Statistical Tables | | Loans for Gig Economy Workers

Trends at a Glance
(Single-family Homes)
  May 18 Apr 18 May 17
Median Price: $1,018,000 $973,000 $858,950
Average Price: $1,098,109 $1,087,397 $961,216
Home Sales: 1027 889 986
SP/LP Ratio: 109.8% 110.3% 107.2%
Days on Market: 16 16 18
(Condos/Townhomes)
  May 18 Apr 18 May 17
Median Price: $650,000 $669,500 $560,000
Average Price: $672,473 $675,210 $584,892
Condo Sales: 337 276 345
SP/LP Ratio: 107.9% 109.2% 104.9%
Days on Market: 15 13 17

Home Prices Reach New Highs, Again

The prices for single-family, re-sale home set new highs in May. This is the third month in a row home prices have reached new highs.

The median price for homes gained 14.2%, year-over-year. The average price was up 18.5% over last May.

The average sales price for re-sale condos in Alameda County gained 15.0% year-over-year. The median price rose 16.1%. The median price has been higher than the year before every month since January 2012.

Multiple offers continue to be the norm. The sales price to list price ratio, or what buyers are paying over what sellers are asking, remains in triple digits: 109.8% for homes and 107.9% for condos.

The ratio has been over 100% since May 2012 for both homes and condos.

Home sales were up 4.2% year-over-year. Year-to-date, home sales are up 2.0%.

Condo sales were down 2.3% from last April. Year-to-date, condo sales are down 9.1%.

Homes are selling quickly, taking sixteen days from being listed to going under contract. Condos are taking fifteen days.

Momentum Statistics

Sales momentum…
for homes fell 0.3 of a point to +4.9.

Pricing momentum…
for single-family homes rose one point to +10.3.

We Calculate…
sales momentum by using a 12-month moving average to eliminate seasonality. By comparing this year's 12-month moving average to last year's, we get a percentage showing market momentum.

In the chart below…

the blue area shows momentum for home sales while the red line shows momentum for pending sales of single-family, re-sale homes. The purple line shows momentum for the median price.

This is an extraordinarily tough market for buyers. It's important to be calm and realistic. If you don't know what to do or where to begin, give me a call and let's discuss your situation and your options.

 

Alameda County Days on Market

Alameda County Days on Market

The real estate market is very hard to generalize. It is a market made up of many micro markets. For complete information on a particular neighborhood or property, call me.

If I can help you devise a strategy, call or click the buying or selling link in the menu to the left.

Monthly Statistics

Complete monthly sales statistics for the Alameda County are below. Monthly graphs are available for each city in the county.

May Sales Statistics
(Single-family Homes)
  Prices Unit     Change from last year Change from last month
Area Median Average Sales DOM SP/LP Median Average Sales Median Average Sales
County $1,018,000 $1,098,109 1,027 16 109.8% 18.5% 14.2% 4.2% 4.6% 1.0% 15.5%
Alameda $1,017,500 $1,087,639 36 14 109.0% -3.1% -0.9% -10.0% -8.5% -10.1% 38.5%
Albany $952,000 $1,082,182 11 11 113.0% -19.8% -7.5% 175.0% -18.6% -8.4% 37.5%
Berkeley $1,475,000 $1,498,894 52 21 111.2% 15.2% 11.6% 13.0% 3.1% 4.7% 13.0%
Castro Valley $885,000 $954,619 55 11 103.8% 8.6% 13.3% 34.1% -2.3% 3.9% 111.5%
Dublin $1,100,000 $1,132,296 57 15 102.6% 12.6% 13.4% 23.9% 4.8% 2.7% 39.0%
Fremont $1,317,500 $1,403,680 132 13 106.9% 30.0% 24.6% -4.3% 3.9% -1.7% 13.8%
Hayward $728,000 $839,625 103 19 102.8% 15.6% 27.5% 25.6% 4.0% 9.4% 28.8%
Livermore $849,975 $944,319 126 14 101.4% 6.6% 1.8% 14.5% 4.9% -0.6% 22.3%
Newark $995,000 $1,047,783 30 10 105.6% 24.4% 24.7% -18.9% -2.9% -1.0% -3.2%
Oakland $900,000 $987,533 211 20 110.0% 23.8% 16.0% -8.7% 5.9% 6.1% -3.7%
Piedmont $2,150,000 $2,367,273 11 17 103.5% 3.6% 12.7% -26.7% -17.8% -20.6% -15.4%
Pleasanton $1,305,000 $1,445,924 82 12 101.1% 15.2% 10.4% 5.1% 5.2% -2.7% 28.1%
San Leandro $690,500 $724,263 64 23 106.4% 6.2% 11.0% 1.6% 3.8% 5.1% 10.3%
San Lorenzo $720,000 $695,726 15 17 103.1% 23.9% 21.0% -6.3% 6.7% 2.2% -16.7%
Union City $1,075,000 $1,119,076 40 10 102.6% 26.2% 30.7% 5.3% 0.9% 3.6% 0.0%

 

