Stats NZ

Impact of COVID-19 on seasonally adjusted and trend series

This page describes how COVID-19 has impacted seasonal adjustment, and why Stats NZ has temporarily suppressed publication of selected time series.

What are seasonally adjusted and trend time series?

In the seasonal adjustment process, the actual value is broken down into three components: trend for medium to long-term movements, seasonal for systematic annual effects, and irregular for short-term unsystematic fluctuations.

The seasonally adjusted values allow us to compare different periods without seasonality contributing to the differences. Trend time series are useful to compare data points against previous peaks and troughs, as well as indicate the direction of the series.

How has COVID-19 impacted seasonal adjustment and trend estimation?

The COVID-19 lockdown and restrictions have caused abrupt changes to actual values for many time series. Our seasonal adjustment calculation initially attributed too much of the unusual values to the seasonal component, and not trend components, and not enough to the irregular component. This would have significantly altered the seasonal pattern and caused large revisions to the seasonally adjusted time series going back years. Hence, we specially treated unusual data points for many time series, so that they were attributed to the irregular component. Special treatment also excludes unusual data from trend estimation.

For series that have been impacted by COVID-19, it is impossible to know how much of this impact will be long-term and part of the trend, or short-term and part of the irregular. Calculating the trend in the usual way could be misleading, and so Stats NZ has suspended publication of the trend for many time series.

Specially treated monthly time series example

The actual value of retail card spending on fuel, from monthly electronic card transactions data, started to fall in late March 2020 as COVID-19 border restrictions and the level 4 lockdown came into effect. Fuel spending plummeted in April 2020, and has partially recovered since, though the actual value in August 2020 was down 19 percent compared with August 2019. The latest fall was partly due to non-essential travel restrictions in Auckland with a regional level 3 lockdown. We suspended publication of the trend series from March 2020 as it does not meet Stats NZ’s usual quality standard.

Created with Highcharts 5.0.14Value ($)Trend series not published from March 2020. NaN in table indicates data not available.Retail card spending on fuel, actual and trend values ($), monthly, March 2010–August 2020ActualTrendMar-10Jun-10Sep-10Dec-10Mar-11Jun-11Sep-11Dec-11Mar-12Jun-12Sep-12Dec-12Mar-13Jun-13Sep-13Dec-13Mar-14Jun-14Sep-14Dec-14Mar-15Jun-15Sep-15Dec-15Mar-16Jun-16Sep-16Dec-16Mar-17Jun-17Sep-17Dec-17Mar-18Jun-18Sep-18Dec-18Mar-19Jun-19Sep-19Dec-19Mar-20Jun-200250M500M750MStats NZ

Retail card spending on fuel, actual and trend values ($), monthly, March 2010–August 2020

