This paper examines the impact of geographic technological diversification on firm innovativeness. Our empirical study conducted on a panel of U.S. manufacturing companies shows that firms with geographic technological diversification are more innovative (as measured by both patents and citations) than firms without. Furthermore, we find that the positive relation between geographic technological diversification and firm innovation is driven by domestic technological diversification, while international technological diversification is negatively related to firm innovation. Our valuation tests further confirm the detrimental effect of international technological diversification on shareholder wealth.

Motivated by several interesting features of the highway mowing auction data from the Texas Department of Transportation (TDoT), we study three competing procurement auction models with endogenous entry. Our entry and bidding models provide several interesting implications. For the first time, we show that even within an independent private value paradigm, as the number of potential bidders increases, bidders' equilibrium bidding behaviour can become less aggressive, and the expected procurement cost may rise because the “entry effect” is always positive and may dominate the negative “competition effect”. We then develop structural models of entry and bidding corresponding to the three models under consideration, controlling for unobserved auction heterogeneity, and use the recently developed semi-parametric Bayesian estimation method to analyse the data. We select the model that best fits the data, and use the corresponding structural estimates to quantify the “entry effect” and the “competition effect” with regard to the individual bids and the procurement cost.

We study the estimation of (joint) moments of microstructure noise based on high frequency data. The estimation is conducted under a nonparametric setting, which allows the underlying price process to have jumps, the observation times to be irregularly spaced, and the noise to be dependent on the price process and to have diurnal features. Estimators of arbitrary orders of (joint) moments are provided, for which we establish consistency as well as central limit theorems. In particular, we provide estimators of autocovariances and autocorrelations of the noise. Simulation studies demonstrate excellent performance of our estimators in the presence of jumps, irregular observation times, and even rounding. Empirical studies reveal (moderate) positive autocorrelations of microstructure noise for the stocks tested.

This study develops a theoretical model to analyze the asset substitution problem over insurance decisions. We find that agency conflict is related to a firm’s risk level and capital structure. In particular, at the optimal leverage, agency conflict occurs only when the risk level is relatively high, which explains why insurance covenants are typically for significant pure risks. Moreover, when the risk level is specified, agency conflict over insurance decisions occurs within a specific leverage range. This is consistent with the findings of some research on the asset substitution problem over speculative risk choices. In addition, we consider premium loadings and conclude that full hedging is not a firm’s optimal risk management strategy, contributing to the literature on optimal hedging decisions with transaction frictions. Our framework with premium loadings can also explain many insurance phenomena, such as risk retention for small losses and subsidies for catastrophe insurance.

We conduct a comprehensive study on momentum spillovers in the Chinese stock market using various types of economic linkages, with particular attention to momentum spillover via news co-mention linkages. We utilize millions of Chinese business news articles and develop a flexible and innovative algorithm to identify linkages among listed firms. We find that news co-mention momentum spillover is stronger than others, unifying various forms of momentum spillover effects in the Chinese market and replacing the role of analyst co-coverage in the U.S. News co-mention identifies a wide range of economically important linkages, particularly recovering more cross-industry linkages than other link identification methods, which contributes to its strong performance.

Open-end corporate bond mutual funds invest in illiquid assets while providing liquid claims to shareholders. Does such liquidity transformation introduce fragility to the corporate bond market? To address this question, we create a novel bond-level latent fragility measure based on asset illiquidity of mutual funds holding the bond. We find that corporate bonds bearing higher fragility subsequently experience higher return volatility and more outflows-induced mutual fund selling over the period of 2006–2019. Using the COVID-19 crisis as a natural experiment, we find that bonds with higher precrisis fragility experienced more negative returns and larger reversals around March 2020.