title: "Behavioral Micro-Foundations for the Space Commons: A Policy Toolkit" authors: "Felipe M. Affonso" journal: "Research Policy" year: 2025 doi: "10.2139/ssrn.6575099" citation: "Affonso, Felipe M. (2025), \"Behavioral Micro-Foundations for the Space Commons: A Policy Toolkit,\" Research Policy." > **Disclaimer:** This is a machine-readable conversion of the published paper for use with AI tools. It may contain conversion errors in formatting, tables, or equations. Always verify against the [published version](https://doi.org/10.2139/ssrn.6575099). FELIPE M. AFFONSO Forthcoming, *Research Policy* Felipe M. Affonso (felipe.affonso@okstate.edu) is an Assistant Professor of Marketing, Spears School of Business, Oklahoma State University, Stillwater, OK 74078. Correspondence concerning this article should be addressed to Felipe M. Affonso. [www.felipemaffonso.com](https://www.felipemaffonso.com). **Abstract** Satellite megaconstellations are transforming the space economy, yet the same commercial expansion that connects remote communities and monitors climate change is contaminating observations from the Hubble Space Telescope, increasing collision risks to irreplaceable scientific assets, and overwhelming governance institutions designed for a handful of state actors. The behavioral forces driving this expansion (status competition, prestige signaling, systematic discounting of long-term costs) are precisely the forces that Cold War-era frameworks fail to address. Because these patterns are predictable, they are also designable. This paper develops the Astro-Economic Behavioral (AEB) Framework, which proposes that the psychological forces producing governance failures can be redirected through choice architecture toward sustainable outcomes without binding enforcement. Three theoretical pillars, Narrative Capital, Conspicuous Exploration, and Behavioral Governance, identify how symbolic value, costly signaling, and decision defaults shape space governance outcomes. These pillars inform four policy instruments that operate through existing international regimes, requiring no new treaty authority: sustainable-practice defaults, a reputational index, loss-framed site designations, and time-bounded safety zones. For each instrument, pre-specified quasi-experimental evaluation designs enable evidence-based iteration. The framework contributes to innovation policy by providing behavioral micro-foundations for governance in emerging sectors where rapid technological change outpaces institutional adaptation. **Keywords:** innovation policy; technology governance; space governance; behavioral economics ## 1. Introduction On November 15, 2021, seven astronauts aboard the International Space Station received an urgent warning: seek shelter immediately. A Russian anti-satellite weapons test[^1] had destroyed a defunct Soviet-era satellite, creating over 1,500 fragments hurtling through low Earth orbit at 28,000 kilometers per hour ([NASA, 2021](#ref-nasa2021)). Among those scrambling to their return vehicles were two Russian cosmonauts, endangered by their own nation's military demonstration. Far from an aberration, this incident followed a pattern visible over a decade earlier, when in 2009 the first accidental hypervelocity collision between two intact satellites (Iridium 33 and Kosmos 2251) created over 2,000 trackable debris fragments ([European Space Agency, 2009](#ref-esa2009)). In 2021, close approaches between Starlink satellites and China's Tiangong space station (on July 1 and October 21) prompted a formal notification to the UN Secretary-General in December 2021 citing dangers to astronaut safety and state responsibility under Articles V and VI of the Outer Space Treaty ([United Nations, 2022](#ref-un2022)). The fragments from such events will persist in orbit for decades, threatening crewed missions and scientific assets including the Hubble Space Telescope and the observatories on which our understanding of the universe depends, because an expanding set of space actors driven by status competition continues to operate under institutions that were never designed for this environment. Why would Russia accept such risks to demonstrate a capability that might render the orbital environment unusable for everyone, including Russia itself? The answer lies in behavioral dynamics that conventional policy analysis overlooks: status signaling, prestige competition, and systematic underweighting of long-term collective costs relative to short-term competitive gains. The challenge confronting space governance meets the criteria that Rittel and Webber ([1973](#ref-rittel1973)) established for "wicked problems"[^2] and, following Levin et al. ([2012](#ref-levin2012)), may constitute a "super wicked" problem where time is running out, those causing the problem are those seeking solutions, no central authority exists, and decision-makers systematically discount long-term sustainability. ### 1.1 The Space Economy and Sustainability Challenge The global space economy is undergoing structural transformations driven by accelerating innovation cycles, declining launch costs, and private R&D investment ([BryceTech, 2024](#ref-brycetech2024); [OECD, 2023](#ref-oecd2023newspace); [Space Foundation, 2024](#ref-spacefoundation2024)). The "New Space" paradigm[^3] involves commercialization that alters how space activities are financed and governed ([Bousedra, 2023](#ref-Bousedra_2023); [Denis et al., 2020](#ref-Denis_2020); [Paikowsky, 2017](#ref-Paikowsky_2017)). In addition, participation is expanding well beyond traditional spacefaring states: India's Chandrayaan-3 achieved the first soft landing near the lunar south pole in August 2023 ([Kanu et al., 2024](#ref-kanu2024)), the UAE's Hope orbiter reached Mars in 2021 ([Amiri et al., 2022](#ref-amiri2022)), Japan's SLIM lander demonstrated precision lunar landing in January 2024 ([Sakai et al., 2025](#ref-sakai2025)), and South Korea achieved independent orbital launch capability with its Nuri rocket ([OECD, 2022a](#ref-oecd2022)). Yet even as new entrants multiply, Rementeria ([2022](#ref-rementeria2022)) demonstrates that established power hierarchies persist, creating conditions for status competition between incumbents seeking to maintain dominance and newcomers seeking to signal capability. The pace of expansion is accelerating: orbital launches more than doubled from approximately 114 in 2020 to over 250 in 2024, active satellites quadrupled from approximately 3,400 to over 14,000 in the same period, and a single operator (Starlink) now accounts for approximately 65% of all active satellites. The global space economy reached a record \$613 billion in 2024 ([Space Foundation, 2025](#ref-spacefoundation2025)), and space represents one of the most R&D-intensive sectors globally. Public investment has historically created the technological foundations upon which commercial innovation now builds ([Fleming et al., 2019](#ref-fleming2019); [Jaffe et al., 1998](#ref-jaffe1998)). Recent research documents substantial economic returns from this investment: Kantor and Whalley ([2025](#ref-kantor2025)) find that public R&D during the space race increased manufacturing employment and capital accumulation among contractor firms, while Corrado et al. ([2023](#ref-corrado2023)) estimate aggregate macroeconomic growth effects from space activity. Scientific research depends on access to the same orbital environment that commercial operators are rapidly filling. Borlaff et al. ([2025](#ref-borlaff2025)) demonstrate that satellite megaconstellations will contaminate over 96% of exposures from future space-based telescopes, with the Hubble Space Telescope already experiencing satellite trail contamination in approximately one-third of its images. Kruk et al. ([2023](#ref-kruk2023)) document that 2.7% of Hubble exposures were crossed by satellites between 2018 and 2021, a fraction projected to increase by an order of magnitude as constellations expand. Ground-based observatories face comparable disruption: the Vera C. Rubin Observatory's planned Legacy Survey of Space and Time, designed to catalogue near-Earth asteroids and map dark matter (the invisible mass that holds galaxies together), could see 30% of all images affected by satellite trails. Boley and Byers ([2021](#ref-boley2021)) argue that megaconstellations create multiple simultaneous tragedies of the commons, degrading ground-based astronomy, orbital safety, and Earth's upper atmosphere. Radio astronomy faces a distinct but related threat: Grigg et al. ([2025](#ref-grigg2025)) report that unintended electromagnetic emissions from Starlink satellites have been detected in the 150.8 MHz band formally protected for radio astronomy. Among the research at stake are observations of the "cosmic dark ages," the period before the first stars formed, when the universe was less than a few hundred million years old. These signals can only be detected from radio-quiet environments, and once commercial transmissions saturate the relevant frequencies, the window for this science closes permanently. Beyond scientific research, the space environment underpins economic infrastructure on which billions of people depend. GPS signals coordinate commercial aviation, synchronize financial transactions, and guide precision agriculture. Weather satellites enable forecasting that prevents billions in storm damage annually. Earth observation satellites monitor climate change, verify arms control agreements, and track illegal fishing. A cascading debris event[^4] could damage not only the space industry but critical infrastructure underlying much of modern economic life. Debris-related costs already impose an estimated \$86-103 million annually ([Adilov et al., 2023](#ref-adilov2023)), with assets at risk exceeding \$191 billion ([OECD, 2022b](#ref-oecd2022orbits)). Adilov et al. ([2023](#ref-adilov2023)) introduce the concept of "Economic Kessler Syndrome" to capture how debris accumulation may render orbital operations economically unviable well before physical cascade thresholds are reached, threatening the innovation infrastructure that supports downstream sectors including telecommunications, positioning, and Earth observation. Together, these scientific and economic impacts illustrate that the governance challenge encompasses the preservation of research infrastructure that is, in some cases, irreplaceable, alongside commercial systems on which modern economies depend. ### 1.2 From Innovation Policy Challenge to Behavioral Framework This paper addresses what Robinson and Mazzucato ([2019](#ref-robinson2019)) identify as a fundamental challenge for innovation policy: how to govern domains that are simultaneously critical to technological progress, increasingly commercialized, and exhibiting tragedy-of-the-commons dynamics. Space exemplifies what Marchant et al. ([2011](#ref-marchant2011)) call the "pacing problem": technology advancing faster than governance institutions can adapt, with the consequences of delayed action compounding over orbital timescales. Space sustainability requires governance suited to "polycentric systems"[^5] where no single actor possesses adequate authority for hierarchical enforcement. Standard policy analysis assumes rational actors calculate material costs and benefits, but the incidents documented above reveal behavioral dynamics that this assumption cannot capture. Costly signaling theory ([Fearon, 1997](#ref-fearon1997); [Zahavi, 1975](#ref-zahavi1975)) explains why destructive demonstrations persist despite their collective costs: signals must be expensive to be credible, and the willingness to degrade the shared environment communicates resolve more effectively than benign alternatives. The same logic drives commercial behavior, where first-mover competitive pressures lead operators like SpaceX to prioritize rapid Starlink deployment over coordinated debris mitigation. Addressing these behavioral patterns requires governance that operates within existing frameworks, building on adaptive governance for complex social-ecological systems ([Folke et al., 2005](#ref-folke2005)) and consistent with what Kuhlmann et al. ([2019](#ref-Kuhlmann_2019)) term "tentative governance": provisional interventions explicitly designed for learning under uncertainty. The Astro-Economic Behavioral (AEB) Framework developed in this paper proposes that these governance problems are failures of behavioral design. The rationale is that existing institutions do not account for the psychological forces that drive actors toward unsustainable outcomes. However, this paper argues that the same behavioral patterns causing governance failures (status competition, narrative-driven attention, systematic discounting of future costs) can be redirected through choice architecture (the deliberate design of decision environments) toward sustainable outcomes without binding enforcement. ### 1.3 Contribution The paper offers three contributions to innovation policy scholarship. The framework provides behavioral micro-foundations for understanding why innovation governance fails when it must operate through influence where command is unavailable. The responsible innovation framework of Stilgoe et al. ([2013](#ref-stilgoe2013)) established anticipation, reflexivity, inclusion, and responsiveness as principles, but left underspecified why actors systematically fail to anticipate, reflect, include, and respond. The AEB Framework explains these failures through documented psychological mechanisms: prestige competition, narrative-driven attention, and systematic discounting of future costs. In addition, the framework translates these theoretical insights into four instruments anchored in existing international regimes that operationalize transformative innovation policy goals ([Schot and Steinmueller, 2018](#ref-schot2018)). Each instrument targets a distinct behavioral mechanism (defaults, social proof, loss aversion, reciprocity), operates through existing institutional frameworks requiring no new treaty authority, and generates evaluable outcomes through quasi-experimental designs. The framework also specifies ex ante evaluation protocols that enable learning and evidence-based iteration, addressing the challenge that randomized controlled trials are typically infeasible in international governance contexts. Pre-specified designs for difference-in-differences, event studies, and synthetic control methods provide methodological infrastructure applicable beyond space governance to other emerging technology domains. The paper proceeds as follows. Section 2 maps the governance context, documenting how legal ambiguity interacts with behavioral incentive structures to produce coordination failures. Section 3 describes the integrative conceptual synthesis methodology. Section 4 develops the Astro-Economic Behavioral (AEB) Framework, specifying how narrative salience, costly signaling, and choice architecture shape space governance outcomes. Section 5 translates these insights into four implementable policy instruments, each targeting a distinct behavioral mechanism and operating through established institutional frameworks. Section 6 presents the integrated evaluation framework with quasi-experimental designs. Section 7 addresses anticipated critiques, scope conditions, and implementation pathways. Section 8 examines ethics and legitimacy, and Section 9 concludes. Figure 1 provides a visual overview of the paper's conceptual architecture. **Figure 1. Conceptual Architecture of the Behavioral Governance Framework.