I was going to move on to another topic, but last night University of Waikato economics academic John Gibson sent me the links to a couple of other papers I hadn’t seen, and I thought it might be worth writing about them. Gibson is one of New Zealand leading empirical research economists and during the lockdown I wrote about one of his efforts to think through, and put numbers on, the costs and benefits of the lockdown, linking lost GDP to possible reductions in life expectancy.

The first of the links Gibson sent through probably won’t appeal to most readers. In this paper, two Motu research economists, Arthur Grimes and Benjmain Davies, set out to formalise how one would apply what is known as “real options analysis” to the choices the government made in late March.   Real options analysis was an addition to the economics literature in the 1990s.  In many ways, it was one of those blindingly obvious ways of looking at things that was probably second nature –  often unconsciously so – to many people making all sorts of decisions in life, but which hadn’t been part of the formal economics toolkit until then.   As Grimes and Davies describe it

A standard result from real options theory (Dixit & Pindyck, 1994; Guthrie, 2009) is that delaying decisions to act can be valuable when (i) decision timing is flexible, (ii) some outcomes are partially or fully irreversible once action is taken, (iii) uncertainty exists about the evolution of an exogenous process that impacts the outcomes of interest, and (iv) the decision-maker can learn about the evolution of the exogenous process over time. Delaying action preserves the option to make a future decision without locking in irreversible costs prior to new information arriving.

It is often applied to private sector investment decisions, but can just as much be applied (and probably should be more often) to some government investment or regulatory etc decisions (or other private choices –  one might think, for example, of a proposal of marriage).

But as Davies and Grimes note, in the choices the government faced in late March, there was uncertainty and potentially irreversible losses whichever direction the government took. In their words

Conditions (i)–(iv) were all met at the outset of COVID-19. However, the two-sided uncertainty at that time made it unclear which option should be preserved: the option to protect economic output initially (by avoiding lockdown) or the option to preserve the chance to eliminate COVID-19 (by entering lockdown).

This is, of course, something of an oversimplification, since there were degrees of possible regulatory responses (and “elimination” itself was not yet the government’s stated goal at the time),  and many –  but probably not all –  of the economic losses would have happened anyway, as individuals and firms responded to perceived risks –  but the point of the short paper is to illustrate the framework, not to offer empirical answers.   The authors chose the March lockdown decision to illustrate the framework, but they could just as well –  or so it seems to me –  have applied it to, for example, the decision to close the border to travellers from the PRC in early February, or to the decisions the government took last week regarding the latest Covid outbreak.

It would seem, also, to be a useful framework in which to think about the way ahead from here –  not in any mechanical sense, but as a way of helping to organise thinking.

The second paper, by Gibson himself, is likely to be of more general interest and –  since it does reach a specific conclusion –  controversial.  I’m a little surprised it doesn’t seem to have been covered elsewhere already.  An earlier version of Gibson’s paper is available here as a University of Waikato Working Paper, and although I will be quoting from a more recent version that Gibson sent me, the abstracts of the two versions are word-for-word identical.

On this occasion the conclusion is well-captured in the title of the paper, “Government Mandated Lockdowns Do Not Reduce Covid-19 Deaths: Implications for Evaluating the Stringent New Zealand Response”.    Capture your interest?  It certainly did mine.

It is an empirical paper using US county-level data, and thus taking advantage of the fact that regulatory powers on these matters typically do not rest at federal level.

Gibson begins by noting that epidemiologists’ simulation models are simply not fit for purpose when it comes to evaluating likely deaths (and, thus, deaths saved from interventions).  Writing of the apparent influence such models had –  whether for support or illumination –  in New Zealand, Gibson writes

It is unfortunate that epidemiological simulations had such impact. The Susceptible,
Infected, Recovered (SIR) epidemiological model, and variants with Exposed and Dead (SEIRD), have infectious people mixing (homogeneously) with others; each person has equal chances to meet any other, regardless of their health status. Yet in reality, people engage in preventative behaviour to reduce risk of exposure; allow for this, and some public actions designed to reduce disease spread may do more harm (Toxvaerd, 2019). These models also have too many degrees of freedom, so are poorly identified from short-run data on cases. For example, Korolev (2020) shows long-run forecasts of U.S. COVID-19 deaths from observationally equivalent SEIRD models ranged from about 30,000 to over a million.

Forecast deaths depend on arbitrary choices by researchers, and data at the time cannot show which forecast is right as so many models are observationally equivalent in the short-run. Elsewhere, Swedish researchers using the Imperial College approach forecast (in mid-April) 80,000 Covid-19 deaths by mid-May (Gardner et al, 2020). In fact, just 3500 died by May 15, with the forecast more than 20-times too high. A final example is the Otago forecasts, which had assumed no case tracing and isolation; using the same simulation model, Harrison (2020) set tracing and isolation success at 50% and forecast deaths fell by 96%.

