The strategic decisions that'll put your company ahead of the curve years from now need to be made beginning day one.
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вторник, 31 октября 2017 г.
Arrow Electronics Explain ‘Engineering Basics’: Inverters & Converters | @Arrow_Dot_com
Zach Wendt from Arrow does a quick walkthrough on the properties and differences between inverters and converters in circuit design:
Welcome to this edition of Engineering Basics where we will be discussing inverters, converters, transformers, and rectifiers. There is a lot of variation and similarities between inverters, converters, transformers and rectifiers and this video will shed some light into those differences.
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Trump watches Monday events in WH...
The president watched Monday's events involving Mueller, Manafort and Gates 'burrowed in at the White House residence', according to new Washington Post reporting. The panel discusses.
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As Open Enrollment for Obamacare Begins, Confusion Reigns
The Affordable Care Act’s fifth open enrollment season starts Wednesday, but after months of attacks in Washington, many consumers are confused about the law.
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Review: IoT Data Logging Services with MQTT
For the last few months, I had been using Sparkfun’s Phant server as a data logger for a small science project. Unfortunately, they’ve had some serious technical issues and have discontinued the service. Phant was good while it lasted: it was easy to use, free, and allowed me to download the data in a CSV format. It shared data with analog.io, which at the time was a good solution for data visualization.
While I could continue using Phant since it is an open-source project and Sparkfun kindly releases the source code for the server on Github, I thought it might be better to do some research, see what’s out there. I decided to write a minimal implementation for each platform as an interesting way to get a feel for each. To that end, I connected a DHT11 temperature/humidity sensor to a NodeMCU board to act as a simple data source.
What Makes IoT Data Logging Services Useful?
To start, I had three main requirements. First of all, the service would be primarily used for data logging , so a proper export feature is a must.
Second, it needs to support MQTT well, and be properly documented so that I can implement it on a wide variety of hardware. An Arduino library is useful, but not sufficient. We’ve previously covered the basics of MQTT if you need a quick refresh.
Finally, it had to be available at a reasonable cost. It did not have to be free of charge, as there are plenty of ways to make a reasonably priced service pay for itself in effort saved or actual income.
After that, there are a lot of things that were optional. A slick dashboard with live graphs is a great way to quickly share data and get people interested. Support for MQTT QoS level 2 (each datapoint is sent exactly once using a 4 way handshake) would be nice as some of the networks I’ll be using will not exactly be reliable and this means better quality data. Finally, if I can host it on my own VPS so that I can rent a server in the countries where I am collecting data, that would really improve reliability in my area.
After considering the above I found five options that seemed to fit the bill: Adafruit.io, Cayenne, Thingspeak, Thingsboard, and Ubidots. I also considered Blynk, but they don’t seem to have documentation available yet to use MQTT with their service. This is a shame because otherwise it looks pretty slick and has a neat smartphone app.
In each case I’ll explain the pros and cons from my standpoint, and provide an implementation example in Lua using a generic MQTT library (from NodeMCU). Most platforms also provide custom libraries or ready-made solutions for Arduino, Raspberry Pi, and others, however I wanted to investigate at a slightly lower level how each service works. As an added benefit, the code will run directly on NodeMCU firmware that supports MQTT.
One criteria not in consideration is security – these data loggers are collecting non-critical scientific data. They’re on an encrypted Wi-Fi network, and do not accept commands from the Internet.
Adafruit IO
I’ve always been impressed with Adafruit’s documentation, and Adafruit IO was no exception. The MQTT communication protocol was well-defined, it was clear how to set things up without any aspect ever feeling ‘dumbed-down’, and there were links to further reading.
Setting up a device in Adafruit IO starts with creating a feed in the user interface, which is easy on the eyes and well thought out:
Once you’ve created a feed, you’ll be able to add it to a dashboard if you wish. The collection of widgets is somewhat sparse compared to some other platforms, but all the necessary ones are there and they can be resized as you need:
To add data to a feed, you need to set your MQTT client to connect to io.adafruit.com, using your Adafruit account name as your username, and your AIO key (to the left in yellow when you log in) as your password. Note that if your device is not using SSL, these credentials can be intercepted, and that Adafruit IO supports SSL. If your device supports SSL, it’s a good idea to use it.
