“Conflicts and Choices in Biodiversity Preservation,” by Metrick & Weitzman

Introduction n What is biodiversity? n How is it measured? n What are we optimizing? n Outline of paper: –Constrained optimization problem w/ biodiversity in objective function –Solution: cost-benefit ranking criterion –Positive “revealed preference” analysis of US. Fish & Wildlife (FWS) use of the Endangered Species Act (ESA)

Economics of Diversity Preservation n Conceptualize a species as if it were a library. n Books in the library are like genes. n Library is at some risk of burning down and losing some books. n 2 classes of benefits: –Direct utility from each library –Indirect utility for overall “diversity” of library books, i.e. genes n How will Noah decide which species to put on the Ark? n Noah must weigh expected gains against cost

Economics of Diversity Preservation n Four concepts: –D i = distinctiveness of i = how unique or different is i –U i = direct utility of i = how much we like or value i per se –  P i = by how much can the survivability of i actually be improved –C i = how much does it cost to improve the survivability of i by  P i –Use a priority ranking base on the criterion: –R i = [D i + U i ](  P i/ C i ) –It will be difficult to measure these variables, but this give us a starting point for thought.

The ESA: What Are We Preserving? n Four factors to consider: –1) utility –2) distinctiveness –3) survivability –4) cost of enhancing survivability n Which factors actually matter in practice? n Find bureaucratic variables as proxies for Noah’s ranking and regress them against proxy variables for utility, distinctiveness, survivability and cost.

The ESA: What Are We Preserving? n 1 st proxy variable for Noah’s ranking: log of number of favorable public comments n 2 nd proxy variable for Noah’s ranking : listing decision itself. –Dummy variable = 1 if listed, 0 otherwise. n 3 rd proxy variable for Noah’s ranking : public money spent from 1989 to 1993 on recovery of that species. 4 species have had over $50 million spent on each of them: chinook salmon, red- cockaded woodpecker, northern spotted owl, and bald eagle. Roughly 1/3 of $914 million spent on all species.

Proxies for 4 key decision variables: n Utility : charismatic megafauna, i.e., large popular animals. –Use log of length of species. Also use dummy variables for each taxonomic class w/in vertebrates: MAMMAL, BIRD, REPTILE, AMPHIBIAN, & FISH. n Diversity: –UNIQUE dummy variable =1 if species is sole representative of its genus; ) otherwise –Also use SUBSPECIES

Proxies for 4 key decision variables: n Survivability: Nature Conservancy, ranks comprehensive list of all U.S vertebrate species of scale from 1 (most endangered ) to 5 (least endangered); ENDANGERMENT n Cost: CONFLICT with development variable from FWS (part of PRIORITY variable used by FWS). CONFLICT is a dummy variable = 1 if the species is in conflict with development; 0 otherwise. Priority runs from 1 (highest priority) to 18 (lowest priority).

Proxies for 4 key decision variables: n LNCOMMENTS results: –Only ENDANGERMENT is statistically significant, but has wrong sign (positive), higher endangerment score (meaning less endangered) receives more comments. Surprising finding n LISTED results: –MAMMAL & BIRD coefficients are positive –AMPHIBIAN coefficient is negative –UNIQUE positive coefficient – SIZE has positive coefficient –ENDANGERMENT has correct negative sign

Proxies for 4 key decision variables: n LNSPEND 3 rd column results: –SIZE coefficient is large and significant is an elasticity. Interpretation: a 8.6 percent increase occurs for a 10 percent increase in size. –ENDANGERMENT is statistically significant, but has wrong sign (positive) again, higher endangerment score (meaning less endangered) receives more funding. Surprising finding –REPTILE has negative coefficient –SIZE has positive coefficient

Proxies for 4 key decision variables: n LNSPEND 4 th column results: –SIZE coefficient is large and significant is an elasticity. 8.6 percent increase for a 10 percent increase in size. –ENDANGERMENT is statistically significant, but has wrong sign (positive) again, higher endangerment score (meaning less endangered) receives more funding. Surprising finding. –PRIORITY has correct negative sign. –CONFLICT has positive sign which is not consistent with cost-benefit formula. Perhaps the intelligence –gathering and policy-making arms of the FWS should be separated.

Summary n 1) People weigh utility the most heavily. n 2) Survivability, diversity, and cost do not seem to play their “expected” role in spending decisions. n 3) Scientific part of the priority system seems to be influenced by same subjective factors that influence spending.