Economics runs on images. The language of economics is built upon the iconic imagery of supply and demand curves, circular flow models, GDP growth curEconomics runs on images. The language of economics is built upon the iconic imagery of supply and demand curves, circular flow models, GDP growth curves and IS-LM models. Raworth seeks to change the language of economics. How? By changing the fundamental images that define economic models.
So what ails Modern Economics? Raworth is not exactly correct in saying that modern economics still runs on the rational-actor model and hence is limited by it. Not when we have Nobel laureates sitting pretty with bestselling books and superstar ideas about behavioural economics that tears down the old models. The problem in fact is not that the models are flawed or that economists are unaware of their own limiting assumptions built into the models. The real problem is that the aims, the end goals, of modern economics are still perhaps out of sync with reality. The neo-liberal idea that everything can be left to the market is only a pipe-dream - no serious policymaker depends on it today. Much of economic progress, just like much of political and societal progress have been made, as Pinker says, by the gradual pushing of the left-right boundary further and further towards the left. What was once marxist is now neo-liberal. The good fight goes on, but trusting the market is not the real problem of the day. That is not the reform needed in economics.
The next big reform has to focus on the overriding goal of all economics - GROWTH! Economic Growth is the assumed solution to all ills. Raworth takes this to be a case of an almost religious belief in a 'Kuznet's Curve of Everything' (in fact a good marker to test if any argument is in part belief-based is to see if there is an assumed Kuznet's curve present in the argument). Almost every argument and every policy seems to assure us that it will get worse now, but it will get better tomorrow as long as Growth continues. Growth must go on.
This is the core paradigm that Raworth really wants to shift. Raworth asks: “What if we started economics not with its long-established theories, but with humanity’s long-term goals, and then sought out the economic thinking that would enable us to achieve them?” How spectacular is that question? Instead of chasing growth and assuming it will give us the things we value, can economics chase the things we value directly?
To be honest, there is nothing particularly new in Raworth's attempt. This is exactly what has been the attempt since the radical 'Limits to Growth' intellectual movement took root. What Raworth is doing differently though is that here the revolution is waged, not using speeches and big ideas, but using images. And in economics nothing is as powerful as images!
Enter the Doughnut: a sort of miracle diagram that is apparently going to change the world. The inner ring represents the “social foundation”, the situation in which everyone on the planet has sufficient food and social security. The outer ring represents the “ecological ceiling”, beyond which excess consumption degrades the environment beyond repair. The aim is to get humanity into the area between the rings, where everyone has enough but not too much – or, as Raworth calls it, “the doughnut’s safe and just space”. [image] Thus the Doughnut is the image Raworth uses to represent the limits to growth, and to rub in the fact that we cannot rely on the processes of growth to redress inequality and solve the problem of pollution. Now, the doughnut is a powerful image and Raworth is a great ambassador for it, but it might not be enough, especially because Raworth clearly pitches her camp on the left as far as economic arguments are concerned - and as we know by now, that is often enough for whole ideas to be rejected unilaterally by the rest of the political and economic community... Reading the book, one feels that she seems a bit overoptimistic about the possibility of changing the predominant neoliberal/conservative mindset, essentially through persuasion, as if she is not fully aware of how deep the fault-lines lie in these things. The doughnut may not be powerful enough an image to pull this off...
But, the main point of the book is not just about the Doughnut, it is that there is a fresh new path towards changing the economic orthodoxy that is built into all political debates - most of the simplistic economics debates are possible because the right has access to some basic ideas and concepts that can be visualised easily - 'Economics 101', as they keep repeating.
Raworth's attempt at providing a powerful counter, and hence a possibility of rebuilding the imagery of economics textbooks is commendable, and could eventually be a game changer - not because of the idea of the doughnut, but because of the approach it represents. A truly significant modern economics book, for a change....more
Take a fun book and add calculus to it. You might expect that to ruin it. Well, no. It 'supplements'. This is the supplementary book to back up the CaTake a fun book and add calculus to it. You might expect that to ruin it. Well, no. It 'supplements'. This is the supplementary book to back up the Cartoon Intro to Economics by the same author. Here we get a summary of the cartoon stuff in plain english, just in case we were not able to follow illustrated examples and adds algebra and plenty of problems and detailed solutions. Together these two books, do make a pretty good text book. But the structural issues pointed out in the review to the original book still stands.
Historians like Braudel can only dream of the kind of history that can be written now. Now that we have minute and granular data on billions of indivi Historians like Braudel can only dream of the kind of history that can be written now. Now that we have minute and granular data on billions of individuals, on how they are living, of what they like, what they search for, who they prefer to be with, what they enjoy reading and watching, where they spend their time, how they react to political events, what their fears are, etc. -- a veritable flood of data -- a dataclysm.