Harrison(2020) is Ian Harrison’s paper that I have previously written about here.

Gibson’s approach is different

My research design exploits variation among U.S. counties, over one-fifth of which just had social distancing rather than lockdown. Political drivers of lockdown provide identification. If the Prime Ministerial claim, that sans lockdown tens of thousands of New Zealanders would die, is correct then one would expect to see more deaths in places without a lockdown. This may explain global fascination with Sweden, as a country without lockdown. However a within-country research design has two benefits; less variation in measuring Covid-19 deaths than for between-country comparisons, and it better suits the highly clustered nature of Covid-19. For example, Lombardy’s Covid-19 death rate was 1500 per million versus 300 per million elsewhere in Italy. The New York death rate (by May 15) was 1410 per million but just 190 per million in the other 49 states. Taking China’s data at face value, Hubei’s death rate was 76 per million versus 0.12 per million elsewhere. With such clustering, analyses using national averages may mislead.

In practical terms, his regression model is as follows

The regressions use 22 control variables, including county population and density, the elder share, the share in nursing homes, nine other demographic and economic characteristics and a set of regional fixed effects. These controls explain about two-thirds of variation in log deaths (as of mid-May). Even with these controls, the errors for the log death equations may correlate with treatment status, if selection into the treatment group (77% of counties) is due to unobservables. Political drivers of lockdown are plausible instruments; counties without lockdown are all in states with Republican governors and if a gubernatorial election is set for November 2020 (11 are) lockdown was more likely. Conditional on the state-level factors, the extent a county became more partisan between the 2012 and 2016 Presidential elections, relative to the state-level change, affects odds of lockdown. It is hard to think of other paths for these variables to affect Covid-19 deaths than via political calculations about lockdown.

There is a fair amount of technical detail in the paper. Many of the expected things do turn out to have mattered.  Thus

…almost two-thirds of variation is explained by early May. The models show deaths are higher if the elderly or those in nursing homes are more of the population; patterns noted in popular discussion of Covid-19. Deaths are higher if whites are a lower share and blacks a higher share of the population, as noted by Millett et al (2020). Counties with higher inequality and more people without health insurance experience more deaths. Fewer deaths occur if the smoking rate is higher, similar to what is found in the U.K. for 17 million NHS patients, where Williamson et al (2020) find current smokers less likely than others to die (as hospital in-patients) with confirmed COVID-19

But this is Gibson’s summary of his results

So the firmest conclusion is that over more than two months after New Zealand’s March 23 lockdown decision, there was no evidence of more Covid-19 deaths in places without lockdowns.

Moreover, he suggests that this was apparent from data that would have been available to New Zealand policymakers when they made lockdown decisions from March to May (and, presumably, of course for this month’s decisions).

Some readers may be inclined to instantly dismiss Gibson as some sort of off-the-planet person simply out to get the government.  I have no idea of his personal politics – and, as I’ve noted, he is a highly regarded New Zealand economists who seems to go where the data lead – but in any case as he notes it isn’t as if he is the only one to find similar results

This ineffectiveness has several causes: real-time activity indicators suggest threat of Covid-19, rather than lockdown per se, drives behaviour (Chetty et al, 2020). Just one-tenth of the 60% fall in consumer mobility in the U.S. was from legal restrictions, with the rest from people voluntarily staying home to avoid infection (Goolsbee and Syverson, 2020).

I don’t suppose anyone has Raj Chetty pegged as (say) a Trump supporter, and as for Goolsbee, that is Austan Goolsbee, former chairman of the Council of Economic Advisers in the Obama administration.  In addition to his paper, there is an accessible interview with Goolsbee here.   This bit captures the point

Adi Kumar: You and Chad Syverson recently published a paper with the National Bureau of Economic Research called, Fear, lockdown, and diversion: Comparing drivers of pandemic economic decline 2020.¹ There you attribute most of the drop in business activity in the United States to people’s own decisions to stay at home, rather than government-imposed restrictions. Can you explain your hypothesis and its implications for policy makers grappling with strategies to reopen the economy?

Austan Goolsbee: We looked at phone records that tracked the locations of 2.3 million businesses around the country. These were mostly retail and services, the kinds of places people physically visit. When we plotted business activity against lockdown timelines through the pandemic, we found that consumer behavior was not aligning with lockdown orders. The visits had trailed off before these were imposed.

We began asking whether government orders drive behavior or not. It’s the classic “identification problem” in economist language—was it causation or just correlation? The disease triggered fear and led people to stop going outside. Then authorities passed laws requiring that they stay at home. So it’s important to figure out how much of what happened next—the sharp fall-off in consumer activity—came from individual choice and how much from public policy.

