The Windsor Research Project – Comparative Challenges

Comparative Challenges 

Given the context of the “post-fact world”, the challenges of presenting data on the challenges that Windsor and Essex County face become clear. Finding comparable and appropriate data is vitally important to not only compare apples to apples but to also set appropriate contexts for discussions in subsequent posts.

For many people, the simple fact that a particular policy, action or activity has been “done over there” is justification and reasoning for it to happen (or not happen) in Windsor or Essex County. This does not mean that inspiration can’t come from other communities or countries successes but context and comparability matter. You can’t just look at X and expect it to happen here,  as there are dozen of reasons why such a policy or action has been successful in other communities and may not be as successful. This post will attempt to establish foundation for providing context to the Windsor-Essex region.

A 2010 thesis from the University of Waterloo highlighted many of the challenges that are faced by mid-sized cities that are looking to revitialize. Although this thesis covered the topic of downtown renewal, it identifies as significant gap in scholarly research looking at mid-size communities and urban renewal in Canada (more or this in another post). The fact that this gap exists doesn’t dissuade some as comparable North American research are often used substitute. It is this comparability when localizing to the Windsor/Essex region that posses a significant challenge when modelling local renewal strategies on other communities.

Starting at a high level of population within our region we can see how different other countries can be. Despite being the largest community in our region, in a broader context Windsor is not that large when compared to comparably ranked communities from around the world

                                             16th Largest City-Region in Each Country*
Location Population Year Measured
Wenzhou, China 9,122,102 2016
Thane, India 1,818,872 2011
Fort Worth Texas 833,312 2015 (est)
Bournemouth/Poole Built-up area (UK) 466,266 2015 (est)
Bouchum, Germany 364,742 2015 (est)
Windsor CMA 329,144 2016
Grenoble France 158,346 2012
Toowoomba Queensland (Aus) 114,622 2015

*taken from appropriate national census databases.

The selection of cities above illustrates the different scale that can be found in the 16th largest city-region in a given country [Note: some of the Cities above are not regional as the country/state does not have regional units of measurement]. If you just examine the City of Windsor, we rank as the 23nd largest community in Canada and comparative communities are Washington DC; Stoke-on-Trent UK or Gelsenkirchen Germany all of which have larger populations and other localized features that provide them competitive advantages and disadvantages. Adding in broader Essex County brings our population 398,953 people which clearly ranks our region as a mid-sized entity but complicates the comparative process.

When we look at the US (as we tend to do) you find dramatic differences in how communities are governed and the specific powers they possess. In Canada municipalities exist at the whim of the Province; in America, Home Rule gives administrative divisions of states the same or similar powers as a state. This means that not only do communities in the US have far greater power to tax, spend and regulate but their rule and authority is grounded in constitutional law, unlike Canadian municipalities (Stanton Chapter 3).

These powers to tax, regulate and even default, means that US governments have far greater abilities to reshape their communities in a rapid manner. The example of Detroit illustrates this, as the city’s bankruptcy saw $7 Billion owed to bondholders, pension plans and creditors written off, freeing massive interest obligations to be redeployed on public works and services. At the same time, billions of dollars of private capital from both for profit and not-for-profit sources poured into the city. These are scales of dollars and financial tools that Canadian municipal politicians even in the largest cities can only dream about. For their part Canadian cities can’t declare bankruptcy in a formal sense, as entities of the Province the buck would be passed up to the next level of government, and to the provincial tax base. In the 1920s and 30s  with 11 percent of Ontario and Quebec municipalities defaulted leading to a series of amalgamations and municipal restructuring across provinces. Ironically this risk of default was a catalyst for the forming or the City of Windsor as we know it today, through an imposed municipal amalgamation by the Province that brought together many of the core neighbourhoods (Walkerville, Ford City, Sandwich Town etc) into Windsor proper.

In a modern context, a municipal bankruptcy would likely result in a provincial takeover of the municipality; vast service and spending cuts as well as increased property taxes. Provinces across Canada also place limits (in many cases) on the levels of debt that a municipality can hold (for more info on municipal debt conditions see here) and due to the lack of other financial tools and a reliance on provincial transfers, the ability for Canadian municipalities (particularly medium sized ones) to finance a transformative process is highly constrained.

