COVID-19 Hotel Forecast: Los Angeles

The global hospitality industry has been ravaged by COVID-19, a classic example of a black swan event. While many are looking backwards to compare the current market environment with the post-9/11 or 2008 Great Recession periods, Phocuswright prefers to look forward - trying to address the tough questions weighing on our collective minds.

Over the coming months, by teaming up with the data science team at LodgIQ, Phocuswright will evaluate a broad swath of hotel-related and other data across a variety of key metropolitan areas. Our key objectives are to model the:

• Level of disruption
• Duration of disruption
• Shape of the recovery curve

The goal is to understand the similarities and differences in hotel market dynamics between destinations. This is especially relevant, as some markets may have yet to peak in terms of the level of infections, while others are seeing active coronavirus case counts decline.

Travel's multimodal nature and interdependency of origin and destination markets within different sectors adds necessary, but not always welcome complexity to the model. Therefore, this forecast is probabilistic, with a high degree of uncertainty. The spread of the virus is path-dependent, non-linear and impacted by measures such as local social distancing and broader geographic quarantines.

The forecasting model will be continually evaluated and refined as more data is collected, stronger signals identified, and new outcomes revealed. Understanding the impact of the virus and the path to recovery across major global markets will help the industry regain solid footing through more informed decision making. The simplest way to understand the impact of the virus is to observe the change to the forecast as the spread progresses.

For those keeping score at home, last week we contrasted the Boston and New York markets. This week we thought it would be interesting to do something similar on the West Coast of the U.S. and compare Los Angeles with our previous San Francisco forecast.

Before we get started, a few points to consider as we progress with our weekly analyses. Moving into our second month, instead of using the original March 1 "pre-COVID-19" forecast as the baseline, we will be looking at the first forecast from the previous month.

As a result, for today's report and for those to follow through the month of May, we use the March 29 forecast as the base. This will eliminate the obvious "things look worse than we thought they would in early March" conclusion, and provide for a more nuanced comparison.

As noted earlier, the dynamics of the results produced by the model are very interesting. At this point in the early progression of the pandemic, weekly cuts produce a classic "X" pattern when contrasting the number of confirmed cases with hotel occupancy percentage and revenue per available room (RevPAR).

What we see are the weekly model revisions continuing to erode for projected occupancy and RevPAR. The model is not yet picking up signals that indicate a "beat expectations" metric - indicative of the upswing one would anticipate seeing as a leading indicator of a recovery. Enough model-talk. Let's dig into Los Angeles.

Los Angeles County represents 25% of California's population. Unfortunately, it has also recorded 55% of California's COVID-19 related deaths. California state and county officials have now introduced timelines for reopening - with some areas beginning to reopen on May 8. Los Angeles Mayor Eric Garcetti's recent comment that "hasty action kills people" provides an indication that Los Angeles may not be leading that charge.

Despite recording its first confirmed case five weeks before San Francisco, and its first death two weeks before San Francisco, Los Angeles was not nearly as proactive in issuing lockdown orders. Instead, it aligned with statutory orders from Governor Gavin Newsom.

Los Angeles, when compared to San Francisco, exhibits some structural benefits and challenges. First, the city is much less dense, with greater reliance on automobiles, creating the area's legendary traffic snarls. Los Angeles' metro transit ridership has dropped 17% over the last five years. Where 33% of those in the San Francisco area ride public transportation, the figure for Los Angelenos is under 11%. The model projects that less density reduces the number of cases, and results in a lower negative impact on hotel demand.

Los Angeles County is currently tracking at 293 cases and 14 deaths per 100,000 population. San Francisco County is currently at 213 cases and 4 deaths per 100,000. San Francisco's lockdown, while devastating to its hotel industry, appears to have successfully flattened the curve.

Those early/strict San Francisco lockdowns produced a May forecast occupancy rate below 8% and a year-over-year (YoY) RevPAR decline of nearly 95%. While the per capita human cost has been greater in Los Angeles, hotel performance has not been as severely impacted.

Los Angeles' coronavirus timeline shows a very early first case and first death, but the lockdown didn't occur until March 19:

• January 26 - Los Angeles County records first coronavirus case
• March 4 - California Governor Gavin Newsom declares state of emergency
• March 11 - Los Angeles County reports first coronavirus death
• March 12 - Disneyland and Disney California Adventure theme parks close
• March 14 - Airports begin screening passengers for coronavirus
• March 18 - California state parks close campgrounds
• March 19 - ‘Safer at Home' Order issued in Los Angeles County following Governor Newsom's stay-home orders for the state
• March 20 - U.S. and Mexico suspend cross-border travel
• April 14 - Governor Newsom issues four-phase guidelines for lifting stay-at-home restrictions
• May 8 - Phase 2 of reopening scheduled to begin - with counties making ultimate decisions

As a result, Los Angeles' rate of RevPAR decline across the weekly forecasts covering the six weeks between March 29 and May 3 has not been nearly as steep as other U.S. gateway cities like New York, Boston and San Francisco. The model projects a bottom in May with RevPAR down 85% YoY. It should be noted that in early April, the model was only seeing a 73% drop, so the model perceives conditions to have deteriorated somewhat.

The inverse correlation "X" pattern depicting confirmed virus cases and weakening hotel demand is apparent for Los Angeles, as in all other global gateway cities.

Figure 1

In May, Los Angeles is projected to see YoY room occupancy decline by 80%, average daily rate (ADR) drop by 28% and RevPAR fall 85%. These compare much more favorably to May's month-end forecast stats for the comparable metrics in San Francisco (occupancy and RevPAR in the negative mid-to-high 90% ranges and ADR off more than 40%).