Our basic idea is to compare places where policies are different on either side of a state border. In Illinois we had shutdown orders, but across the border in Iowa they didn’t. Several metro areas span that border and we have 110 different industries. Take barber shops as an example. If the policies were driving the activity, then we should have seen people still getting haircuts in Iowa but not in Illinois. But that didn’t happen. In the same week, everyone stopped getting their hair cut by similar amounts. That kind of evidence leads to the conclusion that the 60 percent drop in consumer activity from pre-COVID-19 times to the depths of the pandemic was more about individuals’ own decision to stay home. We found that only about 7 percent of the fall-off was due to the policy. Everything else we attribute to other factors, mostly fear.

Those results aren’t about deaths directly, but about mobility and economic activity, but of course the logic of the case for lockdowns is that it is those reductions – forced interpersonal distancing –  that reduces future case and death numbers.

We saw this in New Zealand itself before official restrictions were put in place.  I guess everyone has their own story: mine was of a trip to Auckland on 19 March, before there were any domestic restrictions in place.  Flights were already being cancelled, Wellington airport mid-morning was largely deserted, and my taxi drivers in Auckland told of the hours they had spent waiting for a single fare.

So what are the implications?  This is from Gibson’s abstract

Instead, I use empirical data, based on variation amongst United States counties, over one-fifth of which just had social distancing rather than lockdown. Political drivers of lockdown provide identification. Lockdowns do not reduce Covid-19 deaths. This pattern is visible on each date that key lockdown decisions were made in New Zealand. The ineffectiveness of lockdowns implies New Zealand suffered large economic costs for little benefit in terms of lives saved.

He is, at least implicitly, arguing that we’d have had just as much distancing, in aggregate, without lockdowns (in this case he refers to so-called Level 3 and Level 4 restrictions), as with them.  (As he and others –  including Grimes and Davies – have noted, official advice later released reveals that as late as 20 March official advice to the government had been to stay at the new “Level 2” for 30 days.)

From the final page of his paper

In terms of implications for the future, these results add to the evidence that lockdowns are ineffective. This was also the prior view in public health; for example Inglesby et al (2006: 371) noted: “It is difficult to identify circumstances in the past half century when large-scale quarantine has been effectively used in the control of any disease.”  So when the next pandemic occurs, the Covid-19 lockdowns should not be considered a success that should be replicated. …..If decision-making from March and April is reviewed, any claim that lockdown was necessary to save lives can be treated with strong scepticism. It is especially concerning that there were data available, on the dates of those key decisions, to show that lockdowns are ineffective at reducing Covid-19 deaths.

How plausible is all this?   Perhaps experts in the specific data Gibson uses, or specialist econometricians, can pick some holes and raise some specific doubts.   But as Gibson notes his isn’t the only paper pointing in this sort of direction (and he tells he is finishing another paper suggesting that for a major emerging country “the mobility declines predated the local lockdown orders by two weeks”.   One should probably never revise one’s view too much based on a single set of results, but they can’t be discounted either.

Note also that these results are about “lockdowns”, and are not a direct commentary on the role and value of things like enforced isolation of those found to have the infection or, at least as I read it, on border closures and associated managed isolation policies.  If so, perhaps it is plausible to suppose that private choices –   firms, households, rest homes, community, sporting and religious groups etc –  would have brought about sufficient distancing in New Zealand to have resulted in eventual (domestic) elimination, perhaps at no more deaths than actually occurred in New Zealand.   Perhaps.

If that were so, of course, it would pose questions about the value of the partial lockdown Auckland is currently experiencing.

As Gibson notes, the response of some people is likely to be along the lines of saying that even if his results are (a) robust and (b) applicable to New Zealand, why does it matter?  We (and those US counties that saw deaths fall) got there anyway.

A non-economist might say “what difference does it make?” If people would reduce
interactions anyway, due to perceived Covid-19 risks, having government force them to stay home would seem costless. Yet as economists know, a government diktat approach runs into the central planning problem; no central planner has all the information (collectively) held by parties involved in voluntary exchange (Hayek, 1945). For example, absent lockdown, if a butcher felt they could operate safely and if customers felt they could safely shop at this butchery, voluntary and beneficial exchange could occur. Instead, under the central planning approach applied in New Zealand, butchers were shut but supermarkets selling meat were not. Potentially, much economic surplus (for both consumers and producers) was lost.

And that would seem to be just a small part of it (Gibson was tightly word-count constrained).   We currently have massive overlays of officials deciding who/what is or isn’t a permitted exception to the internal border restrictions –  the sort of thing that should have been sorted out months ago, given the lockdown policy was always potentially regional –  and associated delays, rather than private firms and households making their own choices about what risks to run, or not.   Or we had the official gross over-reach that prohibited you from going for a quiet solo swim at a calm suburban beach in mid-autumn, that makes rules on where, when and what you could hunt  –  none of which had anything to do with public health.  Or that prohibited a priest attending in person to a dying – or bereaved – parishoner, or that prohibited funerals altogether for a time.  Or that banned people from making choices to have small distanced outdoor services –  having advice to hand about risks –  to celebrate Easter, because presumably such things were too hard for officials, unimportant to our ministers etc.   Or –  in my case, and perhaps trivially –  the lockdown rules prohibited me taking my son out for driving lessons, again with no public health implications for anyone.