Once connected, the MQTT topic to publish to is simply your-username/feeds/feed-name. Even though JSON data format is supported, one caveat is that you can really only record one value at a time per feed. You can add latitude, longitude, and elevation to a single feed, but could not add temperature and humidity. By contrast, some platforms let you add more or less arbitrary amounts of variables inside a single feed, which I often find useful for things like weather stations. Nothing stops you from tying multiple feeds to a single dashboard, so I don’t see this as a major flaw. The only shortcoming I’ve been able to find is that Adafruit IO only supports MQTT QoS levels 0 and 1, with no support for 2.
Adafruit IO has convenient data management as well. You can manually add and delete values, a feature missing on some of the other platforms. Downloading the data from a feed is trivial, there’s a button for it when you are viewing a feed.
One truly excellent feature I would like to point out is that there’s an error console. Not only that, but the dashboard flags it red when there’s something new for you to see there. This feature combined with the excellent documentation made Adafruit IO the best platform to learn with — none of the complexity is hidden, but it’s documented and there are tools for debugging. Our sample code to try out this platform is below:
ClientID = 'put anything here'
username = 'your username here'
AIOkey = 'your key here'
m = mqtt.Client(ClientID, 120, username, AIOkey)
m:connect("io.adafruit.com", 1883, 0, function(client) print("connected") m:publish(username.."/feeds/temperature", temp, 0, 1) m:close() end)
function postThingSpeak(level)
m:connect("io.adafruit.com", 1883, 0, function(client) print("connected") m:publish(username.."/feeds/humidity", humi, 0, 1) m:close() end)
end
tmr.alarm(1, 5000, tmr.ALARM_SINGLE, function() postThingSpeak(0) end)
Cayenne
The interface in Cayenne is organized by device. Each device has channels that contain your data. When sending data to a channel, the device can indicate what type of data (e.g. humidity) is being sent to assist in processing. There are quite a few supported data types.
You can create different ‘projects’ that take data from channels on different devices and add them to a common dashboard. Each channel can be displayed as a graph of preset or custom time intervals. The graphs are clean, but are a bit on the small side for larger data sets, and have an odd smoothing effect that created curved lines that didn’t represent the data. I don’t like this feature at all as it makes it harder to see what’s really going on. What I would liked to have seen was an ability to turn off the trend line entirely or at least the smoothing feature.
On the graph view is a ‘Download Chart Data’ button that downloads the data as a CSV file.
Overall Cayenne checked all the boxes, but how easy is it to code for? As it turns out, it has one of the more unusual MQTT setups of the services I investigated. It requires a client ID, a username, and a password specified to connect, and the client ID and username specified again in the MQTT topic:
ClientID = ‘your client ID here’
username = ‘your username here’
password = ‘your password here’
channel = ‘your device channel’
m = mqtt.Client(ClientID, 120, username, password)
m:connect("mqtt.mydevices.com", 1883, 0, function(client) print("connected") m:publish("v1/"..username.."/things/"..ClientID.."/data/"..channel, "temp,c="..temp, 2, 1) m:close() end)
The channels added to each device are named in the web interface, and are simply identified with a number. For example your first channel would be v1//things/<ClientID>/data/0.
In the end, this worked fine and it even supported MQTT QoS level 2.
Thingspeak
First off, Thingspeak has integration with MATLAB. Being able to store, visualize, and analyze data in the same place seems like an excellent feature. I prefer to do hypothesis testing in Python but MATLAB is an excellent choice and all common statistical tests are available.
In Thingspeak, data is sorted into channels. Channels contain fields, and fields contain your data.
The graphs on Thingspeak are tidy and clearly show the data points. However, I couldn’t find a way to resize the graphs in the interface, which ought to be possible because they seem to be generated as SVG graphics.
One very interesting feature is the ability to generate an iframe from the graphs and include them on another website. I gave this a quick try, it worked like a charm. It would have been a neat add-on to this radiation detector.
