15:25:38 housing units we have in the city.

It's just

15:25:41

15:25:45 1.4%, but I think when you started looking at these numbers a

15:25:49 little

15:25:52 bit closer after grouping them by income level, the

15:25:55 realization hits you 81% of these units

15:26:00 are occupied by extremely low, very low

15:26:03 and low income households so we're already talking

15:26:06 exacerbated

15:26:11 housing situation.

So this one

15:26:14 is, and the effort is when we

15:26:17 started doing this

15:26:21 analysis, you look at this same number of

15:26:24 units of a household, close to

15:26:28 96,000 households that face one problem or the other, but then

15:26:31 you group them in different ways and data people, we

15:26:34 find it so fascinating.

It's like now we start

15:26:37 looking by tenure,

15:26:41 occupied -- owner occupied versus

15:26:44 renter occupied.

It's clear,

15:26:47 just under one-half of renter occupied

15:26:50 households, they're one housing problem or the other, and part

15:26:53 of this is a consequence of we don't

15:26:56 have that data but it's attributable to the

15:27:00 housing cost burden, and I was looking at some of

15:27:03 the other AIs from nearby jurisdictions.

15:27:06

Pretty much all along the west coast and

15:27:09 even places on the east coast, it's the housing

15:27:13 cost burden that really contributes

15:27:17 to housing problems.

So this one is by income

15:27:20 level and tenure.

The blue bars are owner

15:27:24 occupied and the green ones are renter

15:27:27 occupied, and along the Y axis,

15:27:30 you see -- X axis, you

15:27:34 have, is it income?

Income

15:27:37 levels.

See?

So much for my new glasses.

15:27:40 On the X axis you have these percentages but clearly

15:27:43 a very high proportion of extremely low,

15:27:46 very low and low-income renter occupied

15:27:50 households have one housing problem

15:27:54 or the other.

This slide is

15:27:58 looking at housing problems and grouped them by race and

15:28:01 ethnicity, and the three bars,

15:28:05 the green is

15:28:08 renter occupied and the beige

15:28:12 is all occupied units.

The disproportionate housing

15:28:15 need, if you look at the bars on the African-American

15:28:20 community, the Hispanics, the Pacific Islanders the disproportionate

15:28:23 housing need really stands up, really high proportion

15:28:26 of households that belong to these race or

15:28:30 ethnic groups do have one or

15:28:33 more of the housing

15:28:37 problems.

Next.

So this slide, and we

15:28:41 always struggle with -- we don't like maps but

15:28:44 it's hard to explain it, but it's

15:28:47 clear, on one hand, you have these

15:28:50 owners with housing problems.

There's spatial distribution and what

15:28:53 you see are these census drives which are the

15:28:56 building blocks for the city of Portland, and then you have

15:29:01 renters.

Clearly on the renter side you see

15:29:07 a lot more dark census, which really means

15:29:10 this is where you find especially

15:29:13 towards the east side high proportion of

15:29:18 renter households who have one or more housing problems.

The owner occupied

15:29:21 it's a little bit more checkered but still

15:29:24 here also there are owner households

15:29:28 that have really high, you know, there's

15:29:32 a spatial concentration of

15:29:35 households that have one or more housing problems and the concentration

15:29:38 seems to be more towards the

15:29:41 east.

These are the spatial distribution of households that

15:29:44 have one or more housing

15:29:47 problems, and next slide, please.

15:29:50

So I'm going to

15:29:55 hand this over to Bimal to talk

15:29:58 about city housing problems.

>> Thank you.

When I

15:30:01 talked about the

15:30:06 numbers [ indiscernible ]

15:30:09 to present really exciting, it's a good

15:30:12 start.

So thank you.

Uma talked about the housing

15:30:15 problems in general, but I'm going to talk about the

15:30:19 city housing problems.

So there are as

15:30:22 Uma said four different criteria, one for plumbing, one

15:30:25 for kitchen facilities and overcrowding

15:30:29 and the cost burden.

