Asset pricing in created markets.

(13) We classified fish stocks as to whether they faced significant initial catch reductions under ITQs by using historical information on catch rates, TAC levels, and references in the literature (see supplementary material in NSK for more information). The following 33 fish stocks were so classified: CRAI-5, CRA7-8, BNS2, ELE3-5, JDO1, MOKI-3, ORH2B, SCH1-3, SCH5, SCH7-8 SKI3, SNA 1-2, SNA8, SPO1-3, SPO7-8, TRE1, HPB2-3.

(14) A testable implication of the present value model is that the time series properties of asset prices and dividends should be the same. That is, if rents are (non) stationary, then agricultural land prices should he (non) stationary. Falk (1991) finds that in the Iowa farmland market both series follow a unit root, while Clark, Fulton, and Scott (1993) reject the hypothesis that the two series have the same time series representations for Illinois farmland.

(15) Both the Wu-Hausman F-test and Durbin-Wu-Hausman chi-squared test strongly reject (p-value < 0.0001) the null hypothesis of exogeneity of the lease price (see Davidson and MacKinnon 1993).

(16) It is reasonable to treat fish prices as given because New Zealand exports about 90% of its commercial catch, yet accounts for less than 1% of world fishing output. Even in the small number of cases in which New Zealand comprises a sizeable fraction of the world catch of individual species, these species have many near-perfect substitutes in the form of other "white fish."

(17) A t-test does not reject the null hypothesis that the coefficient on lease price is equal to 1 for specification (ii), but it does so for specifications (i), (iii), and (iv). We also found that the coefficient on lease price is somewhat higher when the sample is restricted to the second half of the sample period, compared to the first half. This is consistent with the market operating more efficiently the longer it has been in existence.

(18) Because some fish stocks experienced nonmarginal cuts in TAC after the introduction of the ITQ system, we tested whether the year-to-year percentage change in TAC, or the TAC relative to its initial value, had any influence on the results. For both specifications, we also interacted the TAC change variable with a dummy variable indicating whether the change was positive or negative (i.e., we allowed for differential effects of TAC cuts or TAC increases). None of these variables were found to have a statistically significant effect on the quota price when added to the model.

Richard G. Newell is the Gendell Associate Professor of Energy and Environmental Economics at the Nicholas School of the Environment and Earth Sciences, Duke University, Durham, North Carolina and a University Fellow at Resources for the Future. James N. Sanchirico is a Senior Fellow at Resources for the Future, Washington DC 20036. Kerry L. Papps is a Ph.D. student in the Department of Economics at Cornell University, Ithaca, NY. Table 1. Species Included in the New Zealand ITQ System as of 1998 Species Abbreviation Year Entered Barracouta BAR 1986 Blue cod BCO 1986 Bluenose BNS 1986 Alfonsino BYX 1986 Rock lobster CRA 1990 Elephant fish ELE 1986 Flatfish FLA 1986 Grey mullet GMU 1986 Red gurnard GUR 1986 Hake HAK 1986 Hoki HOK 1986 Hapuku and bass HPB 1986 John Dory JDO 1986 Jack mackerel JMA 1987 Ling LIN 1986 Blue moki MOK 1986 Oreo OEO 1986 Orange roughy ORH 1986 Oyster OYS 1996 Paua (abalone) PAU 1987 Packhorse rock lobster PHC 1990 Red cod RCO 1986 Scallops SCA 1992 School shark SCH 1986 Gemfish SKI 1986 Snapper SNA 1986 Rig SPO 1986 Squid SQU 1987 Stargazer STA 1986 Silver warehou SWA 1986 Tarakihi TAR 1986 Trevally THE 1986 Blue warehou WAR 1986 Species Fish Stocks Species Type Barracouta 4 Offshore Blue cod 7 Inshore Bluenose 5 Inshore Alfonsino 5 Inshore Rock lobster 9 Shellfish Elephant fish 5 Inshore Flatfish 4 Inshore Grey mullet 4 Inshore Red gurnard 5 Inshore Hake 3 Offshore Hoki 1 Offshore Hapuku and bass 7 Inshore John Dory 4 Inshore Jack mackerel 3 Offshore Ling 7 Offshore Blue moki 4 Inshore Oreo 4 Offshore Orange roughy 7 Offshore Oyster 2 Shellfish Paua (abalone) 10 Shellfish Packhorse rock lobster 1 Shellfish Red cod 4 Inshore Scallops 2 Shellfish School shark 7 Inshore Gemfish 4 Offshore Snapper 5 Inshore Rig 5 Inshore Squid 3 Offshore Stargazer 7 Inshore Silver warehou 3 Offshore Tarakihi 7 Inshore Trevally 4 Inshore Blue warehou 5 Offshore Table 2. Descriutive Statistics for Determinants of Fishing Quota Asset Prices Variable Mean Std. Dev. Lease price ($/ton) 1,795 4,289 Asset price ($/ton) 20,266 46,870 Export price ($/ton) 8,319 12,096 Export price growth rate 0.013 0.023 Interest rate 0.064 0.022 Normalized percentage of 1.000 0.952 quota sold Natural mortality rate 0.222 0.174 Reduced TAC (dummy indicating 0.273 0.446 fishery had initial reductions) Shellfish (dummy indicating 0.116 0.320 shellfish quota market) Number of leases per quarter 17 20 Number of asset sales per quarter 4 4 Variable Min. Max. Lease price ($/ton) 1 43,663 Asset price ($/ton) 22 358,586 Export price ($/ton) 630 61,009 Export price growth rate -0.027 0.071 Interest rate 0.027 0.110 Normalized percentage of 0.000 11.892 quota sold Natural mortality rate 0.045 1.000 Reduced TAC (dummy indicating 0 1 fishery had initial reductions) Shellfish (dummy indicating 0 1 shellfish quota market) Number of leases per quarter 1 194 Number of asset sales per quarter 1 75 Note: Statistics are based on the 4,120 observation samples from the estimation of quota asset price determinants. Monetary figures are the year 2000 New Zealand dollars, which are typically worth about half a U.S. dollar. Tons are metric tons. Table 3. Determinants of Fishing Quota Asset Prices Variables (i) (ii)

Within

Pooled (Fixed Effects) Logged lease price 0.840 *** 0.861 ***

(instrumented) (ln [pi]) (0.016) (0.234) Interest rate (ln(1 + r)) -3.048 -3.966 **

(1.871) (1.961) Natural mortality rate (1n [theta]) -0.329 ***

(0.071) Growth in output prices (ln(1 + g)) 2.848 ***

(0.583) Normalized percentage of quota 0.013 0.013

sold (s) (0.012) (0.013) Fisheries with initial reductions in 0.099 *

TAC (a) (dummy variable) (0.054) Interaction of time with variable 0.006 0.006

indicating fisheries with initial (0.006) (0.008)

reductions in TAC (a x t) Shellfish (dummy variable) 0.271 ***

(0.056) Seasonal effects Jointly Jointly