What the Hell?!? Friday - Learning New Things Edition

One of my Facebook friends asked:

Does anyone know of the name of the phenomenon that happens when your brain cramps when learning new things?

One of his friends answered

        Brain Sprain

which is probably technically correct.

But my answer, which they both liked, was

       Conservatism!

Quote of the Day

... The single most effective way of avoiding another financial crisis is to reduce the political influence of the banking sector.
--------  Simon Wren-Lewis

via Mark Thoma

 Exactly so.

What the Hell?!? Friday - Grease Edition

No, not this

This!

 

Seriously

!

Goldfish

Goldfish

source

 

Tasty snack

 ~~~

Silverfish

 source

Not so much

Quote of the Day

Quote of the day from reflectionephemeral, commenting at Noahpinion:

the American right is held together by resentment and tribal affinity, lacking any coherent political or ideological ideas.

The individual health insurance mandate was the conservative health care policy for about a quarter century. Then a black Democrat tried to compromise with the right by agreeing to implement it, whereupon every Republican politician in America denounced it as unconstitutional socialist fascism.

As with Milton Friedman, the career of Ronald Reagan is shot through with actions that would have him read out of today's Republican Party. As president, he repeatedly raised taxes, talked to Mikhail Gorbachev (earning him comparisons to Neville Chamberlain), argued that failing to raise the debt ceiling would be ruinous, and later called for an army for the UN.

To today's right, Reagan and Friedman stand for freedom, America, bald eagles, the Constitution, and Screw You Obama. Learning and writing about things that happened in real life is quite beside the point.

Exactly so. The false memory of St. Ronnie is a wild distortion of reality. Reagan raised taxes 11 times. [the net result was to shift the tax burden from the haves to the have-nots, but - hey - a tax increase is a tax increase.]

Quote of the Day

Peter Dorman at Econospeak has some fun playing "guess who?" with this quote"

Probably it is true enough that the great majority are rarely capable of thinking independently, that on most questions they accept views which they find ready-made, and that they will be equally content if born or coaxed into one set of beliefs or another.  In any society freedom of thought will probably be of direct significance only for a small minority.

I certainly didn't know, and I won't spoil it it by revealing the author, who you can easily identify via teh googly.

And, though I am in full agreement with this quote, considering the author, it does strike me as ranking rather high on the irony scale.

W.A.R. - The Nonsense Side of Sabermetrics

I'm all for statistical analysis.  Properly applied it helps us make sense of things that happen in the real world.  Such is the case with most of the baseball stats known as Sabermetrics.  Improperly applied, though, you get gibberish, like the category of Sabermetric statistics collectively known as "Wins Above Replacement." [W.A.R.]  You can read about it's various guises here.

The basic idea in any version of W.A.R is that you gather a bunch of statistics on a player, and use some algorithm to calculate how many more wins the team accrues because of his play, as compared to an entry level replacement just called up from the minors.

It's nonsense.

Consider the case of an offensive player.  [W.A.R. is also calculated for pitchers, but we'll ignore that.]   According to the chosen algorithm, these stats are aggregated and massaged into a single number that represents that alleged contribution to team wins for that player.   The problem is that statistics are probabilistic, but wins and losses happen in specific instances, where statistics are meaningless.

This is such a fundamental and obvious flaw, that I'm astounded that anyone even came up with the idea.

Consider the just concluded three game series with the Tigers visiting the Yankees.  Game 1, Game 2, Game 3.   In this series, Miguel Cabrera, arguably the best hitter in the game today, "went 7-for-13 with two walks and a strikeout for the series, and homered in three consecutive games, each to a different part of the field."  Also he became "the first player in history to homer off Rivera in consecutive at-bats."  [Quotes from Game 3 link.]

Quite an amazing feat for anyone at any time, and even more so for a hitter who is hobbled with a nagging hip flexor injury.  But how much did all of this contribute to wins?  Sadly, not at all.  His two pops off Rivera in games 1 and 3 were dramatic clutch hits, one tying the game and the other setting the stage for Victor Martinez' game tying blast. But in each case, the Yankees went on to pull out the victory.  In game two, a 9-3 Tigers romp, Miggy's HR was just one RBI among many.

This was great hitting overall, most particularly in dramatic clutch situations, but, alas, a wins contribution of exactly zero.

Just a few days earlier in Cleveland, Don Kelly provided the winning punch with a three run homer in a 5-1 Tigers victory.   What do you imagine Kelly's and Carbera's W.A.R. values are? 

 If you're interested, they are 0.9 and 7.3, respectively.

On the pitching side, 17-1 Max Scherzer, with an ERA of 2.84, 9.95 K/9 and 0.8 HR/9 has a WAR of 4.8.

Really.

So - not only is a win the result of clutch play by an individual in a specific circumstance, it's a team result that depends not only on what the rest of the team is doing, but just as much on what the other team has done on that particular day.

Wins Above Replacement.

Nonsense on stilts.

