The USD/CAD exchange rate rose to 1.3815 on August 15, 2025, up 0.01% from the previous session. Over the past month, the Canadian Dollar has weakened 0.91%, and is down by 1.00% over the last 12 months. Canadian Dollar - values, historical data, forecasts and news - updated on August of 2025.

Number of persons in the labour force (employment and unemployment), unemployment rate, participation rate and employment rate by data type (seasonally adjusted and trend-cycle), gender and age group. Data are also available for the standard error of the estimate, the standard error of the month-to-month change and the standard error of the year-over-year change.

The benchmark interest rate in Canada was last recorded at 2.75 percent. This dataset provides - Canada Interest Rate - actual values, historical data, forecast, chart, statistics, economic calendar and news.

Number of employees by North American Industry Classification System (NAICS) and data type (seasonally adjusted, trend-cycle and unadjusted), last 5 months. Data are also available for the standard error of the estimate, the standard error of the month-to-month change and the standard error of the year-over-year change.

This first version of the dataset (CanHoPmlyV1) contains homogenized time series of monthly total precipitation for 425 long-term stations in Canada. As detailed in Wang et al. (2023), it is based on the quality-controlled version 2020 of the Adjusted Daily Rainfall and Snowfall (AdjDlyRS) dataset (Wang et al. 2017; available at https://open.canada.ca/data/en/dataset/d8616c52-a812-44ad-8754-7bcc0d8de305), and on daily total precipitation data from automated gauges (including Belfort, Fisher & Porter, Nipher, Geonor, and Pluvio), with some records from neighbouring stations being joined to form long-term data series. Version 1 of ANUSPLIN surfaces of the adjusted monthly precipitation (MacDonald et al. 2021, available at https://open.canada.ca/data/en/dataset/779ea77a-0ad1-42f2-853e-833e1cbb9a13) was used to infill temporal data gaps in the 425 data series. A comprehensive semi-automatic data homogenization procedure was used to homogenize the data series. The aforementioned ANUSPLIN data and the Twentieth Century Reanalysis 20CRv3 ensemble-mean series of monthly precipitation (Slivinski et al., 2021) were used as reference in the homogeneity tests (Wang et al., 2023). The homogenized dataset provides more realistic trend estimates and shows better spatial consistency of trends than does the raw dataset (Wang et al. 2023). References: Wang, X.L, Y. Feng, V. Y. S. Cheng, H. Xu, 2023: Observed precipitation trends inferred from Canada’s homogenized monthly precipitation dataset, J. Clim., in press. DOI: 10.1175/JCLI-D-23-0193.1. Wang, X. L., H. Xu, B. Qian, Y. Feng, E. Mekis, 2017: The adjusted daily rainfall and snowfall data for Canada. Atmosphere-Ocean, 55:3, 155-168, DOI:10.1080/07055900.2017.1342163. MacDonald, H., D. W. McKenney, X. L. Wang, J. Pedlar, P. Papadopol, K. Lawrence, M. F. Hutchinson, 2021: Spatial Models of adjusted precipitation for Canada at varying time scales. J. Appl. Meteor. And Climatol., 60, 291-304. DOI: 10.1175/JAMC-D-20-0041.1. Slivinski, L. and coauthors, 2019: Towards a more reliable historical reanalysis: Improvements for version 3 of the Twentieth Century Reanalysis system. Q. J. R. Meteor. Soc., 2876-2908, https://doi.org/10.1002/qj.3598.

The data consist of homogenized daily maximum, minimum and mean surface air temperatures for more than 330 locations in Canada; adjusted daily rainfall, snowfall and total precipitation for more than 460 locations. The data are given for the entire period of observation. Please refer to the papers below for detailed information regarding the procedures for homogenization and adjustment. References: Mekis, É. and L.A. Vincent, 2011: An overview of the second generation adjusted daily precipitation dataset for trend analysis in Canada. Atmosphere-Ocean, 49(2), 163-177. Vincent, L. A., X. L. Wang, E. J. Milewska, H. Wan, F. Yang, and V. Swail, 2012. A second generation of homogenized Canadian monthly surface air temperature for climate trend analysis, J. Geophys. Res., 117, D18110, doi:10.1029/2012JD017859. Wang, X.L, Y. Feng, L. A. Vincent, 2013. Observed changes in one-in-20 year extremes of Canadian surface air temperatures. Atmosphere-Ocean. Doi:10.1080/07055900.2013.818526.

