# Anticipatory rulemaking `kaal:entity:anticipatory-rulemaking` **Status.** derived This node is assembled mechanically from the 22 claims that carry the concept tag `anticipatory-rulemaking`. 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 22 claims across 4 works, 2014 to 2016. **2014** - [kaal-2014-dynamicregulationviagove-002](https://wulfkaal.github.io/claims/kaal-2014-dynamicregulationviagove-002) [mechanism/argued] -- Anticipatory dynamic elements in regulation reduce the need for costly and suboptimal ex post trial and error experimentation with stable and presumptively optimal rules. > Anticipatory dynamic elements in regulation can help minimize costly and suboptimal ex-post trial-and-error experimentation with stable and presump- tively optimal rules. Kaal, Dynamic Regulation via Governmental Contracts (2014) - [kaal-2014-dynamicregulationviagove-014](https://wulfkaal.github.io/claims/kaal-2014-dynamicregulationviagove-014) [mechanism/argued] -- Feedback effects allow the necessary information to be acquired ex ante and necessary revisions to be anticipated before rules emerge as suboptimal, rather than ex post after failure has become apparent. > Rather than acquiring the necessary information ex-post after rules have emerged as suboptimal, feedback effects help increase the availability of rele- vant information for rulemaking ex-ante and anticipate necessary revisions before rules emerge as suboptimal Kaal, Dynamic Regulation via Governmental Contracts (2014) - [kaal-2014-dynamicregulationviagove-019](https://wulfkaal.github.io/claims/kaal-2014-dynamicregulationviagove-019) [predictive/argued] -- Trial and error rulemaking could become obsolete if dynamic elements in rulemaking processes systematically anticipated future contingencies and the corresponding regulatory needs. > Trial-and-error-rulemaking could become obsolete if dynamic ele- ments in rulemaking processes systematically anticipated future contingencies and corresponding regulatory needs. Kaal, Dynamic Regulation via Governmental Contracts (2014) - [kaal-2014-dynamicregulationviagove-037](https://wulfkaal.github.io/claims/kaal-2014-dynamicregulationviagove-037) [mechanism/argued] -- Tailoring regulatory solutions to identified regulatory necessities through governmental contracts and then observing how those solutions perform over time lets rulemakers anticipate regulatory demands, which is institution specific ex ante experimentation. > Tailor- ing regulatory solutions to ascertainable regulatory necessities via govern- mental contracts and observing how these regulatory solutions function over time in governmental contracts allows rulemakers to anticipate regulatory demands Kaal, Dynamic Regulation via Governmental Contracts (2014) - [kaal-2014-dynamicregulationviagove-039](https://wulfkaal.github.io/claims/kaal-2014-dynamicregulationviagove-039) [mechanism/argued] -- Investigation, self reporting, and preemptive remedial measures enable anticipation of future contingencies for rulemaking, because investigating additional institutions in the same industry lets the government pinpoint the exact need for regulation more precisely. > Investigation, self- reporting, and preemptive remedial measures facilitate anticipation of future contingencies for rulemaking because the government by investigating addi- tional institutions in the same industry can pinpoint more precisely the exact need for regulation. Kaal, Dynamic Regulation via Governmental Contracts (2014) **2016** - [2740477-004](https://wulfkaal.github.io/claims/2740477-004) [definitional/asserted] -- Dynamic regulation is defined as the study of regulatory phenomena in relation to both preceding and succeeding events, using institution specific and decentralized information to generate feedback effects that support anticipatory rulemaking. > The theory of dynamic regulation conceptualizes the study of regulatory phenomena in relation to preceding and succeeding events, using institution-specific and decentralized information to facilitate feedback effects for anticipatory rulemaking. Wulf A. Kaal, Erik P.M. Vermeulen, Venture Capital as Dynamic Regulation of Disruptive Innovation (2016). SSRN: https://ssrn.com/abstract=2740477 - [2740477-014](https://wulfkaal.github.io/claims/2740477-014) [failure/argued] *(failure mode)* -- The current regulatory framework contains no mechanism that succinctly and anticipatorily informs rulemakers of beneficial innovative ideas, which is the specific informational gap the article proposes to fill. > The current regulatory framework lacks a mechanism that succinctly and anticipatorily informs rulemakers of beneficial innovative ideas. Wulf A. Kaal, Erik P.M. Vermeulen, Venture Capital as Dynamic Regulation of Disruptive Innovation (2016). SSRN: https://ssrn.com/abstract=2740477 - [2740477-018](https://wulfkaal.github.io/claims/2740477-018) [condition/argued] *(failure mode)* -- If rulemakers cannot adequately protect their constituents through stable and presumptively optimal rules, then regulatory supplements that facilitate anticipatory rulemaking are justified. > making it increasingly less likely that rulemakers will be able to effectively protect the public via stable and presumptively