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Econometrics Of Environmental Valuation: The Bayesian Inferences On Willingness To Pay Estimations

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  • Ukpong, Inibehe George

Abstract

This study applied the Bayesian approach to estimate people’s willingness to pay (WTP) for mitigation of environmental hazards in oil producing areas in Nigeria. The Bayesian approach enabled estimation of the mixed logit model employing the normal and log-normal distributions of WTP parameters. The model estimate indicating a negative WTP values for the status quo (STAQUO) attribute suggests that people in oil producing areas in Nigeria do not like the current welfare situation and environmental condition which are characterised by environmental problems, affecting adequate use of resources and ecosystem services. The results also show a comparatively higher WTP for food safety (FOODSAF), poverty rate (POVERTY) and unemployment rate (UNEMP) respectively, suggesting people’s desire for mitigation of undesirable livelihood (welfare) impacts of resource exploitation. On the other hand, the results also indicate positive WTP coefficients for land and water pollution from oil spills (SPILL), gas flaring (GFLARE) and land occupied by oil and gas pipelines (LOCC), suggesting that majority of the people are in support of mitigation strategies or policy change that would ensure significant reduction in environmental pollution, gas flaring, and land-take by oil and gas companies. Oil and gas companies are encouraged to ensure mitigation of environmental and livelihood impacts of the crude oil and gas extraction, including reduction in gas flaring, based on environmental laws and global best drilling practices. The study further recommends application of the willingness to pay approach as an important strategy for assessing the values of environmental resources and the impact of resource use.

Suggested Citation

  • Ukpong, Inibehe George, 2019. "Econometrics Of Environmental Valuation: The Bayesian Inferences On Willingness To Pay Estimations," Review of Agricultural and Applied Economics (RAAE), Faculty of Economics and Management, Slovak Agricultural University in Nitra, vol. 22(2).
  • Handle: RePEc:ags:roaaec:293664
    DOI: 10.22004/ag.econ.293664
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