Inflation Rate in Canada increased to 1.90 percent in June from 1.70 percent in May of 2025. This dataset provides - Canada Inflation Rate - actual values, historical data, forecast, chart, statistics, economic calendar and news.

Overview: Each quarter, the Temporary Foreign Worker Program (TFWP) publishes Labour Market Impact Assessment (LMIA) statistics on Open Government Data Portal, including quarterly and annual LMIA data related to, but not limited to, requested and approved TFW positions, employment location, employment occupations, sectors, TFWP stream and temporary foreign workers by country of origin. The TFWP does not collect data on the number of TFWs who are hired by an employer and have arrived in Canada. The decision to issue a work permit rests with Immigration, Refugees and Citizenship Canada (IRCC) and not all positions on a positive LMIA result in a work permit. For these reasons, data provided in the LMIA statistics cannot be used to calculate the number of TFWs that have entered or will enter Canada. IRCC publishes annual statistics on the number of foreign workers who are issued a work permit: https://open.canada.ca/data/en/dataset/360024f2-17e9-4558-bfc1-3616485d65b9. Please note that all quarterly tables have been updated to NOC 2021 (5 digit and training, education, experience and responsibilities (TEER) based). As such, Table 5, 8, 17, and 24 will no longer be updated but will remain as archived tables. Frequency of Publication: Quarterly LMIA statistics cover data for the four quarters of the previous calendar year and the quarter(s) of the current calendar year. Quarterly data is released within two to three months of the most recent quarter. The release dates for quarterly data are as follows: Q1 (January to March) will be published by early June of the current year; Q2 (April to June) will be published by early September of the current year; Q3 (July to September) will be published by early December of the current year; and Q4 (October to December) will be published by early March of the next year. Annual statistics cover eight consecutive years of LMIA data and are scheduled to be released in March of the next year. Published Data: As part of the quarterly release, the TFWP updates LMIA data for 28 tables broken down by: TFW positions: Tables 1 to 10, 12, 13, and 22 to 24; LMIA applications: Tables 14 to 18; Employers: Tables 11, and 19 to 21; and Seasonal Agricultural Worker Program (SAWP): Tables 25 to 28. In addition, the TFWP publishes 2 lists of employers who were issued a positive or negative LMIA: Employers who were issued a positive LMIA by Program Stream, NOC, and Business Location (https://open.canada.ca/data/en/dataset/90fed587-1364-4f33-a9ee-208181dc0b97/resource/b369ae20-0c7e-4d10-93ca-07c86c91e6fe); and Employers who were issued a negative LMIA by Program Stream, NOC, and Business Location (https://open.canada.ca/data/en/dataset/f82f66f2-a22b-4511-bccf-e1d74db39ae5/resource/94a0dbee-e9d9-4492-ab52-07f0f0fb255b). Things to Remember: 1. When data are presented on positive or negative LMIAs, the decision date is used to allocate which quarter the data falls into. However, when data are presented on when LMIAs are requested, it is based on the date when the LMIA is received by ESDC. 2. As of the publication of 2022Q1- 2023Q4 data (published in April 2024) and going forward, all LMIAs in support of 'Permanent Residence (PR) Only' are included in TFWP statistics, unless indicated otherwise. All quarterly data in this report includes PR Only LMIAs. Dual-intent LMIAs and corresponding positions are included under their respective TFWP stream (e.g., low-wage, high-wage, etc.) This may impact program reporting over time. 3. Attention should be given for data that are presented by ‘Unique Employers’ when it comes to manipulating the data within that specific table. One employer could be counted towards multiple groups if they have multiple positive LMIAs across categories such as program stream, province or territory, or economic region. For example, an employer could request TFWs for two different business locations, and this employer would be counted in the statistics of both economic regions. As such, the sum of the rows within these ‘Unique Employer’ tables will not add up to the aggregate total.

