Trade, Environment & Stuff

What has Europe ever done for us? Well for one thing, the EU has imposed tariffs on biodiesel imported from the USA. Here’s a quick guide.

On March 12 2009, the European Commission imposed provisional anti-dumping and anti-subsidy measures on imports of biodiesel from the United States. Biodiesel is a renewable transport fuel derived primarily from vegetable oils. Imports from the US accounted for 36% of biofuel sold in the UK in 2008/09.

Profitability of UK & EU Biodiesel Sector

Biodiesel can replace regular (mineral) diesel in unmodified vehicle engines, reducing greenhouse gas (GHG) emissions by up to 70%. Its use has been encouraged across Europe, including in the UK where renewable transport fuels must account for 3.25% of road transport fuel sales (by volume), rising to 5% by 2013. Despite this growing market, the profitability of biodiesel production within the EU has fallen year-on-year since 2005, while the market share of US imports rose from 0.4% to 11%. Bad news for Teesside’s Biofuels Corporation amongst others. A recent investigation by the European Commission found evidence that dumping and subsidisation related to imports from the US were a significant cause of this injury.

Production Subsidies

The Commission found that since 2004, US exporters have benefitted from a range of production subsidies – including the biodiesel mixture credit which permits US producers to claim a $1 credit for every gallon of biodiesel blended with mineral diesel. This scheme has led to the ‘splash-and-dash’ trade in which biodiesel from 3^rd countries is imported to the US, mixed with 0.1% mineral diesel and re-exported to the EU: benefitting from both the US blending subsidy and the premium European prices created by policies such as the RTFO. The scale of the subsidy, expressed as a % of import price was estimated to be between of 29% and 41%.

Dumping

Dumping occurs when a producer exports its product for less than the domestic sales price. In economics this is regarded as price discrimination (charging each consumer the maximum price they would be willing to pay). It is a symptom of an uncompetitive market because sellers shouldn’t be able to get away with charging different prices to different people in a market that’s working properly. The investigation found the dumping margin (the % difference between export price and domestic sales price) of US exporters to be 3-73%.

Imposition of Duty

Under the lesser duty rule, the Commission is permitted to impose an import duty equivalent to subsidy margin and dumping margin of the exporter, but no greater than the margin of injury suffered by European producers (the difference between the import price and the price at which European producers would be able to make a reasonable profit). The fact that US exporters were found to benefit from both subsidisation and dumping allowed the Commission to impose duty equivalent to the whole amount of the injury. This is expected to increase the price of US imports to the EU from £436/tonne to £685. The measures will last until July 14 2009. After that they will be subject to a vote in the European Council (i.e. the national governments) and potentially prolonged for a further five years.

Effect of Commission Decision

In the short-term, this decision will increase the price of biodiesel imports to the UK. However, it should be noted that global vegetable oil prices are currently 50% lower than the record levels witnessed 12 months ago. UK producers should benefit, most notably from the ability to set prices in relation to their own costs of production rather than those of subsidised US producers. On the other hand, European consumers will no longer enjoy the privilege of having their biodiesel habit paid for by their American counterparts.

Addicted to Prescription Medication

Anyone who’s watched enough episodes of the Simpsons should be familiar with the Kübler-Ross model. This is the 5-stage process associated with grief and tragedy (denial-anger-bargaining-depression-acceptance). Its economics counterpart is Irving Fisher’s Debt-Deflation Theory of Great Depressions, a document worth revisiting in the current economic climate.