** The figure presents a four-tier vertical flowchart. At the top, a coral-accented box labeled "Governance Challenge: Legal ambiguity x Behavioral incentive structures" branches into three drivers: Localized scarcity (material competition), Prestige competition (status signaling), and Geopolitical fragmentation (coalition dynamics). These feed into the second tier, the "Astro-Economic Behavioral Framework," containing three theoretical pillars: Narrative Capital (salience biases target selection), Conspicuous Exploration (costly signaling drives risk), and Behavioral Governance (choice architecture channels behavior). The third tier, "Four Policy Instruments," presents two rows of instrument-mechanism pairs: (1) Voluntary Registry with Defaults, targeting status quo bias; (2) Responsible Space Actor Index, targeting social proof and status; (3) Loss-Framed Site Designation, targeting loss aversion; and (4) Time-Bounded Safety Zones, targeting reciprocity norms. At the bottom, a coral-accented "Evaluation Framework" box lists the quasi-experimental methods: difference-in-differences, event studies, synthetic control, and qualitative comparative analysis. A dashed coral arrow labeled "Adaptive feedback" loops from the evaluation tier back up to the instruments tier, representing evidence-based iteration. ## 2. The Governance Context: Legal Ambiguity and Behavioral Incentives This section maps the institutional landscape in which behavioral governance must operate: the legal foundations inherited from the Cold War era, the behavioral incentive structures that drive coordination failures, and the achievements of existing governance mechanisms that any new framework must complement. ### 2.1 Legal Foundations and Coordination Gaps The 1967 Outer Space Treaty (OST) establishes foundational principles of international space law, with Article II prohibiting national appropriation while Article IX requires "due regard" for other states' interests and mandates consultations regarding "potentially harmful interference" ([United Nations, 1967](#ref-un1967)). These provisions left ambiguities that contemporary developments have rendered problematic. Several ambiguities in this foundational framework have become particularly consequential as commercial activities expand. The question of whether resource extraction constitutes "appropriation" remains unresolved: the United States and Luxembourg have enacted domestic legislation recognizing property rights in extracted resources ([Luxembourg, 2017](#ref-luxembourg2017); [U.S. Congress, 2015](#ref-uscongress2015)), but no international consensus has emerged ([Jakhu et al., 2017](#ref-jakhu2017)). The Artemis Accords[^6] propose operational "safety zones" around lunar installations, but critics argue these risk circumventing the non-appropriation principle ([Martin and Freeland, 2021](#ref-freeland2021)), while proponents cite Article IX's "due regard" obligation as justification ([Hobe, 2020](#ref-hobe2020)). Perhaps most pressing, no mechanism exists to enforce debris mitigation despite its recognized urgency; the COPUOS[^7] Long-Term Sustainability Guidelines, COSPAR[^8] protocols, ISO 24113 standards (the international technical standard for debris mitigation), and recommendations from the Inter-Agency Space Debris Coordination Committee (IADC, comprising 13 national space agencies) all lack binding authority and systematic compliance assessment ([ISO, 2023](#ref-iso2023); [United Nations, 2019](#ref-un2019)). The Starlink-Tiangong close approaches discussed in Section 1 illustrate the consequences of this institutional fragmentation. China's formal complaint ([United Nations, 2022](#ref-un2022)) highlights the absence of binding separation standards, incomplete data-sharing arrangements, and the lack of any dispute-resolution mechanism for "due regard" claims. This episode, occurring between an Artemis Accords signatory (United States) and non-signatory (China), exemplifies how institutional ambiguity creates opportunities for conflict while providing no pathway toward authoritative resolution. ### 2.2 Behavioral Incentive Structures Legal ambiguity interacts with behavioral dynamics to create systematic governance risks at three levels that purely rational-actor models fail to capture. At the material level, localized scarcity concentrates competition despite space's seemingly unlimited resources. Near-term value concentrates in specific locations: geosynchronous orbital slots (approximately 1,800 usable positions; ITU ([2020](#ref-itu2020))), lunar farside radio-quiet zones essential for radio astronomy, polar ice deposits critical for sustained operations, and sites targeted for space resource extraction. The emerging space mining sector, with six nations having enacted resource-rights legislation ([Luxembourg, 2017](#ref-luxembourg2017); [U.S. Congress, 2015](#ref-uscongress2015)) and commercial ventures pursuing asteroid mineral recovery and lunar helium-3 harvesting, adds a new dimension to the commons problem by creating potential property-rights conflicts in a domain where the relationship between resource extraction and the Outer Space Treaty's non-appropriation principle remains unresolved. These sites exhibit rival consumption (one actor's use diminishes another's access), first-mover advantages, and interference potential without clear property rights, creating classic commons problems where actors rush to establish presence before governance crystallizes ([Libecap, 1989](#ref-libecap1989); [Ostrom, 1990](#ref-ostrom1990)). At the psychological level, prestige competition operates independently of material returns. Space achievements signal technological capability and national power to multiple audiences: geopolitical rivals, domestic publics, commercial investors, and the scientific community. This creates zero-sum status competition that material gains alone cannot satisfy. The ASAT testing pattern illustrates this dynamic starkly. China's 2007 test generated more than 3,500 trackable debris fragments ([Weeden and Samson, 2022](#ref-weeden2022)); the United States' 2008 intercept of USA-193, though conducted at lower altitude to limit persistent debris, demonstrated similar capabilities; and Russia's 2021 test (described in the opening of this paper) endangered its own cosmonauts aboard the International Space Station ([NASA, 2021](#ref-nasa2021)). These tests imposed substantial long-term collective costs, including costs to the testing states themselves, in exchange for short-term signaling benefits. Section 4.2 develops the costly signaling framework ([Fearon, 1997](#ref-fearon1997); [Zahavi, 1975](#ref-zahavi1975)) explaining this pattern: the willingness to degrade the shared orbital environment serves as a credible capability signal precisely because less destructive alternatives would be less costly and therefore less informative. At the political level, geopolitical fragmentation produces competing governance architectures that impede global coordination. The Artemis Accords and the International Lunar Research Station represent parallel frameworks with limited cross-participation, a pattern consistent with what evolutionary psychologists term parochial altruism: stronger cooperation within coalitions than across coalition boundaries ([Choi and Bowles, 2007](#ref-choi2007)). The resulting governance architecture, featuring parallel plurilateral arrangements, creates coordination challenges as each framework develops standards and procedures independently, while the relationship between these plurilateral initiatives and the COPUOS multilateral process remains a subject of ongoing negotiation. These three dynamics create behavioral patterns that rational-actor models treating preferences as exogenous cannot adequately capture. Localized scarcity drives resource competition, psychological scarcity drives status competition, and geopolitical fragmentation drives coalition formation, with each dynamic reinforcing the others in ways that standard policy analysis overlooks. Critically, these governance failures affect not only commercial operators but also the scientific research that depends on the space environment. Megaconstellation deployments driven by commercial signaling dynamics are already degrading the observational conditions on which astronomy and fundamental physics depend ([Boley and Byers, 2021](#ref-boley2021); [Borlaff et al., 2025](#ref-borlaff2025)), while collision risks increasingly threaten irreplaceable research platforms. Before developing the framework that addresses these patterns, the following subsection acknowledges the substantial achievements of existing governance mechanisms, which any new framework must complement rather than replace. ### 2.3 Acknowledging Current System Achievements Existing governance mechanisms have achieved substantial success. The International Space Station, sustained for over two decades across five space agencies despite severe geopolitical tensions including Russia's 2022 invasion of Ukraine, demonstrates that international space cooperation can survive political stress when institutional frameworks provide adequate structure ([Pace, 2020](#ref-pace2023)). India's missions, including the Mars Orbiter Mission (2014) and Chandrayaan program, have achieved significant milestones at a fraction of traditional costs ([Rajagopalan and Stroikos, 2024](#ref-rajagopalan2024)), expanding the range of actors contributing to space science. At the voluntary level, the IADC's guidelines show increasing compliance among responsible operators, and the Space Data Association facilitates conjunction[^9] data sharing among commercial actors. Industry self-regulation has produced autonomous collision avoidance capabilities exceeding regulatory requirements, while the World Economic Forum's Space Sustainability Rating demonstrates that mission-level sustainability scoring can operate in this domain ([World Economic Forum, 2026](#ref-wef2026)). Emerging active debris removal (ADR) technologies demonstrate that remediation of the orbital environment is becoming technically feasible ([Mark and Kamath, 2019](#ref-mark2019adr)), with recent missions such as ESA's ClearSpace-1 program and Astroscale's ELSA-d demonstration advancing from concept to operational testing, and ADR raises new governance questions regarding authorization to remove another state's objects and liability allocation. These achievements notwithstanding, the compliance data reveal precisely the governance gap that behavioral instruments are designed to address. Only 52% of large payloads (\>1000 kg) meet the 25-year disposal requirement, and compliance with the stricter 5-year standard ranges from 5-55% ([ESA, 2023](#ref-esa2023)), demonstrating that voluntary guidelines without behavioral architecture fail to achieve adequate compliance even among actors who accept those guidelines in principle. Voluntary arrangements exclude military satellites, and the ISS model may not translate to governance involving hundreds of commercial actors with diverse time horizons. The AEB Framework aims to complement these existing mechanisms with additional behavioral levers. ## 3. Methodology: Integrative Conceptual Synthesis Having documented the governance context and the behavioral dynamics that drive coordination failures, this section describes how the paper develops its response. The paper employs an integrative conceptual synthesis methodology, combining design science principles with systematic theory development to address an emerging governance challenge ([Jaakkola, 2020](#ref-jaakkola2020); [Van Aken, 2004](#ref-vanaken2004)). Following MacInnis ([2011](#ref-macinnis2011)), the contribution combines "envisioning," conceptualizing a novel governance approach for an emerging policy domain, with "explicating" the mechanisms through which behavioral interventions address space sustainability. This methodological approach is appropriate for emerging domains where empirical data remain scarce and anticipatory governance requires theoretical groundwork prior to implementation ([Guston, 2014](#ref-guston2014)). The synthesis proceeds through four sequential stages. The first stage diagnoses governance failures and behavioral drivers in space innovation systems, drawing on documented incidents, legal ambiguities, and existing policy regimes to identify patterns that current frameworks fail to address. The second synthesizes insights from three distinct literatures (behavioral economics and psychology, international relations and game theory, and commons governance), extracting design principles relevant to the space domain. These principles inform the third stage: developing implementable policy instruments, each specified in terms of the behavioral mechanisms it engages and the conditions under which effects would be expected to manifest. The final stage develops ex ante evaluation protocols that would enable empirical assessment as instruments are piloted and refined. This approach aligns with design-science research traditions that emphasize artifact construction and evaluation design when full-scale empirical implementation is not yet feasible ([Hevner et al., 2004](#ref-Hevner_2004); [Peffers et al., 2007](#ref-Peffers_2007)). The resulting policy instruments constitute what Van Aken ([2004](#ref-vanaken2004)) terms "technological rules," that is, propositions of the form "if you want to achieve outcome Y in situation X, then perform action A," whose validity is ultimately established through pragmatic testing. This methodological approach suits the space governance domain particularly well because the governance innovations are anticipatory, designed to address coordination failures before they become entrenched. The rapid evolution of the space industry, with megaconstellations emerging as a significant phenomenon only within the past five years, means that historical data cannot reliably inform governance approaches for fundamentally novel activities. Space governance presents a domain where existing legal frameworks are increasingly contested, behavioral economics has not previously been applied, and the unique characteristics of orbital resources (non-excludability, rival consumption, international scope) require domain-specific theoretical development ([Whetten, 1989](#ref-whetten1989)). Several strategies address the methodological challenges inherent in conceptual contributions. Following Jaakkola ([2020](#ref-jaakkola2020)), each theoretical claim draws on established literatures, cites meta-analytic evidence where available (particularly for behavioral intervention effect sizes), and specifies falsifiable predictions enabling empirical assessment as implementation proceeds. The pre-specified evaluation designs ensure that the framework generates testable hypotheses amenable to empirical assessment. ## 4. The Astro-Economic Behavioral (AEB) Framework The governance context documented above reveals a repeating pattern: legal ambiguity creates space for behavioral dynamics to drive outcomes that purely rational-actor models cannot predict. The AEB Framework addresses this pattern through three questions (see the middle tier of Figure 1). *Where* does competition concentrate? Narrative Capital explains how symbolic value accumulates on specific celestial targets, predicting which sites will face the most intense competitive pressure. *Why* do actors accept risks that material cost-benefit analysis cannot justify? Conspicuous Exploration applies costly signaling theory to explain how space activities function as credibility signals whose value depends on their costliness. *How* can governance redirect these forces? Behavioral Governance specifies choice architecture instruments that channel status competition and narrative-driven attention toward sustainable outcomes without binding enforcement. ### 4.1 Narrative Capital and Target Selection Celestial targets accumulate what the framework terms *Narrative Capital*: symbolic value derived from cultural associations, historical resonance, and narrative significance that biases resource allocation beyond what material expected returns would predict. This concept extends Bourdieu ([1986](#ref-bourdieu1986))'s notion of symbolic capital to the space domain, where targets like the lunar south pole, Mars, and metallic asteroids carry cultural weight disproportionate to their near-term economic value. The underlying mechanism draws on the Narrative Policy Framework (NPF), which demonstrates through extensive empirical research that policy salience derives substantially from narrative structures (characters, plots, moral framings, and emotional resonance) beyond what objective risk magnitudes or expected value calculations would predict ([Jones and McBeth, 2010](#ref-jones2010); [Shanahan et al., 2018](#ref-shanahan2018)). Narratives spread through social learning biases that cultural evolution scholars have documented, including prestige bias (preferentially copying high-status individuals), content bias (preferentially retaining emotionally resonant information), and conformity bias (preferentially adopting prevalent beliefs) ([Henrich, 2015](#ref-henrich2015)). Consider asteroid 16 Psyche, frequently valued in media coverage at approximately \$10 quintillion based on its metallic composition (e.g., [Elkins-Tanton et al., 2022](#ref-elkinstanton2022)). This valuation is economically meaningless because transportation costs alone would exceed any conceivable market price, and introducing such quantities of metal to Earth markets would collapse the prices on which the valuation depends. Yet the figure persists in media coverage and investor presentations because it serves narrative functions: anchoring prestige claims, attracting attention, and justifying exploration budgets. Commercial interest stems substantially from narrative-driven attention independent of realistic economic calculations. The theoretical claim underlying the Narrative Capital concept is that a bias emerges when narrative salience spikes: high-narrative-capital targets receive disproportionate resources relative to their expected material returns. This bias operates through budget allocation (funding flows toward narratively compelling missions), timeline prioritization (high-NCI targets face accelerated schedules), and risk-tolerance adjustments (actors accept higher risks for narratively significant achievements). For governance purposes, this mechanism predicts which celestial locations will face concentrated competitive pressure before that pressure materializes. Narrative Capital could be operationalized through a composite Narrative Capital Index (NCI) with three measurable components: media salience (coverage frequency weighted by outlet authority and reach), prestige co-mentions (association with high-status concepts such as "historic," "unprecedented," or "first" in media and scientific discourse), and funding-return mismatch (the ratio of allocated resources