Created with Highcharts 5.0.14Value ($)Retail card spending on fuel, actual and trend values ($), monthly, March 2010–August 2020ActualTrendMar-10Jun-10Sep-10Dec-10Mar-11Jun-11Sep-11Dec-11Mar-12Jun-12Sep-12Dec-12Mar-13Jun-13Sep-13Dec-13Mar-14Jun-14Sep-14Dec-14Mar-15Jun-15Sep-15Dec-15Mar-16Jun-16Sep-16Dec-16Mar-17Jun-17Sep-17Dec-17Mar-18Jun-18Sep-18Dec-18Mar-19Jun-19Sep-19Dec-19Mar-20Jun-200250M500M750MStats NZ
MonthActualTrend
Mar-10476,110,724442,926,398
Apr-10448,083,856441,050,993
May-10435,579,880436,863,562
Jun-10412,640,031432,682,781
Jul-10434,349,916431,286,663
Aug-10423,080,551434,368,143
Sep-10427,624,922442,385,280
Oct-10456,522,544454,555,604
Nov-10463,644,547469,547,574
Dec-10517,904,079484,272,349
Jan-11493,705,562495,712,779
Feb-11482,067,997502,689,088
Mar-11542,767,283504,470,699
Apr-11520,843,095501,330,017
May-11494,640,890495,420,005
Jun-11462,668,231488,559,759
Jul-11480,803,473484,914,909
Aug-11475,133,829488,347,584
Sep-11480,486,037499,006,686
Oct-11517,042,539513,101,229
Nov-11533,069,492525,612,273
Dec-11568,621,245532,576,599
Jan-12536,880,572534,736,402
Feb-12528,717,984536,097,236
Mar-12575,527,469539,361,368
Apr-12541,662,960543,944,642
May-12553,444,464549,767,061
Jun-12502,269,054557,720,205
Jul-12518,942,021567,455,762
Aug-12572,697,017577,363,186
Sep-12567,473,986583,945,866
Oct-12592,085,896585,000,345
Nov-12593,339,309583,354,056
Dec-12613,810,356585,513,834
Jan-13599,411,465593,491,402
Feb-13573,516,655602,998,904
Mar-13660,261,925609,206,495
Apr-13597,526,520613,945,248
May-13616,274,636620,742,239
Jun-13594,137,578631,757,825
Jul-13650,006,415643,128,019
Aug-13638,653,467648,853,916
Sep-13624,454,378648,071,129
Oct-13654,984,610646,337,003
Nov-13659,073,553649,245,196
Dec-13701,981,572655,824,342
Jan-14667,928,504660,548,361
Feb-14630,221,747661,338,786
Mar-14683,146,281658,663,550
Apr-14639,872,307654,645,881
May-14660,767,756650,751,410
Jun-14613,257,035646,524,115
Jul-14637,540,235643,310,209
Aug-14631,137,005641,689,240
Sep-14612,931,783639,481,550
Oct-14661,535,976633,107,743
Nov-14634,371,723619,999,499
Dec-14636,624,950603,354,388
Jan-15564,568,925588,498,583
Feb-15543,082,357580,746,724
Mar-15608,812,741582,887,456
Apr-15572,645,965592,672,133
May-15612,304,434605,513,413
Jun-15592,585,755615,575,640
Jul-15625,044,312617,909,641
Aug-15594,576,496613,389,376
Sep-15584,238,916606,155,047
Oct-15614,501,242599,373,763
Nov-15602,050,981591,510,630
Dec-15634,781,098581,828,100
Jan-16568,575,858572,321,858
Feb-16543,823,413566,112,220
Mar-16598,440,869566,223,457
Apr-16561,034,975571,740,439
May-16572,096,528577,472,539
Jun-16569,927,886579,072,436
Jul-16571,179,518577,949,198
Aug-16558,279,120576,760,530
Sep-16561,833,697578,889,367
Oct-16596,133,310586,833,819
Nov-16610,868,659601,342,749
Dec-16668,767,158616,711,326
Jan-17628,115,238627,925,719
Feb-17604,784,008632,317,025
Mar-17655,337,275628,787,656
Apr-17602,211,683618,540,715
May-17614,084,461606,001,999
Jun-17574,958,136594,911,037
Jul-17555,160,387587,510,459
Aug-17579,676,783585,831,982
Sep-17575,223,604592,331,144
Oct-17603,259,795605,733,240
Nov-17642,876,671621,952,356
Dec-17699,520,179636,590,989
Jan-18650,732,945644,264,504
Feb-18609,237,400643,049,996
Mar-18675,502,518638,254,291
Apr-18607,068,804636,121,710
May-18647,814,352639,188,094
Jun-18629,356,926647,198,399
Jul-18621,547,725656,442,538
Aug-18653,451,013661,605,643
Sep-18640,516,741657,127,521
Oct-18681,659,336642,011,828
Nov-18640,306,895619,971,264
Dec-18621,677,545598,571,651
Jan-19589,671,176586,633,144
Feb-19557,452,532586,208,034
Mar-19617,914,186591,127,560
Apr-19587,491,785593,782,086
May-19604,079,447590,821,960
Jun-19550,401,699584,409,400
Jul-19562,189,377578,302,966
Aug-19569,881,650576,027,225
Sep-19555,714,534578,567,080
Oct-19595,827,613583,956,576
Nov-19609,859,317590,126,626
Dec-19632,411,860595,743,331
Jan-20608,805,947599,258,515
Feb-20588,652,070600,347,367
Mar-20503,356,925NaN
Apr-20185,800,072NaN
May-20394,284,349NaN
Jun-20466,078,561NaN
Jul-20517,797,657NaN
Aug-20463,153,317NaN

The seasonal and irregular factors for retail card spending on fuel were showing typical patterns up until February 2020. (See graph below – these are easier to see when ‘irregular factor to August 2020’ is deselected.) The seasonal factor normally ranges between about 0.95 and 1.07, while the irregular factor is usually even closer to 1, except in periods with significant fuel price or volume changes.

