Universal Basic Income--Combined With What Else? [feedly]

Resources and Research on UBI from Tim Taylor

Universal Basic Income--Combined With What Else?
http://conversableeconomist.blogspot.com/2019/09/universal-basic-income-combined-with.html

The idea of  a "universal basic income" has some immediate attraction. If we can land an astronaut on the moon, etc., etc. But along with other slogans like a guaranteed government job or single payer health insurance, the devil is in the details.

Three recent essays offer a useful overview of the choices and tradeoffs. Melissa S. Kearney and Magne Mogstad have written "Universal Basic Income (UBI) as a Policy Response to Current Challenges" for the Aspen Institute Economic Strategy Group (August 23, 2019). Also, the most recent issue of the Annual Review of Economics, published in August 2019, has a three-paper symposium on the universal basic income.

• "Universal Basic Income: Some Theoretical Aspects," by Maitreesh Ghatak and François Maniquet
• "Universal Basic Income in the United States and Advanced Countries," by Hilary Hoynes and Jesse Rothstein
• "Universal Basic Income in the Developing World," by Abhijit Banerjee, Paul Niehaus, and Tavneet Suri

For those who don't have access to the Annual Review of Economics, the first paper is freely available here, the second paper is available as an NBER working paper here, and the third paper is freely available here.

An underlying theme of these discussions is that it is essentially meaningless to discuss the idea of a universal basic income in isolation. Whether you are talking about cost, or effects on distribution of income, or effects on work incentives, it matters considerably whether the universal basic income is views as an addition to any existing income transfer programs, or as a replacement for at least some of those programs.

For example, consider the question of cost.  Hoynes and Rothstein explain this way:

A universal payment of $12,000 per year to each adult U.S. resident over age 18 would cost roughly $3 trillion per year. This is about 75 percent of current total federal expenditures, including all on- and off-budget items, in 2017. (If those over 65 were excluded, the cost would fall by about one-fifth.) Thus, implementing this UBI without cuts to other programs would require nearly doubling federal tax revenue; even eliminating all existing transfer programs – about half of federal expenditures – would make only a dent in the cost. ...

A truly universal UBI would be enormously expensive. The kinds of UBIs often discussed would cost nearly double current total spending on the "big three" programs (Social Security, Medicare, and Medicaid). Moreover, each of these programs would likely be necessary even if a UBI were in place, as each addresses needs that would not be well served by a uniform cash transfer. Expenditures on other existing programs sum up to only a small fraction of the cost of a meaningful UBI. This suggests that a full-scale UBI would require substantial increases in government revenue. The impacts of whatever taxes are imposed to generate this revenue are likely of first-order importance in evaluating the impact of a UBI.

This insight helps to explain why no high-income country has actually adopted a "universal" basic income, and why most proposals for a "universal" basic income aren't really a simple universal payment. Instead, such proposals often include various phaseouts of the payments as other income rises, or rules that some of the money must be spent on purchasing health insurance, and so on and so forth.

On the issue of how a universal basic income would affect the distribution of income, the answer again depends on the extent to which is might replace other programs. The United States, like many other countries, uses "tagging" in its transfer programs, which means that transfer payments are often linked to some characteristic other than income. For example, payments may be linked to age (like Social Security), or to disability, or to whether or how many children are in a household (like Medicaid, the earned income tax credit, food stamps, and others).

Consider the proposal that is sometimes made for taking all the funds now spent on income transfers, and instead using that money for cash payments in the form of a universal basic income. (In "Universal Basic Income: A Thought Experiment" (July 29, 2014), I discuss one proposal along these lines for the US.)  As Hoynes and Rothstein explain, even if you cannibalized all spending on Social Security, Medicare, Medicaid, and every other program that involves government transfers, it wouldn't be enough to support a universal basic income of $12,000 per person. But set aside the cost arguments and instead focus on how the redistribution of income would be affected by moving away from a "tagging" system.

Hoynes and Rothstein do various calculations of how a universal basic income that replaces other government programs would affect who receives the funds. It shouldn't be any surprise that if you stop targeting the elderly, the disabled, and families with children, then households with those characteristics will get less. In contrast, households that are nonelderly, nondisabled, and with no children get tent to get more. They write:

This implies that were we to eliminate current income support programs and apply the funds towards a pure UBI, there would be a relative redistribution from low-earners to zero earners, but the first-order effects would be a massive distribution up the earnings distribution, along with a redistribution from the elderly and disabled towards those who are neither, primarily but not exclusively those without children.

As Kearney and Mogstad write: "The complexity of existing redistribution problems is a real issue, but the complexity is in large part based on seeking to address specific needs for specific groups: health care, housing, food, energy costs, and so on." For those attracted by the simplicity of just paying a flat cash amount to everyone, not linking benefits to family status or type of service, it's important to think seriously about what this shift away from tagging would be giving up.

Another main set of arguments about a universal basic income involves its interaction with labor markets. There are several arguments here that do not necessarily dovetail very well with each other. For example, some supporters of a universal basic income suggest that it will be needed in the future after the robot apocalypse makes most of human labor obsolete. When this actually happens, I'm ready to revisit this argument. But at present, the unemployment rate has been 4% or less for more tha a year and there are plenty of previous warnings about technological change would lead to permanent mass unemployment (here are examples from 1927, 1964, and 1982) that did not come to pass.

