Annual Review 2021

I've been doing these annual reviews since 2011. They're mainly an exercise for me to see what I accomplished and what I didn't in the previous year. 

This was the first year since I have been back living in Canberra in 2007 that I spent the entire year in the Canberra region. In fact, it is the first year since 1991 that I didn't fly on a plane. It's not that unusual for me not to leave my country for a year. I didn't travel outside of Australia in 2019. This year, with a two year old and random snap lockdowns happening in the first part of the year, we were not in the mood to travel anywhere overnight even when it was possible. Then from mid-August came the second Canberra lockdown for 2 plus months (the first was during the first wave of the pandemic in March-May 2020). Luckily I was able to take Isaac (the two year old) to daycare throughout the lockdown, but we had to help homeschool Noah (5 years old). I was impressed how well the school organized things. Before Omicron came along, things had returned almost to normality in Canberra. We still needed to wear masks at the daycare and on the bus and needed to check in sometimes at stores etc. The university has been dragging its feet on the return to campus, but the faculty office areas in the Crawford Building have sometimes been even a little bit busy. In the last week of the year, I finally travelled out of Canberra with my family to go on holidays on the NSW South Coast.

While we've been away from Canberra the number of COVID-19 cases has been growing radically. Almost everyone here is vaccinated and Omicron seems less severe, so it's unclear what this will mean for university activity in 2022. They were planning a more or less complete return to on campus teaching, but who knows now...
 
In Semester 1 (from February to June), I again taught environmental economics and the masters research essay course. But this is the last time I will be teaching them. More about that in the 2022 predictions, below. We taught in hybrid mode. In the environmental economics class there was a joint online lecture for online and on campus students and then separate tutorials for the two groups. It turned out that very few people came to the in person tutorial. Often I had only one student. But this session was much better in my opinion than either of the online sessions. The masters research essay class had separate online and in-person classes.

 

I was awarded a Francqui Chair at the University of Hasselt in Belgium for the 2020-21 academic year. The main duty of the position was to give ten hours of lectures. Of course, I didn't actually travel to Belgium and so I gave five online lectures. You can see the videos and read some commentary on my blog.

 

I can't really think of anything notable to say about my research activity this year. It's mostly been a story of completing existing projects. We finally wrapped up our ARC DP12 project (yes, funding started in 2012 and we submitted the proposal in 2011) with the publication of our paper on the Industrial Revolution in JAERE.

I started working on several new ideas in the second half of the year but they don't seem to be going anywhere or have already been abandoned. The exception is our asymmetry paper, which we started thinking about right at the end of 2020 and now is under review.

We published five papers with a 2021 date:

Stern D. I., J. C. V. Pezzey, and Y. Lu (2021) Directed technical change and the British Industrial Revolution, Journal of the Association of Environmental and Resource Economists 8(6), 1079-1114.

Saunders H., J. Roy, I. Azevedo, D. Chakravarty, S. Dasgupta, S. de la rue du Can, A. Druckman, R. Fouquet, M. Grubb, B.-Q. Lin, R. Lowe, R. Madlener, D. McCoy, L. Mundaca, T. Oreszczyn, S. Sorrell, D. I. Stern, K. Tanaka, and T. Wei (2021) Energy efficiency: What has research delivered in the last 40 years? Annual Review of Environment and Resources 46, 135-165.

Dressel B. and D. I. Stern (2021) Research at public policy schools in the Asia-Pacific region ranked, Asia and the Pacific Policy Studies 8(1), 151-166.

Stern D. I. and R. S. J. Tol (2021) Depth and breadth relevance in citation metrics, Economic Inquiry 59(3), 961-977.

Bruns S. B., A. Moneta, and D. I. Stern (2021) Estimating the economy-wide rebound effect using empirically identified structural vector autoregressions, Energy Economics 97, 105158.

and one paper with a 2022 date:

Jafari M., D. I. Stern, and S. B. Bruns (2022) How large is the economy-wide rebound effect in middle income countries? Evidence from Iran, Ecological Economics 193, 107325.

We posted four new working papers:

How Much Does Physical Infrastructure Contribute to Economic Growth? An Empirical Analysis
December 2021. With Govinda Timilsina and Debasish Das.

Asymmetric Response of Carbon Emissions to Recessions and Expansions and Oil Market Shocks
October 2021. With Xueting Jiang.

How Large is the Economy-Wide Rebound Effect in Middle Income Countries? Evidence from Iran
August 2021. With Mahboubeh Jafari and Stephan Bruns.

Do Energy Efficiency Improvements Reduce Energy Use? Empirical Evidence on the Economy-Wide Rebound Effect in Europe and the United States
May 2021. With Anne Berner, Stephan Bruns, and Alessio Moneta.

