Unit Root Test. ▇▇▇▇▇▇▇-▇▇▇▇▇▇ Unit root test approach was used to establish the integration order of each of the research. Hence, the results of the tests for each of the variables in models with intercept are presented in Table 1 at both logarithmic their first difference levels. H0: b = 0; Ha: b > 0 Variables Critical value @5% Philips ▇▇▇▇▇ test statistics Remarks Order of Integration lnRGDP -3.052169 -4.092715 Stationary I(0) lnGDPIS -3.052169 -4.905193 Stationary I(0) lnINSTA -3.052169 -1.248354 Non-stationary Nil lnINSTC -3.052169 -0.349777 Non-stationary Nil Unit root test result at first differences Variables Critical value @5% Philips ▇▇▇▇▇▇ test statistics Order of Integration lnRGDP - - Stationary I(0) lnGDPIS - - Stationary I(0) lnINSTA 3.065585 -3.073419 Stationary I(1) lnINSTC 3.065585 -9.445244 Stationary I(1) Notes: *Denotes significance at the 5% level and the rejection of the null hypothesis of non-stationarity. Table 2 reveals that the variables of interest are mixture of order I(0) and I(1) i.e at logarithmic level, RGDP and RGDPIS were stationary while INSTA and INSTC were stationary at first difference. This is a prerequisite for employing ARDL as an estimation technique according to ▇▇▇▇▇▇▇▇ and ▇▇▇▇ (2001).
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Sources: Insurance Sector Development and Economic Growth Analysis, Research Study, Insurance Sector Development and Economic Growth Analysis