Category: Uncategorized

Post #1855: An example of why you should do Swedish death cleaning as you age.

 

My recent foray into furniture repair has turned into a lesson on why you should do you own Swedish death cleaning as you age.

To recap, this is what is left of a pair of chairs that got tossed to the curb, across the street from me, here in the middle-class suburbs of DC.  They were in great shape when I picked them off the curb, but years of use by my kids took their toll on the half-century-old fabric and foam.

These were discarded, in excellent condition, alongside heaps of other household goods, by the children of an elderly, recently-widowed woman.  Her kids were clearing out her house, as they prepared to move their mother down to Texas to be near them.

At that time, I couldn’t find any images of these on the internet.  I assumed they were 1970s Sears knockoffs of a mid-century-modern design.  Or similar.  Middle-class couple, middle-class house.  Surely these were nothing special.

Yesterday I started putting these back together, as shown in the just-prior post.  At that time, I didn’t even know what to call them.  But they’re pretty nice, and it would be a shame to see them end up in the dumpster.  So why not.

On a whim — now two decades after my first attempt to ID them — I did another Google search.

I have now gotten a certification, from the son of the designer, that this is (or was) what’s left of a pair of Adrian Pearsall Craft Associates chairs.  

Adrian Pearsall is now something of a legend in U.S. mid-century-modern furniture design.  Properly restored, this pair of chairs would be worth thousands of dollars.

Worse, improperly restoring them is something of a sacrilege.  Not for the money lost, but for taking a valued piece of Americana and destroying it.

This is suddenly a different and more complex task.  All my woodworking plans go out the window.  And now I have to figure out how to proceed, now that I know what they are.  I don’t collect antique furniture, so it’s not clear these have any business staying with me.

I guess the real take-away is that these never should have ended up in the trash.  But they did so, because the prior owner left it up to her kids.  I only discovered the chairs’ secret identity because they became part of my own Swedish death cleaning.  I still have no idea what to do with them, but at least I’m making the decision, with an understanding of what they are.

Post #1848: Housing market data.

 

It’s funny how catastrophes linger in our collective memory, but near-catastrophes fade.

Fifteen years ago, the “housing bubble” that developed during the Bush administration finally collapsed, and almost took down the U.S. banking system with it.  To the point where the Federal Deposit Insurance Corporation (FDIC) ran a negative fund balance, due to the wave of bank failures (below).

Source:  FDIC, , courtesy of the Federal Deposit Insurance Corporation (FDIC), s

By now, most have forgotten how crazy housing prices were in some parts of the country.  And what extraordinary measures the Federal Reserve took to avoid a complete collapse of the U.S. financial system.

We’re still dealing with the fallout from the  2008 near-catastrophe.  In particular, that led to more than a decade during which the Federal Reserve kept interest rates low. Lower than the underlying rate of inflation, in fact.  As I see it, the Fed recapitalized a bankrupt U.S. banking industry on the backs of U.S. savers.

But that era of below-zero real interest began to end a couple of years ago.

And nothing much has happened.  Yet.

Yesterday, a friend pointed out that some economic analysts see the U.S. housing market as once again ripe for a collapse in prices.  Given that I own a house, I thought it was well worth taking the time to look at current U.S. housing market data.  And while I was originally skeptical, I’d now have to say, he has a point.  There’s not a lot of sunshine in the current housing market data.

Continue reading Post #1848: Housing market data.

Post #1842: … and the voice of the chihuahua is heard in our land, …

With apologies to Song of Solomon, 2:12.  But surely the blog title makes at least as much sense as ” .. the voice of the turtle … “.  Whatever.  This post isn’t about Bible specifics.

The background here is that a friend, has a little kid, who really likes a stuffed toy, that has a broken electronic voice-box.

The catch is that the toy in question is a 25-year-old plush chihuahua dog.  It was a promotional giveaway from Taco Bell.  It was never meant to be repaired.

There are probably a lot of these exact Taco Bell chihuahua dogs still in existence.  You can buy one on Etsy (below).  But at this point, it’s a fair bet that the 25-year-old batteries in the device either have died, or will soon die, if the toy is actually used as a toy. So if you want one that talks — and the little girl in question definitely wanted that — you’d best be prepared to replace the batteries, at least.

Source:  Etsy (link to page). 

 

So, would I mind trying to fix it?  Needless to say, replacement parts may be an issue.  And in terms of helpful instructions on the internet, I found none.

In the end, I tried to fix four broken Taco Bell chihuahua voice boxes.  You never know who might want to read about fixing a mute Taco Bell chihuahua plush toy.  So I thought I’d document the fix.  It’s not as if hordes of folks read this blog, even on my best days.  Bottom line, three out of four now work. Continue reading Post #1842: … and the voice of the chihuahua is heard in our land, …

Post #1838: Two electrical issues from our recent vacation.

