# Incomplete information `kaal:entity:incomplete-information` **Status.** derived This node is assembled mechanically from the 8 claims that carry the concept tag `incomplete-information`. It is a roster of what the corpus says under this term. It is **not** an adjudicated definition: no single statement here has been ruled canonical, and no first-appearance call has been made. Read the claims and judge for yourself. ## Every claim under this term 8 claims across 5 works, 2004 to 2021. **2004** - [617681-023](https://wulfkaal.github.io/claims/617681-023) [mechanism/argued] *(failure mode)* -- Fear of judicial bias operates through risk premiums: because investors and managers are uncertain how foreign judges will behave and may assume the worst, they price a decision to incorporate in another Member State higher. > Risk premiums charged by actors often reflect both bounded rationality and incomplete information, and managers and investors thus may put a higher price on a decision to incorporate in another Member State. Christian Kirchner, Richard W. Painter, Wulf A. Kaal, Regulatory Competition in EU Corporate Law after Inspire Art Unbundling Delaware's Product for Euro (2004). SSRN: https://ssrn.com/abstract=617681 **2013** - [2267560-005](https://wulfkaal.github.io/claims/2267560-005) [failure/argued] *(failure mode)* -- Rulemaking conducted under conditions of incomplete information and bounded rationality produces suboptimal outcomes that require costly rule revisions, retractions, and additional rulemaking. > Rulemaking under conditions of incomplete information and bounded rationality can lead to suboptimal outcomes that may require rule revision and/or additional rulemaking. Wulf A. Kaal, Evolution of Law Dynamic Regulation in a New Institutional Economics Framework (2013). SSRN: https://ssrn.com/abstract=2267560 - [2267560-007](https://wulfkaal.github.io/claims/2267560-007) [mechanism/argued] -- The feedback effect between different public rulemakers and between private and public rulemakers reduces incomplete information, which in turn enables the rulemaker to modify the next action in the rulemaking process. > The feedback effect increases the availability of relevant information for rulemaking. At the same time, the reduction of incomplete information in the rulemaking process enables the rulemaker to modify the next action in the rulemaking process. Wulf A. Kaal, Evolution of Law Dynamic Regulation in a New Institutional Economics Framework (2013). SSRN: https://ssrn.com/abstract=2267560 - [2273857-018](https://wulfkaal.github.io/claims/2273857-018) [mechanism/argued] -- The shock conditions that trigger calls for rulemaking have typically not been analyzed or absorbed systematically, so rulemaking under those conditions is associated with high levels of incomplete information. > Shock conditions that call for rulemaking often have not been appropriately analyzed and absorbed in a systematic fashion and are, thus, often associated with high levels of incomplete information. Wulf A. Kaal, Dynamic Regulation of the Financial Services Industry (2013). SSRN: https://ssrn.com/abstract=2273857 - [2273857-019](https://wulfkaal.github.io/claims/2273857-019) [mechanism/argued] -- The bounded rationality of public rulemakers aggravates shock conditions during rulemaking, because rulemakers satisfy their own constituencies rather than all affected parties and are therefore more willing to act on incomplete information. > The bounded rationality of public rulemakers—who are satisfying their respective constituencies rather than all affected parties and, therefore, may be more willing to act in an environment of incomplete information—can aggravate shock conditions during the rulemaking process. Wulf A. Kaal, Dynamic Regulation of the Financial Services Industry (2013). SSRN: https://ssrn.com/abstract=2273857 - [2273857-026](https://wulfkaal.github.io/claims/2273857-026) [failure/argued] *(failure mode)* -- The cyclical nature of public rulemaking under incomplete information and bounded rationality is costly and produces suboptimal regulatory outcomes with long-term implications for financial markets and the economy. > The cyclical nature of public rulemaking under conditions of incomplete information and bounded rationality is costly and can produce suboptimal regulatory outcomes, often with long-term implications for financial markets and the economy. Wulf A. Kaal, Dynamic Regulation of the Financial Services Industry (2013). SSRN: https://ssrn.com/abstract=2273857 **2014** - [kaal-2014-dynamicregulationviagove-003](https://wulfkaal.github.io/claims/kaal-2014-dynamicregulationviagove-003) [design/argued] -- Rulemaking in a dynamic framework postpones the enactment of rules until rulemakers hold sufficient relevant and institution specific information, instead of proceeding by trial and error under incomplete information and bounded rationality. > Rather than engaging in suboptimal trial-and-error rulemaking under conditions of incomplete information and bounded rationality, rulemaking in a dynamic framework postpones enacting rules until rulemakers have sufficient relevant and institution-specific information for rulemaking Kaal, Dynamic Regulation via Governmental Contracts (2014) **2021** - [3782203-033](https://wulfkaal.github.io/claims/3782203-033) [mechanism/argued] -- Anonymity increases rather than decreases the value of reputation tokens, because when potential business partners have less knowledge of a counterparty's identity, the number of reputation tokens held becomes the more important signal. > When potential business partners have less knowledge of your identity, the knowledge from the number of reputation tokens you hold becomes more important. Craig Calcaterra, Wulf A. Kaal, A Technical Perspective on Decentralization (2021). SSRN: https://ssrn.com/abstract=3782203 ## Verify Every claim above resolves to a record carrying a verbatim source quote, the sha256 of the source PDF, and a preformatted citation. Nothing here asks to be taken on trust. curl -s https://wulfkaal.github.io/entities/incomplete-information.md | sha256sum **Canonical form.** This markdown file is the canonical hashed representation of this entity node. Its sha256 is the content hash.