[36100229] Long-run provincial and territorial data
Updated on DBnomics on April 4, 2022 (6:26 PM).
This table contains long-run estimates of economic variables for the provinces and territories. The data are assembled in a fashion that facilitates examinations of economic performance over extended time horizons. Estimates contained in the dataset relate to prices, income and population. The data were originally compiled for the following research paper: M. Brown and R. Macdonald, 2015, Provincial Convergence and Divergence in Canada, 1926 to 2011, Statistics Canada Catalogue no. 11F0027M, Ottawa, Ontario, Economic Analysis Research Paper Series, no. 096. For additional discussion on data construction and data sources, see R. Macdonald, 2015, Constructing Provincial Time Series: A Discussion of Data Sources and Methods, Statistics Canada Catalogue no. 13-604-M, Ottawa, Ontario, Income and Expenditure Accounts Technical Series , no. 077 and R. Macdonald, 2018, Data Sources and Linking Methods for Long-run Provincial and Territorial Data: An Update for Gross Domestic Product, Urbanization, Unemployment and Depreciation, Statistics Canada Catalogue no. 11-633-X, Ottawa, Ontario, Analytical Studies Methods and References Series, no. 2018018. Data for the territories are not presented separately in historical data sources. Consequently, aggregations of Yukon, the Northwest Territories and Nunavut or of the Northwest Territories including Nunavut are presented to extend the data available for these units. For additional discussion on data construction and data sources, see R. Macdonald, 2015, Constructing Provincial Time Series: A Discussion of Data Sources and Methods, Statistics Canada Catalogue no. 13-604-M, Ottawa, Ontario, Income and Expenditure Accounts Technical Series , no. 077 and R. Macdonald, 2018, Data Sources and Linking Methods for Long-run Provincial and Territorial Data: An Update for Gross Domestic Product, Urbanization, Unemployment and Depreciation, Statistics Canada Catalogue no. 11-633-X, Ottawa, Ontario, Analytical Studies Methods and References Series, no. 2018018. Sigma is the standard deviation of the observations. It is calculated for two groups of provinces. The first group consists of all 10 provinces. For years before 1949, Newfoundland and Labrador is not present. The second group consists of all provinces except for Alberta, Saskatchewan and, after 1996, Newfoundland and Labrador. These provinces are excluded because their behaviour is associated with the convergence-divergence dynamic across provinces. For more information, see M. Brown and R. Macdonald, 2015, Provincial Convergence and Divergence in Canada, 1926 to 2011, Statistics Canada Catalogue no. 11F0027M, Ottawa, Ontario, Economic Analysis Research Paper Series, no. 096. Data source indicators: A - Currently produced data; B - Historical data linked to current data; C - Historical estimates constructed using an instrumental variables technique. Data are rounded to improve time series consistency and may be reported with a lag when compared to population program estimates. For the most recent unrounded data please see CANSIM table 051-0001 or CANSIM table 051-0005.