All that of course, assumes that Gibson’s results are robust.  But it all goes to the more general point that proper marginal cost-benefit analyses should have been being done by officials and ministers –  should now be being done –  and aren’t.  It has been known from the start that private distancing choices would make a material difference, but those rational private choices have too rarely been seen factored into New Zealand official decisionmaking.

There is, however, one area in which I think Gibson overstates his case, perhaps quite materially, and that is on the economic consequences of the lockdown choices.   He notes that

Treasury assume that output at Level 4 was reduced by 40%, at Level 3 by 25%, and
at Level 2 by 10-15% (Treasury, 2020). So even with a V-shaped shock and recovery rather than a U or L shape, 33 days of Level 4 and 19 of Level 3 (that ended May 13) would reduce output by ten billion dollars (ca. 3.3% of GDP) compared to staying in Level 2 throughout.

and

 In terms of the (recent) past, the ineffectiveness of lockdowns implies that New Zealand suffered large output losses, of ten billion dollars or more, for no likely benefit in terms of lives saved as a result of the decision to move almost immediately from Level 2 to Level 4.

But this is almost certainly wrong, and in fact inconsistent with many of the other sorts of results re mobility etc that Gibson cites.   We simply do not know how large a share of those (guessed) Level 3 and Level 4 losses would have occurred anyway, as people and firms wound back their own activity.  I know that I had already decided that our children would not have been going to school the next day, if the government had not pre-emptively closed the schools.  Not many people would have been at restaurants, cafes, movie theatres or perhaps even churches in late March and early April, no matter what the government had decided (perhaps especially if they’d still been waving around scary death predictions).   Quite possibly much of the construction sector would have stayed working throughout –  even officials wanted to keep that open in Level 4 but ministers refused –  but a large chunk of the lost output would have happened anyway, at least for several weeks.  From my exchange with him last night, I get the impression Gibson is more optimistic about the economic difference than I would be, but the 3.3 per cent of GDP number must be seen as an overstatement of the economic cost of the lockdown itself.

As I’ve said repeatedly in this series of posts, I’m not championing any particular policy approach from here (although I have been inclined to the view –  in March and now – that the government itself has been inclined to over-react, using sledgehammers (at little or no cost to themselves and officials, in fact possibly feeding saviour narratives) when something more nuanced could credibly have done the job).  I’m not even fully convinced by the Gibson story but  –  in particular coming from someone of his stature –  it deserves to be taken seriously, tested and critiqued rather than –  as some will be tempted to, for a variety of different reasons –  dismissed out of hand.

 

 

In my post late last week I wrote about Martin Lally’s attempt at a cost-benefit analysis around the current government’s strategy of eliminating Covid from (the wider community in) New Zealand.    I was interested in it as much as anything because there was, and is, no sign that the government –  or official agencies (notably Health and Treasury) – has attempted anything of the sort.  As I noted in the body of the post, whatever view one takes on events of the last six months, decision-making from here requires a genuinely marginal analysis, setting aside sunk costs and benefits and focusing just on things that can be controlled or influenced from here on, by New Zealand.

Prompted by that observation, Martin Lally modified his paper slightly to introduce an explicit forward-looking dimension (both versions are now linked to in the earlier post).  He ended up with this strong conclusion

“Switching to a Sweden-style approach is therefore clearly warranted.”

For various reasons, I didn’t think his analysis supported such a strong conclusion.  But as I said in the earlier post, and will no doubt reiterate at the end of this, I don’t have a strong view myself on what the appropriate approach for New Zealand now to take is.    And that is so even though if a coordinated global lockdown for six weeks would in fact wipe out the virus –  and I don’t purport to know if it would – I could imagine endorsing such an approach.   New Zealand voters, New Zealand governments, have to take the rest of the world as it is, not as we might wish it to be.

Probably like quite a lot of other people, I’ve spent a fair amount of time over the last few days trying to think through even how to think about the best answer to the “what approach should New Zealand take?” question. I was prompted initially by the columns by Matthew Hooton and Kate MacNamara in Friday’s Herald, but I’ve been trying to work through my own thoughts, not theirs.

There are too-easy approaches on both sides of the arguments.  As one extreme, there was this the other day from a Nobel (Memorial) Prize winning economist.

Which demonstrates about as little as, say, contrasting New Zealand’s expected fall in June quarter GDP (about 15 per cent) with the (much smaller) reported fall in Swedish GDP, and in turn contrasting those numbers with the respective number of Covid deaths.    Neither set of comparisons sheds almost any light at all, even on the handling of the last 5-6 months, let alone on the way forward.    Samples of one comparator rarely do, unless you are really confident that in all other respects your comparator is near-identical to your country.

