This dissertation explores the roles that the news media and public opinion play in shaping policymaking in American state and local governments, drawing on extensive archives of local newspaper transcripts, media market and circulation data, outputs of the policymaking process in states and municipalities, and measures of public opinion.
In the first paper, I show that media coverage is associated with greater policy responsiveness in state legislatures. When legislators are more likely to be covered by local newspapers and television news broadcasts in their districts, they are better at reflecting constituent preferences in roll-call voting. Defying the seminal theories of electoral accountability, however, I find no evidence that the media affects what the public knows about state politics or how they behave in state legislative elections. Rather, I conjecture that local news affects representation via a more direct, elite-focused “watchdog” mechanism—by informing legislators about public opinion or increasing the perceived costs that politicians face when deciding to cast an unpopular vote.
The second paper examines the implications of news organizations’ decisions as to which local governments to invest in covering routinely. Newspapers are more likely to cover politics in larger cities and those with more white and wealthy residents. In cities and towns that the press covers more frequently, I find that local governments spend more per-capita on providing public goods, particularly policing, parks, housing, and public transportation. This suggests that increasing financial pressures on already resource-constrained news outlets may have negative implications for local public goods provision that could exacerbate existing inequalities in American democracy.
Finally, in the third paper, I offer a methodological contribution to the measurement of public opinion at subnational geographies. Although the development of Multilevel Regression and Poststratification (MRP) has allowed scholars to more accurately estimate subnational public opinion using national polls, its usefulness has been limited in certain contexts because it generally recovers less accurate estimates from cluster-sampled surveys. I propose two approaches to improve estimation from MRP with cluster-sampled polls. The first is pooling data from multiple surveys to produce a larger sample of clusters. The second is Clustered MRP (CMRP), which extends MRP by modeling opinion using the geographic information included in a survey’s cluster-sampling procedure.
| Identifer | oai:union.ndltd.org:columbia.edu/oai:academiccommons.columbia.edu:10.7916/7qqc-m014 |
| Date | January 2024 |
| Creators | Auslen, Michael Edward |
| Source Sets | Columbia University |
| Language | English |
| Detected Language | English |
| Type | Theses |
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