MAINSTREAM macro models fail to represent some of the most basic realities of the financial system. One reason is that doing so is hard. Another is that for a long time it did not seem to make much difference. In the absence of crises, the activities of the financial sector can appear irrelevant for long stretches of time. Small wonder so many academics model the economy as if banks and other intermediaries simply do not exist. The crisis, which was completely unanticipated by the vast majority of academics and policymakers, revealed some of the drawbacks of these shortcuts. In response, a few scholars are trying to rebuild the field. This week’s print edition has some of the story. For this post, I want to focus on one particularly interesting new area of research: the “microfoundations” of the banking sector. Subsequent posts will cover additional topics.

The conventional view, inherited from Paul Samuelson (see yesterday’s post for a more detailed history), is that banks match savers and borrowers. Rather than profit-seeking firms that make loans opportunistically, financial firms are merely a “veil” between savers and borrowers. How they finance themselves and how they decide when to lend are supposedly unimportant. But Hyun Song Shin, an economist at Princeton, believes that this completely misses the point. His research is centred on the idea that “the corporate finance” of banking can be used to realistically model how banks behave. One of his big findings is pretty interesting: banks react to changes in asset prices very differently than households and nonfinancial businesses.

For example, suppose there is a homeowner with an $80,000 mortgage and a $10,000 home equity line on a $100,000 house, giving him equity of $10,000, or a leverage ratio of 9:1. (These numbers have been chosen to make the maths easier.) Then suppose his house goes up in value to $120,000. His equity has just increased to $30,000, so his leverage ratio would now be 3:1. Typically, he will respond by increasing his home equity borrowing, refinancing his mortgage, or maybe running a credit card balance. However, the net increase in debt will generally be less than the increase in his house’s value. Generally, he might borrow an extra $10,000-$15,000. This is still unwise given the mismatch between his illiquid long-duration asset and his fixed-income liabilities, but the result would be a decline in the observed leverage ratio from 9:1 to something like 5:1 or 7:1. This process also works in reverse. People generally cannot cut their debts as quickly as their assets lose value. In practice, this means that leverage ratios usually go up when asset prices go down. The same often applies to nonfinancial businesses.

Banks, however, do the opposite. Rising asset prices cause banks to increase their leverage by borrowing even more than they gained on their asset portfolio. Falling asset prices cause banks to cut their borrowing so much that their leverage ratio actually declines. This means that banks exacerbate the economic cycle on both the upside and the downside. Mr Shin and his colleagues explain this curious phenomenon by looking at banks’ incentives and accounting. Compared to other firms, most banks are Marxist paradises where workers take home the lion’s share of the profits. To justify this unusual arrangement to their supposed owners, bankers say that they are paid commensurate with the return on equity (profits divided by equity outstanding) that they generate. This obviously gives them an incentive to maximise their ROE while still appearing to have robust capital ratios.

The easiest way to do this is to “risk-weight” their assets according to something called Value-at-Risk or VaR. A bank targeting an equity capital ratio of 10% would fund every $100 of “risk-weighted” assets (RWA) with $10 of equity. But this tells us nothing about the actual size of the bank’s balance sheet. The bank could own $400 of assets with an average “risk-weighting” of 0.25, $125 of assets with an average “risk-weighting” of 0.8, or some other combination. Mr Shin has a great chart showing that Barclays’ “risk-weighted” balance sheet has been much more stable than its actual balance sheet over the past two decades:

(The chart also shows that the bank adjusted the liability side of its balance sheet almost exclusively by altering how much debt it owed. By contrast, the amount of equity outstanding barely changed over twenty years. This has implications for the capital requirements debate.)

Barclays’ RWA avoids growing and shrinking as much as its actual balance sheet because its VaR measures systematically move in the opposite direction of the prices of its assets. From one of Mr Shin’s papers on the subject:

The evidence is consistent with the rule of thumb that Value-at-Risk normalized by equity is kept constant over the cycle, even at the height of the crisis. The implication is that intermediaries are shedding risks and withdrawing credit precisely when the financial system is under most stress, thereby serving to amplify the downturn.

Why does this happen? Most VaR measures calculate the risk of an asset by looking at the changes in its price over a given period of time, like the past 36 months, and then expressing this in terms of standard deviations. This is not a very good way to measure risk, since returns are not normally distributed, although it is a great way for bankers to extract the maximum amount of compensation from shareholders during good times. Asset values tend to rise gradually and fall suddenly, hence the old traders’ saying that prices take the escalator up and the elevator down. Thus, a period of rising prices will often coincide with low observed volatility. The VaR model will say that risk has declined and the bank will increase its leverage to maximise its ROE. Conversely, when prices fall, historical volatility will have increased and the asset will appear more risky irrespective of the truth.

Ironically, expensive (low-yielding) assets are more likely to lose value in the future than ones offered at a steep discount, so VaR basically tells banks to buy high and sell low. It all helps explains Mr Shin’s point that banks exacerbate the swings in the cycle by acting as “momentum traders.” The next step for these researchers is building a full-scale macro model that incorporates these ideas.