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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.
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Course by
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التعلم الذاتي
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66 ساعات
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الإنجليزية
Econometrics for Economists and Finance Practitioners
This Specialisation provides rigorous training in econometric methods, via the exploration of theoretical concepts, real-data examples and the application of econometric techniques to industry relevant questions. The methodologies in this Specialisation are an important part of an informed economics and financial decision-making process. You will learn: - How to test economics and finance theories, as well as hypotheses on the relationships between variables. - Study the behaviour of prices, returns, growth and unemployment.
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Course by
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Self Paced
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الإنجليزية
Enjoyable Econometrics
The goal of this MOOC is to show that econometric methods are often needed to answer questions. A question comes first, then data are to be collected, and then finally the model or method comes in. Depending on the data, however, it can happen that methods need to be adapted. For example, where we first look at two variables, later we may need to look at three or more. Or, when data are missing, what then do we do? And, if the data are counts, like the number of newspaper articles citing someone, then matters may change too.
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Course by
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Self Paced
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2 ساعات
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الإنجليزية
The Econometrics of Time Series Data
In this course, you will look at models and approaches that are designed to deal with challenges raised by time series data. The discussion covers the motivation for the use of particular models and the description of the characteristics of time series data, with a special attention raised to the potential memory. You will: – Discuss time series models, that refer to data that have been collected over a period on one or more variables for the same individual.
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Course by
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Self Paced
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31 ساعات
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الإنجليزية
Topics in Applied Econometrics
In this course, you will discover models and approaches that are designed to deal with challenges raised by the empirical econometric modelling and particular types of data. You will: – Explore the motivations of each approach by means of graphs, preliminary statistics and presentation of economic theories – Discuss the problem of identification of the parameters, and how to address this problem by modelling simultaneous equations and causality in economics.
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Course by
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Self Paced
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28 ساعات
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الإنجليزية
Hypotheses Testing in Econometrics
In this course, you will learn why it is rational to use the parameters recovered under the Classical Linear Regression Model for hypothesis testing in uncertain contexts. You will: – Develop your knowledge of the statistical properties of the OLS estimator as you see whether key assumptions work. – Learn that the OLS estimator has some desirable statistical properties, which are the basis of an approach for hypothesis testing to aid rational decision making.
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Course by
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Self Paced
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27 ساعات
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الإنجليزية
Panel Data Analysis with R
In this 1-hour long project-based course, you will learn how to conduct Panel Data (Regression) Analysis. You will receive step-by-step instructions to analyze the 'RENTAL' dataset from 'Introductory Econometrics: A Modern Approach' by Wooldridge using R Studio. In this project, we will discuss three models namely, Ordinary Least Square (OLS), Fixed effects (FE) and Random effects (RE) in brief and check which one fits the model best.
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Course by
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Self Paced
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2 ساعات
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الإنجليزية
The Classical Linear Regression Model
In this course, you will discover the type of questions that econometrics can answer, and the different types of data you might use: time series, cross-sectional, and longitudinal data.
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Course by
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Self Paced
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22 ساعات
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الإنجليزية