This paper compares quasi Monte Carlo methods, in particular so– called (t,m, s)–nets, with classical Monte Carlo approaches for simulating econometric time–series models. Quasi Monte Carlo methods have found successful application in many fields, such as physics, image processing, and the evaluation of finance derivatives. However, they are rarely used in econometrics. Here, we apply both trad...

because of the increasing importance of supplying water for the country, water resource management is of paramount importance. predicting precipitation, as one of the most important climatic parameters, is especially important in using water supplies. time series can be used to predict precipitation. time series analysis seems to be a suitable tool for such forecasting. the present work studies...

In this paper, a combined cross-section and time-series econometric analysis of Spanish regional growth is presented. This analysis operates with a database where the number of cross-sectional units is small for a typical panel of data, while the time dimension is clearly dominant. First, using recent techniques in the econometric analysis of panel data (both panel unit root and panel co-integr...

This work presents the software framework JStatComwhich is geared towards the development of powerful graphical user interfaces for data based analysis methods, especially for econometrics and time series analysis. The concept is to solve all recurring tasks with the help of Java classes and to delegate the execution of special algorithms to external programs, for example Gauss or Matlab. This ...

This report surveys six influential econometric textbooks in terms of their mathematical treatment of causal concepts. It highlights conceptual and notational differences among the authors and points to areas where they deviate significantly from modern standards of causal analysis. We find that econonometric textbooks vary from complete denial to partial acceptance of the causal content of eco...