Econometrics

The budget constraints in the microeconomic approach

Following the last post which gave an example to model the Cobb-Douglas utility function regarding microeconometrics, we need to provide an important aspect related to the behavior of the consumer. That is the budget constraint (referred to as a monetary linear constraint) which limits the number of goods that the consumer can buy and use …

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A brief example to model the Cobb-Douglas utility function using Stata.

Regarding microeconometrics, we can find applications that go from latent variables to model market decisions (like logit and probit models) and techniques to estimate the basic approaches for consumers and producers. In this article, I want to start with an introduction of a basic concept in microeconomics, which is the Cobb-Douglas utility function and its …

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Robust Modeling of Policy Changes: Difference in Difference (DiD)

The difference in Difference (DiD) is a popular method in empirical economics and has important applications in other social sciences as well. DID is a quasi-experimental design that uses panel data to estimate the effects of specific intervention or treatment (such as policy changes, new laws, social program implementation) on outcomes over time and between …

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Taking Logarithms of Growth Rates and Log-based Data.

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 …

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The impact of functional form over the normality assumption in the residuals

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 …

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