The difference with the

15:30:32 one Uma described earlier for the housing problem

15:30:35 is pretty much for the increasing cost burden.

15:30:39

When I say the city has a severe housing

15:30:42 problem, all the criteria plus the 15% cost

15:30:45 burden.

So these are more severe, right?

So what

15:30:50 we find is that all of the

15:30:55 units -- all of the occupied

15:30:58 units are like

15:31:03 20%, and there

15:31:07 [ indiscernible ] and 30% for renter occupied

15:31:10 units.

So emphasizing again what is greater

15:31:13 is one-third of renter occupied units within the

15:31:17 City of Portland have severe

15:31:20 housing problems, and this essentially is

15:31:26 driven by the problem

15:31:29 of cost burden of 50% and

15:31:32 also substandard housing.

Next slide, please.

Here we

15:31:36 are looking at the units with severe housing problems by

15:31:39 income level, and this slide

15:31:42 pretty much follows the slide Uma presented.

So very high

15:31:45 proportion of

15:31:49 extremely low, very low and

15:31:52 low-income households with a high percentage of units with

15:31:55 more severe housing problems, whether they be renters or

15:31:58 owners, but

15:32:01 it's more skewed towards

15:32:05 renters which are high and severe, and

15:32:09 owners do also have on the low-income,

15:32:12 you have some higher severe

15:32:16 housing problems, because more likely the

15:32:20 owner starts and more likely

15:32:23 to be [ indiscernible ].

Next

15:32:28 slide, please.

15:32:32

Similar to the housing problems we saw in general, the

15:32:36 pattern we see is

15:32:40 pretty much

15:32:43 similar, so the various groups by race and

15:32:47 ethnicity, African-American, his uponic, Pacific

15:32:51 Islander have severe housing problems.

So

15:32:55 they face

15:32:58 disproportionate housing needs.

So it's

15:33:01

15:33:05 disproportionate.

Next slide, please.

15:33:09

This is the map showing the distribution of households with

15:33:13 severe housing problems and on the right side is a renter household and on the

15:33:16 left is the owner

15:33:21 households.

The rental households,

15:33:24 similar housing problems are more on the east side and far east

15:33:29 side and also pockets of areas with severe housing

15:33:32 problems in the different tracts in north Portland

15:33:36 and northeast Portland and

15:33:40 some areas in the southwest Portland.

Looking

15:33:44 at the owner households you'll

15:33:47 see that the owner households

15:33:50 are actually less, their percentage is

15:33:53 less than renter households but

15:33:57 [ indiscernible ] all over the city [ indiscernible ],

15:34:00 they are more concentrated

15:34:03 [ indiscernible ].

The last slide, and at this

15:34:06 point,

15:34:10 I'm actually switching to another segment of the data.

15:34:15

We're not looking at severe housing problems but

15:34:18 elderly households with

15:34:21 housing problems.

So we are

15:34:25 looking at the cost burden of

15:34:28 30%, not 50%, and you see

15:34:32 in this chart that the one in the far left is

15:34:35 for owners and renters

15:34:40 with a household having no one older than

15:34:43 62, and the one in the middle

15:34:48 shows the household having household members between the age of

15:34:51 62 to 75, and

15:34:56 extreme right is the household having one

15:34:59 of the members at least the age of 75.

So you can

15:35:02 see whether they be renter or

15:35:06 owner, the older households seem to have a

15:35:10 higher proportion of households with

15:35:14 housing, severe housing problems, and if you look

15:35:19 at the households with severe

15:35:24 housing, the household with one person at the age of 75 has

15:35:27 a higher

15:35:31 proportion of housing problems.

15:35:34

That's the last

15:35:39 slide I have.

So I'm turning it to Niki to summarize some of the findings.

15:35:42 >> Thank you, Bimal.

This slide may look

15:35:45 familiar.

We put it at the last, in

15:35:48 the last parts of the analysis for low-income households.