Looking beyond North America, Europe is home to many of the pinnacles of walkable and urban communities. Yet they have access wide range of financial tools and measure that are not available in North America. Massive EU transfers for infrastructure and environmental projects have enabled local governments to finance infrastructure and economic development on the backs of taxpayers in other countries.

Many of these same cities (video) were laid down 1500+ years ago and the fastest vehicle on the road was a horse drawn wagon. Rome had a population of 400,000 people in 100 BC, this is a number the City of Windsor likely won’t pass this century and our county only now hovers around. The only way to live and do business was to be close to the location that socio-economic activity occurred which created a historical advantage for density. As a Country that has a history only a fraction of that length and a city that was born out of the age of steam 125 years ago, Windsor and Canada never shared those same formative roots and as a result developed differently.

Famed European public transit systems are built off a rail network that is unparalleled in its size and complexity compared to North America. These lines emerged during the industrial revolution when mechanized warfare ravaged the European continent. In the post-Napoleonic era, it was the railway lines that connected supplies to armies, brought troops forward and was the backbone for offensive operations for every European war after 1812. These same rail lines are now the skeleton of both intra/intercity mass transit (video on US rail networks which is pretty applicable to Canada, watch this). Due to the size, disperse populations and industries and a mismatch of timing and industrial progress Canada did not justify a rail network like Europe’s. Modern inter-modal cargo rail is only more efficient at moving goods than truck at distances exceeding 800 km, unfortunately the geographic and industrial densities of Canada did not justify a short distance rail networks thus eliminating the opportunity for regional commuter service outside of Canada’s largest urban centres which in turn created car dependency.

Looking at municipal political structure in Europe, party politics and proportional representation dominate local/regional governments.  This drastically different system has enabled “radical” parties like: Greens, Pirates, Communists and Nationalists to exercise institutional influences on councils and policies that impact cities and regions. Even if not elected, the fact that they exist and compete for elected office forces reactionary governing from the other major parties as they attempt to co-opt policy alternatives. Canada (US has Democrats and Republicans municipally who tend to behave in similar manners as the State and National counterparts) has only a few examples of political parties (Montreal and Vancouver) and none of them are elected proportionately. As a result, policy at a municipal level is formed in dramatically different manners in Canada compared to the US and Europe. The diverse and complex make up of municipal councils in Canada is a subject of an entire chapter of Stanton’s book on local government. The wide range of campaign financing mechanism, size and scope of councils, whether or not councilors are full or part-time and the underlying electoral makeup of a community (to name a few factors) all influence how communities are governed and in many cases make each community in Canada a unique political entity.

Drilling down to institutional level again context matters. Although many call for compact and urban institutional development in our community point to places like Detroit and Buffalo as examples of where institutional practice done right, again comparisons matter. The US health care system for example which allows charging patients for services puts non-profit institutions in a predicament of generating vast sums of revenue and needing to spend it. The Henry Ford Health Care system in 2015 generated $5.1 Billion in revenue and invested $459 million as community benefits in 1 year! In Buffalo, the hospital complex that is the key anchor of the revitalization initiative the Cancer centre alone turned a $50 million profit in 2017.

These institutions have the ability to city build in a way that Canadian counter parts with the largest of foundations can only dream of. The same argument can be made for US colleges and universities with sport revenues from College Football and Basketball and multi-billion dollar endowments. In Canada, these cash strapped institutions development occurs on the backs of provincial grant approvals based on lowest cost principles or fees for users.

What the above illustrates is that at the most basic level context matters. There are reasons why Windsor/Essex County has been built the way it has and why other communities have developed in their own pattern. Those same contextual challenges also hamper how this region can evolve. Beyond being inspired, to look to other communities for cut and paste solutions to perceived local challenges is folly and will not result in a community/region that is measurably better off. In fact in some cases by simply projecting solutions it creates expectations that are not realistic leading to dissatisfaction. By making uninformed comparisons between Windsor/Essex and other communities it in turn fuel divisive debates (particularly on Social Media). This drives polarization of political discourse and the narratives of change in our community. So much oxygen is consumed on these issues that numerous small issues fly under the radar that cumulatively will have greater consequences on our region’s future.

