Introduction to EViews. Manuel Leonard F. Albis UP School of Statistics

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1 Introduction to EViews Manuel Leonard F. Albis UP School of Statistics

2 EViews EViews provides sophisticated data analysis, regression, and forecasting tools on Windows-based computers. Areas where EViews can be useful: Scientific data analysis and evaluation; Financial analysis; Macroeconomic forecasting; Simulation; Sales forecasting; and, Cost analysis.

3 The EViews Window Command Window Main Menu Work Area Status Line

4 EViews Lecture 2. WORKFILE BASICS

5 Eviews Workfile Most of the work in EViews will involve objects that are contained in a workfile, so the first step in any project will be to create a new workfile or to load an existing workfile into memory Workfiles hold a variety of EViews objects, such as equations, graphs, and matrices

6 Creating a workfile Ways to create a workfile: 1. Describing the structure of the workfile employed if data will be entered into EViews by typing or copy-and-pasting data 2. Opening and reading data from a foreign data source

7 Creating a Workfile by Describing Its Structure STEP 1 Select File/New/Workfile from the main menu to open the Workfile Create dialog Workfile Create Window

8 Creating a Workfile by Describing Its Structure STEP 2 Select the appropriate workfile structure type: 1. Unstructured/ Undated: For cross section data Prompt: number of observations 2. Dated-regular frequency: For time series data Prompts: 1. Frequency (Annual, Semi-annual, Quarterly, Monthly, Weekly, Daily- 5 day week, Daily-7 day week) 2. Start date 3. End date

9 Creating a Workfile by Describing Its Structure STEP 2 (continued) 3. Balanced Panel: For panel data Prompts: 1. Frequency (Annual, Semi-annual, Quarterly, Monthly, Weekly, Daily-5 day week, Daily-7 day week) 2. Start date 3. End date 4. Number of cross sections

10 Example: Defining a Workfile Define a workfile for the Export.xls The Excel file contains the monthly data of Exports, FDI and Crisis period indicator, which spans from January 1996 to September 2004

STEP 1: To open a temporary spreadsheet window in which you will

11 Importing data Entering data For small datasets in printed form, you may wish to enter the data by typing at the keyboard. STEP 1: To open a temporary spreadsheet window in which you will enter the data, choose Quick/Empty Group (Edit Series) from the main menu.

12 Importing data STEP 2: Do the following steps:

13 Importing data Copy-and-Pasting Useful for small datasets and other software applications (ex. Excel) STEP 1: Highlight and copy the cells (including the variable headings/names) to be imported into EViews STEP 2: In EViews, create or load a workfile and choose Quick/Empty Group (Edit Series) from the main menu STEP 3: Place the cursor and click the upper-left cell just to the right of the second obs label STEP 4: Select Edit/Paste from the main menu (or simply use the right mouse click to paste)

14 Example: Copy-and-Paste Export.xls

file types that EViews supports (Excel, SAS, SPSS, Stata, Text, etc) STEP 3: Select your file and click OPEN

15 Creating a workfile by reading from a foreign data source STEP 1: Select File/Open/Foreign Data as Workfile to bring up the standard file Open dialog STEP 2: Click the Files of type combo box and select from the list of the file types that EViews supports (Excel, SAS, SPSS, Stata, Text, etc) STEP 3: Select your file and click OPEN Note: A simple alternative to opening the file from the menu is to dragand-drop your foreign file into the EViews window.

16 Creating a workfile by reading from a foreign data source (using Export Data)

17 Creating a workfile by reading from a foreign data source (using Export Data)

18 EViews Lecture 3. OBJECT BASICS

19 EViews Objects Eviews Objects are information stored in a workfile

20 Common Object Type SERIES A collection of information related to a set of observations on a particular variable Contain mostly numeric information Has a spreadsheet view, which shows the raw data, a line graph view, distributional plots, etc. It also allows you to compute simple hypothesis tests and statistics for various subgroups

21 Common Object Type EQUATION A collection of information related to the relationship between a collection of variables Contain complete information about the specification of the equation, the estimation results, as well as references to the underlying data used to construct the estimates Has a representation view showing he equation specification, an actual-fitted-residual view containing plots of fitted values and residuals, etc.