What the Hell?!? Friday -- “I won’t be accepting any invitation from him in the future to go for a drink.” Edition

Linked without comment, 'cuz - really - what could I add?

The link.

Tigers July Wrap Up

Despite starting the month with a loss and returning from the all star break with a shut out loss to the Royals, the Tigers had an excellent July.  They went 18-8 for the month, after going only 14-14 in May and 14-13 in June, and are now 16 games over .500.

The July win percentage was .692.  An entire season with that win rate would yield 112 victories, the third best record since MLB went to the 162 game schedule.  By wide margins, the Tigers increased their runs per game, while cutting down opponents scoring.  This reverses the June trend, which was gong the wrong way.

Here is scoring by month for the season so far.

There are still a couple of troubling features, though, and they're the same ones that have been there all season: opponents are scoring late inning runs and the Tigers aren't.

Here is the breakdown by inning.

Runs have come early and often, with huge output in innings 1, 2, and 6.  But after the 6th, the offense takes the rest of the day off.  Second inning scoring is the same as that from inning 6 - 9 combined.  Only 18% of Tigers runs come in the final three innings.

This hasn't mattered because the Tigers generally win by a comfortable margin.  But it also accounts for a less than stellar record in close or low scoring games.

It's quite a different story for the opponents.

Tigers out score the other teams in every inning until the 8th, when there is a dramatic reverse.  Opponents score 32% of their runs in the final three innings.  Fortunately, though, the Tigers are putting up big totals, so this has not hurt them too badly - for now.

Here is Tigers scoring per game in July.

Despite the mid-month trough - which looks worse than it is because early and late run totals were so high - the season average to date has been on the rise, and is now at 5.18.  Coming into Tuesdays game, the Tigers led the league in scoring with 2 outs, bring in 218 of their 538 runs [at that time] after 2.  That's a remarkable 40.5%.

During the month they outscored their opponents 153 to 92.  That's 1.66 runs for every opponent's run.

Here are some random stats.

It's good to see the Tigers find their bats, and have things trending the right way. But they still need to score more late runs, and shut down the opposition in the 8th and 9th.

Same as it ever was.

June Wrap Up

May Wrap Up

April Wrap Up

Anticipation

The other night watching the Tiger's game, I cited the fact that Max Scherzer gets the best run support of any pitcher in MLB, and within seconds the announcers repeated what I said - not word for word, but certainly the same thought.

Things like that happen once in a while, and it's always striking, at least until the moment passes.

Now it's happened with Krugman.  I've mentioned before that I love it when he agrees with me.  This time I anticipated a rather more complex thought.  In response to this post, on Wednesday one of my FB friends asked if I thought a deep recession or stock market crash was inevitable.

My response: "I don't think anything is inevitable. We could limp along like this, with gradually dimming expectations for 1000 years. It's happened before."

Not a lot of detail, but the intent is clear.  Then today Krugman said this:

But won’t there be an ever-growing demand from the public for action? Actually, that’s not at all clear. While there is growing “austerity fatigue” in Europe, and this might provoke a crisis, the overwhelming result from U.S. political studies is that the level of unemployment matters hardly at all for elections; all that matters is the rate of change in the months leading up to the election. In other words, high unemployment could become accepted as the new normal, politically as well as in economic analysis.

I guess what I’m saying is that I worry that a more or less permanent depression could end up simply becoming accepted as the way things are, that we could suffer endless, gratuitous suffering, yet the political and policy elite would feel no need to change its ways.

He's not quite predicting a lighting quick return to the dark ages, but I'd say we're on the same wave-length here.

Quote of the Day

Quote of the day, in reference to what is happening in Texas, N. Carolina and sadly many other places where Rethugs are in control of the legislatures:

"We're going back to the dark ages at light speed."
---- My Lovely Wife

The Standard Deviation of NGDP Growth Since 1950 - Revised

This is a follow up to The Standard Deviation of NGDP Growth During the Great Inflation.  In that post I showed this 100 point scatter graph of the 12 Quarter average Compounded Annual Rate of Return [CARC] of NGDP vs 12 quarter Standard Deviation [Std Dev] of CARC from 1954 to 1978.  It then occurred to me that some of those red dots that have fallen down close to the yellow trend line might be misallocated.  What they represent are 3 quarters in 1957 when Std Dev had a chance to settle down between recessions, and the tumble down of Std Dev in the early 60's as the high Std Dev values of the the 1960 recession fell out of the 12-point data kernel.

This is illustrated in Graph 1.

Graph 1 CARC vs Std Dev 1954-78, With Points Reallocated

The red dots are data points from 1954 through Q1 '62.  The yellow dots are from Q1 '64 on. The blue dots are the three low Std Dev points from 1957, and the pink dots represent the transitions in and out of the 1957 blue-dot data, and the tumble down in Std Dev from Q2 '62 to Q4 ''63.  The original blue trend line is retained for comparison.  Note that removing these three blue and 8 transitional data points from the pre-1964 data set causes the negative correlation of that period to completely evaporate.