[freq] Frequency
- [A] Annual
[geogr] Geography
- [geogr_1] Canada
- [geogr_10] All provinces excluding Alberta, Saskatchewan and Newfoundland and Labrador
- [geogr_11] Newfoundland and Labrador
- [geogr_12] Prince Edward Island
- [geogr_13] Nova Scotia
- [geogr_14] New Brunswick
- [geogr_15] Quebec
- [geogr_16] Ontario
- [geogr_17] Manitoba
- [geogr_18] Saskatchewan
- [geogr_2] Alberta
- [geogr_3] British Columbia
- [geogr_4] Yukon, Northwest territories, Nunavut
- [geogr_5] Yukon
- [geogr_6] Northwest territories including Nunavut
- [geogr_7] Northwest territories
- [geogr_8] Nunavut
- [geogr_9] All provinces
[sta_mea] Statistical measures
- [sta_mea_1] Linked data
- [sta_mea_2] Sigma
[lon_run_var] Long-run variables
- [lon_run_var_1] Household income per capita
- [lon_run_var_10] Final consumption expenditure per capita
- [lon_run_var_11] Gross fixed capital formation per capita
- [lon_run_var_12] Household disposable income per capita
- [lon_run_var_13] Residential gross fixed capital formation per capita
- [lon_run_var_14] Non-residential gross fixed capital formation per capita
- [lon_run_var_15] Investment in inventories per capita
- [lon_run_var_16] Net exports plus statistical discrepency per capita
- [lon_run_var_17] Final domestic demand per capita
- [lon_run_var_18] Consumption of fixed capital per capita
- [lon_run_var_19] Net domestic product per capita
- [lon_run_var_2] Linked residential gross fixed capital formation price index
- [lon_run_var_20] Real gross domestic income (GDI) per capita
- [lon_run_var_21] Real final domestic demand per capita
- [lon_run_var_22] Real final consumption expenditure per capita
- [lon_run_var_23] Compensation of employees per capita
- [lon_run_var_24] Real gross fixed capital formation per capita
- [lon_run_var_25] Real residential gross fixed capital formation per capita
- [lon_run_var_26] Real non-residential gross fixed capital formation per capita
- [lon_run_var_27] Saving rate (provincial/national)
- [lon_run_var_28] Investment rate - residential
- [lon_run_var_29] Investment rate - non-residential
- [lon_run_var_3] Linked non-residential gross fixed capital formation price index
- [lon_run_var_30] Urbanization rate
- [lon_run_var_31] Depreciation rate
- [lon_run_var_32] Population
- [lon_run_var_33] Linked consumption price index
- [lon_run_var_34] Real household disposable income per capita
- [lon_run_var_35] Unemployment rate
- [lon_run_var_36] Linked final domestic demand price index
- [lon_run_var_37] Linked gross fixed capital formation price index
- [lon_run_var_4] Gross domestic product per capita, income based
- [lon_run_var_5] Gross operating surplus per capita
- [lon_run_var_6] Gross mixed income per capita
- [lon_run_var_7] Taxes less subsidies per capita
