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History of Changes to Betahat

December 19, 2003   

 

V 4.00 of Betahat is released.  There is a new demo and help file on download page.  

The new features from V 3.2 include  

1. Stacked-Time implementation of the Newton algorithm.
2. A new function, named DEL(x:y), that will take the delta (difference) of formula y, using a lag of x time periods.
3. Tabs on the sim form to make room for all the options, including under/over relaxation,  saving the analytic derivatives, and options for setting the initial values when using the Newton or Stacked-Time Newton algorithms.
4. Excel can now be embedded in the spreadsheet tab so the user can use Excel to edit data from within Betahat.
5. Resolution of a problem where the augmented Dickey-Fuller tests were not displayed.
6. Added scalar variables as a data type.  This helps with models such as the Multimod Mark III model which use scalar parameters. 
7. Support for reading TROLL(TM) FRM data files.
8. An increase in the number of seasonal AR and seasonal MA parameters to 6 in ARIMA models.  In previous versions only 1 seasonal AR and 1 seasonal MA was allowed.
9. Another interface for specifying linear models that are nonlinear in variables.  A regression equation can be specified by entering the formulas to use as independent and dependent variables, such as "LOG(Y) CONSTANT LOG(X)" to regress the log of Y on a constant and the log of X.
10. Automatic normalization.  This allows a regression equation to be estimated (or a parameterized equation entered) and then you can specify which variable is endogenous.
11. A new type of equation, called parameterized equations, which make it easy to use equations in simulations that were not estimated in Betahat.  These also make it easy to add policy variables to a simulation.
12. A new command named ENDOGENOUS that allows the user to list the endogenous variables in a simulation when using the Newton or Stacked-Time Newton algorithm.

July 07, 2003   

We have changed the name of our econometric program from Beta to Betahat.  

V 3.20 of Betahat is released.  There is a new demo and help file on download page.  

The new features from V 3.1 include  

1. The addition of a sparse Newton (Newton-Raphson) algorithm for simulations of structural systems.  Analytic derivatives are used to evaluate the Jacobian.  Details of the implementation can be found in the help file.
2. A new simulation option that allows you to write to disk the values of each equation and identity at every iteration.  This can be used to help you track down instability in your model.
3. A new simulation option that allows you to save the jacobian for each iteration when using the Newton algorithm.

June 18, 2003   

V 3.10 of Beta is released.  There are a number of new additions to the web site associated with this.  

1. New demo and help file on download page.  
2. Updated nonlinear benchmarks and nonlinear summary on the Econometric Benchmarks page.  
3. New benchmark on the recently added random number generator.   

The new features from V 3.0 include  

1. The ability to add a tab of data to an existing Excel file, and a table to an existing Access database.
2. The option to use the Excel graphics engine on the Graph tab. 
3. A change to the command line code so that the most recently estimated model could be simulated without naming each equation.
4. More options for multivariate stochastic variance models.
5. Mersenne Twister algorithm for random numbers.
6. The ability to add a residual to stochastic equations for stochastic simulation.
7. The ability when doing a sim to easily use lagged values for undefined endogenous variables on the first iteration.  
8. A second algorithm, Jacobi, for simulations , and Ragged Edge.
9. Analytic derivatives for nonlinear least squares.
   

Version 3.0

1. Moved from 16 bit code for Windows 3.1 to 32 bit for  32 bit Windows versions. 
2. Added ability to handle > 32000 observations per series, which also required a new database format named DT3.  Tested dataset with 2,000,000 observations per series with no problem. 
3. Added ability to read Excel Files.
   

Version 2.10

1. Linear/Nonlinear Full Information Maximum Likelihood with linear/nonlinear constraints within/across equations. 
   
2. Options that define estimation methods to eliminate some pop-up menus. 
   
3. The ability to save the regression and simulation output to Lotus(tm) file format in a standardized way. This is to enable the user to automate routine forecasts with a minimum of effort. 
   
4. The addition of another algorithm for models that require general optimization.
   
5. The LOGIT model type can now allow multinomial LOGIT and a coding other than 0-1 for the dependent variable. 
   
6. A new data file format with the file extension DT2 is used which allows: 
   • Identities to be named. This is useful for users of the command/batch mode interface who previously had to rely on the USEALLIDENT option to specify identities. 
   • The addition of comments about a data series. The comments are saved with the data and can be up to 32,000 characters per series. 
   
7. The ability to write various database formats as well as read. This is useful if you need to perform SQL on data that is not in a database format. You can now read in from, say, text format, save the data in dBase, then read in the dBase format using SQL to select the observations to use. 
   
8. The command/batch mode can now read database formats with SQL in a single command. 
   
9. A much faster and memory efficient method for computing nonlinear 3SLS with the ability to impose nonlinear restrictions across equations. 
   
10. Generalized Method of Moments for systems. 
    
11. New estimators for panel data include Fixed Effects(One Way), Fixed Effects Two Factor, Random Coefficients, and Random Effects(One Way).
    
12. The ability to use stratified data for the pooled and panel estimators.
    
13. Additional methods to correct pooled models for AR-1 errors. 
    
14. Static simulations in addition to the previously available dynamic simulations.
    

Version 1.30

1. Multivariate stochastic variance.
2. Various types of Generalized Method of Moments, linear and nonlinear.
3. The addition of exogenous variables to the vector ARIMA model type.
4. Many more unit root and co-integration tests.
5. Multivariate t regression for robust regression, with uncorrelated or independent errors. 
6. The ability to create price indexes.
7. A very easy to use method to compare forecast values from one simulation to another, whether using the same model type or not.
   
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