Ontario composite economic indicator
Philip Smith (@PhilSmith26)
November 29, 2019
The monthly Ontario composite economic indicator (OCEI) is a summary measure based on 43 statistical time series from Statistics Canada. It is similar to indicators produced and updated regularly by the Chicago Federal Reserve for the US economy, Professor Trevor Tombe for the Alberta economy and Brendon Ogmundson for the BC economy. It shows how rapidly the 43 Ontario time series, collectively, are growing relative to the trend growth and is therefore an indicator of overall economic performance in the Ontario economy.
The 43 time series are diverse and cannot be aggregated directly, but jointly are a proxy for the overall economy. Annual statistics from the provincial economic accounts indicate the average annual growth rate for the Ontario economy in real terms was 1.8% during the 2001-2018 period, so that is the trend real rate of growth. The growth rate for Canada as a whole, on the same basis, is 2.0%. By way of comparison, Ontario's average growth rate in the period 1981-2001 was 3.2% and Canada's was 2.7%.
On a current dollar basis, with no adjustment for inflation, Ontario's growth rates were 6.5% for 1981-2001 and 3.6% for 2001-2018. Canada's growth rates for these periods were 5.8% and 4.0%.
To calculate the OCEI, the 43 time series are de-trended by transforming from levels to 12-month growth rates. They are normalized by subtracting the mean 12-month growth rate and dividing by the standard deviation of the 12-month growth rate. The principal components of the 43 series so transformed are then calculated. The OCEI is the principal component accounting for more of the total variance in the 43 series than any of the other principal components. In the November 2019 edition of the indicator the first principal component accounts for 29% of the total variance.
The OCEI is presented in two charts.
One shows the full indicator, from January 2002 to date. The black line is the indicator. The great recession in 2008-2009 is prominent, as is the subsequent recovery. The coloured bars represent the contributions of the 43 component time series, when they are allocated to four groups. The allocations are common-sense, but somewhat judgemental. For example, the investment group includes building permits, housing starts, SEPH construction employment and the new housing price index while the labour market group includes several series from the LFS and SEPH. It can be seen in the chart, for example, that during the great recession all of the four groups contributed substantially to the decline, while between 2012 and 2016 it was a more mixed picture.
The other chart "zooms in" on the most recent five years, allowing a clearer focus on recent developments. It shows that weakness in the investment indicators prevailed in 2018 and 2019.
The 43 economic time series making up the OCEI are listed in this spreadsheet along with their CODR (formerly CANSIM) vector identifiers and their group memberships. In a few cases, data from a different CODR vector were linked to the time series in order to create a sufficiently long time series.
The OCEI sometimes gives a crystal clear picture, as during the great recession and subsequent recovery in which the indicator groups are unanimous. However, it sometimes gives a more mixed picture with some component time series groups above trend and others below. There is divergence among the indicators in recent periods. This reflects lack of clarity in the real-world picture.
The OCEI itself is, of course, an imperfect indicator. There are under-represented sectors, due to a lack of monthly component time series. The mix of component series is imperfectly balanced and there is no role for economic theory aside from the choice of component series and groups. The indicator groups are purely judgemental, as is the allocation of component series to groups.
The OCEI is subject to revision in subsequent months due to the following reasons (in no particular order):
- Late-coming economic survey data. Sometimes business survey respondents submit data after the close-off date. These data are incorporated in the following month’s edition of the component time series.
- Changes to industry or product classifications. These occur typically every 5-to-10 years and they affect the historical component time series data.
- Survey resampling or redesigns. These occur typically every 5-to-10 years and they affect the historical component time series data.
- Recalculation of principal components. This is done every month, when additional component series data become available and revised component time series data are incorporated for previous months. An alternative, not adopted here, would be to hold the principal component weights fixed for, say, a year.
- Replacement of ARIMA forecasts with actual data. In some cases, when data are not available for the latest month for a particular component time series, forecast values are substituted temporarily, calculated with ARIMA models. These forecasts are replaced with actual data the following month, when the data become available. This is done to permit the OCEI to be released in a timely fashion.
- Seasonal adjustment. When one of the component time series is seasonally adjusted, its historical values will be revised in subsequent months when the seasonal adjustment is updated.
- Changes to the OCEI definition. From time to time the list of component time series comprising the OCEI may be changed. This results in a revised OCEI.
The plan is to release updates to the OCEI every month towards the end of the month, incorporating monthly component time series for the period two months back. Thus, for example, the September indicator is released at the end of November.
Historical OCEI data are being preserved and will permit ex post analysis of revision patterns.
(1) Organization for Economic Cooperation and Development (2008), Handbook on Constructing Composite Indicators: Methodology and User Guide, OECD Publishing, available online.
(2) United Nations Economic Commission for Europe (2019), Guidelines on producing leading, composite and sentiment indicators, United Nations Publications, available online.
Questions or comments? Message me on Twitter @PhilSmith26 or send me an email using the box at www.philipsmith.ca.