to projected economic returns, with higher ratios indicating narrative motivations beyond material ones). Such an index would generate testable predictions: when NCI crosses specified thresholds, theory predicts accelerated mission timelines, reduced risk-mitigation investment, and intensified competitive pressure. These patterns could be assessed empirically as data accumulate, providing an ex ante governance tool that identifies sites requiring enhanced protection before competitive dynamics make such protection politically costly (Online Appendix OA2 specifies the data sources that would support such operationalization). High-NCI targets create governance challenges precisely because they combine scientific or strategic importance with competitive dynamics that discourage caution. Sites of greatest scientific value (Mars special regions potentially harboring life, lunar permanently-shadowed region ice deposits recording billions of years of solar system history) often carry the highest Narrative Capital, attracting the most aggressive competitive behavior. COSPAR planetary protection policy ([COSPAR, 2020](#ref-cospar2020)) recognizes contamination risks at such sites but lacks enforcement mechanisms. The NCI enables preemptive governance: identifying high-NCI sites allows policymakers to implement enhanced protections before missions arrive, when resistance to protective measures is lower than it would be after actors have committed resources. This follows the precedent of the Antarctic Treaty System, which established environmental protections before extensive commercial activity made such restrictions politically costly ([Bastmeijer and Roura, 2004](#ref-bastmeijer2004)). ### 4.2 Conspicuous Exploration as Costly Signaling Space activities function as what the framework terms *Conspicuous Exploration*: high-cost, high-visibility missions that credibly communicate technological capability, organizational competence, and geopolitical resolve precisely because they are expensive, risky, and publicly observable. The concept applies costly signaling theory ([Spence, 1973](#ref-spence1973); [Zahavi, 1975](#ref-zahavi1975)) to explain a pattern that material cost-benefit analysis cannot: why actors undertake space activities whose costs demonstrably exceed their material returns. Signals must be costly to be credible because cheap signals could be mimicked by actors lacking the quality being signaled and would therefore convey no reliable information. Veblen ([1899](#ref-veblen1899)) applied this logic to conspicuous consumption, demonstrating how wasteful expenditure signals wealth precisely because only the wealthy can afford such waste. More recent work demonstrates that status motives amplify costly pro-environmental behaviors when those behaviors are publicly visible ([Griskevicius et al., 2010](#ref-griskevicius2010)), while related research shows that romantic motives can similarly trigger conspicuous prosocial signaling ([Griskevicius et al., 2007](#ref-griskevicius2007)). Conspicuous Exploration operates through signaling to three distinct audiences: geopolitical rivals (demonstrating technological and organizational capacity that transfers to military applications), commercial investors (proving operational competence that predicts future success), and domestic publics (legitimizing expenditures through national pride and symbolic achievements). The signal value operates independently of material mission returns because the very costliness of the undertaking communicates capability more credibly than efficient achievement would, explaining why missions that achieve their objectives efficiently generate weaker signals than those demonstrating capacity for ambitious undertakings. The Cold War Space Race exemplifies this dynamic in its purest form. McDougall ([1985](#ref-mcdougall1985)) documents how Project Apollo served geopolitical signaling objectives alongside its scientific mission. The program's enormous scale reflected signaling imperatives that scientific goals alone would not have justified, because crewed lunar missions demonstrated complex systems integration capabilities that robotic alternatives could not signal with equal credibility. The investment beyond what scientific objectives required was not incidental but constitutive of the signal's value, as Fearon ([1997](#ref-fearon1997)) would predict from the costly signaling framework. The same signaling logic explains contemporary ASAT tests. As discussed in Section 2.2, these debris-generating demonstrations impose substantial long-term collective costs in exchange for short-term signaling benefits. Debris-generating tests credibly signal resolve precisely because cleaner alternatives would be less costly and therefore less credible. A state conducting a debris-generating ASAT test demonstrates not only the technical capability to destroy satellites but also the political willingness to accept international opprobrium and environmental consequences, a combination difficult to counterfeit and therefore valuable as a signal precisely because of its costliness. Private-sector conspicuous exploration manifests in innovation strategy and commercial positioning. Startup launch attempts, even those with low objective success probability, signal risk tolerance and capital access to investors. A public launch attempt functions as a sunk-cost credential demonstrating commitment and capability. This creates rush dynamics central to R&D management: companies prioritize visible technological milestones (launches, demonstrations, deployments) over optimization work that occurs invisibly. First-mover advantages make aggressive technology deployment individually rational for each firm even when collectively risky for the innovation ecosystem as a whole. Large-scale megaconstellation deployment illustrates this tension. SpaceX's rapid Starlink deployment, alongside planned constellations from Amazon's Project Kuiper and existing systems such as OneWeb ([Osoro and Oughton, 2021](#ref-ogutu2021)), has transformed the orbital environment faster than governance frameworks have adapted ([Foust, 2022](#ref-foust2023); [Palmroth et al., 2021](#ref-palmroth2021)). From a costly-signaling perspective, large-scale orbital deployment demonstrates capability and market commitment. The competitive advantage of rapid deployment may outweigh coordination costs for individual operators, even when unmitigated externalities impose costs that no single operator fully internalizes. As documented in Section 1.1, these externalities extend beyond orbital congestion to scientific research, contaminating astronomical observations from both ground-based and space-based telescopes, creating a collective action problem driven by signaling dynamics that rational-actor models overlook. The debris cascade risks modeled by Kessler and Cour-Palais ([1978](#ref-kessler1978)) represent the endpoint of this collective action problem. IADC guidelines and ISO 24113 ([ISO, 2023](#ref-iso2023)) recommend post-mission disposal practices, yet compliance remains voluntary and imperfect (Section 2.3). Operators face misaligned incentives: individual missions capture signaling benefits while externalizing debris risks to all orbital users. The framework explains persistent non-compliance through costly signaling dynamics: actors prioritizing status and competitive positioning discount long-term collective costs relative to short-term signaling gains. ### 4.3 Behavioral Governance Principles The behavioral forces identified by Narrative Capital and Conspicuous Exploration can be redirected toward sustainable outcomes through choice architecture, even without the binding enforcement authority that space governance lacks. Meta-analytic evidence documents meaningful effect sizes (Cohen's d, where values above 0.20 are considered small and above 0.50 medium) for behavioral interventions: d = 0.43 overall ([Mertens et al., 2022](#ref-mertens2022pnas)) and notably stronger effects for default-based instruments (d = 0.68 per Jachimowicz et al. ([2019](#ref-jachimowicz2019))), which constitute the primary mechanism in the proposed instruments. The framework employs defaults where this evidence is strongest, while relying on competence-building interventions where technical expertise is required (such as training planetary protection officers and conjunction screening tools). This approach aligns with tentative governance of emerging technologies ([Budde and Konrad, 2019](#ref-Budde_2019); [Kuhlmann et al., 2019](#ref-Kuhlmann_2019)), which combines provisional, revisable elements with clear procedural commitments. The framework also engages adaptive governance scholarship ([Folke et al., 2005](#ref-folke2005)), which emphasizes learning through feedback in governing complex social-ecological systems, and resonates with emerging proposals for a dedicated Sustainable Development Goal for space ([Losch et al., 2024](#ref-Losch_2024)) and the UN Space2030 Agenda ([United Nations, 2021](#ref-un2021space2030)) that recognize the need for governance frameworks keeping pace with space activity expansion. Accordingly, each instrument includes built-in feedback mechanisms enabling recalibration as experience accumulates. Ostrom ([2010](#ref-ostrom2010))'s work on polycentric governance demonstrates that systems with multiple overlapping governance centers can manage commons problems when hierarchical coordination fails. Space governance exhibits polycentricity by necessity, with authority fragmented across national agencies, international bodies, industry associations, and operators. The proposed instruments work within this reality, linking existing regimes with behavioral levers that operate without requiring politically unattainable comprehensive coordination. Three design principles guide the specific instruments developed in the following section. Each instrument builds on existing international regimes (COPUOS, COSPAR, the International Telecommunication Union \[ITU\], ISO/IADC), leveraging established legitimacy and avoiding the transaction costs of creating new institutional structures. Each enlists insurers and commercial actors for market-based enforcement, aligning private incentives with sustainability objectives where possible. And each employs transparency and reciprocity mechanisms to create reputational pressure, exploiting social proof (the tendency of actors to conform to observed behavior of peers) and status concerns that the AEB Framework identifies as powerful behavioral drivers. These principles ensure that the instruments can be implemented within current institutional capacity while addressing the behavioral dynamics documented above. Table 1 summarizes how the design principles led to specific instruments. **Table 1. Framework Integration: From Theoretical Pillars to Policy Instruments** Theoretical Pillar Core Mechanism Governance Implication Linked Instruments **Behavioral Governance** Defaults, loss framing, and social proof shape choices ([Kahneman and Tversky, 1979](#ref-kahneman1979); [Thaler and Sunstein, 2008](#ref-thaler2008)) Choice architecture can steer behavior without formal enforcement Instrument 1 (Registry Defaults): Status quo bias promotes compliance; All instruments: Transparency mechanisms activate social proof **Conspicuous Exploration** Costly signaling incentivizes visible achievements over sustainability ([Fearon, 1997](#ref-fearon1997); [Veblen, 1899](#ref-veblen1899)) Status competition generates debris externalities requiring coordination mechanisms Instrument 2 (Reputational Index): Channel status-seeking toward compliance; Instrument 4 (Safety Zones): Reciprocal commitments enable status gain through cooperation **Narrative Capital** High-NCI targets attract accelerated timelines and reduced caution ([Bourdieu, 1986](#ref-bourdieu1986); [Henrich, 2015](#ref-henrich2015); [Jones and McBeth, 2010](#ref-jones2010)) Preemptive identification of competition-prone sites enables early protection Instrument 3 (Loss-Framed Site Designation): Loss-framed designation triggers protective norms before resource commitment *Note:* Each pillar informs multiple instruments, and instruments combine mechanisms for complementary effects following policy mix principles ([Rogge and Reichardt, 2016](#ref-Rogge_2016)). *Instrument Selection Rationale.* Several alternatives were considered but not included: cap-and-trade systems and orbital-use fees (no binding allocation authority exists, though economic modeling suggests substantial welfare gains from such fees; Rao et al. ([2020](#ref-rao2020)); OECD ([2022b](#ref-oecd2022orbits))), mandatory liability insurance (moral hazard concerns; Adilov et al. ([2023](#ref-adilov2023))), and technology mandates (premature standardization under the Collingridge dilemma, where governance must act before technological trajectories are fully understood; Collingridge ([1980](#ref-collingridge1980)); ESA ([2023](#ref-esa2023))). By contrast, the four instruments were selected because each (1) targets a distinct behavioral mechanism, (2) addresses a different governance domain, (3) operates through existing frameworks without new treaty authority, and (4) generates evaluable outcomes through quasi-experimental designs. This combination provides complementary coverage while remaining implementable. The framework has important limitations. Behavioral interventions cannot unilaterally restrain deliberate military competition, because where states engage in hard geopolitical conflict, deterrence dynamics and power-based bargaining determine outcomes regardless of choice architecture. The framework's domain of applicability is the broad middle ground of commercial missions, scientific cooperation, and government activities where competitive pressures create sustainability risks but where actors remain responsive to reputational concerns and economic incentives. By reducing friction for cooperation and increasing reputational costs for defection within this domain, behavioral interventions can shift equilibria toward sustainable practices, complementing enforcement-based approaches with mechanisms that operate where formal authority cannot reach. ## 5. Policy Toolkit: Four Implementable Instruments The AEB Framework identifies the behavioral forces driving governance failures; this section translates those theoretical insights into four policy instruments, each targeting a distinct mechanism (see the lower tiers of Figure 1). For each instrument, the following sections specify the behavioral mechanism it engages, describe a potential implementation pathway anchored in existing international regimes, provide a concrete operational illustration, and identify the quasi-experimental design for evaluation. Where specific design parameters lack precise precedent, they represent proposed starting points for empirical calibration, with the evaluation framework enabling iterative refinement as evidence accumulates. Table 2 through Table 4 summarize the instrument parameters, proposed site designations, and evaluation protocols, respectively. The Online Appendix provides extended detail on each instrument, including expected effect sizes grounded in meta-analytic evidence (Online Appendix OA1), data infrastructure and baseline statistics (Online Appendix OA2), full evaluation protocols with statistical specifications (Online Appendix OA3-OA6), institutional precedents informing each instrument's design (Online Appendix OA7), and a phased implementation pathway (Online Appendix, "Potential Implementation Pathways"). ### 5.1 Instrument 1: Voluntary Registry with Sustainable-Practice Defaults Status quo bias, the tendency to disproportionately prefer the current or pre-selected option, shapes compliance when default options are visible and easy to accept ([Johnson and Goldstein, 2003](#ref-johnson2003); [Madrian and Shea, 2001](#ref-madrian2001); [Samuelson and Zeckhauser, 1988](#ref-samuelson1988)). The psychological mechanisms underlying default effects include inertia (effort required to deviate from defaults), implied endorsement (defaults signal recommended behavior), and loss aversion (deviating from defaults frames alternatives as losses relative to the reference point). Transparency strengthens default effects by linking opt-outs to reputational exposure, increasing the perceived social cost of deviation from established norms ([Sunstein, 2014](#ref-sunstein2014)). One potential implementation would build on the existing Article VIII registration framework and the United Nations Register of Objects Launched into Outer Space, administered by the United Nations Office for Outer Space Affairs (UNOOSA) ([United Nations Office for Outer Space Affairs, 2025](#ref-unoosa_register2025)). Such a registry could include pre-selected defaults aligned with established best-practice standards, including COPUOS Long-Term Sustainability Guidelines and relevant national policies, with operators able to opt out from specific defaults by providing written justification recorded in a publicly accessible log ([The White House, 2018](#ref-whitehouse2018spd3); [United Nations, 2019](#ref-un2019)). Table 2 summarizes the proposed default settings, drawn from existing international standards to ensure legitimacy and technical appropriateness. **Table 2. Registry Default Options and Standards (Expanded)** Practice Domain Default Requirements Source Standard Precedent/Justification **Debris Mitigation** Post-mission disposal within 25 years; passivation; collision-avoidance screening; design for demise ISO 24113:2023 / IADC Guidelines Meta-analysis shows d=0.68 for default effects ([Jachimowicz et al., 2019](#ref-jachimowicz2019)) **Planetary Protection** Bioburden limits; special-region avoidance; contamination monitoring for Category III+ missions COSPAR Categories III-V Antarctic Treaty precedent for preemptive environmental protection **Spectrum Discipline** For lunar farside operations, compliance with ITU-R RA.479 transmission restrictions; coordination filing 7+ years before activation ITU-R Recommendation RA.479 ITU advance filing requirements for GEO slots **Data Sharing** Space Situational Awareness (SSA) data contribution to multilateral tracking systems; conjunction warning responsiveness COPUOS LTS Guidelines Space Data Association voluntary precedent **Transparency** Public mission registration 3+ years before launch; trajectory and operational parameter disclosure Article VIII OST / COPUOS UN Register of Objects Launched into Outer Space *Note.