One particularly encouraging statistic is the 28% decline in ADR. This is much lower than the amounts observed in San Francisco and Boston, and more comparable with New York. At this point, the figure reflects more on the hotel class inventory mix in a city, rather than the perilous practice of intentional discounting by hoteliers in a low-demand environment. Fortunately, we continue to see hoteliers exhibit discount pricing restraint.

Differences in YoY RevPAR variance for March and April showed that the impact on Los Angeles was less severe than for most major markets. Some potential good news for Los Angeles is that modeling for the second quarter shows continual improvement in June and July from the May bottom.

Figure 2

The YoY RevPAR disruption forecast for Los Angeles' second quarter 2020 comes in at -76%, the best we have seen thus far for the major U.S. gateways we have evaluated. It's not much, but it's a win for LA. The big unknown is when the Los Angeles County lockdown will completely end. As witnessed in Singapore, even if Los Angeles does everything right, there is a risk that actions taken by neighboring states or counties could jeopardize LA's prospects for recovery. Even California's temporary opening of beaches saw crowds descend, resulting in quick backtracking of the decision and a renewed shutdown.

The patience of the citizenry is clearly being tested. Some sub-groups have grown more vocal in protesting the lockdowns and demanding that personal freedoms and commerce should be prioritized over an increased level of human cost.

One concerning trend has continued for Los Angeles; we are observing that each weekly forecast produces a marginally lower Occ% and RevPAR than the previous week. This indicates that in absolute terms, the prospects for recovery are extending over a longer timeframe, despite finding an absolute bottom in the near term.

The model will continue to monitor cases, unemployment statistics (which are now reaching Great Depression levels nationally) and governmental actions to produce these forecasts based on all information available at the moment.

Figure 3

Figure 4

Los Angeles demand is minimal as traditional demand generators and the entertainment industry remain in shut-down mode. With portions of the massive Los Angeles convention center converted into a field hospital and group demand non-existent, having roughly one third of downtown LA's 8,500 hotels temporarily closed as of mid-April helps somewhat artificially boost occupancy for the remaining properties.

To complicate matters further for hoteliers, homeless advocates are pressing the local government to commandeer hotels to provide housing for 15,000 peoplefrom LA's homeless population. Many hoteliers have stepped up to provide housing for essential workers and healthcare personnel. However, housing the homeless brings additional challenges which, frankly, the hotel industry has fundamentally never been prepared to address.

Again, the conundrum facing hoteliers is that doing the right thing to support social welfare and protect at-risk lives within its local community stands in stark juxtaposition with the branding, segmentation and operational realities. Hoteliers facing this option may be weighing the benefit of local support for exhibiting admirable corporate social responsibility, versus the willingness of potential guests to share a property that is also housing the homeless, as demand begins to return.

Hoteliers will need to clearly develop transition strategies to onboard and house homeless guests, who are in desperate need, and carefully consider an exit strategy associated with returning to normal operations. The public relations and financial benefit of taking in the homeless could easily be undermined by negative press related to asking those guests - who have no other place to go - to leave. There are no easy choices for governments or hoteliers in a pandemic.

Figure 5

Many other global gateway cities would be thrilled to see occupancy rates bottoming out in the mid-teens, particularly after seeing forecasts erode by 10 points over a six-week period. It should be noted that the model's occupancy projections for June were reduced by only four points, to the low 20s, with nearly 10 points of occupancy growth currently expected for July.

For some context, Los Angeles would normally see 90%+ occupancies for July as corporate, group and leisure travel demand builds. The optimism of seeing the doubling of occupancy from May's bottom contrasted with the 60+ point falloff from the typical pace of demand offers stark commentary on the importance of perspective in these uncertain times.

As nearly 40 U.S. states begin to open back up for business, even with some still seeing an increase in daily case counts and deaths, the big unknown remains the readiness of the U.S. population to demonstrate personal responsibility and continue social distancing. With greater mobility and the potential for increased clustering, government leadership will need to execute on plans to provide acceptable levels of testing and contact tracing to avoid the continuation of this first wave of infections.

Mayor Garcetti and Governor Newsom continue to prioritize the welfare of Californians over a rapid opening of businesses - at least over the near- to mid-term. We need to hope that the stereotyped, laid-back Californian ethos will prevail with the population "going with the flow," as opposed to swimming against the tide of a virus that is much less predictable than gnarly surf conditions.

Figure 6

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Figure 8

We continue to identify leading indicators that signal likely pricing strategies as markets decline and recover. ADRs can be misleading in a market experiencing severe supply contraction, as the mix of available rooms may shift to offer higher ratios of economy or luxury properties. Logically, during significant periods of disruption, travelers may become more price-sensitive, but anxious hoteliers engaging in rate wars may suppress pricing not only for their competitive set, but for the destination overall.

It is also important to remember that as the time horizon expands, greater variation may be expected. As more global markets recover from peak virus caseloads, their outcomes will be captured, with the model continually refined to enhance its precision.

This crisis will pass, but until then, the most urgent questions focus on the depth of the decline, the length of its duration and how the recovery will manifest itself. As the analysis continues, the following factors will be closely monitored to identify early signs of recovery:

• Active cases and mortality rates
• Test counts per million
• Government travel policies
• Stock market and volatility indexes
• Unemployment rates

LodgIQ uses state of the art BigData Analytics and AI / Machine Learning algorithms to forecast demand and price hotel rooms. LodgIQ is led by a team of experienced hospitality technologists, data scientists and engineers. Seed funded by Highgate Ventures, LodgIQ is re-imagining revenue management with predictive and prescriptive analytics methods. Our flagship product - LodgIQ RM is used by hotels across the globe, day-in and day-out to understand demand and optimize revenue.