Integration & Orchestration Frameworks

2026-01-28 00:00:00 +0000

Status: Coming Soon

Expected: Q1 2027

Documentation Coming Soon

---

Overview

This meta-domain provides the infrastructure for coordinating multiple analytical frameworks—enabling research questions that span traditional disciplinary boundaries and require outputs from different modeling approaches to be combined coherently.

---

Technical Approach

Problems Addressed

• Analytical silos — Domain-specific models produce outputs that don’t connect; policy questions that span boundaries go unanswered
• Consistency failures — Running separate models on the same scenario produces contradictory results without reconciliation
• Workflow complexity — Multi-stage analyses require manual data handoffs that introduce errors and break audit trails
• Reproducibility gaps — Complex pipelines are difficult to version, share, and replicate
• Stakeholder translation — Technical outputs need transformation for different audiences without losing fidelity

Methodological Foundations

Our integration infrastructure builds on established workflow and modeling coordination approaches:

Method	Application	Key References
Input-Output Analysis	Inter-industry linkages and multiplier effects	Leontief, Miller-Blair
Soft-Linking	Connecting models with different temporal/spatial resolution	Integrated assessment model coupling
DAG Workflows	Directed acyclic graph execution for complex pipelines	Airflow, Prefect paradigms
Scenario Management	Consistent parameter sets across model components	IPCC scenario protocols
Uncertainty Propagation	Monte Carlo and sensitivity across linked models	Global sensitivity analysis

Analysis Outputs

• Integrated results — Unified outputs combining multiple analytical domains
• Consistency reports — Cross-model validation and reconciliation diagnostics
• Audit trails — Complete provenance from inputs through all transformations to outputs
• Scenario comparisons — Side-by-side analysis under alternative assumptions
• Stakeholder reports — Audience-appropriate summaries with appropriate uncertainty communication

Appropriate Applications

• Complex policy analyses spanning economic, social, and environmental domains
• Research programs requiring multiple methodological approaches
• Grant deliverables with multi-model requirements
• Regulatory analyses requiring documented reproducibility
• Strategic planning with scenario uncertainty
• Academic research on model integration methods

---

Planned Capabilities

Multi-Framework Orchestration

• Workflow management for complex analytical pipelines
• Data handoff protocols between framework components
• Consistency checking across integrated outputs

Cross-Domain Synthesis

• Unified reporting across analytical domains
• Scenario comparison and sensitivity visualization
• Stakeholder-oriented output generation

Governance and Validation

• Audit trail infrastructure for complex analyses
• Version control for multi-component runs
• Reproducibility protocols for integrated workflows

---

Development Status

Component	Status
Orchestration engine	Design Phase
Cross-domain interfaces	Design Phase
Validation infrastructure	Not Started
Documentation	Not Started

---

Relationship to Other Domains

The Integration & Orchestration frameworks serve as the coordination layer for all other KRL domains. As individual domain frameworks mature, this layer enables their combination for complex policy questions that cannot be addressed by any single analytical approach.

---

Stay Updated

Register to receive notifications when this framework documentation becomes available.

Register for Updates

---

Khipu Research Labs — info@krlabs.dev

Arts, Media & Culture Frameworks

2026-01-27 00:00:00 +0000

This domain treats cultural dynamics as first-class variables in economic analysis—tools for measuring the economic contribution of creative industries, understanding how media shapes behavior and preferences, and quantifying cultural opportunity and access.

---

Technical Approach

Problems Addressed

• Cultural externality treatment — Standard economic models treat arts and culture as consumption residuals, missing their role in shaping preferences and behavior
• Creative economy measurement — GDP and employment statistics undercount creative occupations embedded across industries
• Media influence opacity — Information campaigns affect behavior, but effects are difficult to quantify with standard survey methods
• Cultural access inequality — Geographic and demographic disparities in cultural opportunity lack systematic measurement
• Valuation challenges — Intangible cultural assets resist standard financial valuation methods

Methodological Foundations

Our frameworks integrate cultural economics with computational social science:

Method	Application	Key References
Cultural Satellite Accounts	Arts sector contribution to GDP	UNESCO Framework for Cultural Statistics
CGE with Cultural Sectors	General equilibrium with creative industry disaggregation	Applied general equilibrium methods
Agent-Based Cultural Dynamics	Preference evolution and social influence	Axelrod cultural dissemination models
Media Reach Modeling	Campaign exposure and behavioral response	Advertising effectiveness literature
Cultural Opportunity Indices	Access, participation, and infrastructure metrics	NEA Arts Participation Survey methodology
IP Valuation	Intellectual property and content lifecycle analysis	Real options and DCF approaches

