We Need To Talk About: The Deficit

Cutting the deficit by gutting our investments in innovation and education is like lightening an overloaded airplane by removing its engine. It may make you feel like you’re flying high at first, but it won’t take long before you feel the impact. – Barack Obama

Whenever we talk about national budgets, it doesn’t take long before someone mentions the “national deficit” and the “national debt”. Indeed, as I’ve noted in some of my commentary on GERS, sometimes it can seem like this is the only thing that makes it to the headlines at all. The almost unchallenged “wisdom” is that a government spending more than it raises in taxes is a terribly bad thing. It’ll leave future generations burdened with debt and, anyway, you wouldn’t run a household’s finances that way, would you?

This is a wisdom that has led us to Austerity and there is barely a politician out there who speaks for any other ideology. It’s not just the Tories. Corbyn’s team is at it, at least  by degrees and even Nicola Sturgeon often speaks the same language when defending Scotland’s finances. (And, yes, I’ve used that same language in the past too. Life is about learning.)

Of course, the root of the obsession lies with the fact that the “national deficit” is something that seems quite close to the politicians and therefore it’s something that they should be “sorting out”. But maybe the economy is a bit less simple than this. Maybe, like the fable of the blind men appraising the elephant, one can get a false impression of the whole by getting too close to one detail.

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Trumped Up Trade Talk

“Sooner or later every war of trade becomes a war of blood.” – Eugene V Debs

This past week has been an interesting one in terms of international trade news. President Trump announced, via a Tweet, that he was slapping import tariffs on Chinese steel and that “trade wars are good, and easy to win“.

The ripples of this announcement are still spreading but already countries and trading blocs like Canada and the EU are considering retaliatory tariffs.

The thing is, China isn’t even a particularly major player in US steel imports. It barely factors on any of the top fives by specific products.

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Irrigating the Data Desert

“Why speculate when you can calculate?” – John Baez, American mathematical physicist

Last week saw the release of Common Weal’s latest policy paper, Scotland’s Data Desert, which examined the gaps in statistical data for Scotland and called for a Scottish Statistics Agency to help fill them.

We weren’t the only ones studying the problem of the dearth of data in Scotland. As part of a year-long program of research into this topic, we got involved with the Scottish Parliament’s Economy, Jobs and Fair Work Committee who had launched their own public consultation looking specifically at the state of economic data in Scotland.

Our response to that consultation led to us being invited to present evidence directly to the committee in September 2017.

The final report from the committee’s investigations was published a few days ago and we are very pleased to say that many of our recomendations have been accepted in the conclusions of the report.

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Scotland’s Data Desert

My latest policy paper for Common Weal – Scotland’s Data Desert – has just been published and can be read here or by clicking the image below. There has also been coverage of the report in The National here and here.

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As a region of the UK, Scotland is in many ways better served by data gathering and analysis than its counterparts. However, as Scotland takes greater control over domestic issues and as the constitutional debate continues to look towards a future in which Scotland takes full responsibility for its own affairs the question is raised as to whether even this level of data provision is adequate for current or future needs – especially in a world where data becomes ever more vital in the development and support of policy. Well served though Scotland may be as a region, as a country it remains a relative “data desert” compared to nearby independent countries.

Many times we’ve watched as politicians and activists have misused data in the public sphere. Sometimes this manifests as a simple misunderstanding of what the data actually says (As when people ask how much of Scotland’s trade leaves the UK via “English ports”). Sometimes though, it’ll be used to make a political point in ways that the data doesn’t really support (such as discussions which use GERS to project beyond what it actually says on Scotland’s finances). There have also been instances of policies being implemented on the basis of limited evidence or of policies being implemented and then left to run without any program in place to monitor their effectiveness.

My latest policy paper for Common Weal is the culmination of over a year of research into the gaps and limitations of data provision in Scotland and discussion with people within the data sectors and civil service in Scotland and the UK. As a political lobbying and research organisation, we are – like many others – dependent on access to data to be able to inform our work and many times we have hit barriers where key data couldn’t be released or simply did not exist.

A Scottish Statistics Agency could help address many of these issues by expanding, co-ordinating and codifying data gathering within Scotland.

An independent Scotland will certainly need its own data and statistics agency but this isn’t just an independence issue as it could be done right now in a devolved Scotland and there are compelling reasons to do so. As said, Scotland already goes above and beyond the UK’s data gathering in many areas but there is certainly room to grow further.

The SSA could well take the form of a monolithic, centralised agency – a bit like the UK’s ONS – in which most or all policy level data is gathered by or for them. It could equally take the form of a more decentralised system whereby a central body co-ordinates and issues targets and directives but the actual gathering could be done by specialised bodies, statisticians embedded within government departments and even by academics and think-tanks. If this model was employed then a system of “kitemarks” could be used to mark data which meets the stringent Code of Practice which would identify data as being good enough for policy-making.

