Some of the most popular models used in Data Analysis imply the use of the so-called “Black Box” approach. Regarding the simplest interpretation one can give in this context, it depends on the inputs and outputs that a certain model can deliver in terms of prediction power. If econometrics is thought to estimate population parameters, …
In this article, we will follow Woolridge (2002) procedure to estimate a set of equations with nonlinear functional forms for panel data using the two-stage least squares estimator. It has to be mentioned that this topic is quite uncommon and not used a lot in applied econometrics, this is due that instrumenting the nonlinear terms …
As we saw in other econometric blogs of M&S Research Hub, the use of logarithms constitutes a usual practice in econometrics, not only for the problems that can be derived from overusing them, but also it was mentioned the advantage to reduce the Heteroscedasticity -HT- (Nau, 2019) present in the series of a dataset, and …
A usual practice while we’re handling economic data, is the use of logarithms, the main idea behind using them is to reduce the Heteroscedasticity -HT- of the data (Nau, 2019). Thus reducing HT, implies reducing the variance of the data. Several times, different authors implement some kind of double logarithm transformation, which is defined as …
Taking Logarithms of Growth Rates and Log-based Data. Read More »
A discussed solution in order to accomplish the normality assumption in regression models relates to the correct specification of a Data Generating Process (Rodríguez Revilla, 2014), the objective here is to demonstrate how functional form might influence the distribution of the residuals in a regression model using ordinary least squares technique. Let’s start with a …
The impact of functional form over the normality assumption in the residuals Read More »