* Passivation refers to depleting a spacecraft's residual energy sources (fuel, batteries, pressurized vessels) after mission completion to prevent accidental explosions that generate debris. Bioburden is the quantity of viable microorganisms on a spacecraft, controlled to prevent biological contamination of celestial bodies. The behavioral mechanism relies on status quo bias to make sustainable practices the path of least resistance. Operators who comply simply accept defaults, while operators who deviate must actively justify their choices, creating both cognitive friction and reputational exposure. The public opt-out log enables monitoring by civil society, insurers, and other operators, thereby activating social proof dynamics where visible compliance by leading operators pressures others toward conformity. To illustrate how this works in practice, consider a commercial operator planning a lunar communications relay mission. During the licensing process, national authorities would direct the operator to UNOOSA's registry portal, where a registration form presents pre-selected compliance commitments: debris mitigation protocols, data sharing agreements, and planetary protection standards. The operator reviews each commitment. Finding them acceptable, the operator submits without changes, and the defaults become binding commitments documented in the public registry. Alternatively, if the operator wishes to decline data sharing due to proprietary concerns, the operator must provide written justification ("competitive sensitivity of orbital parameters; will share aggregated statistics quarterly"). This opt-out appears in the public log, visible to insurers adjusting premiums, investors assessing ESG profiles, and competitors benchmarking compliance. Over time, as major operators join and accept defaults, the registry creates social proof that sustainable practices are industry standard. Evaluation employs difference-in-differences methodology exploiting staggered adoption, measuring disposal compliance, conjunction behavior, planetary protection deviations, and insurance premiums at one, three, and five years post-registration (detailed protocol in Online Appendix Section OA3). ### 5.2 Instrument 2: Responsible Space Actor Reputational Index Public rankings shape investment decisions, contracting outcomes, and talent flows when reputational stakes are high, a pattern documented extensively in corporate reputation research ([Fombrun and Shanley, 1990](#ref-fombrun1990)) and behavioral economics ([Cialdini, 2001](#ref-cialdini2001)). Visibility creates social proof effects where highly-ranked actors attract resources while poorly-ranked actors face constraints, generating compliance incentives independent of formal enforcement. The Space Sustainability Rating demonstrates that mission-level scoring can operate in this domain ([World Economic Forum, 2026](#ref-wef2026)); an operator-level index aggregating compliance behavior across missions would extend this logic to create stronger reputational incentives. A Responsible Space Actor Reputational Index could be administered by a multi-stakeholder body (potentially convened by the Space Safety Coalition with UNOOSA participation) ensuring independence from individual national or commercial interests. Such an index could publish periodic scores based on four categories: debris compliance (disposal success, passivation, collision avoidance responsiveness), spectrum discipline (coordination compliance, interference incidents), planetary protection (COSPAR requirement adherence, waiver patterns), and transparency (voluntary disclosure, space situational awareness \[SSA\] data sharing, conjunction response time). Scoring could use publicly available records supplemented by verified operator disclosures, with methodology published transparently and subject to independent audit. The behavioral mechanism leverages social proof (highly-rated actors set compliance norms), status competition (operators compete for ranking positions), and economic incentives (ratings affect insurance pricing, investment, and procurement decisions). The combination of visibility and consequential outcomes creates stronger compliance pressure than any single mechanism alone. In practical operation, consider an operator receiving notification that its quarterly score has dropped from 78 to 65 following a conjunction incident where the operator failed to respond promptly to collision warnings. The score change appears in the public index; industry media covers the downgrade. Within days, the operator's insurance broker contacts them regarding premium implications for the upcoming renewal cycle. A venture capital firm considering follow-on investment requests an explanation. The operator's management, motivated by these tangible consequences, implements improved conjunction response protocols and demonstrates the improvements to the rating body. At the next quarterly update, the score recovers. The mechanism works not because the rating body has enforcement authority, but because the rating makes compliance visible in ways that matter to actors the operator depends upon. Evaluation employs event study methodology examining firm responses to quarterly releases, comparing operators with score changes to identify rating effects on funding, insurance, procurement, and media sentiment (detailed protocol in Online Appendix Section OA4). ### 5.3 Instrument 3: Loss-Framed Designation of Sites of Extraordinary Scientific Importance Prospect theory demonstrates that loss frames carry substantially greater psychological weight than equivalent gain frames, with losses typically weighted approximately 1.5-2.5 times more heavily than gains of the same magnitude ([Kahneman and Tversky, 1979](#ref-kahneman1979); [Tversky and Kahneman, 1992](#ref-tversky1992)). Systematic reviews of environmental messaging find that loss-framed appeals generate stronger pro-environmental behavioral responses than gain-framed alternatives, particularly for behavioral intentions and actual behavior ([Homar and Cvelbar, 2021](#ref-homar2021)). Framing shapes not only individual decisions but also policy acceptance and institutional design ([Tversky and Kahneman, 1981](#ref-tversky1981)). A multilateral working group (potentially including COPUOS, COSPAR, ITU Radiocommunication Sector, and IAU participation) could pre-designate a limited set of sites as having "extraordinary scientific importance," building on existing scientific protection frameworks including ITU radio quiet zones and COSPAR special regions for Mars and ocean worlds ([COSPAR, 2020](#ref-cospar2020); [ITU-R, 2022](#ref-itur2022)). Effective designation would emphasize irreversibility, that is, the permanent foreclosure of scientific opportunities, framed in concrete terms that activate loss aversion. Table 3 specifies five initial site categories with their scientific rationale and proposed loss-framing language, drawn from existing protection frameworks. **Table 3. Proposed Initial Site Designations (Expanded)** Site Category Specific Examples Scientific Rationale Loss Framing Language Precedent **Lunar Farside Radio-Quiet Zones** ITU-R RA.479 protected regions; Daedalus Crater Uniquely radio-silent environment enabling observations of cosmic dawn, dark ages impossible anywhere on Earth or in cis-lunar space "Irreversible loss of humanity's only radio-silent observatory, with observations impossible to recover once transmissions begin" ITU radio astronomy protection zones **Mars Special Regions** Recurring Slope Lineae; subsurface aquifers; Jezero Crater Environments where terrestrial contamination could permanently foreclose answering astrobiology's central question "Forever preventing discovery of whether life exists beyond Earth, the most consequential scientific question humans can ask" COSPAR Category IV/V protections **Lunar PSR Ice Deposits** Shackleton Crater; Cabeus Crater (LCROSS impact site) Volatile deposits recording 4 billion years of solar system history, destroyed by thermal disturbance from operations "Destroying the only preserved record of early solar system conditions, a library that took billions of years to accumulate" Antarctic ice core protection protocols **Apollo/Luna Heritage Sites** Tranquility Base; Luna 2 impact site Cultural heritage and scientific calibration baselines documenting early lunar exploration "Erasing humanity's first footsteps beyond Earth, cultural heritage belonging to all humanity" UNESCO World Heritage precedents **Lunar Lava Tubes** Marius Hills; Mare Tranquillitatis pits Pristine geological records and potential astrobiology sites; subsurface environments shielded from radiation "Contaminating sealed environments before their scientific potential can be assessed" Cave protection regimes (terrestrial) The designation could employ a traffic-light system scaling review intensity to scientific risk, where green status indicates standard procedures are adequate, yellow status requires enhanced review, and red status creates a presumption against activity absent compelling justification and independent scientific review. Public communications would emphasize irreversibility and time sensitivity through accessible visualizations and scientific narratives, activating loss aversion among publics, policymakers, and operators. The behavioral mechanism combines loss aversion (framing degradation as irreversible loss) with social proof (designated status signals that protective behavior is normatively expected) and identity appeals (linking protection to humanity's collective long-term interests). To illustrate the practical operation, consider a commercial operator planning a communications relay satellite in lunar orbit. During mission design, the operator would receive notification that proposed orbital parameters could create radio interference with a designated heritage site: the Farside radio-quiet zone. The operator consults the public designation registry, which describes the zone not as "scientifically important" but as "irreplaceable for observations of the cosmic dark ages, a window to the universe's first billion years that exists nowhere else and, once closed by interference, cannot be reopened." Facing this loss-framed description, the operator has options. Adjusting orbital parameters to avoid interference imposes modest engineering costs but avoids reputational risk. Proceeding despite the designation is legally permissible but invites public criticism, investor concerns about ESG alignment, and enhanced regulatory scrutiny from national licensing authorities who factor heritage site impacts into their decisions. Most operators, facing this choice architecture, adjust their plans because defending the degradation of an irreplaceable scientific resource would impose reputational costs exceeding the engineering adjustments required. Evaluation employs synthetic control methodology, comparing each designated site to counterfactuals constructed from non-designated comparable sites, tracking interference incidents, waiver requests, and preservation outcomes over extended observation periods (detailed protocol in Online Appendix Section OA5). ### 5.4 Instrument 4: Time-Bounded Safety Zones with Transparency Guardrails Reciprocity norms support cooperation when observability is high and when commitments are mutual, patterns extensively documented in experimental and field research ([Axelrod, 1984](#ref-axelrod1984); [Ostrom, 2010](#ref-ostrom2010)). Sunset clauses (mandatory expiration dates requiring active renewal) reduce resistance to coordination agreements by limiting time horizons, addressing concerns about permanent constraints while enabling cooperation over defined periods ([Ranchordás, 2015](#ref-ranchordas2015)). The combination of limited duration and reciprocal commitment lowers barriers to agreement while creating pathways for renewal based on demonstrated benefits. States declaring safety zones under Artemis Accords or bilateral arrangements could anchor declarations in COPUOS notification to link plurilateral arrangements to multilateral frameworks. Drawing on established international law precedents, five design principles merit consideration. Purpose limitation would tie zones to specific operational risks with engineering justification, adapting the concept of operational safety zones from maritime law (Article 60 of UNCLOS) while incorporating design features that address the well-known limitations of that regime, including weak enforcement, flag-state jurisdiction problems, and the near-impossibility of amendment ([Vaangal, 2022](#ref-vaangal2022)). Specifically, the proposed guardrails add mandatory sunset clauses, transparency requirements, and reciprocal obligations that UNCLOS lacks. Time bounds, following Antarctic Treaty and WTO safeguard precedents, would cap duration with mandatory renewal demonstrating continued necessity. Geographic scope limitation, drawing on the "minimum necessary" principle from environmental law, would constrain zones to operationally necessary areas. Transparency, extending ITU advance coordination procedures, would involve filing declarations with UNOOSA before activation. And reciprocal deconfliction would involve data sharing and mutual recognition of equivalent zones declared under comparable standards. The behavioral mechanism combines reciprocity (mutual commitments are easier to accept than unilateral constraints), transparency (public filing enables monitoring and accountability), and temporal framing (limited duration reduces resistance while creating precedents for renewal). The guardrails distinguish operational coordination from territorial claims, providing assurance to both participants and non-participants about the nature of the commitment. To illustrate the operational logic, consider a scenario where the United States plans a crewed lunar surface mission to the Shackleton Crater rim. In advance of the mission, NASA would file a safety zone declaration with UNOOSA specifying purpose (protecting astronaut safety during surface operations), limited duration, geographic scope justified by engineering analysis of operational requirements, and data-sharing commitments. Another state planning its own mission to a nearby location could review the declaration. Finding it consistent with transparency principles, that state would file its own comparable declaration and share tracking data as reciprocity would suggest. The missions would proceed without conflict, each state having assurance that the other's zone serves operational coordination distinct from territorial appropriation. If a declaration were to appear inconsistent with these principles, claiming territory far larger than operationally justified or lacking sunset provisions, civil society monitors could flag the discrepancy, potentially triggering scrutiny from the COPUOS Legal Subcommittee and reputational consequences. Evaluation employs structured content analysis and Qualitative Comparative Analysis (QCA), tracking guardrail compliance, scope creep, conflict episodes, and reciprocity patterns (detailed protocol in Online Appendix Section OA6). ## 6. Evaluation Framework and Research Design Having specified the four instruments and their behavioral mechanisms, this section develops the evaluation infrastructure needed to assess whether these instruments achieve their intended effects, completing the adaptive feedback loop shown in Figure 1. ### 6.1 Integrated Evaluation Approach The framework integrates evaluation protocols across all instruments, prioritizing rigorous quasi-experimental designs where feasible. Randomized controlled trials (RCTs) are infeasible in international space governance given few actors and ethical constraints on withholding beneficial mechanisms. The alternatives specified here, difference-in-differences (comparing outcomes before and after adoption across adopting and non-adopting groups), event studies (measuring outcomes in a narrow window around