This kitemark system is already used by the UK Statistics Agency (the governing body which regulates the ONS) but could be used to either reflect a Scotland which applies even higher standards than the UK or could be expanded to identify data from outside of government (such as academics and think tanks) which meet those standards. This could allow for greater prespectives to influence government but could also limit the misuse of data by third parties by setting a benchmark to meet.

Of course, this isn’t just a problem of gathering data. As said above, often the data is gathered but difficult to find, difficult to manipulate or cannot be easily combined with other data due to conflicts in their methodologies. Where data can be combined, it has been a reported problem that different groups may be doing the same processing independently. This increases the chance of errors creeping in and also, crucially, results in a lot of time wasted between those groups.

An SSA could therefore be charged with ensuring that policy data meets high standards of trust, transparency, usability and consistency. It could also be responsible for maintaining a central data portal – much like Eurostat or the Gapminder Project – which would allow access to as much data as possible but can do it in a way which makes that data easy to view whether the viewer is an interested member of the public or an expert researcher.

People will, of course, ask how much an SSA would cost and, in truth, the answer is difficult unless we know the precise model – it’s harder to count the budget of a decentralised model than a centralised one – but where Scotland’s proportional share of the UK’s spend on statistics may be around £15 million, other nearby countries like Denmark and Sweden spend several times this figure and create several hundred highly skilled jobs in the process. Even these sums are comparatively small in terms of national budgets but will surely pay for themselves in terms of better targeted, better monitored and, quite simply, better policies.


Common Weal’s ability to do research of this kind is entirely reliant on the generosity of our donors and supporters, both one-off and regular. If you would like to contribute, please visit our website at: allofusfirst.org/donate/

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Banking for the Common Good

“Though the principles of the banking trade may appear somewhat abstruse, the practice is capable of being reduced to strict rules. To depart upon any occasion from these rules, in consequence of some flattering speculation of extraordinary gain, is almost always extremely dangerous, and frequently fatal to the banking company which attempts it.” – Adam Smith, The Wealth of Nations

Do we expect our schools to be run as profit-making enterprises? How about our police services? Fire services? Hospitals? Roads? Rail? How about our utilities like electricity and water?

How you answer those questions will very likely correlate with the political party you most affiliate with and may even depend on where in the UK you live. Some of these may be precious, lifeline public services. Some used to be but were sold off. Some have always been privately run.

Some may work best as purely private institutions – where the market can use efficient competition to create choice and maintain low prices.
Some may work best as entirely public institutions – it can be difficult to “choose” another rail operator if the only trains at your station are run by one company. or if your house is burning to the ground because you had the “wrong” fire mark on the wall or because you can’t pay them to put out the blaze.
Some others may work in a “mixed” system – Perhaps you genuinely can choose to get your healthcare from an NHS hospital or pay for private treatment elsewhere.

How about banks?

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Dundas House, Edinburgh. HQ of RBS.

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The Limits of GDP

“Distinctions must be kept in mind between quantity and quality of growth, between costs and returns, and between the short and long run. Goals for more growth should specify more growth of what and for what.” – Simon Kuznets, developer of the measurement of GDP on the limitations of the statistic.

There’s a measurement of technological advancement in science and science fiction circles known as the Kardashev Scale. It measures how advanced a civilisation is by how much energy it consumes or is able to harness using its technology.

A Type 1 civilisation is able to use the same amount of energy as falls on their home planet from their home star. For Earth-Sol, this is a power consumption of about 7×1017 Watts.

A Type 2 civilisation is able to harness the entire energy output of its home star – either by colonising many star systems or by fully enclosing their home star by energy gathering technology like a Dyson Sphere. For our star, this is about 4×1026 Watts or about 500 million times the energy consumption of a Type 1 civilisation.

Finally, a Type 3 civilisation has the technology to harness the entire energy output of a galaxy – a feat rarely reached in even the most ambitiously scoped sci-fi but see Stephen Baxter’s Xeelee Sequence for beings which are capable of at least this and more. This level of tech involves the consumption of about 4×1037 Watts or about 100 billion times the power used by a Type 2 civilisation.

And where does our wee planet sit in all of this? Carl Sagan extrapolated from these points to create a more comprehensive mathematical formula for calculating a given civilisation’s Kardashev number. He also estimated in 1973 that humans generated an average of 8 Terawatts of power which gave us a Kardashev Number of about 0.70. As of 2015, our energy generation has increased to an average of about 19 TW which makes us now a Type 0.73 civilisation. Extrapolating out linearly, we should hit Type 1 around the year 2325.

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Imagine that the only thing that the scientific community really cared about was our progress up this scale. All of science was bent towards our expanding our power generation and consumption base. And all that politicians cared about was their “Kardashev Growth per year”. It wouldn’t matter if your discipline was physics, chemistry, biology or whatever. Anything that grew the Kardashev number was funded. What would we be missing if that was all we cared about?