The MQTT implementation at Thingspeak is dead simple, requiring only the channel ID and API key:
ChannelID='your channel ID'
apikey = 'your API key'
m = mqtt.Client(ClientID, 120)
m:connect("mqtt.thingspeak.com", 1883, 0, function(client) print("connected") m:publish("channels/"..ChannelID.."/publish/"..apikey, "field1="..temp.."&field2="..humi, 0, 0) m:close() end)
Unfortunately, Thingspeak only supports QoS level 0, which means data can be duplicated or missed on shaky Internet connections. I’m not sure how much this matters in practice, but given their focus on data analysis it would be nice not to have to deal with missing data points.
Thingsboard
Up to this point, we’ve only investigated externally hosted services. If you need something that you can host yourself, Thingsboard is worth checking out. Their setup is a little different from anything we’ve seen so far. Much of it is access control for different users, rule setup for raising alarms/actions, and exciting things that are beyond the scope of this article.
For our purposes in Thingsboard, devices contain telemetry data. Then widgets on dashboards are connected to the telemetry contained in devices. The dashboard creation workflow is convoluted compared to some other platforms, but they have by far the widest selection and coolest looking dashboard widgets I’ve seen, and each of them can be set to display full screen.
However, data export is somewhat inconvenient at first – there’s no download button but it can be done programatically via Curl. This way data export and backup can be automated (e.g. with cron), which suits me fine.
The MQTT implementation here is very straightforward and supports QoS level 2. An access token associated with a device is used on connect, and then any telemetry sent will belong to that device. A very important consideration is that you must not send integer or float data as a string – it will work on real-time displays such as gauges, but any graphs will fail to pull historical data correctly. In other words, do not send {"temperature":"57"}, be sure to send {"temperature":57}. Code example below:
ClientID = 'put anything here'
token = 'your token here'
m = mqtt.Client(ClientID, 120, token)
function postThingsboard(level)
status, temp, humi, temp_dec, humi_dec = dht.read(pin)
print(string.format("DHT Temperature:%d.%03d;Humidity:%d.%03d\r\n",
math.floor(temp),
temp_dec,
math.floor(humi),
humi_dec
))
print('{"temp":'..temp..',"humidity":'..humi..'}')
m:connect("demo.thingsboard.io", 1883, 0, function(client) print("connected") m:publish("v1/devices/me/telemetry", '{"temp":'..temp..’,"humidity":'..humi..'}', 2, 1) m:close() end)
end
tmr.alarm(1, 10000, tmr.ALARM_AUTO, function() postThingsboard(0) end)
Ubidots
Unlike the other platforms reviewed here, Ubidots does not offer a free account tier. That being said, new accounts start off with enough credits to operate a device for 5 months, and USD $5 will purchase enough credit for a device to run for 2 months.
In Ubidots, data is sent to variables, and variables exist within devices. You can create a dashboard by adding widgets and selecting a data variable. User interface is where Ubidots really shines; it has by far the best dashboard creation process and overall it’s immediately clear how to do everything you might need to do… with one exception.
The option to export all data from a variable is accessed by entering the variable, then clicking on ‘variable settings’, where the only two options are ‘Export to CSV’ and ‘Delete Values’ – neither of which are settings. Exporting all data from a device on the other hand is intuitively labeled, and where you would expect it to be, which I’ve indicated with a big red arrow:
As for the MQTT implementation, it’s a bit clunky in my opinion. You connect with your token as your username, and the way data is associated with a particular device is via the MQTT topic. The data keys in the JSON dictionary then have to exactly match the variable names set up in the user interface (which must be unique).
This strikes me as less easy to manage than some of the other platforms, where you specify a device-specific token, and you can use non-unique variable names. Perhaps I’m missing something, but if I’m logging the temperature of 30 different pipes I would personally find it easier to manage unique keys than unique variable names. It does support MQTT QoS level 2 though, which is nice:
clientID = 'anything can go here'
Token = 'your token'
Device = ‘your device name’
m = mqtt.Client(clientID, 120,Token)
m:connect("things.ubidots.com", 1883, 2, function(client) print("connected") m:publish("/v1.6/devices/"..Device, '{"Temperature":"'..temp..'","Humidity":"'..humi..'"}', 2, 1) m:close() end)
Summary
All of these platforms provide data capture, display, and export. They differ a little in their MQTT implementation, but not by very much. For datalogging purposes they’re all sufficient. After trying each of them, a few things stuck with me.