A gentler version of this argument is that a universal basic income would be a way of helping low-wage or low-income workers. But if helping a specific group of low-wage, low-income workers is the goal, then a "universal" payment is a peculiar way of accomplishing it. Instead, it would seem like an expansion of support for low-wage workers, perhaps designed in a way that is linked to work and provides an additional incentive to work, would make more sense.

Would a universal basic income discourage work? The direct evidence on this point remains thin. There have been studies of a few programs that make universal payments to certain groups, like the Alaska Permanent Fund (based on oil revenues from Alaska) or the Eastern Cherokee Native American tribe payments from gaming revenues, but the size of these payments is too small to be a stand-alone income. There have been experiments with something close to a universal basic income in Finland and Ontario, but these experiments were cancelled after a couple of years. There is some evidence from lottery winners, or from increases in disability insurance payments.

 Kearney and Mogstad provide an overview of the available evidence and argue that both economic theory and the existing evidence suggest that a true universal basic income--that is, an income received without any linkage to other income received, will tend to reduce work. In contrast, programs like wage subsidies, job training, or job subsidies seem likely to increase work. They write (citations omitted):

Studies of transfers that are more comparable in size to the types of UBI payments being proposed imply more negative labor supply effects. For example, a study of lottery winners find that, with an average annual prize of $26,000, each $100 in additional earnings reduced labor market earning by $11. A more recent study of lottery winners in Sweden also provides evidence of reduced earnings in response to winning a lottery prize. This study finds that winning a lottery prize leads to an immediate and persistent reduction in earnings. In addition, the effects of any guaranteed income program are likely to most strongly affect those marginally attached to the labor force. On this point, the lessons from expanded access to disability insurance payments is potentially instructive. Economists have found that the marginal beneficiary of a disability insurance award would have been almost 30 percentage points more likely to work had they not received benefits.

An intriguing thought that emerges from several of these papers is that the arguments for a universal basic income may be stronger for low-income countries. As Ghatak and Maniquet emphasize, most low income countries share several characteristics. A larger share of the population is close to subsistence, compared to high-income countries. As a result, a universal payment can help to raise a larger share of population out of poverty, and at a relatively low cost. In addition, the governments of low-income countries often have a hard time implementing detailed tax and welfare policies; for example, such governments may not be able to observe income levels or hours worked very accurately. Thus, linking government payments to income, as well as to disability, number of children, and even age may be more difficult. As they write, "UBI might be more appropriate in developing countries, especially those in which UBI could help circumvent the imperfections of government institutions in charge of helping the poor."

Of the papers I've mentioned here, Ghatak and Maniquet is the only one with a hefty share of math, and thus is likely to be a hard read for the unintiated. However, Banerjee, Niehaus, and Suri dig into the issues of a universal basic income for lower-income countries in more detail. They point out that while we don't have good evidence on pure universal basic income programs in low-income countries (although experiments are underway in some countries), we do  have a lot of evidence on programs in low-income countries that pay cash to recipients under various conditions. They write (citations omitted):

With the most current available data as of 2018, the World Bank identified 552M people living in the developing world who receive some form of cash transfer from their government. While none of these schemes were (to our knowledge) labelled as UBI, they all shared the common and crucial feature that recipients were given the freedom to do what they want with their money. Many transfers (particularly in South and Central America) were paid out conditional on certain conditions being met, but many others (particularly in Africa) were not. And in some cases - pensions, for example - these transfers have a structure (size, frequency, and duration) quite similar to UBI payments, though they are not universal.

What have we learned from the evaluation of these schemes? ...

First, evaluations generally have not found the negative impacts that many feared. Reviewing evidence on "temptation goods," Evans and Popova (2017) find that transfers had on average reduced expenditure on temptation goods by 0.18 standard deviations. In other words, far from blowing their transfers on alcohol and tobacco, recipients appear to drink and smoke less. This finding in no way diminishes the seriousness of substance abuse as an issue for the poor, but it does suggest that lack of money may be a cause of substance abuse rather than a constraint on it. Turning to "dependency" ...  Banerjee et al. (2017b) find no systematic evidence that transfers discourage work.

Second, evaluations have found a great diversity of positive impacts. To give some sense, a partial list of outcomes affected in a positive way in one study or another ... includes income, assets, savings, borrowing, total expenditure, food expenditure, dietary diversity, school attendance, test scores, cognitive development, use of health facilities, labor force participation, child labor migration, domestic violence, women's empowerment, marriage, fertility, and use of contraception, among others. ...

This variety implies that recipients value the flexibility that cash transfers provide: they reveal a preference for many different things. It also implies that a UBI is unlikely to appeal to a technocrat seeking cost-effective ways to increase any particular, narrow outcome.

In addition, they point out that a universal basic income may help economic growth in low-income countries by making it possible for low-income people to deal with the day-to-day risks they face and to make modest investments in small-scale entrepreneurship. And a universal benefit might build political support for a rudimentary social safety net in countries that do not yet have one.

On the other side, even if it is harder for a low-income country to run a precisely targeted income transfer program, imperfect targeting can still be useful. Rema Hanna and Benjamin A. Olken make this case in "Universal Basic Incomes versus Targeted Transfers: Anti-Poverty Programs in Developing Countries," in the Fall 2018 issue of the Journal of Economic Perspectives. They point out that a number of emerging-market countries make transfer payments conditional on behaviors, like whether children attend school or doctor visits, or else on observable characteristics like whether a home has a dirt floor, or a certain kind of roof or appliances. In some places, a "universal" payment requires taking enough time to register for the program or to undertake some work effort that those with higher income see no benefit from applying. In a few places, transfer payments are given to a community, which then must have a formal and open process for distributing those payments among the members of the community. They argue that a truly universal program, with payments going to people of all income levels, is less effective at addressing inequality than a program with imperfect targeting of benefit payments.

