The date displayed in Picture 1 is the compilation date, i.e. the date of the installation files. However, it is
possible that some
upgrades have not yet been included
in the installation files involved. Therefore, after
installing EasyReg, it is recommended that you upgrade it, via menu item "WWW > Upgrade EasyReg to
the latest version."
ression) conducts a wide variety of econometric estimation, testing and
forecasting tasks on all 32 bit Windows platforms, simply by point-and-click. EasyReg is designed for use
in empirical research (including my own), and for teaching econometrics. In the latter case the user can
choose his or her own econometrics level.
EasyReg is called International because it accepts dots and/or commas as decimal delimiters,
regardless of the local number setting of Windows. Therefore, EasyReg runs everywhere in the world
without need to adjust the setting of Windows.
EasyReg has many advanced econometrics features, but here I will focus on data import, data
transformations, linear regression, and Box-Jenkins time series modeling and forecasting.
When you run EasyReg for the first time, most menu items are disabled, because they need data to
work. Therefore, I will show first how to import data in EasyReg.
EasyReg data files and how to import them
EasyReg can import two types of data files, Microsoft Excel files in CSV format, and EasyReg data
files in space delimited text format. I will discuss the latter type first.
EasyReg data files in space delimited text format
This type of file is a
(Notepad or Wordpad) text file with the following format. The first line
contains two numbers, the number of variables (=
), and the missing value code (=
), separated by at least
one space. The next
lines contain the names of the
variables involved. The file names may contain any
character, including spaces, commas, etc., and there is no restriction on their length. However, it is
recommended to keep the variable names short, say no more than ten characters.
The rest of the file contains
the data entries
) for observation
, separated by one or more
is the number of observations. Data entries with value
are interpreted as missing values,
= 0, which indicates that there are no missing values. Therefore, the missing value code should