The Windsor Research Project – Forward

The Windsor Research Project

Forward 

What began as a essay on urban sprawl and some of the challenges faced by Windsor and broader Essex County has evolved into a much more. As 2018 progresses, Windsor-Essex County is in many ways at an inflection point, with the coming years charting the course of this region for the next generation and beyond. Although some might call this alarmist, the interaction of the various socio-economic ecosystems will see of our region fixed in a manner that will then curb the behaviour of various institutions and sectors creating a rigidity that can only be reversed through traumatic shock or a systematic deconstruction.

Despite the name related to this project, I will be looking at all of Essex County. The nature of broader Windsor and Essex County makes these challenges even more pronounced and makes tackling some of the issues that our region faces even more challenging. That being said, as the dominant socio-economic presence in the region Windsor will be the focus of many of the posts.

As a mid-size community there is very little in depth research on issues conducted in our community. This results in a pattern of big announcement being made, excitement and media coverage occurring and then nothing, at least until something unforeseen emerges. As a result, what is needed is some digging. Our region faces a number of significant challenges. Issues of housing stock quality; an expanding opioid crisis, a lack of economic diversification; a weak activist class; increasing political polarization; crumbling infrastructure; high rates of poverty; increasingly harmful urban sprawl; growing inequality; a degrading environment; poor educational attainment; issues of revitalization and/or gentrification; are a sample of some of the perceived/identified challenges. To list these challenges is not to be a naysayer or to speak down about our region. Not only is there data that fundamentally supports the existence of the issues listed above but in many cases they are impacting mid-sized cities across North America. It is by unpacking some of these challenges and the data that outlines them a rational policy discussion can occur. This is what this project is about, an attempt at a data driven analysis and commentary on the challenges that our region faces.

Fundamentally our region faces an existential threat not only from the challenges outlined above but the global pace of change, economic forces beyond our control and a growing internal division. The tragedy is that in many ways the City of Windsor can’t solve these problems alone and the only way to solve them is for our region to do something it doesn’t do very often, compromise. This outcome is not easy or even likely but what the subsequent posts in this series will explore the underlying data that justifies that shifts in thinking are required and I offer up my “informed?” opinions on some of these issue.

Although the exact order and topics of the posts are to be determined, the initial posts will form a foundation for subsequent posts by providing context and framework that illustrates my perspective on issues and some underlying macro level factors that shape the region as a whole.  Hopefully this will tie together into a cohesive narrative.

Hollowing of the Middle

I previously shared a map  twitter (see below) 2006 AT Household MEdian income comparision

What this map shows is the ratio of the After Tax Median Household Income of each Dissemination Area as a ratio to the same measure in Essex County. For clarity, it was $62,122 which means ares showing up in black have a median income 0-30% of the overall regional median income, the pale yellow 170%-247% the median income (white has no data).

A decade and a recession later the map looks different.

[Note the map looks physically different as Statistics Canada changed their default projection shape file for Canada between 2006 and 2011, I couldn’t track down a conversation file]

2016 AT Household MEdian income comparision

So what has changed? Well the median income of the region actually marginally declined to $62,075 while across Canada the median household income rose by nearly 10%.

Comparing the two maps you can see a significant change. Much of Windsor situated north of EC Row, areas of fuschia and light purple have been replaced by swaths of dark purple. The exception to this is Old Riverside (Ward 6) where pockets of orange of solidified. These mappings align with same areas that showed high rates of low income and lower rates of educational attainment in many of these same areas. .

The other big change is the growth in the pale/bright yellow in Lasalle, Lakeshore and South Windsor. Although the top of that rate has lowered from 247% to 217% of the median there are greater concentrations of these pockets in certain area.

Number of Census DA in Middle Median Income Ratios -Essex County
2006 2016
90%-110% 155 114
60%-140% 548 471

The middle class has geographically shrunk in Essex County with the number of neighbourhoods that you can define as middle class (from a statistical standpoint) have clearly declining. Although these neighbourhood do include people of higher (and lower) incomes, the medians illustrate exactly where the middle family is. Across Essex County, what has become clear is that wealth has become more centralized in certain neighbourhoods and for many the opportunity to be successful is dictated by where they live.

