This article is updated in 2022 with more online resources added at the end of this article.
One-stop solution for Econometrics for a beginner. Here, one can find Econometrics Software such as STATA, R, Eviews along with information on Econometrics Models such as Panel Data Models, Probit and Logit Models, Time Series ARIMA Model. You can learn the concepts as well as the courses, software downloads are self-paced and FREE.
This courseware provides a self-paced course on Econometrics. This course was open in 2017 and it provides only static material such as lecture notes, examination notes, and problem sets without solution provided and no visual aid for use of statistical software found.
This website has audio-visual resources for practical use of STATA, Excel, and EVIEWS. Very helpful for beginners in data analysis and Econometrics. Its YouTube channel under the same name is frequently updated, with a great repository of resources for learning how to handle data, and econometrics models. You must be familiar with university statistics and algebra.
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This course offered by Erasmus University Rotterdam, in 2018, in the Coursera platform teaches how to translate data into models to do forecasts and make decisions. This course has an average rating of 4.6 by the users and it takes about 7 weeks of study, 4-8 hours per week. If you can’t take paid classes, you can audit the course to learn it for free. Taught by the faculty of Econometric Institute, Erasmus University, this course is one of a kind.
This is a four-week course, by Duke University, which is less than 9 hours with video tutorials, graded assignments, R lab, and a project that interests you. One of the best resources to learn how to use Linear Regression and R software. Make full use of discussion forums, message boards to clear your doubt.
This is a 6-week course, by the State University of New York, which requires your commitment of fewer than 24 hours in total, involves course material, discussion forums, quizzes, and project assignments. You should take the quiz at the end of each week to test your knowledge. The six modules consist of the following:
(i) basics of statistics (ii) Visualizing Time Series, and beginning to model time series (iii) Stationarity, MA(q) and AR (q) processes (iv) AR(p) process, Yule-Walker equations, and PACF (V) Akaike Information Criterion, Mixed Models, and Integrated Models, and (vi) Seasonality, SARIMA, Forecasting.
Offered by Scott E. Page, from the University of Michigan, this course demands 24 hours commitment. Self-paced this course is divided into 12 weeks. You can learn about decision models, tipping point and economic growth, diversity and Markov process, and Lapyunov function in this course. To join the course click here
1. Explaining the Core Theories of Econometrics
Moderately priced, this course focuses on core theories of Econometrics. This 4-hour on-demand course consists of 13 downloadable video resources. With a rating of 4.1, it demands prior knowledge of algebra and university statistics, you can find it in Udemy.
Priced at $299, this course is offered by Alan Yang, a professor at the Department of International and Public Affairs at Columbia University where he teaches courses in Introductory Statistics, Econometrics, and Quantitative Analysis in Program Evaluation and Causal Inference.
3. Econometrics for Business in R and Python
Mostly aimed at data scientists who want to use econometrics in business decisions, this course teaches how to address finance and marketing business challenges using Causal Inference and Statistical Modeling. Available in Udemy. I will update you about the product soon.
Now here is the new list of online resources added in 2022
This is highly recommended for anyone interested in the field of finance, statistics, and financial econometrics. One of my favorite channels to update my knowledge in econometrics.
In this channel, you can follow the subject topic-wise.
Visit this channel if you want to transition from economics to data science. Very useful if your university syllabus wants you to use R and Python for your projects.