Here's a final comparison between universal basic income in high-income and low-income countries that struck as interesting, from the Banerjee, Niehaus, and Suri paper. They point out that one of the arguments for a universal basic income in low-income countries is that employment in such countries is often sporadic, with many people working a variety of part-time gigs rather than a single steady job, which is part of what makes it hard for the government in a low-income country to adjust benefits in response to income and work status. But of course, there is also concern that a greater share of workers in high-income countries are ending up in the "gig economy"  with a series of part-time jobs, which in turn makes it more challenging for high-income countries to set up programs where transfer programs will make sporadic payments in the gaps between sporadic jobs. Banerjee, Niehaus, and Suri write:  

"[D]eveloping countries already look like one possible future for the developed ones: few people hold stable full-time jobs, many work a variety of part-time gigs instead, and as a result, public policy has never been based on an assumption of universal full-time employment. Perhaps in this there is something the rich countries can learn from the poor."

 -- via my feedly newsfeed

What to watch for in the 2018 Census data on earnings, incomes, and poverty [feedly]

What to watch for in the 2018 Census data on earnings, incomes, and poverty
https://www.epi.org/blog/what-to-watch-for-the-in-the-2018-census-data-on-earnings-incomes-and-poverty/

Next Tuesday is the Census Bureau's release of annual data on earnings, income, poverty, and health insurance coverage for 2018, which will give us a picture of the economic status of working families 11 years into what is now the longest economic expansion in United States history. This data is particularly important because it gives us insight into how evenly (or unevenly) economic growth has been distributed across U.S. households. Other data sources that are released more than once a year too often provide only averages or aggregates— but next week's Census release gives a much more textured picture of how the U.S. economy is working for typical households. In particular, next week's release will help us chart the progress made by the typical American household in clawing back nearly two decades of lost income growth—the result of a failure of incomes to return to the business cycle peaks of 2000 during the slow early-2000s recovery and expansion, and the Great Recession. We'll be paying particular attention to differences in the recovery across racial and ethnic groups.

What happened with incomes in recent years?

After adjusting the series to account for changes to the survey made in 2013, in 2017 real (inflation-adjusted) median incomes for American households rose just 1.8 percent and only managed to return to their pre-Great Recession peaks, even coming off of two years (2015 and 2016) of impressive across-the-board improvements. It is important to note, however, that some of the improvements in inflation-adjusted income we saw in 2015 and 2016 were driven by atypically low inflation—0.1% in 2015, and 1.3% in 2016. We didn't get a similar boost from low inflation in 2017 (inflation increased 2.2% in 2017), and don't expect one in 2018 (inflation increased 2.4% in 2018). We anticipate that an additional year of even modest growth will likely bring the broad middle class back to 2000 incomes. But, for non-elderly households, the latest data will be likely still below the peak reached 18 years prior.

Income

What do we expect in this year's release?

Given the data we've seen for 2018 from other sources, it is likely that earnings, income, and poverty in the 2018 Census data will show some improvement over the past year. But it is also likely that this pace of improvement will be significantly slower than the average of the previous three years. As the economy steadily strengthens, we've seen progress in key labor market indicators, including participation in the labor market and payroll employment, which should boost household labor earnings. The unemployment rate ticked down another 0.5 percentage points in 2018, similar to the drop between 2016 and 2017. The overall labor force participation rate was unchanged between 2017 and 2018, but the employment-to-population ratio continued to increase, 0.3 percentage points overall and 0.8 percentage points for the prime-age population (25-54 years old). These are similar to the increases found between 2016 and 2017.

However, our earlier analysis of hourly wage from the Current Population Survey (CPS) data—of which Tuesday's release is a supplement to—suggests that real wage growth in 2018 continues to be unequal and slower than expected at this point in the business cycle. In 2018, strong growth in hourly wages continued at the top (2.7% at the 95th percentile), while the 20th percentile saw the strongest growth at 4.8% due in part to a tightening labor market as well as state-level minimum wage increases. However, median wages grew only 1.6%.

On Tuesday, we will compare changes earnings, income, and poverty against several benchmarks: over the last year, as well as changes since before the Great Recession and since 2000—the last business cycle peak that can be confidently associated with something close to genuine full employment. Women and men working full-time, full-year, both experienced earnings losses between 2016 and 2017. As of 2017, full-time men had yet to return to 2007 or 2000 levels of earnings. We'll also analyze these changes by race and ethnicity to understand how the economy has treated different demographic groups. Again, the hourly wage data are likely the best predictor of what we can expect for these groups. We will also analyze gender and racial wage gaps to see whether we've made any progress in closing these among full-time, full-year workers. If the hourly wage data are any indication, we expect little change, but perhaps a mild narrowing of the gender wage gap as well as a mild widening of the black-white wage gap.

Second on our agenda will be an examination of trends in median household incomes. Again, we will be looking at these data across a range of households: all households, non-elderly households, and by race and ethnicity. As people continue to return to the labor force and get jobs, we should see improvements in incomes, since labor income is the primary form of income for non-elderly households in the middle of the income distribution. Even if individual earnings do not improve significantly, more working members of a household will increase household incomes.