Analysis Outputs

• Contribution metrics — Direct, indirect, and induced economic impact of cultural sectors
• Behavioral simulations — Agent-based projections of cultural trait evolution and media influence
• Opportunity indices — Cultural access scores by geography and demographic group
• Equity decompositions — Distributional analysis of cultural participation and investment
• Valuation estimates — Economic value of cultural assets, content portfolios, and IP

Appropriate Applications

• Arts and culture economic impact studies
• Creative economy development planning
• Public interest media campaign design
• Cultural equity assessment and policy
• Foundation and NEA grant applications
• Museum, theater, and venue strategic planning
• Content and IP portfolio valuation

---

Available Frameworks

---

Planned Capabilities

Cultural Economics Measurement

• Economic contribution indices for arts and creative sectors
• Satellite account methodologies for cultural industries
• Employment and value-added analysis for creative occupations

Media Influence Modeling

• Information diffusion through social networks
• Attitude formation and preference dynamics
• Public interest communications impact assessment

Cultural Opportunity Analysis

• Access and participation indices by community
• Cultural infrastructure gap analysis
• Investment prioritization for creative economy development

---

Development Roadmap

Component	Status	Expected
CGE-ABM Framework	In Development	Q4 2026
Cultural Contribution Metrics	Design Phase	Q1 2027
Cultural Opportunity Indices	Design Phase	Q2 2027

---

Stay Updated

Register to receive notifications when new frameworks in this domain become available.

Register for Updates

---

Khipu Research Labs — info@krlabs.dev

Financial & Economic Frameworks

2026-01-26 00:00:00 +0000

Status: Coming Soon

Expected: Q4 2026

Documentation Coming Soon

---

Overview

This domain addresses the intersection of financial systems and economic policy—tools for understanding how capital flows, risk dynamics, and market structures interact with community development and household welfare.

---

Technical Approach

Problems Addressed

• Representative agent fiction — Standard macro models assume identical households, missing how shocks affect different wealth levels differently
• Regulatory fragmentation — Basel, CECL, and stress testing requirements use different methodologies that don’t integrate cleanly
• Network blindness — Bilateral exposure data is scarce; systemic risk assessment requires inference from partial information
• Macro-financial disconnect — Real economy models often ignore financial frictions; financial models ignore real economy feedback
• Household heterogeneity — Aggregate statistics obscure financial fragility concentrated in specific population segments

Methodological Foundations

Our frameworks build on established financial and macroeconomic methods:

Method	Application	Key References
Basel III/IV	Capital adequacy, liquidity coverage, leverage ratios	Basel Committee on Banking Supervision
CECL	Current expected credit loss provisioning	FASB ASC 326
CCAR/DFAST	Supervisory stress testing scenarios	Federal Reserve stress testing methodology
DSGE	Dynamic stochastic general equilibrium with financial frictions	Smets-Wouters, Gertler-Karadi
HANK	Heterogeneous agent New Keynesian models	Kaplan, Moll, Violante (2018)
Network Contagion	Interbank exposure and cascade dynamics	Eisenberg-Noe clearing, DebtRank
VaR/ES	Value-at-Risk and Expected Shortfall	Basel market risk standards

Analysis Outputs

• Risk metrics — LCR, NSFR, capital ratios, VaR, Expected Shortfall with confidence bounds
• Stress test results — Capital depletion paths under adverse scenarios
• Contagion maps — Network visualization of systemic risk transmission
• Macro projections — GDP, inflation, employment under policy scenarios with heterogeneous household impacts
• Distributional analysis — Wealth and debt burden dynamics by household quintile
• Regulatory compliance — Structured outputs aligned with supervisory reporting requirements

Appropriate Applications

• Bank regulatory compliance and internal risk assessment
• Macroprudential policy analysis
• Central bank research on monetary transmission
• Academic research on financial stability
• Household financial fragility assessment
• Community development financial institution (CDFI) analysis
• Grant applications for financial inclusion research

---

Planned Capabilities

Risk Assessment Infrastructure

• Systemic risk indicators with distributional decomposition
• Stress testing frameworks for policy scenarios
• Contagion modeling in financial networks

Macroeconomic Modeling

• General equilibrium solvers with financial sector integration
• Monetary-fiscal policy interaction analysis
• Open economy extensions for trade and capital flows

Household Finance Analysis

• Wealth distribution dynamics and mobility
• Debt burden and financial fragility indicators
• Access to credit and financial inclusion metrics

---

Development Status

Component	Status
Risk modeling core	Design Phase
Macro-financial integration	Design Phase
Household finance module	Not Started
Validation protocols	Not Started

---

Stay Updated

Register to receive notifications when this framework documentation becomes available.

