Study Challenges:
Climate change and the transition to low-carbon growth will have profound impacts on almost every sector of the economy in the decades ahead. The need to understand these effects and their implications for the economy and financial system places climate change analysis within the Bank’s mandate.
The physical effects of climate change are already apparent in the increasing number and severity of extreme weather events, such as flooding, hurricanes and wildfires. The resulting catastrophic losses can have significant, widespread impacts on the financial system. The physical risks from more frequent and intense weather events can also adversely affect several parts of the economy. For example, global warming can diminish labour productivity, agricultural yields and industrial output.
While some economic industries are directly tied to fine scale changes in climate, other industries might only be impacted after a catastrophic event. This case study uses public datasets from Government institutions to explore the potential impact of climate change and extreme weather events on economic productivity. The economic data combines various Statistics Canada data products operating at different spatial and temporal scales to produce a crude approximation of the economic productivity per industrial category within Census Subdivisions. The weather data from Canadian weather stations comes from Environment and Climate Change Canada.
The goals of the case study include any or all of:
- Describe the economic landscape in Canada with respect to its changing climate.
- Which regions are experiencing the fastest changing and have the largest potential for subsequent economic impact?
- Are there economic industries that may have already experienced observable impacts from changing climate?
- There is flexibility for you to explore other questions related to potential economic impacts of changing climate and extreme weather events.
Some R code is provided along with a description of the variables is available here.
There are 3 datafiles (zip files are linked):
- [Productivity]: Monthly economic productivity per industrial class per census subdivision
- [Geographies]: Geographic polygons representing the census subdivisions used in the productivity data.
- [Weather Data]: Recordings from Canadian weather stations with their associated latitude and longitude
The lack of timely granular data means that several approximations must be made in order to use the publicly available datasets. About the Data Sets:
- From Statistics Canada, annual provincial Gross Domestic Product (GDP) and the Labour Force Survey (LFS) were combined with monthly national GDP and the 2016 census to subdivide monthly productivity into industrial industries per geographic region. Industrial aggregation is based on the coarsest publicly available division.
- An event affecting a small region might not be noticed at the coarse scale and therefore might be lost in data aggregation and disaggregation. Similarly a large scale localized event that is sizeable enough to have a noticeable impact at the coarsest level will be subdivided equally among the census subdivisions. For example, floods in Calgary in 2013 were severe but the economic impact may have been lost in the aggregation at the provincial or annual level before being approximated back into Calgary’s Census Subdivisions.
- If a climate event damages critical infrastructure in a remote region, it might produce an impact elsewhere in the province that would be picked up by the data, but would be spread across census subdivisions.
- Geography is based on the census descriptions of where people live and not where people work. Someone may work in an industries that does not exist where they reside.
- The Monthly temperature data is based on Environment and Climate Change Canada data: https://climate.weather.gc.ca/historical_data/search_historic_data_e.html
- The data is all derived from open sources, feel free to use and / or include different data as you see fit.
The data provided abides by the data provider's license terms:
https://climate.weather.gc.ca/prods_servs/attachment1_e.html and
https://www.statcan.gc.ca/en/reference/licence
The data products do not constitute an endorsement by Statistics Canada or Environment and Climate Change Canada.
Evaluation & Grading Points
Your case study report and poster must include:
1. The research question(s) you sought to address with your analysis.
2. A discussion on the impact of your assumptions and parameters and the limitations of these types of models.
3. A summary of the key takeaways from your analysis.
Each team should design a poster that evaluates their research question(s), and present their results for approximately 10 minutes (plus an additional 8-10 minutes for discussion). The case study competition will be evaluated as follows:
1. Creative visualizations of the data (25%)
2. Appropriateness, creativity, and understanding of the strengths and limitations of proposed insights (50%)
3. Quality and clarity of presentation (25%)
Organizer Contact Information
Any concerns and questions can be directed to Dr. Dave Campbell dcampbell@bank-banque-canada.ca.
Award
We are pleased to announce that an award of \$1,000 will be given to the winning team by the Bank of Canada. In addition to the financial award, there may be potential for research and internship opportunities for successful teams.