(Also, just a side note on the income data, because of the redesign in 2013, we make an imputation to the historical series, 2000 to 2012 to make them directly comparable to the latest income data. This entails creating a ratio of the original and redesigned 2013 income data within each demographic subgroup, and imputing that backwards to create a consistent series. This is the same adjustment we made last year measuring elderly and nonelderly household incomes as well as incomes by race and ethnicity. The Census Bureau also announced a processing change that will affect data years 2017 and 2018, making them directly incomparable to prior years. Though this is most likely to have the largest effect on health insurance data, incomes and earnings trends are also affected.)

In addition to looking at how median household income growth differed by race and ethnicity, we will examine changes in incomes across the income distribution. Specifically, we will be presenting the growth in income by income fifth and the top 5 percent to assess how much inequality has grown or shrunk over the last few years. Unfortunately, again, the hourly wage data through 2018 indicate that top earners have continued to pull away from the median, and therefore growth in income inequality is likely. Last year, while there was broad-based income growth, the bottom 40% of households still had incomes below their 2000 income levels.

Third, we will provide an analysis of recent trends in poverty. Similar to the previous discussion, we will analyze poverty in 2018 and then make comparisons to 2007 and 2000. We'll also look at poverty by race and ethnicity, and separately for children—who tend to have particularly elevated levels of poverty. Assuming incomes continue to rise, particularly if there's broad-based growth, poverty will hopefully continue to fall.

In addition to the official poverty rate, we will highlight recent trends in the Supplemental Poverty Measure (SPM) being released on Tuesday. The SPM is an alternative to the long-running official poverty measure that attempts to correct some of the substantial weaknesses of the official poverty measure (e.g., the fact that it counts only cash income, often sets possibly too-low thresholds for poverty, and doesn't allow for geographic variability). Because it includes non-cash measures of family income (like food stamps) and the effect of refundable tax credits, the SPM lets us assess how effective public assistance and safety net programs are at lifting people out of poverty. On Tuesday, we will take a deeper look at these data to make an assessment of how poverty, as measured by the SPM, has changed in the recovery and the importance of shoring up not tearing down these programs in future policymaking.

It is important to remember that the data reported next week is the latest installment in just one of the Census Bureau's many long-running series that have been essential to assessing the needs of the American people and the effectiveness of national policies. It's a reminder that fully funding the Census Bureau and all of its useful surveys is critical for accurate measurement of the population and providing necessary insights into the role of policy in improving incomes and reducing poverty.

 -- via my feedly newsfeed

EPI: Racial and ethnic income gaps persist amid uneven growth in household incomes [feedly]

Racial and ethnic income gaps persist amid uneven growth in household incomes
https://www.epi.org/blog/racial-and-ethnic-income-gaps-persist-amid-uneven-growth-in-household-incomes/

esterday's Census Bureau report on income, poverty, and health insurance coverage in 2018 shows that while there was a slowdown in overall median household income growth relative to 2017, income growth was uneven by race and ethnicity. Real median income increased 4.6% among Asian households (from $83,376 to $87,194), 1.8% among African American households (from $40,963 to $41,692), 1.1% among non-Hispanic white households (from $69,851 to $70,642), and only 0.1% among Hispanic households (from $51,390 to $51,450), as seen in Figure A. The only groups for which income growth was statistically significant were Asian and Hispanic households.

In 2018, the median black household earned just 59 cents for every dollar of income the median white household earned (unchanged from 2017), while the median Hispanic household earned just 73 cents (down from 74 cents).

Figure A

Based on EPI's imputed historical income values (see the note under Figure A for an explanation), 11 years after the start of the Great Recession in 2007, only African American households remained below their pre-recession median income. Compared with household incomes in 2007, median household incomes in 2018 were down 2.1 percent for African American households, but up 0.7% for Asian households, 2.3% for non-Hispanic white households, and 13.1% for Hispanic households. Asian households continued to have the highest median income, despite large income losses in the wake of the recession.

The 2018 poverty rates also reflect the patterns of income growth between 2017 and 2018. As seen in Figure B, poverty rates for all groups were down slightly or unchanged, but remained highest among African Americans (20.7%, down 1.0 percentage point), followed by Hispanics (17.6%, down 0.7 percentage points), Asians (10.1%, up 0.4 percentage points), and whites (8.1%, down 0.4 percentage points). African American and Hispanic children continued to face the highest poverty rates—28.5% of African Americans and 23.7% of Hispanics under age 18 lived below the poverty level in 2018. African American children were more than three times as likely to be in poverty as white children (8.9%).

Figure B

The Supplemental Poverty Measure (SPM), an alternative to the long-running official poverty measure, provides an even more accurate measure of a household's economic vulnerability. While the official poverty rate captures only before-tax cash income, the SPM accounts for various noncash benefits and tax credits. The SPM also allows for geographic variability in what constitutes poverty based on differences in the cost of living. According to the 2018 SPM, the official poverty measure understates poverty among Hispanics (the 2018 SPM rate is 21.2% vs. 17.6% by the official poverty measure) and among Asians (14.0% vs. 10.1%), while the measures produce relatively similar rates for whites (8.8% vs. 8.1%) and for African Americans (21.0% vs. 20.7%).

 -- via my feedly newsfeed

Dean Baker/Max Moran/CEPR: Google Is Like Facebook — But a Lot Smarter [feedly]

Interesting article by Dean Baker 's CEPR on lawsuits targeting the tech giants (or not, depending on political savvy).

