๐Ÿ“˜ Chapter 7

Reporting and Visualization
Naguib Lallmahomed ยท naglal@linux-mauritius.com

7.1 Result Presentation

Principles of Effective Reporting:

PrincipleDescription
ClarityResults should be easy to understand
CompletenessAll essential information included
ConcisenessNo unnecessary information
ConsistencyFormatting is uniform
TransparencyMethods clearly described

Essential Elements of a Results Table

Table 1: Determinants of Earnings โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€ (1) (2) (3) OLS 2SLS FE โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€ Education 0.089*** 0.132** 0.095*** (0.012) (0.018) (0.014) Experience 0.026*** 0.024*** 0.025*** (0.008) (0.009) (0.008) โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€ N 1,000 1,000 1,000 Rยฒ 0.456 0.423 0.389 F-statistic 45.23 38.12 52.67 โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€ Notes: *** p<0.01, ** p<0.05, * p<0.10. Standard errors in parentheses. Column (1) uses OLS. Column (2) uses IV with QOB instruments. Column (3) uses Fixed Effects.
Best Practices:

7.2 Publication-Ready Figures

Types of Figures

Figure TypeBest ForExample
Scatter PlotRelationshipsX vs Y
Bar ChartComparisonsCoefficients across models
Line ChartTrendsTime series
HistogramDistributionsResiduals
Box PlotSummary statisticsGroup comparisons
Coefficient PlotModel comparisonOLS vs IV vs FE

Coefficient Plot (Forest Plot)

Education โ”œโ”€โ”€ OLS โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–‘โ–‘โ–‘โ–‘โ–‘โ–‘ 0.089 [0.065, 0.113] โ”œโ”€โ”€ 2SLS โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–‘โ–‘ 0.132 [0.097, 0.167] โ””โ”€โ”€ FE โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–‘โ–‘โ–‘โ–‘โ–‘โ–‘ 0.095 [0.068, 0.122] Experience โ”œโ”€โ”€ OLS โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–‘โ–‘โ–‘โ–‘โ–‘โ–‘โ–‘โ–‘โ–‘โ–‘โ–‘โ–‘โ–‘โ–‘ 0.026 [0.010, 0.042] โ”œโ”€โ”€ 2SLS โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–‘โ–‘โ–‘โ–‘โ–‘โ–‘โ–‘โ–‘โ–‘โ–‘โ–‘โ–‘โ–‘โ–‘ 0.024 [0.006, 0.042] โ””โ”€โ”€ FE โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–‘โ–‘โ–‘โ–‘โ–‘โ–‘โ–‘โ–‘โ–‘โ–‘โ–‘โ–‘โ–‘โ–‘ 0.025 [0.009, 0.041]

Residual Diagnostic Plots

1. Residuals vs Fitted
Residuals โ†‘ โ”‚ o o โ”‚ o o o โ”‚ o o o o โ”‚ o o o o โ”‚ o o o โ”‚ o o โ”‚ o o โ”‚ o o โ”‚ o โ””โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ†’ Fitted Values No pattern โ†’ Good Funnel shape โ†’ Heteroskedasticity
2. Normal Q-Q Plot
Theoretical Quantiles โ†‘ โ”‚ o โ”‚ o โ”‚ o โ”‚o โ”‚ o โ”‚ o โ”‚ o โ””โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ†’ Sample Quantiles Points on line โ†’ Normal S-shape โ†’ Heavy tails

7.3 Interactive Dashboards

An interactive dashboard allows users to explore data and results dynamically through filters, sliders, and clickable elements.

Dashboard Components

ComponentPurpose
FiltersSubset data
SlidersAdjust parameters
HoverGet details (tooltips)
Zoom/PanExplore detail
ExportSave results (tables and figures)

Dashboard Layout

โ”Œโ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ” โ”‚ MORISTAT โ€” Results Dashboard โ”‚ โ”‚ โ”Œโ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ” โ”Œโ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ” โ”‚ โ”‚ โ”‚ Filters โ”‚ โ”‚ Main Plot โ”‚ โ”‚ โ”‚ โ”‚ โ˜‘ Variable1 โ”‚ โ”‚ โ”‚ โ”‚ โ”‚ โ”‚ โ˜‘ Variable2 โ”‚ โ”‚ โ— โ— โ— โ— โ”‚ โ”‚ โ”‚ โ”‚ โ˜‘ Variable3 โ”‚ โ”‚ โ— โ— โ— โ— โ”‚ โ”‚ โ”‚ โ”‚ โ”‚ โ”‚ โ— โ— โ— โ— โ”‚ โ”‚ โ”‚ โ”‚ Period: โ”‚ โ”‚ โ”‚ โ”‚ โ”‚ โ”‚ [2000-2020] โ”‚ โ””โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”˜ โ”‚ โ”‚ โ”‚ โ”‚ โ”Œโ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ” โ”‚ โ”‚ โ”‚ Lambda: โ”‚ โ”‚ Summary Table โ”‚ โ”‚ โ”‚ โ”‚ [====โ—===] โ”‚ โ”‚ Variable Coef SE p-value โ”‚ โ”‚ โ”‚ โ””โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”˜ โ”‚ X1 0.45 0.12 0.001 โ”‚ โ”‚ โ”‚ โ”‚ X2 -0.23 0.08 0.004 โ”‚ โ”‚ โ”‚ โ””โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”˜ โ”‚ โ””โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”˜

7.4 Automated Reporting

Automated reporting generates complete, formatted reports from your analysis with a single command or click.

Benefits of Automated Reporting

BenefitDescription
ReproducibilityExact same results every time
EfficiencyNo manual copying/pasting
ConsistencyUniform formatting
Version ControlTrack changes over time
CollaborationEasy to share

Report Structure

MORISTAT โ€” Regression Report โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€ 1. Executive Summary โ€ข Key findings โ€ข Policy implications 2. Data Description โ€ข Sample size โ€ข Variable summary 3. Model Specification โ€ข Variables โ€ข Estimation method 4. Results โ€ข Coefficient table โ€ข Fit statistics 5. Diagnostics โ€ข Assumption tests โ€ข Outlier diagnostics 6. Robustness Checks โ€ข Sensitivity analysis โ€ข Alternative specifications 7. Conclusion โ€ข Summary of findings โ€ข Limitations โ€ข Future research

7.5 Publication Checklist

Before Submitting

Common Mistakes

MistakeFix
Missing standard errorsAlways include them
No significance starsAdd ***, **, *
Insufficient notesExplain methods, data
Poor figure qualityHigh resolution, clear labels
No diagnosticsReport tests and results

7.6 Chapter Summary

Key Takeaways

  1. Effective tables โ€” Clear, complete, and concise
  2. Professional figures โ€” High-quality, publication-ready
  3. Interactive dashboards โ€” Allow dynamic exploration
  4. Automated reporting โ€” Efficient, reproducible, consistent
  5. Publication checklist โ€” Ensure all elements are present
Checklist for Reporting

7.7 What's Next?

๐Ÿ“˜ Part IV: Putting It All Together

We will now combine everything into a complete research project:

  1. Research Design โ€” Formulating the question
  2. Data Collection โ€” Getting the data
  3. Exploratory Analysis โ€” Understanding the data
  4. Model Selection โ€” Choosing the right model
  5. Estimation โ€” Running the analysis
  6. Diagnostics โ€” Checking assumptions
  7. Robustness โ€” Testing sensitivity
  8. Reporting โ€” Presenting results
  9. Publication โ€” Sharing findings