optimal rules. If rulemakers cannot adequately protect their constituents, regulatory supplements facilitating anticipatory rulemaking may be justified. Wulf A. Kaal, Erik P.M. Vermeulen, Venture Capital as Dynamic Regulation of Disruptive Innovation (2016). SSRN: https://ssrn.com/abstract=2740477 - [2740477-035](https://wulfkaal.github.io/claims/2740477-035) [mechanism/argued] -- Data on venture capital investments lets regulators see where innovation trends are forming and what risks they entail before the disruptive innovation materializes, which is the specific remedy for regulation's reactive timing. > Data on VC investments allows regulators to see where innovation trends exist and what possible risks are entailed before disruptive innovation materializes. Wulf A. Kaal, Erik P.M. Vermeulen, Venture Capital as Dynamic Regulation of Disruptive Innovation (2016). SSRN: https://ssrn.com/abstract=2740477 - [2740477-036](https://wulfkaal.github.io/claims/2740477-036) [design/argued] -- Industry specific venture capital investment data allows regulators to anticipate regulatory needs in the industries carrying the highest levels of disruptive innovation, and the level of disruptive innovation can be quantified by the venture capital dollars flowing into those industries. > For instance, information on industry-specific VC investments allows regulators to anticipate regulatory needs in certain industries that are associated with the highest levels of disruptive innovation. Disruptive innovation may here be quantified with the VC dollar investment in such industries. Wulf A. Kaal, Erik P.M. Vermeulen, Venture Capital as Dynamic Regulation of Disruptive Innovation (2016). SSRN: https://ssrn.com/abstract=2740477 - [2740477-037](https://wulfkaal.github.io/claims/2740477-037) [design/argued] -- By identifying possible contingencies and necessary rule revisions from venture capital investment data ex ante, before disruptive innovation creates problems, regulators could anticipate regulatory needs instead of reacting to them. > By identifying possible contingencies and necessary rule revisions with optimized information from VC investments ex-ante, before disruptive innovation creates problems, regulators could anticipate regulatory needs. Wulf A. Kaal, Erik P.M. Vermeulen, Venture Capital as Dynamic Regulation of Disruptive Innovation (2016). SSRN: https://ssrn.com/abstract=2740477 - [2808132-001](https://wulfkaal.github.io/claims/2808132-001) [normative/argued] -- Regulation is usually reactive because it responds to facts, but the current environment is one of data rather than settled facts; regulation must therefore become proactive and dynamically responsive to data and trends. > Disruptive innovation creates increasing regulatory challenges. The reason for this is simple: Regulation is usually reactive, responding to facts. However, we currently live in a world of data, not facts. Regulation must therefore be proactive and dynamically Wulf A. Kaal, Erik P.M. Vermeulen, How to Regulate Disruptive Innovation - From Facts to Data (2016). SSRN: https://ssrn.com/abstract=2808132 - [2808132-005](https://wulfkaal.github.io/claims/2808132-005) [definitional/asserted] -- Dynamic regulation is defined as conceptualizing regulatory phenomena in relation to both preceding and succeeding events, using institution-specific and decentralized information to generate feedback effects that support anticipatory rulemaking. > The theory of dynamic regulation conceptualizes the study of regulatory phenomena in relation to preceding and succeeding events, using institution-specific and decentralized information to facilitate feedback effects for anticipatory rulemaking.105 Wulf A. Kaal, Erik P.M. Vermeulen, How to Regulate Disruptive Innovation - From Facts to Data (2016). SSRN: https://ssrn.com/abstract=2808132 - [2808132-017](https://wulfkaal.github.io/claims/2808132-017) [failure/argued] *(failure mode)* -- Because facts-based rulemaking does not anticipate the regulatory issues created by innovation, rulemakers may realize far too late, or never, what new regulatory demands a given innovation generates. > facts-based rulemaking did not anticipate regulatory issues created by innovation, rulemakers may not at all or much too late realize what new regulatory demands apply to a given innovation and associated regulatory issue. Wulf A. Kaal, Erik P.M. Vermeulen, How to Regulate Disruptive Innovation - From Facts to Data (2016). SSRN: https://ssrn.com/abstract=2808132 - [2808132-019](https://wulfkaal.github.io/claims/2808132-019) [condition/argued] -- Because rulemakers are increasingly unlikely to be able to protect the public through stable and presumptively optimal rules alone, regulatory supplements that enable anticipatory rulemaking become justified. > rulemakers will be able to effectively protect the public via stable and presumptively optimal rules. If rulemakers cannot adequately protect their constituents, regulatory supplements facilitating anticipatory rulemaking may be justified. Wulf A. Kaal, Erik P.M. Vermeulen, How to Regulate Disruptive Innovation - From Facts to Data (2016). SSRN: https://ssrn.com/abstract=2808132 - [2808132-040](https://wulfkaal.github.io/claims/2808132-040) [predictive/argued] -- Although