Clearly, the emergence of the social media and search giants, and Amazon, raise serious challenges about the meaning of privacy, and of property itself, especially as regards "information" and ideas. Currently there is no way to guarantee the security of either on the Internet. And yet, information infrastructures have penetrated vast domains of human and social activity. Going online means your info is now in the possession, ff not yet technically 'owned', by owners of any network nodes or pipes through which the information was transported, including connected origin and destination. Recall the old law school maxim: Possession in 9/10 of the law.

The problems are obvious, and by no means new (although the scale keeps getting vaster). But the fix is not obvious. One difficulty is economic and the fundamental theory of what constitutes a commodity. Marx spent most of a volume of capital on this. Paul Samuelson (a century later) reduced it to a couple rules defining what was NOT a commodity, but instead a "public good". Knowledge is a perfect example of a (inherently) public good. (https://en.wikipedia.org/wiki/Public_good).

For information to be traded as a commodity in a marketplace requires tremendous and complex public (legal) protection, which is only marginally enforceable. Plus, information is a crappy, leaky store of value. Imagine you are a loan officer at a bank and Bill Gates approaches you for a loan, a big one. You ask, what collateral do you have. He puts a compact terabyte hard drive containing a 100 million lines of computer code for Microsoft Windows on your desk. Do you risk the banks money (belonging to other depositors) with that backing? Who else has the same kind of loaded device? or can create new ones at nearly zero cost? If the collateral is accepted, at what premium interest rate do you charge given the discounted value of the collateral? Compare that to land, real estate, a gold mine, etc.

Despite its inherent weakness as a commodity corporations have dived into it as if driven by necessity more than desire only to discover that their business models based on selling copyrighted software were not sustainable. They began transforming themselves into service companies, leaving the property rights associated with the information itself in limbo and clear as mud.

Then comes AI whose value raises accuracy and scope in prediction and automation by orders of magnitude, but which is powered by HUGE data stores. Those stores are being filled at massive rates as the Internet of Things added to the Internets of people and businesses and governments both profit and non profit expand and yield unimaginable concentrations of data. I doubt that breaking up these enterprises under antitrust law will work. I tend to favor changes in governance at the director level and the inclusion of both employee and public voices and access to private decision-making on issues that can result in immense and unsupportable public risks.

  

Dean Baker: Google Is Like Facebook — But a Lot Smarter
http://cepr.net/publications/op-eds-columns/google-is-like-facebook-but-a-lot-smarter

Max Moran
The American Prospect, September 10, 2019

See article on original site

Big Tech is facing an overdue crisis, but not all Big Tech companies are created equal. It's useful to compare and contrast two of the biggest players at the center of these investigations: Facebook and Google.

Both have received constant negative press for the last few years, ranging from the stories on the Cambridge Analytica bombshell to Google's non-stop internal chaos. Both received slaps on the wrist from the Federal Trade Commission, but both are now facing federal and state-level antitrust investigations.

Yet only one has become a full-blown bad guy to the Democratic party. In July, Ohio Senator Sherrod Brown declared that "Facebook is dangerous" when Congress rightly came down hard on its proposed cryptocurrency, Libra. Two weeks later, however, former President Barack Obama happily cavorted at a Google conference in Sicily. The Google-Obama romance is nothing new—he granted the company famously easy access to his White House—and there have been no audible Democratic criticisms of this latest Obama-Google shoulder-rubbing.

Why the double standard? Facebook and Google have similar, icky business models—mass online surveillance for the sake of advertising. Google has repeatedly, strategically, transgressed some of progressivism's cherished values: opposing war, worker's rights, free speech, free assembly, and more. Silicon Valley earned progressives' good graces for being early supporters of LGBTQ rights, yet YouTube—the same Google subsidiary at the center of the recent FTC settlement over illegally gathering data on children—faced biting criticism in June for inaction against homophobia on the platform.

Perhaps Google simply offers more valuable services than Facebook does. I am writing this essay in Google Docs right now, and hope that it performs well in Google Search results. But the company's dominance across multiple tech sub-sectors, to the point where its own name is a verb, ought to draw more scrutiny from lawmakers, not less.

Indeed, Democrats are rediscovering the power of anti-monopoly politics in no small part due to Google's own actions. When the company pressured the think tank New America to squash its nascent Open Markets unit, that small group of thinkers went independent and doubled down on their critique of Big Tech. They're now the most prominent voices in Washington calling for a new age of antitrust. 

But Open Markets' turbulent path is also indicative of why many Democratic institutions still seem fine with Google. The company is a steady backer of some of the most prominent liberal think tanks in Washington, from New America ($1,000,000+ per year) to the Center for American Progress ($50,000 to $99,999 per year), to the Brookings Institution ($100,000 to $249,999 so far this year).

Google executives have also made direct overtures to elites within the Democratic party establishment for years. Eric Schmidt, then-chairman of Google's parent company Alphabet, was such a major player in the Hillary Clinton campaign that he wore a "staff" badge to her would-be victory party in November 2016. He also turned a good profit off of the campaign, through his startup The Groundwork, which was Clinton's top tech vendor. (It's unclear whether any 2020 presidential candidates are currently using The Groundwork.) Clinton's Chief Technology Officer was a former Google executive. And to get the party's archaic data infrastructure up to par for 2020, the Democrats are naturally turning to Google's analytics tools.

