Measuring the slump

One of the current challenges for economists and others is making sense of the scale of what is happening to economic activity, employment, unemployment, underemployment etc at present.

It isn’t helped by the persistent refusal of successive governments to fund Statistics New Zealand adequately for core functions –  you could think of the Census debacle, but I’m more focused on basic macroeconomic data.  We and Australia are the only two OECD countries without a monthly CPI, our GDP estimates (quarterly only, as with most countries) come out only with a very long lag, we don’t have a monthly industrial production series, and we still don’t have an income-based measure of GDP.   One could add into the mix the degraded state of our timely net migration data too, although for the time being I guess that won’t matter much to anyone (largely closed borders and all that).

Those failings can’t be fixed in short order, although I hope that as we emerge from this crisis the weaknesses in our statistical base will prompt some fresh thinking and a willingness to spend more on these core public services (ones for which there are few votes).

I suggested a couple of weeks ago that for now Statistics New Zealand look at hosting some sort of dashbboard pulling together, and making openly available, all manner of formal and informal economic indicators.  There have to be lots, and I’m sure various government agencies are either producing or collecting all sorts of bits of information, but there are real gaps in what is available to analysts.

There are also some temporary initiatives SNZ could look at implementing.   For example, New Zealand’s unemployment data are drawn from the quarterly Household Labour Force survey.  At present, we can expect no information on anything from the June quarter until early August –  almost four months from now.  But the HLFS is conducted by surveying thousands of households each month, steadily through the quarter.     The full sample will, obviously, tend to produce more accurate estimates than, say, a third of the sample. But there doesn’t seem to be any obvious or good reason why, for now, SNZ could not calculate and publish a subset of the key HLFS series each month, within a couple of weeks of the end of that month, drawing on the sample of households surveyed during that month (still thousands).  The regional numbers might be not worth publishing, and perhaps the fine age breakdowns too, but the headline numbers (unemployment rate, employment rate, participation rate, and perhaps each by male and female) would be very much worth having.  At present, the issue is not whether the unemployment rate is, say, 12.7 or 12.9 per cent, but whether it is more like 10 per cent or more like 15 per cent.  Without the HLFS we have no good way of knowing.   (And while this expedient would be unusual, SNZ has shown some willingness to do the unusual with early reads on foreign merchandise trade data.)  Having this sort of timely monthly data would be likely to be useful for at least the next year.

But there are also some real issues around measurement that are probably more specific to the immediate extreme dislocation.  Take unemployment as an example.  To be counted as unemployed in the HLFS, you have to be without a job, actively looking for a job, available to start work the following week.  And “actively looking” means more than skimming through adverts on job websites.  But right now, in the midst of the partial lockdown, opportunities for search are extremely limited (as are actual vacancies) and many people are extremely constrained in their ability to start work next week even if they wanted to.  There are issues around “employment” too.   To be employed, in an HLFS sense, you have to have done at least an hour’s work for pay in the reference week (assuming you weren’t on annual leave or similar).    But one wonders if the SNZ interviewers have been issued with good guidance as to how to treat people who may be at home at present, still being paid (to some extent or other) but who have done no work at all in the past week (that might encompass people normally doing a job that just can’t be done at home, or public servants never equipped to work from home, or…).  Some of those people might be being only partially paid, through the wage subsidy scheme, but who are pretty certain their current job won’t be there at the end of all this, and who are to all intents and purposes (if not for HLFS purposes) “unemployed” and doing whatever (perhaps little) they can to search for another job.

When we get the full quarterly data there will be a somewhat richer picture of the extent of labour underutilisation (for example, there are questions about hours worked in the reference week relative to usual hours worked), but getting a good read on this month –  which may be the worst of the economic slump –  will always be a bit problematic because we haven’t invested enough in a full monthly HLFS.   I’m not so cynical as to suppose this was a motive (even a month ago when the scheme was designed), but it is certainly convenient that with an election scheduled for September, the current wage subsidy scheme –  which will keep down headline official unemployment numbers, even if beyond that it is little more than (important as that is) a more generous income support scheme – runs into June, encompassing most of the last full HLFS to be out before the scheduled election.

