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Latest version OxMetrics 9

OxMetrics™ A family of of software packages providing an integrated solution for the econometric analysis of time series, forecasting, financial econometric modelling, or statistical analysis of cross-section and panel data. The core packages of the family are OxMetrics™, which provides the user interface, data handling, and graphics, and Ox Professional™, which provides the implementation language. The other elements of the family are interactive, easy-to-use and powerful tools that can help solve your specific modelling and forecasting needs.

The following lists the new features and improvements made to the OxMetrics front end in version 9.

Explore the new solutions of OxMetrics 9.

New Solutions:

• Support for dark mode.
• New default data format: *.oxdata (this is the .in7/.bn7 files together in a zip file).
• Improved CSV reading and writing, and support for zipped CSV files.
• Improved support for high-resolution screens (HiDPI) and improved dialogs.
• Native support for Apple silicon (M1).
• DataFetch to download data from Fred, Quandle, and other data providers.
• And more.

For more information about the new version of OxMetrics, you can also visit the site of Timberlake Consultants Ltd.

OxMetrics Enterprise Edition™ is a single product that includes and integrates all the important components for theoretical and empirical research in econometrics, time series analysis and forecasting, applied economics and financial time series: OxMetrics desktop, Ox Professional, PcGive, G@RCH, and STAMP.

OxMetrics desktop™ and GiveWin™ In 2006 the OxMetrics 'desktop' replaced Givewin as the new front-end for all the members of the OxMetrics™ family. OxMetrics displays reports and graphics, which can be manipulated on screen, offers a calculator and algebraic language for transforming data, and enables the user to open multiple databases. A batch language allows for the automation of many of these tasks. OxMetrics also offers an integrated development environment for Ox programming.

Ox Professional™ (version 5) is an object-oriented programming system. Ox Professional is also part of OxMetrics Enterprise Edition. At its core is a powerful matrix language, which is complemented by a comprehensive statistical library. Among the special features of Ox are its speed (several reviewers rated it much faster than other comparable systems), well-designed syntax and editor, and graphical facilities. Ox can read and write many data formats, including spreadsheets and OxMetrics™ data and graphics files; Ox can run most econometric Gauss™ programs directly if M@ximize is added; if necessary, existing C or FORTRAN code can be added to Ox in the form of dynamic link libraries (DLLs); there is sufficient flexibility in the Ox system to allow it to be fully integrated in applications requiring an econometric or statistical engine; Ox is available on Windows, Linux, and several Unix platforms.

PcGive Professional™ is also part of OxMetrics Enterprise Edition. It provides the latest econometric techniques, from single equation methods to advanced cointegration, volatility models (GARCH, EGARCH and many variations of these models), static and dynamic panel data models, discrete choice models and time-series models such as ARFIMA(p,d,q), and X-12-ARIMA for seasonal adjustment and ARIMA modelling. PcGive is easy to use and flexible, making it suitable both for teaching and research.

STAMP 8.3 for OxMetrics 6.1 is a package designed to model and forecast time series, based on structural time series models. These models use advanced techniques, such as Kalman filtering, but are set up so as to be easy to use -- at the most basic level all that is required is some appreciation of the concepts of trend, seasonal and irregular. The hard work is done by the program, leaving the user free to concentrate on formulating models, then using them to make forecasts. STAMP is also part of OxMetrics Enterprise Edition.

G@RCH Professional™ is an OxMetrics ™ application dedicated to the estimation and forecasting of univariate ARCH-type models. G@RCH provides a user-friendly interface (with rolling menus) as well as some graphical features (through the OxMetrics graphical interface). For repeated tasks, the models can be estimated via the `Batch Editor' of OxMetrics or the Ox programming language (several example files are provided using the G@RCH class). G@RCH is also part of OxMetrics Enterprise Edition.

Ssf Pack 3.0 is a suite of C routines for carrying out computations involving the statistical analysis of univariate and multivariate models in state space form with easy-to-use functions for Ox. SsfPack allows for a full range of different state space forms: from a simple time-invariant model to a complicated multivariate time-varying model. Functions are provided to put standard models such as SARIMA, unobserved components, time-varying regressions and cubic spline models into state space form. Basic functions are available for Kalman filtering, moment smoothing and simulation smoothing. Ready-to-use functions are provided for standard tasks such as likelihood evaluation, forecasting and signal extraction. SsfPack can be easily used for implementing, fitting and analysing Gaussian models relevant to many areas of econometrics and statistics. Furthermore it provides all relevant tools for the treatment of non-Gaussian and nonlinear state space models. In particular, tools are available to implement simulation based estimation methods such as importance sampling and Markov chain Monte Carlo (MCMC) methods. SsfPack is not part of OxMetrics Enterprise Edition. Click here for more informatie.

OxMetrics 9 price request and ordering (via e-mail)

Platform: Windows, Linux en Max OS X

Economic modelling


This short introduction to macro-econometrics focuses on the concepts, tools and techniques needed to model aggregate economic data, here unemployment, wages, prices and money in the UK over a long historical period of approximately 150 years, usually 1860 – 2011, but somewhat shorter for a few of the time series.

See more :

Course Econometrics

Erasmus University Rotterdam : MOOC

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