Adafruit IO was hands down the best platform to learn with. They had excellent documentation, data management, and an error console for debugging. The free account is enough to get started, and the paid account is reasonably priced and powerful enough to get a lot done. If I had to suggest a service to someone wanted to learn how to add IoT data logging to their projects, I would recommend Adafruit IO without hesitation.
Thingspeak integrated data analytics into their platform. I haven’t dug deeply into it, but the idea of having data acquisition, storage, analysis, and decision making in the same place and automated seems brilliant. Can it perform automated hypothesis testing and control systems based on rejection/failure to reject the null hypothesis? I’m not a MATLAB user, but on the surface it looks like it could. Just don’t tell any direct response marketing teams about that.
Ubidots has a slick user interface and is easy to understand. If I had to introduce IoT to children or managers without going into many technical details, this is what I would use. That’s not intended to be a snide remark, it’s just ideal for both groups for different reasons.
Finally, Thingsboard. I had no idea something this mature existed in the IoT space. The possibilities are staggering for both personal and commercial projects since it’s open-source and can be self hosted. To top it off, it has beautiful dashboard widgets that I can actually show clients. My reaction when I saw it was to immediately pick up the phone and start making calls. I don’t know what I’ll be doing yet, but it’s going to be fun, and I’ll try to share it here one day.
Filed under: Featured, reviews, Skills
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Welcome to Obamacare in 2018, where Trump sabotage accidentally led to more free health plans
People can start buying insurance on the Affordable Care Act (ACA) marketplace, otherwise referred to as Obamacare or the Federal Health Insurance Exchange, on Wednesday. Last year, 12.2 million people signed up for an ACA health plan through healthcare.gov or their state’s own health website. Given the dysfunction coming from Washington, D.C., consumer activists are concerned that not as many people will sign up for coverage this year. (Pro-ACA groups have projected anywhere between 1 to 3 million fewer people will enroll.)
This is a big problem. Even though the ACA led to big gains in health insurance coverage, 8.8 percent of the population, or 28.1 million people, is still uninsured, according to findings by the U.S. Census Bureau. A large amount of the uninsured are eligible for subsidized Marketplace coverage or Medicaid, insurance for people with modest income. Health activists are trying to get this population covered, while simultaneously looking to keep people enrolled and maintain the country’s record-low uninsured rate. The uninsured rate has already increased amid the uncertainty coming out of Washington.
This open enrollment period, things will be a little different. Nearly every health expert has found that the change in premium prices this year can largely be attributed to the current administration’s actions on health care. About 2 million people who rely on the ACA for their health insurance and receive no federal assistance will see premium increases that range between 17 to 35 percent for the lowest-cost plans. Additionally, people in eight states, or 29 percent of enrollees, will have only one insurance company option — a drastic increase from just two percent of enrollees in 2016. More competition tends to drive costs down. Robust insurer options has always been challenging, even under the Obama administration.
But overall, things aren’t as bad as they could be. And despite President Donald Trump’s intentions, Obamacare isn’t dead. People, who do receive federal assistance for their health insurance, should know that if they take the time to shop, most could purchase a plan similarly priced to last year’s or — in some cases — even cheaper (despite the president’s intentions). The Department of Health and Human Services (HHS) and Kaiser Family Foundation (KFF) released reports Monday on how the marketplace fares this year, and it doesn’t bode bad for all consumers. In fact, 80 percent of plans offered on healthcare.gov are $75 or less, just nine percent more than last year, according to HHS.
Here’s what consumers who rely on the ACA for health insurance need to know this open enrollment season:
Open enrollment outlook
For consumers who buy plans on the Marketplace, shopping will likely look different than last year’s enrollment period. First off, open enrollment is shorter this year for people who buy plans on healthcare.gov — a decision reportedly made by the Obama administration. People can only buy plans between November 1st and December 15th; people in a handful of states with their own site can shop around for a little longer.