Register for Updates

---

Khipu Research Labs — info@krlabs.dev

Experimental & Research Frameworks

2026-01-25 00:00:00 +0000

Status: Coming Soon

Expected: Q3 2026

Documentation Coming Soon

---

Overview

This domain provides methodological infrastructure for rigorous causal inference—tools that help researchers design studies, estimate treatment effects, and communicate uncertainty in ways that meet the standards of evidence-based practice.

---

Technical Approach

Problems Addressed

• Selection bias — Observational data conflates treatment effects with pre-existing differences between groups
• Heterogeneous effects — Average treatment effects mask variation across subpopulations that matters for targeting
• Identification fragility — Causal claims depend on assumptions that are rarely tested systematically
• Reproducibility gaps — Analysis choices are often undocumented, making replication difficult
• Temporal confounding — Time-varying treatments and staggered adoption complicate standard panel methods

Methodological Foundations

Our frameworks implement peer-reviewed causal inference methods:

Method	Application	Key References
Difference-in-Differences	Policy evaluation with parallel trends	Callaway & Sant’Anna (2021), staggered adoption extensions
Synthetic Control	Comparative case studies with data-driven weighting	Abadie et al. (2010, 2015)
Regression Discontinuity	Sharp and fuzzy designs at policy thresholds	Cattaneo et al. optimal bandwidth selection
Propensity Score Methods	Matching, IPW, and doubly robust estimation	Imbens & Rubin (2015), AIPW estimators
Instrumental Variables	2SLS and weak instrument robust inference	Stock & Yogo tests, Anderson-Rubin confidence sets
Double Machine Learning	High-dimensional confounding with cross-fitting	Chernozhukov et al. (2018)
Bayesian Causal Inference	Prior incorporation and posterior uncertainty	Stan/PyMC implementations
Meta-Learners	CATE estimation (S-learner, T-learner, X-learner, R-learner)	Künzel et al. (2019)

Analysis Outputs

• Treatment effect estimates — ATE, ATT, ATU with confidence intervals and sensitivity bounds
• Heterogeneity analysis — Conditional average treatment effects by subgroup
• Diagnostics — Balance tables, parallel trends tests, placebo checks, sensitivity plots
• Robustness matrices — Effect stability across specification choices
• Pre-analysis documentation — Registered analysis plans with versioning

Appropriate Applications

• Randomized controlled trial analysis
• Quasi-experimental policy evaluation
• Program impact assessment for funders
• Academic research requiring causal identification
• Evidence synthesis and meta-analysis
• What Works Clearinghouse and similar evidence standards
• Grant proposals requiring rigorous evaluation designs

---

Planned Capabilities

Research Design Tools

• Power analysis with heterogeneous treatment effects
• Randomization inference frameworks
• Pre-analysis plan templates with versioning

Causal Inference Pipelines

• Modular estimators (IPW, AIPW, doubly robust)
• Sensitivity analysis for unobserved confounding
• Heterogeneous effects discovery and subgroup analysis

Reproducibility Infrastructure

• Automated audit trails from raw data to results
• Version-controlled analysis pipelines
• Replication package generation

---

Development Status

Component	Status
Estimator library	In Development
Design optimization	Design Phase
Reproducibility tools	Design Phase
Documentation	Not Started

---

Stay Updated

Register to receive notifications when this framework documentation becomes available.

Register for Updates

---

Khipu Research Labs — info@krlabs.dev

Government & Policy Frameworks

2026-01-24 00:00:00 +0000

Status: Coming Soon

Expected: Q3 2026

Documentation Coming Soon

---

Overview

This domain provides computational infrastructure for evidence-based policy analysis—tools that support regulatory impact assessment, program evaluation, and legislative analysis while meeting formal evidence requirements.

---

Technical Approach

Problems Addressed

• Scoring consistency — Legislative proposals require standardized fiscal impact estimates across different analytical teams
• Evidence mandate compliance — GPRA, FFATA, and OMB requirements demand structured documentation of program outcomes
• Distributional blindness — Aggregate cost-benefit ratios obscure who bears costs and who receives benefits
• Policy diffusion uncertainty — State and local adoption patterns are difficult to forecast without systematic modeling
• Interagency coordination — Policies span jurisdictions; isolated agency analysis misses interaction effects

Methodological Foundations

Our frameworks align with established government analytical standards:

