Guy Grossman is a Professor of Political Science. His research is in applied political economy, with a substantive focus on governance, political accountability, international migration and trafficking, and conflict processes. He is the founder and academic director of PDRI as well as a member of the Evidence in Governance and Politics (EGAP) network and faculty affiliate of Stanford’s Immigration Policy Lab (IPL) Penn’s Center for the Study of Ethnicity, Race, and Immigration (CSERI) and Penn’s Identity & Conflict (PIC) Lab.
Grossman has designed and carried out field studies in sites across Africa, in collaboration with various international agencies, including the World Bank, the UK Department for International Development, the US Agency for International Development, and as well as with African governments and local non-governmental organizations.
Grossman’s work has appeared in the Proceedings of the National Academy of Sciences, American Political Science Review, American Journal of Political Science, International Organization, and Journal of Politics, among other journals. He holds a PhD in Political Science from Columbia University (2011, with distinction), as well as MA in Political Philosophy and LLB in Law both from Tel-Aviv University.
(April 2020). Political Partisanship Influences Behavioral Responses to Governors’ Recommendations for COVID-19 Prevention in the United States. Social Science Research Network, 253, 112957.
Voluntary physical distancing is essential for preventing the spread of COVID-19. Political partisanship may influence individuals’ responsiveness to recommendations from political leaders.
Daily mobility during March 2020 was measured using location information from a sample of mobile phones in 3,100 US counties across 49 states. Governors’ Twitter communications were used to determine the timing of messaging about COVID-19 prevention.
Regression analyses examined how political preferences influenced the association between governors’ COVID-19 communications and residents’ mobility patterns. Governors’ recommendations for residents to stay at home preceded stay-at-home orders and led to a significant reduction in mobility that was comparable to the effect of the orders themselves.
Effects were larger in Democratic than Republican-leaning counties, a pattern more pronounced under Republican governors. Democratic-leaning counties also responded more to recommendations from Republican than Democratic governors.
Political partisanship influences citizens’ decisions to voluntarily engage in physical distancing in response to communications by their governor.
(October 2019). It Takes a Village: Peer Effects and Externalities in Technology Adoption. American Journal of Political Science, 64(3), 536-553.
Do social networks matter for the adoption of new forms of political participation? We develop a formal model showing that the quality of communication that takes place in social networks is central to understanding whether a community will adopt forms of political participation where benefits are uncertain and where there are positive externalities associated with participation. Early adopters may exaggerate benefits, leading others to discount information about the technology’s value.
Thus, peer effects are likely to emerge only when informal institutions support truthful communication. We collect social network data for 16 Ugandan villages where an innovative mobile‐based reporting platform was introduced. Consistent with our model, we find variation across villages in the extent of peer effects on technology adoption, as well as evidence supporting additional observable implications. Impediments to social diffusion may help explain the varied uptake of new and increasingly common political communication technologies around the world.
(July 2019). Viral Voting: Social Networks and Political Participation. Quarterly Journal of Political Science.
Social context theory suggests that an important driver of political participation is the behavior of family, friends, co-workers, and neighbors. How do social ties between individuals shape equilibrium behavior in larger populations? Despite theoretical inroads into this question, direct empirical tests remain scarce due to data limitations.
We fill this gap using full social network data from 15 villages in rural Uganda, where village-level turnout is the outcome of interest. We find that levels of participation predicted by structural features of village networks are strongly associated with actual village-level turnout in low-salience local elections, and weakly associated in high-salience presidential elections. We also find these features predict other forms of political participation, including attending village meetings and contributing to village projects.
In addition to demonstrating that networks help explain political participation, we provide evidence that the mechanism of influence is that proposed by social context theory rather than alternative mechanisms like the presence of central brokers or the ability of networks to diffuse information.