We specially treated actual values from March 2020 – reflected and to account for the sudden drop in the irregular component in April 2020 to just 0.3, and partial recovery since.

Created with Highcharts 5.0.14FactorNaN in table indicates data not available.Seasonal and irregular factors for retail card spending on fuel, monthly, March 2010–August 2020Seasonal factor to February 2020Seasonal factor to August 2020Irregular factor to February 2020Irregular factor to August 2020Mar-10Jun-10Sep-10Dec-10Mar-11Jun-11Sep-11Dec-11Mar-12Jun-12Sep-12Dec-12Mar-13Jun-13Sep-13Dec-13Mar-14Jun-14Sep-14Dec-14Mar-15Jun-15Sep-15Dec-15Mar-16Jun-16Sep-16Dec-16Mar-17Jun-17Sep-17Dec-17Mar-18Jun-18Sep-18Dec-18Mar-19Jun-19Sep-19Dec-19Mar-20Jun-200.250.50.7511.25Stats NZ

Seasonal and irregular factors for retail card spending on fuel, monthly, March 2010–August 2020

Created with Highcharts 5.0.14FactorSeasonal and irregular factors for retail card spending on fuel, monthly, March 2010–August 2020Seasonal factor to February 2020Seasonal factor to August 2020Irregular factor to February 2020Irregular factor to August 2020Mar-10Jun-10Sep-10Dec-10Mar-11Jun-11Sep-11Dec-11Mar-12Jun-12Sep-12Dec-12Mar-13Jun-13Sep-13Dec-13Mar-14Jun-14Sep-14Dec-14Mar-15Jun-15Sep-15Dec-15Mar-16Jun-16Sep-16Dec-16Mar-17Jun-17Sep-17Dec-17Mar-18Jun-18Sep-18Dec-18Mar-19Jun-19Sep-19Dec-19Mar-20Jun-200.250.50.7511.25Stats NZ
MonthSeasonal factor to February 2020Seasonal factor to August 2020Irregular factor to February 2020Irregular factor to August 2020
Mar-101.0771.0761.0011
Apr-1011.0021.0091.008
May-101.0081.0080.9970.999
Jun-100.9560.9570.9950.993
Jul-100.9980.9981.0041.004
Aug-100.9840.9830.9960.998
Sep-100.9690.9690.9950.994
Oct-100.9970.9991.0071.006
Nov-100.9990.9990.9910.992
Dec-101.0571.0561.0061.005
Jan-111.0021.0021.0031.004
Feb-110.9670.9661.0031.002
Mar-111.0761.0750.9990.995
Apr-110.99811.0441.036
May-111.0021.0021.0051.004
Jun-110.9470.9480.9990.994
Jul-110.9930.9920.9981
Aug-110.980.980.9950.995
Sep-110.9670.9670.9890.99
Oct-111.0061.0071.011.01
Nov-111.0061.0051.0061.005
Dec-111.0631.06210.999
Jan-121.0061.0061.0041.005
Feb-120.9660.9650.9950.994
Mar-121.0721.0720.9890.99
Apr-120.9910.9931.0141.012
May-1210.9991.0041.002
Jun-120.9440.9460.9560.949
Jul-120.9910.9920.9310.929
Aug-120.980.9791.0091.006
Sep-120.9660.9661.0091.01
Oct-121.0141.01411
Nov-121.0141.0140.9970.997
Dec-121.0671.0670.9910.992
Jan-131.0071.0070.9980.997
Feb-130.960.9591.0011.001
Mar-131.0641.0631.0191.02
Apr-130.9840.9850.9920.991
May-13110.9860.986
Jun-130.9470.9490.9950.995
Jul-130.9920.9931.0211.019
Aug-130.9810.980.9980.999
Sep-130.9680.9681.0041.005
Oct-131.0211.0210.9880.987
Nov-131.0181.0180.9950.994
Dec-131.0691.0691.0071.009
Jan-141.0041.0041.0020.999
Feb-140.9540.9531.0081.008
Mar-141.0561.0560.990.991
Apr-140.9770.9770.9980.997
May-141.0021.0021.0071.008
