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(1) Throughout this article, monetary values are the year 2000 New Zealand dollars, which are typically worth about half a U.S. dollar. Tons are metric tons.

(2) A referee raised the question of whether we should expect the behavior of fishermen to reflect linkages between capital and quota markets. Because fishermen often purchase equipment and vessels using commercially available capital, their decisions are linked with broader capital markets. Figure 1 and the econometric evidence presented herein also bring into question the often-prevailing notion that fishermen do not behave in an economically sophisticated way, and lack an understanding of the relative cost of capital. Having said that, Karpoff (1985) investigates and finds evidence for the existence of nonpecuniary factors in the license prices of Alaska salmon fishery. An interesting question for further research is whether we might be able to undertake a similar analysis.

(3) Recently, McGough, Plantinga, and Provencher (2004) investigate the implications of a rational expectations equilibrium in timber markets on the time series properties of timber prices.

(4) If the discount rates follow a martingale process, then the best predictor of future discount rates at time t is the current rate, i.e., [E.sub.t]([r.sub.t+1]) = [r.sub.t] (LeRoy 1989). This is supported empirically by econometric analyses of interest rates. For a more general analysis of time-varying rates, see Chapter 7 of Campbell, Lo, and MacKinley (1997).

(5) For fish stocks with noncommercial interests, such as the red snapper fishery (Region 1), the TAC for the commercial fishery is denoted the total allowable commercial catch (TACC). For expositional reasons, we use TAC to refer to TACC for these fisheries.

(6) During the time period of our analysis, in addition to the lease and asset markets, fishers had a number of ways to balance their quota holdings and catches within a 30 day window after landing their catch (see NSK). Sanchirico et al. (2006) describe these flexibility mechanisms, how they changed over time (mostly in October 2001), and their level of use.

(7) The flexibility to time fishing trips when port prices are higher, and the elimination of large supply gluts of fresh product, have resulted in increases in price per pound of more than 40% in the Alaskan halibut ITQ fishery (Casey, Wilen, and Dewees 1995). The focus on quality is also evident in New Zealand, where fishermen have changed catching methods in the red snapper fishery in order to sell their catch on the highly profitable Japanese live fish market (Dewees 1998).

(8) Ideally our specification would impose [lim.sub.t[right arrow][infinity]] ln[psi](*) = 1, but this would require a functional form necessitating nonlinear estimation in an instrumental variables panel data context. We have therefore opted for a linear approximation.

(9) Equation (3) is derived under the assumption that factors affecting profit growth (e.g., output prices or costs) persist indefinitely, and it is solved by assuming the convergence of an infinite sum. Therefore, factors that will either grow or decline only over the short-run, such as TAC changes, are not found in the long-run solution of asset prices.

(10) About 30% of lease and 25% of sale observations that did not represent reliable market transactions were omitted. For more information on how these prices were identified, see NSK. In addition, 1,324 of the 4,120 observations have sale prices that are constructed from only one transaction and 281 observations have a lease price calculated from one trade. However, those observations with only one underlying sale transaction come from stocks that have, on average, 2.5 sales per quarter. For leases, this value is 9.4. This suggests that while some stocks may have isolated periods of low market activity, in general they feature a reasonable number of trades.

(11) The New Zealand Ministry of Fisheries uses the mortality rate to construct a measure of natural variability that is factored into the setting of the TAC (Annala, Sullivan, and O'Brien 2000). The assumption is that a stock with higher natural mortality will have fewer age classes and therefore have greater fluctuations in biomass.

(12) We estimate the output price growth rate independently for each species based on a first-order autoregressive model of the log fish price, including a time trend, quarterly (seasonal) effects, and a constant term. The estimates for a small number of species are negative and to avoid taking the logarithm of a negative number, we add and subtract 1 in the denominator of equation (5). Another option would be to directly estimate the growth rate in lease prices, but this introduces econometric issues due to the endogeneity of lease prices.