Bank Deposit Rate Clustering : Theory and Empirical Evidence

Abstract

Like security prices, retail deposit interest rates cluster around integers and "even" fractions. However, explanations for security price clustering are incompatible with deposit rate clustering. A theory based on the limited recall of retail depositors is proposed. It predicts that banks tend to set rates at integers and that rates are "sticky" at these levels. The propensity for integer rates increases with the level of wholesale interest rates and deposit market concentration. When banks set noninteger rates, rates are more likely to be just above, rather than just below, integers. The paper finds substantial empirical support for the theory's implications.RECENT EMPIRICAL RESEARCH HAS DOCUMENTED a widespread tendency for security prices to cluster around integers and "even" fractions of currency units. An example is the decreasing relative frequencies of stock price quotes and transactions made at integer-dollar, half-dollar, quarter-dollar, and eighthdollar price levels. Standard price theory has difficulty rationalizing such clustering because it depends on the arbitrary choice of the pricing system's unit of account. This has led to new theories which explain even-fraction clustering as an implicit convention that reduces traders' costs of negotiating security prices or as a collusive mechanism for maintaining anticompetitive bid-ask price spreads among security dealers. This paper reports a similar integer and even-fraction clustering of interest rates on retail bank deposits. Because theories of security price clustering are not applicable to the clustering of deposit interest rates, a new theory based on consumers' limited recall is proposed. In addition to explaining integer clustering, this theory has a number of other consequences. It predicts that noninteger deposit rates should be more frequently observed at rates just above integers rather than just below integers. It also predicts that retail deposit rates are stickier~less likely to change! when rates are quoted as even, rather than odd, fractions. Additional implications are that * Kahn and Pennacchi are from the University of Illinois, Sopranzetti is from Rutgers University. We are very grateful to

Price clustering on the limit-order book: Evidence from the Stock Exchange of Hong Kong

“…Christie and Schultz (1994a, b) propose the collusion hypothesis and present evidence that Nasdaq dealers avoid odd-eighth quotes to maintain wide spreads. Kahn et al (1999) observe that retail customers tend to underestimate odd-ending prices when recalling them and suggest a limitedrecall hypothesis to explain the more frequent even-ending yields in bank deposits. Booth et al (2000) examine the relation between internal/preference trading and price clustering, noticing that an internal market is more prone to price manipulation or collusion.…”

“…Competition among liquidity suppliers is intense, making collusion on quoted prices practically impossible. Our research makes an important ARTICLE IN PRESS 1 A partial list of recent studies include Ball et al (1985), Harris (1991), Goodhart and Curcio (1991), Colwell et al (1994), Grossman et al (1997), Gwilym et al (1998), Kahn et al (1999), Peltzman (2000), Sopranzetti and Datar (2002), Brown et al (2002), Jones and Lamont (2002), Jones (2003). 2 While Goodhart and Curcio (1991) examine the attraction hypothesis in price clustering in financial markets for the first time, there is a well-established consumer research literature that attributes rounding to human cognitive accessibility (Tversky and Kahneman, 1973;Higgins et al, 1977;Fazio et al, 1982). contribution to the literature for the following reasons.…”

Clustering and psychological barriers in exchange rates

“…It has been explored to only a limited degree in currency markets (Goodhart and Curcio, 1991;De Grauwe and Decupere, 1992;Grossman et al, 1997 and more recently Sopranzetti and Datar, 2002). Clustering is further documented in derivatives, i.e., options and futures markets and bonds (Gwilym et al, 1998a,b) as well as in commodity markets (Ball et al, 1985;Grossman et al, 1997), bank deposit rates (Kahn et al, 1999) initial public-offer auction bids (Kandel et al, 2001) and other price setting processes. 2 This renewed interest in recent periods is in part driven by a need to understand this clustering phenomenon.…”

A computational approach to the optimal structure of bank input prices

“…4 Many articles in the commercial banking literature use distinct interest rate elasticities to characterize the provision of demand and time deposit funds. See Berger and Hannan (1998), Kahn et al (1999), and Sharpe (1997) for example. Others empirically establish different interest rate sensitivities for the two accounts.…”