econometrics

Question-to-target connection

Record whether work targets an economic relationship, causal effect, forecast, model restriction or methodological property.

1. Which economic question or recurring econometric problem motivates the work? definition
2. What quantity, hypothesis or prediction would count as answering that question? measurement

Basis of disciplinary membership

Record the convention under which an application or theoretical contribution belongs to econometrics, including legitimate overlap.

1. What connects this work to econometrics beyond its use of a statistical technique? boundary
2. Which disciplinary source supports this placement, and does it recognise overlapping membership? provenance

Economic variable operationalisation

Record how concepts such as income, prices, productivity or expectations are represented, transformed and compared.

1. How is each target economic construct represented, including units, aggregation, deflation or proxy choices? measurement
2. Which measurement errors, revisions or definition changes could alter the interpretation of the relationship? boundary

Observation process

Record sampling, selection, attrition, timing and dependence features that constrain econometric methods.

1. How were units selected and observed, and which population and period can they represent? provenance
2. Which serial, clustered, spatial or cross-sectional dependencies must the analysis accommodate? measurement

Identification argument

Record whether the target is uniquely recoverable, bounded or unidentified under the stated model and assumptions.

1. Which assumptions connect the target quantity to the observable distribution? definition
2. Do those assumptions imply point identification, partial identification or non-identification? boundary

Intervention claim warrant

Record assignment, exclusion, comparability or structural assumptions and the populations or regimes over which conclusions are claimed.

1. How does the design address confounding, simultaneity, selection or other relevant sources of endogeneity? boundary
2. What additional assumptions are needed to use the result for a new population, policy or equilibrium? action

Procedure validity

Record the conditions supporting estimation and inference, including finite-sample limitations and relevant asymptotic arguments.

1. Which properties justify the estimator for this target and data structure, and under what conditions? definition
2. How are uncertainty estimates affected by dependence, weak identification, model selection or limited sample size? measurement

Objective-specific validation

Record specification checks, sensitivity analyses, forecast evaluation and reproducibility evidence without treating them as interchangeable guarantees.

1. Which diagnostics or sensitivity analyses address the assumptions most consequential for the stated conclusion? action
2. For predictive work, how are performance and uncertainty evaluated on appropriately separated observations without future-information leakage? measurement
3. Can the reported results be reproduced from the documented data transformations and computational procedure? provenance

Versioned field placement

Record verified labels and codes, their scheme versions and the distinctions each scheme makes.

1. Which verified entries in JEL, MSC, UDC, DDC or other relevant schemes cover econometrics, and in which editions? provenance
2. How does each scheme distinguish econometric theory, applied econometrics and neighbouring statistical or economic fields? boundary

Institutional and literature markers

Link learned societies, journal scopes, degree curricula and defining handbooks to the specific aspects of econometrics they document.

1. Which society statements, journal scopes and degree curricula explicitly identify econometrics as a field or specialisation? provenance
2. Which handbooks or methodological reviews support the proposed coverage, and where do their definitions differ? boundary

Check these first

Recalled without web access and unsourced; every item is a lead to verify.

• This describes the academic discipline, rather than its practitioners or literature; no narrower registry sense was supplied.
• The Econometric Society and its journal Econometrica are established institutional markers; the listed kinds overlap rather than forming an exclusive classification.
• No sources were consulted; classification details should be verified before publication, and the field has no single intrinsic measurement scale or universal technical standard.

1. Which of these check these first hold for the sense of econometrics this model covers, and on what evidence? provenance

Kinds and varieties

Recalled without web access and unsourced; every item is a lead to verify.

• Theoretical econometrics
• Applied econometrics
• Microeconometrics
• Macroeconometrics
• Time-series econometrics
• Panel-data econometrics

1. Which of these kinds and varieties hold for the sense of econometrics this model covers, and on what evidence? provenance

Identifiers and schemes

Recalled without web access and unsourced; every item is a lead to verify.

• JEL Classification System - C01 - Econometrics; maintained by the American Economic Association within category C, Mathematical and Quantitative Methods.

1. Which of these identifiers and schemes hold for the sense of econometrics this model covers, and on what evidence? provenance

Real-world use

Recalled without web access and unsourced; every item is a lead to verify.

• Estimating effects of policies or interventions when the research design supports causal identification
• Forecasting economic quantities such as inflation, employment and output
• Estimating consumer demand, price elasticities and firm behaviour
• Testing economic theories against observed data
• Estimating and evaluating models of financial returns and risk

1. Which of these real-world use hold for the sense of econometrics this model covers, and on what evidence? provenance

Failure modes and hazards

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• Endogeneity, including omitted confounding, simultaneity and some forms of measurement error, can invalidate coefficient interpretations.
• Weak instruments or failure of identifying assumptions can make causal estimates unreliable.
• Ignoring nonstationarity, serial dependence or structural breaks can produce misleading time-series results.
• Incorrect treatment of heteroskedasticity, clustering or sample selection can invalidate inference.
• Specification searching, multiple testing and selective reporting can exaggerate evidence.

1. Which of these failure modes and hazards hold for the sense of econometrics this model covers, and on what evidence? provenance

Neighbouring kinds and how to tell them apart

Recalled without web access and unsourced; every item is a lead to verify.

• Statistics - Statistics develops methods for learning from data generally; econometrics adapts and develops these methods around economic questions, models and identification problems.
• Mathematical economics - Mathematical economics formalises economic reasoning; econometrics connects models and hypotheses to observed data through estimation and inference.
• Economic statistics - Economic statistics emphasises constructing and describing economic data and indicators; econometrics emphasises estimating relationships and testing models using such data.
• Causal inference - Causal inference studies intervention effects across disciplines; econometrics overlaps substantially but also includes forecasting and estimation without causal claims.
• Machine learning - Machine learning often emphasises predictive performance and flexible algorithms; econometrics also emphasises economic interpretation, identification and statistical inference, with substantial methodological overlap.

1. Which of these neighbouring kinds and how to tell them apart hold for the sense of econometrics this model covers, and on what evidence? provenance