- [lon_run_var_8] Statistical discrepancy per capita
- [lon_run_var_9] Gross domestic product per capita, expenditure based
This dataset has 684 series:
- from
- 1926=419.8
- to
- 2016=45,970.7
- min:
- 261.2
- max:
- 45,970.7
- avg:
- 12,212.026
- σ:
- 14,156.055
- from
- 1926=NA
- to
- 2016=123.5
- min:
- 8.1
- max:
- 123.5
- avg:
- 47.121
- σ:
- 35.467
- from
- 1926=NA
- to
- 2016=121.1
- min:
- 15.5
- max:
- 121.1
- avg:
- 63.224
- σ:
- 34.382
- from
- 1926=NA
- to
- 2016=56,129.3
- min:
- 1,430.5
- max:
- 56,129.3
- avg:
- 20,752.322
- σ:
- 18,060.096
- from
- 1926=NA
- to
- 2016=14,310.9
- min:
- 403.3
- max:
- 15,682.4
- avg:
- 5,345.47
- σ:
- 4,914.484
- from
- 1926=NA
- to
- 2016=6,657
- min:
- 226.6
- max:
- 6,657
- avg:
- 2,474.584
- σ:
- 2,093.959
- from
- 1926=NA
- to
- 2016=6,340.9
- min:
- 158.7
- max:
- 6,340.9
- avg:
- 2,350.276
- σ:
- 2,001.199
- from
- 1926=NA
- to
- 2016=31.9
- min:
- -136.5
- max:
- 54.6
- avg:
- -4.516
- σ:
- 40.75
- from
- 1926=NA
- to
- 2016=56,129.3
- min:
- 1,430.5
- max:
- 56,129.3
- avg:
- 20,752.322
- σ:
- 18,060.096
- from
- 1926=NA
- to
- 2016=44,503.9
- min:
- 1,073.6
- max:
- 44,503.9
- avg:
- 15,863.331
- σ:
- 13,858.62
Series code | 1926 | 1927 | 1928 | 1929 | 1930 | 1931 | 1932 | 1933 | 1934 | 1935 | 1936 | 1937 | 1938 | 1939 | 1940 | 1941 | 1942 | 1943 | 1944 | 1945 | 1946 | 1947 | 1948 | 1949 | 1950 | 1951 | 1952 | 1953 | 1954 | 1955 | 1956 | 1957 | 1958 | 1959 | 1960 | 1961 | 1962 | 1963 | 1964 | 1965 | 1966 | 1967 | 1968 | 1969 | 1970 | 1971 | 1972 | 1973 | 1974 | 1975 | 1976 | 1977 | 1978 | 1979 | 1980 | 1981 | 1982 | 1983 | 1984 | 1985 | 1986 | 1987 | 1988 | 1989 | 1990 | 1991 | 1992 | 1993 | 1994 | 1995 | 1996 | 1997 | 1998 | 1999 | 2000 | 2001 | 2002 | 2003 | 2004 | 2005 | 2006 | 2007 | 2008 | 2009 | 2010 | 2011 | 2012 | 2013 | 2014 | 2015 | 2016 |
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
[1.1.1] | 419.8 | 434.4 | 457.4 | 454.9 | 420.8 | 345.8 | 285 | 261.2 | 289.1 | 306.4 | 321.7 | 360.4 | 361.8 | 377.6 | 427.2 | 504.6 | 631.2 | 678.5 | 738.1 | 752.7 | 786.6 | 858.3 | 968.6 | 982.5 | 1026.2 | 1182.8 | 1266.3 | 1295.4 | 1267.4 | 1332.3 | 1438.9 | 1488.1 | 1535.5 | 1582.9 | 1631.8 | 1635.9 | 1748.9 | 1827.2 | 1931.2 | 2093.2 | 2307.2 | 2485.5 | 2688.6 | 2938.6 | 3128.8 | 3352 | 3763.4 | 4341 | 5092.5 | 5855.8 | 6594.5 | 7206.6 | 7964.7 | 8868.4 | 9928.4 | 11553.2 | 12643.9 | 13281.4 | 14252.5 | 15359.8 | 16284.2 | 17309.3 | 18751 | 19955.2 | 21010.9 | 21485.9 | 21915.2 | 22330.7 | 22671 | 23203.9 | 23588.3 | 24454.6 | 25467.9 | 26512 | 27953.6 | 28990.3 | 29463 | 30197.3 | 31558.9 | 32846.2 | 34731.1 | 36614.5 | 37845 | 37648.9 | 38639 | 40158.1 | 41462 | 42666.1 | 43781.5 | 45512.7 | 45970.7 |