The Trump administration is making it harder for people to enroll in the ACA in a number of ways:
- Shutting down the healthcare.gov website for 12 hours nearly every Sunday
- Cutting funding by 40 percent to groups that help people enroll. (Cuts have shut down or scaled back a handful of navigator groups nationwide.)
- Slashing the advertisement and promotion budget by 90 percent. (Now, most enrollees don’t know about key open enrollment dates.)
- Made premium subsidies less generous at first. (The administration put in place a new rule that tethered the subsidy to a less generous plan.)
This is a pretty bleak description of open enrollment, but it’s not all that way.
For example, a returning ACA customer in Palm Beach County, Florida received some good healthcare.gov news Saturday. Greg Jenkins, a navigator for the Epilepsy Foundation based in Florida, told the ACA customer — who’ll go nameless for privacy concerns — that her Florida Blue plan premium is just a dollar more expensive than last year’s.
“She was elated,” Jenkins told ThinkProgress. She was under the impression premiums were skyrocketing. Fortunately for her, she receives subsidized care. She’s looking at a plan that’ll cost a $1 per doctor visit, $2 for generic drugs, and no deductible. She’s looking to re-enroll in her silver plan come November 1st, Jenkins said.
You better shop around
To get a good deal, consumers are advised to shop around. This is true for most shopping experiences, but it is especially crucial (and harder) for people looking to buy plans on the Marketplace this year. Last open enrollment period, nearly 3 million people automatically re-enrolled in their health plan. This year, these people — and others tempted to do the same — are being told to browse around first.
There are four different metal plans on the ACA that vary according to how much the insurer covers: bronze, silver, gold, and platinum. Premiums for 2018 are significantly rising in most U.S. counties, in part due to the Trump administration’s decision to end key subsidy payment to insurers. But it’s also true that as premiums go up so do premium tax credits, a federal subsidy tethered to the lowest-cost silver plan.
Many states loaded rate hikes to the lowest-cost silver plan and so now the premium tax credit are especially generous. According to HHS, the average tax credit will increase by an estimated 45 percent from 2017. A majority, or 83 percent, of current ACA enrollees qualify for these tax credits.
For the other 17 percent of ACA enrollees, there’s really no way around pricey plans. Or as Jenkins put it they are “out of luck.” Get America Covered’s co-founder and former HHS official Joshua Peck’s only recommendation for those with no subsidies was to shop.
“For people who have marketplace coverage, subsidies or not, return to healthcare.gov,” he said in a press call on Monday. “Look at options an plans available — every year benefits and prices change.”
Take advantage of all options
“If there is some upside to a silver plan growing from a consumer perspective — and if you have subsidized care — it’s [that] can get a good rate on a bronze or gold plan,” Chris Sloan, senior manager of the health industry consulting firm Avalere, told ThinkProgress. According to Avalere, premiums for silver plans on the exchange increased 34 percent on average.
While consumers tend to gravitate more toward purchasing silver plans — because they fall roughly in the middle in terms of coverage and cost — gold and bronze plans are a viable and sometimes cheaper option.
In fact, there are hundreds of counties nationwide where premium tax credits cover the full premium for the lowest-cost bronze plan, according to KFF, effectively leaving some consumers with zero monthly insurance costs. It’s quite the sell upfront, but only if consumers don’t mind high out-of-pocket costs once they need care. Bronze plan deductibles can be very high, meaning people with this plan need to pay thousands of dollars before the insurer starts to pay its share.
“If it’s well publicized, it could be a good idea for the young invisibles, if they are low-income,” said Sloan. Whether this happens, who knows, he said.
Islara Souto, the statewide navigation project director for Epilepsy Foundation in Florida, couldn’t recall a time she personally enrolled anyone in a bronze plan. Her navigator program covers 35 counties and enrolled nearly 3,000 people last year in either the Marketplace or Medicaid.
