Macroeconomic Modelling Using Eviews: Cointegration, VAR and VECM

The lecture was delivered on the Online Course on Macroeconomic Modelling, estimating and modelling on http://elearning.aneconomist.com. Students on this course will get all the lessons also in form of recorded videos and will be offered to select their specific topics in the offered course which will then be presented Live and Interactively.

Transcript

1. 1. Time Series Modelling using Eviews 2. Macroeconomic Modelling using Eviews 3. Macroeconometrics using Eviews By: Muhammad Anees Saturday, October 27, 2012 Learn Econometrics, Applied Statistics, Stata, SPSS, Eviews, R and Matlab on http://elearning.aneconomist.com
2. Plan of the Session • Some Theoretical Aspects? • Modelling the Systems • Proceeding with Eviews (Eviews 7)
3. Macroeconomic Models • What is Model? o Mathematical Models identifies the exact relation between included variables? o Macroeconomic variables are GDP, Investment, Consumption, Saving, Imports and Exports etc. measured at the National Level? o Macroeconomic Model is thus the mathematical function which elaborates the relationship of included macroeconomic variables? * • Types of Models? o Linear, Non-Linear? o Linear: Which shows ratio of constant changes in dependent (DV) and independent variables (IV): Slope=ratio of changes in DV & IV= / o Non-Linear Models on the other hands some variable ratios of IV and DV
4. Examples • A simple model to show the macroeconomic condition is the identification of the relationship between macroeconomic variables. • A linear model will thus be defined for example as = ( , , , , )? • We should check the nature of the variables and its impact the relation being one sided or two sided, example is one o Investment: Autonomous and induced nature o Consumption: Autonomous and Induced nature o All other can be explained as above. For details, please read some elementary books on Macroeconomic theory. o Hence the relation between any two macroeconomic variable is not that much straightforward to estimate.
5. Flow of Modelling Strategy It depicts the flow of identifying a model for the system
6. Model The Variable s Data Eviews Steps Our Todays Strategy Identify a simple Model and Estimate the Model using Eviews 7 using the given data for Pakistan Second Session Will continue from here and will develop a more technical model
7. Macroeconomic Model of Pakistan Economy: The real Sector • The sample Modelling of Pakistan’s real economy will develop the relationship between GDP, E , I, GVA, (X-M: BOP or Trade Balance)? • The model we will elaborate and estimate is GDP = E + I + GVA+(X – M)? • Known issues? o The relation between the macroeconomic variable poses some technical, Econometric challenges to estimate. And read some literature on what are these challenges if estimated using simple Regression or Vector Autoregressive Models/Cointegrated Relations? • These issues are for the next sessions, please wait!!!!
8. The data • We have extracted a sample dataset from the databank of World bank which is available from data.worldbank.org • The variables included are: o GDP: o E: o I: o GVA o X-M • The data is from variables (gdp ge inv gva imp exp) • We take log of each series so when the log difference is used, it will show growth rates of the series/variable
9. Econometric Techniques • OLS o Please read the first section of Growth Models reading which will explain each step we proceed to run the regression using OLS and related tests. • Unit Root o We will need these types of tests when we need to run a regression model using time series data o As we estimate the model (any other model can be used equally) using OLS, so the results will be SPURIOUS/not be consistent. o In this case, we need to estimate the stationarity of the series. If series are stationary, then we will be using OLS and may/may not include the trend/time variable o If the series are not stationary then we will test for whether each series is uniformly/same integrated. Which means they become stationary at the same level of differencing. o Detailed discussion on these and the following contents will be provided tomorrow. This is introduced here to convince you that we can not rely on the OLS estimates of our model using time series data. • Cointegration • VAR • VECM
10. Appendix • Estimating the Model using OLS • Testing for Issues in the estimated Models • Some Econometric tests which could be used to determine whether the model estimated is best fitted • Why we need to use alternative/Time Series regression Models? Read the Unit Roots, VAR and Cointegration Testing topics from the given reading material. We will improve our current model in second session. • Contact information: Please use only moodle@aneconomist.com for discussion regarding these contents. This email is specific to course related discussions.
11. Please read the notes below for details
12. Workfile Dialague to create workfile
13. New Workfile where data will be imported.
14. Import Wizard
15. Import Wizard: Data Specification
17. Dated Workfile with Complete dataset
18. Estimating the Macroeconomic Model we defined.
19. Regression Results
20. OLS Examples where it is Spurious
21. What Then if OLS is Spurious • If we use most of the Time Series data for running OLS, then results are spurious if the Data is Not Stationary/Unit Root. Now how to test Unit Roots. Let us what we can do using Eviews.
22. Unit Roots Testing
23. Unit Roots Testing
24. Unit Root Results
25. Unit Root test with First Difference
26. Unit Roots and Order of Integration • If we find that all the series are unit root or stationary then decide as following: o All Series are not Unit Root or say they are stationary in Levels, then these are called Integrated of Order Zero and termed as I(0) o All the series are Unit Root at Levels and Stationary at First Difference then The are Integrated of Order One or I(1) o All the series are unit root even at First Differences but Stationary at Second Differences then These are Integrated of Order Two or I(2). o And Hence On… o We proceed in the same lines and once the Integration is determined, then we can test whether they are Co-Integrated. This is for tomorrow along with Theory, Practice and Issues.
27. We have learn Step by Step • Today we started modelling simple Macroeconomic Scenarios and this can be extended to any type of models and enclosure of any type of and list of macroeconomic variables. Do your practice on the following model and determine where the series are stationary using the Time Series data. • = , , , , • Note description of variables are available in Dataset second sheet.
28. Outcome of Todays Session • We hope to know now: • Modelling any Macroeconomic Scenario • Estimate the using Basic regression and test for whether regression is Spurious • When Spurious how to proceed with further our model estimation.
29. • Thanks for your attendance. • Please email any confusion regarding initiating your modelling strategy. • Also please read the suggested contents so we are confident for tomorrow session.