Financial regulation: Efficiency vs stability trade-off

Over at Rates Blog the trilogy of articles I’ve put up about the GFC has been completed with this one.  The first two artices are here and here, and the blog post I did on them are here and here.  Infometrics will be popping up some more articles on Tuesday’s, but they won’t be on the GFC anymore 😉

So in the first two I mentioned uncertainty about the lender of last resort function as a catalyst for the crisis, and a reason why it persisted.  However, this isn’t a costless function – it is true that introducing financial regulation to induce “stability” will impact on the efficiency of the financial markets.

We like to pretend this is not the case.  We like to pretend that the government has the knowledge and ability to figure out what the “externality” is and what “credit ratios” are appropriate – and so faced with a crisis we tend to focus solely on stability.

However, this is not the case.  In fact, the crisis occurred in part due to our determination to make the banking sector around the world more competitive – leading to the development of the shadow banking sector to avoid regulation.  In such a case, we can only get “appropriate” regulation when we in turn accept lower competitiveness in the banking sector.  And given the “supernormal profits” banks get in this case, they are ripe for second best style regulation through the central bank.

In truth, we either throw out the central bank and have competition over the medium of account through banks directly (allowing them to work together in the face of bank runs), or we have a central bank who directly regulates the whole businesses – it was our attempt to get the best of both worlds that helped us wander into the situation we found ourselves in.

Now none of this is news for central banks – they have been trying to length maturities for bank liabilities and clarify and improve regulation in the banking sector for some time.  The crisis was a reminder of the unintended consequences of regulation – firms (in this case banks) can innovate to avoid regulation as well, and that can be costly.  This must be taken into account, and the full cost involved should be accepted, when it comes to setting up policy – rather than throwing around piecemeal rushed ideas and concepts.

More on describing the crisis

Rates blog posted another article by me, this time talking about why the GFC persisted.  So in the first one I laid down Fed actions as the catalyst, and in the second one I’ve primarily laid the blame on institutional confusion in Europe.  I’m not sure anyone will find this article, by itself, particularly enlightening.  These first two are both simply descriptive (although with a background structure guiding what I talk about), and their only purpose is to illustrate that the “crisis” itself was kicked off by a sudden change in the expected actions of policy makers, and uncertainty about that action.  This isn’t to say that even with perfect policy we wouldn’t have had a recession – but it is to say that the depth and length of the slowdown that has occurred is related to such policy inconsistency.

So if we live in a world where we have decided that a lender of last resort is required in the case of such a crisis, what does that mean for the rest of the time.  After all such a commitment leads to moral hazard.  I’ll be covering that next week in the conclusion article.

The reason I’ve tied these three articles together as I have is because I wanted to create a clear narrative, and then work out what that suggests from policy – that requires answering a bunch of stylised facts (the timing in the crisis, the length of the crisis) with a central story.  The world is not that simple, and so every movement and every “bad thing” that occurred cannot be explained by such a clear narrative.  But it does allow us to help identify an issue and then understand what this means.

Is advertising evil?

Vox says the data supports Matt’s priors:

There is an old debate in economic theory… about whether advertising increases or decreases the prices of consumer goods. Some have argued that advertising provides information to consumers, such as information on prices or the existence of products. This information increases the degree of competition in a market, and thereby lowers consumer prices. On the other hand, there is the view that advertising changes the preferences of consumers, for example by shifting demand curves outwards, increasing the monopoly power of brands or decreasing elasticities of substitution. All these effects should lead to an increase of market prices.

…advertising increased consumer prices in some industries such as alcohol, tobacco and transportation, in which the persuasive effect dominates. But it also decreased consumer prices in other industries such as food. …those industries which exhibit the informative price include more information in their advertisements, consistent with the interpretation of informational and persuasive forces of advertising.

The aggregate effect is informative, which means that, on average, advertising decreases consumer prices.

Also, a perspective from inside advertising.

Behavioural politics

Niclas Berggren:

This study analyzes leading research in behavioral economics to see whether it contains advocacy of paternalism and whether it addresses the potential cognitive limitations and biases of the policymakers who are going to implement paternalist policies. The findings reveal that 20.7% of the studied articles in behavioral economics propose paternalist policy action and that 95.5% of these do not contain any analysis of the cognitive ability of policymakers. This suggests that behavioral political economy, in which the analytical tools of behavioral economics are applied to political decision-makers as well, would offer a useful extension of the research program.

This paper will be music to Eric’s ears!


How does theory stack up to the data?

Levine and Zheng review the evidence:

The relationship between economic theory and experimental evidence is controversial. One could easily get the impression from reading the experimental literature that economic theory has little or no significance for explaining experimental results. The point of this essay is that this is a tremendously misleading impression. Economic theory makes strong predictions about many situations, and is generally quite accurate in predicting behavior in the laboratory. Most familiar situations where the theory is thought to fail, the failure is to properly apply the theory, and not in the theory failing to explain the evidence. …The idea that experimental economics has somehow overturned years of theoretical research is ludicrous.

Wellbeing and GDP

Plenty has been written on the inadequacy of GDP as a measure of welfare and numerous alternative measures have been constructed. Given the proliferation of alternatives, we might wish to know what additional informational content they have over and above GDP. Grimes et al presented a paper at this year’s NZAE conference that investigates the power of the measures in predicting migration flows over the past fifty years. Essentially it estimates the additional information about a country’s attractiveness for migration that the wellbeing measures contain, over and above any income (GNI) differences.

[There] is clear evidence that migration flows respond to relative material wellbeing of countries …[We] find also that the Life Satisfaction measure adds further information over and above material wellbeing. …Thus while clearly important for predicting an objective wellbeing outcome, an index of material wellbeing is an insufficient index for measuring aggregate wellbeing for potential migrants; some measure of broader life satisfaction (that is uncorrelated with material wellbeing factors) must also be included in the definition of aggregate wellbeing…

Looking at the coefficients in their tables it seems that the life satisfaction measure is about half as important in determining migration decisions as income differences. Other measures of wellbeing turn out not to significantly influence migration decisions, over and above incomes and life satisfaction differences. Impressively, Grimes et al are able to explain 50-60% of migration flows using just these two variables!

If you’re interested in non-GDP measures of wellbeing I recommend reading the whole paper: it’s short, packed with good stuff, and brings some much needed empirical evidence to the discussion of which factors matter for welfare.