Author Archives: Diane Coyle

Historicism and its enemies

Posted on by

By the time I had to head back to the station yesterday, I’d almost finished reading the manuscript I’m reviewing, so I borrowed Karl Popper’s [amazon_link id=”0415278465″ target=”_blank” ]The Poverty of Historicism[/amazon_link] from the shelves of my University of Manchester office mate John Salter (as he teaches political economy, and theories of justice, he has a fine and tempting collection of classics).

I’m not very far into it yet, but it’s striking that Popper excludes economics from his pronouncements about methodology in the social sciences. Eg, “I am convinced that such historicist doctrines of method are at bottom responsible for the unsatisfactory state of the theoretical social sciences (other than economic theory).” No doubt all will be revealed, but it’s surprising to read this at a time when economics is widely criticised.

[amazon_image id=”0415065690″ link=”true” target=”_blank” size=”medium” ]The Poverty of Historicism[/amazon_image]

Next book?

Posted on by

I’ve almost finished reading Richard Flanagan’s [amazon_link id=”0701189053″ target=”_blank” ]The Narrow Road to the Deep North[/amazon_link] – a worthy Booker winner. (Not about economics, of course!) I need a short read for the train tomorrow and think it’s going to be [amazon_link id=”026202859X” target=”_blank” ]Understanding Global Crises: An Emerging Paradigm[/amazon_link] by Assaf Razin.

[amazon_image id=”0701189053″ link=”true” target=”_blank” size=”medium” ]The Narrow Road to the Deep North[/amazon_image]    [amazon_image id=”026202859X” link=”true” target=”_blank” size=”medium” ]Understanding Global Crises: An Emerging Paradigm[/amazon_image]

Nanny state or government Mad Men?

Posted on by

[amazon_link id=”0691164371″ target=”_blank” ]Government Paternalism: Nanny State or Helpful Friend[/amazon_link] by Julian Le Grand and Bill New has landed on my desk and it looks a very interesting assessment of the trade-off between good ‘outcomes’ from nudge policies and the infantilization of individual choice – a useful counterbalance to the series of books from Cass Sunstein advocating nudging. (Gilles St Paul has a counter-nudge book too, [amazon_link id=”0691128170″ target=”_blank” ]The Tyranny of Utility: Behavioural Science and the Rise of Paternalism[/amazon_link].)

Although recognising the power of the argument that governments (and others) can’t avoid ‘nudging’ because the status quo is a choice architecture anyway, I lean towards being very uneasy about the enthusiasm for policymakers using behavioural techniques (familiar to ad men and Mad Men) to manipulate behaviour. So I’m looking forward to this new book.

[amazon_image id=”0691164371″ link=”true” target=”_blank” size=”medium” ]Government Paternalism: Nanny State or Helpful Friend?[/amazon_image]

Mastering ‘Metrics

Posted on by

I had thought Joshua Angrist and Jörn-Steffen Pischke had reached the pinnacle of accomplishment when it came to econometrics texts with their [amazon_link id=”0691120358″ target=”_blank” ]Mostly Harmless Econometrics[/amazon_link]. That’s a fabulous, clear, practical manual – it’s so good that my eldest son, a recently-minted economist, has perma-borrowed my copy. What was particularly good about that book is its clarity about the importance of thinking through your null and alternative hypotheses – it’s one of my bugbears in life that people so rarely are clear about their counterfactual.

[amazon_image id=”0691120358″ link=”true” target=”_blank” size=”medium” ]Mostly Harmless Econometrics: An Empiricist’s Companion[/amazon_image]

Yesterday I read – devoured – almost all of [amazon_link id=”0691152845″ target=”_blank” ]Mastering ‘Metrics: The Path From Cause to Effect[/amazon_link], their follow-up textbook, covering more basic material at a level suitable for students meeting it for the first time – but also for practising economists who learned their econometrics long ago. Econometrics is one of the unsung fields of economics where there has been a stupendous amount of progress during the past 20 years, due to a mixture of more data, faster computers, better software – and improved econometric methodology. A lot of this methodological advance happened after I did my PhD (macro – yes, really! – and econometrics), so although I’ve picked up a lot of the material this book covers, I found it an incredibly illuminating read.