Windsor’s Unemployment Rate is SOFT

Back in Feb. I was interviewed by Dave Battegello of the Windsor Star on the City’s unemployment rate. At the time our City’s unemployment had fallen from 6% in December to 4.6% in January.

In the interview although I agreed that the drop in unemployment was good news, I cast some healthy skepticism on the data:

Frazier Fathers, manager of community impact for the local United Way, said the last month’s jobless number for Windsor may be good news, but whether it’s really reflective of the employment sector locally remains to be seen.

“Statistics Canada’s survey is a relatively small sample,” he said. “Sometimes month to month it may be higher or lower. What you really want to look at is the trend. If the number remains the same next month and the month after, that would be really good sign.”

Poverty does remain high in Windsor and the job participation rate — those in the community actively working or seeking a job — is about five per cent lower in Windsor than the provincial average, Fathers said.

“You have fewer in our economy who are working. We have lost a lot of good-paying jobs and some jobs have been replaced with lower paying jobs,” Fathers said. “Seeing the low unemployment number is good news, but whether the number is real remains to be seen.”

This opinion wasn’t that popular in some circles.

For those that don’t know, the unemployment rate is calculated through a monthly survey across the country, the Labour Force Survey (full guide and details of the survey can be found here). In summary, Statistics Canada surveys a rolling sample of people in our region (and in regions across the country) on a monthly basis with approximately 1/6 of the sample turning over each month, with people dropping off and being added in. A selected person would cycle through the labour force survey in 6 months. It is from that sample that the local employment, unemployment, participation, and other rates are calculated.

So give the design of the survey a month to month decline of a significant nature is a rare event. The rate drop from December to January was triggered by 3,700 people in the Windsor CMA finding work that month, a significant change given the lack (from my recollection) of significant hiring announcements. Given this along with the fact that this change represented only the 3rd time in a 15 months the participation rate rose above 61% it told me that this number was soft. By soft I mean that it was more of a statistical vagabond rather than a true indicator of the local economy.

Now, 3 months later I am ready to say I was right, that number was Soft! Although I would agree that January was a good month for the Windsor CMA from an employment standpoint, despite the fanfare awarded to the sudden drop in unemployment those gains have slowly been given back. Although total employment is actually up since January that is only true if the CMAs population grew by 1,600 people as the participation rate has dropped back to 60.5% (it has averaged 60.3% since Dec 2016). The actual labour force size has only changed by 100 people between December and April’s employment numbers with the exact same employment rate (57.1%).

The fact that the unemployment number has subsequently inched back up by equal intervals (0.3%) hints at a over representative sample being added in January. As the chart below illustrates there is a steady uptick month after month in the data.

Unemployment no error

Beyond this slow but steady up tick in the intervening months the other factor that I want to touch on is the margin of error for our local labour force data. Each month there is 0.8% standard error on the reported value. Almost a full percent in variation! The graph below shows the same rates with their confidence range:

Unemployment

Given that we are adding almost a full percentage (or subtracting) the question is why are celebrating this number every month? This is why economists call the Labour Force Survey as a “random number generator” and actually have turned the data release into a bit of a guessing game each month on twitter #LFSGuesses

Know Your Ward: Summary

As a part of an ongoing blog series, I will be digging into some of the socio-economic data for the 10 Wards in Windsor. I would note that Census data doesn’t not exactly align with the Windsor Ward map as some census dissemination areas straddle ward boundaries there is some minor variation in the data posted here and the actual for the Ward.

