This study set out to investigate the impact of the business environment on economic growth in Africa. In this regard, the current study carefully selects two estimation techniques based on their relevance to the study’s objectives and their peculiarities. The study adopted the Newey West Regression Estimator and the Quantile Regression techniques for the estimations in a rather stepwise manner. In the words of Koenker and Bassett (1978), data sets with variables that are not normally distributed and have a nonlinear relationship with the independent variables may produce biased estimates. One possible method to counteract this problem is to adopt the quantile regression technique (Wooldridge, 2020). The main strength of quantile regression is that it facilitates the relationships between variables outside the mean. This method also ensures the robustness of the results. Similarly, most macroeconomic panel datasets face the problems of autocorrelation and heteroskedasticity, especially when the panel model has a lagged value. One appropriate model to handle such data is to use an estimator called the Newey-West estimation strategy (Stock & Watson, 2020). According to Koenker and Bassett (1978), the quantile regression can be specified as the following:
\({y}_{it}={x}_{it}^{i}{\alpha }_{\phi }+{u}_{it} , with {Quant}_{\phi } {y}_{it}|{x}_{it }\) =\({x}_{it}^{i}{\alpha }_{\phi }\)...............................(1)
where \({y}_{it}\)is the growth rate, \({x}_{it }\) is a vector of regressors, \(\alpha\) is the vector of parameters to be estimated, and \(u\) is a vector of residuals. \({Quant}_{\phi } {y}_{it}|{x}_{it }\) denotes the\(\phi\) conditional quantile of \({y}_{it}\) given \({x}_{it }\).
Following the general form in model 1, we specify four equations in a stepwise manner to establish the linkages between the constituents of the business environment: business disclosure index, the cost of business startup, the total number of days required to start a business, and lending interest rate, respectively, and economic growth in Africa as in models 2, 3, 4, and 5, respectively.
\({lnGDP}_{it}=\alpha +{\beta }_{1}BEDI+{\beta }_{2}{INF}_{it} + {\beta }_{3}{lnEXR}_{it}+{\beta }_{4}{FDI}_{it}+\) \({u}_{it}\) …………………2
\({lnGDP}_{it}=\alpha +{\beta }_{1}CBST+{\beta }_{2}{INF}_{it} + {\beta }_{3}{lnEXR}_{it}+{\beta }_{4}{FDI}_{it}+\) \({u}_{it}\) …………………3
\({lnGDP}_{it}=\alpha +{\beta }_{1}TRBS+{\beta }_{2}{INF}_{it} + {\beta }_{3}{lnEXR}_{it}+{\beta }_{4}{FDI}_{it}+\) \({u}_{it}\) …………………4
\({lnGDP}_{it}=\alpha +{\beta }_{1}LIR+{\beta }_{2}{INF}_{it} + {\beta }_{3}{lnEXR}_{it}+{\beta }_{4}{FDI}_{it}+\) \({u}_{it}\) ……………….. .…5
Where \(BEDI\)=Business Extent Disclosure Index, \(CBST\) = Cost of Business Start Up, \(TRBS\) = Total Number of Days required to Startup Business, \(LIR=Lending Interest Rate,\) \(INF\)= Inflation, Consumer Prices (annual %) \(lnEXR\)= Log of Official Exchange Rate, and FDI = Foreign Direct Investment, Net inflows (% of GDP).
Similarly, the generic form of the Newey West Regression equation is given as the following:
$${y}_{it}={x}_{it}^{i}{\alpha }_{\phi }+{u}_{it}$$
6
...............................
where \({y}_{it}\)is the growth rate, \({x}_{it }\) is the predictor variable, \(\alpha\) parameters to be estimated, and \(u\) is the error term.
Following the specification in model 6, the operational form of the regression equations set out to model the nexus between the components of the business environment: business disclosure index, the cost of business startup, the total number of days required to start a business, and the lending interest rate, respectively, and economic growth are specified in models 7, 8, 9, and 10, respectively.
\({lnGDP}_{it}=\alpha +{\beta }_{1}BEDI+{\beta }_{2}{INF}_{it} + {\beta }_{3}{lnEXR}_{it}+{\beta }_{4}{FDI}_{it}+\) \({u}_{it}\) …………………7
\({lnGDP}_{it}=\alpha +{\beta }_{1}CBST+{\beta }_{2}{INF}_{it} + {\beta }_{3}{lnEXR}_{it}+{\beta }_{4}{FDI}_{it}+\) \({u}_{it}\) …………………8
\({lnGDP}_{it}=\alpha +{\beta }_{1}TRBS+{\beta }_{2}{INF}_{it} + {\beta }_{3}{lnEXR}_{it}+{\beta }_{4}{FDI}_{it}+\) \({u}_{it}\) …………………9
\({lnGDP}_{it}=\alpha +{\beta }_{1}LIR+{\beta }_{2}{INF}_{it} + {\beta }_{3}{lnEXR}_{it}+{\beta }_{4}{FDI}_{it}+\) \({u}_{it}\) ……………….. .…10
Where \(BEDI\)=Business Extent Disclosure Index, \(CBST\) = Cost of Business Start Up, \(TRBS\) = Total Number of Days required to Start up Business, \(LIR=Lending Interest Rate,\) \(INF\)= Inflation, Consumer Prices (annual %) \(lnEXR\)= Log of Official Exchange Rate, FDI = Foreign Direct Investment, Net inflows (% of GDP)