Relevant and even prescient commentary on news, politics and the economy.

The Overseas Cash Grab

NYT Dealbook points to a how the 2 trillion dollar overseas money can come “home” and how money is spent.  2005 comes to mind the last time repatriation of “overseas money” comes to mind.

Linda Beale Repatriation holiday lobbying – Money Speaks and More on repatriation.

Taxprof blog here and Senate report here.

The Overseas Cash Grab (from Dealbook)

Corporate chiefs in the United States have bemoaned for years the taxes that they would face if they brought home more than $2 trillion in cash kept overseas.

They may soon stop complaining. President Trump and the Republican-controlled Congress are widely believed to be open to lowering taxes on funds that companies bring back.

For lawmakers, the idea of a tide of funds coming home creates visions of infrastructure investment and job creation. But on Wall Street, it has set off hopes for another spending priority: mergers and acquisitions. And deals often lead to job losses.

The differing visions come amid a broader debate about whether cutting taxes spurs investment or leads to higher incomes and more jobs.

Among other things, there are questions about the ways people respond to lower taxes. If your tax is lowered, would you strive to be more productive at work? Or would you take advantage of a higher income that came at no extra effort?

Either way, the more pressing issue may be at whether a tax overhaul can happen at all.

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Jamie Dimon on labor force participatioin and disability

by New Deal democrat

Jamie Dimon on labor force participation and disability

First of all, sorry for the light posting this week. I’ve had some urgent business I need to attend to irl.

But I wanted to post this for future reference. Via Business Insider, this is from Jamie Dimon’s letter to stockholders:

If the work participation rate for this group [men ages 25-54] went back to just 93% – the current average for the other developed nations – approximately 10 million more people would be working in the United States. Some other highly disturbing facts include: Fifty-seven percent of these non-working males are on disability ….

I don’t know where he got the 57% statistic from, but if it is true it is potent evidence that the main factor behind the 60 year long decline in prime age labor force participation by men is an increase in those on disability, probably due to both the expansion of the program, and better longevity and diagnostics — and probably also tied in to opiate addiction as well.

cross posted with Bonddadd blog

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Could Incompetence Lead To Reelection?

by Barkley Rosser  (originally published at  Econospeak)

Could Incompetence Lead To Reelection?

I know, I know, it is way too early to talk about the presidential election of 2020, so maybe this is more relevant to midterms, and more likely it is just something merely momentary.  Nevertheless, it occurs to me that the increasingly apparent incompetence of our current president could possibly play into helping him get reelected in 2020.

His incompetence is manifesting itself substantially in his inability to achieve many of the things that he campaigned on most loudly, including repealing and replacing Obamacare, introducing massive trade protectionism, sharply cutting taxes for the rich, and sharply stopping immigration. Of course his new administration, which included probably the most incompetent, insane, and corrupt set of cabinet secretaries and other officials in US history, are doing and will be doing things that will be terribly damaging to American society on many fronts, including the environment, education, womens’ rights, the arts, financial market stability, minority rights, and a long list of others, with many of these very important.  The Trump administration is doing and will do a great deal of damage.  But none of  these were really red meat headline issues in his campaign.  They were not the items that got his angry mobs at rallies chanting and yelling and more generally making public fools of themselves while scaring much of the rest of the population.  Those issues were the ones I mentioned up front, the ones that Trump seems so far not to be actually doing much about after all the ranting and raving.

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A little bit about our supreme court and corporate power

In case you did not see this, it is my Senator’s opening comments at the Gorsuch hearings.  He sums up just what a 5/4 split court has been doing.

 

This is his discussion on Cspan about his book: Captured: The Corporate Infiltration of American Democracy

 

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Why Economists Are Bad At Economics

by Sandwichman

Why Economists Are Bad At Economics

If you want an informed, thoughtful analysis of the effects of robotization on productivity, investment, employment and wages, ask an art school professor. Jason E. Smith’s two-part series, “Nowhere to Go: Automation, Then and Now,” (part one and part two) at Brooklyn Rail cuts through all the statistical aggregation category errors to highlight the accumulation dilemma that economists just don’t seem capable of either grasping or admitting.

Current speculations on both the promise and threat of automation are confronted with an ongoing crisis of accumulation. In this climate, a fragmentary implementation of automation is unlikely either to liberate large fractions of humanity from work, or produce mass unemployment of the sort envisioned over and again by commentators for the past century.

Smith has a PhD in comparative literature, which perhaps explains why he can tell the difference between an arbitrary catch-all term like “service sector” and the very different and distinctive components that are lumped together in it. Both promise and threat evaporate when the components are dis-aggregated and the jumble untangled. Definitely worth a read.

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The Murder Rate – A Regression with Many Variables

In this post, I want to look at the murder rate, by state. I ran a regression with the state murder rate for 2015 as the dependent variable, and literally threw the kitchen sink at it: demographics, weaponry, income, education, population density, etc. Basically, if its something some reasonable percentage of the population believes matters, and I could find data for it, I threw it into the hopper.

I also included variables relating to immigration status. The latter stems from some from some debate in the comments section to other posts in which I stated my belief that illegal immigrants drive up the crime rate. Several detractors insisted that illegal immigrants have lower, not higher crime rates than the rest of the population, and that I am racist to boot. Before presenting results, I will note – I am not too proud to admit the regression results did not fit with my preconceptions. I am also not too proud to admit the regression results did not fit with the preconceptions of my detractors. Finally, while I am always interested in whatever the data has to say, I suspect my detractors will really, really not the results.

