Abstract: Technological innovation is a key driver of long-term economic growth and thus an important force behind fluctuations of stock prices. Technology spillovers across firms play a vital role in generating long-term economy-wide growth from technological innovations. A primary channel through which innovation percolates in the economy is the reallocation and mobilization of human capital in the talent markets. While some of the value to technological innovation can be held by firms in the form of patents, most of these innovative ideas and technological skills are embodied in the human capital of talents. Since the compensation and reallocation of talents are largely determined by the market structure of talents, such as concentration, bargain power, and searching frictions, understanding the market structure of talent is critical to understanding technological progress, economic growth, and asset prices. This research project aims to understand how innovation propagates through the reallocation of talents, and how this innovation diffusion process is shaped by the competition structure of talent labor markets. Specifically, we exploit various heterogenous shocks to firms, including credit supply shocks, financial constraints shocks, innovation shocks, to examine how firms react in their hiring and firing decisions under different competition structures of talent labor markets. Further, we also investigate how product market competition affects the spillover of technological advances through talent labor markets. Particularly, to understand firm demand for talents over time and across occupations, we will be able to leverage the granular-level data from Burning Glass Technologies to understand the specific research and innovation related skills demanded by employers. Moreover, in this project, we will be able to use matched employer-employee data from the US Census, which spans all private non-farm firms to understand how employees respond to firm-level shocks and how these shocks impact their decision to move across firms. Finally, we will also exploit the granular-level patent data to provide direct tests on whether reallocation of talents facilitate transmission of technological advances, and if so, to what extent.