This might seem a bit arbitrary; but now we can observe a more tightly packed red data set, and the behavior of the pink data points does seem to be unusual.  The string of high side outliers in the yellow data set occurs in 1971-2, and is associated with the 1970-71 recession.

This piqued my curiosity, so I took a look at the bigger picture - all 253 quarterly data points from Q1 1950 through Q1 2013, shown in Graph 2. 

 Graph 2 - CARC vs Std Dev 1950 to 2012

I see the great majority of these points clustering or stringing out along imaginary upward sloping lines that suggest coherent data subsets, and a relatively small number of points [39, or 15.4% of the total] where the data is in transition between sets.

I parsed it out as shown in graph 3.

Graph 3 - CARC vs Std Dev 1950 to 2012 - Parsed Data

The data points are color coded to correspond with the straight lines that best fit each subset of data, describing 5 distinct realms.  Equations for the lines and R^2 values are also presented in corresponding colors.

The 39 light green dots represent the lowest Std Dev to CARC relationship.  The 72 dark green dots represent a slightly higher relationship. These two subset occur across all decades from the 60's on in times of stable NGDP growth, i.e times outside of recessions.  There are 41 blue points, representing a medium-high relationship.  These occur when the economy is either in or coming out of a recession.   The 53 yellow points represent a high Std Dev to CARC relationship.  This has occurred during especially severe recessions, or when recessions repeat within the 12 quarter data kernel.  The 8 red dots at the top of the graph are ultra-high.  They demonstrate the severe economic instability of the early post WW II years.  Four of these subsets exhibit extremely high R^2 values, above 0.91; and the fifth  [yellow] is quite respectable at 0.74.  The 39 pink dots occur in discrete short periods when Std Dev rises or falls sharply.

This is an unusual way of looking at GDP data, but I feel pretty good about it, because the linear subsets sort themselves out quite reasonably, and to my eye do not look contrived.  Also, the data points of each subset generally follow the trend lines, in either clusters or strings, for several consecutive quarters.  These subsets are trend stationary along the entire time span of the FRED data set, irrespective of inflation or disinflation; high or low levels of NGDP growth; and whether CARC is rising or falling.  This suggests that the relationship between CARC and Std Dev is not random.  Rather, it is deterministic, and also quantized.  I'm reminded of the chart of nested Phillip's curves Noah Smith posted, and the quantization of electron energy levels diagram shown here.

To draw an analogy, recessions provide the activation energy to boost the Std Dev from a low level trend line to a higher level trend line.  When the recession ends, the Std Dev naturally decays down to a lower level.

To bring this back into the real world, Graph 4 shows the 12 period CARC average from 1950 to 2013, with the CARC data points color coded to correspond with graph 2.

Graph 4 - CARC Color Coded to match Graph 2

The color coding is indicative of the economic conditions as described for Graph 3.   Note that each of these data sets is coherent, irrespective of the inflationary environment or the long trend NGDP growth level.  It is the presence or absence of recessions that mainly determines the realm in which the Std Dev of CARC resides. Outside of recessions, the data resides along one of the green lines.  When not following any of these lines, the CARC - Std Dev relationship is transitional, moving into and out of recessions.

What strikes me is that I simply eyeballed straight lines through this scatter of data as an exercise in curiosity, and it wound up making some sort of coherent sense. Each of the realms associated with the best fit lines is trend stationary in a way that is robust across time and varying economic conditions.

But NGDP growth, per se, tells you absolutely nothing about either the rate of inflation nor the Std Dev realm.  So - the big question in my mind is this: how can NGDP targeting be expected to lead to controlled, relatively stable economic growth at any desired level, unless you can also control not only the underlying rate of inflation, but also which Standard Deviation realm you end up in?

For anyone who's curious, Graph 5 shows the CARC - Std Dev scatter, color coded this time by decade.

Graph 5 - CARC vs Std Dev by Decades

Red - 1950-59
Yellow - 1960-69
Light Blue - 1970-79
Purple - 1980-89
Orange - 1990-99
Green - 2000-09
Blue - 2010-13

Note three things. 1) As the data moves across time, when it gets to one of the realms described by Graph 3, it tends to linger there.  These trend stationary realms have real traction.  2) Transitions generally take a short, quick route to the next trend line.  3) Since 1980 there has been a choppy but relentless migration to lower and lower NGDP growth.  We are now stuck in the worst recovery on record, and the lowest growth period ever to occur outside of a recession.  In fact, NDGP growth is now lower than that which has occurred within most recessions.

Whether fiscal policy, monetary policy, trade policy or something else I can't think of  is to blame, this is, to borrow a phrase from my seven-year-old granddaughter Emily, a "total epic fail" of economic policy.  It is grim on a scale unprecedented in the post WW II period.