Research Paper Rubric for Doctoral Economics
Moving beyond basic mechanics to novel contribution is the primary hurdle for PhD candidates. By distinguishing Methodological & Quantitative Rigor from Inference & Critical Robustness, this tool helps faculty pinpoint where students struggle to link math to economic intuition.
Rubric Overview
| Dimension | Distinguished | Accomplished | Proficient | Developing | Novice |
|---|---|---|---|---|---|
Theoretical Framing & Contribution20% | The student demonstrates a sophisticated command of the economic canon, synthesizing disparate literature streams to construct a nuanced theoretical framework that precisely isolates a novel contribution. | The research is thoroughly positioned within the literature with a logically derived theoretical model; the gap is clearly identified and the contribution is explicitly argued. | The work demonstrates competent knowledge of relevant economic literature and establishes a functional theoretical basis for the research, though the synthesis may be standard or formulaic. | The student attempts to situate the research within the field but relies on summarization rather than synthesis, and the theoretical link to the hypothesis is tenuous or under-explained. | The work fails to engage with the economic canon; the theoretical framework is missing, fundamentally flawed, or unrelated to the research question. |
Methodological & Quantitative Rigor35% | Work demonstrates sophisticated technical mastery, utilizing advanced identification strategies or derivations to rigorously isolate mechanisms and rule out alternative explanations. | Work is thorough and technically sound, featuring a well-defended identification strategy, precise notation, and necessary robustness checks to support the main analysis. | Work executes core methodological requirements accurately using standard approaches; the model is correctly specified and mathematically valid, though it may lack extensive stress-testing. | Work attempts to apply a specific methodology or derivation but is hindered by inconsistent execution, minor mathematical errors, or gaps in the defense of the identification strategy. | Work is methodologically misaligned or incomplete, relying on inappropriate statistical tests, containing fatal mathematical errors, or lacking a coherent strategy for identification. |
Inference & Critical Robustness25% | The analysis demonstrates sophisticated economic intuition, using advanced robustness checks to systematically rule out alternative explanations and falsify competing mechanisms. | The work provides a thorough interpretation of economic magnitude and defends the main results with targeted robustness checks that address specific threats to validity. | The work accurately interprets the direction and statistical significance of coefficients and performs standard robustness checks required for the methodology. | The work interprets the basic sign of coefficients correctly but lacks economic context, and robustness checks are either generic, misapplied, or superficial. | The work presents raw statistical output without meaningful interpretation or fails to distinguish between correlation and causation. |
Academic Exposition & Style20% | The writing exhibits professional polish and rhetorical sophistication, engaging the reader through precise terminology and an elegant, logical progression of ideas that mirrors high-quality academic publications. | The paper is well-organized and clearly written, adhering strictly to field standards with strong mechanics and effective data presentation, though it may lack the stylistic economy of professional work. | The writing meets core academic requirements with functional clarity and standard organization, although the prose may be formulaic or lack smooth transitions between complex ideas. | The work attempts an academic tone and structure but is hindered by frequent mechanical errors, inconsistent formatting, or a lack of clarity in the progression of arguments. | The writing is fragmentary or informal, failing to adhere to basic academic standards for structure, citation, or mechanics, rendering the argument difficult to follow. |
Detailed Grading Criteria
Theoretical Framing & Contribution
20%“The Foundation”Evaluates the student's ability to position their research within the existing economic canon. Measures how effectively the student synthesizes prior literature to identify a gap and constructs a logical theoretical model or hypothesis. Focuses on the derivation of the research question and the novelty of the contribution.
