# Presentation: 700601

## Economic Heterogeneity 

**in the Atlantic and Gulf of Mexico Longline Fishery**.
-  *Ivar Strand*
*Professor Emeritus*
*University of Maryland*

- Sociologists have made a point of emphasizing the differences
- in communities and community structures in the management of
- fisheries. I wanted to see if there were differences in economic
- behavior if behavior were studied on a more local level.

## The purpose of the paper: 

- Examine how the activities and risk preferences
- of fishermen vary at a localized scale.

- Why risk preferences?

- What scale?

- What setting?

## Slide 3

## N-S

**N-S**

## E-W

**E-W**

## My intentions are to examine the fishing location and return

- homeport decision. The fishing areas are defined
- according to the map and the homeport region

** **
**     ****1.)    **New England- ports north of New York;
**     ****2.)    **Mid-Atlantic- ports north of Cape Hatteras to, but not including, Connecticut;
**     ****3.)    **South Atlantic- ports south of Cape Hatteras to Florida;
**     ****4.)    **East Coast of Florida- ports north of Key West to, but not including, Georgia;
**     ****5.)    **Eastern Gulf of Mexico- ports east of Lousiana to Key West;
-      **6.)    **Western Gulf of Mexico- ports east of Mexico to, but not including, Mississippi

## We used a random utility model specification where

- Individual n on trip t chooses the location/landing port choice
- J  by maximizing expected utility:

- for which the second order approximation for
- the expected utility is:

## Must specify the utility function and have the initial

- wealth. Two commonly used utility function are
- the logarithmic and the quadratic. The second order
- approximation for these was attempted :

- Quadratic utility (2 parameters)

-  Log utility (one parameter)

## What is needed are the expected lottery returns 

- (net payoffs at site/port) and the initial wealth position.

- Developed expected returns based on harvests (catch/set mile) for each of the possible combinations. Used a weighted combination of all trips in area/port for the last three weeks. Did not use previous history. Calculated the mean and variance for these to develop the expected returns. Computed costs on the basis of miles from homeport.

- Wealth was estimated by using the market value of the vessel as estimated by Porter et al. and by assuming that everyone’s net wealth was 0.

## TX

- NC, SEFL

- MD, NE

- LA,  SWFL

- FL Keys

- Expected utility of return (K dollars)

## Arrow-Pratt Measure versus Return (K dollars)

- FL Keys

- MD,NE

- NC,SEFL

- A Measure
- of risk aversion

## But in the random utility case, we (the researchers) do not

- know exactly what U is, only know EU:

## For the quadratic case:

***AP(r)*****=*

## Computed AP(R)* for fixed levels of probabilities

- and obtain similar results to before but one reversal:

- FL Keys

- MD,NE

- NC,SEFL

*AP(R)* *versus returns

## But depends on R and should program that into it. 

- This may eliminate the property of increasing risk aversion. Yet to be done.

## Conclusions:

- 	Economic structure as well as risk 	preferences do vary at local levels. Still it
- 	may be a function of the resource stocks.

- Found that individuals operating in the Florida Keys had the greatest aversion to risk, both when considering the researcher’s uncertainty and when not.

- The other risk aversion parameters were not too
- dissimilar. Will likely try to test for significant
- differences.