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May 31, 2014

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Posted: 31 May 2014 01:31 AM PDT

Piketty, Krugman, and Wren-Lewis Respond to the FT

Posted: 30 May 2014 03:08 PM PDT

Piketty's full response from Vox EU (see also Paul Krugman: Thomas Doubting Refuted and Simon Wren-Lewis: What the Financial Times got (very) wrong):

Response to FT, by Thomas Piketty, Vox EU: This is a response to the criticisms - which I interpret as requests for additional information – that were published in the Financial Times on May 23 2014 (see FT article here).1 These criticisms only refer to the series reported in chapter 10 of my book Capital in the 21st century, and not to the other figures and tables presented in the other chapters, so in what follows I will only refer to these series.
This response should be read jointly with the technical appendix to my book, and particularly with the appendix to chapter 10 (available here). The page numbers given below refer to the HUP edition of my book that was published in March 2014.
Let me start by saying that the reason why I put all excel files on line, including all the detailed excel formulas about data constructions and adjustments, is precisely because I want to promote an open and transparent debate about these important and sensitive measurement issues.
Let me also say that I certainly agree that available data sources on wealth inequality are much less systematic than what we have for income inequality. In fact, one of the main reasons why I am in favor of wealth taxation, international cooperation and automatic exchange of bank information is that this would be a way to develop more financial transparency and more reliable sources of information on wealth dynamics (even if the tax was charged at very low rates, which everybody could agree with).
For the time being, we have to do with what we have, that is, a very diverse and heterogeneous set of data sources on wealth: historical inheritance declarations and estate tax statistics, scarce property and wealth tax data; household surveys with self-reported data on wealth (with typically a lot of under-reporting at the top); Forbes-type wealth rankings (which certainly give a more realistic picture of very top wealth groups than wealth surveys, but which also raise significant methodological problems, to say the least). As I make clear in the book, in the on-line appendix, and in the many technical papers on which this book relies, I have no doubt that my historical data series can be improved and will be improved in the future (this is why I put everything on line). In fact, the "World Top Incomes Database" (WTID) is set to become a "World Wealth and Income Database" in the coming years, and together with my colleagues we will put on-line updated estimates covering more countries. But I would be very surprised if any of the substantive conclusions about the long run evolution of wealth distributions was much affected by these improvements.
I welcome all criticisms and I am very happy that this book contributes to stimulate a global debate about these important issues. My problem with the FT criticisms is twofold. First, I did not find the FT criticism particularly constructive. The FT suggests that I made mistakes and errors in my computations, which is simply wrong, as I show below. The corrections proposed by the FT to my series (and with which I disagree) are for the most part relatively minor, and do not affect the long run evolutions and my overall analysis, contrarily to what the FT suggests. Next, the FT corrections that are somewhat more important are based upon methodological choices that are quite debatable (to say the least). In particular, the FT simply chooses to ignore the Saez-Zucman 2014 study, which indicates a higher rise in top wealth shares in the United States during recent decades than what I report in my book (if anything, my book underestimates the rise in wealth inequality). Regarding Britain, the FT seems to put a lot of trust in self-reported wealth survey data that notoriously underestimates wealth inequality.
I will start by giving an overview of the series on wealth inequality that I present in chapter 10 of my book. I will then respond to the specific points raised by the FT.
Overview of the series on wealth inequality reported in chapter 10
The long run series on wealth inequality provided in chapter 10 of my book deal with only four countries: France, Britain, Sweden, and the United States.
Figure 10.1. Wealth inequality in France, 1810-2010 (p.340)
Figure 10.2. Wealth inequality in versus France 1810-2010 (p.341)
Figure 10.3. Wealth inequality in Britain, 1810-2010 (p.344)
Figure 10.4. Wealth inequality in Sweden, 1810-2010 (p.345)
Figure 10.5. Wealth inequality in the United States, 1810-2010 (p.348)
Figure 10.6. Wealth inequality in Europe versus the US, 1810-2010 (p.349)
The series used to construct figures 10.1-10.6, replicated in the book on p.340-348 are available in table S10.1, as well as in the corresponding excel file.
These wealth inequality series deal with much fewer countries and are substantially more exploratory than the empirical material provided in other parts of the book: income and population growth in chapters 1-2; wealth-income ratios in chapters 3-6; income inequality series in chapters 7-9. This follows from the fact that available data sources on wealth inequality are much less systematic than data sources on growth, wealth-income ratios and income inequality. In particular, we do have yearly income declarations statistics for dozens of countries, but we do not have yearly wealth declarations statistics for most countries. So we have to do with the diverse set of sources that I described above.
I believe that the data we have on wealth inequality is sufficient to reach a number of conclusions. Namely, wealth inequality was extremely high and rising in European countries during the 19th century and up until World War 1 (with a top 10% wealth share around 90% of total wealth in 1910), then declined until the 1960s-1970s (down to about 50-60% for the top 10% wealth share); and finally increased moderately since the 1980s-1990s. In the United States, wealth inequality was less extreme than in Europe until World War 1, but it was less strongly affected by the 20th century shocks, and in recent decades it rose more strongly than in Europe. Both in Europe and in the United States, wealth inequality is less extreme than what it was in Europe on the eve on World War 1.
