Source: http://dilbert.com/strips/comic/2007-08-08/ (h/t John Quiggin)
The error in the Reinhart-Rogoff (2010) [RR thereafter] paper titled “Growth in a time of debt“, also published in AER. RR (2010) concluded that a public debt-to-GDP ratio above 90% drags on a country’s economic growth. More importantly, there is somewhat a nonlinear relationship between debt and economic growth. Herndon, Ash and Pollin (2013) tried to replicate the results in RR (2010) and find that when the debt-GDP ratio breaches 90%, growth slows to 2.2% and not the -0.1% that RR (2010) finds.
This error is needed to get the results they published, and it would go a long way to explaining why it has been impossible for others to replicate these results. If this error turns out to be an actual mistake Reinhart-Rogoff made, well, all I can hope is that future historians note that one of the core empirical points providing the intellectual foundation for the global move to austerity in the early 2010s was based on someone accidentally not updating a row formula in Excel. – Next New Deal.
As a researcher in this area, I’ve read that paper a while ago. Yes, it is an influential paper. Yes, a mistake is a mistake. But,
i. It is one of the many papers that have been published on this topic involving debt-GDP ratio, and implications on the economy. And, I do not really think policymakers actually based their decisions to promote austerity soley on these papers. Paul Krugman explains what I think rather well in this piece. The Altlantic provides a rather good take on this too.
ii. Debt-GDP ratios above 90% can’t be good for an economy, whether a linear or nonlinear relationship between debt-GDP ratio and economic growth exists.
Economists and researchers alike should definitely be responsible for the work they put out to public and for the work they publish. As an economist that is a perfectionist and rather pedantic, I know how easy it is to make mistakes in what you do, despite the number of times you may have checked through your work. It is scary to know that you may still make mistakes despite your best efforts, especially when you are handling lots of data. Unfortunately, in academia, there isn’t a whole lot of cross-checking going on. It is already difficult to find someone working closely in the same field, using the same methodologies.
I was searching for some papers the other day, and came across these papers. I haven’t read through the whole paper, but have merely taken a glance through them, and mostly jumped straight to the tables. Fairly interesting insights, some of which you would probably have already known if you are an economist.
Disclaimer: All tables are from the papers.
Interesting new papers:
There is an increase in percentage of authors in the “51 and above” age group publishing in top economic journals over the years. The paper suggests that older economists are now healthier and more active compared to previous cohorts, and that the abolition of mandatory retirement for faculty in 1994 (that is a US regulation?) also increased the monetary incentives to continue publishing. In my daily reads of papers for my research, I do notice several papers published by prominent older economists, some of which are an extension of work done a while ago. Many of these publications also focus on contemporary topics relevant to the 2008-2009 global financial crisis. Perhaps crises and the aftermath of more data does result in more publications by older economists?
If data is anything to go by, I think this set of data suggests that it is indeed harder for someone who has just entered academia in Economics to publish, and that not many females has published in top economic journals (even if that percentage has increased slightly over time). But, really, that latter point is probably due to the fact that the Economics field is still men dominated.
More people are co-authoring over the years. It’s a good thing to know that there are more interactions between economists these days! I think people realise there could be synergy in co-authoring, although I really am not too sure about having 5 co-authors.
I have always thought that the “Theory with simulation” category is growing. I think it would be hard to conduct any research under the “borrowed data” category, just because to get a set of data these days, you really have to get it from different sources. Gone are the days where you can get data from just one source.
Theory with simulation includes calibration in macroeconomics; borrowed data are all data sets that are copied directly from books (the old technology) or provided electronically; self-generated data include data sets assembled from diverse electronic or other sources; and experiments include both laboratory work and author-initiated field experiments.
Some facts I found interesting:
1. Annual submissions to the top-5 journals nearly doubled from 1990 to 2012.
2. The total number of articles published in these journals actually declined from 400 per year in the late 1970s to 300 per year most recently. As a result, the acceptance rate has fallen from 15% to 6%, with potential implications for the career progression of young scholars.
9. Although the fraction of articles from different fields published in the top-5 has remained relatively stable, there are important cohort trends in the citations received by papers from different fields, with rising citations to more recent papers in Development and International, and declining citations to recent papers in Econometrics and Theory.
As a PhD student who has been in this academic environment for the last three years, I’ve seen how important journal publications are. I’ve seen people who have left when they were on a tenure track because they couldn’t get enough publications. I have seen peers who have started submitting to journals over the years because they would like to be an academic after finishing their PhD. I suspect the correlation between the number of publications and probability of getting tenured/getting an academic job has probably jumped over the years.
No. 9 is actually a little surprising, with regards to the declining citations to recent papers in Econometrics and Theory.
It is a lovely saturday in Canberra. Spring has finally arrived in Canberra. For me, September-November is the most beautiful part of the year in Canberra. The weather is often perfect, even if it rains. The flowers are blooming. The sun is shining on brightly.
Yet, I find myself stuck in the office for the rest of the day. I’ve just realised that I have been working on my PhD in the office on weekends rather diligently since mid last year. Well, of course, I don’t work on the PhD 24/7, since I do spend time on other things outside the PhD. Research is a very independent and lonely task. That also explains why I like spending time outside of the PhD with people not doing a PhD, or working on something else.
Am I working too much? Can I afford to work less?
I have friends outside of the PhD who claim that I need to have better time management skills, and to treat the PhD as a job. I do treat the PhD as a job, except this is one hell of a strenuous job. I may not be the most efficient, smartest or fastest worker around. But, I don’t spend time staring at my screen doing nothing either. I don’t know about the working hours of my other PhD friends. But, from what I observe, seeing them come into their offices during weekends, most of them work similar hours too. Of course, quantity isn’t quality. But, with the PhD, I beg to differ. With the PhD, I take on this view: For quality work to happen, effort and many hours of work needs to be invested.
So, for every minute spent in the office, I am either reading something, understanding some methodology, collecting/sorting data, writing and amending papers, preparing tutorial materials, or working on Matlab codes. All these tasks takes a lot of time. More often than ever, it is common for me to spend the whole day trying to understand a certain methodology yet not quite understanding it. It is also common for me to work on a code for months, yet not quite finishing it. Well, I can’t help it since I am also picking up Matlab skills along the way, coming into the PhD with zero knowledge on programming.
How else would you juggle the PhD and life then?
For me, I can’t imagine entertaining the thought of submitting my thesis sometime before the end of next year if I don’t put in the hours during the weekend.