a specific policy change to isolate its causal effect), synthetic control (constructing a weighted comparison unit to estimate what would have happened absent intervention), and qualitative comparative analysis (QCA), represent the most rigorous available approaches ([Abadie, 2021](#ref-abadie2021); [Callaway and Sant'Anna, 2021](#ref-callaway2021); [Ragin, 2008](#ref-ragin2008)). **Table 4. Evaluation Framework Summary (Expanded)** Intervention Primary Outcomes Identification Strategy Key Data Sources Timeline Expected Effect Size **Voluntary Registry** Disposal compliance, conjunction behavior, insurance premiums Difference-in-differences with staggered adoption (Callaway & Sant'Anna estimator) Space-Track CDMs, UNOOSA filings, insurer reports Multi-year follow-up (duration informed by ISO 24113 disposal timelines) d ≈ 0.30-0.50, attenuated from meta-analytic benchmark for active-choice context (Online Appendix OA1) **Reputational Index** Funding rounds, insurance premiums, contract awards, media sentiment Event study around periodic releases with pre-trend diagnostics Crunchbase/PitchBook, procurement databases, media corpora Short-term windows around releases Effect sizes informed by corporate reputation literature ([Fombrun and Shanley, 1990](#ref-fombrun1990)) **Site Designation** Interference incidents, waiver requests, planning changes, access preservation Synthetic control with matched sites and permutation inference ITU filings, COSPAR records, mission announcements Long-term horizon (matching mission planning cycles) Depends on site characteristics **Safety Zones** Compliance with guardrails, scope creep, conflicts, legal compatibility Content analysis and QCA audit with inter-rater reliability UNOOSA filings, COPUOS records, satellite imagery Ongoing monitoring with periodic comprehensive review Qualitative assessment ### 6.2 Outcome Metrics The evaluation framework identifies six measurable outcome categories. Debris compliance metrics include post-mission disposal success rates, passivation completion, and time-to-disposal relative to operational lifetime. Collision risk is measured through conjunction data message frequency per mission-year normalized by orbital density, close approach distances, and collision avoidance maneuver frequency. Planetary protection indicators encompass COSPAR waiver request frequency, documented bioburden exceedances, and special region approach incidents. Spectrum discipline is tracked through ITU coordination compliance, documented interference incidents, and radio quiet zone violations. Economic indicators capture insurance premium differentials between compliant and non-compliant operators (controlling for mission characteristics), investment flows by operator rating category, and procurement outcomes. Finally, geopolitical cooperation is assessed through data-sharing participation rates, conflict incidents, and reciprocity patterns in zone recognition. ## 7. Addressing Anticipated Critiques The framework developed above raises several questions regarding generalizability, scope conditions, legal compatibility, robustness to geopolitical competition, and practical implementation. This section begins by articulating the paper's broader contributions to innovation policy scholarship, then addresses five categories of anticipated critique, concluding with a discussion of implementation pathways and the barriers that must be overcome. ### 7.1 Contribution to Innovation Policy and Technology Governance This paper makes three contributions to innovation policy scholarship beyond its application to space governance. First, the framework provides behavioral foundations for responsible innovation by endogenizing the preferences that standard innovation economics treats as exogenous. Where Stilgoe et al. ([2013](#ref-stilgoe2013)) identified the governance principles that responsible innovation should achieve, the AEB Framework specifies why those goals prove elusive: prestige-seeking from evolved cognitive architecture ([Choi and Bowles, 2007](#ref-choi2007); [Griskevicius et al., 2010](#ref-griskevicius2010)), narrative-shaped attention allocation ([Henrich, 2015](#ref-henrich2015); [Jones and McBeth, 2010](#ref-jones2010)), and context-dependent decision-making through status quo bias ([Samuelson and Zeckhauser, 1988](#ref-samuelson1988); [Sunstein, 2014](#ref-sunstein2014)) generate predictable failures of anticipation and responsiveness. This diagnostic precision suggests how choice architecture can channel the same psychological forces toward sustainable outcomes. Second, it operationalizes transformative innovation policy by showing how behavioral governance can complement traditional instruments when binding regulation proves infeasible. Schot and Steinmueller ([2018](#ref-schot2018)) called for innovation policy addressing societal challenges including collective action problems and commons dilemmas, and Mazzucato ([2018](#ref-mazzucato2018)) argued that mission-oriented policy requires governance frameworks capable of steering innovation toward socially desirable outcomes. Space sustainability exemplifies such challenges: the "pacing problem" ([Marchant et al., 2011](#ref-marchant2011)) means that governance must be designed anticipatorily ([Guston, 2014](#ref-guston2014)) because the uncoordinated expansion of commercial activities threatens both the innovation infrastructure supporting downstream sectors and the scientific research platforms (space telescopes, radio observatories, planetary science missions) on which fundamental discovery depends ([Borlaff et al., 2025](#ref-borlaff2025)). The framework addresses the implementation gap between transformative goals and available policy tools. Third, this article contributes pre-specified evaluation infrastructure to a domain where such infrastructure remains underdeveloped. Innovation policy scholarship has emphasized the importance of rigorous evaluation ([Cunningham et al., 2016](#ref-cunningham2016)), yet evaluation frameworks for anticipatory governance in emerging sectors remain sparse. The quasi-experimental designs specified here (difference-in-differences, event studies, synthetic control, qualitative comparative analysis) enable evidence-based iteration where randomized trials are infeasible, providing methodological infrastructure applicable to innovation policy evaluation beyond space. ### 7.2 Scope Conditions for Behavioral Interventions Recent meta-analyses have moderated enthusiasm about behavioral intervention effectiveness, with Maier et al. ([2022](#ref-maier2022)) arguing that effect size estimates drop substantially after adjusting for publication bias, and Loewenstein and Chater ([2017](#ref-loewenstein2017)) cautioning that choice architecture addresses symptoms while structural causes persist. The framework addresses these concerns by targeting default-based interventions to compliance decisions where meta-analytic evidence is strongest (Section 4.3), and by combining behavioral mechanisms with market incentives to achieve policy-relevant magnitudes. Insurance premium adjustments for compliance recognition ([Jin and Vasserman, 2021](#ref-jin2021)), funding access conditioned on ratings, and procurement preferences amplify behavioral effects beyond what choice architecture alone could deliver. The framework's built-in evaluation designs enable assessment of whether these instruments achieve their intended effects. ### 7.3 Legal Compatibility of Safety Zones Whether safety zones proposed in the Artemis Accords comply with OST Article II's non-appropriation principle remains debated. Scholars disagree on whether exclusive-use zones functionally constitute appropriation ([Jakhu et al., 2017](#ref-jakhu2017); [Martin and Freeland, 2021](#ref-freeland2021)) or whether Article IX's "due regard" provision permits operational separation ([Hobe, 2020](#ref-hobe2020); [Sundahl, 2013](#ref-sundahl2013)). UNCLOS maritime safety zones, while providing a conceptual precedent, have been subject to substantial criticism regarding enforcement failures, flag-state jurisdiction problems, and the effective impossibility of treaty amendment ([Vaangal, 2022](#ref-vaangal2022)). The framework's proposed safety zones are explicitly designed to avoid these pitfalls: sunset clauses prevent permanent territorial claims, transparency requirements enable monitoring by non-participants, and reciprocal obligations create mutual accountability absent from the UNCLOS regime. The Antarctic Treaty, whose preemptive environmental protections succeeded precisely because they preceded commercial exploitation ([Bastmeijer and Roura, 2004](#ref-bastmeijer2004)), provides a more apt precedent than UNCLOS for the approach advocated here. The framework's contribution is institutional design minimizing abuse risk while enabling coordination. The five guardrails (purpose limitation, time bounds, geographic scope, transparency, reciprocity) distinguish operational coordination from territorial claims through monitorable criteria. The evaluation framework explicitly tracks scope creep, documenting any expansion beyond operational justification. ### 7.4 Reputational Mechanisms Under Geopolitical Competition The framework would be expected to produce heterogeneous effects across actor types (see Online Appendix Table OA5 for expected responsiveness patterns by operator type). States with independent media and competitive electoral accountability face stronger domestic reputational incentives, while states with more centralized governance structures may face weaker domestic but potentially strong international reputational pressures, as Sheehan ([2013](#ref-sheehan2013)) documents for China's space program, where international prestige has been a primary policy driver. Multiple enforcement channels create additional incentives beyond domestic reputation alone, because insurance premiums, investment access, procurement decisions, and technical reciprocity in SSA data sharing all respond to demonstrated responsibility regardless of governance structure. Moreover, coalition strategies can achieve improvements without universal participation, as behavioral interventions facilitate cooperative equilibria among willing participants while creating competitive pressure where responsible actors capture reputational and economic benefits. Behavioral interventions cannot, however, compel states engaged in hard geopolitical competition, and where military activities dominate, deterrence dynamics will determine outcomes. The framework's contribution addresses the broad middle ground of commercial and scientific activities where cooperation benefits all actors but where competitive pressures create sustainability risks that traditional regulatory approaches cannot reach. ### 7.5 Limitations Regarding Technological Uncertainty The Collingridge ([1980](#ref-collingridge1980)) dilemma applies directly to space governance, where intervention is easiest early when understanding of consequences remains limited, yet most needed later when technological trajectories are entrenched and difficult to alter. Space governance faces this acutely, exemplifying the "pacing problem" identified in Section 1.2. The framework addresses uncertainty through several design features (see Online Appendix for detailed methodology). Built-in provisionality includes sunset clauses and mandatory review periods, and as Ranchordás ([2015](#ref-ranchordas2015)) argue, experimental regulations balance innovation with governance needs. Pre-specified evaluation designs generate evidence enabling iterative adjustment, aligning with experimentalist governance principles ([Sabel and Zeitlin, 2012](#ref-sabel2012)). The underlying behavioral principles (status quo bias, loss aversion, reciprocity) remain stable across technological generations, providing robustness over context-specific optimization ([Marchau et al., 2019](#ref-marchau2019)). Following Migaud et al. ([2021](#ref-migaud2021)), the instruments include feedback mechanisms enabling governance to evolve alongside industry maturation, although even adaptive mechanisms may fail to anticipate disruptive innovations, and the transition from behavioral "soft" governance to binding "hard" rules remains underspecified, a limitation future research could address. ### 7.6 Implementation Pathways and Barriers The framework must confront the practical question of how voluntary governance instruments gain adoption in a domain characterized by sovereignty concerns, divergent interests, and no central enforcement authority. Recent experience with space governance initiatives offers both encouraging precedents and sobering lessons about the barriers involved. The most relevant adoption model is the Artemis Accords, which grew from eight signatories in October 2020 to over sixty by early 2026. The Accords were structured as bilateral agreements between the United States and each signatory rather than as a multilateral treaty ([Deplano, 2021](#ref-deplano2021)), a design choice that enabled rapid expansion by avoiding the consensus requirements that slow multilateral negotiations. As NASA Administrator Jim Bridenstine acknowledged at the time of the Accords' launch, pursuing the same objectives through COPUOS "would have taken too long" ([National Aeronautics and Space Administration, 2020](#ref-nasa2020artemis)). The core incentive for participation was access to collaborative opportunities within the Artemis lunar program, creating a tangible benefit tied to signing. However, the Accords also illustrate a fundamental limitation: Russia and China remain outside the framework, and the resulting governance fragmentation between the Artemis Accords and the International Lunar Research Station reproduces rather than resolves the coordination challenge. The World Economic Forum's Space Sustainability Rating (SSR) provides a second precedent, operating through voluntary assessment rather than state-level diplomacy ([Rathnasabapathy et al., 2025](#ref-rathnasabapathy2025)). Developed by a consortium including ESA, MIT Media Lab, and BryceTech, and operated as a nonprofit by the EPFL Space Center, the SSR assigns bronze, silver, gold, or platinum ratings to individual missions based on six sustainability modules. Beta testers have included SpaceX, Planet, OneWeb, Airbus, and Astroscale, and Eutelsat Group earned a platinum rating in June 2024. The SSR model demonstrates that market-facing sustainability assessments can attract participation from major operators when designed as positive credentials analogous to LEED certification in green building, rather than as punitive compliance mechanisms. These precedents suggest that the proposed instruments would face several identifiable barriers. The absence of enforcement mechanisms means that compliance is guided by cost-benefit assessment rather than legal obligation, and where compliance costs are high relative to non-compliance costs, adoption will be incomplete. ESA's Space Environment Report documents that even the improving compliance rates with existing voluntary guidelines (approximately 80-90% for rocket body disposal, but substantially lower for payload disposal by mass) still result in net growth of the orbital population, indicating that voluntary measures alone may prove insufficient. Regulatory arbitrage presents a further challenge: operators can register in jurisdictions with weaker oversight requirements, analogous to the "flags of convenience" problem that has undermined maritime governance under UNCLOS. The fragmentation among major spacefaring powers means that no voluntary initiative currently includes all significant actors, and geopolitical competition between the Artemis and ILRS frameworks may impede universal adoption. Overcoming these barriers likely requires a coalition-of-the-willing strategy rather than universal participation from the outset. The proposed instruments are designed to create competitive advantages for early adopters through insurance premium differentiation, preferential procurement, and reputational benefits that make non-participation costly over time. National licensing authorities can amplify adoption by incorporating registry standards into domestic launch authorization requirements, as the U.S. Federal Communications Commission did when it adopted a five-year post-mission disposal rule in September 2022 ([Federal Communications Commission, 2022](#ref-fcc2022)). The COPUOS Working Group on the Long-Term Sustainability of Outer Space Activities, which produced twenty-one consensus guidelines through four expert groups over eight years (2010-2018) ([Martinez, 2021](#ref-martinez2021)), demonstrates that multilateral expert deliberation on space governance is feasible, although time-consuming. Expert road-testing of the specific instruments proposed here, through dedicated COPUOS working groups, the recently established Action Team on Lunar Activities, or academic-industry partnerships, represents a natural and necessary next step that this paper's framework is designed to inform rather than replace. ## 8. Ethics and Legitimacy of Behavioral Instruments in Global Governance International governance operates through institutional legitimacy in the absence of direct democratic authorization, making