[amazon_image id=”0691152845″ link=”true” target=”_blank” size=”medium” ]Mastering ‘Metrics: The Path from Cause to Effect[/amazon_image]

The perspective the book takes is how to answer questions about causality, and it presents five approaches: randomised trials, regression, IV/2SLS, regression discontinuity design, and differences in differences. Each chapter sets out an empirical question which is used to take the reader step by step through the methodology. The chapters mainly use verbal explanation, with a minimum of equations, and each has a more technical but still extremely clear appendix for students or practitioners needing that material. There are plenty of practical tips, for example, on how to interpret the size of coefficients, how to sense check results, how to check whether there might be omitted variables bias and what sign/size it might be. I love it that they say, your software programme will calculate this complicated standard error for you, no need to memorize the extremely complicated formula (I speak bitterly as one who wrote Fortran programmes to calculate the damn things, 30 years ago). Each of the examples reveals why simple, compelling data correlations of the kind discussed constantly in the world of policy can be completely misleading – or not.

Another nice feature is that each chapter ends with a couple of pages on the pioneers of statistical methods, explaining their contribution and the kinds of empirical problem they were innovating to be able to address.

It isn’t a perfect book. There’s a Kung Fu theme which is meant to make it more approachable and fun, but grated with me a bit. Still, it may be as close to perfection as you can get in this world to an introductory econometrics text. Ideal for students, ideal for older economists who privately admit they could do with brushing up their econometric knowledge a bit, as they look at the figures generated by their software packages. I’ll find this a very useful book, not least when it comes to reading other economists’ papers. It explains how to set about delivering on the huge promise of economics as a careful, empirical science, although of course there is no substitute for thinking carefully about the context in which any given set of data has been generated, and what causal influences could have given rise to it.

Update: Dimitrios Diamantaras pointed me via Twitter to Francis Diebold’s dyspeptic review of Mostly Harmless Econometrics – I think the tone of this is harsh and seems to be mainly concerned with the title; but it is worth noting that the two Angrist and Pischke books indeed do not cover time series econometrics.

Oh so happy….

Posted on by

Maybe the universe is trying to send me a message. Last week I read a self-help book (about how to solve problems) that I’d been sent, [amazon_link id=”1250042038″ target=”_blank” ]It’s Not About the Shark[/amazon_link] by David Niven. This past couple of days I’ve read Paul Dolan’s [amazon_link id=”0141977531″ target=”_blank” ]Happiness by Design: Finding pleasure and purpose in everyday life[/amazon_link]. Although somewhat sceptical about happiness economics, I’d heard him talk about his work and thought it sounded interesting. Well, the first half of the book is indeed interesting – more below – but the second half is a self-help manual. Who knows what it says about me, but I’m just not interested. As far as I can tell, not having read many of them, it seems thoroughly sensible.

[amazon_image id=”0141977531″ link=”true” target=”_blank” size=”medium” ]Happiness by Design: Finding Pleasure and Purpose in Everyday Life[/amazon_image]

Back to the first half of the book. There are several things about Dolan’s approach that make it far more plausible than the conventional approach to happiness. One is that he defines ‘happiness’ as the combination of pleasure and a sense of purpose, and not just the first of these as is standard. This must surely be right; and he argues that the evidence indicates people need a mix of both. You then have to read the rest of the book remembering that ‘happiness’ is not just ‘pleasure’.

Another is that he distinguishes people’s retrospective evaluation of their ‘happiness’ from their experience through time, and argues – again, I think convincingly – that the latter is more reliable for empirical research. He therefore prefers the data collected from the day reconstruction method as coming closer to experienced ‘happiness’ rather than the surveys that ask people to evaluate their state: “overall, would you say on a scale of one to six that ….” The evidence suggests that: “The circumstances of your life (income, marital status, age etc) matter much more to your evaluating self, and what you do matters more to your experiencing self.” So for example, unemployment clearly leads to lower evaluations of happiness but makes little difference to people’s DRM responses because mostly being at work is not a pleasurable experience (although it does give people a sense of purpose).

The third point he makes is that: “Your happiness is determined by how you allocate your attention.” Attention is a scarce resource. In place of the conventional approach which seeks to relate inputs (income, health, sunshine, marriage) to the final output, happiness, Dolan sees these inputs as stimuli in competition for your attention, with attention determining how they affect your ‘happiness’. The same inputs (income, health, sunshine, marriage) can lead to a different output depending on your attentional ‘production function’. He suggests that you can change your production function by directing your attention differently (and in the second half offers advice about how to do it). As he notes: “There are surprisingly few researchers who think about happiness in terms of your time use.” But time is the ultimate scarce resource.

This seems plausible, although I don’t know enough of the psychology literature – dating back to [amazon_link id=”1604590661″ target=”_blank” ]William James[/amazon_link] – to really evaluate it. It strikes a chord with me though since attending a couple of years ago a fascinating workshop in Toulouse on the attention question, when it was clear from the way the cognitive scientists and psychologists talked that a standard economics model of competition subject to a budget constraint (brain energy) could offer real insight into thinking about attention.