Key Indicators
- •Synthesizes seminal and recent literature to establish the research context
- •Identifies a specific theoretical or empirical gap within the economic canon
- •Constructs a logical theoretical model or framework grounded in economic principles
- •Derives testable hypotheses or propositions directly from the theoretical assumptions
- •Articulates the specific marginal contribution to the sub-field
Grading Guidance
Moving from Level 1 to Level 2 requires shifting from a disconnected bibliography to a thematic review. A student at Level 1 merely lists summaries of papers, whereas a Level 2 student begins to group literature by theme or methodology, though they may struggle to clearly articulate where their own work fits or rely on a generic theoretical framework that is not tailored to their specific question. The transition from Level 2 to Level 3 marks the threshold of competence, defined by the successful derivation of a research question from a clearly identified gap. While Level 2 work describes the literature and proposes a topic, Level 3 work explicitly connects the two, utilizing a standard economic model or logical framework to generate consistent hypotheses. At this stage, the theoretical mechanism is functional and the logic is sound, even if the contribution is modest or the model is a direct application of existing work without modification. Moving from Level 3 to Level 4 involves a leap from application to adaptation. A Level 4 student does not just apply a standard model; they modify or extend theoretical assumptions to capture the specific nuances of their research question, ensuring a tight fit between the theory and the empirical strategy. Finally, reaching Level 5 requires elevating the work from a marginal contribution to a significant insight. At this distinguished level, the theoretical framing is elegant and parsimonious, offering a novel mechanism or generalization that challenges or significantly refines prevailing economic wisdom, rendering the paper potentially publishable in top-tier journals.
Proficiency Levels
Distinguished
The student demonstrates a sophisticated command of the economic canon, synthesizing disparate literature streams to construct a nuanced theoretical framework that precisely isolates a novel contribution.
Does the work demonstrate sophisticated understanding that goes beyond requirements, with effective synthesis and analytical depth in its theoretical framing?
- •Synthesizes conflicting or disparate streams of literature to justify the research gap (rather than just listing agreements).
- •Justifies specific theoretical modeling choices or assumptions against potential alternatives.
- •Articulates the contribution's magnitude and limitations with high precision relative to seminal works.
- •Derives hypotheses that address complex mechanisms or second-order effects.
↑ Unlike Level 4, the work goes beyond a thorough critique of existing literature to offer a sophisticated synthesis that bridges gaps or resolves tensions between theoretical perspectives.
Accomplished
The research is thoroughly positioned within the literature with a logically derived theoretical model; the gap is clearly identified and the contribution is explicitly argued.
Is the work thoroughly developed and logically structured, with well-supported arguments and polished execution of the theoretical model?
- •Organizes the literature review thematically to build a logical argument toward the research question.
- •Explicitly states the marginal contribution relative to specific prior studies (e.g., 'This paper extends Author X by...').
- •Presents a theoretical model or framework where assumptions and variables are clearly defined.
- •Anticipates and addresses at least one major theoretical counterargument or alternative explanation.
↑ Unlike Level 3, the work critically evaluates the quality or methodology of prior studies rather than simply reporting their findings.
Proficient
The work demonstrates competent knowledge of relevant economic literature and establishes a functional theoretical basis for the research, though the synthesis may be standard or formulaic.
Does the work execute all core requirements accurately, properly citing relevant literature and stating a clear hypothesis?
- •Cites seminal and relevant contemporary works to establish context.
- •Identifies a specific research gap, even if the justification is standard (e.g., lack of data or regional focus).
- •Proposes a hypothesis or model that is logically consistent with the cited literature.
- •Connects the research question to established economic theory without significant conceptual errors.
↑ Unlike Level 2, the literature review is organized by concept rather than author, and the theoretical model is complete enough to generate testable predictions.
Developing
The student attempts to situate the research within the field but relies on summarization rather than synthesis, and the theoretical link to the hypothesis is tenuous or under-explained.
Does the work attempt core requirements, even if execution is inconsistent or limited by gaps in the theoretical derivation?
- •Lists summaries of prior papers (annotated bibliography style) rather than integrating them.
- •Asserts a research gap without providing sufficient evidence that the gap exists.
- •Presents a theoretical framework that lacks definition of key variables or assumptions.
- •Includes citations that are tangential or fail to support the central research question.
↑ Unlike Level 1, the work includes relevant literature and attempts to construct a theoretical basis, even if the execution lacks cohesion.
Novice
The work fails to engage with the economic canon; the theoretical framework is missing, fundamentally flawed, or unrelated to the research question.
Is the work incomplete or misaligned, failing to apply fundamental concepts of theoretical framing?
- •Omits discussion of seminal literature or relies entirely on non-academic sources.
- •Fails to articulate a clear research question or hypothesis.
