Cities, infrastructure and growth

By way of a follow up to yesterday’s post on the new book

, I read recently a very interesting paper by David Starkie (Investment and Growth: The Impact of Britain’s Post-War Trunk Roads Programme, In Economic Affairs, Feb 2015) in which he argues that the construction of the British motorways in the 1960s and 70s had no discernible effect on productivity and growth. One reason was that pre-existing commercial traffic was intra-regional whereas the motorways radiated out from London. Contrast yesterday’s map of how the motorways were planned:

Motorway planning

Motorway planning

with this map from the article showing road freight patterns in the 1950s, before the construction of the motorways.

1950s road freight

1950s road freight

A second reason was that the productivity advantage from time saving was eaten by higher real wages and lower labour productivity. Although it is always hard to discern the effect of specific investments or technologies in GDP growth figures (as the cliometrics literature dating back to Vogel has found over and over – see Nick Crafts on why one should not read too much into the small numbers), I wholly agree with David’s conclusions:

“First, economic relationships are complex and changes can lead to unexpected consequences….Second, the time taken for institutions and commercial structures to
adapt to change can extend over decades, which suggests that the impact on output and growth will be long-term… [Third], as the structure of the economy adapts to transport improvements, there is not necessarily a (sizable) net gain but a partial shift in activity into new economic sectors and geographical areas.”

I’ve argued on the FT’s blog The Exchange that standard cost-benefit analysis does not do a good job when it comes to big infrastructure projects (like a motorway or HS2) because it is a tool for assessing marginal changes, not ones which might involve large non-linearities – behaviour changes or network effects.There is some work being done on non-marginal CBA (eg Cameron Hepburn’s paper for example) but it is not (yet?) standard practice.

Like many/most economists, I think we need much more infrastructure investment now – see for example the report of the LSE Growth Commission,

. My reading of the trunk roads article is that David Starkie would be more sceptical than I am but we certainly share the point about complex, long and uncertain responses; it isn’t about saving 20 minutes on your journey time to increase the amount of time you can spend in a meeting at the other end.

[amazon_image id=”1909890022″ link=”true” target=”_blank” size=”medium” ]Investing for Prosperity: A Manifesto for Growth[/amazon_image]


The information economy

I very much enjoyed reading Cesar Hidalgo’s

. It’s a very original perspective on the process of secular economic growth, bringing together not only several strands of the economics literature – growth theory, institutional economics, social capital etc – but also physics, biology and information theory. So it’s certainly ambitious, and I found it largely persuasive.

[amazon_image id=”B00R3C1V0Q” link=”true” target=”_blank” size=”medium” ]Why Information Grows: The Evolution of Order, from Atoms to Economies[/amazon_image]

Hidalgo’s first point is that we are misled by thinking of the information economy as ‘weightless’ (a term I think I coined, or at least popularised, in my 1996 book The Weightless World) into forgetting that information is nevertheless physical. “Information is not a thing; rather, it is the arrangement of physical things. It is physical order.” He links the order of the economy to the order of the universe that can exist in pockets despite entropy. Economic order comes about through information embodied in things (‘crystallised imagination’) and in the way people organise themselves to apply knowledge and know-how. The first section is rather poetic. Hidalgo describes a tree as a computer powered by sunlight. “A tree processes the information that is available in its environment.” He describes a colleague at MIT who lost both his legs to frostbite while mountaineering, and built his own prosthetics: “He is walking on solidified pieces of his own imagination.”

The book goes on to consider products imported and exported by countries in terms of ‘crystallised imagination’, which requires “an enormous amount of knowledge and know-how.” Knowledge is the set of instructions – a book describing how to play a guitar – and know-how is the practical experience enabling application – the process of learning and practising playing to produce lovely music. Hidalgo introduces the concept of a ‘personbyte’ – the limit to the knowledge and know-how that can be embodied in one individual. For an economy to go beyond that requires collective organisation. He argues against the normal economic argument that economic development is the process of acquiring the ability to consumer more goods and services. “Economic development is based not on the ability of a pocket of the economy to consumer but on the ability of people to turn their dreams into reality.” (This part doesn’t wholly convince me – it’s an appealing case but surely consumption matters too.)

The book then turns to the idea of the economy as a social and technological system for amplifying knowledge and know-how, and looks at institutional economics and the role of social capital in growth in this context. Conveying know-how is difficult, and becoming more so as time goes by and the economy becomes more diverse and complex. The “computational capacity” of the economy needs to grow, but it is constrained by the ability for knowledge and know-how to be embodied in networks of people – hence the value of trust, as it makes that easier.