But I’ve increasingly come to wonder whether GDP comparisons can tell us much at all for these purposes.    Perhaps they would do so, at least in principle, if governments only took –  or failed to take – public health measures, but in fact they do palliative economic stuff as well.    In principle, it isn’t that hard to keep measured GDP up even in a tight lockdown –  all sorts of government-funded make-work activities could achieve that (measured) effect.  But even without going to that extreme, a government that throws huge amounts of income support at people whose normal business/work is impeded by lockdowns –  or private social distancing –  will, in the short-run, generate more GDP than an alternative strategy (simply not letting people starve).    And yet in doing so it constrains future fiscal policy choices –  real choices around government goods and services and future income support and taxes –  in ways that won’t show up in short-term GDP calculations, perhaps not even in long-term ones.

No actual advanced country government has gone to either extreme –  keeping GDP all the way up “artificially”, or providing just enough support to avoid starvation –  but there is quite a range of support measures that have been put in place, differing in generosity,  duration, incentives effect, etc etc.   And it is very hard to do good cross-country comparisons.  I noticed on Stuff an op-ed from the local economist Shamubeel Eaqub.   He seems to be a supporter of the current elimination approach,  and believes it is a win-win (health and economics approach).   In many respects his short article is a not-unreasonable discussion of some of the issues.  But then notice this line, used in discussing this year’s economic outcomes for New Zealand and Sweden

The scale of fiscal stimulus has been larger than in Sweden. The IMF’s tallies show Sweden’s stimulus of 11 per cent to 17 per cent of GDP, compared to 21 per cent in New Zealand. It is difficult to tell how much of the difference is because of the public health approach versus other considerations. But the fiscal stimulus is around $15b to $33b larger, some of which will be simply spent (for example wage subsidies), while others will add infrastructure and future economic growth. These are not yet possible to tease out – but gives a sense of the difference in government response.

Which on the one hand acknowledges that our economic outcomes might in part simply reflect a choice to put more of a fiscal mortgage on our future, but on the other fails to distinguish what has been spent over recent months, what is just provisions either uncommitted or for future years, let alone the composition of that support.   The New Zealand government’s total commitments might be 20+ per cent of GDP, but what has been actually paid out this year is some relatively modest fraction of that.  Presumably there are similar issues with every country’s numbers.   In New Zealand the immediate relevance is the point many commentators have made: as the wage subsidy ends it is likely our economic activity will fall away, independent of any different choices around public health interventions.

There are similar issues down the track.  For example, Lally attempted to use the comparison between The Treasury’s December 2019 and May 2020 economic projections as a base for thinking about what economic difference the health intervention might have made.  But if fiscal policy can support incomes/GDP in the short-term, as it has done this year, macro policy more generally (fiscal and monetary policy) can support demand and activity over the sort of multi-year horizon (a) Treasury’s forecasts looked at, and (b) that we realistically face on current policies, given the needed border restrictions.  A sufficiently aggressive macro policy could get us back to full employment fairly quickly, and if Treasury or the Bank don’t forecast that that is a reflection on expected stabilisation policy choices, not on the merits, cost, or otherwise of the elimination strategy.     And, on the other hand, even achieving full employment that way might result in its own distortions.

It is likely that a national elimination strategy will lower potential output relative to the pre-Covid counterfactual but that effect might be quite modest, relative to the gains from getting actual output and employment quickly back to potential.    And it still doesn’t answer the question –  the important economic question – of whether, for New Zealand, a national elimination strategy will lower potential output (including per capita) over (say) the next five years in total by more or less than some mitigation strategy would.  And again, specifics are likely to matter.  If you are in an economy in which foreign tourism matters enormously the answers may differ somewhat than if your economy is one that prospers almost entirely by exporting things (without needing much people movement).   “May” in part because we don’t know how much travel would occur voluntarily even if travel were relatively unrestricted among a (hypothetical) group of countries pursuing something less than elimination.   European evidence this (northern) summer suggests that would not be close to zero.

And as I noted the other day, one of the biggest problems in all this is that no one –  certainly no one championing the elimination strategy –  can articulate a credible exit strategy from the regime of tight border controls, with –  in effect – heavy effective taxes on people who do move.  I read an interesting piece on Newsroom this morning by a journalist who appears to have fully convinced himself of the case for the status quo.   But there was no discussion at all as to where and how it all ends.   We cannot –  it seems from all I read –  simply assume a widely available fully effective vaccine in short order.  We cannot, it seems, simply assume the virus will go away in short order.  And we cannot assume the rest of the world suddenly adopts strategies that might lead to general suppression and/or elimination.