- •Presents no theoretical model or conceptual framework to guide the analysis.
- •Demonstrates fundamental misunderstandings of core economic concepts relevant to the topic.
Methodological & Quantitative Rigor
35%“The Engine”CriticalAssesses technical correctness and the validity of the identification strategy. Measures the execution of mathematical derivations, econometric specifications, and data handling. Focuses strictly on the mechanical accuracy of the proofs or statistical tests, separate from their interpretation.
Key Indicators
- •Executes mathematical derivations with logical precision and algebraic accuracy
- •Specifies econometric models that align directly with the theoretical framework
- •Validates identification strategies through appropriate robustness checks and placebo tests
- •Implements robust data cleaning procedures and handles missing values systematically
- •Calculates standard errors using appropriate clustering or correction methods
Grading Guidance
Moving from Level 1 to Level 2 requires shifting from fundamentally flawed or incoherent methodologies to recognizable economic tools, even if executed with mechanical errors. While a Level 1 submission relies on inappropriate estimators or contains fatal mathematical contradictions, a Level 2 submission attempts the correct identification strategy (e.g., Difference-in-Differences) but may mismanage data cleaning or neglect basic standard error clustering. The transition to Level 3 marks the competence threshold, where the core econometric specifications and mathematical proofs are mechanically correct; the student successfully runs the intended models without coding errors, although the approach may lack necessary robustness checks or sophisticated handling of endogeneity. To advance from Level 3 to Level 4, the work must demonstrate a rigorous defense of the identification strategy. This involves not just running the main regression correctly, but actively validating assumptions through parallel trends tests, placebo tests, or alternative specifications that rule out confounding variables. Finally, reaching Level 5 distinguishes a technically sound paper from a professionally polished contribution. At this level, the methodological execution is flawless and elegant; mathematical derivations are concise, data handling is transparently documented for reproducibility, and the quantitative rigor withstands the highest level of scrutiny expected in top-tier field journals.
Proficiency Levels
Distinguished
Work demonstrates sophisticated technical mastery, utilizing advanced identification strategies or derivations to rigorously isolate mechanisms and rule out alternative explanations.
Does the work demonstrate sophisticated technical mastery by rigorously defending the identification strategy against complex threats and executing derivations with high precision?
- •Executes sophisticated auxiliary tests (e.g., placebo tests, falsification tests, bounding exercises) to validate the identification strategy.
- •Formalizes mathematical derivations that seamlessly bridge theoretical assumptions with empirical specifications.
- •Demonstrates advanced handling of data complexities, such as non-random attrition or complex survey weights, without simplification.
- •Anticipates and mathematically addresses subtle threats to validity (e.g., dynamic selection bias) beyond standard controls.
↑ Unlike Level 4, the work goes beyond standard robustness checks to proactively stress-test the methodology against complex or theoretical counter-explanations.
Accomplished
Work is thorough and technically sound, featuring a well-defended identification strategy, precise notation, and necessary robustness checks to support the main analysis.
Is the identification strategy thoroughly defended with appropriate robustness checks and precise technical execution?
- •Includes relevant robustness checks (e.g., alternative specifications, subsample analyses) that confirm the stability of results.
- •Justifies the choice of estimator or model explicitly against potential endogeneity or violation of assumptions.
- •Presents mathematical proofs or derivations that are logically complete and free of notation errors.
- •Handles standard errors appropriately for the data structure (e.g., clustering, heteroskedasticity-consistency).
↑ Unlike Level 3, the work includes explicit robustness checks or sensitivity analyses rather than relying solely on the primary model specification.
Proficient
Work executes core methodological requirements accurately using standard approaches; the model is correctly specified and mathematically valid, though it may lack extensive stress-testing.
Are the econometric specifications and mathematical derivations technically correct and applied according to standard conventions?
- •Specifies the regression equation or mathematical model correctly given the research design.
- •Applies standard data cleaning procedures to handle missing values or outliers without introducing bias.
- •Calculates and reports statistical significance using appropriate tests for the data type.
- •Identifies the strategy for causal inference (e.g., Fixed Effects, IV) but may not extensively defend it against all threats.