[1.1.10] | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | 8.1 | 9.3 | 9.4 | 9.4 | 9.4 | 9.7 | 9.4 | 9.7 | 9.6 | 9.6 | 9.9 | 9.9 | 9.9 | 10.2 | 10.7 | 11.4 | 12.2 | 12.9 | 13.2 | 13.9 | 14.4 | 15.3 | 16.8 | 19.9 | 23.3 | 24.9 | 26.7 | 27.5 | 28.8 | 30.9 | 33.6 | 37.6 | 38.5 | 40 | 41.6 | 42.9 | 46.1 | 50.9 | 54.4 | 57.7 | 57.4 | 59.2 | 59.9 | 61.6 | 63.4 | 63.4 | 63.3 | 64.4 | 65.2 | 66.8 | 68.3 | 70 | 73.1 | 76.8 | 81.5 | 85.4 | 91.7 | 100 | 103.7 | 103.1 | 106 | 109.1 | 111.8 | 113.4 | 116.3 | 119.2 | 123.5 |
[1.1.11] | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | 15.5 | 17.8 | 18.4 | 18.4 | 18.4 | 18.9 | 19.6 | 19.8 | 20 | 20.7 | 20.9 | 21.2 | 21.4 | 22.1 | 22.6 | 23.7 | 24.7 | 25.3 | 25.6 | 26.7 | 28 | 29.4 | 30.7 | 33 | 38.4 | 43.3 | 46.2 | 49.1 | 52.7 | 57.5 | 62.6 | 68.9 | 74.3 | 75.1 | 77.1 | 78.8 | 79.9 | 81 | 82.7 | 84.5 | 86.4 | 83.5 | 84.2 | 84.7 | 87.6 | 88.4 | 88.7 | 90.5 | 92.2 | 91.7 | 92.8 | 93.9 | 95.5 | 93.8 | 94.6 | 95.5 | 97.8 | 100 | 104 | 106.7 | 105.4 | 107.1 | 109.5 | 111.2 | 115.2 | 119.1 | 121.1 |
[1.1.12] | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | 1430.5 | 1631.1 | 1780.8 | 1818.5 | 1775 | 1906.4 | 2092.9 | 2119.6 | 2138 | 2217 | 2259.1 | 2295 | 2443.8 | 2575.7 | 2769.4 | 2998.2 | 3292.8 | 3477.6 | 3740.4 | 4059.9 | 4307 | 4564.5 | 5038.2 | 5839.2 | 6878.3 | 7640.4 | 8685.9 | 9485.4 | 10407.4 | 11765.1 | 13060.6 | 14791.4 | 15398.9 | 16545.1 | 17973.3 | 19273.8 | 20093.7 | 21625.7 | 23305.7 | 24527.3 | 25025.9 | 24940 | 25237.5 | 25958.3 | 27223.8 | 28290.4 | 28943.5 | 30224.8 | 31082.4 | 33039.9 | 35924.8 | 36766.1 | 37930.9 | 39514.9 | 41680.1 | 43949.3 | 45814.7 | 47845.3 | 49718.3 | 46608.1 | 48878.6 | 51536.9 | 52454.1 | 53980.2 | 56005.7 | 55673.2 | 56129.3 |
[1.1.13] | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | 403.3 | 462.7 | 446.4 | 456.4 | 439.1 | 502.4 | 561.1 | 555.6 | 527.6 | 581.6 | 576.9 | 589.5 | 634.8 | 677.6 | 753.6 | 795.2 | 850.8 | 869.7 | 942.5 | 987.3 | 1007.3 | 1051.4 | 1204.6 | 1472 | 1765.9 | 1907 | 2093.9 | 2155.9 | 2474.9 | 3023.3 | 3451.3 | 3516.6 | 3461.4 | 4140 | 4743.6 | 5138.3 | 4930.2 | 5439.7 | 5678.1 | 5696.9 | 5448 | 4929.4 | 4864 | 5311 | 6155.2 | 6668.6 | 6963.8 | 7396.9 | 7293 | 8242.2 | 9521.8 | 9657.3 | 9923.9 | 10770 | 11600.4 | 12661.7 | 13070.4 | 13437.4 | 14406.6 | 11757.6 | 13209 | 14489.2 | 14273 | 14743.4 | 15682.4 | 14393 | 14310.9 |
[1.1.14] | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | 226.6 | 257.6 | 261.3 | 261 | 243.6 | 274.5 | 286.7 | 269.4 | 291.6 | 289.5 | 278.8 | 272.1 | 295.6 | 314 | 328.1 | 343.5 | 368 | 363 | 402.8 | 453.9 | 456.9 | 502.6 | 555.4 | 682.9 | 827.8 | 892 | 1057.8 | 1126.3 | 1301.3 | 1457 | 1553.4 | 1782.9 | 1896.6 | 1988.2 | 2166.1 | 2321.1 | 2501.9 | 2602.7 | 2843.3 | 3027.9 | 3155.7 | 3237.5 | 3325.7 | 3433.5 | 3550.4 | 3662.1 | 3760.9 | 3801.4 | 3956.8 | 4061.4 | 4222 | 4386.4 | 4516.8 | 4635 | 4805.9 | 4912.1 | 5071.1 | 5357.6 | 5545.8 | 5566.1 | 5732.5 | 5898.1 | 6019.8 | 6154.8 | 6260.2 | 6484.8 | 6657 |
