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EViews Software. EViews 9. EViews blends the best of modern software technology with cutting edge features. The result is a state- of- the art program that offers unprecedented power within a flexible, object- oriented interface. Explore the world of EViews and discover why it's the worldwide leader in Windows- based econometric software and the choice of those who demand the very best.
What's New in EViews 9. EViews now features a wide range of exciting changes and improvements. The following is an overview of the most important features in EViews 9. EViews 8. EViews Interface. Command capture from the interactive interface. Dockable command and capture window interface.
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Database and workfile object preview. Group Members View. Group Object Preview. Data Handling. Enhanced import and linking of data. A powerful new FRED database interface. Direct read and write access to data stored on cloud drive services. Dated data table template support for saving and importing customized settings.
New frequency conversion methods. Graphs, Tables and Spools.
New mixed graph types. Graph pan and zoom. Multi- graph viewing slideshow.
Rectangle and ellipse drawing. Arrow, rectangle, and ellipse data- based anchoring.
Tables, graphs, and spools may now be saved in La. Te. X format. Model Interface. Print view. Equation view find. Scenario descriptions. Scenario view. Model protection. Econometrics and Statistics. Forecasting. Automatic ARIMA forecasting of a series.
Forecast evaluation and combination testing. Forecast averaging. VAR forecasting. Diebold- Mariano test. Estimation. Mixed- Data Sampling (MIDAS) Regression. Autoregressive Distributed Lag regression (ARDL) with automatic lag selection.
ML and GLS ARMA estimation. ARFIMA estimation. Pooled mean group estimation of panel data ARDL models. Threshold regression. A new optimization engine. FIML with Variance Restrictions.
Testing and Diagnostics. Unit root tests with a structural break. Cross- section Dependence Tests. Panel Effects Tests. Powerful Analytical Tools. In contrast with most other econometric software, there is no reason for most users to learn a complicated command language.
EViews' built- in procedures are a mouse- click away and provide the tools most frequently used in practical econometric and forecasting work. Basic Statistical Analysis. EViews supports a wide range of basic statistical analyses, encompassing everything from simple descriptive statistics to parametric and nonparametric hypothesis tests. Basic descriptive statistics are quickly and easily computed over an entire sample, by a categorization based on one or more variables, or by cross- section or period in panel or pooled data.
Hypothesis tests on mean, median and variance may be carried out, including testing against specific values, testing for equality between series, or testing for equality within a single series when classified by other variables (allowing you to perform one- way ANOVA). Tools for covariance and factor analysis allow you to examine the relationships between variables. You can visualize the distribution of your data using histograms, theoretical distribution, kernel density, or cumulative distribution, survivor, and quantile plots. QQ- plots (quantile- quantile plots) may be used to compare the distribution of a pair of series, or the distribution of a single series against a variety of theoretical distributions. You can even perform Kolmogorov- Smirnov, Liliefors, Cramer von Mises, and Anderson- Darling tests to see whether your series is distributed normally, or whether it comes from another distribution such as an exponential, extreme value, logistic, chi- square, Weibull, or gamma distribution. EViews also produces scatter plots with curve fitting using ordinary, transformation, kernel, and nearest neighbor regression. Time Series Statistics and Tools.
Explore the time series properties of your data with tools ranging from simple autocorrelation plots to frequency filters, from Q- statistics to unit root tests. EViews provides autocorrelation and partial autocorrelation functions, Q- statistics, and cross- correlation functions, as well as unit root tests (ADF, Phillips- Perron, KPSS, DFGLS, ERS, or Ng- Perron for single time series and Levin- Lin- Chu, Breitung, Im- Pesaran- Shin, Fisher, or Hadri for panel data), cointegration tests (Johansen for with Mac. Kinnon- Haug- Michelis critical values and p- values ordinary data, and Pedroni, Kao, or Fisher for panel data), causality, and independence tests. EViews also provides easy- to- use front- end support for the U.