transparency and contestability central design requirements for behavioral instruments. Because choice architecture can obscure policy choices if implemented opaquely ([Loewenstein and Chater, 2017](#ref-loewenstein2017)), several safeguards merit consideration. Ex-ante transparency would involve publishing all defaults, scoring rules, and criteria before implementation, and drawing registry defaults from established international standards (ISO, COSPAR, ITU-R) grounds legitimacy in prior multilateral consensus. Autonomy preservation ensures that all interventions preserve operator choice through voluntary participation. The registry permits opt-outs with stated justification, site designations employ graduated guidance that stops short of outright prohibition, and safety zones include sunset clauses ensuring periodic reassessment. Contestability and independent audit provide accountability mechanisms compensating for the absence of democratic authorization. Design features such as appeals windows for ratings, peer review for site designations, and pre-specified evaluation protocols would help ensure that behavioral instruments remain subject to scrutiny and revision. Together, these safeguards address the requirement that behavioral instruments operating in international contexts must maintain legitimacy through procedural openness even when formal democratic accountability is absent. ## 9. Conclusion Space governance confronts a fundamental challenge because Cold War institutions cannot manage contemporary multi-actor expansion driven by both commercial ambition and scientific exploration, and traditional analysis assuming rational optimization misses behavioral patterns that create predictable governance failures. The Astro-Economic Behavioral (AEB) Framework addresses this through behavioral micro-foundations, modeling how narrative salience biases target selection (Narrative Capital), costly signaling drives high-risk activities (Conspicuous Exploration), and choice architecture channels these forces toward sustainable outcomes (Behavioral Governance). These mechanisms generate testable predictions distinguishing AEB from rational-actor models. The framework specifies four instruments anchored in existing regimes. Registry defaults, a reputational index, loss-framed designations, and time-bounded safety zones require no new treaties and leverage behavioral mechanisms where meta-analytic evidence supports effectiveness. Pre-specified quasi-experimental evaluation designs enable evidence-based iteration where RCTs are infeasible. The framework has important limitations: it cannot restrain deliberate military competition, reputational mechanisms work heterogeneously across actor types, and polycentric governance lacks binding enforcement. These constraints require complementary approaches, but the framework's contribution is making responsible behavior easier and more attractive for actors motivated by scientific discovery and commercial success, reducing friction for cooperation and increasing reputational costs for defection to shift equilibria toward sustainable practices. A phased approach would enable learning (the Online Appendix specifies a three-phase implementation pathway from foundation building through pilot programs to site designations and safety zones), with evaluation and evidence-based refinement allowing the framework to evolve while opening research agendas for behavioral scientists, policy scholars, and legal analysts. The window for preventive governance is narrowing. Satellite megaconstellations are already degrading astronomical observations from both ground and space ([Borlaff et al., 2025](#ref-borlaff2025); [Kruk et al., 2023](#ref-kruk2023)), unintended radio emissions threaten frequency bands protected for scientific use, and escalating debris densities increase collision risks to irreplaceable research assets. Acting now with behavioral insights, rigorous evaluation, and adaptive iteration offers the best prospect for preserving space as an environment for both scientific discovery and sustainable commercial activity. ## Data Availability Statement No new data were created or analyzed in this study. The framework provides designs for future data collection and evaluation. **Funding Statement** This research did not receive specific funding from public, commercial, or not-for-profit sources. **Competing Interests** The authors declare no competing interests. ## Appendix: Glossary of Key Terms Term Definition Low Earth Orbit (LEO) Orbital region from approximately 160 to 2,000 km altitude, hosting the majority of commercial satellites and the International Space Station Geostationary Orbit (GEO) Circular orbit at 35,786 km altitude where satellites appear stationary relative to Earth's surface, critical for telecommunications and weather observation Space Debris Non-functional spacecraft, spent rocket stages, and fragments from collisions or deterioration that remain in orbit, posing collision risks to operational assets Kessler Syndrome A theoretical cascade scenario in which debris density reaches a point where collisions generate more debris than natural decay removes, potentially rendering certain orbital regions unusable for generations Conjunction A predicted close approach between two space objects, requiring assessment and potentially avoidance maneuvers Megaconstellation Large satellite systems comprising hundreds or thousands of coordinated satellites in low Earth orbit, such as SpaceX's Starlink, Amazon's Project Kuiper, and OneWeb Passivation Depleting a spacecraft's residual energy sources (fuel, batteries, pressurized vessels) after mission completion to prevent accidental explosions that generate debris Bioburden The quantity of viable microorganisms on a spacecraft, controlled to prevent biological contamination of celestial bodies during exploration missions Active Debris Removal (ADR) Technologies and missions designed to physically remove existing debris from orbit, such as ESA's ClearSpace-1 and Astroscale's ELSA-d Outer Space Treaty (OST) The 1967 treaty forming the foundation of international space law, establishing principles including non-appropriation of celestial bodies and "due regard" for other states' interests Artemis Accords A set of bilateral agreements initiated by the United States in 2020 establishing principles for cooperative lunar exploration, signed by over 60 nations as of early 2026 COPUOS United Nations Committee on the Peaceful Uses of Outer Space, the primary multilateral forum for developing space governance norms COSPAR Committee on Space Research, the scientific body that establishes planetary protection categories and guidelines IADC Inter-Agency Space Debris Coordination Committee, comprising 13 national space agencies, which develops consensus guidelines for debris mitigation ITU International Telecommunication Union, the UN agency that coordinates global radio spectrum allocation and satellite orbital positions UNOOSA United Nations Office for Outer Space Affairs, which administers the UN Register of Objects Launched into Outer Space and supports COPUOS ISO 24113 The international technical standard specifying debris mitigation requirements for spacecraft design and operations SSA Space Situational Awareness, the tracking and monitoring of objects in orbit to predict conjunctions and manage collision risk ## References Abadie, A., 2021. 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[^2]: "Wicked problems" describes challenges where the problem definition itself is contested, solutions cannot be tested before implementation, and stakeholders hold fundamentally different views about success. [^3]: "New Space" refers to the shift from government-dominated space programs to commercial and entrepreneurial space activities, characterized by private investment, rapid iteration, and cost reduction through reusable launch vehicles and mass-produced satellites. [^4]: NASA scientist Donald Kessler modeled the "Kessler Syndrome" in 1978: a scenario where debris density triggers a cascading chain reaction, potentially rendering entire orbital regions unusable for generations. [^5]: Polycentric governance describes systems where multiple overlapping centers of authority govern the same domain, each with limited jurisdiction. Ostrom ([2010](#ref-ostrom2010)) demonstrated that such systems can effectively manage commons resources when designed with appropriate feedback mechanisms. [^6]: The Artemis Accords, initiated by the United States in 2020, establish principles for cooperative lunar exploration through bilateral agreements ([NASA, 2026](#ref-nasa2026)). They remain controversial because they were developed outside the COPUOS multilateral process and because China and Russia have declined to participate, instead pursuing the International Lunar Research Station as an alternative framework. Section 7.6 discusses their adoption trajectory in detail. [^7]: The United Nations Committee on the Peaceful Uses of Outer Space (COPUOS), established in 1959, is the primary multilateral forum for developing international space governance norms and guidelines. [^8]: The Committee on Space Research (COSPAR), an interdisciplinary scientific body, establishes planetary protection categories and guidelines to prevent biological contamination of celestial bodies. [^9]: A conjunction is a predicted close approach between two objects in orbit, requiring assessment of collision risk and potentially an avoidance maneuver by one or both operators. # Online Appendix This appendix provides detailed operationalization of the behavioral governance framework developed in the main text. For each of the four instruments, the following sections specify the theoretical mechanisms, design parameters, expected effect sizes grounded in the behavioral economics literature, and quasi-experimental evaluation protocols. The appendix serves two purposes: to provide sufficient detail for implementation by governance bodies, and to establish falsifiable predictions enabling the framework's empirical validation. **Table of Contents** - Potential Implementation Pathways - OA1. Theoretical Foundations and Expected Effect Sizes - OA2. Data Infrastructure - OA3. Instrument 1: Default-Based Voluntary Registry - OA4. Instrument 2: Responsible Space Actor Reputational Index - OA5. Instrument 3: Loss-Framed Site Designation - OA6. Instrument 4: Reciprocal Safety Zone Commitments - OA7. Existing System References and Institutional Precedents ## Potential Implementation Pathways This section outlines potential pathways through which the behavioral governance framework could be implemented, drawing on precedents from existing multilateral bodies (COPUOS, COSPAR) without requiring creation of new institutions. *Phase 1: Foundation Building.* An initial phase would establish institutional relationships and data infrastructure without requiring consensus on binding commitments. A working group within COPUOS Scientific and Technical Subcommittee could develop the voluntary registry architecture (Instrument 1), building on existing best practice guidelines rather than negotiating new treaty obligations. Simultaneously, an independent consortium modeled on the World Economic Forum's Space Sustainability Rating initiative could design scoring methodology for the reputational index (Instrument 2). This phase would involve negotiating data access agreements with SSA providers (Space-Track, LeoLabs), establishing baseline metrics using ESA Space Environment Report data, and recruiting academic partners for evaluation protocol development. Critically, foundation-building should engage the full range of spacefaring actors, including emerging space nations such as India, the UAE, Japan, and South Korea, whose rapidly growing programs bring diverse institutional models and governance perspectives ([Amiri et al., 2022](#ref-amiri2022); [Rajagopalan and Stroikos, 2024](#ref-rajagopalan2024)), as well as commercial operators spanning megaconstellation providers (SpaceX, Amazon Kuiper, OneWeb) and the emerging active debris removal sector ([Mark and Kamath, 2019](#ref-mark2019adr); [Osoro and Oughton, 2021](#ref-ogutu2021)). *Phase 2: Pilot Implementation.* A subsequent phase would launch pilot programs for Instruments 1 and 2 with voluntary early adopters. Experience from analogous domains suggests that leading commercial operators and government agencies with strong sustainability commitments typically participate first, establishing demonstration effects that encourage broader adoption. Registry and reputational index pilots would benefit from participation across diverse actor types (commercial operators of varying scale, established and emerging government agencies, and international organizations) and orbital regimes (LEO, MEO, GEO). Inclusivity across governance structures is essential: the framework's instruments must demonstrate utility for operators under diverse regulatory environments, from the entrepreneurial commercial sector to state-funded programs pursuing development objectives ([Palmroth et al., 2021](#ref-palmroth2021)). Evaluation protocols would be pre-registered before first data collection. *Phase 3: Site Designations and Safety Zones.* Instruments 3 and 4 would require longer development timelines due to greater geopolitical complexity. Loss-framed site designations might begin with scientifically uncontroversial cases (Apollo heritage sites, lunar farside radio-quiet zones) where broad support exists, building precedent before addressing resource-relevant sites where commercial interests compete. Safety zone framework development would benefit from engagement across both the Artemis Accords and the International Lunar Research Station frameworks, as well as states participating in neither, to ensure that coordination mechanisms serve all spacefaring nations rather than reinforcing existing governance fragmentation. Active debris removal governance, addressing questions of authorization, liability, and priority for removing objects in crowded orbital regimes, represents a particularly urgent area where early multilateral engagement could prevent conflicting unilateral approaches ([Mark and Kamath, 2019](#ref-mark2019adr)). *Considerations for Implementation.* Successful implementation would require sustained attention to several factors: maintaining voluntary character to preserve participation incentives, ensuring transparency in scoring and designation processes to build legitimacy, building evaluation capacity from the outset, and creating feedback mechanisms enabling framework adaptation as experience accumulates. The adaptive design features (sunset clauses, pre-specified revision triggers) discussed in the main text operationalize this commitment to learning-by-doing, and embedding evaluation protocols during the design phase ensures that evidence accumulates alongside implementation experience. ## OA1. Theoretical Foundations and Expected Effect Sizes ### OA1.1 Behavioral Mechanisms in Commons Governance The four instruments proposed in the main text each leverage distinct psychological mechanisms documented in behavioral economics and social psychology. Before specifying evaluation designs, this section articulates the theoretical predictions underlying each instrument and derives expected effect sizes from meta-analytic evidence. *Default Effects.* The first instrument, a voluntary registry with pre-selected commitments, exploits the well-documented tendency for decision-makers to accept default options regardless of their stated preferences. Jachimowicz and colleagues' ([2019](#ref-jachimowicz2019)) meta-analysis of 58 studies encompassing over 70,000 participants finds that default-based interventions produce effects of Cohen's d ≈ 0.68, placing them among the most reliable behavioral policy tools. However, effect sizes vary substantially with choice architecture design: defaults in active choice environments, where individuals explicitly decide among options, generally show smaller effects than those in passive enrollment contexts where defaults apply without explicit choice. The space governance context likely resembles active choice (operators explicitly decide whether to join the registry), suggesting effect sizes toward the lower end of the documented range. *Status Competition.* The second instrument, a reputational sustainability index, channels competitive instincts toward prosocial outcomes by making sustainability performance visible and comparable. The psychological foundation draws from evolutionary approaches to status signaling ([Griskevicius et al., 2010](#ref-griskevicius2010)) and organizational research on ESG ratings ([Berg et al., 2022](#ref-bergkoelbelrigobon2022)). Unlike defaults, which operate through inertia, reputational mechanisms require active processing of social comparison information. Berg and colleagues ([2022](#ref-bergkoelbelrigobon2022)) document that ESG ratings diverge substantially across providers, with pairwise correlations ranging from 0.38 to 0.71, driven primarily by measurement divergence (56%) and scope divergence (38%). This divergence itself creates reputational stakes: because ratings are consequential for investment flows and public perception, operators have incentives to signal compliance visibly rather than rely on favorable assessment by any single rater. *Loss Aversion.