately, the wealth of a country.
Hence, the construction industry is regarded as an essential and highly visible contributor to the process of growth (Field and Ofori, 1988). The significant role of the construction industry in the national economy has been highlighted by Turin (1969). On the basis of cross section of data from a large number of countries at various levels of development, Turin (1969) argued that there is a positive relationship between construction output and economic growth. Furthermore, as economies grow construction output grows at a faster rate, assuming a higher proportion of GDP.
In a recent article Drewer returns to the ‘construction and development’ debate. Using data for 1990 similar to that assembled by Turin for 1970, he shows that global construction output has become increasingly concentrated in the developed market economies. He goes on to argue that this new evidence does not support Turin’s propositions. The issue of concern here is whether the construction sector and the aggregate economy are fragmented or mutually dependent, and whether construction activity contributes to economic growth and /or vice versa.
Studies have shown that the interdependence between the construction sector and other economic sectors is not static but changes as the nation’s economy grows and develops 2. 2 Tools for Measuring Strength of Linkage: Two analytical tools, which most widely used for measuring the strength of the linkage, sector vise economic performance and production interdependence and to analyze economic relationships, are: (i) Leontief’s (1936) Input–output analysis and ii) The new econometric methodology developed by Engle and Granger Bon (1988) is one of the few researchers who applied the concept of Leontief input-output matrix to the construction industry. He considered the input–output technique to be ideal, for it provides a framework with which to study both direct and indirect resource utilization in the construction sector and industrial interdependence. He also found that the input–output tool can be used for studies of the construction sector in three broad aspects: employment creation potential, role in the economy, and identification of major suppliers to the construction industry.
Rameezdeen et al, (2006), also used input283 output table to analyze the significance of construction in a developing economy and its relationships with other sectors of the national economy. With the popularity of the new econometric methodology presented by Engle and Granger, many modeling studies related to economic and financial issues have applied this new technique to analyze economic relationships. Green (1997) applied the Granger causality test to determine the relationship between GDP and residential and non-residential investment, using quarterly national income and gross domestic product data for the period 1959–1992.
His results showed that residential investment causes, but is not caused by GDP, while non-residential investment does not cause, but is caused by GDP. He concluded that housing leads and other types of investment lag the business cycle (Lean, 2001). Tse and Ganesan (1997) is also used the same econometric technique (Granger causality test) to determine the causal relationship between construction flows and GDP using quarterly Hong Kong data from 1983 to 1989. They found that the GDP leads the construction flow and not vice versa. 2. Research Objective: The objective of the present paper is to examine the specific lead lag relationships between construction flow and gross domestic product (GDP). For obtaining this goal we will use annual data for construction sector and economic GDP of Kenya from 1950 to 2005. Granger causality methodology is commonly applied to investigations on the relationships among money supply, stock prices and inflation, but very few researchers tested the linkages between the construction sector and the aggregate economy using this method.
Here we will use the same approach to identify whether there is a unidirectional or bidirectional causal relation between construction sector and economic growth in the case of Kenya. In addition, we will use unit root tests to examine the stationarity of both series (construction sector and GDP) and co integration test will use to find out the existence of long run relationship between these variables. It is a powerful concept, because it allows us to describe the existence of an equilibrium or stationary relationship among two or more time series, each of which is individually non- stationary. . Methodology: A simple statistical and econometric analysis will be used to know the general properties of data and to see the relationship among variables of interest like construction sector (LCNS) and aggregate economy of Kenya (LGDP). This study uses time series annual data (1950 to 2005) to demonstrate the causal relationship between construction sector and GDP in Kenya. A time series is a sequence of values or readings ordered by a time parameter, such as hourly and yearly readings.
When time series data is used for analysis in econometrics, several statistical techniques and steps must be undertaken. First of all unit root test has been applied to each series individually in order to provide information about the data being stationary. Non-stationary data contains unit roots. The existences of unit roots make hypothesis test results unreliable. If the data are non-stationary, then frequently stationarity can be achieved by first differencing (Granger and Newbold, 1986) that is, obtaining the differences between the current value and that of the previous period.
Once stationarity is determined, structural modeling of the variables or testing for causality can take place. The causality test aims to verify whether historical variations of the construction data follow or precede the GDP. To test for the 284 existence of unit roots and to determine the degree of differences in order to obtain the stationary series of LGDP and LCNS, Augmented Dickey- Fuller Test (ADF) has been applied. If the time series data of each variable is found to be non-stationary at level, then there may exists a long run relationship between these variables, LGDP and LCNS.
Johansen’s (1988) co-integration test has been used in order to know the existence of long run relationship between these variables. A series is said to be integrated if it accumulates some past effects, such a series is non-stationary because its future path depends upon all such past influences, and is not tied to some mean to which it must eventually return. To transform a co-integrated series to achieve stationarity, we must differentiate it at least once. The number of times the data have to be differenced to become stationary is the order of integration.
If a series is differenced d times to become stationary, it is said to be integrated of order I(d). However, a linear combination of series may have a lower order of integration than any one of them has individually. In this case, the variables are said to be co-integrated. The following section presents the results of the simple descriptive statistical analysis and then unit root analysis to study the stationarity of GDP and construction flow. Accordingly, we employ Granger causality methodology to investigate the lead lag relationships between the construction flow and the GDP. . 1 Data and Descriptive Statistical Analysis: The annual data for the period 1950 to 2005 is being used for empirical analysis. Construction industry flows (LCNS) and Gross Domestic Product (LGDP) data in local currency is employed to analyze the dynamic relationship between GDP and construction sector. All the variables are expressed in natural logarithms so that they may be considered elasticity of the relevant variables. We examine the contemporaneous correlation and check for the evidence of Granger causality between these two variables.