Hidalgo’s work on the

enters here: there is a strong positive correlation between a complexity index and long term growth (over 10 years). The falling cost of communications and the emergence of standards have increased the number of long-distance market links (instead of transactions within single firms), and this know-how transfer is made far easier by high trust, which enables larger networks. Low trust economies are often characterised by more family firms and rely more on the state to spread knowledge and know-how through its support for industries.

There is a very nice analogy of the economy as a jigsaw. “Moving a complex industry is like trying to move a jigsaw puzzle from one table to another. The more pieces in the puzzle, the harder it will be to move it, as the puzzle falls apart when we fail to move all the pieces at the same time.” It is easier to move just a few pieces to another table that already has part of the puzzle in place. Thus economies mostly grow out from their earlier set of products, which embody the know-how they already have – they already have some of the pieces. The description of this process would very much appeal to evolutionary economists.

A final point that very much intrigues me is measuring growth. Hidalgo makes the same point as the final chapter of my 

book, that in adding things up in terms of their monetary value we are not capturing the value of diversity: three spoons are not as valuable as a knife, fork and spoon. He says that using market price denomination to aggregate implicitly assumes there is friction-free trading; but this is often not possible, especially with stock variables. He advocates looking at the disaggregated economy via input-output tables.  “The mix of products exported by a region’s industries represents a fingerprint of its productive capacities that does not suppress the identity of the economic elements involved.”

So a highly recommended read for anyone interested in economic growth and development. The insistence on the embodied-ness of knowledge and know-how is surely correct, and also a useful corrective to overly-abstract accounts of economic development, including quite a lot of the newer institutional literature (as

argues, this often amounts to the advice to poorer countries to “be more like Denmark”, ignoring the trajectory from here to there). It’s also a pleasure to read such a well-written economics book; from now on I’ll be envisioning the economy in terms of crystals of imagination.


Generalizing about Africa (& why it’s a bad idea)

This morning I attended a breakfast at the Centre for Global Development at which Morten Jerven spoke about his new book,

,” which I’m now looking forward to reading – especially after enjoying his previous book,
. The new book is published today.

[amazon_image id=”1783601329″ link=”true” target=”_blank” size=”medium” ]Africa: Why Economists Get it Wrong (African Arguments)[/amazon_image]  [amazon_image id=”080147860X” link=”true” target=”_blank” size=”medium” ]Poor Numbers: How We are Misled by African Development Statistics and What to Do About it (Cornell Studies in Political Economy)[/amazon_image]

His talk kicked off with a critique of two successive approaches to ‘Africa’ by economists – a category refined in discussion to macroeconomists, and not absolutely all of those. The first approach was cross-country regression analysis, given its definitive shape by

, in which a dummy variable for African countries would have a negative coefficient. (Charles Kenny has an excellent critical review of growth regressions, and Dani Rodrik has a terrific paper on the limitations of trying to get policy prescriptions from this approach.) The second approach takes low growth in African countries as a given and tries to pin that to institutional failures – corruption, clientilism, lack of transparency etc – and is perhaps symbolized by Acemoglu and Robinson in their ambitious
. Morten Jerven said, “There are economists who have written non-modest books.” He argued that the latter approach leads to policy prescriptions of the kind that ask, “Why aren’t you like Denmark?”

[amazon_image id=”0262522543″ link=”true” target=”_blank” size=”medium” ]Determinants of Economic Growth: A Cross-country Empirical Study (Lionel Robbins Lectures)[/amazon_image]  [amazon_image id=”B007HLIUN4″ link=”true” target=”_blank” size=”medium” ]Why Nations Fail: The Origins of Power, Prosperity and Poverty[/amazon_image]

Instead, he suggests focusing on trajectories from today’s specific situation, rather than seeking to explain deviations from a rich world ‘norm’. He argued too for, “Fingertip knowledge of each country’s data.” Yes!! The standard international datasets lead researchers to think history started in 1960, and also are misleading because they interpolate or otherwise guess to fill in the many gaps “They should leave gaps if there are no data – or at least put them in a different colour,” Jerven says.

There was some challenge from the attendees. One said that there clearly is something distinctive to explain about most African economies, where people are still poor on average. Another argued that most economists in the development field do recognise the need for a rich description of specific economies, so the book attacks a straw man. However, I think Jerven is right to highlight the cavalier approach far too many economists have to the data, and their tendency to generalise. Surely he is right when he says, “A paper about ‘Africa’ gets more citations than a paper about ‘Tanzania’.”?

And how valid are those generalisations, when you consider the following Economist covers from 2000 and 2011. Was there really so much change in just over a decade?



Or Rising?

Or Rising?


What should rule the world after GDP?

by Dirk Philipsen is out next month. As a GDP-afficionado, I was eager to read it and found it an enjoyable read and generally thought-provoking, although not agreeing with the author on all points.

