TAILIEUCHUNG - Lecture Introductory Econometrics for Finance: Chapter 11 - Chris Brooks

In this chapter, you will learn how to: Describe the key features of panel data and outline the advantages and disadvantages of working with panels rather than other structures; explain the intuition behind seemingly unrelated regressions and propose examples of where they may be usefully employed; contrast the fixed effect and random effect approaches to panel model specification, determining which is the more appropriate in particular cases; construct and estimate panel models in EViews. | ‘Introductory Econometrics for Finance’ © Chris Brooks 2013 Chapter 11 Panel Data ‘Introductory Econometrics for Finance’ © Chris Brooks 2013 The Nature of Panel Data Panel data, also known as longitudinal data, have both time series and cross-sectional dimensions. They arise when we measure the same collection of people or objects over a period of time. Econometrically, the setup is where yit is the dependent variable, is the intercept term, is a k 1 vector of parameters to be estimated on the explanatory variables, xit; t = 1, , T; i = 1, , N. The simplest way to deal with this data would be to estimate a single, pooled regression on all the observations together. But pooling the data assumes that there is no heterogeneity – . the same relationship holds for all the data. ‘Introductory Econometrics for Finance’ © Chris Brooks 2013 The Advantages of using Panel Data There are a number of advantages from using a full panel technique when a panel of data is .

• Kinh tế học
• Econometrics for Finance
• Introductory Econometrics for Finance
• Regression model
• Purpose of econometrics
• Panel data
• Fixed effects models
• Econometric model
• Financial modelling
• Straight lines
• Statistical foundations
• Classical linear regression model
• Regression analysis
• Multiple linear regression
• Statistical distributions
• Univariate time series modelling
• Stochastic processes
• Multivariate models
• Simultaneous equations models
• Modelling long run relationship
• Stochastic non stationarity
• Modelling volatility
• GARCH models
• Switching models
• Switching behaviour
• Limited dependent variable models
• Linear probability model
• Simulation methods
• Random number generation
• Empirical research project
• Research project
• Financial data