Fisher offers a fairly generic, but detailed and seemingly up-to-date portrait of how over-indebtedness leads to depression and, if left unchallenged, to serious and prolonged deflationary spiral. It was written in 1933, and he’d personally lost a fortune from the Wall St crash, so I guess it was fresh in his mind. The Kübler-Ross bit is Fisher’s diagnosis of 4 distinct phases of over-indebtedness:

a) the lure of prospective dividends or gains in income in the remote future

b) the hope of selling at a profit and realizing a capital gain in the immediate future

c) the vogue of reckless promotions, taking advantage of the habituation of the public to great expectations

d) the development of downright fraud, imposing on a public which had grown credulous and gullible

Of course, in 2009 as in 1933, it’s easy to be wise ex post and realise that all this is as old as the great bronze crash of 2000 BC. Nevertheless several aspects of Fisher’s 3-D analysis (debt, deflation, do something about it) appear just as valid today. Notably:

The Universe is always sort of random

- Fisher does not reject the idea of a steady-state equilibrium in the economy but states that at any given time an economic variable (e.g. industrial output) will at best be fluctuating randomly around its equilibrium path due to countless interacting factors. On the other hand, if the economy is shifted far enough from equilibrium, due to a shock of some kind, it might not right itself automatically and could very well ‘capsize’.

This time it’s different. This time it’s always different

- There is no such thing as a business cycle or recurring economic crisis as a purely temporal phenomenon (like a swinging pendulum). Instead, a combination of steady trends, haphazard disturbances and cyclical tendencies are interacting at any given moment. For 2009, I would be tempted to identify financial de-regulation as the key long-term trend (repeal of the Glass-Steagall Act in 1999, creation of the Eurodollar market in 1957) and to define a cyclical tendency as being the time it takes for the previous boom to fade from living memory and be replaced by something that initially looks a bit different. Fisher notes that there is typically a genuinely novel economic opportunity that triggers the cycle of speculative indebtedness: housing this time, dot-coms last time. Fisher himself mentions technological advances of the 1920s and various railroad and construction booms in the 19th century.

Debt-deflation. It’s all downhill

- If remedial action is not taken, indebtedness and deflation set off a downward spiral of long-term depression via a 9-stage chain of consequences (Kübler-Ross again). The early stages are mass debt liquidiation (i.e. try to get rid of dodgy assets and raise enough cash to pay off your debts). This leads to deflation (i.e. falling price level, which is the same as rising nominal value of money) because everyone is selling and no-one is buying and money from loans that are paid back isn’t leant back out again. Among other things, deflation causes the real value of people’s debts to grow-and-grow. Then businesses go bankrupt, people lose confidence and hoard money as a precaution (Keynes’ Paradox of Thrift) and everything starts to reinforce itself. I guess we’ve had most of stage 1) (liquidation) and we’re probably entering stage 9) about now (they’re not in strict chronological order).

- Stage 9) is the increasing disparity between nominal and real interest rates (Keynes’ Liquidity Trap). This is when it is impossible to lower real interest rates in order to expand the amount of credit in the economy, and keep a lid on the real cost of debt. This can occur for two main reasons: i) because banks are scared of lending so the gap widens between the headline interest rate (set by the central bank) and the level banks actually charge and ii) because the central bank can’t set a nominal interest rate lower than zero (otherwise it would be paying you to borrow money). If nominal interest rates are set at 1%, and there’s deflation of 2% then the real rate of interest is 3%. But if you cut rates to zero, you’re left with a real interest rate of 2% and no more room to cut them.

Despair is the Least Constructive Response

If the last 2 points seem decidely gloomy and fatalistic, worry not! Although the speculation and indebtedness elements of Fisher’s work seem fairly ubiquitous, the spiralling-deflation-everything-gets-worse parts need only occur if the situation is not addressed. Fisher stresses that if enough action is taken, early enough to reflate the economy, the worst of a depression can be avoided*. So cut interest rates, and when you can’t cut them any more find other ways of pumping money into the economy, increase government spending (hopefully in cost-effective ways and on something genuinely useful in the long-term), try anything that makes doing business less risky and hoarding cash under the mattress less attractive. Central banks and governments the world over are trying lots of these, let’s hope they work.