This book is an early, tentative, and often highly constrained attempt at creating the sort of narrative that this flood of data allows. It is restricted to the data collected from a dating site and hence comes with all the constrains and conditions that would imply (the sample would tend to be young, unmarried, middle-class and mostly male, for instance).
Event though the book does not have any revelations about who we are (when no one is looking -- or at least, when we think so!), it does attempt to corroborate some of the social research that usually reaches us as anecdotes with hard data, and that is its real value -- as a trend-setter.
If you read a lot of popular nonfiction, there are a couple things in Dataclysm that you might find unusual. The first is the color red. The second is that the book deals in aggregates and big numbers, and that makes for a curious absence in a story supposedly about people: there are very few individuals here. Graphs and charts and tables appear in abundance, but there are almost no names. It’s become a cliché of pop science to use something small and quirky as a lens for big events—to tell the history of the world via a turnip, to trace a war back to a fish, to shine a penlight through a prism just so and cast the whole pretty rainbow on your bedroom wall.
I’m going in the opposite direction. I’m taking something big—an enormous set of what people are doing and thinking and saying, terabytes of data—and filtering from it many small things: what your network of friends says about the stability of your marriage, how Asians (and whites and blacks and Latinos) are least likely to describe themselves, where and why gay people stay in the closet, how writing has changed in the last ten years, and how anger hasn’t. The idea is to move our understanding of ourselves away from narratives and toward numbers, or, rather, to think in such a way that numbers are the narrative.
That is why the author says that he likes to think of his book a sort of Anti-Outliers. The exciting stories are not limited to what a few exceptional individuals are doing, but also in the aggregated activities of millions of Joes. No anecdotes for you, but here are some fun graphs....more
Quite comprehensive - and with a more approachable presentation than most modern text books. Surprising. Should read more of the Economists and less o Quite comprehensive - and with a more approachable presentation than most modern text books. Surprising. Should read more of the Economists and less of the Textbooks (and even less of Commentaries)....more
A very ordinary effort. Levitt & Dubner tells us the recipe to “Think Like a Freak”. Most of the ingredients are quite ordinary and alm Not Very Freaky
A very ordinary effort. Levitt & Dubner tells us the recipe to “Think Like a Freak”. Most of the ingredients are quite ordinary and almost all are trodden territory. A wholly unnecessary book.
1. That all the Big Problems of the world are too tough to solve for ordinary people like us and that we should nibble at the edges. - A bit about game theory and about how most problems arise due to private vs public conflicts and how we need learn to realign incentives to solve small problems. Keep nudging the incentives and solving small incentive-problems. The very soul of Freakonomics. 2. That we should learn - to say “I don’t know” more often, especially the experts. A few stories thrown in about how stupid people who try to predict the future are. - Also, don’t bring your moral compass into your predictions/decisions. And always look for feedback if you want to keep improving. 3. That we have to learn - to ask the Right Question. Reframe the question to get ahead. - Endlessly experiment to get the right feedback on the reframed problem. The ‘abortion & crime’ story is repeated. AGAIN! 4. That we should - Think like a Child: Have fun. Don’t ignore the obvious. Think small. 5. That we should obsess over - Incentives, Again: Understand contexts; Reframe contexts. Use appropriate incentives. NEVER mix your incentives! 6. That we can win arguments: How to win an Argument: Don’t pretend your argument is perfect. Acknowledge their viewpoint and... meh. 7. That we might want to think of - When to Quit: Avoid the sunk cost fallacy. BTW, this chapter is for us too — We (Levitt & Dubner) just might quit writing this stuff!
In short, nothing really exciting, nothing novel. Nothing that fires the imagination. I am not at all freaked out by the ideas & stories presented here. They can still spin a good yarn, but that gets old fast without the essential ingredient - radical ideas.
If indeed the freakish duo decides to call it quits, it would be a pity that this was added to their otherwise magnificent legacy. ...more
The Mismeasure of "Progress": A Race to the Bottom?
This is a quick history of macroeconomics, dressed up as a history of GDP. It does cover the in The Mismeasure of "Progress": A Race to the Bottom?
This is a quick history of macroeconomics, dressed up as a history of GDP. It does cover the initial struggles of measurement, standardization etc, and also covers the modern debates over the efficacy of GDP/GNP as a useful aggregate measure. But in the end it is just a very compressed history of the evolution of macroeconomic ideas - primarily because the measurement tools of any science will closely follow the ideas that create the imperative to measure in the first place.
GDP: History’s Puppet
One interesting thing to note is that it was always crises that led to adjustment in measuring:
The need to pay for the World Wars made us realize the need to quantify the economy better. It was the experience of the Great Depression had already naturally focused political attention on how fast—or not—economic output was growing, and governments wanted both to measure and to influence it.