[amazon_image id=”0691166528″ link=”true” target=”_blank” size=”medium” ]The Little Big Number: How GDP Came to Rule the World and What to Do about It[/amazon_image]

My main disagreement was more about tone and exaggeration in what is a rather emotional book. There are for example assertions like: “It is safe to say our ancestors, for some 200,000 years prior to the agricultural revolution, engaged in labour only to the very extent to which it helped them survive.” Really? No cave paintings, ancient jewellry, religion? Was Stonehenge essential for survival? Or, because of our “fixation with the accumulation of things”, trying to capture the reality of late 18th century life “by saying that people were poor would represent a fundamental misread.” So were they not less well-nourished than us with more illnesses and shorter lives and many children dying in infancy? Did women (and even men) not spend hours in domestic drudgery? I don’t hesitate to call people in the 18th century poor on this basis; it’s nothing to do with a passion for accumulating cars or handbags. I don’t want more than one washing machine but wouldn’t be without the one – just like Hans Rosling’s mother.

Many readers will like the polemical tone of

; it’s obvious I didn’t. Apart from that, this is an interesting book looking at the history of GDP, its inadequacies as a measure of social welfare, and the environmental consequences of seeking continuing economic growth. It covers some of the same ground as my own
, with additional detail. The book identifies the turn to growth rather than levels of national income as a policy aim in the 1950s. Philipsen attributes this to American optimism as the victor in World War 2. I wonder if it isn’t more related to the dawning Cold War, and the need to demonstrate over and over again that the American system was superior to the Soviet one? Geoff Tily (pdf) pinpoints an OECD document of 1961 as the first official reference to targetting growth, so quite a while after the end of the Second World War. (And as ever for anyone who hasn’t read it, I highly recommend Francis Spufford’s

The Soviet bloc used Net Material Product as their definition of ‘the economy’. The statistics were highly suspect, even those calculated as a best effort by the CIA; it wasn’t really until the mid-1980s, with glasnost, that the true, sustained weakness of growth in the planned economies became evident. There is a nice anecdote in the book: “Once Soviet archives opened to historical research in the years after 1991, we learned that American GDP figures of the Soviet national economy had been far more accurate than estimates provided by the Soviet Union’s own economic planners, who found it near-impossible to come up with reliable data for their centralized planned economy. What did Soviet planners do? They spied on American economists calculating Soviet GDP, and then incorporated what they learned from their American colleagues into their own planning.” Of course, the Americans were spying on the Soviets to get the basic data. Who knows what the figures meant? But the queues and shortages and poor quality of goods were all real.

The second half of the book looks at the ‘Beyond GDP’ debate, although oddly asserting that nobody paid much attention to the issues between Robert Kennedy’s assassination and Congressional hearings in 2001. This is a little US-centric; the global environmental movement kept the candle burning for alternatives all through that period. Philipsen concurs with the kinds of indicator like the Global Progress Index that show progress coming to a complete halt in the 1970s. This always seems absurd to me: even if that was a real turning point in terms of costs to the environment, which gets a heavy weight in the alternative index, there has been a lot of welfare-enhancing innovation and straightforward growth since the 1970s. It’s not just the invention of tamoxifen or the internet, but the fact that more westerners live in houses with phones, indoor toilets and central heating. Sure, there’s a trade-off with the environment but is that really no progress? Nor is Philipsen interested in the issues about defining either market output or social welfare for the growing category of digital goods that are often free and have strong public good characteristics.

As for what to do about it, the book advocates ditching GDP completely, and having a national dialogue about economic goals based on the principles of sustainability, equity, democratic accountability and economic viability. It isn’t clear how this prescription fits with the several ‘dashboard’ initiatives under way now, which are described here. The dashboard approach is attractive, as is public consultation. However, it isn’t yet clear which dashboard is best or what should go in it – it’s easy to end up with a laundry list of good things, and no analytical framework for assessing outcomes or trade-offs. So the real need now is for the hard grind of the kind that Kuznets, Stone and Meade and their many colleagues sustained through the 1930s and 40s in creating the national accounts to make a GDP-plus set of social accounts practical.

I still think dropping GDP altogether would be a mistake – hence ‘affectionate’. How would a government run fiscal policy or a central bank monetary policy without a nominal GDP figure and some of the national accounts detail? The national accounts statistics as a whole also contain a lot of the material that could furnish a meaningful dashboard, so again it would be a waste of an intellectual asset to ditch all of that.

However, the answer to the underlying question, are we going to move ‘beyond GDP’ is: yes.


