Knowledge that Transforms

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Central bank balance sheet expansion, through actions like quantitative easing, is run through commercial banks. While this increases liquid central bank reserves held on commercial bank balance sheets, demandable uninsured deposits issued to finance the reserves also increase. Subsequent shrinkage in the central bank balance sheet may entail shrinkage in bank‐held reserves without a commensurate reduction in deposit claims. Furthermore, during episodes of liquidity stress, when many claims on liquidity are called, surplus banks may hoard reserves. As a result, central bank balance sheet expansion may create less additional liquidity than typically thought, and indeed, may increase the probability and severity of episodes of liquidity stress.

We train a machine learning method on a class of informed trades to develop a new measure of informed trading, informed trading intensity (ITI). ITI increases before earnings, mergers and acquisitions, and news announcements, and has implications for return reversal and asset pricing. ITI is effective because it captures nonlinearities and interactions between informed trading, volume, and volatility. This data‐driven approach can shed light on the economics of informed trading, including impatient informed trading, commonality in informed trading, and models of informed trading. Overall, learning from informed trading data can generate an effective informed trading measure.

Using novel data from the pharmaceutical industry, we study product prices and innovation around mergers. Exploiting within‐deal variation in product market consolidation, we show that prices increase more for drugs in consolidating markets than for matched control drugs. Estimates indicate a 2% average price effect that persists for about one year. Price increases expand with acquirer‐target product similarity and are more pronounced within less competitive product markets with fewer players and no generic competition. Examination of trade‐offs reveals these deals generate significant shareholder value. They also spur labeling and other manufacturing‐related innovation, but not the development of new drugs.

The psychology literature documents that individuals derive current utility from their beliefs about future events. We show that, as a result, investors in financial markets choose to disagree about both private information and price information. When objective price informativeness is low, each investor dismisses the private signals of others and ignores price information. In contrast, when prices are sufficiently informative, heterogeneous interpretations arise endogenously: most investors ignore prices, while the rest condition on it. Our analysis demonstrates how observed deviations from rational expectations (e.g., dismissiveness, overconfidence) arise endogenously, interact with each other, and vary with economic conditions.

We combine state minimum wage changes with individual‐level income and credit data to estimate the effect of wage gains on the debt of low‐wage workers. In the three years following a $0.88 minimum wage increase, low‐wage workers experience a $2,712 income increase and a $856 decrease in debt. The entire decline in debt comes from less student loan borrowing among enrolled college students. Credit constraints, buffer‐stock behavior, and other rational channels cannot explain the reduction in student debt. Our results are consistent with students perceiving a utility cost of borrowing student debt arising from mental accounting.