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Eviews Commands

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Submitted By hamidreza559
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Summary of important EViews-Commands
Import of data from EXCEL: if the xlsx-format does not work, use File.xls Choice of sample period: Sample / @all @first @last 1990 2010 1981Q3 2005Q1 1960M1 2000M11 in command line e.g.: smpl @first 1990 Univariate statistics: Click series / View / Spreadsheet Graph Descriptive Statistics&Tests Correlogram

data as numbers Graphics z.B. histogram, mean, etc. autocorrelationen

Generation/Transformation of series: Generate / x = 0 generates a series with zeros Generate / pi = (pc – pc(-1))/pc(-1)*100 Generates the inflation rate in % based on prices pc Generate / x = log(y) taking logs Generate / dlx = dlog(x) dlx = log(x) – log(x(-1)) Growth rate in continuous time Generate / y = exp(x) exp(x) as command: series x=0 Trend variable (linear): Generate / t = @trend Standard normal distributed realizations: Generate / x = nrnd Lags, lagged variables, taking differences: Generate / x1 = x(-1) x1(t) = x(t-1), Lag 1 of x Generate / dx = d(x) dx(t) = x(t) – x(t-1) = (1-B)x(t) first difference Generate / d2x = d(x,2) d2x(t) = dx(t) – dx(t-1) = (1-B)^(2)x(t) taking first differences twice Generate / d12x = d(x,0,12) d12x(t) = x(t) - x(t-12) = [1-B^(12)]x(t) seasonal difference for monthly data Generate d12_1x = d(x,1,12) d12_1x(t) = (1-B)[1-B^(12)]x(t) Geneartion of dummy variables: seasonal dummies: s=1,2,3,... Generate / ds = @seas(s) as command: series ds = @seas(s) Generate / d1 = 0 and manually in View/Spreadsheet use Edit+/p-value for x of a test statistic as command:

(N-, t-, scalar p scalar p scalar p scalar p scalar p

Chi2-, F-distribution) = 1 - @cnorm(x) = 1 - @cnorm(abs(x))*2 = 1 - @ctdist(x,df) = 1 - @cchisq(x,df) = 1 - @cfdist(x,df1,df2)

1-sided, right 2-sided 1-sided, right

df ... degrees of freedom Determinant of correlation matrix: (as command) group grpx x1 x2 x3 x4 matrix x = @convert(grpx) group assigned to a data matrix scalar det = @det( @cor(x) ) @cor(X) makes correlation matrix Statistics for 2 or more series: Correlation matrix: Mark the series by klicking / right mouse / Open as Group / View / / Covariance Analysis (z.B. Correlation) as command e.g.: scalar corrxy = @cor(x,y) Estimation: Quick / Estimate Equation / y c x1 x2 Option: LS ... OLS Enter the estimation period bivariate correlation coeff y = a1 + a2*x1 + a3*x2 + u

as command: ls y c x1 x2 with storage in equation “eq3”: eq3.ls y c x1 x2 ARMA Model: Option: LS Model specification: y c AR(1) AR(2) MA(1) MA(2) MA(3)

ARMA(2,3) with non zero mean

with heteroscedasticity robust standard errors: Options: Covariance Coefficient Matrix / White (z.B.) System estimation: Open a multivariate equation system: Object / New Object / System Equations e.g.: y1 = c(1) + c(2)*x1 + c(3)*y2 y2 = c(4) + c(5)*x2 + c(6)*x3 Instruments if needed e.g.: inst x2 z7 Choose estimation method Forecasting with LS, ...: in LS Output (Equation) / Forecast Forecast period, enter series name for forecasted values (e.g. yf) and forecast error stdev (e.g. syf). Plot of the forecast: Object in Workfile menu / New Object / Group / (or mark series with mouse / right click Open / as Group) Enter the elements: yf forecasted values y observed values (yf - 1.96*syf) forecast interval, lower border (yf + 1.96*syf) forecast interval, upper border

Testing for structural breaks: in Equation / View / Stability Diagnostics / / Chow Breakpoint Test / Enter: Start of 2., 3., ... period / Chow Forecast Test / Enter: Start of 2.period, ... / Recursive Estimates / CUSUM Statistics for residuals: autocorrelation, heteroscedasticity in Equation / View / Residual Diagnostics / ... Autocorrelation, Heteroscedasticity Storing residuals: in Equation / Proc / Make Residual Series Testing for Unit Roots: View / Unit Root Test (Augmented Dickey Fuller) Testing for cointegration: Collect the variables in a group / View / Cointegration Test (Johansen) Estimation of a VAR or CIVAR: Mark dependent variables / Open as VAR (with right mouse-button)

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