Which 5 assumptions for pooled OLS using first differences are required for FD to be unbiased & consistent?

1. The error terms must have zero mean - This means that the random component of the disturbance is expected to have an average of zero across all observations, ensuring that the model remains unbiased. 2. The error terms must be homoskedastic - This means that the error component of the disturbance must remain constant across all observations of the model, ensuring that there is no heteroscedasticity in the model. 3. The error terms must be uncorrelated - This means that the errors in the disturbance must be independent of the other terms in the model. This allows the model to remain unbiased and consistent. 4. The error terms must be normally distributed - This means that the random component of the disturbance is expected to be normally distributed, this assumption helps the model remain unbiased and consistent. 5. The number of periods must be sufficient - This means that the model must have enough periods in order to ensure that the model remains both unbiased and consistent. If there are too few periods, then the model will not be accurate.