Notice how none of these examples concern or reflect Google's lobbying or campaign contributions, the most commonly-cited metrics for influence in Washington. Sure, Google hires plenty of lobbyists and doles out plenty of campaign money. But where Google outshines Facebook is in its wielding of soft money and soft power—tools which aren't designed to directly coerce a lawmaker, but rather, to build that lawmaker's fondness for the company as a whole. Not a single writer or intellectual threw their weight behind Libra to provide Facebook with some cover on Capitol Hill. But Google has a whole network of allies it can draw on in academia and beyond. And all of those favors for the Democratic establishment over the years add up.

It's time that the public, and certainly Democratic elected officials, came to grips with the truth: Google isn't your friend. It isn't your research assistant. It isn't a bunch of quirky nerds tinkering in their dad's basement to create some techno-utopia. It's a multinational for-profit company, and it will fight hard to protect and build its profits, no matter what.

Democrats, if you're reading, here's a shot of reality: Google doesn't just donate to think tanks on the center-left of the political spectrum. It also funds libertarian and right-wing institutions like the American Enterprise Institute, the Cato Institute, and the Heritage Foundation. It's working more and more closely with the Koch network, which has taken a special interest in the new antitrust movement around Big Tech. (Koch Industries, after all, has its fingers in a lot of different economic sectors. Charles Koch's son Chase, the heir-apparent of the corporation, is also tiptoeing into Silicon Valley's venture capital game.)

You can see Google returning the favor in its donation disclosures, which reveal cash flowing to George Mason University, the Kochs' favorite breeding ground for libertarian ideology. Google has been a GMU donor since at least 2011. GMU also hosts an institute which evangelizes weak antitrust enforcement to foreign countries. It is run by Joshua Wright, a former FTC commissioner who has taken plenty of Google money to fund four of his own papers defending Google on antitrust issues.

Google also has ties to the top tech-focused think tanks. It gave at least $200,000 to the Center for Democracy and Technology last year, which has proposed a data privacy bill far feebler than the Californian law that Google is scrambling to weaken. It lists the Information Technology and Innovation Foundation as another funding recipient, but since that think tank doesn't disclose its donors, we don't know the size of the checks. Regardless, ITIF regularly publishes reports like "The Misguided 'Case Against Google'" or "The Costs of an Unnecessarily Stringent Federal Data Privacy Law," whose sourcing has been mocked by tech policy experts.

All of this—the academics, the think tanks, the work for Democratic campaigns—contributes to a strong ecosystem of Google defenders in Washington, and a strong Democratic inclination against acting too harshly. It's uncomfortable to bring the hammer down on a company which, objectively, did a lot to help them during the last administration.

But times have changed. The growing progressive base of the Democratic party needs to know that old friendships, elite cocktail parties, and the proverbial smoke-filled rooms which Google has so masterfully maneuvered won't prevent Democrats from doing what needs to be done: curbing this modern-day titan's abuses. If they don't, then we're likely to get the future Google is building: one with weak settlements when it violates the law, leaked data, and an even more broken political economy.

 -- via my feedly newsfeed

Jared Bernstein: Payrolls slow and the trade war is hurting manufacturing. But underlying job market still solid. [feedly]

Payrolls slow and the trade war is hurting manufacturing. But underlying job market still solid.
http://jaredbernsteinblog.com/payrolls-slow-and-the-trade-war-is-hurting-manufacturing-but-underlying-job-market-still-solid/

Payrolls rose by 130,000 last month and the unemployment rate held at 3.7 percent, close to a 50-year low and the same level as the past 3 months. Still, job growth is cooling (25,000 of this month's gains were temporary decennial Census workers), as the pace of monthly gains, while still strong enough to support low unemployment, has slowed. Wage growth also stayed parked at about where it has been in recent months, and there's some evidence that the trade war is taking a toll on factory jobs. However, the job market remains strong, real wages are growing, and consumer spending will continue to be supported by these dynamics.

The slowdown in payrolls

To get a clearer take on the underlying trend in job growth, our monthly smoother shows the average monthly gain over 3, 6, and 12-month periods. This month, however, we add an extra bar to our usual smoother, as we believe it is important to begin to incorporate a recent BLS revision, based on more accurate jobs data, into our assessment of the US job market. This preliminary benchmark revision estimates that employers added 500,000 fewer jobs to US payrolls between April of 2018 and March of 2019 (BLS will officially wedge their final estimate into the payroll data by Feb 2020). The second bar includes the result of this revision, showing that over the past year, payroll growth was likely closer to 150K per month than 175K per month.

To be sure, this is still solid payroll growth at this stage of the expansion and as noted below, in tandem with real wage growth, it's strong enough job growth to support the recovery and keep unemployment around where it is. However, using the preliminary revised data, the pace of payroll gains has slowed from 1.6% last year to 1.3% this year. Clearly, that's not a big deceleration, and it's also not unexpected in a job market closing in on full employment. But it is a slower trend which I expect to persist.

The trade war

The trade war that the Trump administration has been waging is clearly taking a toll on the global economy. While its impact is greater in countries more exposed to trade, like Germany, than the US, our manufacturers have been hit by these new taxes (tariffs) on their imported inputs and by retaliatory tariffs on their exports. To what extent is this showing up in factory employment, hours, and wages?

Manufacturing employment has slowed since the Trump administration began ramping up tariffs at the beginning of last year. Last month, factory jobs rose just 3K and durable manufacturing employment was unchanged. Thus far this year, the factory sector has added 5.5K jobs per month on average, compared to 22K for all of last year.