[1.1.15] | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | 158.7 | 191.7 | 203.5 | 211.9 | 209.1 | 222.4 | 243.9 | 251.2 | 248.4 | 264.7 | 269.9 | 274.9 | 304 | 312.7 | 346.6 | 384.6 | 416.2 | 450.6 | 484 | 528.4 | 548.3 | 578.3 | 646.3 | 717.4 | 825.5 | 778 | 943.3 | 1029.9 | 1091.4 | 1159.7 | 1172.3 | 1548.7 | 1631.9 | 1689.2 | 1773.3 | 1920 | 2176.6 | 2410.2 | 2679 | 2973.6 | 3081.5 | 3168.2 | 3263.6 | 3375.6 | 3475.5 | 3588.8 | 3624.5 | 3807.1 | 3901.4 | 4102.4 | 4225 | 4189.5 | 4470.6 | 4505.3 | 4718.3 | 4883.4 | 5000.9 | 5184.2 | 5099.6 | 5110.8 | 5262.8 | 5406.9 | 5558.9 | 5735.6 | 5950.7 | 6166.2 | 6340.9 |
[1.1.16] | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | -16.9 | -36 | 54.6 | 31.7 | 29 | 18.3 | 23.8 | 20.7 | 47.9 | 15.7 | 35.7 | 27.7 | 15.4 | 19.1 | -5.3 | -2.2 | 14 | 9.2 | -2.3 | -23.5 | 32.9 | 16.4 | -50.4 | -87.2 | -135.3 | -69.8 | -136.5 | -9.3 | -48.5 | -104.6 | -67.3 | 14.9 | 42.1 | 41.4 | 23.5 | -8 | 31.6 | -39.7 | -38.7 | -34.1 | -21.1 | 30.2 | 46.4 | 11.5 | -13.4 | -1 | 13.4 | -39.2 | -18.6 | -47.1 | -33.6 | 3.4 | -23.3 | -28.1 | -8.1 | -15 | 5.7 | 29.8 | 9.8 | 25.4 | 40.3 | 30 | 29.8 | 3.1 | 14.7 | -29.5 | 31.9 |
[1.1.17] | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | 1430.5 | 1631.1 | 1780.8 | 1818.5 | 1775 | 1906.4 | 2092.9 | 2119.6 | 2138 | 2217 | 2259.1 | 2295 | 2443.8 | 2575.7 | 2769.4 | 2998.2 | 3292.8 | 3477.6 | 3740.4 | 4059.9 | 4307 | 4564.5 | 5038.2 | 5839.2 | 6878.3 | 7640.4 | 8685.9 | 9485.4 | 10407.4 | 11765.1 | 13060.6 | 14791.4 | 15398.9 | 16545.1 | 17973.3 | 19273.8 | 20093.7 | 21625.7 | 23305.7 | 24527.3 | 25025.9 | 24940 | 25237.5 | 25958.3 | 27223.8 | 28290.4 | 28943.5 | 30224.8 | 31082.4 | 33039.9 | 35924.8 | 36766.1 | 37930.9 | 39514.9 | 41680.1 | 43949.3 | 45814.7 | 47845.3 | 49718.3 | 46608.1 | 48878.6 | 51536.9 | 52454.1 | 53980.2 | 56005.7 | 55673.2 | 56129.3 |
[1.1.18] | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | 1073.6 | 1216.2 | 1323.7 | 1371.8 | 1383.2 | 1456 | 1555.1 | 1598.8 | 1654.4 | 1715 | 1759.4 | 1794.3 | 1871.8 | 1962.5 | 2071.4 | 2217.3 | 2409.7 | 2619.4 | 2824.4 | 3043.1 | 3272.6 | 3469.3 | 3802.9 | 4283.2 | 4944.9 | 5719.9 | 6434.2 | 7146.7 | 7789.3 | 8602.2 | 9588.7 | 10938 | 11763.5 | 12689.4 | 13585.8 | 14650.9 | 15554.5 | 16509.7 | 17583.1 | 18665.5 | 19609.7 | 20260.6 | 20720.5 | 21153.4 | 21565 | 21908.5 | 22326.3 | 23176.6 | 23899.6 | 24958.9 | 26442.8 | 27428.3 | 28748.9 | 29864.4 | 30897.2 | 32250.3 | 33751.6 | 35394.7 | 36873.7 | 37061 | 38351.1 | 39709 | 40441.6 | 41393.5 | 42610.5 | 43626.2 | 44503.9 |
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