We have three papers under review at the moment (one – the Europe rebound one – is a resubmission). There are twelve other papers on my to do list, but they range from one we are actively trying to complete, to ones that I haven't really done anything on any time recently.

Google Scholar citations exceeded 21,000 with an h-index of 55. I wrote more blogposts this year. Fifteen in total compared to ten in 2020. Twitter followers rose from 1500 to more than 1650 over the year. I did 3 external assessments of people for promotion or tenure for universities in Australia, Hong Kong, and Germany. Fewer than last year. I only did 11 reviews for journals. I used to do around double this three or more years back. And I reviewed a bunch of papers for EAERE, a proposal for the ARC, as well as giving people feedback on their papers etc.

My PhD student Xueting Zhang completed her first research year. She has made a lot of progress, with three papers at various stages of completion. My other student Debasish Das continued his work on prepaid metering and a lot of other stuff, some of which you can check out on his Google Scholar profile.

Looking forward to 2022, a few things can be predicted: 

• I will be teaching a new course (for me) in the second semester: Agricultural and Resource Economics. It is going to take a lot of work to prepare this course. 
• As a result, I won't be teaching in the first semester. Officially, I will be on long service leave, which is how I got my teaching reduced to one course for the year. But I will need to work hard on both the course and research right from the start of the year. OK, I'm feeling like taking 4th January off :) The university has encouraged us to take long service leave to help the budget situation. Taking the leave releases money from the account where it has been set aside and they don't need to pay my salary from the recurrent budget.
  
• I'm hoping we will get our paper on the rebound effect in Europe accepted very soon.
• I probably will stay in Australia for this year too. Anyway, I haven't set up any international travel at this stage.
  

Estimating the Effect of Physical Infrastructure on Economic Growth

I have a new working paper coauthored with Govinda Timilsina of the World Bank and my PhD student Debasish Das. It is a panel data study of the effect of various forms of infrastructure on the level of GDP. 

Compared to existing studies, we use more recent data, include new types of infrastructure such as mobile phones, and provide separate estimates for developing and developed countries. We find larger effects than most previous studies. We also find that infrastructure has a larger effect in more recent years (1992-2017) than in earlier years (1970-1991), and the effects of infrastructure are higher in developing economies than in industrialized economies. The long-run effects seem to be much larger than the initial impact. We also tried to estimate the effect of infrastructure on the rate of economic growth. Controlling for the initial level of GDP per worker we found a null result. So, we can't say that having more infrastructure means a more rapid rate of economic growth.

Getting good quality data that is comparable across countries is really a problem in this area of research. Many types of infrastructure only have data available for a few years. The ones that have more panel-like data often suffer from differences in definition across countries – such as what is a road or a motorway – or unexplained jumps in individual countries. So, our results are subject to a lot of measurement error.

Our main analysis uses data on five types of infrastructure – roads, railways, electric generation capacity, fixed line telephones, and mobile telephones*:

Following some previous research, we aggregate the individual types of infrastructure using principal component analysis. We use two principal components. One factor seems to be related to transport infrastructure and the other to electricity and telecommunications. Still, we can recover estimates of the effect of each individual type of infrastructure.

Also following some previous research, we use the Pooled Mean Group estimator to estimate a dynamic panel regression model. This allows us to test for the weak exogeneity of the explanatory variables, allowing us to give the results a somewhat causal interpretation.

The table shows the percentage change in GDP per worker for a 1% change in each infrastructure type. Getting standard errors for these estimates would be rather tricky.** Interestingly, the PMG estimates are mostly much larger than the static fixed effects estimates. Static fixed effects can be expected to converge to a short-run estimate of the effects while PMG should be a better estimate of long-run effects. Fixed effects also tends to inflate the effects of measurement error. 

Maybe the most innovative thing in the paper is that we plot the impulse response functions of GDP with respect to a 1% increase in each of the two main types of infrastructure:

PC1 is electricity and communications and PC2 transport infrastructure.*** Long-run effects of infrastructure are much larger than the short-run effects. In the short run, transport infrastructure even has a negative impact.

* Note that the graphs show the country means of these variables, while we actually use the deviations from those means over time in each country. 

** We only estimate the GDP-infrastructure relationship, but I think we would need time series models for each of the explanatory variables in order to sample from those models' residuals in a bootstrapping procedure. Bootstrapping is needed because we first carry out the principal components analysis and then estimate the PMG model in a second stage. These elasticities are combinations of the parameters from those two models.

*** We could get a confidence interval for these impulse response functions if we assume that the explanatory variables in the PMG model are deterministic as this analysis assumes...