The product of manufacturing employment and weekly hours yields the aggregate hour index for the sector, a very good proxy for labor demand. The next figure looks at the year-over-year change in this index for blue collar and for all manufacturing workers. Starting about a year ago, a clear deceleration is evident, and for the non-managers—who comprise about 70 percent of the sector's employment—total hours worked have outright declined in recent months (relative to a year ago).

After slowing in 2018, manufacturing wages for blue-collar workers have picked up pace in recent months and are now growing at about the same rate of other mid-level workers.

In sum, at least in terms of jobs and hours, the trade war is hurting manufacturing workers. I'm sure some will push back that this near-term pain is worth the longer-term gains from a "victory" in the trade war. I find this totally unconvincing, as victory apparently means getting China to be more accommodating to US multinationals. That is, were China to stop insisting on tech transfers, or issue more licenses to our multinationals, we'll get more, not less, offshoring of US jobs.

Wages still stalled

Wage gains are still stalled, though at a level above inflation, so real paychecks are growing on average (see third figure below). The stalling is clear in the 6-months rolling average, and is not particularly surprising as the job market has not particularly tightened further over this period. That is, low unemployment is providing workers with more bargaining clout than they'd have in less tight job markets, but this force appears to be holding steady for now.

Stronger Household Survey

Participation ticked up and the closely watched employment rate for prime-age workers (25-54) hit a cyclical high of 80%, just 0.3 ppts below its 2007 peak. While we can't say much about one month's change, this important measure of core labor market capacity had previously been stalled. If it continues to rise, it will suggest there's still more room-to-run in the job market, and especially given low inflation, a strong rationale for the Federal Reserve to do what they can to extend the run.

Bottom line, the job market will handily support consumer spending in the near term, staving off any recessionary threats from the trade war and the global slowing to which it has contributed. However, payroll gains have slowed somewhat, especially in manufacturing, and, I suspect, in any other sectors with global connections (i.e., tradeable goods and services). We will continue to monitor this and any other fragilities related to the trade war or whatever other unforced policy errors are forthcoming.

 -- via my feedly newsfeed

Jared Bernstein: The 2018 Poverty, Income, and health coverage results: a tale of three forces. [feedly]

The 2018 Poverty, Income, and health coverage results: a tale of three forces.
http://jaredbernsteinblog.com/the-2018-poverty-income-and-health-coverage-results-a-tale-of-three-forces/

This morning, the Census Bureau released new data on health insurance coverage, poverty, and middle-class incomes. While the data are for last year, they shine an important light on key aspects of families' living standards that we don't get from the more up-to-date macro-indicators, like GDP and unemployment.

As the economic recovery that began over a decade ago persisted through 2018, poverty once again fell, by half-a-percentage point, from 12.3 percent to 11.8 percent. Other results from the report show that anti-poverty and income support programs lifted millions of people out of poverty, including 27 million through Social Security alone. Though the real median household income—the income of the household right in the middle of the income scale—increased slightly less than 1 percent last year, the increase was not statistically significant. Median earnings of full-time men and women workers both rose significantly, by over 3 percent for each (for reasons discussed below, sometimes earnings rise significantly but income does not).

Health coverage, however, significantly deteriorated last year, as the share of the uninsured rose for the first time since 2009, from 7.9 percent to 8.5 percent. In total, 27.5 million lacked coverage in 2018, an increase of 1.9 million over 2017. This result is partially driven by actions of the Trump administration to undermine the Affordable Care Act (note that Medicaid coverage was down by 0.7 percentage points), and in this regard, it should be taken as a powerful signal of the impact of conservative policy on U.S. health coverage.

Taken together, the poverty, income, and health coverage results tell a tale of three powerful forces: the strong economy, effective anti-poverty programs, and the Trump administration's ongoing attack on affordable health coverage. A strong labor market is an essential asset for working-age families, and the data are clear that poor people respond to the opportunities associated with a labor market closing in on full employment. Anti-poverty programs are lifting millions of economically vulnerable persons, including seniors and children, out of poverty. But while a strong labor market and a responsive safety net help to solve a lot of problems, the history of both U.S. and other countries shows that it takes national health care policy to ensure families have access to affordable coverage. The ACA was and is playing that role, but efforts to undermine its effectiveness are evident in the Census data.

Poverty, Income, Inequality

The Census provides two measures of poverty: the official poverty measure (OPM) and the Supplement Poverty Measure (SPM). The latter is a more accurate metric as it uses an updated and more realistic income threshold to determine poverty status, and it counts important benefits that the OPM leaves out. While the two measures often track each other, year-to-year, that wasn't the case last year, as the SPM rose an insignificant one-tenth of a percent, from 13.0 to 13.1 percent, while the OPM fell a significant half-a-percent, from 12.3 to 11.8 percent. Because the SPM has a higher income threshold than the OPM, 4.4 million more people were poor by that more accurate measure.

Because it counts anti-poverty policies that the official measure leaves out, one particularly useful characteristic of the SPM data is that it breaks out the millions of people lifted out of poverty by specific anti-poverty programs. For example, refundable tax credits, such as the Earned Income Tax Credit and the Child Tax Credit lifted about 8 million people out of poverty in 2018; SNAP (food stamps) lifted 3 million more out each, and Social Security was the most powerful poverty reducer, lifting 27 million out of poverty in 2018, 18 million of whom were elderly (65 and older).

