For all those who’ve accused university lecturers of having it easy with only a few teaching hours a week:
This study analyzes self-reported faculty workload in a Canadian research intensive university. …Results show an average weekly workload of 56.97 hours of which 44.1% is allocated to teaching, 35.2% to research, 5.8% to administrative tasks and 14.8% to service.
Noah Smith recently smashed math in economics (specifically macroeconomics) stating:
Math can also be used as obscurantism; if every paper in a field starts with a dense thicket of formal statements and functional equations, it will be difficult for even very smart outsiders to come in and evaluate what the people in a field are doing with their time. Again, I doubt all but the most cynical macroeconomists would be intentionally obscurantist; they would just be subtly rewarded for doing things that ended up having an obscurantist result.
Paul Krugman then neatly defends maths, stating the following:
mathematical models are useful in economics: used properly, they help you think clearly, in a way that unaided words can’t.
And:
What is true is that all too many economists have lost sight of this purpose; they treat their models as The Truth, and/or judge each others’ work by how hard the math is.
This all reminds me of one of my favourite quotes Read more
They sound fancy and complex but this is a good explanation from XKCD. What I really like about it is that it emphasises how competition among networks is not unambiguously beneficial to consumers. For more on network effects and why they’re not the same as externalities check out the Palgrave description.
Via Vox Eu comes a piece looking at the distributional consequences of resource booms – using Australian data. Their conclusion:
We need good time series data from developing countries to see whether the distributional impact is bigger there than what we find for Australia. Until then, the analysis here seems timely and relevant, not just for Australia, but for all resource-rich developing countries as the price volatility experienced by the former since the late 19th century was greater than that for the average commodity-exporting low-income country.
The distributional impact of commodity-price shocks in Australia (Canada and New Zealand) should yield important lessons for primary producers from the developmental south.
True – the idea that taxation should be more progressive the more dispersed income and wealth is is an old and widely accepted idea. And this gives us another way to conceptualise it, with a relevant shock for the NZ and Australian context. However, a couple of things to keep in mind when thinking about these issues are: Read more
From the Pagan report on modelling at the Bank of England:
Models and forecasts are important inputs into any decision-making process …[The] model used in the monetary policy process needs to incorporate the views of the MPC about the way the economy functions, ie to be theoretically coherent, and also be able to replicate historical data on the UK economy, ie to be empirically coherent. It is hard to achieve both of these simultaneously and some trade-off needs to be made when selecting the model.
Apparently it’s not possible for economic models to simultaneously match the data and reflect the way economists view the world. If that were true then it would indicate that economic theory is wrong. Perhaps not categorically wrong, but certainly a long way from reflecting the way the world actually works. It would mean that the modelling simplifications were the wrong ones and discarded important information and mechanisms.
What I think Pagan is trying to get at is that there are two classes of economic models at the moment. Read more
The RBNZ announced LVR (loan to value) restrictions will start on 1 October 2013. It will limit high LVR (over 80%) to 10% of new lending. Matt has already written about this.
This post adds some data for context. The following figures are from the March 2013 quarter General Disclosure Statements, published on each bank’s website.