↑ Unlike Level 2, the execution is technically accurate and free of mechanical errors that would invalidate the primary results.
Developing
Work attempts to apply a specific methodology or derivation but is hindered by inconsistent execution, minor mathematical errors, or gaps in the defense of the identification strategy.
Does the work attempt a specific methodological approach, despite technical errors or gaps in the identification strategy?
- •Attempts a recognized identification strategy but omits necessary conditions or assumptions (e.g., failing to discuss the exclusion restriction in IV).
- •Contains minor algebraic slips in derivations that do not collapse the entire argument.
- •Selects control variables or functional forms that are partially inconsistent with the theoretical framework.
- •Describes data handling procedures but leaves ambiguity regarding sample selection or exclusion criteria.
↑ Unlike Level 1, the work demonstrates a recognizable attempt to apply a valid methodological framework, even if the execution is flawed.
Novice
Work is methodologically misaligned or incomplete, relying on inappropriate statistical tests, containing fatal mathematical errors, or lacking a coherent strategy for identification.
Is the methodological approach fundamentally misaligned with the research question or mathematically unsound?
- •Misapplies fundamental statistical tests (e.g., using OLS on a nominal dependent variable without justification).
- •Presents mathematical derivations with logical breaks or fatal errors that invalidate the conclusion.
- •Fails to define the estimation strategy or model specification entirely.
- •Omits critical technical details regarding data sources, variable construction, or sample definition.
Inference & Critical Robustness
25%“The Insight”Evaluates the transition from statistical outputs to economic intuition. Measures the student's capacity to interpret coefficients, defend against alternative explanations through robustness checks, and discuss mechanisms. Focuses on the logical leap from 'statistically significant' to 'economically meaningful'.
Key Indicators
- •Translates coefficient magnitudes into tangible economic scenarios or policy implications
- •Designs robustness specifications to rule out specific confounding factors or alternative explanations
- •Articulates the causal mechanism linking the independent variable to the outcome
- •Evaluates the plausibility of results against existing theoretical or empirical literature
- •Justifies the selection of control variables and functional forms based on economic theory
- •Distinguishes clearly between statistical significance and economic meaningfulness
Grading Guidance
Moving from Level 1 to Level 2 requires the student to shift from merely pasting statistical software output to providing a basic verbal description of the results. While a Level 1 submission might list coefficients and p-values without context, a Level 2 submission correctly identifies the sign and significance of the estimates, though it may lack interpretation of magnitude or economic relevance. To cross the threshold into Level 3 (Competence), the student must interpret the coefficients in real-world terms (e.g., elasticities, dollar amounts) and include standard robustness checks. At this stage, the student demonstrates that the results are not artifacts of a single specification, even if the defense against alternative hypotheses remains generic. The transition from Level 3 to Level 4 involves a leap from mechanical reporting to critical argumentation. A Level 4 student does not simply run 'standard' checks but selects robustness tests that specifically target the most likely threats to validity (e.g., placebo tests, sample restrictions). They discuss *why* the result holds, linking statistical findings to a clear economic mechanism. Finally, achieving Level 5 (Excellence) requires a masterful synthesis where the student anticipates and systematically dismantles subtle alternative explanations. At this level, the distinction between statistical significance and economic significance is paramount; the student contextualizes the magnitude of the findings within the broader literature, demonstrating that the effect size matters for policy or theory, not just that it differs from zero.
Proficiency Levels
Distinguished
The analysis demonstrates sophisticated economic intuition, using advanced robustness checks to systematically rule out alternative explanations and falsify competing mechanisms.
Does the work effectively synthesize statistical evidence to proactively dismantle alternative economic explanations and discuss nuances like heterogeneity or external validity?
- •Conducts specific falsification or placebo tests to rule out spurious correlations.
- •Discusses effect heterogeneity (e.g., how results differ across subgroups) to refine the economic mechanism.
- •Explicitly contrasts the preferred economic mechanism against at least one competing theory using empirical evidence.
- •Translates statistical estimates into precise policy or theoretical implications with caveats regarding external validity.
↑ Unlike Level 4, the work does not just support its own hypothesis but actively and effectively attempts to falsify it through sophisticated testing of alternative mechanisms.