May Sales Statistics
(Condos/Town Homes)
  Prices Unit     Change from last year Change from last month
  Median Average Sales DOM SP/LP Median Average Sales Median Average Sales
County $650,000 $672,473 337 15 107.9% 16.1% 15.0% -2.3% -0.4% -2.9% 22.1%
Alameda $746,000 $686,150 16 25 105.3% 4.8% 1.3% -20.0% -7.1% -8.0% 23.1%
Albany $610,000 $610,000 1 36 100.0% 16.2% 10.5% -66.7% -11.6% -9.0% -75.0%
Berkeley $759,000 $740,600 5 15 107.4% -6.1% -3.9% 0.0% -5.2% -2.6% -28.6%
Castro Valley $695,000 $718,255 11 11 104.7% 18.3% 20.3% 37.5% 37.5% 33.0% 450.0%
Dublin $770,000 $757,323 29 16 103.3% 16.7% 22.7% 11.5% 2.6% 2.7% -12.1%
Emeryville $590,000 $622,067 15 18 110.9% 50.5% 30.1% 36.4% -4.6% -3.3% 0.0%
Fremont $765,000 $767,049 59 9 112.2% 14.2% 15.3% 11.3% -2.5% -1.7% 68.6%
Hayward $485,000 $500,701 35 13 105.5% 8.4% 4.7% -7.9% -1.6% 1.9% 25.0%
Livermore $651,000 $624,739 23 14 104.0% 15.8% 11.3% 27.8% 5.4% 5.0% 21.1%
Newark $650,000 $663,549 17 12 106.0% 12.1% 9.3% 21.4% -9.1% -3.7% 54.5%
Oakland $650,250 $692,728 83 19 109.2% 8.9% 14.9% -8.8% -0.6% -3.8% 18.6%
Pleasanton $700,500 $693,814 18 10 105.7% 3.8% 6.0% 5.9% 1.9% 3.6% 20.0%
San Leandro $500,000 $491,308 13 15 107.3% 18.2% 18.7% 0.0% 10.5% 14.4% 0.0%
Union City $605,000 $624,182 11 9 111.9% 43.0% 50.8% -15.4% -9.0% -10.8% 0.0%

Loans for Gig Economy Workers

The two biggest sources of home-mortgage money in the country — investors Fannie Mae and Freddie Mac — are quietly working on ways to make qualifying for a home purchase easier for participants in the booming “gig” economy.

The gig economy refers to hundreds of income-earning activities that allow workers to set their own hours, work for as long or as little as they choose, and function as independent contractors or freelancers as opposed to salaried employees. Prominent examples include people who work as drivers for Uber or Lyft, assemble Ikea furniture through TaskRabbit and offer rooms in their homes on Airbnb.

Estimates vary, but anywhere from just under 20 percent to 30 percent or more of the U.S. workforce participates in some way in the gig economy. Last year, Intuit, which owns TurboTax, estimated that 34 percent of the workforce earned money in gig pursuits and projected that this could rise to 43 percent by 2020.

But when buying a home, the challenge for these workers is to make their gig-sourced earnings count as income for mortgage-qualification purposes. Lenders typically look for stable and continuing income streams: two years of documented income plus reasonable prospects that those earnings will continue for another several years. Lenders also routinely obtain tax-return transcripts from the Internal Revenue Service to confirm an applicant’s self-reported income.

Gig income often doesn’t fit neatly into these boxes. It can be sporadic and variable, depending on how much time an individual is able to devote to the work. Gig earnings can be substantial — thousands of dollars a month — but if that money can’t qualify as “income” under existing mortgage-industry guidelines, it may not help in buying a home with a standard mortgage.

“We’re seeing gig income becoming more and more prevalent, especially among the younger demographic — first-time buyers who have embraced things like Uber and Airbnb as a means to make money,” John Meussner, executive loan officer for Mason-McDuffie Mortgage in San Ramon, Calif., told me.

Yet those earnings may not qualify for conventional mortgages.

Enter Fannie Mae and Freddie Mac.

Fannie recently surveyed 3,000 lending executives and found that gig income on applications is increasingly common, but 95 percent said it’s difficult under current guidelines to use these earnings to approve borrowers’ applications. Two of every 3 lenders said better treatment of this income would either “significantly” or “somewhat” improve “access to credit” for many buyers.

Fannie and Freddie are actively pursuing projects that would do just that. The tricky part for both companies: Whatever solutions they develop must still produce high-quality loans with low risks of default at the end of the process, and ideally must be automatable — that is, borrower information could be entered into Fannie’s and Freddie’s electronic underwriting systems at the application stage.

Freddie’s efforts come under its “borrower of the future” initiative. Terri Merlino, vice president and chief credit officer for single-family business, told me the company is studying automated solutions “outside the box” to validate income from different sources for self-employed and gig-economy earners. Neither Freddie nor Fannie was able to discuss details on what they’re considering, but Freddie confirmed its partnership with high-tech software company LoanBeam, which provides automated verifications of multiple income streams of self-employed and other borrowers.

Meussner hopes that Fannie and Freddie take a more realistic perspective on gig earnings.

“If someone is pulling income from Uber for only six months” — which won’t qualify under the two-years standard — “they may have been doing similar things for years beforehand” for a different company. “That should be [the] primary focus rather than the exact employer and position that generated the income.” After all, Meussner said, “if someone can make similar income over the course of years doing various things in various places [in the gig economy], it could be argued they’re more dependable than someone with a long history with a salaried position in a field that is being disrupted by tech, in which case the loss of a job would be devastating financially.”

You can bet Fannie and Freddie are listening to recommendations like this.

Bottom line: If you make money in the gig economy, be aware that your earnings may not be “income” for conventional mortgage purposes. But sometime soon, if pilot programs and research now underway at Freddie Mac and Fannie Mae are successful, they just might.