Method	Application	Alignment
CBO Scoring Methodology	Budgetary impact estimation for legislation	Congressional Budget Office standards
OMB Circular A-4	Regulatory impact analysis with benefit-cost principles	Executive Order requirements
GPRA Modernization Act	Performance measurement and strategic planning	GAO evaluation standards
Policy Diffusion Models	State adoption patterns and spillover estimation	Berry & Berry event history approaches
Spatial Econometrics	Geographic spillovers and jurisdictional interaction	Anselin spatial regression methods

Analysis Outputs

• Fiscal scores — 10-year budget window projections with sensitivity ranges
• Regulatory impact statements — Structured cost-benefit documentation meeting OMB requirements
• Performance metrics — GPRA-aligned outcome indicators with baseline and target tracking
• Distributional tables — Impact breakdowns by income quintile, geography, and demographic group
• Diffusion projections — Expected adoption curves across jurisdictions under policy scenarios

Appropriate Applications

• Legislative fiscal impact analysis
• Regulatory impact assessment (Executive Order 12866 compliance)
• Program evaluation and performance reporting
• Evidence Act and GPRA documentation
• Interagency policy coordination analysis
• State and local policy adoption forecasting
• Grant applications requiring policy impact evidence

---

Planned Capabilities

Regulatory Impact Assessment

• Cost-benefit analysis with equity weighting
• Distributional impact decomposition by demographic group
• Compliance burden estimation across affected populations

Program Evaluation Infrastructure

• Causal inference pipelines for treatment effect estimation
• Difference-in-differences, regression discontinuity, synthetic control
• Sensitivity analysis for identification assumptions

Legislative Effect Estimation

• Policy simulation for proposed legislation
• Revenue and expenditure projections
• Affected population identification and impact quantification

---

Development Status

Component	Status
RIA computation modules	Design Phase
Evaluation pipeline	In Development
Evidence documentation standards	Design Phase
Validation protocols	Not Started

---

Stay Updated

Register to receive notifications when this framework documentation becomes available.

Register for Updates

---

Khipu Research Labs — info@krlabs.dev

Socioeconomic & Academic Frameworks

2026-01-23 00:00:00 +0000

Status: Coming Soon

Expected: Q2 2026

Documentation Coming Soon

---

Overview

This domain addresses foundational challenges in development economics and social measurement—how to quantify complex, multidimensional phenomena like poverty, human development, and inequality in ways that support both research rigor and policy relevance.

---

Technical Approach

Problems Addressed

• Aggregation bias in poverty measurement — Single-dimension metrics (income alone) miss deprivations that don’t correlate with consumption
• Within-group heterogeneity — National averages obscure subnational and demographic variation that matters for targeting
• Climate-development tradeoffs — Sectoral policies interact across domains; isolated analysis produces misleading guidance
• Temporal dynamics — Static snapshots miss how households move in and out of deprivation over time

Methodological Foundations

Our frameworks build on established, peer-reviewed methodologies:

Method	Application	Key References
Alkire-Foster	Multidimensional poverty measurement with flexible cutoffs and decomposition	Oxford Poverty & Human Development Initiative
UNDP Composite Indices	HDI, IHDI, GDI, GII computation with inequality adjustment	UN Human Development Reports methodology
Social Accounting Matrix (SAM)	Economy-wide accounting linking production, income, and expenditure	IFPRI, World Bank GTAP
Integrated Assessment Models	Climate-economy interaction (DICE, GCAM-style approaches)	Nordhaus, JGCRI
CGE-Microsimulation Linking	Macro shocks traced to household-level welfare impacts	World Bank GIDD methodology

Analysis Outputs

• Scalar indices — MPI, HDI, SPI, and custom composite measures with confidence bounds
• Decompositions — By dimension, demographic group, administrative unit, and time period
• Projections — Forward scenarios under policy and climate assumptions
• Contribution analysis — Which deprivations drive aggregate poverty in each context
• Targeting diagnostics — Identification of high-priority populations and intervention points

Appropriate Applications

• SDG monitoring and progress tracking
• National poverty assessment and strategy development
• Climate adaptation planning with equity considerations
• Program targeting and resource allocation
• Academic research on multidimensional welfare
• Grant proposals requiring rigorous measurement frameworks

---

Planned Capabilities

Multidimensional Poverty Indices

• Automated computation with demographic decomposition
• Alkire-Foster methodology implementation
• Spatial and temporal analysis across administrative units

Human Development Indicators

• SDG-aligned indicator computation and monitoring
• Inequality-adjusted metrics (IHDI, GDI, GII)
• Sub-national and intersectional disaggregation

Integrated Assessment

• Climate-equity integration for adaptation planning
• Cross-sector impact modeling (education, health, income)
• Long-horizon projection with explicit uncertainty bounds

---

Development Status

Component	Status
Index computation engine	In Development
Data pipeline infrastructure	Design Phase
Validation protocols	Not Started
Documentation	Not Started

---

Stay Updated

Register to receive notifications when this framework documentation becomes available.