Monthly average retail prices for selected products, for Canada and provinces. Prices are presented for the current month and the previous four months. Prices are based on transaction data from Canadian retailers, and are presented in Canadian current dollars.

This table contains 27 series, with data starting from 1981 (not all combinations necessarily have data for all years). This table contains data described by the following dimensions (Not all combinations are available): Geography (1 item: Canada) Type of currency (27 items: Australian dollar, monthly average; Brazilian real, monthly average; Chinese renminbi, monthly average; European euro, monthly average; ...).

Income of individuals by age group, sex and income source, Canada, provinces and selected census metropolitan areas, annual.

Annual indexes for major components and special aggregates of the Consumer Price Index (CPI), for Canada, provinces, Whitehorse, Yellowknife and Iqaluit. Data are presented for the last five years. The base year for the index is 2002=100.

Introducing the Indeed Job Postings Index

Hiring Lab's Job Postings Tracker is being re-released as the Indeed Job Postings Index. By Chris Glynn

Indeed Hiring Lab is re-releasing our Job Postings Tracker as the Indeed Job Postings Index, a daily measure of labor market activity that is updated and will continue to be released weekly. Covering seven national markets in the US, Canada, United Kingdom, Ireland, France, Germany, and Australia, the Indeed Job Postings Index meets one of Hiring Lab’s primary goals: produce high quality and high frequency labor market metrics using Indeed’s proprietary data.

The primary difference between the Indeed Job Postings Index and the legacy Job Postings Tracker is the level. The Indeed Job Postings Index is set to 100 on February 1, 2020, and this effectively provides a uniform level shift of 100 to the existing Job Postings Tracker across all time points.The Job Postings Tracker measured the percent change in postings from February 1st, 2020. For example, if the Job Postings Tracker were 40%, the corresponding Indeed Job Postings Index on the same date would be 140. Additionally, we are now including year-over-year and month-over-month percent changes in the Indeed Job Postings Index as part of our data portal on hiringlab.org/data and on our GitHub page. Month-over-month changes are calculated as 28 day (4 week) differences to control for day of week.

As Covid-19 fades from the global labor market discussion, moving to an index better reflects current economic conditions. The Indeed Job Postings Index allows us to compare job postings more naturally across flexible date ranges as opposed to comparing to the pre-pandemic baseline. It also places Indeed’s job postings metric in a broader class of macroeconomic indexes such as the Case Shiller Index that measures house price appreciation and the Consumer Price Index that measures inflation.

Data Schema Each market covered by a Hiring Lab economist has a folder in this repo. Each folder contains the following files:

aggregate_job_postings_{country_code}.csv This file contains the % change in seasonally-adjusted postings since February 1, 2020 for total job postings and new jobs postings (on Indeed for 7 days or fewer) for that market, as well as non-seasonally adjusted postings since February 1, 2020 for total job postings.

job_postings_by_sector_{country_code}.csv This file contains the % change in seasonally-adjusted postings since February 1, 2020 for occupational sectors for that market. We do not share sectoral data for Ireland.

For certain markets, we also share subnational job postings trends. In the United States, we provide:

metro_job_postings_us.csv This file contains the % change in seasonally-adjusted postings since February 1, 2020 for total job postings in US metropolitan areas with a population of at least 500,000 people.

state_job_postings_us.csv This file contains the % change in seasonally-adjusted postings since February 1, 2020 for total job postings in the US states and the District of Columbia.

In Canada, we provide:

provincial_postings_ca.csv This file contains the % change in seasonally-adjusted postings since February 1, 2020 for total job postings in each Canadian provinces. In the United Kingdom, we provide:

regional_postings_gb.csv This file contains the % change in seasonally-adjusted postings since February 1, 2020 for total job postings in each region in the UK.

city_postings_gb.csv This file contains the % change in seasonally-adjusted postings since February 1, 2020 for total job postings in each city in the UK.

