I conducted research on the effects of natural disasters on credit growth, using 2008-2022 panel data. All of my independent variables are represented in the lag, and I also include the lag dependent variable as a regressor. When comparing the coefficient of lag dependent variable between GMM, OLS, and FEM, with GMM are always greater than FEM and OLS. Is there an explanation for this condition? Is there any treatment that can be done so that the GMM value is between OLS and FEM?
GMM, OLS, and FEM coefficients may differ depending to assumptions and model parameters. GMM and FEM assume distinct relationships between independent variables and unobserved heterogeneity, while OLS assumes no correlation. Reducing endogeneity and getting the GMM coefficient closer to the OLS and FEM coefficients, add covariates or re-specify the model. An Instrumental Variables technique could discover an exogenous variable that impacts credit growth but is uncorrelated with the error term. A dynamic panel model explicitly models lag dependability and offers additional flexibility in the correlation pattern between independent variables and unobserved heterogeneity.
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