Economic crisis has always been trigger for interest in alternative measurements. The combination of the Great Depression and World War II brought us GDP in the first place. The crisis of the mid-1970s combined with the nascent environmental movement to prompt an initial wave of interest in new types of indicator, although these took a decade or so to come to fruition.
The present crisis has breathed new life into a range of alternative approaches such as “happiness,” welfare indexes, and dashboard approaches, not to mention raising a serious question mark over the current standard method for calculating the contribution financial services make to the economy.
Is this crisis (or this cascade of interacting crises) the time for leaving behind GDP and turning to some new way of understanding and measuring “the economy”?
+++
Which brings us to the following discussion on what could happen if we fail to adjust GDP to reflect the new crisis and the urgent requirement to orient our economy better by measuring it better.
Standards-Lowering Competition: A Race to the Bottom?
As Herman Daly says in his 'Ecological Economics':
At the same time that international trade agreements make it difficult for countries to legislate against externalities, the need to compete for market share reduces national incentives to legislate against externalities in what is known as standards-lowering competition (a race to the bottom).
The country that does the poorest job of internalizing all social and environmental costs of production into its prices gets a competitive advantage in international trade. More of world production shifts to countries that do the poorest job of counting costs—a sure recipe for reducing the efficiency of global production. As uncounted, externalized costs increase, the positive correlation between GDP growth and welfare disappears or even becomes negative.
Recall the prescient words of John Ruskin: “That which seems to be wealth” becomes in verity the “gilded index of far reaching ruin.” The first rule of efficiency is “count all the costs,” not “specialize according to comparative advantage.”
+++
The continued use of GNP/GDP as a proxy for welfare should remind us of the quote often attributed to Yogi Berra:
Philip Hans Franses takes the reader through the most elementary concepts of econometrics, or as much as is possible in such a s A Demonstrable Problem
Philip Hans Franses takes the reader through the most elementary concepts of econometrics, or as much as is possible in such a short book. This is well supplemented by a series of practical research questions in various economic disciplines, which are then ‘demonstrated’ for the reader by showing how they can be answered using econometric methods and models.
This makes the book a good introduction to the empirical practices of the ‘real’ econometric world, which, as the author takes pains to emphasize is slightly different from the typical text book assumed world where the data is reliable, the questions are already framed and the variables are not suspect, with only the modeling (even the models are often taken for granted in standard textbooks!) and the statistical tools occupying center stage.
This format of a typical econometrics textbook has its origin in a traditional view of econometrics, where the econometricians were supposed to match (mainly macro-) economic theories to data, often with an explicit goal to substantiate the theory. In the unlucky event that the econometric model failed to provide evidence in favor of the theory, it was usually perceived that perhaps the data were wrong or the estimation method was incorrect, implying that the econometrician could start all over again.
This view assumed that most aspects of a model, like the relevant variables, the way they are measured, the data themselves, and the functional form, are already available to the econometrician, and the only thing s/he needs to do is to fit the model to the data. The model components are usually assumed to originate from an (often macro-) economic theory, and there is great confidence in its validity.
A consequence of this confidence is that if the data cannot be summarized by this model, the econometric textbook first advises us to consider alternative estimation techniques. Finally, and conditional upon a successful result, the resultant empirical econometric model is used to confirm (and perhaps in some cases, to disconfirm) the thoughts summarized in the economic theory.
The author instead realizes that the most common refrain from newbie researches out in the field is “where do I start?” and takes his discussion forward from there. With this introduction that shows the process of econometric research in simplistic but essential detail, Franses makes sure that the student will be less clueless when confronting a possible opportunity to pose a useful question.
The most valuable chapter in the book (Chapter 4) addresses this problem even more directly and contains step-by-step discussion of sample research case studies. These are meant to indicate that the main ideas in the book shine through present-day applied econometrics. These illustrations suggest that there is a straight line from understanding how to handle the basic regression model to handling regime-switching models and a multinomial probit model, for example.
To conclude, I quote the concluding paragraph from the introduction, which I simply loved. It is a valuable economic exercise to indulge in, to strengthen the analytic muscles or even just to pass time!
Finally, as a way of examining whether a reader has appreciated the content of this book, one might think about the following exercise. Take a newspaper or a news magazine and look for articles on economic issues. In many articles are reports on decisions which have been made, forecasts that have been generated, and questions that have been answered. Take one of these articles, and then ask whether these decisions, forecasts, and answers could have been based on the outcomes of an econometric model. What kind of data could one have used? What could the model have looked like? Would one have great confidence in these outcomes, and how does this extend to the reported decisions, forecasts, and answers?
Loading...