22 Working with objects Naming objects You must name an object if you wish to keep its results If you do not name an object, it will be called UNTITLED Unnamed objects are not saved with the workfile, so they are deleted when the workfile is closed and removed from memory When you give an object a name, the name will appear in the directory of the workfile, and the object will be saved as part of the workfile when the workfile is saved o The following names are reserved and cannot be used as object names: ABS, ACOS, AND, AR, ASIN, C, CON, CNORM, COEF, COS, D, DLOG, DNORM, ELSE, ENDIF, EXP, LOG, LOGIT, LPT1, LPT2, MA, NA, NOT, NRND, OR, PDL, RESID, RND, SAR, SIN, SMA, SQR, and THEN

23 Working with objects Naming objects STEP 1: Open the object window STEP 2: Click the Name button and the Object Name window will appear STEP 3: Enter the name, and optionally, a display name to be used when labeling the object tables and graphs.

24 Working with objects Labeling objects EViews objects have label fields where you can provide extended annotation and commentary

25 Working with objects Copy-and-pasting objects Copying an object means EViews will create a new untitled object containing an exact copy of the original object The new object duplicates all features of the original except for the name When two workfiles are in memory at the same time, you may copy objects between them using copy-and-paste

26 Working with objects Copy-and-pasting objects STEP 1: Highlight the objects you want to copy in the source workfile STEP 2: Select Edit/Copy from the main menu (right clicking the object also works) STEP 3: Select the destination workfile by clicking on its titlebar STEP 4: Select either Edit/Paste or Edit/Paste Special from the main menu (or simply Paste or Paste Special following a right mouse click)

27 Working with objects Freezing objects The second method of copying information from an object is to freeze a view of the object If you click Object/Freeze Output or press the Freeze button on the object s toolbar, a table or graph object is created that duplicates the current view of the original object The primary feature of freezing an object is that the tables and graphs created by freezing may be edited for presentations or reports Frozen views do not change when the workfile sample or data change

28 Working with objects Deleting objects STEP 1: To delete an object or objects from your workfile, select the object/s in the workfile directory STEP 2: Click Delete or Object/Delete Selected on the workfile toolbar EViews will prompt you to make certain that you wish to delete the objects.

29 EViews Lecture 4. BASIC DATA HANDLING

30 Basic Data Handling The process of entering, reading, editing, manipulating, and generating data forms the foundation of most data analyses EViews provides you with a sophisticated set of data manipulation tools that make the task as simple and straightforward as possible There are three cornerstones of data handling in EViews: the two most common data objects, series and groups, and the use of samples which define the set of observations in the workfile that we wish to use in analysis

31 Basic Data Handling The actual numeric values that make up your data will generally be held in one or more of EViews data objects For most users, series and groups will by far be the most important objects, so they will be the primary focus of our discussion

32 Series An EViews series contains a set of observations on a numeric variable For series in dated workfiles, the observations are presumed to be observed regularly over time For undated data, the observations are not assumed to follow any particular frequency Note that series object may only be used to hold numeric data. If you wish to work with alphanumeric data, you should employ alpha series

33 Series Creating a series STEP 1: In the main menu, select Object/New Object STEP 2: Select Series; you may, at this time, provide a name for the series STEP 3: Click OK. EViews will open a spreadsheet view of the new series object

34 Series Editing a series STEP 1: Open the spreadsheet view of the series STEP 2: Make certain that the spreadsheet window is in edit mode. Use the Edit +/- button on the toolbar to toggle between edit mode and protected mode STEP 3: To change a value for an observation, select the cell, type in the value, and press ENTER STEP 4: When you have finished editing, you should protect yourself from inadvertently changing values of your data by clicking on Edit +/- to turn off edit mode. Note: When editing series values, you should pay particular attention to the series display format, which tells you the units in which your series are displayed

35 Groups When working with multiple series, you will often want to create a group object to help you manage your data A group is a list of series names that provides simultaneous access to all of the elements in the list A set of variables may be analyzed, graphed, or printed using the group object, rather than each one of the individual series Once a group is defined, you can use the group name in many places to refer to all of the series contained in the group

36 Groups Creating groups STEP 1: In the main menu, select Object/New Object STEP 2: Select Group. You may, at this time, provide a name for the group STEP 3: Enter the names of the series to be included in the group, separated by spaces Note that a group may be included to be a part of a group. Series expressions (mathematical expressions that may involve one or more series) may also be added in a group STEP 4: Click OK. A group window will open showing a spreadsheet view of the group