The final interesting observation from Fisher is that the roots of the next speculative boom can probably be found in the reflation policy that cured the last one. Eventually, pumping more money into the economy leads to inflation and not much else. In the short-term, especially in a financial crisis or liquidity trap, this is not true – which is why reflationary policies are both useful and necessary. But more money and more inflation ‘bail out’ those whose indebtedness caused the crisis in the first place by reducing the real value of their debt and allowing them access to affordable credit once more. This is moral hazard on a massive scale, surely hastening the arrival of the next boom and crisis. But without some sort of reflation, the depression would be much more prolonged and painful for all concerned. London Banker’s scary chart** is interesting in this regard. I wonder how many Greater or lesser Depressions we’ve avoided through reflation over the years, and what exactly to expect if and when the graph comes tumbling down.

So finally what have we learned? A debt-deflation-depression is a terrible thing, so if it looks like we’re facing one, policymakers should try to throw the kitchen sink at it, as intelligently as possible. This means that although people who worry about future generations’ government debt and eventual inflation have a point, the short-term and long-term pain of not attempting reflation could be far worse. However, we’ve also learned that by addressing the current potential depression in this way, we’re probably causing the next one.

I suppose the answer is that right now we should try every policy trick in the book, including various policies to forgive the financially foolish – but just this once, ok? Honestly this is the last time! Then once the debt-depression crisis is over, longer-term financial and credit (re-)regulation will be re-enacted so that the next crisis is smaller and further away. I wonder how many times we’ve heard that before…

———–

* Fisher thinks the Great Depression would have been worse were it not for FDR’s policies. Pundits, of varying degrees of sanity, continue to argue over this even today. See Krugman’s blog archive for argument on the subject. I have no idea.

** The chart refers to the US economy. Anyone know if the ratio is any healthier for the UK?

The Blogging Trap

Why does this blog only have 2 (ok 3) posts? Well, apart from apathy I’ve been preparing a review on the basics of the Keynes is back / liquidity trap is baaack issue. But it’s just so complicated it’s taking me forever. Reading begets yet more reading and yet more unexplained terminology – hopefully more of a Russian doll than Peer Gynt’s onion. In the meantime here are some interesting observations:

- Snappy Keynes quotes as blog titles are this season’s must-have accessory (here, here, here, here, here). At least this blog is ahead of the curve on something – although the last link shows that Marginal Revolution was posting on Keynes’ sex diaries back in January.

- There’s plenty of inciteful comment out there on the economics of financial-crisis-becomes-liquidity-crisis-becomes-economic-depression. See any of the economist links on the right. But there are also plenty of influential people who haven’t quite grasped the issues at stake. Check out the leading article on Newsnight 08/01/09. Paul Mason tells you everything you need to know about quantitative easing/printing money and why we’re considering it now. James Caan is sceptical about its relevance while simultaneously restating the very problems that are the rationale for printing money in the first place.

- For francophone readers, two recent editions of radio France Culture’s l’économie en questions provide an absolutely excellent guide to the economics of the Great Depression and global policies since WW2, each time explaining the implications for the present day (without resorting to pompous Radio4-style ‘lessons of history’ waffle).

Why has this blog only had one post?

Because the author has just learned he’s sitting an exam soon. More to follow in December…

Why are some countries poor? Part 1 – the Cobb-Douglas production function

We know that some countries have less resources than others per head of population. But is this enough to explain why some countries are poorer than others? To start off this blog, we’re going to try to answer this question by looking at the paper Total factor productivity differences: Appropriate technology vs. efficiency by Michał Jerzmanowski.

The paper looks at differences in income per capita across different countries. Why are some countries poorer than others? Do they lack resources? Are they inefficient? Maybe they have combinations of resources that just don’t combine well with current technology. The paper tries to see if any of these theories are convincing and uses a number of different economics techniques in the process.

Resources vs. Productivity: the Cobb-Douglas Production Function

We know that in broad terms an economy’s output per capita depends on two things

1) the resources the economy has at its disposal
&
2) productivity – the level of output that you can squeeze out of a given resource combination.

