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May 12, 2017
Lecture to Bath Royal Literary and Scientific Institution
10 May 2017
There is a lot of discussion going on about the state of economics today. A lot of criticism is coming from outside the academic establishment – from students, journalists, public intellectuals and policy makers. This has occurred since the financial crash of 2008 and subsequent recession, although it can also be seen as really an intensification of much older debates about economic thought that have been going on for many years before that. There has been intense debate, within the economics ‘profession’, about the way the subject was done, going back at least to the sixties if not earlier. However it had ceased to take place within the mainstream and nowadays most critical writing is confined to a few fringe academic journals, while the main journals have become almost exclusively the domain of a narrow range of orthodox thinking. This lack of open debate was very unhealthy.
(By the way, economics must be one of a very few academic disciplines whose members refer to themselves as a “profession”. I wonder if this terminology endows the orthodoxy that occupies the pages of the mainstream journals and textbooks with additional authority.)
One of the most remarkable instances of criticism emanating from government circles occurred in 2008 when the queen was visiting LSE just after the crash and she asked the assembled dignitaries why nobody had seen it coming.
One answer is to say that economics is concerned with understanding how the economy works rather than forecasting. After all, nobody would expect a political scientist to forecast the result of every election. But that begs another question: “if economists understand how the economy works, how come they have not been able to design institutions and policies to prevent such crises from happening?”
But anyway many economists are engaged in forecasting and their inability to spot the crash was a major failure of their methodology. The fact that the crash happened was also a consequence of seriously flawed thinking underpinning the policy regime in force.
Following the crash students intensified their complaints about the syllabuses of courses they were being taught. They complained that their courses were too preoccupied with the properties of abstract models not rooted in the real world and they demanded more relevance. For example a group that started at Manchester University called the Post-Crash Economics society
(http://www.post-crasheconomics.com) was set up to campaign for more relevance and methodological pluralism in courses, but it met with limited success. This is actually a renewal of earlier campaigns such as the post- autistic economics movement that began in France in 2000, arguing against the dominance of a single method – which is known as neoclassical economics - and for a pluralism of approaches. They likened the mainstream discipline of economics to someone suffering from autism: someone who continues with the same asocial behaviour regardless of any outside influences. This gave rise to the Post Autistic Economic Review, now renamed the Real World Economic Review. Review. (http://www.paecon.net/PAEReview/ )
So what is the problem? Are the students and critics right? Or is it just that they lack the skills necessary to do mainstream economics?
Is economics too mathematical?
A very common criticism of economics teaching and scholarship generally is that it has become far too mathematical. Students today have to take and pass prerequisite courses in quantitative methods before they can study economic principles. Both mathematical and statistical techniques are required. Also scholarship is heavily mathematical with economics writing in academic journals and textbooks couched in algebraic symbolism which makes it extremely difficult to read for all but a few initiates who already have expertise in the area. The usual response is to say that complainers should just get on with it: that is the way economics is.
It is true that academic writing about economics should be written in clear language and not pretend to be something – mathematics - that it is not. This is a major and valid criticism of the way economics is done.
It is interesting and perhaps somewhat ironic that today’s economists who write in this way are failing to follow the advice of one of the founding fathers of neoclassical economics, Alfred Marshall,
who was responsible for the supply and demand framework and partial equilibrium analysis of markets. He wrote:
“[I had] a growing feeling in the later years of my work at the subject thata good mathematical theorem dealing with economic hypotheses was very unlikely to be good economics: and I went more and more on the rules - (1) Use mathematics as a shorthand language, rather than an engine of inquiry. (2) Keep to them till you have done. (3) Translate into English. (4) Then illustrate by examples that are important in real life. (5) Burn the mathematics.”
His work was mathematically very rigorous but written so as to be comprehensible to the reader. That does not suggest that mathematics has to be a prerequisite to studying economics at undergraduate lev el though it might be needed before conducting research.
There is an issue about what sort of quantitative techniques students should be expected to know. Statistics is essential because economics is all about measurement. But in their first year students only need to be taught basic economic statistics – that is the measurement of the economy. Students should know about how an index number is constructed so they can understand things like the consumer price index, or the rate of growth of GDP, and graphical representation of trends. Only high school maths is required for this. This is quantitative methods for describing the economy at a very basic level, the foundations for a proper understanding.
More advanced topics such as optimization theory, statistical inference and parameter estimation have to do with economic modelling and not required for an economics degree. Some of the techniques students are taught are really of questionable use. It really does not aid understanding or develop useful skills to have to derive demand functions from first principles expressed exclusively in algebraic terms, with a given utility function – very few are likely to ever need to do that in their later career, only those who go on to very advanced theoretical research. Studying the idea of a demand function and the nature and meaning of a utility function are far more important.
So I do not agree with the simple proposition that the subject is just too mathematical. Quantification is intrinsic to economics. But I think that often what is taught is the wrong sort of quantitative methods – more to do with abstract economic modelling than with the measurement of the real world economy. And too much economics scholarship is expressed using needless mathematical notation, a form of jargon. Economists should heed the advice of Marshall and write in clear English.
The reduction of macro to micro: the neglect of Keynesian economics and the ascendency of neoclassical economics
What has gone wrong with economics is not only that there is too much writing couched in needlessly mathematical terms but something more fundamental than that. It is that there has occurred a major shift of focus away from macro to micro. There has also been a shift away from real-world empirical relevance to mainly theoretical argument. Macroeconomics – by which I mean primarily the economics of Keynes – is no longer taught in many universities. By that I mean it is not taught properly. The economics of Keynes has been sidelined.
To continue reading, download the full paper here.
February 21, 2015
Writing about web page http://www.lrb.co.uk/v37/n04/simon-wren-lewis/the-austerity-con
A must read piece by Simon Wren-Lewis in the LRB on the false economics of austerity. He shows that trying to cut the deficit by austerity measures is counterproductive and damages the economy. He estimates that the cost to the UK economy in permanently lost output due to George Osborne's policies is at least £100billion or 5% of GDP.