Inequality, economics and politics – Thomas Piketty at the Bank of England

On Friday I attended an excellent conference at the Bank of England (organised by the Centre for Economic Policy Research) at which four speakers – Peter Lindert, Jaume Ventura, Orazio Attanasio and Tim Besley – gave presentations on aspects of

, and Thomas Piketty responded to their comments and critiques. The presentations are due to go on the Bank’s website at some stage, although aren’t there yet.

[amazon_image id=”B00I2WNYJW” link=”true” target=”_blank” size=”medium” ]Capital in the Twenty-First Century[/amazon_image]

Peter Lindert drew on material from his forthcoming book with Jeffrey Williamson (and also has a working paper on the Piketty book), to characterise the long-run trends in inequality as the result of ‘lucky’ historical accidents that wipe out concentrations of wealth, combined with policies that help the society stay equal. The period 1910 to the 1970s was the ‘great levelling’, due to wars, and there has subsequently been a fanning out in countries’ experience but in many cases a rise in top incomes. In this, he agrees with Piketty’s book; but disagrees with the famous ‘r>g means rising inequality’ prediction. Demography, technology and politics (mainly education and inheritance tax) – with a role for geography in the case of frontier societies – are his favoured explanations. South Korea, for example, has an inheritance tax of 50%: in principle the heirs of the ailing Lee Kun-Hee of Samsung will be due to pay £4bn in tax when he dies.

Jaume Ventura focussed on the dynamics of economic growth that might explain inequality trends: a u-shaped long-run evolution in the capital-income ratio; the changing components of wealth, with land playing a decreasing part; a not-quite-u-shaped evolution in capital-labour shares (the capital share has risen but is not back to its historic highs); and a stable return to capital of 4-5%. Like Prof Lindert, Prof Ventura does not think the model implied in

, and the r>g inequality, stacks up. He argued that the assumptions in the book imply a world of multiple equilibria and cycles or chaotic dynamics, and also that the growth model ignores all the lessons of endogenous growth. He said: “There has been a change in the deep structure of capital in the 21st century.” Bubble-like capital gains now play a large part.

The two final papers moved on from diagnosis to solutions. Orazio Attanasio described the recent research confirming the importance of people’s early years, before the age of 3 and certainly before 10, for their lifetime earnings. Parents’ status and income is important but works through the early effects on a child’s cognitive and non-cognitive abilities. Early experiences even have epigenetic effects. He concluded that the biggest policy problem is the bottom 10% in society, not the top 1%. But also – optimistically – that individuals’ life outcomes can be changed by appropriate early interventions.Prof Attanasio also discussed the optimal level of the top tax rate – recent estimates range from 42% to 86% as the rate that would maximise revenue – to which Thomas Piketty replied that top tax rates should be seen as pollution taxes, the aim being to stop behaviour imposing an externality rather than maximising revenue. However, as 25% of UK income tax comes from the richest 1% (54% from the richest 10%), it would be a bold government that ignored tax revenues.

Tim Besley gave a fascinating talk about the political economy of inequality, referring to his most recent book with Torsten Persson,

. He asked, does inequality undermine effective governance? In democracies there is normally thought to be a compact where the rich trade some redistribution in return for security of their property rights. But people don’t mind some kinds of high incomes – footballers vs bankers. And there is no link (looking across countries) between either top (marginal) tax rates and inequality. Quoting Lenin’s
, Prof Besley said there is no empirical support for the frequent claim that the median voter is decisive in political choices: “Democracy for an insignificant minority, democracy for the rich – that is the democracy of capitalist society.” He went on to show evidence that inequality limits the demands for social action, which over time reduces the capacity of the state to act – its legal capacity, fiscal capacity, and capacity to deliver public goods. Finally, he said, there is also evidence that from time to time the values of citizens shift markedly – after the war, for instance, in the overwhelming support for the NHS and welfare state. I couldn’t agree more with his final comment that there are three kinds of economics – the positive, the normative, and political economy.

When I read

, I found it hard to work out the growth model implicit in the book, so was reassured that much cleverer economists than me found fault with them. However, as several of the speakers said, that doesn’t make it any less important a book. It has changed the public debate and climate of opinion about inequality, in large part through the long years of hard work giving us the first ever (open) data base of historical figures, the World Top Incomes Database. Jaume Ventura said his advanced macro students have to read it, along with Angus Maddison’s
I was also most impressed by Prof Piketty’s openness to the critiques: “Every conclusion in the book is a temporary conclusion, and subject to discussion,” he said.

[amazon_image id=”9264022619″ link=”true” target=”_blank” size=”medium” ]Development Centre Studies The World Economy: Volume 1: A Millennial Perspective and Volume 2: Historical Statistics: v. 1 & 2 combined[/amazon_image]