q: On the overlap window where both coarse milestone-to-milestone latency (1958-2026) and fine key-decision-point latency (modern subperiod) can be built from the same programs, report their Pearson correlation, the coarse-minus-fine level gap in months, and whether that gap is constant or drifts over time.

facet: measurement

raised_by: maddison

priority: high

query_terms: NASA milestone interval latency two-resolution splice validation

query_terms: coarse fine measurement correlation level gap drift over time

query_terms: NTRS GAO key decision point milestone-to-milestone overlap window

status: open


q: Re-estimate the latency-cost association under at least two independent deflators (NASA New Start Inflation Index versus an economy-wide GDP price deflator) and report how much beta moves; add the New Start Inflation Index source document to the corpus as a discrete citable, versioned source first.

facet: empirics

query_terms: NASA New Start Inflation Index source document deflator

query_terms: GDP price deflator real cost growth space program

query_terms: deflator sensitivity cost overrun coefficient stability


q: For re-baselined programs, show the distribution of latency and cost-growth computed against the original versus the re-set baseline, and state which baseline the panel uses by era (informal practitioner targets pre-modern versus GAO/JCL-anchored commitments).

query_terms: NASA program re-baseline original versus reset cost growth distribution

query_terms: joint confidence level baseline 70 percent GAO commitment

query_terms: era-heterogeneous baseline denominator cost growth schedule slip


q: Publish the exact era-boundary rule: prove the periodization is derived from a documented structural break in a measured series (cost-growth, cadence, or appropriations), not from a chosen reform calendar co-determined with the authorization-regime treatment, and show the latency coefficient under at least two materially different defensible periodizations.

facet: identification

query_terms: structural break test periodization NASA cost growth cadence appropriations

query_terms: era boundary endogenous reform calendar treatment co-determination

query_terms: coefficient invariance alternative periodization sensitivity


q: Decompose phase cost growth into a time-rate standing-cost component (priced from documented monthly burn during idle authorization intervals) and a residual, and show latency is associated with the residual (genuine productivity loss: rework, requirements churn, re-baselining) and not merely the standing-cost term elapsed schedule predicts by construction.

facet: mechanism

query_terms: growth accounting standing cost residual total factor productivity decomposition

query_terms: NASA monthly burn rate idle authorization standing cost

query_terms: rework requirements churn productivity loss cost growth residual


q: Produce per-decade counts of program-phase observations and the share of latency values point-identified versus bounded, then re-estimate the latency association on the pre-1980 segment alone, so the panel can see whether the long-run claim survives outside the data-dense modern window or is a modern-NASA finding in historical costume.

query_terms: per-decade observation counts unbalanced panel coverage NASA 1958-1980

query_terms: point-identified versus bounded latency uncertainty bands

query_terms: pre-1980 segment re-estimation long-run robustness


q: Show from the assembled panel that residual within-program-within-era latency tracks a documented rule-of-the-game change (regress residual latency on a coded register of rule-text changes, reporting R-squared), rather than idiosyncratic case-handling noise; if residual latency is orthogonal to documented rule changes, the coefficient cannot speak to the institutional mechanism.

raised_by: north

query_terms: residual latency regressed coded register rule-text changes R-squared

query_terms: institutions versus organizations rules of the game fixed effects

query_terms: NASA NPR procurement-reform rule change register documentary


q: Validate, on a subset of programs, that documentary latency correlates with an independent de facto measure of when the decision was actually settled (internal correspondence timestamps, oral-history dates, working-group minutes), so the measure indexes the transaction cost of deciding and not the cadence of paperwork.

query_terms: de jure de facto rule gap documentary latency validation NASA

query_terms: internal correspondence oral history working-group minutes decision date

query_terms: construct validity transaction cost deciding paperwork cadence


q: Demonstrate the exclusion restriction empirically: that authorizing-office workload affects cost growth, schedule slip, and cadence ONLY through latency and not through a direct congestion or rationing channel (zero partial association of workload with outcomes conditional on latency), given workload and the appropriations cycle are themselves products of the institutional matrix under test.

