Quantile Regression using STATA

Why Quantile Regression?

1. Provides more complete picture on relationship between Y and X: it allows us to study the impact of independent variables on different quantiles of the dependent variable. Normal regression is based on mean of Y.
2. Robust to outliers in Y observations.
3. Estimation and inferences are distribution-free.

Application of Quantile Regression using Stata:

Panel Technique using STATA

*0. Data preparation stage:

set more off

* Download and open the dataset using Stata: LINK

* To start recording the commands and outputs:

log using Panel_log.log, replace

Tips for Stata

                                                               

Tip 1: Steps for preparing data for Stata (panel format):

If you have data in this format:

Company______Accounts______2013______2014____2015
Petronas         Total Assets         1500           1700         2000
Petronas            EBIT                  750             850          1000

An, you need to transpose the data to make it look like this:

Publication-Quality Tables in Stata

Creating Publication-Quality Tables in Stata

Stata's tables are, in general, clear and informative. However, they are not in the format or of the aesthetic quality normally used in publications. Several Stata users have written programs that create publication-quality tables. This article will discuss esttab (think "estimates table") by Ben Jann. The esttab command takes the results of previous estimation or other commands, puts them in a publication-quality table, and then saves that table in a format you cause use directly in your paper such as RTF or LaTeX. Major topics for this article include creating tables of regression results, tables of summary statistics, and frequency tables.

The estout Package

The esttab command is just one member of a family of commands, or package, called estout. In fact, esttab is just a "wrapper" for a command called estout. The estout command gives you full control over the table to be created, but flexibility requires complexity and estout is fairly difficult to use. The esttab command runs estout for you and handles many of the details estout requires, allowing you to create the most common tables relatively easily. We will also discuss estpost, which puts results like summary statistics in a form esttab can work with. The ability to handle summary statistics and frequencies in addition to regression results is one of the reasons we elected to focus this article on esttab.