(For my academic friends who want to draw parallels with the current obsession with citation number and impact factors…you’re not wrong, but…next time.)

It’s worth noting that whilst total global power generation has increased by a factor of 2.4 since 1973, global population has only increased by a factor of about 1.8. The “global average human” today is using about 33% more power than the “global average human” of 1973. This is due to a massive reduction in global poverty and an unbelievable expansion of buying power and access to technology around the globe.

Of course, there are limits to this kind of measurement. Technology doesn’t just get more powerful and more widespread as it develops, it also gets more efficient. The fitness band I’m wearing right now weighs less than 100g but has orders of magnitude more computing power and uses orders of magnitude less electrical power than my first desktop PC from the mid-1990s – never mind the room-sized behemoths of the early days of computing in the 1950s and ’60s.

We also must think about the environmental impact of our technology – another major difference between 1973 and now is the exponential expansion of renewable energy technology at the expense of fossil fuels.

A 2015 Megawatt emits about 20% less carbon dioxide than a 1973 Megawatt and that figure is about to fall dramatically over the next decade as we electrify our heat and transport industry.

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So obviously, rendering a civilisation’s level of technological development down into a single number and then measuring the growth of that number might be interesting and may be useful as a very broad comparator but it probably doesn’t tell anything useful about the shape of that society or what’s going on inside it.

So why do we expect the same from other renderings such as Gross Domestic Product?

This measure – essentially the sum value of all economic activity within a country in a year – was developed in its modern form in the 1930s and has since become the gold standard of national statistics. Huge swathes of statistics are measured either in relation to it (think of “national debt as a % of GDP”) or as a derivative of it (GDP growth” or “GDP per capita”, for instance).

But even at its inception, the creator of it noted the limitations. A measure of the growth of GDP says very little about how that growth has occurred or who has benefited from it.

I was able to discuss some of these issues when I visited the Scottish Parliament’s Economy, Jobs and Fair Work Committee earlier this week as well as in an article in CommonSpace yesterday.

The Scottish Government has, to its credit, tried to improve some of the measurements it uses via program like the National Planning Framework. One of these is the idea of “inclusive growth” which explicitly states that measures should be taken to ensure that when economic growth occurs, it should not simply accumulate with the top few percent.

It’s a laudable goal but I still have my reservations in that the metric is still pinned onto the concept of “growth”. Just as a growing economy may accumulate wealth in the top, it’s possible that a recession could increase inequality too. Imagine a drop in the economy that causes mass unemployment, reduction in working hours, an increase in casual, part time and “gig” labour whilst at the same time the wealthiest are bailed out by the state. You know…a bit like what happened in 2008.

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Just as it’s possible to try to ensure inclusive growth, it should also be possible to ensure inclusive de-growth when recessions come and inclusive stasis when economies are growing. The government would be well advised to focus as much on inclusivity as it does on growth, maybe more so.

To be fair, there was at least some logic to using GDP as our measure of economic development. For many years, wage growth was pretty firmly linked to economic growth. If the company you worked for did well, you did well. But two great shifts have happened in the past 40 years. The first came in 1979 with the rise of neoliberalism. The economic programs enacted by Thatcher and others were coupled with a decoupling of wages and growth such that the latter started to pull away from the former. The gutting of the unions and the reduction of collective bargaining was perhaps chief among those reforms.

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The second decoupling came in the wake of the 2008 Financial Crisis. This time it came in “productivity” – the amount of GDP generated by a given hour’s labour. It’s a complex topic but part of this has come from the rise of the “gig economy” where folk have – often through somewhat convoluted means – become “self-employed” and have lost access to even individual bargaining. With no commitment at all to the company that they “service” (rather than work for), it’s no surprise that innovation and investment have declined. Not that it’s the fault of those workers. With no commitment to them, the company needn’t care beyond short term profit extraction and share price either.

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Another possible reason for the decoupling of productivity and wages (as well as the stagnation of productivity overall) is the rise of certain sectors of the economy that don’t quite fit with older measures such as “added value” and suchlike. I’m talking here about jobs like personal care. It could be possible to “increase productivity” in personal care but if that means “service more clients per shift” then what you’re asking carers to do is cut visiting times from 30 minutes down to 15 minutes down to 10 minutes…

So maybe we don’t want “productive” care. I’d prefer effective care. And maybe jobs like care don’t produce huge feedback multipliers in the economy but there are other ways that such care could be considered “valuable”. Especially to the person receiving that care.

So, just as the Kardashev Scale is for technology, GDP should only be dubiously taken as the be-all-and-end-all of economic development. Politicians really should start taking note of what’s going on underneath that headline number. It’s a harder story to tell, true, but economies are far too complex for the “simple” story to be sufficient.

And if it turns out we’re simply not measuring enough to answer our questions, well…that’s a story for another day.

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