QMUL - Topics in Applied Econometrics
- Offered byCoursera
Topics in Applied Econometrics at Coursera Overview
Duration | 28 hours |
Start from | Start Now |
Total fee | Free |
Mode of learning | Online |
Official Website | Explore Free Course  |
Credential | Certificate |
Topics in Applied Econometrics at Coursera Highlights
- Flexible deadlines in accordance to your schedule.
- Earn a Certificate upon completion
Topics in Applied Econometrics at Coursera Course details
- 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.
- Examine the key features of panel data, and highlight the advantages and disadvantages of working with panel data rather than other structures of data.
- Learn how to choose what econometric specification to adopt by introducing the test for poolability and the Hausman tests.
- Discuss models for probability that are used where the variable under investigation is qualitative, and needs to be treated with a different approach.
- Learn how to apply this approach to building an Early Warning system to forecast systemic banking crises using data from the World Bank.
Topics in Applied Econometrics at Coursera Curriculum
Random Regressors
Welcome to Topics in Applied Econometrics
Random Regressors
Simultaneous Equation Models
Identification of Parameters
The Estimating Equation
The Problem with Random Regressors
The Instrumental Variable Approach
Simultaneous Equation Models
Identification of Parameters: Demand and Supply
Finding Instruments
Reparameterisation
Identifying Problems with the Approach
Understanding of Conditions, Identification and Causality
Understanding Identification
Knowledge Check: Random Regressors
Panel Data Models: The Basics
Panel Data
The Solow Growth Model
Fixed Effects Models
Estimation of the Model
Features of Panel Data Analysis
The Solow Growth Model
How the Fixed Effects Model Works
Understanding the Advantages of Panel Data
Understanding the Pooled Model
Understanding the Solow Growth Model
Understanding Fixed Effects Models
Knowledge Check: Panel Data Models: The Basics
Further Analysis of Panel Data Models
Fixed or Random Effects
The Use of Time
Dynamic Panel Data
Controlling the Heterogeneity
Selecting which Model
The Use of Time effects models
Dynamic Panel Data Models
Understanding the Differences Between Fixed Effects or Random Effects
Choosing Fixed Effects or Random Effects
Understanding Time Effects
Understanding Dynamic Panel Data Models
Knowledge Check: Further Analysis of Panel Data Models
Probability Models
Linear Probability Models
Logit and Probit Models
Marginal Effects
The Multinomial Model
Using Linear Probability Models
Linear Probability Models: An Example
Limitations of Logit and Probit Models
Interpreting Marginal Effects
Maximum Likelihood Estimators (MLE)
The Logit and Probit Multinomial Model
Congratulations
Understanding Probability Models
When to Use OLS
Understanding Random Effects
Knowledge Check: Probability Models
Topics in Applied Econometrics at Coursera Admission Process
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