Skip to content

Econometrics and causal inference plays an important role in technology, particularly in areas such as machine learning and artificial intelligence. In these fields, the goal is often to understand the causal relationships between variables in order to make predictions or decisions.

Notifications You must be signed in to change notification settings

andromeda0505/Econometrics-methods

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

7 Commits
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

Repository files navigation

Econometrics techniques

Econometrics is an empirical of economics that applies mathematical and statistical models with economic theories to understand, explain and measure causality in economic systems, strategic decisions, the tech industry, and business.

Difference-in-Differences

The difference-in-differences method is a quasi-experimental approach that compares the changes in outcomes over time between a population enrolled in a program (the treatment group) and a population that is not (the comparison group). It is a useful tool for data analysis.

Regression Discontinuity Design

Regression Discontinuity Design (RDD) is a quasi-experimental evaluation option that measures the impact of an intervention, or treatment, by applying a treatment assignment mechanism based on a continuous eligibility index which is a variable with a continuous distribution.

Propensity Score Matching

The propensity score is the probability of treatment assignment conditional on observed baseline characteristics. The propensity score allows one to design and analyze an observational (nonrandomized) study so that it mimics some of the particular characteristics of a randomized controlled trial. In particular, the propensity score is a balancing score: conditional on the propensity score, the distribution of observed baseline covariates will be similar between treated and untreated subjects.

Survival Analysis

Survival Analysis is a field of statistical tools used to assess the time until an event occurs. As the name implies, this “event” could be death (of humans with a particular disease process, crops or plants under certain conditions, animals, etc.), but it also could be any number of alternatives (the failure of a structural beam or engineering component, the reoccurrence of a disease process, customer churn rate, etc.).

License

Creative Commons License
Data Exploration and Numerical Experimentation is licensed under a Creative Commons Attribution 4.0 International License.

About

Econometrics and causal inference plays an important role in technology, particularly in areas such as machine learning and artificial intelligence. In these fields, the goal is often to understand the causal relationships between variables in order to make predictions or decisions.

Resources

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published