Model objects, Policy simulations and Forecasting in E-views: a step by step approach. Tinashe Bvirindi

Transcription

1 Model objects, Policy simulations and Forecasting in E-views: a step by step approach By Tinashe Bvirindi tbvirindi@gmail.com

2 Layout Model object creation Solving a model (in sample) Forecasting out of sample Conducting policy simulations and ploting response functions

3 Modelling in E-views A model consists of a set of equations that jointly describe the relationship between a set of variables. The equations can be: Simple Identities, Results of single equations, or Results of multiple equation estimators

4 Modelling in E-views The equations are combined in a single object to derive deterministic or stochastic joint forecasts or simulations for all the variables in the model. Deterministic setting: model inputs are fixed at known values and a single path is calculated for the output variable Stochastic setting: uncertainty is incorporated into the model by adding a random element to the coefficients, equation residuals or exogenous variables Models allow us to conduct policy simulations

5 Modelling in Eviews In Eviews for the model to have a unique solution, there should typically be as many equations as there are endogenous variables Each equatin in the model must have a unique endogenous variable assigned to it. Any variable that is not assigned as an endogenous variable is considered exogenous to the model.

6 Creating a model object To create a model object, click on Object, in the main window and select New Object

7 Building a model Give the model a name of your choice Now on the type of object, select Model and click OK

8 Model object

9 Model object Equations in Eviews can either be inline or linked Inline - the equation is specified as text within the model linked the equation brings its specification into the model from an external eviews object e.g. a single equation object The advantage of linking is that it allows coupling of the model with the estimation procedure underlying the equations. Equations can either be stochastic equations or identities

10 Creating a linked equation To create a linked equation, right click on the equation of choice then copy it

11 Creating a linked equation Now take the copied equation and then paste it in this window

12 Creating a linked equation Select the yes to all option

13 Linked equations In this equation window all the pasted equations will appear, with a list of their explanatory variables List of variables The scenario in question appears here

14 Linked equations To views the variable dependencies and their classifications click on the Variables button Adds stands for add factors Exogenous variables are labelled and have an X Endogenous variables are equation variables and have and En

15 Advantage of linking the equations Once we added our equations as linked equations we can go back and re-estimate our equations and automatically update the model to the new estimates as follows: Click on Proc, then select the Links button and click update all links and recompile

16 Adding identities In order to add identities, right click the mouse while in the VIEW equation window. Right click anywhere in this window and click on insert

17 Adding identities Once you select insert this dialogue box will appear and then you enter the identity into the model source edit window and click OK

18 Creating inline equations To create an inline equation first copy the equation representations First open the equation of choice and click on view, then select representations

19 Creating inline equations Once this output comes out copy the substituted coefficients

20 Creating an inline equation Click on the text toggle/ button and paste the copied equation into this window

21 Inline equations In order to view the dependence structure of the variables, click on variables Then click Yes to save modifications and compile

22 Inline equations Click on view to see the equations or the block structure of the model Inline text equation Block structure

23 Solving equations Once you have inputed all the equations into the model the next step is to solve the model There are many options available for solving the model in Eviews For now we concentrate on the basic techniques To solve the model simpy click on solve However, before we solve the data we may want to input the exogenous variables we wish to use in policy simulations as in line text

24 Solving the model NB: this technique is a shortcut and is sometimes not advisable Click on text and type the variable you wish to employ in policy simulations

25 Solving the model Click on solve and then click on Yes To save and compile modifications

26 Solving the model Once you click save this dialogue box will appear Click on deterministic Choose baseline scenario Select static solution for model evaluation Adjust the sample size over which to solve the model to avoid initialising the model on missing values

27 Solving the model Once you have set all the conditions click OK to solve the model You will then receive the following solution message

28 Workfile appearance after initial solve The solution of the baseline scenario is saved with and underscore of zero in the workfile

29 Forecasting- static solution Plot the baseline lm3 from the static solution against the actual lm3

30 Forecast- dynamic solution (recursive) Re-solve the model but this time selecting the dynamic solution and plot the baseline from the dynamic solution against the actual This result shows how the model Would have performed if we had used it back in 2000 If satisfied with performance of the model against historical date we can use the model to forecast future values of endogenous variables

31 Forecasting out of sample First step is to decide on the value of exogenous variables. If they are not available the re is need to provide these.

32 Out of sample forecasting Eviews uses a Monte Carlo simulation technique to generate the uncertainty surrounding our forecasts To generate this graph, click the solve button and in the model solution dialogue select stochastic, and tick the standard deviation box in Active and click OK Then go to Proc, Make graph, and in the solution series box select mean+2s.d and reset sample period to 2003Q1 to 2011Q4, and click OK

33 Policy simulations Having satisfied ourselves of our model s capabilities in and outside the sample we may conduct policy simulations In the policy simulations, we are mainly interested in the impact that the exogenous variable will have on the endogenous variables and ultimately on our model Economists- interest is to assess the effect of policy variable on macroeconomic aggregates Risk manager/ supervisor- interest is to determine the level of stress that an external event may induce on the endogenous variables

34 Policy simulations Step 1: create a scenario In the model object window click on View, then select Scenarios

35 Policy simulations Click on create new and then OK

36 Policy simulations Click on the Variables button

37 Policy simulations Right click on the exogenous variable of interest and the select properties on the drop down menu

38 Policy simulations Tick in the use override series in scenario and click OK

39 Policy simulation Once the variable is set the text changes to red

40 Policy simulation- temporary shock Lets assume a temporary shock of a sudden increase in nominal income of 10% per quarter for the period 2001Q1 to 2003Q3 To do policy simulation we make use of a very simple command Set the period over which the shock takes place And calibrate the shock

41 Policy simulation Once the sample size is set and the shock is specified then we proceed to solve the model Click on solve in the model object window

42 Policy simulation Reset simulation type to deterministic Make sure the set scenario is active and click ok Set the interval over which you want to estimate

43 Policy simulations Solution message for the scenario

44 Plotting the results Whilst still in the model object click on the Proc Button and select the make graph option

45 Policy simulation: shock vs baseline Select list of variables and list endogenous variables Make sure that the actuals and scenario are selected Reset horizon and click OK

46 Policy shock simulation

47 IMPULSE RESPONSE OF LM3 TO LNGDP Money supply has a lagged response to income, relationship is error correcting, shocks die down after about 5 years

48 Class exercise 1. Estimate the following error correction models: D(LSTCKPR) LSTCKPR(-1) LTDC(-1) LCPI(-1) LP_R(-1) C D(LTDC(-1)) D(LCPI(-4)) D(LP_R(-1)) D(LSTCKPR(-1)) D(LM3) LM3(-1) LNGDP(-1) LCPI(-1) LP_R(-1) C D(LM3(-1)) D(LCPI(-3)) D(LNGDP(- 4)) D(LP_R(-4)) D(LTDC) LTDC(-1) LR(-1) LM3(-1) LNGDP(-1) LNEER(-1) C D(LR(-1)) D(LTDC(-1)) D(LM3(-1)) D(LNGDP(-3)) D(LNEER(-2)) 2. Create a model object with the three equations and solve it. 3. Perform an in sample forecast and produce an out of sample forecast showing the level of uncertainty associated with the forecast. 4. Trace the impact of an increase in GDP on money demand, the stock price and domestic credit and comment 5. Plot the impulse response function

49 References