Now perhaps we can move to a model in which the testing at the border is finally being done consistently, competently and comprehensively –  as we were promised a couple of months ago – so that the threat of lurching into fresh lockdowns with no notice (and, evidently, with grossly inadequate preparations by ministers and officials) is largely, if never completely removed.    That sounds more or less plausible.  But it had better be true, since the fresh uncertainty that last week’s episode reintroduced is itself no small thing.

But even managing that won’t change the border being largely closed, indefinitely (even if at some point there is a pleasing travel “bubble” with Taiwan and the Cook Islands).   At a personal level, the border doesn’t greatly affect me now.  I wasn’t planning on going anywhere any time soon, and I’m among what might be a small minority of New Zealanders (let alone resident foreigners) with no close relatives living/working overseas (very few distant ones either).  No one in my family depends on the tourism sector.  But some 28 per cent of people resident in New Zealand are foreign born, and a fair chunk of those born in New Zealand in recent decades are now living overseas.  A large chunk of people work in businesses that depend on foreign tourism, export education etc.

Personal connections matter, even if they don’t show up in GDP numbers.   Weddings missed, funeral missed, Christmases not shared, grandchildren/grandparents not hugged all matter. They are the sort of things that make for a full life.  And sure technology helps, but no one really thinks it is the same, not for years and years anyway.

Now, a reasonable counter to these points is a reminder that New Zealand can only control what we do.  The rest of the world will do what it will.  Australians aren’t even free to leave the country at present –  whether for New Zealand or anywhere – and won’t let New Zealanders in anyway.  They’d presumably be even less likely to if we took a mitigation path instead.

If I were really forced to make a pick, I would probably go with the view that a well-managed  elimination approach will have a lower GDP cost (even with all the caveats above) than a mitigation approach.  But no one really knows do they?   As an example, case numbers and deaths have tailed off in Sweden too, but no one knows whether that is sustainable, or what the longer-term costs of their (private and government) restrictions and distancing measures might be (or what they might be applied to another country, like New Zealand.

And then one is still left trying to weigh the other costs and risks and implications of what maintaining the elimination strategy might mean, especially if we continued to have a government that didn’t do the basics well and then relied on extreme measures to contain relatively limited outbreaks (as happened in April –  recall the toughest lockdown in the world, the ban on swimming, the ban on funerals).     Tough restrictions might be tolerable in a very time-limited scenario –  the big wave of the 1918 flu in New Zealand swept through in about six weeks – but we are already months into Covid and, to repeat, there is no obvious end in sight.

There is a group of people –  presumably mostly on the left –  who seem only to happy to coerce populations without limit, talking (for example) of mandatory masks apparently indefinitely, or constraining capacity on individual buses and trains while doing nothing to increase capacity, or having lockdowns on a whim (even with compensation).  These same people are probably also quite happy to have people increasingly dependent on the grace and favour of governments, for handouts (new wage subsidies), for favoured stimulus programmes (the reward to lobbying and connections), and who are quite unbothered by –  for example –  banning the public celebration of Easter this year, even outdoors, even in modest gatherings.   Or banning funerals, some of the sorts of things that define our culture, our humanity.   There are people, even on the right, who seem only too happy to have privacy protections tossed out the window, allowing the state to track us all for the (indefinite) duration.  Of course, Covid is not some conspiracy to enable bigger more powerful governments –  any more than, say, World War Two was – but it, and the indefinite elimination approach, tends to have that effect anyway.

There don’t seem to be easy answers.  I –  unaffected much by the border – might prefer something like a highly-capably managed version of our elimination approach for now.  If it works, we mostly keep our freedoms, even if we are poorer.  There is also the option value of waiting –  if we abandon the elimination approach, it would be expensive to reinstate it later, and there are no commitment mechanisms to keep a government to a mitigation path after once it decided to try it.

But I can understand that for many the freedom to travel – without huge effective taxes –  is one of the important freedoms.   And again not one really captured in GDP.

I haven’t said much here about the likely increase in lives lost (and impairment of quality of life for some who didn’t die) were we to move to a mitigation strategy.  That is not because those effects are unimportant.  I touched on them in the earlier post, but I don’t purport to have a distinctive perspective on anything around how the virus itself might then progress through New Zealand.  But again, the absence of a credible exit strategy puts those costs, those people (who could be you, or me, or our families) in a different light.  One parallel that struck me some months ago were the lives we put on the line in World War Two.   No one really wanted a war, but in the end no one could see a satisfactory outcome unless we committed to war, knowing that would involved –  almost certainly –  large losses of lives of young men (mostly).    The parallel isn’t exact by any means, but I still find it worth reflecting on.

This has all been rather discursive, and inconclusive –  as much about helping to sort through my own thinking as anything else.  To repeat, I am not championing any specific strategy for New Zealand at present.  And I remain worried about the apparently weak levels of capability in our public service and political system to evaluate options and/or effective and efficiently operate whatever option is chosen from time to time.

