Panel data models are used when the data is varying across time and cross-sections. In such casing using OLS will have to assume any one of the dimension as constant and other as random, but in reality we cannot assume the country differences to be constant or random. Hence this leads to the concept of […]
Chapter 4 – Fixed and Random Effect Panel Data models in R studio Read More »
AutoRegressive Integrated Moving Average (ARIMA) Models are used to find the unpredictable deviation from the mean portion of the series. And if the data has high frequency then AutoRegressive Conditional Heteroskedasticity (ARCH) or Generalized AutoRegressive Conditional Heteroskedasticity (GARCH) models are used to estimate the volatility of the series.
Chapter 3 – ARIMA – ARCH/GARCH Models using R Studio Read More »
This session details on estimating Stepwise regression in R Studio as a solution to weak multicollinearity.
Chapter 1 – R Studio – Stepwise Regressions Read More »
This session will account to a detailed testing of multicollinearity. This include generation of a scatter plot matrix with correlation values and histograms useful for descriptive statistics. Further there is a wide array of tests including VIF, Tolerence test, |X’X| test etc.
Chapter 1 – R Studio – Detailed Testing of Multicollinearity Read More »
Econistics in proud to announce that Econistics.com has officially initiated sharing econometrics and software packages related tutorials. You can visit the YouTube studio at https://www.youtube.com/channel/UCsfzzsa8ZpuDZSW-SU6ysJg/featured?view_as=subscriber Further we do have instagram page https://www.instagram.com/econistics/ here and twitter handle at @post_econistics
Launching Econistics YouTube Channel Read More »
Todays session is about learning Python, specifically how to import a csv data file and doing some basic data exploration tasks.
Chapter 1 – Python Jupyter – Importing CSV Data Read More »
In this session we are going through a detailed account to assess post regression diagnostics in Cross sectional OLS using R Studio. These tests include Outlier Test, Influential Observations test, Non linearity test, Non normality test, multicollinearity test, heteroskedasticity test, and autocorrelation test
In this video we will be talking about how to estimate simple OLS method in R studio. and learn basic interpretation skills.
Chapter 1 – R Studio – Running Simple OLS for Cross section data Read More »
Welcome to Econistics.com. Today we are discussing how to interpret a descriptive statistics table. Secondly we will be talking about how to make a subset of a data by removing the qualitative variables. And lastly we will be talking about how to make correlation plots and save those plots.
Chapter 1 – R Studio – Making Correlation Plots and Data Subsets Read More »
Welcome to Econistics.com. Today we are discussing how to import an Excel data file into R studio. This import is done using all relevant commands. Further in this session we are learning how to view the data and generating descriptive statistics.
Chapter 1 – R Studio – Reading Data and Doing Descriptive Stats. Read More »