“They want to use their insurance; they don’t want it to collect dust,” Souto said referring to the high deductible that deters her costumers from buying bronze plans.
Souto told ThinkProgress that a lot of her customers are interested in coming and perusing their options. She has scheduled seven appointments last week after speaking with 15 current enrollees. She hopes they will take advantage of all options available.
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Ex-Trump campaign adviser: Papadopoulos was just a 'coffee boy'
Former Trump campaign adviser Michael Caputo downplayed George Papadopoulos' role in the 2016 campaign, calling him a volunteer "coffee boy."
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White House releases official portraits of Trump, Pence
The White House released the official portraits of President Donald Trump and Vice President Mike Pence on Tuesday, more than nine months after they took office.
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Ben Krasnow Tackles ‘E-Paper Hacking’ Using ‘Chip on Glass’ Tech for 3Hz Refresh Rate
In this episode of Applied Science, Ben Krasnow examines a 4.2″ 400×300 e-ink display from Wavetech, explaining how the e-paper display works, as well as showing the ‘chip on glass‘ tech powering this specific module, and getting the display to refresh at 3Hz for pretty smooth animations, on e-paper! Watch:
How to modify E-paper display firmware to get 3Hz update rate.
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From A Garage to Its Own Warehouse, How Boxed Grew Fast
Cheih Huang of Boxed shares how did he scaled his business so fast, and what he learned about how to grow a business to the size it needs to be.
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New Jersey Likely to Elect a Governor Determined to Legalize Marijuana
A legalization bill is sailing through the Legislature and Democrat Phil Murphy has pledged to sign it. He has a commanding lead in the polls.
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Author who predicted Trump's win pens 'Win...
Author Scott Adams predicted in 2015 that Trump had a 98 percent chance of winning. Adams joins Morning Joe to discuss Trump as a master persuader and his new book 'Win Bigly.'
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Ben Krasnow Tackles ‘E-Paper Hacking’ Using ‘Chip on Glass’ Tech for 3Hz Refresh Rate
In this episode of Applied Science, Ben Krasnow examines a 4.2″ 400×300 e-ink display from Wavetech, explaining how the e-paper display works, as well as showing the ‘chip on glass‘ tech powering this specific module, and getting the display to refresh at 3Hz for pretty smooth animations, on e-paper! Watch:
How to modify E-paper display firmware to get 3Hz update rate.
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Unbuttoned: Paul Manafort’s Shopping Sprees Hit Home
Clothes maketh the man but they can also bringeth him down. The indictment of the former Trump campaign manager indicated that he spent about $1.3 million in New York and Beverly Hills.
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Mueller puts out 'just enough to scare'...
What is the message Mueller is sending with his indictments? What is Manafort's next step? Law professor Ryan Goodman, Matthew Miller and Dr. Evelyn Farkas discuss the latest details.
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Trump distances himself from indictments, says Papadopoulos has 'proven to be a liar'
President Trump said “low level” campaign volunteer George Papadopoulos has “already proven to be a liar,” again promising “no collusion,” and urged the special counsel to investigate the “DEMS” early Tuesday in the wake of the special counsel’s first round of charges in the probe into Russian meddling and potential collusion with Trump campaign officials in the 2016 presidential election.
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Trump tries to dismiss adviser he praised as
The pattern is amazing: when someone in Donald Trump's orbit is embroiled in scandal, he pretend to barely know who they are.
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Case-Shiller: National House Price Index increased 6.1% year-over-year in August
S&P/Case-Shiller released the monthly Home Price Indices for August ("August" is a 3 month average of June, July and August prices).
This release includes prices for 20 individual cities, two composite indices (for 10 cities and 20 cities) and the monthly National index.
Note: Case-Shiller reports Not Seasonally Adjusted (NSA), I use the SA data for the graphs.
From S&P: The S&P Corelogic Case-Shiller National Home Price NSA Index Reaches New High as Momentum Continues
Click on graph for larger image.
The first graph shows the nominal seasonally adjusted Composite 10, Composite 20 and National indices (the Composite 20 was started in January 2000).