For those interested in understanding Sweden itself, I saw a link the other day – I think on Marginal Revolution –  to this interesting, but avowedly incomplete, look at some of the distinctive features of the Swedish experience and system.

Back in the last “lockdown” I linked to various pieces of work by other economists attempting to make sense of, evaluate etc, choices the government was making.   There was Ian Harrison’s work challenging some of the modelling estimates the Prime Minister liked to wave around and some aspects of the “Level 4” restrictions.  There was an early attempt at a cost-benefit analysis by Bryce Wilkinson of the New Zealand Initiative, and another exercise looking at a similar question in a different way by John Gibson at Waikato University.  There was another exercise that I never wrote about, but which is reported and linked to here, by Martin Lally, a consultant economist and former Victoria University academic.

What was striking, even at the time, was that there was no sign that the government had commissioned from officials, or officials had undertaken anyway, any sort of serious cost-benefit analysis of the sorts of intervention they were looking at and imposed.  It always seemed likely at the time that there was nothing of the sort –  the public sector had, after all, been woefully underprepared, sluggish in getting any serious planning underway, and complacent for too long that this was largely someone else’s (PRC’s) problem  Anyway, when the government finally got round to publishing the relevant documents, sure enough there was no serious structured attempt to cost and evaluate alternative policy options.  (It is not, I hasten to add, that any cost-benefit analysis can give one “the” answers, but it provides a disciplined framework to analyse the options, assumpions and sensitivities.)  But there was nothing –  even though the New Zealand authorities had the best part of two months of lead time.

These issues take on a fresh salience with this week’s out-of-the-blue partial lockdown of Auckland, and the government decision later today.  It prompted me to finally go and take a look at an exercise undertaken by an economist at the Productivity Commission in early May, illustrating for the benefit of The Treasury –  who we used to assume were the champions of robust cost-benefit analysis –  how the decision in late April on whether to extend “Level 4” for another five days might have been rigorously analysed in a careful cost-benefit framework, looking only at the marginal costs and benefits of the two options the government had had in front of it.    The author concluded that, with the information available at the time, the extension was probably not justified, but that is less relevant than the fact that an economist at another agency was having to do this for The Treasury after the event.  Apparently neither The Treasury nor ministers had been interested in getting such analysis done when the decisions were being made.

Restrictions –  border restrictions –  have remained in place, but there seems to have been relatively little interest in evaluating the costs and benefits of those choices.  But this week’s restrictions have brought the issue back into focus.     There have been a couple of newspaper articles, notably in today’s Herald: this by Kate MacNamara, and a column by (newly returned from working for the National Party) Matthew Hooton.  MacNamara explicitly ends her piece with the argument

“There will be a time when the best option is to ease border restrictions, abandon lockdowns, and let our health system, including tracking and tracing, do the heavy lifting. We need credible analysis to help us know if that time is now.”

I’d say “perhaps” to the first sentence –  and it remains troubling that there is no identified or championed (by the government) credible exit strategy from our current eliminationist/closed-borders model – but would strongly echo the call for serious, open, analysis on the issue and options.

Martin Lally’s latest paper on a cost-benefit approach isn’t that analysis –  we need proper marginal analysis on the costs and benefits from here, with what has happened to now in principle largely irrelevant (sunk costs and all that).  But Martin’s paper, which he has given me permission to share

Martin Lally cost-benefit assessment of Covid lockdown August 2020

is still a useful look back at the merits of choices made over recent months, and probably sheds at least some light –  poses some questions –  on how the choices going forward might look.

His conclusion is as follows (QALY = “quality-adjusted life year”)

This paper considers the effect of the New Zealand government adopting a suppression policy versus a milder mitigation policy, with the actions of other governments taken as given. The cost per QALY saved from doing so would seem to have been vastly in excess of the currently used value for a QALY of $45,000. Consideration of alternative parameter values and recognition of factors omitted from the analysis would not likely reverse this imbalance in cost per QALY saved versus currently accepted figures for the value of a QALY. The suppression policy was therefore dramatically inconsistent with long-established views about the value of a QALY.

The broad approach is to look at lives saved by the government’s elimination approach and the (primarily) economic costs of that strategy.   Neither is necessarily straightforward.  On the economic side, one sometimes hears champions of the government touting a view that there is no such economic cost –  in fact, I heard former Labour leader Phil Goff make exactly that claim this morning. Locking down hard, while costly initially, is –  these champions conveniently claim – its own reward; initial losses more than outweighed by the subsequent gains (faster sustained recovery etc).  But there is no actual evidence for these claims –  at best such an outcome could be considered as one scenario.  (In the early days, the PM was claiming support from 1918, suggestions I looked at here.)