facet: rival

query_terms: exclusion restriction workload instrument partial association conditional latency

query_terms: congestion rationing channel direct effect cost schedule cadence

query_terms: appropriations cycle endogenous institutional matrix instrument validity


q: Anchor the NASA latency-to-cost/schedule coefficient against at least one out-of-NASA institutional regime (DoD milestone-decision-authority SAR programs, ESA, or commercial fixed-price firm-commitment contracts) and report whether sign and magnitude survive a change of the funding-commitment rules.

query_terms: DoD Selected Acquisition Report cost overrun latency milestone decision authority

query_terms: ESA commercial fixed-price firm-commitment contract cost growth

query_terms: cross-institutional replication latency coefficient sign magnitude


q: State the scope condition formally: is H1 (latency drives overrun) a portable causal law or a property of NASA's institutional matrix that would weaken or reverse under fixed-price firm-commitment rules where the time cost of authorization is borne by the contractor? Name the specific rule-of-the-game feature the mechanism requires and predict the coefficient's direction when that feature is removed.

facet: governance

priority: normal

query_terms: scope condition portable causal law institutional matrix transaction cost

query_terms: cost-reimbursement risk allocation annual re-authorization multi-layer review

query_terms: fixed-price firm-commitment contractor time cost coefficient direction


q: Partition the NASA panel by documented internal rule-regime (named reorganizations and procurement-reform statutes; the appropriations/review/reserve rules of 1965, 1990, 2020 differ) and show the latency coefficient is stable across regimes rather than a composite averaging over distinct transaction-cost structures; if beta differs by regime, report it per regime.

query_terms: NASA internal rule-regime partition reorganization procurement-reform statute

query_terms: latency coefficient stability per-regime transaction-cost structure

query_terms: appropriations review reserve rules 1965 1990 2020 regime


q: State the stronger assumption that licenses reading the continuous-latency beta as a marginal effect (per +1 month), and show empirically whether the ATT(latency) curve is flat across the dose support or whether its slope is driven by selection-into-dose; absent that, restrict the claim to ATT-at-observed-dose.

query_terms: continuous treatment difference-in-differences selection into dose ATT

query_terms: marginal effect parallel trends dose-response homogeneity assumption

query_terms: ATT latency curve flat dose support cross-dose slope


q: Show the documentary distribution of the foreseeability-to-realization gap and report pre-period placebo ATT(g,t) on cost growth and schedule slip for cohorts entering each discrete regime; non-zero pre-period placebos mean no-anticipation fails and the latency coefficient is contaminated by anticipatory baseline-setting.

query_terms: no-anticipation assumption pre-period placebo ATT event study

query_terms: baseline gaming optimistic baseline anticipated latency violation

query_terms: pretest parallel trends low power sensitivity bounds


q: Provide the Goodman-Bacon-style decomposition of the INSTRUMENTED (2SLS) estimand, not the OLS TWFE one: is the 2SLS latency coefficient a convex-weighted average of program-phase effects or does it place negative weight on some program-time cells, and does the exclusion restriction survive dynamic portfolio-difficulty spillovers?

query_terms: Goodman-Bacon decomposition instrumented 2SLS estimand negative weights

query_terms: convex weighted average program-time cells forbidden comparison

query_terms: dynamic portfolio-difficulty spillover exclusion restriction IV


q: Produce the implied-weight (Goodman-Bacon / effective-sample) decomposition of the preferred FE-IV latency coefficient: each program's and each era's share of identifying variation, ranked, and show whether a handful of long-cycle flagships (Apollo, Shuttle, Constellation, SLS, JWST) supply the majority of the weight, in which case the estimand must be restated as the effect for that dominant subset.

query_terms: effective sample weights implied weight decomposition FE-IV

query_terms: flagship program weight concentration Apollo Shuttle Constellation SLS JWST

query_terms: wild cluster bootstrap few large programs estimand restatement


q: Partition the panel by era regime (Apollo/Cold-War, Shuttle, post-Challenger, post-Constellation/commercial) and report ATT(latency) era-by-era rather than pooled; show whether the latency-cost association holds sign and magnitude within the modern regime a current manager operates in, or whether the pooled headline is carried by extinct early cohorts.