Windsor Wards

Demographics Ward 1 Ward 2 Ward 3 Ward 4 Ward 5
Total Population 2016 22,395 23,590 19,766 23,757 19,291
Total Population 2011 21,970 22,674 19,141 23,392 19,149
Average Population Density (Per Square KM) 2100.67 3462.6 5749 3765 273
% Pop under 19 22.98% 13.99% 17.80% 21.80% 19.20%
% Pop over 65 22.13% 20.10% 18.01% 14.40% 18.33%
Total Single Parent Families 970 1700 1295 1760 1525
% of Female Led Single Parent Families 75% 84.40% 82.60% 82.10% 80.3%
Demographics Ward 6 Ward 7 Ward 8 Ward 9 Ward 10
Total Population 2016 22,288 26,584 17,821 20,739 20,956
Total Population 2011 22,237 24,996 17,531 19,991 19,809
Average Population Density (Per Square KM) 5512 2871 3118 2217 2315
% Pop under 19 17.98 22.97% 24.74% 27.90% 27.80%
% Pop over 65 22.92% 20.40% 18.37% 12.20% 15.23%
Total Single Parent Families 1385 1284 1593 865 925
% of Female Led Single Parent Families 78.70% 80.40% 83.37% 79.19 82.50%
Income Ward 1 Ward 2 Ward 3 Ward 4 Ward 5
After Tax Median Income $35,365 $19,379 20523 $26,990 $28,235
After Tax Average Income $43,818 $23,401 25182 $31,242 $31,408
Low Income Rate (LIM) 8.90% 44.65% 44.94 28.78% 19.95%
% of population in the bottom income decile 7.50% 35.87% 33.50% 19.40% 13.01%
% of population in the top income decile 17.90% 1.67% 2.50% 5.14% 2.60%
Income Ward 6 Ward 7 Ward 8 Ward 9 Ward 10
After Tax Median Income $32,922 $31,721 $26,608 $31,843 $27,569
After Tax Average Income $38,685 $35,904 $29,271 $38,930 $33,683
Low Income Rate (LIM) 13.85% 12.04% 28.74% 11.85% 21.12%
% of population in the bottom income decile 9.40% 6.20% 21.28% 7.60% 13.70%
% of population in the top income decile 7.20% 8.05% 2.00% 8.70% 8.30%
Total Occupied Dwellings Ward 1 Ward 2 Ward 3 Ward 4 Ward 5 Ward 6 Ward 7 Ward 8 Ward 9 Ward 10
% of Public Transit Users to reach Employment 1.10% 12.70% 10.30% 7.20% 6.08% 4.10% 2.02% 5.70% 1.60% 2.60%
Total – Occupied private dwellings by number of bedrooms Ward 1 Ward 2 Ward 3 Ward 4 Ward 5
  No bedrooms 0% 1% 3% 0% 0%
  1 bedroom 2% 25% 42% 15% 14%
  2 bedrooms 16% 29% 29% 31% 34%
  3 bedrooms 49% 31% 17% 38% 38%
  4 or more bedrooms 33% 15% 8% 16% 13%
Total – Occupied private dwellings by number of bedrooms Ward 6 Ward 7 Ward 8 Ward 9 Ward 10
  No bedrooms 1% 0% 0% 0% 1%
  1 bedroom 20% 3% 14% 2% 2%
  2 bedrooms 27% 22% 26% 13% 17%
  3 bedrooms 39% 45% 48% 46% 47%
  4 or more bedrooms 14% 29% 11% 39% 33%

 