 

My wife and I just returned from a brief vacation in Ocean City (OC), Maryland. 

Our annual OC vacation has changed since our kids have grown up.  Without the need to entertain the kids, the beach experience becomes a lot more, eh, ritualized, for want of a better term. Continue reading Post #1838: Two electrical issues from our recent vacation.

Post #1830A: Leaf extras-for-stat-nerds

 

The statistically savvy among you might have noticed something odd about the graph at the end of the last post.

When I let unconstrained math (via Excel) determine the best straight-line fit to these data points, it appears to tell me that these cars lost about 4% of battery capacity for every 10K miles.

But …

But what that doesn’t do is guarantee that with zero miles, I predict that you’ll have 100% of original capacity.

And that matters, because it looks like a lot of these cars must have lost a lot of range early on, that is, at low mileage.  And that loss of battery range doesn’t get factored into the 4% per 10K range loss estimate.

So this is a rare instance of a straight-line fit for which you are justified in “setting the intercept” manually, rather than letting an unconstrained least-squares fit to the data do it.  By definition, the line has to pass through zero miles matching 100% of original range.

Look what happens when I do that:

On average, pinning the linear trend to pass through 0 miles = 100% of original range, range loss is more like 8% per 10K miles. 

The whole cluster of dots is quite “low” on that graph, so to speak.  Those cars on average followed a path of losing a lot of range early on.  And having the loss taper off to a mere 4% per year.

My guess is that exponential decay is the line you’d like to fit, for something wasting away.  But I can’t seem to get Excel to give a trend passing through the required point, with the required shape.  So I freehanded what I think the Conventional Wisdom says about the time-path of battery loss.

No matter how you cut it, the actual observed battery loss over this range amounts to much more than 4%/10K miles.  The mid-point of the fitted line sits around a 40% loss over 5K miles.  That’s the 8%/year calculated when the regression line was pinned at 100% capacity at zero miles.

Why the high range losses?  Is this just a market for lemons, or are the dashboard estimates biased?

George Akerlof, economist, once wrote a piece whose title began “The Market for ‘Lemons’: ”  The paper is pretty deep, but the takeaway is pretty simple.  In this case, it boils down to: People sell their cars when those cars are lemons, not when they are peaches.

That’s one obvious explanation of why these losses appear far larger-than-expected.  (Where, lurking in the background is the idea that EVs lose, oh, like two percent a year, maybe, based on looking at a few graphs in the past.)  The point is, maybe most of these cars appear in the used car listings precisely because they had above-average battery capacity losses.  And that’s why their prior owners sold them.  And I’m seeing them.

The other possibility is that the mileage estimated from the dashboard readout is substantially biased downwards.  (I know it has a high variance, as it depends on recent driving style.  Leaf aficionados refer to it as the “guess gauge”.  That should just add noise, not bias, I think.)

There is one element of bias in what I did in my calculation, in that the range bars are each about 8 percent thick.  For example, when I saw four range bars, my calculation assumed the car was (4/12 =) 33% charged.  But if four bars is really just 3.5 bars, on average, then that charge level is actually just a shade over 28%, on average.  I would then triple that error in arriving at 100% of charge, and so end up understating total range by a factor of about 15%.

Adjusting for that  would require multiplying my range estimate by (1/.85 =) about 18%.  The upshot is that what looked like a 60-mile range based on the dashboard could plausibly be a 70-mile range in reality.

That said, I’m not sure this materially changes the situation.  No matter how I slice it, the range of the car I’m interested is far lower than the Recurrent.com estimate that I had been looking at.

Finally, I can’t fully discount that the losses observed in this low-end used car sample are typical of a random sample of Leafs.  But if it were, I doubt there’d be many Leaf fans out there.

On net, I think the explanation is that I’m looking at a market for lemons.  By looking only at the low-cost end of the market, and only looking at what people are trying to sell, I’m probably looking at a fairly biased sample of all Leafs.

Unfortunately, that’s the sample of cars I’m buying from, if I continue down this path.  Perhaps time for a re-think.

Post #1816: Bow rehairing finale, fitting the tip wedge.

 

In brief:  I finished rehairing a cheap fiberglass bow by making and installing a version of the tip wedge from this YouTube series by Gilles Nehr.

It’s crude.  I used low-grade poplar wood from Home Depot, and shaped it using sandpaper.

But it works.  My cheap bow is now (inexpertly) rehaired, as shown below.

The one thing I can say for sure is that this goes a lot faster once you have a little experience with it.  Making and fitting the tip wedge took less than an hour.

Continue reading Post #1816: Bow rehairing finale, fitting the tip wedge.