37 Groups Editing in a group STEP 1: Open the group window and make certain that the group spreadsheet is in protected mode. STEP 2: To change a value for an observation, select the cell, type in the value, and press ENTER. Note: Since groups are simply references to series, editing the series within a group changes the values in the original series Note: As with series spreadsheet views, you may click Smpl +/- to toggle between showing all the observations in the workfile and showing only those observations in the current sample

38 Samples The sample is the set (often a subset) of observations in the workfile to be included in the data display and in performing statistical procedures Samples may be specified using ranges of observations (usually for time series) and if conditions that observations must satisfy to be included

39 Samples The Workfile Sample When you create a workfile, the workfile sample or global sample is set initially to be the entire range of the workfile. It tells EViews what set of observations you wish to use for subsequent operations. You can always determine the current workfile sample of observations by looking at the top of your workfile window.

40 Samples Changing the Sample EViews provides special keywords that may make entering sample date pairs the entire workfile first last observation

41 Samples Changing the sample You may find it easier to set your workfile sample from the command window using the smpl command. STEP 1:In the command window just type: Smpl start_obs end_obs if if_command STEP 2: Press enter.

42 Samples Changing the sample Sample offsets (examples) smpl 1953m1 1953m1+11 Sample that includes 12 observations in the calendar year beginning in Sample where the first observation is dropped.

43 EViews Lecture 5. WORKING WITH DATA

44 Numeric expressions An EViews expression is a combination of numbers, series names, functions, and mathematical and relational operators. You can use these expressions to: Calculate a new series from existing series Describe a sample of observations Describe an equation for estimation or forecasting

45 Numeric expressions: operators Eviews follows the usual order in evaluating expressions with operator precedence order as follows (from highest precedence to lowest): Unary minus/negation (-), unary plus (+) Exponentiation (^) Multiplication (*), division (/) Addition (+), subtraction (-) Comparison (<, >, <=, >=, =) and, or To enforce a particular order of evaluation, you can use parentheses

46 Numeric Expressions: lags and leads Lags are specified as negative numbers example: x(-4) is the fourth lag of x Leads are specified as positive numbers example: y(2) is the second lead of y

47 Numeric Expressions: differences EViews has several built-in functions for working with difference data in either levels or in logs Examples: d(x) x x(-1) dlog(x) log(x) log(x(-1)) d(x,4) fourth order difference of x d(x,1,4) first order difference of x with a seasonal difference at lag 4 d(x,0,4) x with a seasonal difference at lag 4

48 Series One of the primary uses of expressions is to generate new series from existing data or to modify the values in an existing series. Creating/modifying a series STEP 1: Select Quick/Generate Series or click the Genr button on the workfile toolbar; EViews opens a window prompting you for additional information

49 Series Creating/modifying a series (STEP 2) Basic assignment Type the series name, followed by an equal sign and then an expression For example, in the previous slide, y = 2^x + 37*z means that if there is no series named y, EViews will create the y series and will fill each element of the y series with the value of the expression. If the series y exists, EViews will replace the y values

50 Series Creating/modifying a series (STEP 2) Dynamic assignment You can also perform dynamic assignment by using lagged values of the destination series on the right side of the equality Example: y = y +y(-1) This creates a y series with the cumulative sum of y

51 Scalars Scalar objects are different from series in that they hold a single number instead of data for each observation in the sample. Scalars are created by the commands of the form: scalar scalar_name = number Scalar objects have no window views, to see the value of the scalar, double click on the scalar name in the workfile window and the value will be displayed in the status line.

52 EViews Lecture 6. BASIC DATA ANALYSIS

53 Basic data analysis EViews provides various statistical graphs, descriptive statistics, and procedures as views and procedures of a numeric series Series views compute various statistics for single series and display these statistics in various forms such as spreadsheets, tables, and graphs Series procedures create new series from the data in existing series. These procedures include various seasonal adjustment methods, exponential smoothing methods, and the Hodrick- Prescott filter

54 Series: View Button The series View dropdown menu is divided into four blocks This includes descriptive statistics, and important time-series tests

Series: Descriptive statistics and tests Skewness positive (negative) skewness means that the distribution has a long right (left) tail Kurtosis the kurtosis of the normal distribution is 3; if the