Perhaps that line might have seemed more plausible to some just a few days ago.  But then, with essentially no notice, our largest city was flung back into a partial-lockdown, and whatever choices the government announces today, we are told to expect more of these events, timing and size of course unknown and unknowable.    So we take further real output losses now and –  perhaps at least importantly – fresh huge uncertainty (affecting all manner of firms, and households too).    Perhaps the government can finally fix up border testing –  isn’t it just staggering that two-thirds of people working at aiports/MIQ facilities etc haven’t been tested at all? – reducing the chance of further outbreaks/lockdowns.  But even if that were done as best as humanly possible, it wouldn’t change the limitations of the closed border itself.

And the difficulty for champions of the “own reward” model is the absence of a compelling exit strategy.   If we could count on the virus simply dying out, going away, by some clearly defined date next year, the calculations change quite a lot.  There is a credible exit strategy then, and we just have to hold on til then.  Similarly it we could count on a highly effective vaccine being generally available by some clearly defined date next year, again things look more encouraging for the “own reward” story.   Perhaps those too are scenarios to add into a serious evaluation of the strategy.  Along with scenarios in which there is never a very effective vaccine and/or the virus remains much as it is indefinitely.

In any case, what Lally does is to assume that some –  quite moderate –  proportion of the difference between the Treasury’s GDP forecasts from last December and those from this year’s Budget should be treated as the cost of the elimination approach.  His central case assumes 25 per cent.  That may be too high.

The other side of the equation is, of course, lives saved (and reductions in impairments to the quality of life, of those with serious but non-fatal Covid).  Of course, some of that early modelling suggested catastrophic losses if we hadn’t gone to a fairly severe lockdown.  But if, as Harrison suggested, those numbers didn’t look that plausible at the time, they look much less so now.    Lally focuses on the case of Sweden, which has pursued –  not always well –  something closer to a mitigation policy.

To date Sweden has suffered 570 deaths per 1m of population and the increase in the rate is tailing away to zero.  New Zealand’s population of 5m implies 2,850 deaths under a Sweden-style mitigation policy. The QALYs saved would then be (2,850 – 22)*5*0.5 = 7,070.

It is a sample of one, but again he illustrates that you can assume a materially higher numbers of QALYs saved and the calculations still don’t end up very favourable to the New Zealand approach.   A further caveat is that, although he notes the point, Lally does not explicitly allow for the QALYs saved in respect of the people with serious non-fatal Covid cases.  The Productivity Commission piece does include some estimates, and if I’ve read document correctly, the effect is to double the overall QALYs saved.

Lally is very conscious of the sensitivities in his analysis. This is the last extract I’m going to quote.

The parameters used in this analysis are debatable. The death rate under a mitigation policy may be much larger than estimated here. If it is doubled, the cost per QALY saved would halve to $4.25m, but would still be 94 times the usually accepted figure. The GDP loss from the current path relative to that if there is no curtailment in economic activity could be smaller. If it were halved, in addition to the death rate being doubled, the cost per QALY saved would fall further to $2.12m but this would still be 47 times the usually accepted figure. The remaining parameter is the proportion of the GDP loss due to lockdown rather than mitigation, which is unknown. However, any reasonable proportion will produce a cost per QALY saved well in excess of the usual figure of $45,000.

(Incidentally, I prefer a high number for the value of a QALY –  the Productivity Commission paper discusses some of the options.)

My point in this post is not to articulate a strong personal view on what the government should have done, or should do now.  As I’ve said in past posts, my visceral reactions tends to be more cautious than my analytical one, and one shouldn’t discount visceral reactions.  And in the last lockdowns, my bigger concerns were about the overreach in many of the non-economic restrictions –  remember the government that totally banned funerals, or a solitary swim at a quiet suburban beach.

But I reckon there is crying need for more analysis –  open and transparent, disciplined analysis, exploring a wide range of asssumptions and scenarios.  As I noted, Lally’s paper isn’t that for the period ahead –  we need marginal analysis from here, that explicitly takes account of the uncertainty of the relevant end dates –  but it is still worth reading, perhaps especially so in conjunction with the (slightly longer, more detailed, and better-tabulated) Productivity Commission piece, which represents the sort of analysis we should be expecting from our core government officials –  notably The Treasury –  were they adequately (well, excellently) doing their job.   And as the government ploughs on –  apparently supported by all other parties –  with their eliminationist approach, we deserve a credible, carefully evaluated, exit strategy.  At present, there is none.

UPDATE: Lally has responded to my point that his paper is not a marginal approach (costs and benefits from here) and so can’t shed light on choices from here, and has added a paragraph (in this version) offering one way of looking at that question concluding that

“Switching to a Sweden-style approach is therefore clearly warranted.”

Those who believe that virtue is its own reward (as above) will certainly not be persuaded.   My own reaction is that  –  as per my final paragraph –  more analysis is needed, drawing on the combined expertise of economists and epidemiologists.