So… without further ado, the output from R:

r output 20170402a

What does this all mean? Simply put, only two variables are statistically significant at the 5% (or even 10%) level: percent of the population made up of non-Hispanic Whites, and population density. The greater the share of the population made up of non-Hispanic Whites, the lower the murder rate. On the other hand, the greater the population density, the higher the murder rate. To those who don’t use statistics very often, remember – this is taking into account all other variables.

Now, there are a few variables that come close to being statistically significant at the 10% level. In other words, it is possible (not necessarily likely, just possible) that under other circumstances – with a better defined model, or more precise variables – these variables would prove to be statistically significant as well. These variables are:

1. Percent of the population made up foreign citizens here legally. That variable would have a negative effect on the murder rate if it were statistically significant.
2. Percent of the population that is Asian. This variable also would have a negative effect on the murder rate if it were statistically significant.
3. Percent of the population age 18 to 64. Obviously, most of the murders are committed by people within a subset of this range – probably around 18 to 30. If I had the data to separate out this cohort, I believe we would find that the more people in this cohort, the greater the murder rate.

So… what doesn’t matter? First, the percentage of the population made up of illegal immigrants. Ditto the percentage of the population made up of naturalized citizens. These did not increase the murder rate nor lower it. If the murder rate parallels the crime rate in general, then the media narrative that illegal immigrants have lower crime rates than the population as a whole is not supported and to some extent contradicted by the data.

Second, race & ethnicity don’t matter, at least once you pull out non-Hispanic Whites and maybe Asians. Holding all other variables (including education and income) constant, it doesn’t appear that the murder rate differs in a statistically significant way from one non-Hispanic White or Asian racial/ethnic group to another.

Median income doesn’t matter. Neither does the percentage of the population with an income under 20K. Or the percentage of the population with an income over 100K. Or education level. The murder rate is not affected by these variables.

Another thing that doesn’t matter is the degree to which the population happens to be armed. And Lord knows, there are all sorts of variables here. These include “destructive devices” (think grenades, rockets, missiles, mines, poison gas, explosives, or incendiary devices – apparently all these and more are registered by the ATF), machine guns, silencers, short barreled rifles, short barreled shotguns, or other. The innocuous sounding other group includes your garden variety revolvers and pistols.

So essentially, in summary – accounting for education, income, nativity. immigration status, the regression suggests that having more non-Hispanic Whites decreases the murder rate, and having a greater population density increases the murder rate. No other variables in this regression are statistically significant.

Anyway, I can babble on about the results. For example, it would be interesting to see immigrants (both legal and illegal) broken up with enough granularity to see if the results of non-Hispanic Whites and Asians apply to immigrants as well.

But enough of my prattling. What are your thoughts?

As always, if you want my spreadsheet, drop me a line. If you contact me within a month of the publication of this post, I will send it to you and possibly make some sort of witty remark. Since I am adorable, I probably will send you my spreadsheet after that date as well, but I reserve the right to have a file crash, lose my computer, acquire dementia, or die if too much has elapsed. My contact info is my first name (mike) and a dot, then my last name (kimel – only one m there) at gmail dot com.

Links and details to the data are in my spreadsheet.  But if you want to replicate it yourself (it was a pain in the butt, but who am I to stop you?) the data are listed below. Where possible (which was the case for only a few exceptions, as noted below), I tried to use 2015 data to match the murder rate.

2014 data on firearms came from Exhibit 8 from this document produced by the Bureau of Alcohol, Tobacco and Firearms.

Population from the Census. 2015 data was used for most purposes. 2014 data was used for firearms per capita data.

Population density from 2010 was obtained from the Census.

2015 median hh income came from the Census.

A number of other variables came from the Census CPS Table Creator. This was used for data on race, income, native v. naturalized citizens v. foreigner, educational attainment, age, and gender.

Pew estimates on illegal immigrants, including Mexican v. non-Mexican, were available for 2014.

Finally, the number of 2015 murders originated with the FBI, but was present in this handy dandy file compiled by the Murder Accountability Project.

 

Update…  April 2, 2017  4:01 PM

I forgot to mention a couple corrections to the data:

1. The Pew data on % of illegal aliens that come from Mexico included a few NAs, in each case for states with a very low percentage of the population being made up of illegal immigrants.  In those instances, I assigned the national average share (i.e., 52% of the unauthorized aliens are from Mexico).

2.  The CPS table information on race and ethnicity had a few examples where no information was given for a given combination of race & ethnicity.  In each case, it was possible to determine that the number was very small because the sum total of the other race & ethnicity combinations came close to 100%.  In those instances, I simply replaced the NA with a zero.

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How Between-Firm Inequality Drives Economic and Social Inequality

Conversable Economist takes an interesting look at inequality: (worth a look…hat tip Spencer England)

How Between-Firm Inequality Drives Economic and Social Inequality

“The real engine fueling rising income inequality is `firm inequality’: In an increasingly winner-take-all or at least winner-take-most economy, the best-educated and most-skilled employees cluster inside the most successful companies, their incomes rising dramatically compared with those of outsiders. This corporate segregation is accelerated by the relentless outsourcing and automation of noncore activities and by growing investment in technology.”

In contrast, a rise in between-firm inequality suggests that the US and other leading economies are becoming a more economically segregated, in the sense that those with high pay and those with lower pay are becoming less likely to have the same employer. It means that the classic “American dream” success story, of someone being hired in the mailroom or as a secretary or janitor, and then getting promoted up the company ladder, is less likely to occur. Nowadays, those jobs in the mailroom or the secretarial pool or the janitorial work are more likely to involve working for an outside contractor. In that sense, some of the rungs on the bottom of the ladder of success have been sawed off.

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