New CCEP Working Papers

We have some new working papers from CCEP. The latest is from Zhongxiang Zhang who will be an associate in the CCEP network. It is titled "Who Should Bear the Cost of China's Carbon Emissions Embodied in Goods for Exports?".

Recently we also put up papers by Leo Dobes and Bruce Chapman "Financing Adaptation to Climate-Induced Retreat from Coastal Inundation and Erosion" and Harry Clarke and Robert Waushik: "Australia's Carbon Pricing Strategies in a Global Context".

Do You have Good Examples of the Role of Energy in the Economy?

A journalist wrote to me for help. They are writing a popular book on the effects of energy scarcities on our economy, wealth and way of living. What good non-academic sources are there that he could use? He is especially looking for strong examples that people can relate to to illustrate two things: our massive reliance on energy in everyday life, and the key that it holds for growth.

Completed a Choice Modeling Survey

This week, I was a respondent to a choice modeling survey for the first time. The purpose of the survey was to find out about reliability of supply of water, electricity, gas etc. So this was something that I as a consumer have a lot of knowledge about and a lot of interest in and it is a clear private market. So all the criticisms about environmental valuation don't apply here. Choice modeling is often used to obtain environmental valuations and I think it is superior to other approaches in that application.

The online survey gave us eight different scenarios of possible packages with varying prices and utility reliability that we could pick from. Each scenario had three different packages - our current service plus two alternatives. Each alternative had around 10 different characteristics. I've always wondered whether survey respondents could handle that and thought that you just need to give each respondent one choice set and survey more people. I was just overwhelmed with information.



I chose the current package in every case. Partly because of the information overload but also because saving $50-$400 a year on my utility bill is just not worth it to me to suffer from multiple power cuts each year and the like, which is what the trade-offs were about. Even when I lived in East Jerusalem in the 1980s as an undergrad student we didn't have that many power cuts (Troy, NY was almost as bad :)). So I'm thinking the results of this survey will be pretty insensitive to price except for the more extreme scenarios at low incomes. $400 is a big deal to someone on $30,000 a year (Australian full time minimum wage), but $50 isn't for someone on $60,000 (average wages).

Being a social science researcher myself I always feel sympathetic to people carrying out surveys and often do them. But I get really annoyed when a surveyer has me on the phone for more than a quarter of an hour asking endless questions or when an online survey turns out to have tens of pages of questions. Why do people design surveys like this that are going to either have less patient people drop out of or refuse to respond or just give random answers to either from impatience or choice fatigue?

Wiley-JoES Online Conference: Communications with Economists

The Journal of Economic Surveys will be holding an online conference from 16th to 18th November. Keynote speakers are Tom Stanley, David Hendry, and Charles Nossair and there are other interesting sessions too. Registration is free. There will be live videocast of the key sessions on the web and they will also be viewable after the event. There will be commissioned discussants as well as discussion by partcipants. Sounds like an interesting venture and I plan on participating.

Why Our Malaria and Climate Change Research is Important

This morning I was interviewed by Clement Paligaru on the Breakfast Show on Radio Australia. This is Australia's international broadcaster. One of the questions that he asked me was why it was important to know that malaria was declining despite climate change rather than thinking that malaria incidence was increasing due to climate change. What I came up with was that if we think that the disease will just become more widespread in the face of climate change regardless of what we do we might be apathetic about doing the things which have reduced the incidence of the disease. I'm not sure how convincing that is. But the rise in cases in the 1990s was probably due to resistance to chloroquine, an older antimalarial drug, and not climate change. That is something that is important to know.

Good Casual Analysis from Bad

Recently, I wrote about Tatu Westling's paper on "male organ" length and economic growth. I argued that it was likely a case of omitted variables bias and there wasn't real causality here. And certainly this relationship wasn't stable over time. This paper did get a lot of media coverage and hence a lot of downloads. Now Westling has teamed up with a fellow student to analyse the incident. They find that other papers on their website also experienced an increase in downloads which can be attributed to a spillover effect from the interest in Westling's paper. They use differences in differences and regression discontinuity methods. This sounds pretty solid as the interest in the paper in question was a pretty exogenous shock. So having star papers in your working paper series will help increase downloads of other papers. This is similar to the Matthew effect in citations. Authors with lots of citations tend to get more and more citations and publishing a landmark paper will result in your other papers getting cited more too.

Malaria Cases in Kericho, Kenya

In my IPCC AR5 chapter writing group we have been told to think of "iconic figures" we could use in the chapter. In our paper on malaria and climate change in East Africa, I think this is the iconic figure:



It just shows monthly malaria cases at the tea estate hospital in Kericho, Kenya. The increase in malaria in the 90s was linked by some researchers to climate change. But in this decade, malaria cases have collapsed at this location. In the meantime we find that there does seem to be a significant increase in temperature especially when the most recent years are included in the analysis. The figure is simple and really easy to understand.

