STOCK MARKET: RESEARCH METHODOLOGY



CHAPTER THREE
RESEARCH METHODOLOGY
3.1       Model Specification:
            Theoretical framework and model investment functions have been specified using various major theories, particularly, the neoclassical models (Jorgenson, 1967, Tobin, 1969), accelerator models (Koyek, 1954) and the financing theory (Morck, 1990). We shall adopt our model from Mistati (2006), the study of impact of capital market on investment growth in sub-saharan African in which the financing theory is used to incorporate capital market variables into aculerator model. Though the q-theory has been popularly used to link investment and capital market variables. Thus, assuming constant elasticity of substitution (Q) between capital and the variable inputs, we observe the following relation between desired capital stock (K), the expected level of output(Y) and the expected rental cost of capital (C).

Kt           =          aUtCt              -------------------------------------------(1)
∆Kt        =          aUtCt               ------------------------------------------(2)
We then use the conventional capital accumulation identify specified in equation (3) below to define investment(1)
Kt           =          (1-d)Kt            + I1      -----------------------------------(3)
Where a refers to depreciation of capital from equation (3), we obtain
Kt-Kt-1  =  It-dKt-I                  -------------------------------------------(4)
Re-arranging equation (4), assuming d=D and solving for It yields the following expression.
∆Kt  =  It-1      -------------------------------------------------(5)
Substituting (5) into (2) and express the result in log form where lower cases henceforth denote the log form of the variables;
It  =  a+ ∆y                 -----------------------------------------(6)
Equation (6) represents the basic investment function. To account for slow adjustment of the actual capital stock to the desired capital stock, we nest this within a dynamic regression model yielding the following model
It  =  Plt-1  +  l1∆yt  + l2∆yt-1  + Vt  ---------------------------(7)
Where the first two terms on the right hand side are lagged investment and output growth rates, respectively. ∆y represents lagged growth role of capital while Vt capital while Vt captures the individual error components. We proceed to incorporate our capital market variables in the equation below (Pilgril and Schich, 2008, Lynch, 2005, Durham, 2009)
It  =  It-1 + l1∆yt + l2∆yt-1 + l3capital Mt + aoXt+ a1Dt + Vt    --------- (8)
Where capital M represents all the capital market development indicators i.e size of stock market indicators, two liquidity of the stock market indicators, market capitalization and the vector Xt captures other factors influence investment in developing countries and Dt is a country specific vector of dummy variables.
            The model incorporates objectives (1) and (2) simultaneously.
3.2.      Methods of Estimation.
            We shall use the method, Ordinary least Squares (OLS) in the model estimation since the study involves a time series. We shall test for the existence of co-integration between private investment and the right hand side of equation (8). Error correction mode (ELM) estimations would be used to ascertain the short run impact of capital market variables on the growth of private investment and speed of adjustment of investment towards its long-run equilibrium value.
            In a systematic manner, the main features of an econometric analysis are incorporated in the model specification. This research work will employ ordinary least squares (OLS) estimation because of its reliable traits as the bet unbiased estimator. Its error term has a maximum and equal variance. The stochastic term has a zero mean-conditional mean value is zero and normally distributed.
            The ADL model is a highly statistically significant approach to determine the cointegration relation in an annual data samples for validity (Ghatak and Siddiki 2008). Provisions were made to ensure adherence to the principle of parsimony, dynamism and model stimulation. Provisions were also made to ensure numerical accuracy, data stationary and cointegration elimination if cointegration exist sin the model, by the application of Error Correction mechanism (ECM).
3.4       Data Sources
            The data for the study are quarterly data between 1990 to 2010, a period of twenty (20) years. The sources of these data are central Bank of Nigeria, statistical bulletin and Annual Report and statement of account, various years; Stock Exchange Bulletin. The Global Financial Data (www.globalfindata.com), and international financial statistics.
1.         Economic adjustment and investment performances in developing countries. The Nigeria Experience.
2          Stock Market Development and Economic Growth Evidence from Nigeria.
3.         Determinates of rural poverty: Evidences form southeast Nigeria.



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