Payal Shah is a research scientist at the Okinawa Institute of Science and Technology, Graduate University. Her research primarily uses economic theory to analyze social and environmental consequences of natural resource management policies, formulate optimal strategies to address environmental challenges such as climate change, and to evaluate preferences for environmental services. Payal received a Ph.D. in Agricultural and Applied Economics (2013) and a M.Sc. in Agricultural and Consumer Economics (2009) from the University of Illinois at Urbana-Champaign. She also has an MBA in Finance (2004) from Management Development Institute, India.
Main research topics:
1) Quantifying the impact of policy interventions for marine and terrestrial conservation
2) Optimal conservation planning in the face of climate change uncertainty
3) Valuation of marine ecosystem services
4) Using stochastic optimization tools for designing optimal conservation policy
Peer Reviewed Articles
Ando, Amy W. and Shah, Payal. 2010. Demand-side factors in optimal land conservation choice, Resource and Energy Economics, 32, 203-221.
Shah, Payal and Baylis, Kathy. 2015. Evaluating the Impact of Protection on Deforestation in Indonesia between 2000 and 2010 using Remote Sensing Data. PLoS ONE 10(6): e0124872. doi:10.1371/journal.pone.0124872
Shah, Payal and Ando, Amy W. 2015. Downside vs. symmetric risk in natural resource portfolio design to manage climate-change uncertainty. Land Economics, 91(4), 664-687.
Ando, Amy, W. and Shah, Payal. 2016. The Economics of Conservation and Finance: A Review of the Literature. International Review of Environmental and Resource Economics, 8 (3–4), 321-357. http://dx.doi.org/10.1561/101.00000072
Shah, Payal and Ando, Amy W. 2016. Permanent and Temporary Policy Incentives for Conservation under Stochastic Returns from Competing Land Uses. American Journal of Agricultural Economics, p.aaw032.
Shah, Payal, Mallory, Mindy, Ando, Amy W., and Guntenspergen, Glenn. 2016. Fine‐resolution conservation planning with limited climate‐change information. Conservation Biology.
Schwanitz, Valeria Jana, Wierling, August and Shah, Payal. 2017. Assessing the Impact of Renewable Energy on Regional Sustainability—A Comparative Study of Sogn og Fjordane (Norway) and Okinawa (Japan). Sustainability, 9(11), p.1969.
Mcclenachan, Loren, Matsuura, Ryunosuke., Shah, Payal. and Dissanayake, Sahan. 2018. Shifted historical baselines reduce willingness to pay for conservation. Frontiers in Marine Science, 5, p.48.
Shah, Payal, Dissanayake, Sahan, T. M., Fujita, Yoko and Nunes, Paulo, A.D. 2019. Impact of a local, coastal community based management regimw when defining marine protectde areas: Empirical results from a study in Okinawa, Japan. PLOS One. https://doi.org/10.1371/journal.pone.0213354
Yamaguchi, Rintaro and Shah, Payal. 2020. Spatial Discounting of Ecosystem Services. Resource and Energy Economics, 101186.
- Shah, Payal, Dissanayake, Sahan, T.M., Carlson, Nils, Fujita, Yoko, and Nunes, Paulo A.L.D. 2016. Preferences for marine protection in Okinawa: A comparison of management options and two groups of beneficiaries. Handbook on the Economics and Management for Sustainable Oceans, UN Environmental Programme and Edward Elgar Publishing House, UK
- Loechl, Paul, M., Kemme, Michael, R., Shah, Payal, S., & Goran, William, D. 2012. Resource Efficiency in the US Army Corps of Engineers: Examination of Strategies to Reduce Energy Use and Greenhouse Gas Emissions (No. ERDC/CERL-TR-12-17). Engineer Research and Development Center Champaign IL Construction Engineering Research Lab.
Mieno, Taro, Tanaka, Kenta, Shah, Payal. Optimal timing of irreversible land use conversion under uncertainty: An experimental approach. In review.
- Baylis, Kathy, Fullerton, Don and Shah, Payal. What drives forest leakage? In preparation.
- Ando, Amy W., Mallory, Mindy, Shah, Payal and Guntenspergen, Glenn. Portfolio analysis with spatial targeting and projects to reduce effects of climate change. In preparation.
- Yamaguchi, Rintaro and Shah, Payal. Spatial Discounting of Ecosystem Services. In preparation.