aggregate venture capital sector data arguably only confirms what media reporting already showed for 2005 to 2015, the venture capital data, especially examined granularly, may provide earlier signals for regulators to identify areas of prospective regulatory need. > only confirms media reporting on innovation trends between 2005 and 2015, the VC data used herein may provide earlier signals for regulators to identify possible areas of regulatory need in the face of increasingly disruptive innovation. Wulf A. Kaal, Erik P.M. Vermeulen, How to Regulate Disruptive Innovation - From Facts to Data (2016). SSRN: https://ssrn.com/abstract=2808132 - [2808132-043](https://wulfkaal.github.io/claims/2808132-043) [mechanism/argued] -- Regulation is mostly reactive and follows business cycles rather than being proactive; data on venture capital investments lets regulators see where innovation trends are heading and what risks they entail before the disruptive innovation actually materializes. > Regulation is mostly reactive, following business cycles, rather than proactive. Data on VC investments allows regulators to see where innovation trends are going and the possible risks they entail before disruptive innovation materializes. Should regulators Wulf A. Kaal, Erik P.M. Vermeulen, How to Regulate Disruptive Innovation - From Facts to Data (2016). SSRN: https://ssrn.com/abstract=2808132 - [2808132-044](https://wulfkaal.github.io/claims/2808132-044) [mechanism/argued] -- Feedback effects from venture capitalists' finance allocations toward innovative products give rulemakers timely, decentralized, industry-specific and entity-specific information that allows them to adapt rules in anticipation of regulatory issues. > anticipatory rulemaking. Through the feedback effects that are facilitated by venture capitalists' finance allocations towards innovative products, rulemakers can obtain timely and decentralized industry- and entity-specific information that allows them to adapt Wulf A. Kaal, Erik P.M. Vermeulen, How to Regulate Disruptive Innovation - From Facts to Data (2016). SSRN: https://ssrn.com/abstract=2808132 - [2808132-047](https://wulfkaal.github.io/claims/2808132-047) [failure/argued] *(failure mode)* -- Even if regulators could obtain the depth of information needed for anticipatory rulemaking, acting on venture capital signals risks wasting scarce regulatory resources, because venture capital funds make many investments that do not succeed and companies still incubating may raise no clear regulatory issues. > anticipatory rulemaking, there may be risk of waste of scarce regulatory resources because VC funds make many investments, not all of which turn out to be successful. Moreover, if companies that received VC financing are still incubating, it may be largely Wulf A. Kaal, Erik P.M. Vermeulen, How to Regulate Disruptive Innovation - From Facts to Data (2016). SSRN: https://ssrn.com/abstract=2808132 - [2808132-048](https://wulfkaal.github.io/claims/2808132-048) [design/argued] -- Regulators should take anticipatory measures only after cross-validation and triangulation, that is, when multiple independent data analyses point unanimously toward a specific demand for regulatory action. > high-quality, decentralized, and real-time information for rulemaking. If and when multiple data analyses together point unanimously in the direction of a certain demand for regulatory action, regulators should take anticipatory measures after cross-validation Wulf A. Kaal, Erik P.M. Vermeulen, How to Regulate Disruptive Innovation - From Facts to Data (2016). SSRN: https://ssrn.com/abstract=2808132 - [2808132-049](https://wulfkaal.github.io/claims/2808132-049) [failure/asserted] *(failure mode)* -- No regulatory processes or data evaluation capabilities currently exist that could carry out the cross-validated analyses and support the anticipatory regulatory action the authors propose. > and triangulation. Currently no regulatory processes and data evaluation exist that could facilitate such analyses and anticipatory regulatory action. Wulf A. Kaal, Erik P.M. Vermeulen, How to Regulate Disruptive Innovation - From Facts to Data (2016). SSRN: https://ssrn.com/abstract=2808132 - [2831040-032](https://wulfkaal.github.io/claims/2831040-032) [design/argued] -- Anticipatory rulemaking in the dynamic framework is accomplished by combining institution specific, decentralized, and timely information with feedback effects, which can occur between public and private rulemakers, between outcomes and institutions, across jurisdictions, and between rules and rulemaking processes. > It relies on the use of institution-specific, decentralized, and timely information5 in combination with feedback effects (Kaal 2014b). Feedback effects can occur in several settings including feedback processes between different public and private rulemakers Wulf A. Kaal, Dynamic Regulation for Innovation (2016). SSRN: https://ssrn.com/abstract=2831040 ## 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/anticipatory-rulemaking.md | sha256sum **Canonical form.** This markdown file is the canonical hashed representation of this entity node. Its sha256 is the content hash.