Question

How can the fixed effects estimator solve problems of endogeneity?what type of endogeneity does it handle, and how?

Answer 1

In purely economic inference, endogeneity is the correlation between the error that occurs in the inferences of data with the variables that lead to the inference. When the parameters in a statistical model are static or fixed, it is called the fixed effect. The fixed effects model states that the quantity and the price of a commodity are correlated. If the per capita quantity of a quantity is regressed, it will result in defining the coefficient of the price which would mean that with an increase or decrease in the price of a commodity, there is an increase or decrease in the per capita of the commodity. This is lead to an increase in the price of the commodity. This gives us the idea that regression is affected by the bias of endogeneity as the variable bias are ommitted in it.Therefore the fixed effects estimator reveals that the bias in the endogeneity suffer from the variable change difference which has to be addressed in order to reach to a clear and justified result of the models of the statistical calculation.

  The bias in the endogeneity has a high probability of leading the inference to incorrect values and inconsistent estimates. This may lead to inaccurate interpretations of the theory or the calculations may become severely misleading. One of the most important effects of such bias is that this may lead to a wrong sign being calculated with the coefficients. This issue is now being deeply investigated and the market experts are trying to get a proper solution to this issue. The sources of endogeneity can be discussed as dynamic endogeneity, simultaneity endogeneity and unobserved endogeneity. All these types of endogeneity are the bias of inference which need proper exercise of static or fixed effects model to calculate the implicit error values which could impact the complete statistical calculation and may lead to wrong values as the answers, thus impacting the whole process of statistical inference.