Time Series Analysis (MIT 14.384)
by Anna Mikusheva · MIT OpenCourseWare
Time series methods in econometrics: stationary and non-stationary models, vector autoregressions, frequency-domain methods, persistent series, structural breaks, and estimating DSGE models by simulated moments, maximum likelihood and Bayesian methods. Provides 23 lecture note files and a problem set. Prepares you for empirical macroeconomic research.
More resources on Econometrics
r/econometrics Wiki
The econometrics subreddit's wiki index, where practitioners and graduate students collect textbook recommendations, software advice, and answers to recurring questions. Useful for orienting yourself before choosing a first course or text.
Data Analysis for Social Scientists (MIT 14.310x)
Probability, statistics and modern data analysis for social and policy questions: regression, experimental design, randomized trials and A/B tests, machine learning and visualization, taught with R. Includes 24 lecture videos, lecture slides and problem sets. Afterwards you can run and interpret your own empirical analyses.
Econometrics (MIT 14.382)
Graduate econometrics on key models and their identification, estimation and inference, including linear regression, instrumental variables, and high-dimensional and quantile methods, with hands-on work on real data sets. Provides 18 detailed lecture note files, problem sets and exams. Prepares you for empirical research.
Introduction to Statistical Methods in Economics (MIT 14.30)
Probability and statistics for economists: probability theory, random variables and distributions, sampling theory, estimation, confidence intervals and hypothesis testing. Provides 25 lecture note files, problem sets with solutions, and exams. Leaves you ready for a first regression-based econometrics course.
Econometrics: Methods and Applications
Welcome! Do you wish to know how to analyze and solve business and economic questions with data analysis tools? Then Econometrics by Erasmus University Rotterdam is the right course for you, as you learn how to translate data into models to make forecasts and to support decision making. * What do I learn? When you know econometrics, you are able to translate data into models to make forecasts and to support decision making in a wide variety of fields, ranging from macroeconomics to finance and marketing. Our course starts with introductory lectures on simple and multiple regression, followed by topics of special interest to deal with model specification, endogenous variables, binary choice data, and time series data. You learn these key topics in econometrics by watching the videos with in-video quizzes and by making post-video training exercises. * Do I need prior knowledge? The course is suitable for (advanced undergraduate) students in economics, finance, business, engineering, and data analysis, as well as for those who work in these fields. The course requires some basics of matrices, probability, and statistics, which are reviewed in the Building Blocks module. If you are searching for a MOOC on econometrics of a more introductory nature that needs less background in mathematics, you may be interested in the Coursera course “Enjoyable Econometrics” that is also from Erasmus University Rotterdam. * What literature can I consult to support my studies? You can follow the MOOC without studying additional sources. Further reading of the discussed topics (including the Building Blocks) is provided in the textbook that we wrote and on which the MOOC is based: Econometric Methods with Applications in Business and Economics, Oxford University Press. The connection between the MOOC modules and the book chapters is shown in the Course Guide – Further Information – How can I continue my studies. * Will there be teaching assistants active to guide me through the course? Staff and PhD students of our Econometric Institute will provide guidance in January and February of each year. In other periods, we provide only elementary guidance. We always advise you to connect with fellow learners of this course to discuss topics and exercises. * How will I get a certificate? To gain the certificate of this course, you are asked to make six Test Exercises (one per module) and a Case Project. Further, you perform peer-reviewing activities of the work of three of your fellow learners of this MOOC. You gain the certificate if you pass all seven assignments. Have a nice journey into the world of Econometrics! The Econometrics team
Statistics for Business and Economics
Mathematically rigorous business statistics textbook covering probability, sampling distributions, estimation, hypothesis testing, regression, and time series through applied business and economics problems. Readers learn to design and interpret statistical tests rather than simply run canned software procedures.