In pointonjoel/Kenometrics: Support Tools for Econometrics Classes

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Kenometrics

The goal of Kenometrics is to provide a set of functions which allow econometrics students to simply conduct important manipulations and tests.

Installation

You can install the released version of Kenometrics from CRAN with:

install.packages("Kenometrics")

To install the latest development version from GitHub:

install.packages("devtools")
devtools::install_github("pointonjoel/Kenometrics")

Overview

The Kenometrics package enables lecturers and students to teach and implement fundamental econometric techniques. This project has taken many hours; if you find the package useful then please consider donating using the donation badge (linked to PayPal) above. Additionally, if you have a feature you would like to see added then please get in touch with Joel Pointon (and consider donating!). Below is a summary of the functions on offer and how they can be used:

• get_data() A single function to find and source data from a variety of sources (txt, Excel)
• ttest() Conduct a t-test (with a specific hypothesised mean, not necessarily 0)
• chow() Conduct a chow test (it adds an intercept and dummy slope and tests the significance depending on if one is testing for a break in the intercept, slope or both)
• make_ts() Make the data time-series (to allow for lagged variables etc.)
• make_numeric() Make the data of numeric form, to allow to conversion from zoo to numeric (reversing the make_ts function)
• ADF() Conduct an ADF test (and if the data are non stationary, it adds the first-difference to the data frame)
• LRM() Find and test the significance of the long run multiplier

The Kenometrics package takes many existing packages and incorporates them as dependencies, simplifying the existing functions they provide. Dependencies include, but are not limited to: wooldridge, zoo, dynlm, readxl and tseries. Having all of these bundled into one package and harnessed for econometrics means that students can quickly begin putting theory into practice. Without Kenometrics, testing for non-stationary data, for example, can be long-winded and and require multiple packages. However, Kenometrics simplifies the code into one line and includes all other necessary packages. Although, students are encouraged to look into the code, which is written in a simple and intuitive way, to see how they could complete the data manipulations without Kenometrics.

pointonjoel/Kenometrics documentation built on Jan. 24, 2021, 6:05 a.m.