Github link: https://github.com/hiring-lab/job_postings_tracker#data-schema Hiring Lab Link: https://www.hiringlab.org/2022/12/15/introducing-the-indeed-job-postings-index/

People who have been granted permanent resident status in Canada. Please note that in these datasets, the figures have been suppressed or rounded to prevent the identification of individuals when the datasets are compiled and compared with other publicly available statistics. Values between 0 and 5 are shown as “--“ and all other values are rounded to the nearest multiple of 5. This may result to the sum of the figures not equating to the totals indicated.

This table contains 45 series, with data for years 1950 - 2015 (not all combinations necessarily have data for all years), and was last released on 2016-01-05. This table contains data described by the following dimensions (Not all combinations are available): Geography (1 items: Canada ...), Type of currency (45 items: United States dollar; noon spot rate; average; Danish krone; noon spot rate; average; French franc; noon spot rate; average; Belgian franc; noon spot rate; average ...).

The suite of gridded precipitation datasets includes the ANUSPLIN-gridded datasets of daily precipitation since 1900 (ANUSPLIN-AdjPdly), pentad average precipitation rates since 1950 (ANUSPLIN-AdjP5d), and monthly total precipitation since 1872 (ANUSPLIN-AdjPmly), on a 0.083333ºx 0.083333º latitude-longitude grid over Canada. For version 1 of these datasets, the daily precipitation data were generated from the ANUSPLIN surfaces fitted to the Adjusted Daily Rainfall and Snowfall (AdjDlyRS) dataset version 2016, which includes 3346 stations of manual observations (Wang et al. 2017; available at https://open.canada.ca/data/en/dataset/d8616c52-a812-44ad-8754-7bcc0d8de305). The monthly and pentad gridded data were generated from the ANUSPLIN surfaces fitted respectively to the monthly and pentad station data that were derived from the corresponding daily station data. When deriving the monthly station data from the daily station data, the monthly total precipitation was set to missing if there was one or more missing daily value in the month (zero tolerance for missing). The same zero tolerance for missing observations was applied in the calculation of the pentad average precipitation rates. Details of the ANUSPLIN modelling of these three gridded precipitation datasets are provided in MacDonald et al. (2020), along with comparison to the unadjusted ANUSPLIN-gridded daily precipitation dataset (Hutchinson et al. 2009). Note that the unadjusted precipitation data significantly underestimate both the precipitation amount and the regional mean long-term trend therein (MacDonald et al. 2020). It is important to point out that these ANUSPLIN-AdjP datasets are not homogenized and thus should not be used to assess climate trends/changes before ensuring the temporal homogeneity of the data. Considering there were no or few stations in the North in the early period, the gridded values in the period before 1930 were set to missing (missing code -999.00) for all gridpoints north of 65ºN and west of 110ºW (including 110ºW) and for all gridpoints north of 55ºN and east of 110ºW. The gridded values in the period of 1930-1949 were also set to missing for all gridpoints north of 70ºN. For the period from 1950 onwards, the grid covers the whole land mass of Canada. References: (1) MacDonald, H., D.W. McKenney, X.L. Wang, J. Pedlar, P. Papadopol, K. Lawrence, and M.F. Hutchinson, 2021: Spatial models of adjusted precipitation for Canada at varying time scales. J. Appl. Meteor. Climatol., 60, 291-304. doi: 10.1175/JAMC-D-20-0041.1. (2) Wang, X.L., H. Xu, B. Qian, Y. Feng, and E. Mekis, 2017: Adjusted daily rainfall and snowfall data for Canada. Atmos.-Ocean, 55, 155–168, doi:10.1080/07055900.2017.1342163. (3) Hutchinson, M.F.,D.W. McKenney, K. Lawrence, J.H. Pedlar, R. F.Hopkinson, E.Milewska, and P. Papadopol, 2009: Development and testing of Canada-wide interpolated spatial models of daily minimum–maximum temperature and precipitation for 1961–2003. J. Appl. Meteorol. Climatol., 48, 725-741. doi:10.1175/2008JAMC1979.1.