15:35:51

On the left is the box with

15:35:55 definitions.

We just want to keep

15:35:58 returning to this as we go through this planning process, because we are

15:36:01 using definitions of barriers, and

15:36:04 impediments so I have that there for your reference

15:36:07 as you look through this again and then on the right we have the

15:36:10 high-level points that Bimal and Uma would

15:36:13 like us to take away from the presentation today.

Being

15:36:16 severely housing cost burdened, which is paying more than

15:36:20 50% of household income on housing costs, or cost

15:36:23 burdened, defined as paying more than 30% of your household income on

15:36:26 housing costs S primarily driving

15:36:29 what is the housing problem as defined by

15:36:32 HUD, experienced by extremely low, very low,

15:36:36 and low-income households.

A

15:36:39 disproportionate housing need exists for African-Americans, Hispanics,

15:36:42 and Pacific Islander

15:36:45 households in Portland.

15:36:49

While only a small fraction of the City of Portland's

15:36:53 housing stock is classified as substandard, just over

15:36:56 80% of this stock is occupied by extremely low,

15:37:00 very low and low-income households and finally, elderly

15:37:03 owner and renter households that contain at least

15:37:06 one household member aged 7 aor more experience a very high

15:37:09 incidence of the housing problem.

15:37:12 5 or more experience a very high incidence of the housing problem.

or more experience a very high

15:37:13 incidence of the housing problem.

or more experience a very high incidence of the housing problem.

15:37:19 Next steps, we will be reviewing

15:37:23 these prior summary points and bringing them up again when

15:37:27 we start to have policy

15:37:31 conversations and representations and also

15:37:34 look at dissimilarity and analysis.

15:37:37

In the housing plan we'll move through the identified

15:37:41 analysis which was constructed

15:37:44 loosely on the standard analysis of impediments by

15:37:47 HUD, and that concludes today's presentation.

I'll give it back to Dr.

15:37:51 Holt so we can collect your comments and feedback.

>>

15:37:54 Thank you very much.

Great information.

Hopefully you have it

15:37:57 in your inbox as well so you can

15:38:00 refer to it.

I will begin by going to those who are with

15:38:03 us remotely and give you an opportunity for

15:38:06 feedback and/or question, if

15:38:11 you do have one.

I will have you

15:38:15 indicate by hand raise, that way we don't

15:38:22 overspeak one another.

15:38:27

Christina?

>> Thank you.

15:38:30 Thank you, Bimal, Uma.

Nice to see

15:38:33 you again.

That was really great information.

I had a quick question

15:38:36 in terms of how are we determining the number

15:38:39 of substandard housing units?

That seems like a really

15:38:43 small number, and I just think I know from personal experience that

15:38:46 the number is much larger than that so I'm wondering if

15:38:49 it's relying on BDS reported inspections

15:38:50 or where we're getting that number from.

Thanks.

15:39:00 >> Great question.

>> So Christina, I'm not

15:39:03 entirely sure how the collection occurs at the

15:39:06 local level, but the data

15:39:09 is based off of regular census

15:39:14 data, and my guess is because it's tied to the housing

15:39:19 condition, it's not ACS, probably

15:39:22 it's called American Housing Survey

15:39:27 which takes into account policy and probably they're getting a sample

15:39:30 and putting together this

15:39:35 tabulation, but then please also note the definition for substandard

15:39:38 is really

15:39:41 specific.

It's just

15:39:45 incomplete kitchen

15:39:48 and/or incomplete plumbing.

15:39:51

Probably this number doesn't resonate close to the

15:39:54 truth is likely true but this is the best we have to work

15:39:58 with, and we can always kind of go back to the

15:40:01 age of the

15:40:06 housing and the assumption the multifamily we'll build more and

15:40:09 more in the recent decades and those are

15:40:14 much better quality.

Probably the number is high, but it may

15:40:17 not be that high.

>> Can I just ask

15:40:20 a follow-up question?

