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LIMDEP 10: Econometrics software
LIMDEP Version 10 is an integrated program for estimation and analysis of linear and nonlinear models, with cross section, time series and panel data.
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Developer: Latest release: Operating systems: Type: |
Econometric Software, Inc. 10.0 (2012) Windows XP, Vista, 7 Econometrics |
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Contents:
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Overview
LIMDEP has long been a leader in the field of econometric analysis and has provided many recent innovations including cutting edge techniques in panel data analysis, frontier and efficiency estimation and discrete choice modeling. The collection of techniques and procedures for analyzing panel data is without parallel in any other computer program available anywhere. Recognized for years as the standard software for the estimation and manipulation of discrete and limited dependent variable models, LIMDEP 10 is now unsurpassed in the breadth and variety of its estimation tools.
The main feature of the package is a suite of more than 100 built-in estimators for all forms of the linear regression model, and stochastic frontier, discrete choice and limited dependent variable models, including models for binary, censored, truncated, survival, count, discrete and continuous variables and a variety of sample selection models. No other program offers a wider range of single and multiple equation linear and nonlinear models.
LIMDEP is a true state-of-the-art program that is used for teaching and research at thousands of universities, government agencies, research institutes, businesses and industries around the world.
LIMDEP is a Complete Econometrics Package
LIMDEP takes the form of an econometrics studio. Analysis of a data set is done interactively in a set of windows. Program control may be from a script or in an unstructured session of instructions and manipulations. The program is designed to allow easy setup of data for estimation, specification of different forms of the models, experimentation with different specifications, hypothesis testing, analysis of data and model results and construction of special procedures and estimators.
LIMDEP offers a complete set of tools for econometric analysis. In addition to the estimation programs, LIMDEP provides:
- Data management, including input from all standard sources (such as Excel), all manner of transformations and sample controls
- Built-in estimation programs plus a programming language, matrix algebra package and scientific calculator that allow you to write your own estimators, test statistics and simulation and analysis programs
- Model specification and post estimation tools for simulation, hypothesis testing and partial effects for all models
- Random number, vector and matrix capabilities for bootstrapping, Gibbs sampling and Monte Carlo simulation
- A wide range of graphical and numeric descriptive statistics capabilities
- Optimization tools that allow you to construct your own likelihood, GMM, or maximum simulated likelihood estimators
- Analysis tools including graphics, numerical analysis and post estimation tools for specification and hypothesis testing
- An extensive PDF documentation set, with over 2,500 pages, containing full reference guides for the programs, background econometrics, and sample applications
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What’s New in LIMDEP Version 10?
LIMDEP 10 continues our expansion of our premier software for cross section, panel and time series data analysis. Version 10 contains major new extensions to the program for estimation and analysis of econometric models and a long list of new models and features. Our new electronic documentation with over 2,500 pages contains full reference guides for the program, background econometrics, and sample applications.
Model Estimation, Analysis and Simulation
- Interactions and Nonlinearities: Models that contain interactions, products, powers and logs of variables are now specified explicitly. The basic command structure is fully integrated throughout the entire program, not just layered on top of a few models. Every specification of every model can use this structure. This will provide a significant convenience in the specification of models. But, the major benefit of this explicit format comes in terms of how it enables you to obtain partial effects and simulations for your models
- Partial Effects: Partial effects, using the sample averages of the effects or calculations at the means of the data, can be computed automatically for any variable in any model regardless of how intricate. Effects can be simulated for specified values or ranges of variables, and tabulated or plotted with confidence intervals. The lack of appropriate calculations of partial effects for models that contain interactions and nonlinearities has been recognized as a major shortcoming of software and of many published analyses. LIMDEP’s new PARTIAL EFFECTS command solves this problem. This feature can be used with all models fit by LIMDEP, or with a function of your own that need not be part of any built in model in the program. This feature will change the way you analyze nonlinear models
- Model Simulation and Oaxaca Decomposition: The partial effects feature can also be used to simulate the prediction function (usually the conditional mean) for any model fit by LIMDEP, or any model or equation that you wish to specify in the SIMULATE command. Simulations can involve scenarios, such as tracing the sample average prediction of a probability or a count of outcomes as a function of age. The simulation feature is also useful for computing Oaxaca decompositions for subgroups of the sample. Like PARTIAL EFFECTS and SIMULATE, DECOMPOSE is used with all models built into LIMDEP, or with a function or model that you specify yourself
- Multiple Imputation: The technique of multiple imputation for handling missing data has been gaining popularity. LIMDEP’s new implementation of this technique is woven into the entire program, not just a few specific models. Any estimator, even your own created with MAXIMIZE, or any other computation involving data that produces a coefficient vector and a sampling covariance matrix, can be based on multiple imputed data sets. And, we have built this technique to bypass the need to create multiple data sets – traditionally, the need to replicate the full data set has hobbled this method. LIMDEP’s implementation of multiple imputation uses only the existing data set. The results are fully replicable as well. (You can create and save the imputed data sets if you wish).
Extensions of Estimation and Analysis Methods
- Streamlined output with additional test and diagnostic statistics
- Restrictions and hypothesis tests in all models
- Simpler natural format for model specification
- Single step estimation for testing multiple hypotheses
- Numerous new features for user written iterative and looping procedures
- New Wald features for computing standard errors
- Sample average functions as an alternative to computing functions at the means of the data
- Variances using the delta method account for the averaging procedure
- Multiple new functions for matrix algebra program
- Expanded graphics capabilities
- New additions for kernel density estimation, including plotting multiple KDEs in the same figure
- Contour plots
- Enhanced tools for creating and labeling graphs
- Robust covariance estimators for linear models
- Jackknife and bootstrap estimators for standard errors and confidence intervals and for large sample behavior of test statistics
- Extension of panel data to nearly all model frameworks
New Models and Data Analysis Settings
We continue to develop and implement new models that appear in the literature. Some of the model frameworks that have been added in LIMDEP 10 include:
- Models for count data:
- Zero truncation for count data models with panel data
- NB-X – negative binomial model for underdispersion
- NB-E – negative binomial model with endogenous truncation (on site sampling)
- Poisson and negative binomial models with endogenous treatment effects
- Poisson – inverse gauss mixture
- Generalized Poisson with zero inflation and 1/2/P nested functional forms
- Count data hurdle models with endogenous participation
- Non- and semiparametric regression models:
- Lowess nonparametric regression
- QREG for quantile regression
- QCREG for quantile regression for count data
- LIML estimator for regression with endogenous RHS variables
- Binary and ordered choice:
- Ordered probit with endogenous treatment effects
- Generalized ordered choice with random parameters and thresholds
- Fractional response model for panel data
- Arc tangent model for binary choice
- Stochastic frontier:
- FRONTIER with nonparametric frontier function
- Battese-Coelli panel data frontier models
- New automated tools for specification tests and calculations such as technical efficiencies
- MAXIMIZE/MINIMIZE with random parameters
- Numerical Analysis
- FUNCTION to plot and simulate any specified function
- SOLVE to locate the solutions to f(x)=0
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Prices
| LIMDEP & NLOGIT |
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To order LIMDEP & NLOGIT software, please contact our sales team either by email: info@timberlake.co.uk, phone: +44 (0) 20 8697 3377 or fill out an online order form.
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