query_terms: era-by-era ATT latency disaggregated estimate modern regime

query_terms: pooled coefficient carried by extinct early cohorts Apollo Shuttle

query_terms: regime partition latency cost association sign magnitude


q: State the target population for the policy claim and demonstrate, from the panel's entry/exit/censoring structure, that the estimand's implicit weights match it: do cancelled/censored program-phases (Constellation, SLS upper stage, second mobile launcher) get weight proportional to managerial relevance, or does survivorship tilt the effective sample toward programs that completed despite their latency, breaking transportability to in-flight and future programs?

query_terms: target population transportability estimand implicit weights managerial relevance

query_terms: censored cancelled program-phase survivorship tilt effective sample

query_terms: Constellation SLS upper stage second mobile launcher censoring


q: Show from the candidate's own panel that latency Granger-precedes cost/schedule trouble (and not vice versa) at the within-phase level, with an asymmetric cross-lag; if trouble predicts next-period latency as strongly as the reverse, the single-equation beta is a loop coefficient mislabeled as one-way cause.

raised_by: forrester

query_terms: cross-lagged Granger precedence latency cost schedule trouble within-phase

query_terms: closed feedback loop open-loop coefficient single equation bias

query_terms: rework schedule pressure ripple effect bidirectional feedback


q: After documented latency-compressing regime switches (reorganizations cutting reporting layers; procurement reforms shortening authorization), does the post-regime cost-growth and schedule-slip trajectory bend as the static beta predicts, or does latency reappear elsewhere (informal pre-decision staffing, rework, reasserted reviews) so total elapsed program time does not fall?

query_terms: policy resistance latency-compressing reorganization event study trajectory

query_terms: schedule pressure rework compensating loop elapsed time absorbed

query_terms: procurement reform shortening authorization total elapsed program time


q: Show the latency-to-outcome delay is shorter than the phase window, i.e. that a phase's latency consequences land within that phase rather than being carried into later phases; if the dominant delay exceeds the phase, the phase-level beta attributes to phase p an accumulation phase p only seeded (a stock-flow / bathtub timing error).

query_terms: latency-to-outcome impulse response distributed lag phase window

query_terms: stock flow bathtub timing error accumulation seeded later phase

query_terms: within-program identification delay structure carried forward


q: On the modern KDP-dated subperiod, build a within-program count of authorization events per phase and test whether it rises endogenously as a phase's cost-growth accumulates, then report whether beta is stable once you condition on the loop's own state (delay -> requirements drift -> re-reviews -> added authorization events -> longer latency).

query_terms: authorization event count per phase rises endogenously cost growth

query_terms: reinforcing loop requirements drift re-reviews latency endogeneity

query_terms: KDP-dated subperiod beta stability condition loop state


q: On programs with dated interim cost/schedule re-baselines within a phase, reconstruct the accumulation trajectory and test whether latency predicts the RATE of cost accrual at the moment it occurs versus the END-of-phase stock, demonstrating the phase-end beta is not a mechanical integration artifact (long phases score higher cost growth merely because the bathtub had more time to fill).

query_terms: within-phase accrual rate versus end-of-phase stock latency regression

query_terms: integration artifact elapsed time bathtub fill cost growth

query_terms: dated interim re-baseline accumulation trajectory rate decomposition


q: Aggregate to the authorizing-office-by-year level, regress total office latency on the contemporaneous count of programs in the queue to test queue-congestion dynamics, then show the summed program-level betas reproduce the observed agency-level cadence series rather than committing a fallacy of composition.

query_terms: authorizing office by-year queue congestion latency program count

query_terms: fallacy of composition actor-level aggregate cadence reproduce

query_terms: congestion externality coordination burden super-linear scaling


q: Hand-code a stratified sample of authorization intervals into the three Allison process types (Model I rational pause, Model II organizational-routine queue clearing, Model III bureaucratic side-payment) and show the headline latency coefficient survives when re-estimated with process-type interaction terms.

raised_by: allison

query_terms: Allison Model I II III process type hand-code authorization interval

query_terms: rational actor organizational process bureaucratic politics latency decomposition

query_terms: process-type interaction term coefficient survival NASA


q: Document the seat each leading instrument operates from (workload = Model II organizational congestion; appropriations clock = Model III OMB/committee bargaining) and provide an overidentification/placebo test (e.g., no-year-funded programs insulated from the appropriations cycle) distinguishing a true instrument from a channel that is part of the mechanism.

