Wednesday, November 27, 2019
Introduction to Recessions: Volume I
This article is an edited draft of the introductory section of my book. I filled it in last, on the theory that I should only state what is in the text after the rest of it is finished. I am giving the manuscript a short look-over before passing along to editing. Realistically, the earliest publication date will be in early January. The text is longer than my previous works, at around 60,000 words. Has quite a few figures depicting historical data and simulation results (haven't counted, but I think more than previous books). Going forward, my articles will return to being more eclectic, as I will resuming looking at a variety of topics.
This book looks at the theory of recessions from a (mainly) post-Keynesian perspective. What are the mechanisms behind recessions, and what do various theories or models predict?
This volume is what might be described as a “guided survey”: there is a theoretical narrative, but it is developed by surveying existing theories. The writing style is at an intermediate level, being at about the same complexity as what might be seen in the business press, but with a large body of footnotes/endnotes to point readers to academic papers. Existing academic survey papers are leaned on heavily, giving a starting point for literature surveys by readers. Real-world data and simulation results are used to illustrate points; only a few elementary equations appear.
The main theoretical argument is that recessions are inherently hard to forecast. Anyone who has read financial market commentary for an extended period will not be surprised by this; missed recession calls are a pervasive phenomenon. The interesting question is: why are recessions hard to forecast? The mechanisms outlined in this book help explain why theory suggests that this should be so.
In addition to a focus on theory, there is a chapter on empirical recession models. These are models that take economic and financial time series and are used to generate recession forecasts. Since these are algorithms that operate on time series data, they are not closely tied to any theoretical model of how the economy works. The models surveyed were largely generated by economists who would be considered mainstream, and so one might not view this volume as purely post-Keynesian.
As the book title suggests, this is the first volume of a two-volume work. Although considerable amounts of research were done on the topics that are to be part of Volume II, the research was still in progress. The possibility exists that my thinking on matters will shift, and so the discussion of the contents of the second volume remain tentative.
(c) Brian Romanchuk 2019