S. Census Bureau's X1. X1. 2- ARIMA seasonal adjustment programs, as well as the Tramo/Seats software, which is quite frequently used by European researchers. Simple seasonal adjustment using additive and multiplicative difference methods is also supported in EViews. You can even use EViews to compute trends and cycles from time series data using the Hodrick- Prescott filter, Baxter- King, Christiano- Fitzgerald fixed length and Christiano- Fitzgerald asymmetric full sample band- pass (frequency) filters. Panel and Pooled Data Statistics and Tools. EViews features a wide variety of tools designed to facilitate working with both panel or pooled/time series- cross section data.
Define panel structures with virtually no limit on the number of cross- sections or groups, or on the number of periods or observations in a group. Dated or undated, balanced or unbalanced, and regular or irregular frequency panel data sets are all handled naturally within the EViews framework. Data structure tools facilitate transforming your data from stacked (panel) to unstacked (pooled) formats, and back again. Smart links, auto series, and data extraction tools, allow you to slice, match merge, frequency convert, and summarize your data with ease.
Support for basic longitudinal data analysis ranges from convenient by- group and by- period statistics, tests, and graphs, to sophisticated panel unit root (Levin- Lin- Chu, Breitung, Im- Pesaran- Shin, or Fisher) and cointegration diagnostics (Pedroni (2. Pedroni (1. 99. 9), and Kao, or the Fisher- type test). Specialized tools for displaying panel data graphs allow you to view stacked, individual, or summary displays. Display line graphs of each graph in a single graph frame or in individual frames. Or show summary statistics for the panel data taken across cross- sections, with mean (or median) and standard deviation (or quantile) bands. Estimation. EViews includes a wide range of single and multiple equation estimation techniques for both time series and cross section data.
Basic estimators include ordinary least squares (multiple regression), two- stage least squares, and nonlinear least squares. Weighted estimation is available with all of these techniques. Specifications may include polynomial lag structures on any number of independent variables.
Single Equation Estimation. EViews allows you to choose from a full set of basic single equation estimators including: ordinary and nonlinear least squares (multiple regression), weighted least squares, two- stage least squares (instrumental variables), quantile regression (including least absolute deviations estimation), and stepwise linear regression.
Weighted estimation is available for all of these techniques. Specifications may include polynomial lag structures on any number of independent variables. For time series analysis, EViews estimates ARMA and ARMAX models, and a wide range of ARCH specifications. Structural time series models may be estimated using the state space object. In addition to these basic estimators, EViews supports estimation and diagnostics for a variety of advanced models. Generalised Method of Moments.
EViews supports GMM estimation for both cross- section and time series data (single and multiple equation). Weighting options include the White covariance matrix for cross- section data and a variety of HAC covariance matrices for time series data. The HAC options include prewhitening, a variety of kernels, and fixed, Andrews, or Newey- West bandwith selection methods. You can estimate a GMM equation using either iterative procedures, or a continuously updating procedure. Post- estimation diagnostics for GMM equations, including weak instrument statistics, are also available. Limited Dependent Variables.
When your dependent variable takes on a limited set of values or is censored or truncated, EViews can take account of this information in the estimation procedure. Binary, ordered, censored, and truncated models may be estimated for likelihood functions based on normal, logistic, and extreme value errors.
Count models may use Poisson, negative binomial, and quasi- maximum likelihood (QML) specifications. EViews optionally reports generalised linear model or QML standard errors. ARCHIf the variance of your series fluctuates over time, EViews can estimate the path of the variance using a wide variety of Autoregressive Conditional Heteroskedasticity (ARCH) models. EViews handles GARCH(p,q), EGARCH(p,q), TARCH(p,q), PARCH(p,q), and Component GARCH specifications and provides maximum likelihood estimation for errors following a normal, Student's t or Generalized Error Distribution. The mean equation of ARCH models may include ARCH and ARMA terms, and both the mean and variance equations allow for exogenous variables. Limited Dependent Variables.
EViews also supports estimation of a range of limited dependent variable models. Binary, ordered, censored, and truncated models may be estimated for likelihood functions based on normal, logistic, and extreme value errors.
Count models may use Poisson, negative binomial, and quasi- maximum likelihood (QML) specifications. EViews optionally reports generalized linear model or QML standard errors. Panel Data Analysis and Pooled Time Series- Cross Section. EViews offers various panel and pooled data estimation methods. In addition to ordinary linear and non- linear least- squares, equation estimation methods include 2. SLS/IV and Generalized 2.