|
Dalibor
Stevanovic's Homepage Full
professor |
|
|
LCDMA
is a large monthly Canadian dataset for macroeconomic
analysis. It contains hundreds of Canadian and provincial
economic indicators. It is designed to be updated regularly
in real-time through StatCan database and is publicly
available. It relieves users to deal with data changes and
methodological revisions. The zip file contains: (i) raw
data collected from StatCan starting from 1914; (ii)
stationary and balanced panel starting from 1981M01; (iii)
detailed data description. Data are subject to change as new
information and StatCan updates arrive.
Important
note:
This
work is a public service for academic, educational and
professional communities. Please cite the paper properly
when you use this dataset. Suggested citation:
Stevanovic,
Dalibor;
Surprenant, Stéphane; Leroux, Maxime; Fortin-Gagnon,
Olivier, 2021, "Large Canadian Database for
Macroeconomic Analysis (LCDMA) - Vintages",
https://doi.org/10.5683/SP3/59JYPU, Scholars Portal
Dataverse, V1, UNF:6:ncxLZ5kO683egg7+EUOcSw== [fileUNF] The
release schedule can be found here: Release.
Data are updated twice per month according to
important release dates and reference periods. The first
update is on the 3th Wednesday of the month (CPI
release). The second update is on the last working
day of the month (GDP by industry).
This dataset has been constructed by Fortin-Gagnon, O., Leroux, M., Stevanovic, D. and S. Surprenant (2022), A Large Canadian Database for Macroeconomic Analysis. This paper provides four useful features of this dataset. First, the factor structure explains a sizeable part of variation the dataset and appears as an appropriate mean of dimension reduction. Second, the dataset is useful to capture turning points of the Canadian business cycle. Third, it has substantial predictive power when forecasting key macroeconomic indicators. Fourth, the richness of the panel is used to study the effectiveness of the monetary policy across regions and sectors. A
quarterly dataset has been added since November 2019.
It contains quarterly averages of the monthly dataset, plus
quarterly series: GDP and its components, implicit price
indices, business indicators and income.
Real-time
vintages:
|
|