55 Series: Descriptive statistics and tests Skewness positive (negative) skewness means that the distribution has a long right (left) tail Kurtosis the kurtosis of the normal distribution is 3; if the kurtosis is greater (less) than 3, the distribution is leptokurtic (platykurtic) Jarque-Bera test statistic for testing whether the series is normally distributed (null hypothesis: normal distribution)

Series: Series Distribution Tests Mean test Ho: mean of the series is equal to the specified value Variance test - Ho: variance of the series is equal

56 Series: Series Distribution Tests Mean test Ho: mean of the series is equal to the specified value Variance test - Ho: variance of the series is equal to the specified value Median test - Ho: median of the series is equal to the specified value Ha: mean/variance/median is not equal to the specified value

lags These functions characterize the pattern of temporal

57 Series: Correlogram This view displays the autocorrelation and partial autocorrelation functions up to the specified order of lags These functions characterize the pattern of temporal dependence in the series and typically make sense only for time series data

58 Unit Root test This view carries out the Augmented Dickey- Fuller (ADF), GLS transformed Dickey-Fuller (DFGLS), Phillips-Perron (PP), etc.

59 Series: Proc Button Series procedures may be used to generate new series that are based upon the data in the original series You may also use series procs to resample from the original series, to perform seasonal adjustment or exponential smoothing

60 Graphing the Data Constructing graphs from data is an important part of the process of data analysis and presentation The last part of this section shall focus on describing the basics of graphing data in series using the View/Graph menu item

61 Graphing the Data Another way of graphing data is to select Quick/Graph You will then be required to enter the list of series, groups, and/or series expressions you want to graph

62 Graphing the Data After clicking OK, the Graph Options dialog will appear The Graph Options dialog has multiple pages that specify various settings for the graph view The Type page is of central importance since it controls the graph you wish to display

63 EViews Lecture 7. BASIC SINGLE-EQUATION REGRESSION

64 Single-equation regression Single-equation regression is one of the most versatile and widely used statistical techniques Basic regression techniques in EViews: specifying and estimating a regression model performing simple diagnostic analysis using the estimation results in further analysis

65 Specifying an Equation in EViews Click Quick/Estimate equation to open the Equation Estimation dialog You then have to specify: Equation specification Estimation settings

66 EViews Lecture 8. PRELIMINARY TIME-SERIES TESTS

67 Test for Unit Root Dickey-Fuller Test The Dickey-Fuller test statistics is derived from the estimation of the 1 st order autoregressive model y t = ρy t 1 + ε t, ε t ~WN(0, σ ε 2 ) Note that if ρ = 1, then y t is a random walk (unit root process); while if ρ < 1, then the process is a stationary AR(1)

68 Test for Unit Root Dickey-Fuller Test Subtracting y t 1 on both sides of the equation, y t y t 1 = ρy t 1 y t 1 + ε t Δy t = ρ 1 y t 1 + ε t Note that if ρ = 1, then y t is a random walk (unit root process); while if ρ < 1, then the process is a stationary AR(1)

69 Test for Unit Root Dickey-Fuller Test The hypotheses are: H 0 : ρ 1 = 0 (series has a unit root) H a : ρ 1 < 0 (series has no unit root) If the null hypothesis is not rejected, then it does not necessarily mean that the series has a single unit root or generated by an integrated of order 1 process (denoted by I(1)) The next step is to repeat the procedure on the first difference of the series

70 Test for Unit Root Augmented Dickey-Fuller Test Controls for serial correlations by adding lagged terms of the dependent variable Δy t = α + δ t + ρ 1 y t 1 + p i=1 φ i Δy t i + ε t The number of lags, p, is determined using an automatic selection procedure that minimizes an information criterion (Akaike or Schwarz) The maximum value of p is p max = 12 T

71 Example: Test for Unit Root

73 Test for Seasonality Regression-Based Test The approach is to regress the stationary series with the seasonal dummy variables The F-statistic of the regression model captures the information on the amount of variability explained by the seasonal dummy variables

74 Test for Seasonality Regression-Based Test The model is given by y t = β 0 + S 1 i=1 β i SEAS ti + ε t The hypotheses are: H 0 : β i = 0, i = 1,, S 1 (no seasonality) H a : at least one β i 0 (with seasonality)

Chapter 1: An Overview of Regression Analysis

Chapter 1: An Overview of Regression Analysis In this chapter: 1. A simple example of regression analysis (UE 1.4): a) Creating an EViews workfile b) Entering data into an EViews workfile c) Creating a