How concentrated is Toronto's growth, and what would balance look like?
Executive Summary
Toronto's economic activity is heavily concentrated. The top 5 wards (20% of the city) capture a disproportionate share of every measured metric. The bottom 10 wards (40% of the city) collectively have less activity than the top 2 wards alone in most categories.
This concentration is not random — it's systematic. Wards that score high on one metric tend to score high on all of them, and vice versa. The correlation between building permits and business licences is 0.748, indicating that investment clusters geographically.
Key Findings
The top 5 capture the majority. Across all four metrics, the top 5 wards hold between 23% and 38% of city-wide totals. The bottom 10 hold as little as 20%.
Growth reinforces itself. Strong cross-metric correlations mean wards with more building permits also attract more businesses and more development applications. There is no evidence of natural rebalancing.
The gap to median is achievable. For the bottom 5 wards, the gap to the city median score (0.342) ranges from 0.20 to 0.30. These are large but not insurmountable gaps, especially if targeted interventions focus on the weakest metric per ward.
Concentration Analysis
Share of city-wide totals held by the top 5 wards vs. the bottom 10:
Metric
Top 5 Share
Bottom 10 Share
Ratio
Building Permits
32%
24%
1.4x
Dev Applications
38%
20%
1.9x
Business Licences
31%
29%
1.1x
Childcare Capacity
23%
32%
0.7x
Extreme Comparison: Spadina-Fort York vs. Scarborough-Rouge Park
Metric
Spadina-Fort York (#1)
Scarborough-Rouge Park (#25)
Ratio
Building Permits
15,076
3,302
4.6x
Dev Applications
2,236
544
4.1x
Business Licences
10,524
2,720
3.9x
Childcare Capacity
3,099
2,085
1.5x
Metric Correlations
How strongly do the four metrics move together across wards?
Metric A
Metric B
Correlation
Building Permits
Dev Applications
0.744 (strong)
Building Permits
Business Licences
0.748 (strong)
Building Permits
Childcare Capacity
0.530 (moderate)
Dev Applications
Business Licences
0.577 (moderate)
Dev Applications
Childcare Capacity
0.194 (weak)
Business Licences
Childcare Capacity
0.087 (weak)
Path to Median: Bottom 5 Wards
What it would take for the lowest-scoring wards to reach the city median score of 0.342:
Ward
Current Score
Gap to Median
Biggest Deficit
Scarborough Centre
0.263
0.080
Childcare Capacity (+0.35)
York South-Weston
0.251
0.091
Childcare Capacity (+0.25)
Don Valley North
0.238
0.104
Business Licences (+0.31)
Etobicoke Centre
0.212
0.130
Business Licences (+0.34)
Don Valley East
0.182
0.160
Business Licences (+0.28)
Recommendations
Break the concentration cycle. Growth incentives (tax breaks, streamlined approvals, infrastructure investment) should be geographically targeted at wards scoring below 0.2. The current pattern — where investment attracts more investment — will not self-correct.
Focus on each ward's weakest metric. Rather than a blanket approach, identify the single biggest deficit per ward and target it. For Scarborough-Rouge Park, the priority is business licences (norm score: 0.016). For Don Valley North, it's business licences as well (0.028). Childcare is the most evenly distributed metric and needs the least rebalancing.
Set measurable targets. Use the median score (0.342) as a city-wide benchmark. A reasonable 5-year goal: reduce the number of wards scoring below 0.2 from 7 to fewer than 3.
Monitor quarterly. Re-run this scoring framework each quarter as new data is published. Track whether the concentration ratios are tightening or widening. If the top-5 share of building permits exceeds 38%, concentration is worsening.
Confidence and Limitations
Data sources: Four datasets from Toronto Open Data (Building Permits, Development Applications, Business Licences, Child Care Centres). Scored 2026-03-29. Weights: Building Permits 35%, Dev Applications 25%, Business Licences 25%, Childcare 15%.
What's missing: Employment data, transit accessibility, population density, housing affordability, and public investment spending. These would provide a fuller picture of whether concentration is a problem or a natural outcome of urban geography.
Interpretation: Concentration is not inherently negative — downtown cores naturally attract more activity. The concern is when outer wards show persistently low activity across all metrics, suggesting structural barriers rather than natural variation. This report measures the degree of imbalance; policy decisions should weigh additional context.