* The third instrument, loss-framed site designations, leverages the asymmetric weighting of losses relative to equivalent gains documented by Kahneman and Tversky ([1979](#ref-kahneman1979); [1992](#ref-tversky1992)) and confirmed across diverse contexts ([Tversky and Kahneman, 1991](#ref-tversky1991)). The loss aversion coefficient (λ) typically ranges from 1.5 to 2.5, meaning losses are weighted approximately twice as heavily as equivalent gains. Framing heritage sites as shared resources "at risk of irreversible loss" rather than as areas "eligible for protection" would, in principle, generate stronger behavioral responses. However, significant uncertainty remains about whether loss aversion documented in individual decision-making translates to organizational contexts. Reference point formation itself varies substantially across individuals ([Baillon et al., 2020](#ref-baillon2020)), and organizational decision-making involves committees, procedures, and institutional norms that may attenuate or redirect loss-averse responses. *Reciprocity Norms.* The fourth instrument, reciprocal safety zone commitments, operationalizes the deeply rooted human tendency to respond to cooperation with cooperation. Experimental economics research documents strong reciprocity in diverse economic contexts ([Fehr and Gächter, 2000](#ref-fehr2000)), and international relations scholarship identifies reciprocity as a mechanism sustaining cooperation even without formal enforcement ([Keohane, 1986](#ref-keohane1986)). The safety zone design channels reciprocity through transparency requirements: operators who receive transparent information about others' activities face social pressure to reciprocate with their own transparency. ### OA1.2 Expected Effect Magnitudes Table OA1 synthesizes effect size expectations for each instrument, grounded in the meta-analytic evidence reviewed above. These predictions serve as benchmarks for evaluation, and observed effects substantially below these ranges would suggest the mechanisms may operate differently in space governance contexts than in the laboratory or field settings generating the meta-analytic estimates. **Table OA1: Expected Effect Sizes by Instrument** Instrument Mechanism Meta-Analytic Benchmark Space Context Prediction Uncertainty Default Registry Status quo bias d = 0.68 \[0.53, 0.83\] d = 0.30-0.50 High (active choice context) Reputational Index Status competition ESG rating divergence creates reputational stakes 10-20% funding differential Moderate Site Designation Loss aversion λ = 1.5-2.5 Attenuated in organizations High Safety Zones Reciprocity Strong lab effects Unknown in polycentric governance Very high The wide uncertainty bands reflect a fundamental limitation. Behavioral governance has not been implemented in international space governance, and extrapolation from laboratory or domestic policy contexts involves substantial assumptions. The evaluation framework below is designed to generate evidence reducing this uncertainty. ## OA2. Data Infrastructure ### OA2.1 Outcome Measurement Rigorous evaluation requires clearly operationalized outcome metrics aligned with the governance objectives articulated in the main text. The framework distinguishes between operational outcomes (observable changes in satellite behavior and debris creation) and behavioral process metrics that test whether the theorized psychological mechanisms operate as predicted. *Primary Operational Outcomes.* Post-mission disposal compliance can be measured as a binary indicator of whether a satellite successfully executed controlled deorbit or placement into a graveyard orbit compliant with ISO 24113:2023 guidelines. Measurement requires analyzing orbital element changes at end-of-life using the U.S. Space Surveillance Network catalog (Space-Track) supplemented by high-precision commercial tracking services such as LeoLabs. Current baseline compliance rates for LEO post-mission disposal are approximately 52% for large payloads (\>1000 kg) under the 25-year standard, with the stricter 5-year standard showing compliance of 5-55% depending on operator type ([ESA, 2023](#ref-esa2023)). Conjunction risk could be measured as the rate of Conjunction Data Messages (CDMs) per satellite-year, normalized by the object density of the specific orbital regime. The 18th Space Defense Squadron issues approximately 1.5 million CDMs annually; effective governance would be expected to manifest as reduced CDM rates among compliant operators relative to non-compliant operators in comparable orbital shells. *Behavioral Process Metrics.* Beyond operational outcomes, the evaluation must assess whether the theorized behavioral mechanisms operate as predicted. For the default-based registry, the critical process metric is the opt-out rate. Behavioral economics predicts that fewer than 20% of operators will actively reject pre-checked commitments, regardless of their prior compliance intentions. Observing substantially higher opt-out rates would suggest defaults are less effective in this context than laboratory evidence predicts. For the reputational index, process metrics include media mention volume following score releases, correlation between scores and executive communications in earnings calls or investor presentations, and whether operators proactively cite favorable scores in marketing materials. These indicators test whether the index achieves salience, a necessary condition for status competition effects. For loss-framed designations, stated preference methods (contingent valuation surveys) can assess whether heritage framing affects willingness-to-pay for site access relative to equivalent non-framed restrictions. For safety zones, the key process metric is reciprocity patterns, specifically the correlation between an operator's transparency level and the transparency it receives from other operators. ### OA2.2 Data Sources and Access Requirements The evaluation requires integration of diverse data sources spanning space situational awareness, financial markets, regulatory filings, and behavioral indicators. Table OA2 specifies the necessary data access arrangements. **Table OA2: Data Sources and Access Protocols** Source Data Type Access Model Notes Space-Track (18th SDS) TLEs, CDMs User agreement Primary SSA source ESA DISCOS Object catalog, decay data Research agreement European supplement LeoLabs / ExoAnalytic High-precision tracking Commercial license Maneuver detection UNOOSA Registry Article VIII filings Public Registration compliance ITU Frequency filings Public Spectrum coordination Crunchbase / PitchBook Venture funding API access Financial outcomes Insurance consortium Premium trends Anonymized aggregate Requires industry partnership CelesTrak Supplementary TLE data Public Kelso (2007) precision analysis Space Data Association SSA sharing metrics Membership Industry consortium data NASA CARA Conjunction assessment Agreement Conjunction Assessment Risk Analysis ISRO / IN-SPACe Indian space activity data Government request Emerging space nation data KARI Korean space program data Government request Emerging space nation data JAXA Japanese space activity data Research agreement ADR and lunar mission data Important data access limitations merit acknowledgment. Insurance pricing data are commercially sensitive; insurers have no incentive to share disaggregated premium information that competitors could exploit. One approach involves working through industry associations (such as the Space Data Association or the International Space Safety Foundation) to obtain anonymized, aggregated premium trends rather than individual quotes. Where insurance data prove entirely inaccessible, the evaluation framework specifies alternative outcome measures (funding announcement patterns, contract award criteria) that can proxy for market responses without requiring proprietary data. COSPAR Planetary Protection dossiers present similar confidentiality constraints; evaluation may need to rely on publicly announced mission categories rather than detailed dossier contents. ### OA2.3 Baseline Statistics and Reference Values Table OA2a provides baseline statistics from the ESA Space Environment Report 2023 and other authoritative sources, establishing reference points against which policy effects could be measured. **Table OA2a: Baseline Statistics (2023)** Metric Value Source Notes Trackable objects \>10cm \~36,500 ESA 2023 Increasing \~5% annually Tracked debris objects \~31,870 ESA 2023 Fragments, rocket bodies, derelict satellites Active satellites \~8,800 (2023); \~14,000 (2024) UCS Database 2023; ESA 2025 Majority in LEO; rapid growth driven by megaconstellations LEO PMD compliance (large) \~52% ESA 2023 Disposal within 25 years LEO PMD compliance (5-year) 5-55% ESA 2023 Varies by operator type GEO PMD compliance \~85% ESA 2023 Higher compliance than LEO Annual CDMs issued \~1.5 million 18th SDS Conjunction Data Messages ISS avoidance maneuvers \~3/year NASA ODPO Average 2015-2023 Space economy size \$613 billion Space Foundation 2025 Global annual revenue (2024) These baseline values enable effect size estimation and provide benchmarks for the evaluation designs specified in subsequent sections. For instance, a registry intervention increasing LEO PMD compliance from 52% to 62% would represent a 10 percentage point improvement (d ≈ 0.40), establishing a concrete threshold against which observed outcomes can be compared. ## OA3. Instrument 1: Default-Based Voluntary Registry ### OA3.1 Design Specification The voluntary registry embeds behavioral defaults into a standardized commitment architecture. Table OA3 specifies the operational default settings and their justifications, disaggregating the debris mitigation commitments from Table 2 of the main text into granular elements. **Table OA3: Registry Default Parameters** Commitment Element Default Setting Justification Post-mission disposal 25 years, active deorbit ISO 24113:2023 guideline Collision avoidance Accept CDMs, maneuver when warranted Space Data Association protocol End-of-life notification 30-day advance filing IADC guideline 6.3.1 SSA data sharing Share orbital data with consortium Existing voluntary best practice Passivation Full passivation at end-of-life ESA Clean Space Initiative The behavioral mechanism operates through status quo bias: operators joining the registry encounter pre-checked commitment boxes requiring active effort to reject. The critical design question is whether opt-out would be frictionless (simple unchecking) or require justification. Behavioral economics suggests some friction enhances default effectiveness ([Madrian and Shea, 2001](#ref-madrian2001)), but excessive friction may deter registry participation entirely. One design option would require a brief written justification for any commitment rejection, striking a balance between preserving defaults' behavioral force and maintaining voluntary participation. ### OA3.2 Evaluation Design: Difference-in-Differences The identification strategy exploits staggered voluntary adoption. Operators join the registry at different times, creating natural variation in treatment timing that enables causal inference through Difference-in-Differences (DiD) estimation. The baseline specification takes the form: $$Y_{it} = \alpha + \beta \cdot \text{Registry}_{it} + \gamma_{i} + \delta_{t} + X_{it}'\theta + \epsilon_{it}$$ where $Y_{it}$ represents the outcome (e.g., PMD compliance) for operator $i$ at time $t$, $\text{Registry}_{it}$ indicates whether the operator has joined the registry by time $t$, $\gamma_{i}$ captures operator fixed effects controlling for time-invariant characteristics, $\delta_{t}$ captures time fixed effects controlling for common shocks affecting all operators, and $X_{it}$ includes time-varying controls such as launch cadence and national regulatory changes. The coefficient $\beta$ represents the Average Treatment Effect on the Treated (ATT), the causal effect of registry participation on compliance outcomes. Standard errors must be clustered at the operator level to account for serial correlation within operators across time ([Bertrand et al., 2004](#ref-bertrand2004)). The critical identifying assumption is that, absent registry participation, treated and control operators would have followed parallel outcome trajectories. This assumption cannot be directly tested but can be assessed through event-study specifications examining pre-treatment trends. ### OA3.3 Addressing Heterogeneous Treatment Effects Recent econometric literature has identified serious biases in standard Two-Way Fixed Effects (TWFE) estimators when treatment timing is staggered and treatment effects vary across cohorts or over time ([Chaisemartin and D'Haultfoeuille, 2020](#ref-dechaisemartin2020); [Goodman-Bacon, 2021](#ref-goodmanbacon2021)). Goodman-Bacon ([2021](#ref-goodmanbacon2021)) demonstrates that the TWFE estimator constitutes a weighted average of all possible two-by-two DiD comparisons, including problematic comparisons using already-treated units as controls. When treatment effects are heterogeneous, these weights can be negative, potentially producing estimates with the wrong sign. The evaluation must therefore implement robust alternative estimators. Callaway and Sant'Anna ([2021](#ref-callaway2021)) propose an estimator that constructs the ATT by comparing treated units only to "clean" controls (units not yet treated at the relevant time), avoiding the contamination problems inherent in TWFE. Sun and Abraham ([2021](#ref-sunandabraham2021)) develop an interaction-weighted estimator for event study specifications that correctly accounts for treatment effect heterogeneity across adoption cohorts. Roth and colleagues ([2023](#ref-roth2023)) provide comprehensive guidance on selecting among these modern DiD estimators based on data characteristics and research questions. ### OA3.4 Testing the Behavioral Mechanism Establishing that registry participation increases compliance is necessary but insufficient; the evaluation must also test whether the specific behavioral mechanism (default effects) drives the observed changes. This requires within-registry comparison of operators who accepted default commitments against operators who actively selected equivalent commitments after defaults were removed or unchecked. If defaults operate through the theorized psychological mechanism (status quo bias plus implicit endorsement), operators accepting pre-checked defaults would be expected to exhibit higher compliance than operators making equivalent active choices. Observing no difference would suggest that registry effects operate through selection (already-compliant operators disproportionately join) or commitment devices (explicit public commitment changes subsequent behavior) rather than defaults specifically. Both alternative mechanisms could still support the policy, but would change the understanding of why it works and how to improve it. ### OA3.5 Statistical Power Detecting policy-relevant effects requires sufficient statistical power. Using the Jachimowicz et al. ([2019](#ref-jachimowicz2019)) benchmark of d ≈ 0.68 for default effects, but adjusting downward to d ≈ 0.40 for the active-choice context of voluntary registry enrollment, minimum sample size requirements can be calculated as follows. For a panel design tracking 100 operators over 5 years with quarterly observations, assuming baseline PMD compliance of approximately 50% and intra-class correlation of 0.10, the design achieves 80% power to detect an effect of approximately 8-10 percentage points, corresponding to Cohen's d ≈ 0.40. This represents the minimum detectable effect (MDE); smaller true effects would likely go undetected. If the actual effect size in space governance is smaller than the laboratory benchmark (plausible given the high-stakes context), larger samples or longer observation periods would be required. ## OA4. Instrument 2: Responsible Space Actor Reputational Index ### OA4.1 Design Specification The reputational index makes sustainability performance visible and comparable, enabling market and social sanctions for poor performance. Table OA4 specifies the scoring methodology and component weights for the four categories described in the main text. **Table OA4: Index Scoring Components** Category Weight Component Metrics Precedent Debris Compliance 35% PMD rate, passivation completion, collision avoidance responsiveness, debris-generating events WEF Space Sustainability Rating Spectrum Discipline 25% ITU coordination compliance, interference incidents, radio quiet zone respect ITU regulatory framework Planetary Protection 20% COSPAR requirement adherence, waiver patterns, bioburden monitoring COSPAR assessment criteria Transparency & Data Sharing 20% Voluntary disclosure, SSA data sharing, registry participation, conjunction response time ESG disclosure frameworks The index could be released periodically to maintain salience while allowing sufficient time for behavioral responses between releases. Scoring methodology would need to be published transparently because perceived arbitrariness would undermine the index's