The gridded dataset of homogenized monthly mean values of daily maximum, minimum and mean surface air temperatures, CanGridT, was produced using a kriging-based gridding scheme, i.e., the KGNGA scheme of Abbasnezhadi and Wang (2024), to grid an updated version of the Third Generation of Homogenized Temperature dataset (see details below). More specifically, ordinary kriging was used to grid the 1961-1990 climate normal values and the anomalies, separately; the resulting gridded datasets were used to produce the gridded dataset of monthly mean values of daily maximum, minimum and mean temperatures. Here, daily mean temperature is the average of daily maximum and minimum temperatures. As detailed in Vincent et al. (2020), the Third Generation of Homogenized Temperature dataset (available at Climate data: homogenized surface air temperature data - Canada.ca) was prepared for use in climate trend analysis in Canada. Daily observations from nearby sites were often joined to create a long data series. This includes the observations taken at Reference Climate Stations and from some of the NavCan sites which are used to extend past climate observations into recent times. This dataset contains long data series of daily maximum, minimum and mean temperatures for 780 locations across Canada. The data were quality controlled. The daily minimum temperatures from 1961 to recent years were adjusted to diminish the effects of the change in observing time (climatological day definition) in 1961 at principal stations (Vincent et al. 2009). In cases of station joining, parallel daily data, when available, were used to detect and diminish non-climatic shifts (Vincent et al. 2018), as using parallel observations is the most reliable way to do data homogenization. Series of annual and seasonal mean temperatures were tested for homogeneity and homogenized when necessary. Daily temperatures were adjusted using a Quantile-Matching procedure (Wang et al. 2010) to remove non-climatic shifts if needed. The Third Generation of Homogenized Temperature dataset has been updated to the end of 2023, in which around 500 out of the 780 stations are active (reporting some data). The gridded version of the updated dataset is this CanGridT mlyV3.1 dataset, which has been used to assess warming in Canada. This dataset differs from the CanGRD data in two aspects: CanGridT contains gridded temperatures on a 10-km EASE grid, while CanGRD contains gridded anomalies of temperatures on a 50-km EASE grid. References Abbasnezhadi, K. and X. L. Wang, 2024: Comparison of gridding methods for precipitation over Canada and assessment of station/data density effects on gridding results. Atmos.-Ocean, 62:4, 320-346, https://doi.org/10.1080/07055900.2024.2394829. Vincent, L.A., M.M. Hartwell and X.L. Wang, 2020: A Third Generation of Homogenized Temperature for Trend Analysis and Monitoring Changes in Canada’s Climate. Atmosphere-Ocean. https://doi.org/10.1080/07055900.2020.1765728. Vincent, L.A., E.J. Milewska, X. L. Wang, and M. M. Hartwell, 2018. Uncertainty in homogenized daily temperatures and derived indices of extremes illustrated using parallel observations in Canada, Intl. J. Climatol., 38:2, 692-707. DOI: 10.1002/JOC.5203. Vincent, L.A., E.J. Milewska, R. Hopkinson and L. Malone, 2009: Bias in minimum temperature introduced by a redefinition of the climatological day at the Canadian synoptic stations. Journal of Applied Meteorology and Climatology, 48, 2160-2168. DOI: 10.1175/2009JAMC2191.1. Wang, X. L., H. Chen, Y. Wu, Y. Feng, and Q. Pu, 2010: New techniques for detection and adjustment of shifts in daily precipitation data series. J. Appl. Meteor. Climatol., 49, 2416-2436. DOI: 10.1175/2010JAMC2376.1.

The yield on Canada 10Y Bond Yield eased to 3.44% on August 18, 2025, marking a 0.03 percentage point decrease from the previous session. Over the past month, the yield has fallen by 0.16 points, though it remains 0.37 points higher than a year ago, according to over-the-counter interbank yield quotes for this government bond maturity. Canada 10-Year Government Bond Yield - values, historical data, forecasts and news - updated on August of 2025.

