Abstract
We study dynamic labour supply using data on paua (abalone) divers in New Zealand. The divers face stable, flat prices per kilogram after each catch, but experience transitory wage changes due to varying weather and water conditions, and are free to vary their daily working hours and display an intermittent working pattern. We find nonlinear wage elasticities, rejecting the standard neo-classical prediction that these divers should work long hours during days when wages are high and quit early during days when hourly wages are low. We explore potentially distorting factors, but find little evidence. Applying Kőszegi and Rabin's (2006) theory where workers have both income and hours targets could explain our result. In particular, our divers appear to be primarily guided by the hours target.
Acknowledgements
Thanks to Olof Johansson-Stenman for comments. Financial support from Formas through the program Human Cooperation to Manage Natural Resources (COMMONS), and support from Sida to the Environmental Economics Unit at University of Gothenburg is acknowledged.
Notes
1 NZ$1 = US$0.74, November 2010.
2 For example, under the Fisheries Amendment Act 1986, no one can own or lease more than 20% of paua ITQs in a single Quota Management Area (QMA).
3 Newell et al. (2005) find the New Zealand ITQ system to be a potentially effective instrument for efficient fisheries management.
4 All data are confidential.
5 E = excellent, very good visibility, lot less swell than usual for this area and time of year; G = good, better than average, but not as good as excellent; A = average visibility and the swell was average for this area and time of the year; P = poor conditions, better than very poor, but not as good as average; V = very poor visibility for this area and time of year, and there was a lot more swell than usual for this area and time of year; UNREPORTED = diver did not supply the information.
6 Personal communication with Jeremy Cooper, CEO Paua Industry Council Ltd.
7 Including log wage cubed in the estimations for PAU 5D renders all wage terms insignificant and reduces the fit of the model.