Accomplished
The work provides a thorough interpretation of economic magnitude and defends the main results with targeted robustness checks that address specific threats to validity.
Is the interpretation grounded in economic magnitude (not just significance) and supported by a logical strategy to address identification concerns?
- •Converts regression coefficients into interpretable economic units (e.g., elasticities, standard deviation changes).
- •Justifies the inclusion of specific control variables or fixed effects based on identification strategy.
- •Addresses potential endogeneity or selection bias explicitly in the text.
- •Links statistical findings clearly to the theoretical framework established earlier in the paper.
↑ Unlike Level 3, the interpretation quantifies the economic 'size' of the effect rather than just the statistical significance, and robustness checks are targeted rather than generic.
Proficient
The work accurately interprets the direction and statistical significance of coefficients and performs standard robustness checks required for the methodology.
Does the work correctly interpret the sign and significance of key variables and include baseline robustness checks?
- •Correctly identifies the direction of the effect and its statistical significance (p-values/t-stats).
- •Includes standard robustness checks common to the field (e.g., adding basic controls, changing sample periods).
- •Proposes a plausible economic mechanism for the observed results.
- •Avoids making causal claims that are strictly unsupported by the research design.
↑ Unlike Level 2, the robustness checks are relevant to the specific model used, and the interpretation accurately distinguishes between statistical significance and causal proof.
Developing
The work interprets the basic sign of coefficients correctly but lacks economic context, and robustness checks are either generic, misapplied, or superficial.
Does the work attempt to interpret the statistical output and provide some form of verification, even if limited by gaps in economic reasoning?
- •States whether the relationship between variables is positive or negative based on output.
- •Attempts robustness checks (e.g., adds variables) but fails to explain *why* they are necessary.
- •Confuses statistical significance (p-value) with economic importance (magnitude).
- •Relies heavily on technical jargon without translating it into economic intuition.
↑ Unlike Level 1, the student correctly reads the basic statistical output (sign and significance) and recognizes the need for some form of verification.
Novice
The work presents raw statistical output without meaningful interpretation or fails to distinguish between correlation and causation.
Is the work missing critical interpretations of the data or failing to address basic validity concerns?
- •Presents regression tables or charts with no accompanying textual interpretation.
- •Makes strong causal claims based solely on simple correlations without caveats.
- •Omits any discussion of robustness, sensitivity, or alternative explanations.
- •Misinterprets the meaning of coefficients (e.g., interpreting a log-log coefficient as a level change).
Academic Exposition & Style
20%“The Delivery”Evaluates the clarity, precision, and efficiency of the writing. Measures adherence to field-specific rhetorical standards (e.g., AER style), organization of the argument flow, and the quality of data visualization (tables/figures). Explicitly includes grammar and citation mechanics.
Key Indicators
- •Structures the narrative logically following standard economic research protocols (Intro, Model, Empirics, Conclusion).
- •Articulates complex economic arguments with precision, parsimony, and a formal academic tone.
- •Formats tables and figures to be self-contained, including clear notes, standard errors, and significance levels.
- •Integrates citations seamlessly to contextualize contributions within existing literature.
- •Adheres strictly to grammar, syntax, and specific formatting guidelines (e.g., AER style).
Grading Guidance
Moving from Level 1 to Level 2 requires shifting from a disorganized or colloquial draft to one that attempts a standard academic structure. The writing must abandon conversational tone for an attempt at formal register, even if transitions are clunky or the prose is verbose. Citations must be present to distinguish the work from opinion, even if formatting errors persist. To reach Level 3, the writer must demonstrate competence in economic rhetoric—specifically, the ability to separate the theoretical framework from the empirical strategy clearly. Tables must be formatted correctly (e.g., standard errors in parentheses, properly aligned decimals) rather than appearing as raw statistical software output. The argument flows logically without major gaps, though it may lack stylistic polish or optimal efficiency. The transition to Level 4 is marked by economy and precision. The author removes redundant text, ensuring the introduction acts as a concise roadmap rather than a summary. Tables and figures become fully self-contained with precise notes, allowing readers to understand results without consulting the text. Level 5 work exhibits the rhetorical sophistication of a top-tier journal submission; the narrative anticipates and preempts reader skepticism through careful phrasing, and the prose communicates complex ideas with absolute economy of words.
