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The Future of Homes: From Smart to Autonomous

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For years, consumers have been promised that their homes will be connected and smart, integrating the latest technology to optimize and control lighting, heating, energy consumption, electronic devices, and security features.

However, the future has come a little slower than expected. By the end of 2017, it’s estimated that only 16.3% of Americans will live in a smart home, though this percentage will increase to 35.6% by 2021.

Examining the Smart Home Market

Today’s infographic comes from Insurance Quotes, and it helps to give an overview of the current market as well as the reasons for hesitation in the switch to smart homes.

The infographic also provides a future outlook, including the impending movement to “autonomous” smart homes.

The Future of Homes: From Smart to Autonomous

In 2016, smart systems were installed in about 45% of all homes in the U.S. that got renovated.

However, they are far from ubiquitous yet – many consumers still have concerns that are holding the market back from reaching its full potential.

Top Trepidations

The largest hindrance to smart homes for now is cost, which is cited by 42% of consumers as an obstacle.

However, there is also evidence that a fear of devices being hacked is also a challenge for many wanting to adopt the technology – in fact, 17% prospective buyers cite privacy and security concerns as a top hindrance. Further, about 10% of consumers have already had smart home devices hacked, and 87% of them had to shell out money to solve the issue.

Paradoxically, even though technologically superior security systems are a top reason that homeowners want to have smarter homes in the first place, the vast majority of IT experts say that IoT apps such as those used at home are far harder to secure than regular mobile apps.

Autonomous Smart Homes

After smart homes, the next logical step is an autonomous smart home that can learn based on your habits and behaviors. Such a home would recognize you and other family members, adapting things like temperature, lighting, or recommendations to you automatically based on your lifestyle and activities.

For this to work – everything would need to be truly connected: your mattress would assess how you sleep, your alarm would connect to your coffee maker, and the morning lighting would be shifted to match your evolving preferences.

While there are many uncertainties about what an autonomous smart home would mean, the inevitability of their rise is clear.

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Mapped: The Countries With the Highest Housing Bubble Risks

Which real estate markets have the highest risk of seeing a correction? These maps highlight housing bubble risks using data from four key indicators.

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Mapped: Countries With the Highest Housing Bubble Risks

With a decade-long bull market and an ultra low interest rate environment globally, it’s not surprising to see capital flock to housing assets.

For many investors, real estate is considered as good of a place as any to park money—but what happens when things get a little too frothy, and the fundamentals begin to slip away?

In recent years, experts have been closely watching several indicators that point to rising bubble risks in some housing markets. Further, they are also warning that countries like Canada and New Zealand may be overdue for a correction in housing prices.

Key Housing Market Indicators

Earlier this week, Bloomberg published results from a new study by economist Niraj Shah as he aimed to build a housing bubble dashboard.

It tracks four key metrics:

  1. House Price-Rent Ratio
    The ratio of house prices to the annualized cost of rent
  2. House Price-Income Ratio
    The ratio of house prices to household income
  3. Real House Prices
    Housing prices adjusted for inflation
  4. Credit to Households (% of GDP)
    Amount of debt held by households, compared to total economic output

Ranking high on just one of these metrics is a warning sign for a country’s housing market, while ranking high on multiple measures signals even greater fragility.

Housing Bubble Risks, by Indicator

Let’s look at each bubble risk indicator, and see how they apply to the 22 countries covered by the housing dashboard.

It should be noted that most of the measures here are shown in an index form, using the year 2015 as a base year. In other words, the data is not representative of the ratio itself—but instead, how much the ratio has risen or fallen since 2015.

1. House Price-Rent Ratio

When looking at housing prices in comparison to rents, there are four countries that stand out.

New Zealand (196.8) and Canada (195.9) have seen ratios of housing prices to rents nearly double since 2015. Meanwhile, Sweden (172.8) and Norway (168.2) are not far behind.

Elsewhere in the world, this ratio is much more in line with expectations. For example, in Portugal—where house prices have skyrocketed over recent years—rents have increased at nearly the same rate, giving the country a 99.2 score.

2. House Price-Income Ratio

There are three familiar names at the top of this bubble indicator: New Zealand (156.8), Canada (155.3), and Sweden (145.7).

In places where rents are lagging housing prices, so are the levels of household income. For how long will people afford to buy increasingly expensive houses, if their incomes continue to lag?

3. Real House Prices

Real house prices have increased in all of the 22 markets, with the exception of Italy (95.5).

For this indicator, there are five markets that stand out as having fast-rising prices: Portugal (131.8), Ireland (127.6), Netherlands (121.9), Canada (124.1), and New Zealand (121.9). The latter two (Canada/New Zealand) have appeared near the top of all three bubble indicators, so far.