As noted, median household income, inflation-adjusted, rose less than a percent last year, a statistically insignificant change (meaning a change that is statistically indistinguishable from no change at all). Yet, real median earnings of full-time, full-year workers rose more than 3 percent for both men and women. It is hard to square these results, but they are not that unusual and probably have something to do with the changing composition of households and the fact that the median male worker is different from the median female worker and neither are necessarily in the median household. Note, for example, that family households (basically, two or more related people) and non-family households (people living alone) both rose significantly last year. But when the Census smushes them together, we get an insignificant increase.

I conclude from this and other information in the report, like the fact that the number of full-year workers rose 2.3 million, or the evidence showing real wage gains last year for middle and low-wage worker, that the strong labor market helped to boost family incomes in 2018 (though as I show below, these gains are slowing over time). Another key factor pushing up wage growth at the low end of the pay scale were the minimum wage hikes that occurred in 18 states in 2018, affecting 4.5 million workers, according to EPI.

Here's one way to look at this relationship between labor markets and, in this case, poverty outcomes. It's a scatterplot of unemployment against the change in poverty rates (using the OPM for which we have a long, consistent time series). It shows how low unemployment correlates with declines in the poverty rate and vice-versa. Why? Because able-bodied, poor people respond to tight labor markets, an important fact that pushes back on the alleged need for work requirements.

Sources: Census, BLS

Unfortunately, over the past few decades, labor markets have not consistently provided the job and earnings opportunities that help to support income growth for families in the bottom half of the income scale and longer-term comparisons show real median income not too far above its pre-recession peaks in 2000 and 2007. Moreover, as inequality has increased, we cannot blithely extrapolate from positive macro-indicators, like unemployment and GDP, to indicators like poverty and median income that will often reflect less improvement in periods when growth disproportionately accrues higher up the income and wealth scale. Though these Census data are less comprehensive than some other sources of inequality data, they do show that in 2018, the highest fifth of households held more income (52 percent of it) than the bottom 80 percent. Though, as noted, the survey has changed over the years such that long-term comparisons should be made with care, in 1967, this share was 44 percent, meaning the bottom 80 percent controlled more income than the top fifth. This increase in inequality is solidly confirmed in much other data.

The table below brings the critical dimension of race into the analysis (note: none of the income changes shown for 2018 are statistically significant). Median household income growth was slower in 2018 relative to earlier years, particularly for Hispanic families. Note also how poverty rates for blacks and Hispanics are multiples of those of whites. The scatterplot shows that lower unemployment correlates with lower poverty, and the table shows this effect to be greater for non-whites, who, over this period, experienced larger declines in unemployment accompanied by bigger drops in poverty. For example, over this period both white unemployment and poverty fell about 1 percentage point. For blacks, the comparable declines are 3 points for both variables. Hispanic poverty was down almost 4 percentage points.

Sources: Census, BLS.

Health Coverage

As noted, as soon as the ACA passed, the expansion of Medicaid coverage and premium subsidies through the exchanges quickly reduced the share of people without coverage. The discussion above—the one noting the increase in the uninsured rate—focused on the main national survey featured by the Census today (the ASEC). But due to its many discontinuities, to compare changes over time it is better to use the other survey results released by Census today, from the American Community Survey (ACS).

This figure clearly shows the historical coverage gains made by the ACA, but it also shows those gains fading in 2017 and this year, in 2018 (the 0.2 point increase in the uninsured rate last year is statistically significant).

Source: ACS

In recent years, gridlock, dysfunction, government shutdowns, and the general unwillingness of Congress to deal with our fundamental challenges has led to a justified skepticism of our federal system. But it's worth remembering that not too far back, this system passed and implemented the largest and most consequential change in national health policy since the advent of Medicaid and Medicare in the 1960s. And the results, in terms of increased coverage, were equally dramatic.

This insight makes today's health coverage results extremely concerning, as they reveal the impact of policies to reverse those gains. This attack on affordable coverage, according to my CBPP colleagues, "began on President Trump's first day in office, with an executive order calling on federal agencies to waive and delay ACA provisions "to the maximum extent permitted by law."' They include repealing the individual mandate, anti-immigrant measures that are likely leading immigrants to avoid publicly-provided coverage, cuts in ACA outreach and enrollment assistance, work requirements that hassle people off of the Medicaid rolls, and a wide variety of waivers and eligibility barriers designed to shrink public coverage and shift medical costs onto consumers.

What's it all mean?

The Census report is a tale of three powerful forces. First, the momentum from the strong economy continues to boost work and wages for low- and middle-income people. Second, anti-poverty programs are reliably helping to lift millions out of poverty. Third, such gains can be reversed by policies hostile to them. It is thus extremely worrisome to consider actions the Trump administration is taking to reduce government support of poor households, especially those with immigrants. Such actions include work requirements that ramp-up administrative demand to hassle low-income people off of Medicaid and SNAP; the "public charge" changes that threaten to block legal immigrants from seeking support they and their children need, changes in poverty measurement designed to make it look like fewer people are poor (and thus reduce their eligibility for assistance), and changes to nutritional support also designed to kick currently eligible persons off the roles.

The economy and complementary work supports are helping many low- and moderate income get ahead. Significant gaps persist, especially with regard to race. But the underlying trends of poverty and income have been favorable. Health coverage tells a different story and we must be vigilant not to let these same political forces do to anti-poverty programs what they're doing to health programs.

 -- via my feedly newsfeed