query_terms: instrument seat Model II congestion Model III appropriations bargaining

query_terms: overidentification placebo no-year-funded program insulated appropriations

query_terms: exclusion restriction channel versus exogenous nudge falsification


q: Construct an independent documentary proxy for bureaucratic-bargaining intensity per program-phase (distinct reprogramming requests, count of competing center stakeholders, congressional-mark reversals) and show the latency coefficient is robust to it, ruling out the Model III common-cause where long latency and high cost growth are co-produced resultants of one coalition fight.

query_terms: bureaucratic bargaining intensity proxy reprogramming competing center stakeholders

query_terms: congressional mark reversal coalition fight common cause confound

query_terms: latency cost growth co-produced resultant robustness Model III


q: Partition each authorization interval by which seat owns the pending decision (Mission Directorate HQ, field-center program office, OMB passback, appropriations subcommittee) and report whether the latency-to-cost/schedule association holds WITHIN a seat or is only a between-seat composition effect.

query_terms: seat-partitioned authorization interval within-seat between-seat beta

query_terms: Mission Directorate field center OMB passback appropriations subcommittee

query_terms: composition effect latency cost schedule association decomposition


q: Build a measure of each program's portfolio standing (directorate champion, congressional-district interest, flagship designation) and test whether authorizing-office workload predicts cost/schedule DIFFERENTLY for portfolio winners versus losers; if the path runs only through deprioritized losers, the workload exclusion restriction fails.

query_terms: program portfolio standing champion district flagship queue priority

query_terms: workload winners losers interaction exclusion restriction deprioritized

query_terms: bureaucratic competence procurement outcomes standing queue order


q: Isolate documented discrete RE-SEATING events (clearance layer eliminated, authority delegated downward, review office stood up/disbanded) and show in an event study that the SAME programs' latency and cost/schedule outcomes move together after re-seating; if they do not, latency is a passive marker of regime, not a lever.

query_terms: re-seating event study clearance eliminated authority delegated review office

query_terms: latency cost schedule co-movement same program seat change

query_terms: natural experiment causal lever versus passive regime marker


q: Reconstruct, from the contemporaneous documentary trail, the date substantive commitment crystallized versus the date the recorded authorization fired, and show the divergence distribution (in months) across a stratified sample of NASA program-phases, before the recorded authorization can be treated as the decision.

raised_by: mintzberg

query_terms: emergent strategy commitment crystallization versus authorization date divergence

query_terms: deliberate emergent realized strategy ratification month gap

query_terms: documentary trail stratified program-phase construct validation


q: Using process-rich cases (oral histories, NASA institutional histories, Apollo management-control record), show that documentary latency correlates with an independent, process-derived measure of how long substantive deliberation actually took, so the variable indexes decision speed rather than records-keeping density.

query_terms: managerial work fragmented verbally mediated deliberation duration process-derived

query_terms: oral history Apollo management control deliberation time correlation latency

query_terms: convergent validity decision speed records-keeping density


q: Produce, per era, an estimate of what fraction of substantive decision time the documentary trigger-to-authorization interval captures, and show that this capture fraction is stable enough across eras that a within-era latency coefficient compares like with like.

query_terms: per-era capture fraction substantive decision time documentary interval

query_terms: era-dependent review formalization latency meaning 1965 versus 2020

query_terms: within-era coefficient like-with-like stability capture


q: Stratify the panel by dominant coordinating configuration per program-phase (routine production/operations versus novel first-of-kind development) and show whether the latency-cost slope is heterogeneous, or whether the pooled beta averages a productive (machine-bureaucratic conformance) and a destructive (adhocratic mutual-adjustment) coefficient into a meaningless mean.

query_terms: Structure in Fives configuration machine bureaucracy adhocracy mutual adjustment

query_terms: configuration-stratified latency slope routine versus novel first-of-kind

query_terms: pooled coefficient opposite-sign averaging conformance mutual adjustment


q: On a hand-coded sample with oral histories or contemporaneous correspondence, demonstrate the documentary trigger/authorization timestamps are not the LATE ratifying bookends of a process that substantively opened and closed earlier, and that this ratification lag is uncorrelated with phase difficulty rather than a measure of how much administrative ceremony a hard phase generates.

