Assignment Overview
This phase requires the development of a comprehensive methodology and results section. The submission must integrate refined elements from Phases 1 and 2 while presenting cultured analytical approaches and empirical findings that address all three research questions established in your study.
Learning Objectives
- Upon completion of this phase, you should demonstrate the ability to:
- Apply advanced statistical modeling techniques using STATA software for business and accounting research
- Develop comprehensive methodological frameworks that address multiple research questions, providing a unified approach to addressing these questions.
- Present empirical results with professional academic standards.
- Validate model performance through appropriate diagnostic procedures.
- Synthesize statistical findings within established theoretical contexts
Required Submission Components
Section 1: Refined Introduction and Research Framework
- Research Questions: Present all three research questions with precise, testable formulations
- Hypotheses Development: State formal hypotheses corresponding to each research question
- Theoretical Framework: Concise integration of theory supporting methodological choices
- Study Significance: Brief explanation of contribution to business/accounting literatureDataset Overview: Source description, temporal coverage, sample characteristics
Section 2: Enhanced Literature Review
- Theoretical Foundations: Literature supporting the conceptual framework for all research questions
- Empirical Evidence: Prior studies examining similar research problems or methodological approaches
- Methodological Support: Academic sources justifying the statistical techniques employed
- Gap Identification: Clear articulation of research contribution to existing knowledge
- Model Development Rationale: Literature-based justification for analytical approach
Section 3: Research Methodology
Research Design: Overall analytical framework linking research questions to empirical strategyData Description:
- Sample selection criteria and justification
- Variable definitions and measurement approaches
- Descriptive statistics for key variables
Model Specification:
- Separate models for each research question
- Mathematical formulation of statistical models
- Variable selection rationale
Estimation Techniques:
- STATA procedures employed for each model
- Justification for chosen statistical methods
Assumption Testing:
- Diagnostic procedures for model validation
- Remedial measures for assumption violations
Robustness Checks: Additional analyses to confirm result stability
Section 4: Results and Analysis
- Descriptive Analysis:
- Sample characteristics and variable distributions
- Correlation matrices and preliminary relationships
Model Results:
- Separate presentation for each research question
- Coefficient estimates with statistical significance
- Model fit statistics and diagnostic measures
Hypothesis Testing:
- Formal testing results for each hypothesis
- Statistical significance and effect size interpretation
Additional Analyses:
- Sensitivity testing and alternative specifications
- Subgroup analyses were appropriate
Results Synthesis: Integration of findings across all research questions
Section 5: Robustness and Validation
- Model Diagnostics: Comprehensive testing of statistical assumptions
- Alternative Specifications: Results from alternative model formulations
Sensitivity Analysis: Impact of different sample selections or variable definitions
- Cross-Validation: Out-of-sample testing where applicable
- Limitation Discussion: Methodological constraints and their implications
Section 6: Academic Presentation Standards
- APA Formatting: Consistent citation style and reference formatting (Reference/ Ending Citation-single space)
- Table Presentation: Professional formatting of statistical results
- Figure Quality: Clear, publication-ready visualizations
- Writing Clarity: Academic prose with logical flow
- Integration Quality: Seamless incorporation of Phases 1-2 feedback
Section 7: Technical Documentation
Technical Requirements
Data Standards
Sample Size: Minimum 25,000 observations (10,000 for taxation studies) / Approved sample size by the course Professor.
Variables: Minimum 3 dependent variables, minimum 6 independent variables across all models, and control variables
Data Quality: Professional-level cleaning with documented procedures
Software Access
- STATA: Access Stata via the VLab
Links to an external site. if you are off campus, and AppsAnywhere
- Links to an external site. when you are using a campus computer
Replication: All analyses must be fully reproducible
Model Requirements
Multiple Models: Distinct analytical approaches for each research question
Statistical Rigor: Appropriate techniques for data characteristics and research objectives
File Submission Requirements
Primary Deliverables
Research Paper: Save your submission file as: “Teamname_Methodology_Results.docx”
- Integration of refined Phases 1 & 2 content
- Complete methodology and results sections
- A* journal formatting standards (Modified APA 7/ LCOB formatting-Refer to class instructions-Ending citations should be single-spaced)
- STATA Package:
- Clean dataset: “”Teamname_STATA__Final_Data.dta”
- Analysis code(STATA Comands): ” Teamname_Analysis.docx”
Organization Standards
File Naming: Consistent conventions across all submissions
Code Documentation: Clear comments enabling independent replication
Results Organization: Logical sequence matching paper presentation
Quality Control: Error-free files with professional presentation
Evaluation Emphasis
Methodological Rigor (40 points)
- A tasteful analytical framework addressing all research questions, utilizing appropriate statistical techniques with proper justification.
- Comprehensive diagnostic testing and validation procedures
Results Presentation (35 points)
- Clear, professional presentation of empirical findings
- Effective integration of multiple analytical components
- Publication-quality tables, figures, and statistical reporting
Academic Standards (25 points)
- A* journal-level writing and organization
- Proper integration of the theoretical framework with empirical analysis
- Comprehensive incorporation of previous phase feedback