Household Wealth Ward 1 Ward 2 Ward 3 Ward 4 Ward 5 Ward 6 Ward 7 Ward 8 Ward 9 Ward 10
Number of Households with and income greater than $150,000 1005 (12.5% of total households) 70 (0.7%) 150 (1.44%) 345 (3.24%) 170 (1.8%) 495 (4.6%) 700 (7.01%) 165 (2.3%)] 650 (9.5%) 575 (8.4%)
Standard Deviation of AT Median Income
Ward 1 Ward 2 Ward 3 Ward 4 Ward 5 Ward 6 Ward 7 Ward 8 Ward 9 Ward 10
3527.49 5898.6 4254.4 7449.82 3987.78 5000.08 3567.87 5560.67 4932.81 5596.17
Top 5 Industries of Employment
Ward 1 Ward 2 Ward 3
31-33 Manufacturing 1825 (17.5%) 31-33 Manufacturing 1,795 (19%) 31-33 Manufacturing 1250 (16%)
62 Health care and social assistance 1355 (13%) 72 Accommodation and food services 1,075 (11%) 44-45 Retail trade 960 (12%)
61 Educational services 1160 (11.1%) 44-45 Retail trade 980 (10.2%) 72 Accommodation and food services 930 (12%)
44-45 Retail trade 1045 (10%) 62 Health care and social assistance 970 (10%) 62 Health care and social assistance 850 (11%)
72 Accommodation and food services 820 (7.8%) 56 Administrative and support, waste management and remediation services 890 (9.2%) 56 Administrative and support, waste management and remediation services 665 (9%)
Ward 4 Ward 5 Ward 6
31-33 Manufacturing 2120 (18%) 31-33 Manufacturing 2130 (23%) 31-33 Manufacturing 2320 (22%)
62 Health care and social assistance 1440 (13%) 44-45 Retail trade 1085 (12%) 62 Health care and social assistance 1415 (13%)
72 Accommodation and food services 1210 (11%) 62 Health care and social assistance 1005 (11%) 44-45 Retail trade 1060 (10%)
44-45 Retail trade 1140 (10%) 72 Accommodation and food services 855 (9%) 61 Educational services 820 (8%)
56 Administrative and support, waste management and remediation services 810 (7%) 56 Administrative and support, waste management and remediation services 655 (7%) 72 Accommodation and food services 680 (6%)
Ward 7 Ward 8 Ward 9
31-33 Manufacturing 2655 (21%) 31-33 Manufacturing 1680 (23%) 31-33 Manufacturing 2280 (22%)
62 Health care and social assistance 1780 (14%) 44-45 Retail trade 965 (13%) 62 Health care and social assistance 1240 (12%)
44-45 Retail trade 1280 (10%) 62 Health care and social assistance 790 (11%) 44-45 Retail trade 1025 (10%)
72 Accommodation and food services 930 (7.5%) 72 Accommodation and food services 685 (9.4%) 72 Accommodation and food services 855 (8.4%)
61 Educational services 915 (7.4%) 56 Administrative and support, waste management and remediation services 470 (6.5%) 61 Educational services 710 (7%)
Ward 10
31-33 Manufacturing 1645 (18%)
62 Health care and social assistance 1180 (12.7%)
44-45 Retail trade 1115 (12.3%)
72 Accommodation and food services 755 (8.3%)
61 Educational services 745 (8.2%)

Book List

A few people have been asking where is my blog post/series on Windsor, Sprawl, Housing etc. going to be posted – short answer is that it is coming. In the meantime, if you are interested in the subject, here is the Book List that forms the foundation for that work. In the last year or so I have either read or am currently in the process of reading all of these books. Assuming I don’t expand this book list, as for why it is taking me so long, I blame Lucy!

IMG_20170313_091821_415

(not really cause who could blame that face!)

Christmas in September… Putting money where our mouths are.

On Wednesday, the next batch of Census data is released and it is the only standalone data set of the year: Income Data…

In 2011, the Census tracked the status of Windsor in 2010 during the teeth of the recession. The question at hand is how far has Windsor and Essex County come from the from that low point. In 2011, Windsor was home to the highest rates of low income people living in low income neighbourhoods in Canada; 1 in 4 children were growing up in Poverty; 44% of single mothers lived in poverty are just some of the top line items.

When mapped it looked like this:Windsor Population Living in Low Income 2011

One of the more interesting maps actually comes from the Median Income levels of each of these neighbourhoods.

Median Income

Obviously median income shows what the middle income of the population of income earners is within a particular space. The scaling I used on this data is a broader than has been previously mapped in our community.

What to Watch For Tomorrow: 

  • How big of a swing in low income % occurs
    • There are going to be major gains in poverty reduction in our community, largely because of the improvement in the overall economy. What is happening at a neighbourhood level? Some neighbourhoods had poverty rates in 2011 in excess of 75%, even if significant gains are made what are the poverty levels in these areas? Are we willing to celebrate 1 in 4 in poverty in some areas
    • What about specific demographic groups in our single parents, seniors and children fair?
  • How does median income change in our region? Based on the mapping above basically 1/3 of the neighbourhoods in Windsor had a median income less than the poverty line. How has that improved.
    • Also looking at the urban/suburban spread. With the exception of Walkerville (5 top richest neighbourhoods in all of Essex County in 2011) how does the core do in comparison to the suburban fringe and the neighbouring suburban municipalities?
    • Gender split in median income isn’t something that I have looked to closely at but it would be interesting to see how that has changed over time.
  • How do these numbers compare to 2006 and 2001 prior to the great recession?

Once this data is available a big thing to consider is how we build resiliency in our community. If the swings that we see are largely just driven by economic cycles the question becomes how do we invest now to ensure that during the next downturn things don’t get as bad as they did in 2011.