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              8107  table                  
  DataTimeTable      41x5              3827  timetable              
  Description        34x55             3740  char                   
  dates              41x1               328  double                 
  series              1x5               878  cell                   

Data, DataTable, and DataTimeTable 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.

Time series plots in Econometric Modeler label the x-axis with sampling times when they are attached to the data. Although you can import DataTimeTable to use this feature, consider preparing DataTable as a timetable.

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.

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

DTT is a timetable containing the five time series and a variable named Time representing the time base. DTT 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                 
  DataTable          234x1             32337  table                  
  DataTimeTable      234x1              4727  timetable              
  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.

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

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