Table-3 presents summery statistic of the data and table- 4 tell us that there is a strong correlation between construction sector and GDP of Kenya during 1950 to 2005. Annual observations of GDP and construction sector are taken from Handbook of Statistics of Kenya Economy, 2005 and various issues of Economic Survey of Kenya. Table 3 Descriptive statistics LCNS LGDP Mean 8. 605299 11. 98993 Median 8. 996238 11. 90110 Maximum 11. 87699 15. 62865 Minimum 4. 976734 9. 126524 Std. Dev. 2. 184803 2. 082374 Skewness -0. 140903 0. 195506 Kurtosis 1. 651252 1. 664931
Jarque-Bera 4. 429918 4. 515697 Probability 0. 109158 0. 104575 Observations 56 Apparently as the government is geared to enhance rural development in its development agenda, the construction industry faces the daunting task to be part of the development philosophy. The construction industry has to ensure that it has the capacity to deliver development projects as per the needs of the government and in the time scale specified. Many a development projects are in the pipeline, most notable, road projects, schools, police and teachers’ houses, boreholes, among many others.
The construction industry would add value to the country’s development agenda through successfully undertaking the said projects. Certainly, the construction industry loses credibility, trust and reputation in the eyes of the publics if projects it undertakes do not live to the expectations of the people. The government’s rural development project could further spur the growth of indigenous construction companies which will in the end trickle-down economic benefits to the country and the citizens.
The mushrooming of indigenous construction firms with capacity to handle large scale jobs will save the country from losing forex as most projects will be handled locally, hence requiring no need for forex to pay international construction firm. This could certainly write a new chapter in the history of the construction industry in the country. As the small construction firms will be developing they will certainly be competing for construction jobs in other countries within Africa and possibly beyond. This could make the construction industry a reliable partner in bringing into the country the required forex.
The exposure of the construction industry abroad could as well play the ambassadorial role of marketing services that Malawi can offer in Africa and beyond. If one sector successfully storms the international market, other sectors stand an easy chance as they actually ride on the success of the pioneer service provider. References Anaman K. A and Amponsah. C, (2007). Analysis of the causality links between the growth of the construction industry and the growth of the macro economy in Ghana, Institute of Economic Affairs, Accra, Ghana Ball, C. M. 1965) Employment effects of construction expenditures, Monthly labour Review, 88, 154- 158. Ball, R. (1981) Employment created by construction, expenditures, Monthly labour Review, 104, 38-44. Bon, R. (1988). Direct and indirect resource utilization by the construction sector: the case of the USA since World War II, Habitat International, 12(1), 49–74. Bon, R. (1992). The future of international construction: secular patterns of growth and decline. Habitat International, 16(3), 119–28 Census and Statistics Department of HKSAR (1985–2002) Hong Kong Monthly Digest of Statistics, Census and Statistics Department of HKSAR, Hong Kong.
Bon, R. and Pietroforte, R. (1990) Historical comparison of construction sectors in the United States, Japan, Italy, and Finland using input-output tables, Construction Management and Economics, 8, 233- 247. Bon, R. and Pietroforte, R. (1993) New construction versus maintenance and repair construction technology in the USA since World War I. , Construction Management and Economics, 11, 151–62. Bon, R. , Birgonul, T. and Ozdogan, I. (1999) An input– output analysis of the Turkish construction sector, 1973– 1990: a note. Construction Management and Economics, 17, 543–51.
Chen, J. J. (1998) The characteristics and current status of China’s construction industry, Construction Management and Economics, 16, 711-719. Dickey, D. A. and Fuller, W. A. (1979) Distributions of the estimators for autoregressive time series with a unit root. Journal of the American Statistical Association, 74, 427- -31 Drewer, S (1997) Construction and development: Further reflections on the work of Duccio Turin. Proceedings of the First International Conference on Construction Industry Development, Singapore 9- 11 December. Engle, R. F. and Issler, V. 1993) Estimating Sectoral Cycles Using Co integration and Common Features, Working Paper No. 4529, National Bureau of Economic Research. Field, B. and Ofori, G. (1988) Construction and economic development – a case study. Third World Planning Review, 10(1), 41–50. Fox, L. P. (1976) Building construction as an engine of growth: an evaluation of the Columbian development plan. Ph. D. dissertation, The University of North Carolina. Granger, C. W. J. and Newbold, P. (1986) Forecasting Economic Time Series, Academic Press, Orlando, FL. Granger, C. W. J. and Newbold, P. (1974) Spurious regressions in econometrics.
Journal of Econometrics, 2, 111–20. Green, R. K. (1997) Follow the leader: how changes in residential and non-residential investment predict changes in GDP. Real Estate Economics, 25(2), 253–70. Harris, R. (1995) Using Cointegration Analysis in Econometric Modeling, Prentice-Hall, Englewood Cliffs, NJ. Hassan. S. A. (2002) Construction Industry. (Kenya) published by Economic Review 2002. Hillebrandt, P. (1985) Analysis of the British Construction Industry, Macmillan, London. Hirschman, A. O. (1958) The Strategy of Economic Development, Yale University Press, New Haven, CT.
Hua. B. G. (1995). Residential construction demand forecasting using economic indicators: a comparative study of artificial neural networks and multiple regression School of Building and Estate Management, National University of Singapore ILO Geneva (2001), The construction industry in the twenty first century: Its image, employment prospects and skill requirements, International Labor Office Geneva Lean, S. C
Remember. This is just a sample.
You can get your custom paper from our expert writers