Jun-140.9550.95711.001
Jul-140.9920.9950.9930.99
Aug-140.9820.9811.0021.004
Sep-140.9680.9680.9940.994
Oct-141.0221.0221.0181.015
Nov-141.0211.0211.0071.007
Dec-141.0731.0720.9880.986
Jan-151.0031.0030.9530.951
Feb-150.9510.9510.9930.992
Mar-151.051.051.0011.002
Apr-150.9730.9730.990.989
May-151.0051.0041.0071.008
Jun-150.9630.9631.0041.003
Jul-150.9870.9921.0211.012
Aug-150.9820.9810.9970.998
Sep-150.9680.9680.9940.993
Oct-151.0221.0220.9980.998
Nov-151.0231.0221.0041.005
Dec-151.0741.0731.0111.011
Jan-161.0031.0030.9910.991
Feb-160.9520.9510.9890.989
Mar-161.0471.0471.0041.003
Apr-160.9730.9721.0071.006
May-161.0081.0080.9880.99
Jun-160.9670.9661.0131.015
Jul-160.9790.9871.0071.002
Aug-160.980.980.9890.99
Sep-160.9670.9670.9970.997
Oct-161.021.021.0051.006
Nov-161.0251.0240.990.988
Dec-161.0771.0741.0031.004
Jan-171.0051.0051.0021.003
Feb-170.9540.9531.0121.012
Mar-171.0471.0460.990.988
Apr-170.9740.9751.0021.004
May-171.0091.0091.0091.006
Jun-170.9680.9650.9960.995
Jul-170.9710.9810.9850.973
Aug-170.9780.9791.0081.005
Sep-170.9670.9681.0021
Oct-171.0191.0190.980.985
Nov-171.0261.0251.0011.004
Dec-171.0771.0731.0181.025
Jan-181.0081.0061.0041.006
Feb-180.9580.9560.9970.999
Mar-181.0471.0481.0051.004
Apr-180.9760.9780.9860.985
May-181.0091.0091.0010.999
Jun-180.9660.9611.0061.009
Jul-180.9650.9770.9880.977
Aug-180.9780.9791.0051.001
Sep-180.9670.9691.011.01
Oct-181.0171.0171.0481.045
Nov-181.0281.0261.0021.001
Dec-181.0771.0720.9770.978
Jan-191.0111.0060.9940.993
Feb-190.9610.9581.0021.001
Mar-191.0481.0490.9980.997
Apr-190.9770.981.0131.013
May-191.0091.0081.0021.007
Jun-190.9640.9570.9710.988
Jul-190.9610.9751.0050.999
Aug-190.9780.9810.9981.003
Sep-190.9680.9710.9960.998
Oct-191.0171.0180.9990.996
Nov-191.0291.0261.0051.004
Dec-191.0761.0690.9971.001
Jan-201.0121.0051.0041.003
Feb-200.9610.9580.9970.997
Mar-20NaN1.05NaN0.804
Apr-20NaN0.981NaN0.314
May-20NaN1.008NaN0.651
Jun-20NaN0.955NaN0.812
Jul-20NaN0.975NaN0.871
Aug-20NaN0.983NaN0.785

How long will Stats NZ specially treat some time series?

For series that are only temporarily impacted by COVID-19, these special treatments will be left in place, so that the short-term but large effect of COVID-19 will not have a long-term impact on the trend or seasonal pattern, and post-COVID-19 values can be treated the same as normal.

For series that have permanent or long-term alterations to the trend or seasonal components, such as for travel and migration, seasonal adjustment may be temporarily ceased, until there is enough information to accurately calculate the new trend behaviour or seasonal pattern.

We produce the seasonally adjusted and trend series using the X13-ARIMA-SEATS package developed by the U.S. Census Bureau. See Seasonal adjustment in Stats NZ for more information.

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