(There are going to be some related sorts of issues with the other main labour market series, the Quarterly Employment Survey, which captures people employed and the hours they are paid for –  both valuable in normal times –  not the amount of work actually being done.  In some areas of the GDP estimates, QES numbers are used.)

I’ve been quite surprised by how small the forecasts for the fall in GDP over the June quarters from a couple of banks have been  (although also not sure how long ago they were finalised).  As noted yesterday, I struggle to see how right now the economy is not running at perhaps 50 per cent of normal (even if a larger percentage of the workforce than that may still be on full pay).  Even if there was a considerable rebound in May and June, if the government decides to allow more activities to occur, it is easy to see a 20-25 per cent fall in GDP in the June quarter.     But whatever the “true” scale of the fall, it seems unlikely that SNZ will have a close-to-accurate read on that fall (and then only quarterly, on official measures) for a very long time, perhaps ever.  We may be more reliant on academic estimates, generated in research papers in years to come, for a “true” read.  And without quarterly (business) income data at present, whatever official estimates SNZ does publish later this year are likely to have substantial margins of error, and be subject to substantial revisions for years to come (it takes several years for GDP numbers to settle towards finality at the best of times).  Indicators that serve reasonably well in normal times may be little use in this exceptional period.

Thus, it will be easy enough to get data on who has been paid, and how much, during this quarter, but not on what they are actually producing.    Working from home is generally less productive –  if it were not so, it would be done more often in normal times.  Working at physical distance is generally less productive (ditto).  But if, for example, much of the public sector component of GDP is estimated from employment/paid hours data….and many of those people are doing little, or even doing quite a bit but much less productively, how will the official statistics ever capture that as a reduction in real GDP?  Nominal GDP data should be subject to fewer distortions, and perhaps we will need to focus more on that than usual over the next couple of quarters.

No doubt there are all sorts of smaller issues, many of which perhaps don’t matter as much.  Clearly the effective cost of groceries has risen this month –  between waiting times, limited choice, no packers etc –  but I’m sure none of that will end up in the CPI.  The actual potential consumption basket is also very different now than in normal times – and in some respects may stay different for some time to come (overseas travel components of the CPI anyone?).

There are real challenges here for analysts and for statistical agencies, in our case SNZ.    In some cases, there are no easy answers (in others, there are some possible remedies).  What would be helpful early on would be some proactive communication from Statistics New Zealand on how they are planning to respond, and to meet the reasonable public demands for information, partial as much of may for a time inevitably be.    It isn’t a time for insisting on utter accuracy: that is important in normal times, but at present the urgency of the situation outweighs that, with more of a need for timely indicative numbers.  As an example of what can be done, see the recent estimate by the French national statistical agency, stepping outside their normal formal frameworks but using the data they, and only they, have overall access to, to produce estimates of the real-time loss of GDP (to which I was pointed by an SNZ manager).  There are gaps here that really only SNZ can adequately fill.

6 thoughts on “Measuring the slump

  1. Agree with the general thrust of your comments, but SNZ has been badly run for a long time – certainly since the beginning of this century – and recovering from that will take a long time. It is underfunded because it is so badly managed no one could ever recommend them having money to build infrastructure.

    If we want timely, creative and intelligent use of NZ’s statistical resources it will come from the universities. All now have direct access to the datalab though they still have to jump through SNZ bureaucratic hoops. SNZ should hand over control of data to named people in the universities, then you might see policy analysis of the type you describe.

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  2. Re your second sentence, I think the causation runs both ways. In addition, there have been clear political emphases (notably the IANZ focus) which, consistent with the rest of the public service, have been more focused on the luxury products than on building/maintaining excellent core product/capability.

    I wish I shared your optimism re universities – more optimism perhaps around researchers at places like Motu and NZI

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  3. The Universities are in for their own hiding, having become “Sellors” oi Qualifications rather then rigorous places of academic research… their staffing levels are going to be smashed

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  4.  You comment on the difficulty of assembling quarterly GDP figures promptly.  Surely there is a place for a rolling quarterly GDP figure based on the monthly figures that would be useful in assessing the future? Keep up the good work.  Regards, Don Irvine

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  5. interesting option, although I suspect it would have to be done by stepping outside the formal national accounts compilation rules – as the French have done – as some of the key data collections for the current official GDP numbers are only done on a quarterly basis.

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