This dissertation studies spillovers in urban and housing markets. The first chapter studies the micro-structure of segmented local housing markets. With housing transactions data on 188 U.S. cities from 2000 to 2015, this chapter builds a workhorse model to study house price dynamics that includes supply side differences across cities. I show that heterogeneity in supply responses cross-sectionally is key to explain price changes overtime in an assignment model framework. The market clearing process in the assignment model operates in a vertically ranked order and matches the joint distributions of households and houses, generating two countervailing forces where demand spills upwards and supply is added from the top down. These two forces result in mismatch in demand and supply at some segments which causes general equilibrium spillovers to prices in other segments. I structurally estimate the spillovers, show they drive house price segmentation, and account for 8% of variation in prices on average. These findings provide new insights on within-market GE spillovers across price ranks in local housing markets, and help us understand how supply side housing policies could have substantial amplification effects beyond their targeted segments through this mechanism. The second chapter studies telecommunications infrastructure and productivity. Broadband Internet is considered an important determinant of economic and population growth. I estimate the effect of Internet infrastructure on the population and employment growth of U.S. cities over 20 years period after the Internet became widely available in the 1990s. I employ an instrumental variables strategy which uses AT&T Long Lines of 1960 to address the concerns that the location of Internet network is not random. I find that a 10% increase in a city's Internet infrastructure causes about 1.7% increase in its population and 2.4% increase in its service sector employment.