A central tenet of financial economics is that stock prices aggregate different pieces of information about fundamentals held by myriad of investors, who devote time and effort to acquire such information to make trading profits. As a result, stock prices provide forward-looking signals about future fundamentals to various agents in the real economy (e.g., regulators, central bankers, analysts, or corporate managers), who can in turn use them to guide their decisions (e.g., monetary policy or corporate investment). On this ground, a large research effort (surveyed below) has been devoted in the past decades to empirically measure stock price informativeness (i.e., their ability to predict future fundamentals), and assess the informational role of stock prices in facilitating resource allocation in the real economy. To date, the theoretical and empirical literature studying price informativeness remains however remarkably silent about the horizon over which informativeness is measured (and defined). Yet, it is conceptually very different for a firm's stock price to be informative about what will be its fundamental value next year as opposed to in ten years. In theory, there is little reason to believe that the horizon dimension of irrelevant. On the one hand, different groups of investors may trade on information pertaining to distinct horizons (e.g., some short-term and other long-term), potentially generating a ``term structure'' of stock price informativeness. On the other hand, agents relying on stock price as a source of information typically have to form expectations about fundamentals over different horizons (e.g., projects' cash flows). Hence, it appears of paramount importance to understand whether there exists a term structure of stock price informativeness, and if so, how it influences the informational role of stock markets for the real economy. The goal of this proposal is to study these questions (for the first time), through three related projects. Project 1: The project's objective is to develop and evaluate a new (theory-based) empirical measure of the informativeness of stock prices at different horizons to characterize the term structure of stock price informativeness. We propose to do so by comparing actual firms' stock prices to the hypothetical stock prices that would be obtained if investors had perfect foresight at different horizons (e.g., one or five years) and used a present-value approach to determine asset prices. Project 2: The project's objective is to use our new measure to study the evolution of informativeness of stock price over the last 60 years all over the world. Financial markets have experienced dramatic changes in the last decades, ranging from regulations, technologies, data availability (e.g., big data), trading mechanisms and locations, or the composition of investors (e.g., high-frequency traders or passive investors). All these factors may have contributed to improve or hamper the ability of stock prices to predict future fundamental values, and modify the term structure of price informativeness. Project 3: The project's objective is to assess whether the term structure of stock price informativeness matters for firms' investment decisions. Intuitively, when deciding on investment projects, corporate managers have to form expectations about future payoffs at different horizons. Hence, if they rely on information embedded in prices as a source of information, they should be sensitive to the term structure of stock price informativeness. This project thus explores the interplay between the term structure of price informativeness (using our new measure) and corporate decisions, and assess the resulting gain (or loss) in economic efficiency.