Register for Updates

---

Khipu Research Labs — info@krlabs.dev

CGE-ABM Framework

2026-01-22 00:00:00 +0000

Version: 2.0

Status: Conceptual Framework — Under Development

Validation Target: Q4 2026 - Q1 2027

Download Full Report (PDF)

---

Introduction

Problem

Policy analysis faces a persistent structural gap. Macro models provide economy-wide consistency but flatten populations into “representative agents”—averaging away the distributional effects that matter most for equity. Micro models capture heterogeneity but lack the aggregate constraints that keep results economically coherent.

The tools available today force a choice: rigor at the macro level, or realism at the micro level. For research programs concerned with how policies actually affect different communities, this is an unacceptable trade-off.

Objective

This framework bridges macro and micro scales through bi-directional coupling between a Computable General Equilibrium (CGE) model and an Agent-Based Model (ABM). The goal is structured scenario exploration: examining how policies interact with social dynamics to produce equity outcomes, without collapsing into false precision or losing aggregate consistency.

---

Methods

System Architecture

The framework specifies a modular architecture with five primary components:

Component	Description	Status
Economic (CGE)	General equilibrium solver with SAM calibration, nested production functions, and market-clearing conditions	Core: Complete
Social (ABM)	10,000+ heterogeneous agents with demographic attributes, cultural profiles, and social network positions	70% Complete
Equity Assessment	Gini coefficient, Theil index, and Atkinson index with decomposition capabilities	Validated
Media Influence	Broadcast signal model for information campaigns affecting cultural traits	60% Complete
Integration	Bi-directional coupling orchestrating CGE-ABM feedback loops	One-way: Complete

Data Sources

• Economic Data: BEA Input-Output tables, IMPLAN databases, state-level SAMs
• Social Data: ACS PUMS, CPS, Consumer Expenditure Survey, PSID
• Cultural Proxies: World Values Survey, General Social Survey
• Network Structures: Calibrated canonical models (small-world, scale-free, spatial lattice)

Key Assumptions

1. Competitive markets with flexible prices (no quantity rationing)
2. Annual time-stepping with within-period equilibrium
3. Stylized social network topologies
4. Simplified media effects (broadcast without algorithmic targeting)
5. Exogenous technology and productivity

---

Results

Scenario Templates

The framework demonstrates four scenario templates illustrating analytical capabilities:

1. Progressive Tax Reform

• Policy: +10% marginal rate on top quintile, +$2,000 transfers to bottom quintiles
• Media: Tax fairness campaign (60% reach)
• Expected: ~14% Gini reduction, ~-0.8% GDP impact

2. Environmental Policy

• Policy: $50/ton carbon tax with lump-sum rebate
• Media: Climate awareness campaign (70% reach)
• Expected: 20-30% emissions reduction, sectoral reallocation

3. Education Equity Investment

• Policy: +2% GDP education spending to bottom quintiles
• Media: Education opportunity campaign
• Expected: ~10% Gini reduction over 50-year horizon

4. Social Cohesion Shock

• Scenario: Polarizing media event causing trust distribution bifurcation
• Expected: Network segregation, ~-1.5% GDP, persistent polarization

These are conceptual templates—NOT empirical results or predictions.

---

Discussion

Validation Status

Phase	Status
Component-level testing	Complete
One-way integration	Validated
Two-way coupling stability	60% Complete
Empirical calibration	Not Started
Historical backcasting	Not Started
Peer review	Not Started

Limitations

• CGE equilibrium assumptions may overstate market efficiency
• Cultural parameters have weak empirical grounding
• Media model excludes algorithmic targeting and echo chambers
• Within-group heterogeneity underrepresented
• Time horizon limited to 5-20 years

Appropriate Use Cases

• Academic research and methodological development
• Scenario exploration and comparative policy analysis
• Stakeholder deliberation and policy discussion
• Educational demonstrations of multi-scale modeling

Not Approved For

• Regulatory compliance determinations
• Automated decision-making or policy optimization
• Predictive forecasting of specific outcomes
• Sole basis for irreversible resource allocation

---

Access

The framework is positioned as a decision-support tool for deliberation, not a predictive engine. Reference implementation available under Apache 2.0 license.

Download Full Whitepaper (PDF)

---

Framework developed by Khipu Research Labs. For inquiries: info@krlabs.dev