Real Estate Report presented by Connie Landes

After reaching new highs in April, the prices for single-family, resale homes dipped in May.

The average price fell 5.2%, but was up 1.3% year-over-year.

The median price was off 4.4%, and it was down 1.3% year-over-year, to $856,000.

Sales of single-family, re-sale homes in May were up by 35.2%, year-over-year.

There were 173 homes sold. The average number of homes sold in a month since January 2003 is 160.

The median price for condos was down 2.3% year-over-year. The average price was up 3.7% compared to last May.

Multiple offers continue to be the norm. The sales price to list price ratio, or what buyers are paying over what sellers are asking continues to hover around 100%: 102.2% for homes and 101.0% for condos.

Homes and condos are selling quickly. It is taking only twenty-three days from when a home is listed to when it goes into contract. The average since January 2003 is sixty-four days.

Condos are taking twenty-six days. The average is sixty-five days.

All of this is due to an incredible lack of inventory. Since January 2003, Santa Cruz County has averaged 145 days of inventory. Last month it was forty-nine. The number of homes for sale as of the fifth of June was 281. The average is 720.

Condos have averaged 224 days of inventory since 2003. Last month it was thirty-five. The number of condos for sale as of the fifth of June was fifty-nine. The average is 147.

Mortgage investors want to make it easier for gig economy workers to get loans 

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.