New Economist

Econoblogger navel gazing

There are few things more tedious than bloggers writing about blogging. So apologies for the navel gazing. I just wanted to note, for those who may find it of interest, the following recent posts:

* The Bayesian Heresy blog has posted its Economics Blog Awards 2008

* Aaron Schiff at 26econ.com has conducted a survey of more than one hundred econobloggers, and summarised the results

For some reason I missed his email, so I'd better get a belated response off to him!

The number of econobloggers has grown like topsy over the past two years. There are now more than 200 of them. Two useful econoblog rankings and directories to sort through the maze are:

* Aaron Schiff's Economics Blog Directory & Ranking, which uses Technorati rankings

* Brain Gongol's Traffic Rankings for Business and Economics Websites, which uses publicly-available traffic logs

New book online: Daron Acemoglu's 'Introduction to Modern Economic Growth'

When Dani Rodrik recently asked his many readers which economist they most wanted to see start a blog, MIT's Daron Acemoglu came second only to Joseph Stiglitz. Rodrik asked him if he would start a blog:

Daron Acemoglu responds by saying blogging "seems like a lot of work." He adds "I am already overcommitted, so it's a bit scary to take something else on."

Busy? And how! Acemoglu has somehow found the time to write a new magnum opus. His Introduction to Modern Economic Growth is a whopping 1,169 pages. It covers the whol gamut, from the Solow growth model to the role of political regimes and institutions. Acemoglu explains the background to this textbook in his introduction:

This book grew out of the first graduate-level introduction to macroeconomics course I have taught at MIT. Parts of the book have also been taught as part of a second-year graduate macroeconomics.

In the preface, Acemoglu writes that the book is intended to serve two purposes:

First and foremost, this is a book about economic growth and long-run economic development. The process of economic growth and the sources of differences in economic performance across nations are some of the most interesting, important and challenging areas in modern social science. The primary purpose of this book is to introduce graduate students to these major questions and to the theoretical tools necessary for studying them. The book therefore strives to provide students with a strong background in dynamic economic analysis, since only such a background will enable a serious study of economic growth and economic development. It also tries to provide a clear discussion of the broad empirical patterns and historical processes underlying the current state of the world economy. This is motivated by my belief that to understand why some countries grow and some fail to do so, economists have to move beyond the mechanics of models and pose questions about the fundamental causes of economic growth.

In a somewhat different capacity, this book is also a graduate-level introduction to modern macroeconomics and dynamic economic analysis. It is sometimes commented that, unlike basic microeconomic theory, there is no core of current macroeconomic theory that is shared by all economists. This is not entirely true. While there is disagreement among macroeconomists about how to approach short-run macroeconomic phenomena and what the boundaries of macroeconomics should be, there is broad agreement about the workhorse models of dynamic macroeconomic analysis. These include the Solow growth model, the neoclassical growth model, the overlapping-generations model and models of technological change and technology adoption. Since these are all models of economic growth, a thorough treatment of modern economic growth can also provide (and perhaps should provide) an introduction to this core material of modern macroeconomics. Although there are several good graduate-level macroeconomic textbooks, they typically spend relatively little time on the basic core material and do not develop the links between modern macroeconomic analysis and economic dynamics on the one hand and general equilibrium theory on the other. In contrast, the current book does not cover any of the shortrun topics in macroeconomics, but provides a thorough and rigorous introduction to what I view to be the core of macroeconomics. Therefore, the second purpose of the book is to provide a first graduate-level course in modern macroeconomics.

A considerable achivement. Acemoglu asks readers to note that "this is a preliminary draft of the book manuscript. The draft certainly contains mistakes. Comments and suggestions for corrections are welcome."

Psychology and economics

Stefano DellaVigna from UC Berkeley has written a very useful review of Psychology and Economics: Evidence from the Field (PDF). Hat tip: Andrew Leigh

In the conclusions DellVigna specuates on future research topics:

..future research is likely to reduce the imbalance across fields in economics and across topics in psychology. While the research in behavioral finance and consumption savings is very active, relatively few studies, instead, have tackled mortgage markets, development, and political decisions, fields ripe for exploration. Future research is also likely to explore psychological phenomena that have been largely neglected. For example, emotions,automatic processing, and implicit discrimination are likely to matter for economic decisions such as divorce, judicial sentencing, and policing. Ten years from now, we will hopefully be able to assess quantitatively which psychological factors matter in which decisions.

I identify two specific areas for future research: the market interaction between standard and non-standard agents, as in Section 5, and public policy applications. The market interaction is likely to find several additional applications, for example to the interaction between politicians and voters. In addition, this area is likely to investigate the judgmental biases, such as overconfidence, of experienced agents such as managers and politicians.

For another recent review of the literature, see my earlier post, Who are the behavioral economists and what do they say?

New econometric textbook online

'Marshall Jevons' of the weblog The Bayesian Heresy alerts us to a new graduate-level econometrics textbook, available free online, by Professor Bruce E. Hansen from the University of Wisconsin. Here is a direct link to the PDF (1.2Mb).

Fitting data curves

One of the problems with standard economics training is that the econometrics focuses on linear regression and tends to skip over non-linear functions. Most economists would never consider a curve may be, say, a Poisson distribution. Many sem to think adding a squared or cubed term to their model is the height of sophistication!

Part of the problem is that few economists seem to eyeball the data before crunching it. Now there's a tool to help. In a new post on the Statistical Modeling, Causal Inference, and Social Science blog, Aleks Jakulin at Columbia University points us to a great online tool, ZunZun. It lets you use 2 and 3 dimensional 'Function Finders' to "help determine the best curve fit for your data".

I've tried it and it works. Of course, one needs to avoid over-fitting the data. But the developer of the software, James R. Phillips, has promised to add the AIC sooon; this will help select the more parsimonius function. 

