My name is Jonathan Sweeney. I am a Postdoctoral Scholar at the University of California Santa Cruz. I work on topics in management strategy evaluation, Bayesian methods, and decision analysis. Currently I study the swordfish, sardine, and albacore fisheries along the west coast of the US. My recent dissertation work has been on predicting the effects of policy changes on Hawaii's fishing industry.

Research Areas:

Management Strategy Evaluation

Bayesian Methods

Decision Analysis


Department of Economics

Saunders Hall 542

2424 Maile Way, Honolulu, HI 96822



PhD Economics, University of Hawaii at Manoa, 2018

BA Biology, Reed College, 2008

Curriculum Vitae


Published Papers:

Sweeney, J.R., Howitt, R.E., Chan, H., Pan, M., and P. Leung. 2017. How do fishery policies affect Hawaii's longline fishing industry? Calibrating a positive mathematical programming model. Natural Resource Modeling 00:e12127. PDF

Oberle, B., Ogle, K., Penagos Zuluaga, J.C., Sweeney, J.R., and A.E. Zanne. 2016. A Bayesian model for xylem vessel length accommodates subsampling and reveals skewed distributions in species that dominate seasonal habitats. Journal of Plant Hydraulics 3(e003).

Revell, L. J., Mahler, D.L., Sweeney, J.R., Sobotka, M., Fancher, V.E., and J.B. Losos. 2010. Nonlinear selection and the evolution of variances and covariances for continuous characters in an anole. Journal of Evolutionary Biology 23(2):407-421.

Working Papers:

Sweeney, J.R. Balancing goods and bads: A Bayesian analysis of fishery regulatory decisions.

Sweeney, J.R., and T. Halliday. Estimating a dynamic structural model of fishers' labor supply.

Works in Progress:

Bayesian calibration of positive mathematical programming models.

How will expanding Papahanaumokuakea Marine National Monument impact local fishing communities in Hawaii? An application of positive mathematical programming

Fisher landing decisions: Evaluating the benefits of market entry coordination.


Sustainable Development (ECON 350) Fall 2016


Principles of Microeconomics (ECON 130) Fall 2013

Teaching Assistant


Bayesian IV and Causal Inference

  • Code for constructing a simple Bayesian IV estimator, and replicating Imbens and Rubin (1997).
  • Gaussian Process Sea Turtle Forecast

  • Code for building a Gaussian process forecast in Stan. Many thanks to Nathan Sanders and Victor Lei for making their code available.
  • Toy Decision Analysis

  • Solution to BDA3 Chapter 9, exercise 1. How many widgets should you manufaction in order to maximize your expected profit? Here's the solution.
  • Global Fishing Watch Animation

  • Code for creating animation using Global Fishing Watch data.