Temporary residents who are in Canada on a study permit in the observed calendar year. Datasets include study permit holders by year in which permit(s) became effective or with a valid permit in a calendar year or on December 31st. Please note that in these datasets, the figures have been suppressed or rounded to prevent the identification of individuals when the datasets are compiled and compared with other publicly available statistics. Values between 0 and 5 are shown as “--“ and all other values are rounded to the nearest multiple of 5. This may result to the sum of the figures not equating to the totals indicated.

The first version of this gridded dataset (on a 10-km EASE grid) of monthly total precipitation amounts was produced using a kriging-based gridding scheme to grid the Canadian homogenized monthly precipitation dataset CanHoPmlyV1 (Wang et al. 2023; available at https://open.canada.ca/data/dataset/1dd0c28e-2266-42e2-8985-2f47659e9d02). More specifically, ordinary kriging was used to grid the 1961-1990 climate normal values and the relative anomalies, separately; the resulting gridded datasets were used to produce this gridded dataset of monthly total precipitation amounts (Wang et al. 2023, Abbasnezhadi and Wang, 2024). As detailed in Wang et al. (2023), CanHomPmlyV1 is based on the quality-controlled version 2020 of the Adjusted Daily Rainfall and Snowfall (AdjDlyRS) dataset (Wang et al. 2017, available at https://open.canada.ca/data/en/dataset/d8616c52-a812-44ad-8754-7bcc0d8de305), and on daily total precipitation data from automated gauges (including Belfort, Fisher & Porter, Nipher, Geonor, and Pluvio), with some records from neighbouring stations being joined to form long-term data series. Version 1 of ANUSPLIN surfaces of the adjusted monthly precipitation (MacDonald et al. 2021) was used to infill temporal data gaps in the 425 data series. A comprehensive semi-automatic data homogenization procedure was used to homogenize the data series. The aforementioned ANUSPLIN data and the Twentieth Century Reanalysis 20CRv3 ensemble-mean series of monthly precipitation (Slivinski et al., 2019) were used as reference in the homogeneity tests (Wang et al., 2023). The homogenized dataset CanHoPmlyV1, and its gridded version CanGridP mlyV1, which was called CanKrig mlyPv1 in Wang et al. (2023), provide more realistic estimates of precipitation trends (Wang et al. 2023). Although the latter is much better than the pre-existing CanGRD precipitation relative anomalies data, both gridded datasets contain biases due to changes in data availability over time and space (i.e., inhomogeneous sampling), which are non-negligible in the early period. Such biases are being assessed and corrected to produce a sampling bias-corrected gridded dataset CanGridP mlyV2 (upcoming). References: Abbasnezhadi, K. and X. L. Wang, 2024: Comparison of gridding methods for precipitation over Canada and assessment of station/data density effects on gridding results. Atmos.-Ocean, 62:4, 320-346, https://doi.org/10.1080/07055900.2024.2394829. Wang, X.L, Y. Feng, V. Y. S. Cheng, H. Xu, 2023: Observed precipitation trends inferred from Canada’s homogenized monthly precipitation dataset, J. Clim., 36, 7957-7971. DOI: 10.1175/JCLI-D-23-0193.1. Wang, X. L., H. Xu, B. Qian, Y. Feng, E. Mekis, 2017: The adjusted daily rainfall and snowfall data for Canada. Atmos.-Ocean, 55:3, 155-168, DOI:10.1080/07055900.2017.1342163. MacDonald, H., D. W. McKenney, X. L. Wang, J. Pedlar, P. Papadopol, K. Lawrence, M. F. Hutchinson, 2021: Spatial Models of adjusted precipitation for Canada at varying time scales. J. Appl. Meteor. And Climatol., 60, 291-304. DOI: 10.1175/JAMC-D-20-0041.1. Slivinski, L. and coauthors, 2019: Towards a more reliable historical reanalysis: Improvements for version 3 of the Twentieth Century Reanalysis system. Q. J. R. Meteor. Soc., 2876-2908, https://doi.org/10.1002/qj.3598.