This study theoretically and empirically examines the impact of intangible capital on firm markups. The current research follows Altomonte et al. (2021) and first establishes a theoretical framework of intangible capital affecting firm markups. Accordingly, this study finds that an increase in intangible capital results in an increase in firm markups via the “production efficiency” channel but a decrease in firm markups via the “market-based pricing” channel. We use the data of Chinese manufacturing firms to further empirically study the influence of intangible capital on firm markups and its influencing mechanism. After a series of robustness and endogeneity tests, this research finds that intangible capital is conducive to increasing firm markups. Results of the empirical analysis also reveal that the positive impact of an increase in intangible capital on the markups of Chinese manufacturing firms via the “production efficiency” channel are higher than the negative impact of an increase in intangible capital via the “market-based pricing” channel. Moreover, the impact on the markups of different types of firms are not the same, with significant heterogeneity characteristics. This study provides micro evidence from a large developing country on how intangible capital affects the change in firm markups, thereby providing a new perspective on the economic effects of intangible capital.

We propose a sufficient statistics approach to measuring Ricardian comparative advantage in a quantitative trade model featuring cross-country differences in productivity, factor prices, market size, as well as monopolistic competition, endogenous markups, and firm heterogeneity. The model’s micro-foundations do not necessarily imply that the relevant data for the proposed sufficient statistics must include micro information, but its micro-structure is needed to understand how only macro information can be used instead. Applying the approach to Chinese microdata and cross-country macrodata, we show that imperfect competition with endogenous markups and firm heterogeneity have far-reaching implications for correctly measuring Ricardian comparative advantage.

A significant number of procurements in both public and private sectors have adopted the practice of splitting the award among multiple bidders in an auction, as an alternative to the one-winner-take-all approach. This aims to encourage participation from small firms and reduce dependency on a single supplier. One prominent example is China’s national drug procurement multiple-winner auction, where the drug supply is divided among several winners, increasing in proportion to the number of participants. Given the societal importance of drug prices, it is crucial to properly examine the rationale for using split-award auctions. However, there is limited theoretical and empirical guidance available in the literature. This paper investigates the competitive impact of split-award auctions on key outcomes, such as participation and procurement costs, using both a theoretical framework and empirical evidence. Theoretically, it demonstrates that split-award auctions consistently boost participation but also increase expected procurement costs in almost all instances. The expected procurement cost decreases only if the split-award auction raises participation from 0 to 1 compared to the winner-take-all auction. Empirically, the paper estimates the direction and magnitude of the effects on participation and expected procurement costs using drug procurement data. The findings reveal that split-award auctions moderately increase average participation by 0.85 bidders (17%), but significantly raise the unit expected procurement cost by 4 CNY (38%). Almost half of the overall increase in expected procurement costs stems from reallocating production to more expensive bidders, while the other half results from increased markups charged by bidders in response to this reallocation.

We decompose the difference between a firm’s market and book values into two components: intangible assets that can be created by competing firms through SG&A/R&D expenditures, and the residual denoted as franchise value (FV). The estimated parameters in the model for creating intangible assets by capitalizing R&D/SG&A expenditures vary significantly across industries. Consistent with FV being a measure of economic rents and quasi-rents, ceteris paribus, higher FV firms face fewer product market threats, have higher markups, and their investments are less sensitive to their total Tobin’s Q. In contrast, firms with higher capitalized intangible assets, face higher product market threats.

We identify negative spillovers exerted by large, successful manufacturing plants on other local production facilities in China. A short-lived alliance between the U.S.S.R. and China led to the construction of 150 "Million-Rouble plants" in the 1950s. Our identification strategy exploits the ephemeral geopolitical context and the relative position of allied and enemy airbases to isolate exogenous variation in plant location decisions. We find a boom-and-bust pattern in hosting counties: treated counties are twice as productive as control counties in 1982, but 30% less productive in 2010. The average other establishment in treated counties is unproductive, does not innovate, and charges high markups. We find that (over)specialization limits technological spillovers. This prevents the emergence of new industrial clusters and leads to a flight of entrepreneurs.

Predicted TFP gains under Hsieh and Klenow (2009)’s framework are sensitive to demand elasticities and returns to scale, but simultaneously estimating them is difficult. We solve this problem by developing a framework allowing for an arbitrary distribution of firm-level markups and use microdata to estimate industry-specific production elasticities, within-industry type-specific demand elasticities when types are not observed, and firm-specific distortions. We apply our model to 2005 Chinese firm-level data and find that the predicted Total Factor Productivity (TFP) gains are 44% which is half of the previous findings. While the variation in markups does not affect predicted TFP gains, it lowers the predicted increase in labor income share by one-third, suggesting lower gains to average workers due to heterogeneous markups.