Temperature and Malaria Trends in Highland East Africa

Our article: "Temperature and Malaria Trends in Highland East Africa" is published today in PLoS ONE. I've noted some of the key points already in a series of posts as the article developed. The key points are:

• In 2002 we (Hay et al., 2002) could find little evidence of significant increase in temperature or precipitation in the East African highlands in a period of a surge in malaria cases. It, therefore, seemed most likely that the increased malaria was mainly due to other causes such as increased drug resistance.


• This was a very controversial finding, which has been discussed by various other researchers who generally find that there has been a significant increase in temperature in these areas and that, therefore the increase in malaria was likely due to this.


• We have now tested the more recent versions of the UEA CRU database as well as the temperature series from Kericho in Kenya prepared by Omumbo et al. (2011) using a new robust test for trends in series.


• Using the new test, we find that there is no significant trend in the data we originally tested but that there is a significant increase in mean temperature in the newer versions of the CRU database for the same pre 1995 period. This change in data explains the results of several of our critics.


• When the post 1995 data is included in our tests the results show an even more significant increase in temperature.


• We do not find a significant increase in temperature in the Kericho data for the period up to 1995 but there is a significant trend when post 1995 data is included.


• We conclude that there is now clear evidence of increased temperatures in highland East Africa especially in the last 15 years.
• The twist is that malaria incidence has now declined. So it's still not clear if climate change was the main cause of the surge in malaria and despite recent warming malaria has radically reduced and, therefore, other factors appear to be more important than climate in malaria incidence.
  

Press release version.

Launch of the Masters of Energy Change and Public Seminar

An Energy Change Institute public seminar. Program:

• Introduction by Energy Change Institute Director Ken Baldwin


• Andrew Blakers, ANU College of Engineering & Computer Science


• David Stern, Crawford School


• Tom Faunce, ANU College of Law

Monday 26 September 2011 5.30 – 6:30pm, followed by light refreshments.

Tours of ANU energy research facilities at 4:30

Building 131 Finkel Lecture Theatre, John Curtin School of Medical Research, Garran Road.

The official launch of the new ANU Master of Energy Change will follow the event.

Econometrics for Grumblers

Econometrics for Grumblers is the title of a recent paper in the Journal of Economic Surveys by Markus Eberhardt and Francis Teal (Working paper version). It is a survey of the cross-country economic growth literature with an emphasis on the econometric problems encountered. The biggest problem is that the state of technology or productivity is unobserved - the famous "residual" in the Solow model - and that:

1. The levels of the inputs - human capital and labor etc - which are usually explanatory variables in a growth model are affected by this unobserved variable. This results in a correlation between the error term in the model and the explanatory variables. The explanatory variables are then said to be endogenous.

2. The state of technology is non-stationary and probably has a stochastic trend.

3. The level of technology and rate of change are different in every country.

4. But the level of technology and rate of change are likely correlated across countries.

These aren't the only problems of course :) These issues have lead many to reject the usefulness of doing cross-country economic growth econometrics. Eberhardt and Teal review the literature thoroughly highlighting the underlying assumptions of each study and suggesting a new approach that they have used in their work.

I have been struggling with the issues in 1 to 4 above in a lot of my recent research, particularly on the environmental Kuznets curve and energy efficiency. I've used a variety of econometric techniques to try to deal with the issues but this gives me some new ideas to check out in more depth.

CCEP Working Papers in August 2011

We put up several new papers and so got quite a lot of downloads this month. Papers tend to get a lot of downloads when they first appear on NEP. We got out highest number of abstract views and second highest number of downloads this month since launching the series. In terms of downloads per item, only two STATA related series rank higher in the world! But new series tend to have a high rate of downloads per item, of course.

Erratum: Elasticities of substitution and complementarity, Journal of Productivity Analysis 36(1): 79-89

I hate looking at my published papers because there are often typos in them which I didn't catch at the proofs stage... One of our PhD students, Nitin Gupta, found a typo in my paper: Elasticities of substitution and complementarity, Journal of Productivity Analysis 36(1): 79-89. The formula in equation (20) for the Allen Elasticity of Substitution between inputs Xi and Xj, AESij, should be:



The denominator is wrong in the formula in the paper. The formula for AESii is correct. Note that these formulae only make sense if you have normalized the data in some way. If, for example, you have indexed all variables to one in the first year then the formula will give the elasticity in the first year. It makes the most sense when like me you have normalized on the sample mean for each variable and so this elasticity is at some notional mean point. If you want to calculate the elasticity at different points in time or you haven't normalized the data then you can't use this formula. This is because the parameters associated with the first order terms in the translog function depend on the units used.

The good news is that I used the correct formula in all the calculations in the paper. The bigger picture message is don't believe that a formula is correct just because it is printed in a refereed journal!