Two new Euro blogs

I have just added to my blogroll two rather impressive European econoblogs:

* Euro Intelligence, by FT writer Wolfgang Munchau and economist Susanne Mundschenk. Styled on Nouriel Roubini's RGE website, it "is free – for an initial period. We will launch a subscription service later this year." So enjoy it while you can. The daily press summary is paricularly helpful.

* Eurozone Watch, by economist Sebastian Dullien and political economist Daniela Schwarzer. It promises "monitoring economics and economic governance of the euro area"

Both promise much - I will be checking them regularly.

New book: 'Data Analysis Using Regression and Multilevel/Hierarchical Models'

Anyone familiar with Andrew Gelman's excellent blog, Statistical Modeling, Causal Inference, and Social Science, would be keen to see his new book, aco-authored with Jennifer Hill. The book is titled Data Analysis Using Regression and Multilevel/Hierarchical Models, and has just been published by Cambridge University Press.

Judging by its table of contents it covers plenty of ground, including several that have been neglected by other authors:

1. Why?; 2. Concepts and methods from basic probability and statistics;

Part IA. Single-level Regression: 3. Linear regression: the basics; 4. Linear regression: before and after fitting the model; 5. Logistic regression; 6. Generalized linear models;

Part IB. Working with Regression Inferences: 7. Simulation of probability models and statistical inferences; 8. Simulation for checking statistical procedures and model fits; 9. Causal inference using regression on the treatment variable; 10. Causal inference using more advanced models;

Part IIA. Multilevel Regression: 11. Multilevel structures; 12. Multilevel linear models: the basics; 13. Multilevel linear models: varying slopes, non-nested models and other complexities; 14. Multilevel logistic regression; 15. Multilevel generalized linear models;

Part IIB. Fitting Multilevel Models: 16. Multilevel modeling in bugs and R: the basics; 17. Fitting multilevel linear and generalized linear models in bugs and R; 18. Likelihood and Bayesian inference and computation; 19. Debugging and speeding convergence;

Part III. From Data Collection to Model Understanding to Model Checking: 20. Sample size and power calculations; 21. Understanding and summarizing the fitted models; 22. Analysis of variance; 23. Causal inference using multilevel models; 24. Model checking and comparison; 25. Missing data imputation;

Appendixes: A. Six quick tips to improve your regression modeling; B. Statistical graphics for research and presentation; C. Software; References.

Caveat: I've ordered it but have not yet seen a copy. Comments welcome from those who have.

Watch out Chicago!

Tomorrow a thousand or two economists descend on the windy city for the American Economic Association's annual gabfest. The conference program is online, as are many of the conference papers. Over coming days I'll be posting here about a few that caught my eye...

A bird's eye view of econometrics

Want to get to grips with econometrics? Look no further. John F. Geweke (Iowa), Joel L. Horowitz (Northwestern) and Hashem Pesaran (Cambridge) offer Econometrics: A Bird’s Eye View (PDF here) in a new IZA discussion paper.

Prepared for the forthcoming New Palgrave Dictionary of Economics and Law, it provides a comprehensive 72 page overview of the subject, including a boggling 386 references! Here is the abstract:

As a unified discipline, econometrics is still relatively young and has been transforming and expanding very rapidly over the past few decades. Major advances have taken place in the analysis of cross sectional data by means of semi-parametric and non-parametric techniques. Heterogeneity of economic relations across individuals, firms and industries is increasingly acknowledged and attempts have been made to take them into account either by integrating out their effects or by modeling the sources of heterogeneity when suitable panel data exists.

The counterfactual considerations that underlie policy analysis and treatment evaluation have been given a more satisfactory foundation. New time series econometric techniques have been developed and employed extensively in the areas of macroeconometrics and finance. Non-linear econometric techniques are used increasingly in the analysis of cross section and time series observations.

Applications of Bayesian techniques to econometric problems have been given new impetus largely thanks to advances in computer power and computational techniques. The use of Bayesian techniques have in turn provided the investigators with a unifying framework where the tasks of forecasting, decision making, model evaluation and learning can be considered as parts of the same interactive and iterative process; thus paving the way for establishing the foundation of “real time econometrics”. This paper attempts to provide an overview of some of these developments.

The authors conclude that econometrics "has come a long way over a relatively short period", and that "both in theory and practice ..[it] has already gone well beyond what its founders envisaged." But there are also a number of difficulties. First, economic statistics are seldom "the results of designed experiments, but are obtained as by-products of business and government activities". They don't always suit economic analysis. Second, models are rarely fully specified:

..the specification of econometric models inevitably involves important auxiliary assumptions about functional forms, dynamic specifications, latent variables, etc. with respect to which economic theory is silent or gives only an incomplete guide.

Third, economic theory is incomplete and:

..on its own cannot be expected to provide a complete model specification has important consequences for testing and evaluation of economic theories, for forecasting and real time decision making. The incompleteness of economic theories makes the task of testing them a formidable undertaking.

In general it will not be possible to say whether the results of the statistical tests have a bearing on the economic theory or the auxiliary assumptions. This ambiguity in testing theories, known as the Duhem-Quine thesis, is not confined to econometrics... The problem is, however, especially serious in econometrics because theory is far less developed in economics than it is in the natural sciences.

Plenty of food for thought here.

Free NBER Working Papers

Some econoblogger readers must get frustrated by the frequent references to NBER Working Papers. Acedemics forget that while they get them free, others have to pay. So it is welcome news that the NBER have announced a free trial, available at www.nber.org/trial

Free trial subscription to NBER Working Papers through November 15, 2006.

All working papers issued since October 2004 can be downloaded without charge. Each registered user is limited to 100 free papers.

Registered users will also be offered free downloads from the abstract page of each eligible working paper.