Proficiency Levels
Distinguished
The writing exhibits professional polish and rhetorical sophistication, engaging the reader through precise terminology and an elegant, logical progression of ideas that mirrors high-quality academic publications.
Does the writing demonstrate professional-grade clarity and rhetorical sophistication, integrating complex data and arguments with seamless transitions and precision?
- •Uses precise, field-specific terminology correctly without overuse or jargon-stuffing.
- •Tables and figures are self-contained (stand-alone captions) and professionally formatted.
- •Paragraph transitions explicitly link the previous point to the next, creating a seamless narrative flow.
- •Citations are flawlessly integrated into the sentence structure rather than merely listed.
↑ Unlike Level 4, the writing achieves a level of conciseness and rhetorical elegance that renders the reading effortless, rather than just clear and correct.
Accomplished
The paper is well-organized and clearly written, adhering strictly to field standards with strong mechanics and effective data presentation, though it may lack the stylistic economy of professional work.
Is the exposition thoroughly developed and logically structured, with clear adherence to style guides and effective data visualization?
- •Structure follows standard academic conventions (e.g., Intro, Methods, Results) with clear headings.
- •Grammar and syntax are polished with no distracting errors.
- •Tables and figures are clear, labeled correctly, and explicitly referenced in the text.
- •Citations are mechanically correct and consistently applied throughout.
↑ Unlike Level 3, the argument flows logically between sections without disjointed jumps, and the style is consistently formal rather than functional.
Proficient
The writing meets core academic requirements with functional clarity and standard organization, although the prose may be formulaic or lack smooth transitions between complex ideas.
Does the work execute core stylistic and organizational requirements accurately, ensuring the argument is readable and the formatting is compliant?
- •Follows the required citation style (e.g., APA, Chicago) with only minor, non-systemic errors.
- •Paragraphs have clear topic sentences, though transitions between paragraphs may be abrupt.
- •Visuals (tables/figures) are present and legible but may look like raw software output rather than formatted exhibits.
- •Language is academic in tone, avoiding colloquialisms.
↑ Unlike Level 2, the work is mechanically sound and organized enough to be read without confusion, even if the style is repetitive.
Developing
The work attempts an academic tone and structure but is hindered by frequent mechanical errors, inconsistent formatting, or a lack of clarity in the progression of arguments.
Does the work attempt to follow academic conventions, even if execution is marred by frequent errors or organizational gaps?
- •Contains frequent grammatical or syntactical errors that occasionally impede meaning.
- •Citations are present but contain systemic formatting errors or inconsistencies.
- •Visuals are included but may be poorly labeled, blurry, or not referenced in the text.
- •Organization is discernible but disjointed (e.g., points jump around without logical connection).
↑ Unlike Level 1, the writing maintains a basic academic structure and attempts to cite sources, acknowledging the need for scholarly conventions.
Novice
The writing is fragmentary or informal, failing to adhere to basic academic standards for structure, citation, or mechanics, rendering the argument difficult to follow.
Is the work incomplete or misaligned, failing to apply fundamental academic writing and formatting concepts?
- •Uses informal or colloquial language inappropriate for doctoral research.
- •Missing critical structural elements (e.g., no clear introduction or conclusion).
- •Fails to cite sources or uses a completely incorrect citation format.
- •Visuals are missing where required or are completely uninterpreted.
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How to Use This Rubric
This evaluation tool focuses on the "publication readiness" of doctoral work, balancing technical accuracy with narrative flow. By weighing Methodological & Quantitative Rigor heavily, it ensures the identification strategy is sound before critiquing the nuance of the Theoretical Framing & Contribution.
When distinguishing between proficiency levels, look for the shift from mechanical correctness to intuitive argument. A high score in Inference & Critical Robustness requires the student to not only report coefficients but to defend them against alternative explanations using specific robustness checks.
MarkInMinutes can automate grading with this rubric, allowing you to focus on the economic implications rather than formatting feedback.
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