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. It is recommended that you have completed and understood the previous two courses in this Specialisation: The Classical Linear Regression Model and Hypothesis Testing in Econometrics. By the end of this course, you will be able to: – Respond appropriately to issues raised by some feature of the data – Resolve address problems raised by identification and causality – Resolve problems raised by simultaneous equation and instrumental variables models – Resolve problems raised by longitudinal data – Resolve problems raised by probability models – Manipulate and plot the different types of data.