legitimacy and reduce its behavioral effects. Third-party audits of scoring consistency and methodology documentation, modeled on credit rating agency oversight requirements, could enhance credibility. ### OA4.2 Evaluation Design: Event Study The identification strategy treats quarterly index releases as discrete information shocks whose effects can be isolated using event study methodology ([MacKinlay, 1997](#ref-mackinlay1997)). The design compares outcomes in narrow windows (e.g., ±30 days) around release dates for operators experiencing significant score changes (upgrades or downgrades) relative to operators with stable scores. The event study specification takes the form: $$Y_{it} = \alpha + \sum_{\tau = - 30}^{30}\beta_{\tau}^{Up}(\text{Upgrade}_{i} \times D_{it}^{\tau}) + \sum_{\tau = - 30}^{30}\beta_{\tau}^{Down}(\text{Downgrade}_{i} \times D_{it}^{\tau}) + \gamma_{i} + \delta_{t} + \epsilon_{it}$$ where $Y_{it}$ represents the outcome (funding announcements, media sentiment, insurance quote requests) for operator $i$ at calendar time $t$, $\text{Upgrade}_{i}$ and $\text{Downgrade}_{i}$ indicate operators experiencing significant score changes in the relevant quarter, and $D_{it}^{\tau}$ are event-time indicators measuring days relative to the release date (τ = 0). The coefficients $\beta_{\tau}^{Up}$ and $\beta_{\tau}^{Down}$ trace the dynamic response to score changes across event time. The cumulative average effect (CAE) summarizes the overall impact by summing post-event coefficients. Statistical significance is assessed against the null hypothesis that scores contain no decision-relevant information beyond what market participants already knew. A potential identification threat is reverse causality: operators improving their behavior would both receive upgrades and show improved outcomes, and the event study design mitigates this concern by examining responses within narrow windows around release dates, since behavioral improvements typically precede score changes by months while market responses to score announcements occur within days. ### OA4.3 Heterogeneous Effects by Operator Type A critical test of the framework concerns operator heterogeneity. Reputational mechanisms would be expected to affect capital-dependent commercial operators more strongly than government agencies with budget allocations independent of market perception. Table OA5 specifies expected responsiveness patterns. **Table OA5: Expected Responsiveness by Operator Type** Operator Type Funding Source Expected Responsiveness Rationale VC-backed startup Venture capital High Dependent on investor sentiment Public commercial Equity markets Medium-High ESG investor sensitivity Government agency Budget appropriation Low Political rather than market accountability State enterprise (pluralistic media) Mixed Medium Multiple domestic accountability channels State enterprise (centralized governance) State budget Low Reputational pressure operates primarily through international channels Observing uniform effects across operator types would contradict the theorized status competition mechanism, and effects would instead be expected to concentrate among operators facing genuine reputational stakes. Conversely, observing effects only among government agencies would suggest mechanisms other than market pressure (perhaps diplomatic or bureaucratic) drive behavioral responses. ## OA5. Instrument 3: Loss-Framed Site Designation ### OA5.1 Design Specification Loss-framed designations leverage psychological asymmetries in how actors process potential gains versus potential losses. Designating sites as "heritage" or "protection zones" reframes the policy question from "grant access privileges?" (gain frame) to "permit irreversible loss of shared resources?" (loss frame). Table OA6 specifies site categories and their associated loss frames. **Table OA6: Site Categories and Loss Framing** Site Category Examples Loss Frame Psychological Target Scientific Heritage Apollo 11 site, Luna 2 impact site "Irreplaceable record of human achievement" Collective identity loss Radio-Quiet Zones Lunar Farside "Unique window to early universe now at risk" Scientific capability loss Geological Reserves Shackleton Crater ice deposits "Non-renewable resource requiring stewardship" Future option loss Biological Protection Potential Mars biosignature sites "Risk of irreversible contamination" Discovery potential loss Loss-framed descriptions would be expected to generate stronger protective responses than equivalent gain-framed descriptions. An operator told "access to Shackleton Crater requires forfeiting shared ice reserves" would be expected to exhibit greater reluctance than one told "Shackleton Crater access enables resource extraction opportunities." Both descriptions refer to the same physical reality; only the framing differs. ### OA5.2 Evaluation Design: Synthetic Control Method Evaluating site designations presents a fundamental identification challenge. Designated sites are unique, lacking natural control groups. The Lunar Farside radio-quiet zone, for example, has no comparable undesignated site with similar electromagnetic characteristics against which to benchmark outcomes. The Synthetic Control Method (SCM) developed by Abadie and colleagues ([Abadie et al., 2015](#ref-abadie2015), [2010](#ref-abadie2010)) addresses this challenge by constructing a counterfactual from weighted combinations of comparison sites. The method identifies weights that make the synthetic control closely match the treated site's pre-designation characteristics and outcome trajectory. Post-designation divergence between the actual site and its synthetic counterfactual estimates the causal effect. Let $j = 1$ denote the designated site and $j = 2,...,J$ denote the donor pool of comparable undesignated sites. The method selects weights $W = (w_{2},...,w_{J})'$ to minimize the distance between the treated site's pre-designation characteristics ($X_{1}$) and the weighted average of donor site characteristics ($X_{0}W$): $$\min_{W}|X_{1} - X_{0}W|\text{ subject to }w_{j} \geq 0,\sum_{j = 2}^{J}w_{j} = 1$$ The treatment effect at post-designation time $t$ is estimated as: $${\widehat{\tau}}_{1t} = Y_{1t} - \sum_{j = 2}^{J}w_{j}^{*}Y_{jt}$$ representing the difference between the designated site's actual outcome and what the synthetic control predicts it would have been absent designation. ### OA5.3 Feasibility Limitations Significant challenges arise in applying SCM to unique celestial sites. The Lunar Farside radio-quiet zone has no sites with comparable geological and electromagnetic characteristics; constructing a meaningful synthetic control may be impossible. Additionally, SCM requires sufficient pre-treatment data (typically 5-10 years) to estimate stable weights, and emerging lunar activities may lack adequate historical baselines. Where SCM proves infeasible, alternative approaches include: Interrupted Time Series (ITS) analysis examining trend breaks in mission planning activity following designation; mechanism-focused evaluation testing loss-framing effects through surveys or experimental vignettes without claiming aggregate causal effects; and comparative case study methodology documenting designation processes and outcomes across sites without formal synthetic weighting ([George and Bennett, 2005](#ref-georgebennett2005)). These alternatives sacrifice causal identification precision but may be the only feasible approaches for genuinely unique sites. ### OA5.4 Inference and Robustness SCM does not rely on standard errors for inference; instead, significance is assessed through permutation tests. The placebo-in-space test iteratively applies SCM to each donor pool site as if it were the treated site, generating a distribution of placebo effects. The estimated effect for the actual designated site is considered significant if it exceeds the placebo distribution, indicating that the observed effect is unlikely to have arisen by chance. Additional robustness checks include placebo-in-time tests (artificially shifting the designation date earlier to verify no effect appears before actual designation) and leave-one-out analysis (verifying that weights remain stable when individual donor sites are removed). ## OA6. Instrument 4: Reciprocal Safety Zone Commitments ### OA6.1 Design Specification The safety zone framework operationalizes the Outer Space Treaty's Article IX "due regard" obligation through behavioral design. Because specifying binding rules for resource extraction activities is likely infeasible given current geopolitical dynamics, the framework establishes transparency guardrails that channel reciprocity norms toward cooperative outcomes. Table OA7 specifies the compliance criteria for each guardrail. **Table OA7: Safety Zone Guardrail Specifications** Guardrail Compliant Non-Compliant Purpose Limitation Specific operational need documented Resource exclusivity or strategic denial Time Bounds Limited duration with automatic sunset Open-ended or extended without renewal Geographic Scope Limitation Minimum necessary with engineering analysis Expansive without operational justification Transparency Filed in advance of activation with full parameter disclosure Late or incomplete filing Reciprocal Deconfliction SSA sharing protocol established No coordination mechanism The behavioral hypothesis is that transparency creates reciprocity pressures. Operators receiving transparent safety zone information face social expectations to reciprocate with their own transparency. Violations become visible and carry reputational costs beyond bilateral relationships, activating third-party enforcement through status competition mechanisms. ### OA6.2 Evaluation Design: Qualitative Comparative Analysis The expected small number of safety zone declarations within a reasonable evaluation window (likely 5-15 cases over five years) precludes standard large-N econometric analysis. Qualitative Comparative Analysis (QCA) developed by Ragin ([2008](#ref-ragin2008)) offers a systematic approach to small-N causal inference appropriate for this context. QCA identifies configurations of conditions associated with outcomes of interest (compliance versus violation). Unlike regression analysis, which estimates the average effect of individual variables holding others constant, QCA examines how combinations of conditions jointly produce outcomes, appropriate when the same outcome can arise from multiple distinct causal pathways (equifinality) and individual conditions may be necessary but insufficient for the outcome. The analysis proceeds by constructing a truth table mapping all observed configurations of conditions (e.g., declaring state type, mission complexity, resource value, geopolitical context) to the outcome (compliance with all five guardrails versus violation). Logical minimization then identifies sufficient and necessary conditions for compliance. Important sample size constraints apply. Formal QCA typically requires a minimum of 12-15 cases for meaningful logical minimization. With fewer declarations, the analysis would need to limit conditions to 2-3 maximum and interpret results as exploratory pattern description rather than formal causal inference. If N \< 12, structured focused comparison ([George and Bennett, 2005](#ref-georgebennett2005)) may be more appropriate than formal QCA. ### OA6.3 Compliance Monitoring Beyond evaluation of the framework's aggregate effects, ongoing compliance monitoring would be essential to detect scope creep, the gradual expansion of safety zones beyond their original justifications toward de facto resource appropriation. Monitoring protocols could include independent coding of all declarations against the five guardrails, with inter-coder reliability established through dual coding and consensus resolution. Satellite imagery from commercial providers (Planet Labs, Maxar) enables verification that actual operational activities match declared zone boundaries and purposes. Significant discrepancies between declared and actual scope could trigger enhanced review. Textual analysis of renewal applications could assess whether justification language shifts from operational necessity toward resource exclusivity over time, a linguistic indicator of scope creep that may precede formal boundary expansion. ## OA7. Existing System References and Institutional Precedents This section catalogs existing governance systems that inform the proposed instruments, providing policymakers with concrete precedents and contact points for implementation. *Voluntary Commitment Registries (Instrument 1 Precedents).* The UN Global Compact provides the closest organizational model: a voluntary commitment platform where corporations pledge adherence to principles covering human rights, labor, environment, and anti-corruption. Launched in 2000, it now includes over 15,000 corporate participants. Critical design lessons include: commitments without monitoring yield limited behavioral change (the "blue-washing" critique); transparent reporting requirements enhance commitment credibility; and participant differentiation (active vs. non-communicating) creates reputational stakes. The proposed space registry incorporates these lessons through pre-specified compliance metrics and transparent tracking. The Space Data Association (SDA) provides a space-specific precedent for voluntary data sharing. Founded in 2009 by Inmarsat, Intelsat, and SES, the SDA facilitates conjunction warning and frequency coordination among members. Its success demonstrates that commercial competitors will share sensitive operational data when collective benefits are evident and participation is reciprocal. *Reputational Indices (Instrument 2 Precedents).* The World Economic Forum's Space Sustainability Rating (SSR), launched in 2022, provides direct precedent. The SSR scores satellite operators on debris mitigation, collision avoidance, data sharing, and mission design, with annual assessments published publicly. Early evidence suggests operators actively seek favorable scores for use in investor communications and regulatory contexts. The proposed reputational index builds on the SSR methodology while adding behavioral outcome tracking. ESG rating agencies (MSCI, Sustainalytics, CDP) demonstrate how reputational scoring affects capital allocation. Berg, Koelbel, and Rigobon (2022) document that ESG ratings, despite methodological divergence across providers, influence institutional investment flows. Space-specific ratings that align with ESG frameworks where possible would enable integration into existing responsible investment workflows. *Heritage Designations (Instrument 3 Precedents).* UNESCO World Heritage Sites provide the strongest institutional precedent for loss-framed designation. The 1972 Convention established that certain sites possess "outstanding universal value" warranting international protection. Designation creates legal obligations for state parties and normative expectations affecting development decisions even in non-party states. The proposed celestial heritage designation adapts this model for extra-terrestrial contexts, recognizing that existing treaty frameworks (Outer Space Treaty Article II) preclude territorial claims while permitting activity-based governance. The Antarctic Treaty System, particularly the Protocol on Environmental Protection (1991), provides precedent for governing shared spaces without territorial sovereignty. Specially Protected Areas (ASPAs) restrict activities to preserve scientific or environmental values, with permits required for access. The 5-year management plan review cycle informs the proposed sunset clause duration for celestial safety zones. *Safety Zone Frameworks (Instrument 4 Precedents).* UNCLOS Article 60 authorizes coastal states to establish 500-meter safety zones around artificial islands and installations. While context differs (ocean vs. space), the legal architecture demonstrates how activity-based zones can protect operations without asserting territorial sovereignty. The proposed safety zone framework adapts this approach for celestial surfaces, with transparency requirements replacing enforcement authority. The Artemis Accords (2020) provide precedent for safety zone concepts in space resource contexts. Section 11 establishes that signatories will provide notification of activities and coordinate to prevent harmful interference. With over 60 signatories including India, Japan, the Republic of Korea, the UAE, and numerous European, African, and Latin American states, the Accords demonstrate broad political feasibility for safety zone discussions. However, China and Russia's parallel International Lunar Research Station framework demonstrates that safety zone governance must ultimately accommodate actors outside any single plurilateral arrangement. *Existing Data Infrastructure.* Space-Track (www.space-track.org): The 18th Space Defense Squadron's public portal provides Two-Line Elements (TLEs) and Conjunction Data Messages (CDMs) for registered users. This is the primary data source for debris tracking and collision assessment. Registration requires U.S. government approval but is routinely granted for research purposes. 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