/**
 * State Capacity Modeling
 *
 * Based on Worldwide Governance Indicators (WGI) 2024
 * Research: Hanson & Sigman (2021), Thomann et al. (2023)
 *
 * @module core/StateCapacity
 */
/**
 * State capacity metrics from WGI
 * All values on -2.5 to +2.5 scale (WGI standard)
 */
export interface StateCapacityMetrics {
    /**
     * Government Effectiveness (WGI)
     * Quality of public services, civil service, policy formulation
     *
     * Examples:
     * - Singapore: +2.36 (highest)
     * - Switzerland: +2.0
     * - USA: +1.5
     * - China: +0.3
     * - Venezuela: -1.68 (lowest in dataset)
     */
    governmentEffectiveness: number;
    /**
     * Control of Corruption (WGI)
     * Extent to which public power is exercised for private gain
     *
     * Examples:
     * - Denmark: +2.2 (highest)
     * - Singapore: +2.2
     * - USA: +1.3
     * - Russia: -0.9
     * - Venezuela: -1.6 (highest corruption)
     */
    controlOfCorruption: number;
    /**
     * Regulatory Quality (WGI)
     * Ability to formulate and implement sound policies
     *
     * Examples:
     * - Singapore: +2.1
     * - New Zealand: +1.9
     * - USA: +1.6
     * - Brazil: -0.1
     * - Venezuela: -2.2
     */
    regulatoryQuality: number;
}
/**
 * Derived capacity metrics for simulation
 */
export interface DerivedCapacity {
    /**
     * Policy success rate multiplier
     * Formula: 1.0 + (0.3 × governmentEffectiveness)
     *
     * Research: Thomann et al. (2023) - bureaucratic performance
     *
     * Examples:
     * - Singapore (GE=2.36): 1.71 (71% boost)
     * - USA (GE=1.5): 1.45 (45% boost)
     * - Venezuela (GE=-1.68): 0.50 (50% penalty)
     */
    policySuccessMultiplier: number;
    /**
     * Implementation noise (0.0 to 0.5 scale)
     * Formula: (2.5 - controlOfCorruption) / 10
     *
     * Represents gap between policy intent and actual outcome
     *
     * Examples:
     * - Singapore (CoC=2.2): 0.03 (3% noise)
     * - USA (CoC=1.3): 0.12 (12% noise)
     * - Russia (CoC=-0.9): 0.34 (34% noise)
     * - Venezuela (CoC=-1.6): 0.41 (41% noise)
     */
    implementationNoise: number;
    /**
     * AI comprehension lag (months)
     * How long to understand new AI capabilities
     *
     * Formula based on government effectiveness:
     * - High capacity (GE > 1.5): 12-30 months
     * - Medium capacity (GE 0-1.5): 36-60 months
     * - Low capacity (GE < 0): 60-96 months
     */
    aiComprehensionLagMonths: number;
    /**
     * Overall capacity score (0-1 scale)
     * Simple average of normalized WGI metrics
     */
    overallCapacity: number;
}
/**
 * Complete state capacity assessment
 */
export interface StateCapacity {
    /** Raw WGI metrics */
    metrics: StateCapacityMetrics;
    /** Derived simulation metrics */
    derived: DerivedCapacity;
    /** Data confidence (0-1, based on WGI confidence intervals) */
    dataConfidence: number;
    /** Year of data */
    dataYear: number;
}
/**
 * Calculate derived capacity metrics from WGI data
 */
export declare function calculateDerivedCapacity(metrics: StateCapacityMetrics): DerivedCapacity;
/**
 * Create state capacity from WGI metrics
 */
export declare function createStateCapacity(metrics: StateCapacityMetrics, dataYear?: number, dataConfidence?: number): StateCapacity;
/**
 * WGI data confidence by country type
 *
 * Research: V-Dem confidence intervals analysis
 * - Democracies: ±0.05-0.10 (high confidence)
 * - Hybrid regimes: ±0.10-0.15 (medium confidence)
 * - Autocracies: ±0.15-0.25 (low confidence, data opacity)
 */
export declare function estimateDataConfidence(governmentType: string, controlOfCorruption: number): number;