Belief Formation, Signal Quality, and Information Sources: Experimental Evidence on Air Quality from Pakistan
This research, conducted in collaboration with the University of California, Davis and Williams College, by Dr. Sanval Nasim, Assistant Professor at MGSHSS, aims to develop a forecast model of day-ahead air pollution using inputs from government and private monitors across Lahore. Reliable information on air quality could generate considerable public benefit, especially when avoidance measures are costly to resource constrained citizens, such as increased demand for protective masks. Governments in developing countries, however, often struggle to provide consistent and reliable air quality information that would allow citizens to form accurate beliefs about air pollution. Provision of reliable and trusted information is critical for the public to adapt to air pollution, as Lahore consistently ranks as having some of the worst air quality around the world. This study will explore if citizens of Lahore update their beliefs about air quality and modify avoidance behaviors when they receive information attributed to different sources: government or a private citizens’ group. This research will provide valuable feedback to the efficacy of environmental monitoring systems by the Punjab Environment Protection Department and private-sector alternatives.