The paper empirically explores how more trade transparency affects market liquidity. The analysis takes advantage of a unique setting in which the Shanghai Stock Exchange offered more trade transparency to market participants subscribing to a new software package. First, the results show that the additional data disclosure increased trading activity, but also increased transactions costs through wider bid–ask spreads. Thus, in contrast to popular policy belief, the paper finds that more transparency need not improve market liquidity. Second, the paper finds a particularly strong immediate liquidity impact accompanied by altered trading behavior, which suggests a significant impact on institutional traders subscribing relatively early. Lastly, since the effective level of market transparency is bound to depend on how many traders are subscribing to the data, the study can empirically establish the functional form between market-wide transparency and liquidity. The relationship is non-monotonic, which can explain the lack of consensus in the existing literature where each empirical study is naturally confined to specific parts of the transparency domain.

For an incompatible patient–donor pair, kidney exchanges often forbid receipt-before-donation (the patient receives a kidney before the donor donates) and donation-before-receipt, causing a double-coincidence-of-wants problem. We study an algorithm, the Unpaired kidney exchange algorithm, which eliminates this problem. In a dynamic matching model, we show that the waiting time of patients under Unpaired is close to optimal and substantially shorter than under widely used algorithms. Using a rich administrative dataset from France, we show that Unpaired achieves a match rate of 63% and an average waiting time of 176 days for transplanted patients. The (infeasible) optimal algorithm is only slightly better (64% and 144 days); widely used algorithms deliver less than 40% match rate and at least 232 days waiting times. We discuss a range of solutions that can address the potential practical incentive challenges of Unpaired. In particular, we extend our analysis to an environment where a deceased donor waitlist can be integrated to improve the performance of algorithms. We show that our theoretical and empirical comparisons continue to hold. Finally, based on these analyses, we propose a practical version of the Unpaired algorithm.