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We would like to thank William E. Alexander, Peter Clark, Tito Cordelia, Gianni De Nicolo, Xavier Freixas, Philipp Hartmann, Charles Siegman, Geoffrey Wood, and participants at an IMF seminar for helpful comments and conversations, and Satvinder Singh for research assistance.
It was presumably on grounds such as these that some observers expect the European Central Bank not to assume any LOLR role, although the Maastricht Treaty (Articles 105.2, 105.5, 105.6) and the ESCB Status (Articles 22, 25.1) are rather ambiguous about this issue.
The problem in the case of Barings was that there was insufficient information on the potential close-out cost of Leeson’s derivative position. With the Bank of England (rightly) being unwilling to provide a guarantee to limit any such loss, no private institution was willing to buy Barings over the key weekend.
In addition to depositors’ withdrawals, in a crisis commercial banks may also rationally withdraw from making new loans, as argued by Flannery (1996).
A further tenet of the “liberal” position on the use of LOLR is that CB losses can, and should, always be avoided by an appropriate requirement for collateral; indeed that the availability of appropriate “good” collateral should be the touchstone determining whether LOLR is made available at all. But there is yet another “liberal” principle constraining LOLR which is that it should only be made available at penal rates. The two principles are inconsistent. If a commercial bank seeking help from a CB will be charged a penal rate, and also potentially suffer reputational damage, it will seek first to use its “good” collateral to borrow in the open market. Only after it has exhausted its available market opportunities will it then seek help from the CB on less advantageous terms.
Even if a commercial bank seeking help from a CB will usually have used up its best collateral already, (to borrow on finer terms from the market), the CB may be able to extract such tough terms for its LOLR lending that its own resources are largely protected in the case of an insolvency. But some (junior) creditors would then be hit all the harder, and there would still be a reputational loss to the CB, perhaps the more severe if it was perceived as refusing to take its “share” of the losses - especially if it was also responsible for bank supervision.
The existence of such “contagion effects” is a contentious issue. See, e.g., Rochet and Tirole (1996) for theoretical discussions. Kaufman (1998) notes for the USA that “the variance in the annual bank failure rate was greater [than for non-banks]; bank failures were clustered in a small number of years. Such clustering is consistent with the presence of bank contagion and systemic risk and contributes to the widespread public fear of bank failure.”
We offer no empirical evidence here either of the actual likelihood of contagion or, what is just as important, of CBs’ perceptions of such likelihood. Readers can make their own subjective judgement of this.
For the USA, the monetary data are taken from Friedman and Schwartz (1982). Data on bank failures (deposits, post 1918, and number of suspended banks), are taken from Historical Statistics of the United States - Colonial Times to 1970. The monetary data for H and M are annual averages; call money rates are annual averages of monthly data.
For Australia, the monetary data were mainly taken from Butlin, Hall and White (1971) and the interest rate data from Mitchell (1983). For deposits, the data are for the final quarter (average) of each year. For reserves, data are reported as of December for each year until 1900. For 1900-1912, data are as of June for each year, and so were averaged over two years in order to centre on December. Data on currency in circulation (end year) are taken from Mitchell (1983). Both H and M are thus approximately end-year.
The monthly data for Mexico are taken from IFS over the period May 1990 till November 1997. The interest rate used is the Treasury bill rate, reported as a monthly average.
All practical descriptions of LOLR activities reveal that the CB is under tremendous time-pressure to take decisions (e.g. before the market reopens) and has to do so when in possession of only sketchy details of the “true” financial position of the commercial bank needing help.
The other root is
It would, of course, be possible to formalize the objective function of commercial bank management, and construct a more complete game of CB/commercial bank intervention. We shall pursue this in related research concerned with the issue of the imposition of sanctions in response to excessive risk taking.
There are some exceptions to this dictum. The Comptroller of the Currency, at the time of the Continental Illinois crisis, stated that all larger banks would also be automatically rescued. The Japanese monetary authorities in recent years have made it publicly known that the large City banks are ring-fenced against failure.
For example Johnson Matthey’s involvement in the gold market in London. Again, BCCI and Drexel Lambert could be let go, because their interconnectedness was low, and hence k was also low. Per contra, the interconnectedness of LTCM was high.
Our problem in the case of contagion, or of moral hazard alone, is a standard dynamic programming problem and can be solved by using the standard dynamic programming approach. We decided to choose the Lagrange approach because it appears more efficient and useful in dealing with non-quadratic objective functions (the joint case of contagion and moral hazard in Subsection 4.3). For consistency in approach and easy exposition, we use the Lagrange approach for the whole paper. See Chow (1997) for more discussions of this method.
Technically, we should have a further Lagrange multiplier, τt, and include τt (1 − pt) in the Lagrange function to take fully into consideration the case of 0 ≤ pt ≤ 1. For simplicity, we assume 0 < pt < 1 (and 0 < ht < 1) thus τt = 0, and thus ignore it in the Lagrange function here (and below).
It is easy to check that the sufficient conditions for global optimization in this case of contagion, and moral hazard below, are satisfied.
Because both the objective function and two constraints are convex in It, ht and pt, global optimality is warranted. With this in mind, we can quite comfortably linearize the first order conditions around the steady states to solve the problem analytically.