The Composite 10 index is off 5.8% from the peak, and up 0.5% in August (SA).
The Composite 20 index is off 3.1% from the peak, and up 0.4% (SA) in August.
The National index is 4.3% above the bubble peak (SA), and up 0.5% (SA) in August. The National index is up 41.0% from the post-bubble low set in December 2011 (SA).
The second graph shows the Year over year change in all three indices.
The Composite 10 SA is up 5.4% compared to August 2016. The Composite 20 SA is up 6.0% year-over-year.
The National index SA is up 6.1% year-over-year.
Note: According to the data, prices increased in 19 of 20 cities month-over-month seasonally adjusted.
I'll have more later.
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This release includes prices for 20 individual cities, two composite indices (for 10 cities and 20 cities) and the monthly National index.
Note: Case-Shiller reports Not Seasonally Adjusted (NSA), I use the SA data for the graphs.
From S&P: The S&P Corelogic Case-Shiller National Home Price NSA Index Reaches New High as Momentum Continues
The S&P CoreLogic Case-Shiller U.S. National Home Price NSA Index, covering all nine U.S. census divisions, reported a 6.1% annual gain in August, up from 5.9% in the previous month. The 10-City Composite annual increase came in at 5.3%, up from 5.2% the previous month. The 20-City Composite posted a 5.9% year-over-year gain, up from 5.8% the previous month.
Seattle, Las Vegas, and San Diego reported the highest year-over-year gains among the 20 cities. In August, Seattle led the way with a 13.2% year-over-year price increase, followed by Las Vegas with an 8.6% increase, and San Diego with a 7.8% increase. Nine cities reported greater price increases in the year ending August 2017 versus the year ending July 2017.
...
Before seasonal adjustment, the National Index posted a month-over-month gain of 0.5% in August. The 10-City and 20-City Composites reported increases of 0.5% and 0.4% respectively. After seasonal adjustment, the National Index recorded a 0.5% month-over-month increase in August. The 10-City Composite and 20-City Composite both posted 0.5% month-over-month increases. Nineteen of 20 cities reported increases in August both before and after seasonal adjustment.
“Home price increases appear to be unstoppable,” says David M. Blitzer, Managing Director and Chairman of the Index Committee at S&P Dow Jones Indices. “August saw the National Index annual rate tick up to 6.1%; all 20 cities followed in the report were up year-over-year while one, Atlanta, saw the seasonally adjusted monthly number slip 0.2%. Most prices across the rest of the economy are barely moving compared to housing. Over the last year the consumer price index rose 2.2%, driven largely by energy costs. Aside from oil, the only other major item with price gains close to housing was hospital services, which were up 4.6%. Wages climbed 3.6% in the year to August.
“The ongoing rise in home prices poses questions of why prices are climbing and whether they will continue to outpace most of the economy. Currently, low mortgage rates combined with an improving economy are supporting home prices. Low interest rates raise the value of both real and financial longlived assets. The price gains are not simply a rebound from the financial crisis; nationally and in nine of the 20 cities in the report, home prices have reached new all-time highs. However, home prices will not rise forever. Measures of affordability are beginning to slide, indicating that the pool of buyers is shrinking. The Federal Reserve is pushing short term interest rates upward and mortgage rates are likely to follow over time, removing a key factor supporting rising home prices.”
emphasis added
Click on graph for larger image.The first graph shows the nominal seasonally adjusted Composite 10, Composite 20 and National indices (the Composite 20 was started in January 2000).
The Composite 10 index is off 5.8% from the peak, and up 0.5% in August (SA).
The Composite 20 index is off 3.1% from the peak, and up 0.4% (SA) in August.
The National index is 4.3% above the bubble peak (SA), and up 0.5% (SA) in August. The National index is up 41.0% from the post-bubble low set in December 2011 (SA).
The second graph shows the Year over year change in all three indices.The Composite 10 SA is up 5.4% compared to August 2016. The Composite 20 SA is up 6.0% year-over-year.
The National index SA is up 6.1% year-over-year.
Note: According to the data, prices increased in 19 of 20 cities month-over-month seasonally adjusted.
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