Making Abundant Natural Resources Work for Developing Economies

is the dependent variable. Thus, it is likely that the causality runs from output to bankcredit (i.e. the ‘demand-following’ view holds) and not the other way round.Table 6: Panel cointegration results (dependent variable is output)No time effectsTime effectspanel v-stat 3.29062* 2.32362**panel rho-stat 2.99823** 2.07107**panel pp-stat 1.78481*** -0.15133panel adf-stat -0.06330 -0.76715group rho-stat 3.28265* 2.94134*group pp-stat -0.17588 -1.89151***group adf-stat -2.06033** -1.43575The figures in parentheses are the t-statisticsFinancial indicator used here is bank credit* rejects the null hypothesis of no cointegration at the 1% level of significance** rejects the null hypothesis of no cointegration at the 5% level of significance*** rejects the null hypothesis of no cointegration at the 10% level of significanceTable 7: Panel cointegration results (dependent variable is bank credit)No time effectsTime effectspanel v-stat 0.07442 -0.76400panel rho-stat 1.04770 0.93788panel pp-stat -3.03874* -3.29792*panel adf-stat -2.13464** -4.33891*group rho-stat 2.44831** 2.43490**group pp-stat -3.35229* -3.01468*group adf-stat -2.67426** -3.24600*The figures in parentheses are the t-statisticsFinancial indicator used here is bank credit* rejects the null hypothesis of no cointegration at the 1% level of significance** rejects the null hypothesis of no cointegration at the 5% level of significance*** rejects the null hypothesis of no cointegration at the 10% level of significanceTable 8 presents the fully modified OLS estimates (FMOLS) of the cointegratingrelationship. The results show that there is a statistically significant negativeassociation between bank credit and the intensity of natural resources.