Source: Author’s Computation based on datz extracted from the WDI Than Ananrintnsn annlrroarm nt than teanno nf (4 Source: Author’s Computation based on data extracted from the WDI the variables in the model shows that and become maximized of 0.5% till 2023. Financial efficiency shown in Figure 4.2 fluctuated between 1990 and 2023.It witnessed a record low of 0.45% in 2011 and a record high of 0.65% in 2022. Lastly, financial depths as 4.1.2 Basic Descriptive Statistics Resu before experiencing increase till date. The cointegration models that portray the long run behavior of the variables are estimated using Auto regressive distributive lag (ARDL) model with the specification of both the short and long riin ahart farmea nf ANITIATIAN £rrneaiiita Source: E-views 12, Author’s computation Autocorrelation test result for Growth in Agriculture Model The serial correlation LM test in Table 4.6 shows that growth in agriculture model is free from serial correlation at 5% level. This is represented in the figure below: As shown in Table 4.7, the Cumulative Sum (CUSUM) of Squares line is within the 5% critical value bounds. Therefore, the estimates of the long-run model for