To figure out which of these is more important in explaining output per capita, Jerzmanowski first shows that we could use the popular Cobb-Douglas idea of how an economy works.

This means that output per capita (y) is produced by a combination of physical capital (k – e.g. machines), human capital (h – e.g. engineering qualifications) and total factor productivity (A). Total factor productivity is a single number, that essentially scales up a country’s combination of inputs k & h, to equal observed output y. The Cobb-Douglas function, as demonstrated above, has a couple of special features that make it simple to understand – but maybe too simple to represent reality.

i) α and (1-α) tell us the shares of physical and human capital in y. Say the amount of k available increases by 2%: if α = 0.4 then we know that output y will increase by 0.8%.

ii) the economy displays constant returns to scale. If k and h both double, we know output will also double.

Fascinating stuff, but we want to know whether productivity (A) or resources (k,h) are more important in real life. So let’s assume we’re looking at data for a number of countries. We can find data for y, k and h from publications by organisations like the World Bank: and that information is enough to work out A and α. Once we know this, we can do the following…

- we can take logs of both sides

log(y) = log(A) + α log(k) + (1-α) log(h)

Taking logs of both sides (meaning that we’re now using the natural logarithm of the items in the first equation) means that we’re now comparing the relative changes in A, k or h. More usefully, it means we can now express output in terms of “A plus other stuff”. That is:

log(y) = Â + OtherStuff

where  = log(A) and OtherStuff = α log(k) + (1-α) log(h). Once we’ve done this…

- we can calculate the variance of log(y): Var(log(y))

If we collect data for y, k and h from a number of different countries, then we have several different examples of each equation we’ve seen so far. This allows us to compare the values between countries by calculating the variance of y,  and OtherStuff. For each single variable, variance is a measure of the extent to which the variable differs from its mean average value. For example, the variance of  is given by:

(Correction**)

where ^Ā (can’t type it in html) is the average value of Â, and Âi is the the log of the productivity (A) in each country i. So the variance is the sum (Σ) of the square of the difference between Âi and ^Ā for each different country divided by (n-1). (n-1) is the number of ‘degrees of freedom’ we have. This means that if we estimate ^Ā by looking at 20 countries, we only have 19 independent values of Âi (once you know the average value of Âi, the value of the 20th observation is not independent from the value of the other 19). We need to use the square because otherwise the values of Âi that are higher and lower than μ would cancel each other out (the square of a positive or negative number is always positive). Once we’ve worked out var(y), var(Â) and var(OtherStuff)…

- We can estimate which of  or OtherStuff is more important in explaining the level of output, y

We can approximate the importance of  and OtherStuff (productivity and resources respectively) by calculating their relative share in the observed variations in total output:

According to Jerzmanowski’s figures, Ia is around 0.23 and Iotherstuff is around 0.39. In other words, productivity differences explain around 23% of the variation in output between countries while differences in the resources countries have accounts for around 39%. Note that these two figures do not add up to 100%. This is because we have ignored the covariance of  and OtherStuff – the extent to which a change in one variable affects the other.

So what have we learned so far?

- It seems that productivity differences explain only 23% of the differences in output per capita between countries.

- Differences in resources seem to explain more, 39%.

But there’s still a lot we don’t know.

- What is ‘productivity’ anyway? So far we’ve rather lazily assumed it just means anything that affects output that we can’t identify by counting productive resources like k and h.

- Aaand.., because 0.23 + 0.39 ≠ 1, we suspect that  affects OtherStuff – i.e. these variables are not independent.

- The results all rely on the assumption that creating economic output could be explained fairly well by the Cobb-Douglas production function. But we don’t really know if this true. In fact, we suspect it’s a fairly weak tool for explaining differences in output since it only explains 0.23 + 0.39 = 62% of the differences between countries.

Luckily, before we decide why some countries are richer than others, Jerzmanowski’s paper has a few more tricks to show us. But they can wait for another post.

** Correction:

The variance section originally read.

But the variance is the average deviation of a value around the mean – not the total. Oops