Lawyers’ contingent fee (CF) rates are rather uniform, often one-third of the recovery. Arguably, this uniformity is a type of anti-competitive price-fixing, which results in clients paying supra-competitive fees. This paper challenges this argument. It shows that uniform CF rates provide clients with an important advantage, as such rates enable them to make a de facto “take-it-or-leave-it” offer. Consequently, lawyers cannot exploit their private information, and clients retain the transaction’s entire surplus and may hire the best lawyer among those who find it profitable to handle the case.
The paper also addresses the effect of uniformity of CF rates when lawyers refer cases to other lawyers. It shows that uniformity facilitates matching of clients and lawyers through the referral system. It also demonstrates that the fact that both direct clients and those obtained through paid-for referrals pay the same CF rate does not attest to cross-subsidization. The clients whose cases are transferred for a referral fee (paid by the handling lawyer) “pay” for the referral service by obtaining a less highly ranked lawyer.
We would like to thank Nora Engstrom, Nuno Garoupa, Yehonatan Givati, Saul Levmore, Ariel Porat, Eric Posner, two anonymous reviewers and participants in workshops at UC Berkeley and the Hebrew University of Jerusalem for their valuable comments on earlier drafts, and Meirav Furth for her excellent research assistance. Finally, we are grateful for the financial support provided by the Milton and Miriam Handler Foundation and the Aharon Barak Center for Interdisciplinary Legal Research at the Hebrew University of Jerusalem.
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Note that the ranking of lawyers may – and usually does – depend on the type of claim. Thus, Lawyer A may be ranked higher than Lawyer B in medical-malpractice cases while B is ranked higher in car-accident cases. It follows that reciprocal referrals between two lawyers may both be to a higher-ranking lawyer (Parikh, 2001:156–158). See also Section 5.2
In fact, the expected recovery is determined by the distribution of the possible sums of recovery. In a discrete setting, it is an aggregation of the products of each sum and the likelihood of its recovery, and in a continuance setting, it is the integral over the probability density function.
This is a very plausible assumption, because the lawyer’s reservation hourly fee is not exogenous, but determined according to the demand for her services. If the demand for the services of a certain lawyer exceeds her capacity, one would expect her reservation hourly fee to increase accordingly.
A comparable claim can be made regarding any sub-market in which lawyers charge other uniform CF rates, such as a non-negotiable variable fee depending on how the case is resolved (e.g. 25% if it is settled without trial, 33% if it goes to trial, and 40% if there is an appeal), provided that the probability of settling/trial/appeal is uniform for all attorneys.
Note that this result differs from the standard result in the literature regarding two-party negotiation under asymmetric information. According to the standard result, efficiency requires that the informed, rather than the uninformed, party would make the contract offer (e.g. Wang, 1998; Bolton and Dewatripont, 2005:243).
The same tendency is manifest in variable-percentage CF rates, where the common pattern is a scale of rates of 1/4, 1/3, and 2/5 or 1/2, depending on the stage to which the case gets. It is also manifest in the common referral fees, where, according to one study, some 80% of the negotiated referral fee rates are either one-third or one-half of the handling lawyer’s fee (Spurr, 1988:100–102).
In Kritzer’s survey, 25% of the individual clients and 33% of the organizational ones reported that fees were not discussed at all with the lawyer prior to receiving the bill (Kritzer, 1990:57).
To see why, suppose that the expected returns to the client from the two lawyers are the same. Specifically, denote by k the CF rate, p the probability of success, and d the amount of recovery. The client’s expected return from the better lawyer is (1–k)pd while the expected return from the lower-ranked lawyer who charges a lower CF rate is (1–k’)p’d’, where k > k’, p> p’, and d > d’. Assuming, without loss of generality, u(0) = 0, we obtain that the expected utilities of the two returns are pu((1–k)d) and p’u((1–k’)d’). We assume that (1–k)pd= (1–k’)p’d’. It follows that p’ = (1–k)pd/(1–k’)d’, and the expected utility of hiring the lower-ranked lawyer becomes (1–k)pdu((1–k’)d’)/(1–k’)d’. The expected utility from the better lawyer is higher than that from the other lawyer iff
This inequality holds because by (1–k)pd = (1–k’)p’d’, together with p > p’, we obtain that (1–k)d < (1–k’)d’, and since u is concave and u(0) = 0, the ratio u(x)/x decreases with x.
For instance, hiring a particular lawyer may yield a relatively low p and high d, whereas hiring a less-qualified lawyer would yield a lower expected value p’d’ < pd, but may result in higher probability of winning the case (p’ > p), which might be sufficient to compensate the risk-averse client for the lower expected value. In addition, a risk-averse plaintiff may be more interested in establishing the defendant’s liability than in the scope of damages awarded, and if a particular lawyer is better at attaining high damages once liability is determined, but not in proving liability, the client may be better off with someone else.
The actual scope of work required ex post may of course differ from the scope expected ex ante, but since there is no difference in this respect between negotiated and uniform CF rates, the model assumes away this possibility.
Conceivably, the ranking would have been different had the pricing scheme, and thus the incentives it provides, been different.
This is especially true if the lawyer’s input includes not only hours of work but also other aspects of her “production function,” which are often unobservable.
If both cases are expected to yield an effective hourly rate that is not lower than the attorney’s reservation price, then it may reasonably be assumed that she will accept both. See supra note 4 and accompanying text.
At least in theory, the incentive created by the ongoing relationship between the referring and the handling lawyers may outweigh the reduction in incentives due to fee splitting – in which case finding an appropriate lawyer through a referral may be advisable even if the client is knowledgeable about lawyers’ ranking.
As detailed in Section 5.1, while top lawyers obtain most of their cases through referrals, the majority of lawyers, who handle the lion’s share of the CF cases, obtain most of their cases directly.
Charging direct and transferred clients the same CF rate is analogous to a policy of uniform spatial pricing, where a seller charges a uniform delivered price for its goods regardless of the differences in transportation costs to customers in different locations. Such policy may be profit-maximizing under certain assumptions regarding demand functions (Lederer, 2010). For instance, if transferred clients are ordinarily poorer than direct ones – a plausible assumption given that their recourse to the referral system indicates that they are less sophisticated and knowledgeable – then the uniform pricing of the two populations may be a profit-maximizing strategy.
Take, for example, a case whose expected value, pidi, is $270,000 and the number of hours it requires, h, is 100. The expected fee under the standard one-third CF rate is $90,000. A client who finds her own legal representation would hire an attorney whose reservation hourly fee, wi, is $900. In contrast, a client with the same case, who approaches an unsuitable lawyer who then transfers her case, can only expect a handling lawyer whose reservation hourly fee is $600, as two-ninths of $270,000 is $60,000.
Contrary to the prediction of his theoretical model, Spurr (1988:102–107) found no statistically significant correlation between the referral fee and gross recovery.
©2014 by Walter de Gruyter Berlin / Boston