Prepare Time Series Data for Econometric Modeler App

These examples show how to prepare time series data at the MATLAB^® command line for use in the Econometric Modeler app.

You can import only one variable into Econometric Modeler. The variable can exist in the MATLAB Workspace or a MAT-file.

A row in a MATLAB timetable contains simultaneously sampled observations. When you import a timetable, the app plots associated times on the x axis of time series plots and enables you to overlay recession bands on the plots. Therefore, these examples show how to create timetables for univariate and multivariate time series data. For other supported data types and variable orientation, see Prepare Data for Econometric Modeler App.

Prepare Table of Multivariate Data for Import

This example shows how to create a MATLAB timetable from synchronized data stored in a MATLAB table. The data set contains annual Canadian inflation and interest rates from 1954 through 1994.

At the command line, clear the Workspace, then load the Data_Canada.mat data set. Display all variables in the workspace.

clear all
load Data_Canada
whos

   Name              Size            Bytes  Class     Attributes

  Data             41x5              1640  double              
  DataTable        41x5              8379  table               
  Description      34x55             3740  char                
  dates            41x1               328  double              
  series            1x5               918  cell         

Data and DataTable contain the time series, and dates contains the sampling years as a numeric vector. The row names of DataTable are the sampling years. For more details about the data set, enter Description at the command line.

Clear the row names of DataTable.

DataTable.Properties.RowNames = {};

Convert the sampling years to a datetime vector. Specify the years, and assume that measurements were taken at the end of December. Specify that the time format is the sampling year.

dates = datetime(dates,12,31,'Format','yyyy');

Convert the table DataTable to a timetable by associating the rows with the sampling times in dates.

DataTable = table2timetable(DataTable,'RowTimes',dates);

DataTable is a timetable containing the five time series and a variable named Time representing the time base. DataTable is prepared for importing into Econometric Modeler.

If your time series are not synchronized (that is, do not share a common time base), then you must synchronize them before you import them into the app. For more details, see synchronize and Combine Timetables and Synchronize Their Data.

Prepare Numeric Vector for Import

This example shows how to create a timetable from a univariate time series stored as a numeric column vector. The data set contains the quarterly US gross domestic product (GDP) prices from 1947 through 2005.

At the command line, clear the workspace, then load the Data_GDP.mat data set. Display all variables in the workspace.

clear all
load Data_GDP
whos

  Name               Size            Bytes  Class     Attributes

  Data             234x1              1872  double              
  Description       22x59             2596  char                
  dates            234x1              1872  double

Data contains the time series, and dates contains the sampling times as serial date numbers. For more details about the data set, enter Description at the command line.

Convert the sampling times to a datetime vector. By default, MATLAB stores the hours, minutes, and seconds when converting from serial date numbers. Remove these clock times from the data.

dates = datetime(dates,'ConvertFrom','datenum','Format','ddMMMyyyy',...
     'Locale','en_US');

Create a timetable containing the data, and associate each row with the corresponding sampling time in dates. Name the variable GDP.

DataTable = timetable(Data,'RowTimes',dates,'VariableNames',{'GDP'});

DataTable is a timetable, and is prepared for importing into Econometric Modeler.