4. Credit to Households (% of GDP)

Exceedingly high debt ratios point to a strain on consumer finances – and when finances are strained, the chance of a default increases.

Switzerland (128.7%), Australia (120.3%), and Denmark (115.4%) top the list here with consumer debt far exceeding country GDP levels. However, Canada still makes an appearance in the top five with a debt-to-GDP ratio of 100.7%.

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Mapped: The Salary Needed to Buy a Home in 50 U.S. Metro Areas

The annual salary needed to buy a home in the U.S. ranges from $38k to $255k, depending on the metropolitan area you are looking in.

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The Salary Needed to Buy a Home in 50 U.S. Metro Areas

Over the last year, home prices have risen in 49 of the biggest 50 metro areas in the United States.

At the same time, mortgage rates have hit seven-year highs, making things more expensive for any prospective home buyer.

With this context in mind, today’s map comes from HowMuch.net, and it shows the salary needed to buy a home in the 50 largest U.S. metro areas.

The Least and Most Expensive Metro Areas

As a reference point, the median home in the United States costs about $257,600, according to the National Association of Realtors.

 Median Home PriceMontly Payment (PITI)Salary Needed
National$257,600$1,433.91$61,453.51

With a 20% down payment and a 4.90% mortgage rate, and taking into account what’s needed to pay principal, interest, taxes, and insurance (PITI) on the home, it would mean a prospective buyer would need to have $61,453.51 in salary to afford such a purchase.

However, based on your frame of reference, this national estimate may seem extremely low or quite high. That’s because the salary required to buy in different major cities in the U.S. can fall anywhere between $37,659 to $254,835.

The 10 Cheapest Metro Areas

Here are the cheapest metro areas in the U.S., based on data and calculations from HSH.com:

RankMetro AreaMedian Home PriceMonthly Payment (PITI)Salary Needed
#1Pittsburgh$141,625$878.73$37,659.86
#2Cleveland$150,100$943.55$40,437.72
#3Oklahoma City$161,000$964.49$41,335.41
#4Memphis$174,000$966.02$41,400.93
#5Indianapolis$185,200$986.74$42,288.92
#6Louisville$180,100$987.54$42,323.15
#7Cincinnati$169,400$1,013.37$43,429.97
#8St. Louis$174,100$1,031.70$44,215.56
#9Birmingham$202,300$1,040.51$44,593.35
#10Buffalo$154,200$1,066.29$45,698.05

After the dust settles, Pittsburgh ranks as the cheapest metro area in the U.S. to buy a home. According to these calculations, buying a median home in Pittsburgh – which includes the surrounding metro area – requires an annual income of less than $40,000 to buy.

Just missing the list was Detroit, where a salary of $48,002.89 is needed.

The 10 Most Expensive Metro Areas

Now, here are the priciest markets in the country, also based on data from HSH.com:

RankMetro AreaMedian Home PriceMonthly Payment (PITI)Salary Needed
#1San Jose$1,250,000$5,946.17$254,835.73
#2San Francisco$952,200$4,642.82$198,978.01
#3San Diego$626,000$3,071.62$131,640.79
#4Los Angeles$576,100$2,873.64$123,156.01
#5Boston$460,300$2,491.76$106,789.93
#6New York City$403,900$2,465.97$105,684.33
#7Seattle$489,600$2,458.58$105,367.89
#8Washington, D.C.$417,400$2,202.87$94,408.70
#9Denver$438,300$2,139.02$91,672.45
#10Portland$389,000$1,987.37$85,173.08

Topping the list of the most expensive metro areas are San Jose and San Francisco, which are both cities fueled by the economic boom in Silicon Valley. Meanwhile, two other major metro areas in California, Los Angeles and San Diego, are not far behind.

New York City only ranks in sixth here, though it is worth noting that the NYC metro area extends well beyond the five boroughs. It includes Newark, Jersey City, and many nearby counties as well.

As a final point, it’s worth mentioning that all cities here (with the exception of Denver) are in coastal states.

Notes on Calculations

Data on median home prices comes from the National Association of Realtors and is based on 2018 Q4 information, while national mortgage rate data is derived from weekly surveys by Freddie Mac and the Mortgage Bankers Association of America for 30-year fixed rate mortgages.

Calculations include tax and homeowners insurance costs to determine the annual salary it takes to afford the base cost of owning a home (principal, interest, property tax and homeowner’s insurance, or PITI) in the nation’s 50 largest metropolitan areas.

Standard 28% “front-end” debt ratios and a 20% down payments subtracted from the median-home-price data are used to arrive at these figures.

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