15:40:24

Sorry to nit-pick on

15:40:28 this.

Is the assumption these were not provided with lack of a

15:40:31 complete kitchen or complete plumbing at the time of rental or that

15:40:34 it could have fallen into that state because of failure

15:40:37 to make routine repairs and maintenance?

>> It is at

15:40:40 the time of data collection, so it has nothing to do

15:40:43 with who provided

15:40:46 what.

>> Thanks.

>> Thank you.

15:40:50 Allan?

>> Thanks, Dr. Holt.

Thanks

15:40:53 for the presentation.

A couple

15:40:57 pieces, one is I

15:41:02 think particularly with the fair housing aspects of pieces that we're looking at

15:41:05 here, I think it's helpful for us to

15:41:08 cross-tab the data and the demographics and

15:41:11 this is a less demographic one, one example is in

15:41:14 the severe housing problems that shows the

15:41:18 bars, and Bimal, you pointed this out in the little caption it points

15:41:21 it out but we could also

15:41:24 potentially use stack bars to illustrate in that 30%, right, as

15:41:27 you said, most of that is made up of the

15:41:30 issue around cost burden, rather than the other

15:41:34 disproportionate housing needs, right?

Those I'm

15:41:37 assuming are smaller percentage so we could see that the issue there is

15:41:40 cost burden.

We could see that through I

15:41:43 stacked bar potentially.

The other place I think where

15:41:47 cross-referencing some of the demographics might be helpful is we

15:41:50 sort of know this intrinsically about

15:41:53 the demographics geographically and spatially

15:41:56 but where we show a spatial distribution of households

15:41:59 again with the housing problems, we might also be

15:42:04 able to show with cross-hatching or something the areas that

15:42:07 have the demographics related to race and ethnicity which we

15:42:10 know are also focused on the eastern part of the city, so

15:42:13 that we see the darker areas that have the housing

15:42:16 problems, and also see a darker

15:42:20 cross-hatching illustrating those are areas with higher concentrations

15:42:23 of communities of color generally speaking.

So again, I think we know

15:42:26 it sort of inuively and we can narrate

15:42:29 it.

We might also show it

15:42:33 visually.

>>

15:42:37 I agree with

15:42:40 you.

[ Indiscernible ]

15:42:52

In terms of stacking

15:42:55 data, it's very likely, it's possible to

15:42:59 get the data from what we have gotten.

We only know we

15:43:03 had one of the four housing problems but we don't really know the

15:43:07 breakdown of those four

15:43:10 housing problems.

That data can be more

15:43:17 likely [ indiscernible ] but I don't think [ indiscernible ].

>> So we're just

15:43:20 making an assertion though then that it's, that the

15:43:23 higher proportion problem

15:43:26 is the cost burden?

Not necessarily the underlying

15:43:30 data, okay.

>> For the housing problem, the difference between

15:43:33 the housing problem is the cost burden,

15:43:42 so you know, that's the main

15:43:45 difference [ indiscernible ].

>>

15:43:49 Okay, thank you.

>>

15:43:52 Dung?

>> Hi.

Let me just

15:43:56 lower my hand.

Thank you for the

15:44:02 presentation.

I just have some things as we were going over the

15:44:06 data I had curiosity about that might

15:44:09 kind of overlap

15:44:12 with some other questions, cross-sectional information that we

15:44:16 can look at.

Some things that sparked my interest were

15:44:19 especially around the elderly households, the

15:44:23 75 and up, something that I don't know that

15:44:26 we would be able to pull information from if we have

15:44:30 access to that is whether they were, because I think the way

15:44:35 it was phrased was households with somebody

15:44:38 in certain age category, 75 and up and

15:44:41 65 and up but not

15:44:45 including 75 and up.

I was curious about if it

15:44:49 has any impact.

