A Fast Literature Search Engine based on top-quality journals, by Dr. Mingze Gao.
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- Please kindly let me know [mingze.gao@mq.edu.au] in case of any errors.
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Results 513 resources
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This paper studies, theoretically and experimentally, the effects of overconfidence and fake news on information aggregation and the quality of democratic choice in a common-interest setting. We theoretically show that overconfidence exacerbates the adverse effects of widespread misinformation (i.e., fake news). We then analyze richer models that allow for partisanship, targeted misinformation intended to sway public opinion, and news signals correlated across voters (due to media ownership concentration or censorship). In our experiment, overconfidence severely undermines information aggregation, suggesting that the effect of overconfidence can be much more pronounced at the collective than at the individual level.
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In the single-IV model, researchers commonly rely on t-ratio-based inference, even though the literature has quantified its potentially severe large-sample distortions. Building on Stock and Yogo (2005), we introduce the tF critical value function, leading to a standard error adjustment that is a smooth function of the first-stage F-statistic. For one-quarter of specifications in 61 AER papers, corrected standard errors are at least 49 and 136 percent larger than conventional 2SLS standard errors at the 5 percent and 1 percent significance levels, respectively. tF confidence intervals have shorter expected length than those of Anderson and Rubin (1949), whenever both are bounded.
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Does variation in how religious festivals are celebrated have economic consequences? We study the economic impacts of the timing of Catholic patron saint day festivals in Mexico. For causal identification, we exploit cross-locality variation in festival dates and in the timing of agricultural seasons. We estimate the impact of "agriculturally coinciding" festivals (those coinciding with peak planting or harvest months) on long-run economic development of localities. Agriculturally coinciding festivals lead to lower household income and worse development outcomes overall. These negative effects are likely due to lower agricultural productivity, which inhibits structural transformation out of agriculture. Agriculturally coinciding festivals may nonetheless persist because they also lead to higher religiosity and social capital.
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Analogous to Stambaugh (1999), this paper derives the small sample bias of estimators in J-horizon predictive regressions, providing a closed-form solution in terms of the sample size, horizon and persistence of the predictive variable. For large J, the bias is linear in JT with a slope that depends on the predictive variable's persistence. The paper offers a number of other useful results, including (i) important extensions to the original Stambaugh (1999) setting, (ii) closed-form bias formulas for popular alternative long-horizon estimators, (iii) out-of-sample analysis with and without bias adjustments, along with new interpretations of out-of-sample statistics, and (iv) a detailed investigation of the bias of the overlapping estimator's standard error based on the methods of Hansen and Hodrick (1980) and Newey and West (1987). The small sample bias adjustments substantially reduce the magnitude of long-horizon estimates of predictability.
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We empirically examine the effects of index investing using predictions derived from a Grossman-Stiglitz framework. An exogenous increase in index investing leads to lower information production as measured by Google searches, EDGAR views, and analyst reports, yet price informativeness remains unchanged. These findings are consistent with an equilibrium in which investors choose to gather private information whenever it is profitable. As index investing increases, there are fewer privately-informed active investors (so overall information production drops), but the mix of investors adjusts until the returns to active investing are unchanged. As a result, passive investing does not undermine price efficiency.
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We model how a cyber attack may be amplified through the U.S. financial system, focusing on the wholesale payments network. We estimate that spillovers of an attack on one of the five most active banks would impair 31% of the network, on average, with some days significantly worse. When other banks respond by liquidity hoarding, forgone payment activity can reach more than 2.5 times daily GDP. A reverse stress test shows attacks on groups of small banks can also impair a significant amount of the network. Interconnectedness through third-party providers and financial market utilities poses additional risks.
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We study how the arrival of macro-news affects the stock market's ability to incorporate the information in firm-level earnings announcements. Existing theories suggest that macro and firm-level earnings news are attention substitutes; macro-news announcements crowd out firm-level attention, causing less efficient processing of firm-level earnings announcements. We find the opposite: the sensitivity of announcement returns to earnings news is 17% stronger, and post-earnings announcement drift 71% weaker, on macro-news days. This suggests a complementary relationship between macro and micro news that is consistent with either investor attention or information transmission channels.
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We use the introduction of a U.S. commercial credit bureau to study when lenders adopt voluntary information sharing technology and the resulting consequences for competition and credit access. Our results suggest that lenders trade off access to new markets against heightened competition for their own borrowers. Lenders that initially do not adopt lose borrowers to competitors that do, which ultimately compels them to adopt and leads to the formation of an information sharing system. Access to credit improves but only for high-quality borrowers in markets with greater lender adoption. We provide the first direct evidence on when financial intermediaries adopt information sharing technologies and how sharing systems form and evolve.
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We document that networks that gain access to political power and use it for patronage appointments also gain control over resource allocation in the private sector. Specifically, following a presidential election in Korea, the president appoints members of his network into important positions in government, and private banks respond by appointing executives from the same network to establish links to the administration. Consequently, firms linked to the network obtain more credit at a lower rate from government and private banks alike, despite higher default rates. Micro-level data on loans and variation in network links for the same firm across lenders over time sharpen the interpretation of our results. In a parsimonious model, we show that efficiency costs are higher when government and private banks are controlled by the same group rather than different groups: in-group firms invest in more unprofitable projects, whereas out-group firms lack funding for highly profitable investments.
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We identify a group of “suspicious” firms that use stock splits, perhaps along with other activities, to artificially inflate their share prices. Following the initiation of suspicious splits, share prices temporarily increase, and subsequently decline below their presplit levels. Using account level data, we find that small retail investors acquire shares in firms initiating suspicious splits, while more sophisticated investors accumulate positions before suspicious split announcements and sell in the postsplit period. We also find that insiders sell large blocks of shares and obtain loans using company stock as collateral around the initiation of suspicious splits.
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Journals
- American Economic Review (115)
- Journal of Finance (69)
- Journal of Financial Economics (202)
- Review of Financial Studies (127)
Topic
- Bond (33)
- CEO (5)
- Mergers and Acquisitions (4)
- Director (3)
- Capital Structure (2)
Resource type
- Journal Article (513)