query_terms: ratification bookend trigger authorization timestamp late artifact oral history

query_terms: ratification lag correlated phase difficulty administrative ceremony

query_terms: compliance versus learning standardized review machinery NASA


q: On documented latency-compressing reorganizations, show post-regime cost-and-schedule improvement that EXCEEDS the mechanical removal of the compressed waiting time, the only test ruling out the latency remedy being a downstream symptom of machine-bureaucratic configuration mismatch rather than the cause; the era fixed effects currently absorb exactly this discriminating regime variation.

query_terms: post-reorganization improvement exceeds mechanical latency removal symptom cause

query_terms: configuration mismatch machine bureaucracy novel work co-product

query_terms: era fixed effects absorb regime variation cause symptom discrimination


q: Specify the era partition granularity and demonstrate from the NASA appropriations record whether within-era residual variation in the appropriations-calendar instrument is statistically independent of the funding-instability index; if they co-move within era, the exclusion restriction fails through the fiscal-regime back-door and no first-stage F can save it.

raised_by: pearl

query_terms: fiscal-political regime back-door instrument funding-instability index independence

query_terms: within-era residual appropriations-calendar continuing resolution co-movement

query_terms: exclusion restriction d-separation era granularity first-stage F


q: Show, from the milestone taxonomy in the NASA program records, the exact set-theoretic decomposition of a phase's elapsed time into authorization intervals versus engineering-execution intervals, and prove the two are disjoint; if any authorization month is also in the schedule-slip numerator, the schedule-slip result is mechanically tautological and must be dropped.

query_terms: set-theoretic decomposition phase elapsed time authorization engineering disjoint

query_terms: schedule slip numerator latency component identity tautology

query_terms: NASA NTRS milestone interval taxonomy KDP confirmation review SRB


q: From GAO/NTRS records, exhibit for a sample of program-phases the dated sequence showing the latency-clock-start event precedes the first documented risk-elevation, review-board finding, or requirements-change request in that phase; if the risk signal systematically predates the latency-start event, the early-measurement defense collapses and the arrow runs difficulty -> latency.

query_terms: dated event sequence latency trigger precedes risk elevation requirements change

query_terms: anticipated difficulty phase entry immature TRL contested baseline confounder

query_terms: reverse causation temporal precedence early measurement defense GAO NTRS


q: Draw the explicitly mediated DAG (latency -> mediator [standing-cost accrual / requirements churn / workforce idle] -> cost, with an unobserved program-difficulty confounder), state whether the latency-to-cost effect is front-door identifiable through the mediator without the contested IV, and name which line items in the three named datasets would populate the mediator node at program-phase resolution.

query_terms: front-door criterion mediator standing-cost requirements churn workforce idle

query_terms: mediated DAG program-difficulty confounder arrows mediator outcome

query_terms: mediator node measurement NASA budget records program-phase resolution


q: State the error structure of the two-resolution latency scalar on the DAG: is the coarse-era measurement error classical (independent of true latency, attenuating beta) or non-classical and correlated with the era node and the outcome (sparse-documentation eras also being looser-baseline, larger-overrun eras)? Show, on the documented overlap window, the joint distribution of (coarse latency, fine latency, outcome).

query_terms: non-classical differential measurement error era documentary density collider

query_terms: errors-in-variables coarse fine latency joint distribution outcome overlap

query_terms: era fixed effect collider-adjacent downstream mismeasured latency outcome


q: Pre-register and report the conditional-independence (overidentification) test of the exclusion restriction on the assembled panel (instrument independent of outcome residual given latency and controls), and commit that a non-vanishing partial correlation FALSIFIES the exclusion restriction and the IV, not merely flags a robustness footnote.

query_terms: conditional independence overidentification test exclusion restriction vanishing partial correlation

query_terms: DAG testable implication d-separation falsification pre-register

query_terms: two instruments one endogenous regressor overidentified instrument outcome residual


q: Fit the tail of the cost-growth and schedule-slip distributions on the assembled panel and estimate the tail exponent alpha (Hill estimator on upper order statistics plus max-to-sum ratio convergence plot); if alpha <= 2 variance is undefined, clustered SEs estimate a non-existent moment, and beta does not converge to a stable population mean, so report what the coefficient is an estimate OF.