I would imagine so,

15:44:53 if the household is a person who for example

15:44:58 is 75 and alone rather than a part of

15:45:02 a household, just being on the hotline, you hear

15:45:07 about a lot of times people having a hard time advocating for themselves

15:45:10 especially if they're alone and don't have a

15:45:14 safety network or

15:45:17 community supporting them and also I don't know if this would

15:45:20 really, I think part of this information kind of in

15:45:23 the background of

15:45:26 it would be the households with an elderly person in it

15:45:29 could be like multigenerational

15:45:34 households that are often

15:45:37 publicly different cultural

15:45:40 backgrounds, and then also some

15:45:46 curiosity around this often kind of is intersectional but

15:45:50 the elderly households and

15:45:53 people with disabilities, so just as I was looking at

15:45:56 the information, I was thinking about what are the barriers

15:46:00 that they would come across and how do they

15:46:04 access services and how do they

15:46:08 prevent, you know, the substandard

15:46:11 conditions from happening?

Although those categories had to do

15:46:14 more with the general categories of housing problems

15:46:17 for owners, so that kind of captures like

15:46:21 the

15:46:25 overcrowding and the income, the ability to pay the rent

15:46:28 as well as like the other substandard housing conditions, but

15:46:31 yeah, just

15:46:34 some thoughts and some questions that came to mind as

15:46:38 I was listening to the presentation.

15:46:42 >> Thank you very much for that feedback.

15:46:43

I don't know if anyone wants to respond.

15:46:46 >> I wanted to say thanks for the feedback.

That's

15:46:50 great.

Actually it was a breakdown

15:46:55 of the data by [ indiscernible ]

15:46:59

not specifically by race.

I'm not sure if that makes

15:47:03 sense at this point by race and ethnicity.

15:47:12 >> Dung, it's good to see

15:47:16 you.

How we are thinking about

15:47:20 the household types and

15:47:24 it's about are -- because this is tied into the household and are

15:47:27 there other people, and it's just that we'd

15:47:30 have to go back to our source,

15:47:34 ACS and cross that with household types and a

15:47:37 lot of these much older

15:47:40 households, those are

15:47:44 single-person households.

I don't have the data with me

15:47:47 but especially in the city there's a

15:47:50 significant portion of elderly households who are

15:47:57 single-person households and this comes up to being tied to

15:48:00 fixed income and the taxes are high.

If

15:48:04 there is interest we could detail the household

15:48:07 types by age.

>> Thank you.

Great comment.

15:48:12 I see no other hands.

I'll give a moment for those

15:48:18 who are in our remote

15:48:22 meeting space.

Excellent.

I will go to

15:48:25 the committee members who are in the room.

Barbara, any

15:48:27 comments?

>> No.

>> Jesse?

15:48:30 >> No, I don't have anything to add that wasn't

15:48:34 covered.

>> Push your button so we can capture it.

15:48:38 >> There we go.

No, I don't have anything to add

15:48:41 that wasn't covered.

Thank you.

>> Okay,

15:48:45 excellent.

Well, without any further

15:48:49 discussion, thank you, presenters, for the

15:48:54 information that was covered and the interaction and dialogue.

The next

15:48:57 item on our agenda is the space

15:48:59 for public comment.

Do we have anyone signed up for public comment?

15:49:15 Okay.

Let me start with Jane

15:49:18 Hubbard.

Are you present?

15:49:27

Joan Moore?

Kathleen Swift?

15:49:41 Well, I think we have gone through the agenda for the day.

15:49:47 Great for us to be together on this sunny

15:49:50 afternoon in July.

Any closing comments?

15:49:56 >> I will follow up with an updated

15:50:00 version of the presentation.

We have a few final

15:50:03 edits, as well as a follow-up information that Uma

15:50:06 and Bimal want to add on, and other than

15:50:10 that, I would just say our next meeting is

15:50:12 scheduled in October, and we will be sending out materials for

15:50:17 that shortly.

>> Thanks, everyone.

Have an

15:50:20 incredible afternoon.

Stay well.

Stay