raised_by: taleb

query_terms: tail exponent alpha Hill estimator cost overrun fat tail infinite variance

query_terms: max-to-sum ratio convergence megaproject Extremistan cost growth

query_terms: clustered standard error non-existent moment mean non-convergent


q: Run a jackknife-by-extreme-deletion on the headline latency coefficient (delete the single most extreme cost-growth program, then top two, then top five) and plot beta and its interval versus number of tail programs excluded; pre-register an instability threshold (sign flip, loss of significance, or movement exceeding the coefficient's own SE) at which the mean frame is conceded to have failed.

query_terms: jackknife leave-extreme-out latency coefficient tail program deletion

query_terms: Constellation top-k catastrophic program influence sign flip significance

query_terms: pre-register falsification threshold mean frame failed tail estimand


q: Re-pose the hypothesis on the tail: estimate whether latency shifts the tail exponent or the conditional probability of extreme overrun (quantile regression at the 90th/95th percentile, or a tail-index regression), not the conditional mean, and test whether latency's tail effect matches its mean effect in sign and significance; a null mean effect with a positive tail effect is a rejection of H0, not a confirmation.

query_terms: quantile regression 90th 95th percentile cost growth latency tail effect

query_terms: tail-index regression conditional probability extreme overrun ruin

query_terms: absorbing barrier Kessler ruin decision rule tail estimand re-anchor


q: Enumerate the population of NASA programs (1958-2026) that never reached authorization or were terminated during a long latency interval (cancelled, zeroed, pre-authorization limbo) from GAO new-start/cancellation records, NTRS, and budget justifications, and report what fraction of candidate phase-observations is missing from the survivor panel for that reason.

query_terms: NASA program cancellation termination pre-authorization limbo graveyard census

query_terms: GAO new-start cancellation record NTRS budget justification 1958-2026

query_terms: survivor panel missing fraction censored program-phase denominator


q: Produce a Heckman-style selection model or Manski-style bounds argument from the survivor panel plus the enumerated cancellation set that quantifies the sign and magnitude of survivorship bias on the latency coefficient, showing whether survivor-only beta is an upper or lower bound and how wide the bound is once dead programs re-enter.

query_terms: Heckman selection model Manski bounds survivorship bias latency coefficient

query_terms: survivor-only beta upper lower bound dead programs re-enter

query_terms: collider selection survival downstream latency censored cancellation


q: Demonstrate the policy claim 'compress latency to reduce overrun' is estimable when the worst latency outcome (cancellation/ruin) is structurally excluded from every dependent variable, or restate the contribution as a within-survivor association that is silent on, and possibly opposite to, latency's effect on program-killing ruin (e.g., via a cancellation-hazard outcome).

query_terms: cancellation hazard ruin-inclusive outcome within-survivor scope restriction

query_terms: absorbing barrier program death dependent variable baseline censored

query_terms: policy claim compress latency overrun ruin opposite effect


q: Add an optimist/synthesist OR normative-strategic seat (none was on the panel) that asks whether latency carries an unpriced option value or hedging benefit (deliberate delay buying information, avoiding premature commitment to an immature design), so the dissertation does not implicitly assume all latency is pure waste; show the optimal-latency interior solution rather than a monotone compress-it-to-zero policy.

raised_by: moderator

query_terms: option value of delay real options deliberate latency information acquisition

query_terms: optimal latency interior solution premature commitment immature design

query_terms: value of waiting hedging benefit acquisition decision deferral


q: Re-estimate the latency-cost association under at least two independent deflators (NASA New Start Inflation Index versus an economy-wide GDP price deflator) and report how much beta moves; add the New Start Inflation Index source document to the corpus as a discrete, citable, versioned source first. The GDP deflator alternative is recognised in the space-economy forecasting literature but no resolvable external citation for the specific OCEA report was available at time of interrogation; locating and verifying an external DOI or URL for the OCEA source (Bryce/SIA Forecasting the Space Economy, source key SD08) is a prerequisite before this claim can be grounded.

query_terms: NASA New Start Inflation Index source document deflator versioned citable

query_terms: OCEA Bryce SIA Forecasting Space Economy GDP price deflator external DOI

query_terms: dual deflator sensitivity cost overrun beta stability space program

status: partial