I believe that the data that we have is sufficient to reach these conclusions, but that it is insufficient to go much beyond that. In particular, our ability to measure the most recent trends in wealth inequality is limited, partly due to the huge rise in cross border financial assets and offshore wealth. According to Forbes-type wealth rankings, the very top of the world wealth distribution has been rising about three times faster than average wealth at the global level over the 1987-2013 period (see chapter 12 of my book, in particular Table 12.1. The growth rate of top global wealth, 1987-2013). This seems to be clear evidence than wealth inequality is rising, partly because the rate of return to very large portfolios is higher than the growth rate. This interpretation is consistent with what I find with the returns to large university endowments (see Table 12.2. The return on the capital endowments of US universities, 1980-2010). But we do not really know whether this holds only at the very very top or for bigger groups (say, above 10 millions $ and not only above 1 billion $). Let me make very clear that I do not believe that r>g is the only force that determines the dynamics of wealth inequality. There are many other important forces that could in principle drive wealth inequality in other directions. The main message coming from my book is not that there should always be a deterministic trend toward ever rising inequality (I do not believe in this); the main message is that we need more democratic transparency about wealth dynamics, so that we are able to adjust our institutions and policies to whatever we observe.
I now consider each of the four countries one by one and respond to the specific points raised by the FT. I start with Sweden (the first country for which the FT expresses concerns), and then move to France, the United States, and finally to Britain (arguably the country with the biggest data problems) and to the European average.
Sweden (see figure 10.4 here)
The FT does not point out any significant disagreement regarding Sweden. Their corrected figure looks virtually identical to mine (see their figure on Sweden here).
The FT argues however that my choice of years from raw data sources is not entirely clear. For instance, they point out that raw data for year "1908" for year "1910", year "1935" for year "1930", and so on. These issues are already explained in the book and in the technical appendix, but they probably need to be clarified. Generally speaking, when I present series on wealth-income ratios and wealth inequality (and also for some figures on income inequality), I usually choose to present decennial averages rather than yearly series. This is because wealth series often display a lot of short-run volatility (in particular due to sharp movements in asset prices). So in order to focus the attention on long-run evolutions, it is better to abstract from these short-run movements and show decennial averages. See for instance the wealth-income series presented in chapter 5: contrast figure 5.1 and figure 5.5. When full yearly series are available, the way decennial averages are computed in the book is the following: "1900" usually refers to the average "1900-1909", and so on. This is further explained in the technical paper "Capital is back..." (Piketty-Zucman QJE 2014) available here.
In the case of the wealth inequality series reported in chapter 10, the raw series are usually not available on annual basis, so I compute decennial averages on the basis of the closest years available. This is clearly explained in the chapter 10 excel file (see sheet "TS10.1"). For instance, "1870" is computed as the average for years "1873-1877", "1910" as the average "1907-1908", and so on. These choices can be discussed and improved, but they are reasonably transparent (they are explicitly mentioned in the excel table, which apparently the FT did not notice), and as one can check they have negligible impact on long run evolutions.
The FT also suggests that I made a transcription error by using the estimate for 1908 for the top 1% wealth share (namely, 53.8% of total wealth) for year 1920 (instead of the correct raw estimate for that year, namely 51.5% of total wealth). In fact, this adjustment was intended to correct for the fact that there is a break in a data sources in 1908: pre-1908 series use estate tax data, while post-1908 use wealth tax data, resulting into somewhat lower top wealth (as exemplified by year 1908, for which both data sources co-exist; see Waldenstrom 2009, Table 3.A1, p.120-121). This is standard practice, but I agree that this adjustment should have been made more explicit in the technical appendix and excel file.2 In any case, whatever adjustment one chooses to make to deal with this break in series is again going to have a negligible impact on long-run patterns.
France (see figure 10.1 and figure 10.2)
The FT does not point out any significant disagreement regarding France. Their corrected figure looks virtually identical to mine (see their figure on France here).
The FT argues however that no explanation is given for some of the data construction. Namely, the FT claims the following: "The original source reports data relative to the distribution of wealth among the dead. In order to obtain the distribution of wealth across the living, Prof Piketty augments the share of the top 10 per cent of the dead by 1 per cent and the wealth share of the top 1 per cent by 5 per cent. An adjustment of this sort is standard practice in this type of calculations to correct for the fact that those who die are not representative of the living population. Prof. Piketty does not explain why the adjustment is usually constant. But in one year, 1910, it is not constant and the adjustment scale rises to 2 per cent and 8 per cent respectively. There is no explanation."
This is a surprising statement, because all necessary explanations are actually given in the technical research paper on which these series are based (see Piketty-Postel-Vinay-Rosenthal AER 2006) and in the chapter 10 excel file (see sheet "TS10.1DetailsFR"). Namely, the PPVR AER 2006 paper includes detailed, year-by-year estimates of how differential mortality affects wealth inequality among the living, and finds that the ratio between top wealth shares among the living and top wealth shares among decedents rises at the end of the 19th century and in the early 20th century. Intuitively, this is because differential mortality effects seem to become stronger around that time (namely, life expectancy rises quite fast among top wealth holders, but much less so for the rest of the population). One can see this explicitly in table A4 of the working paper version of the PPVR AER 2006 article; this is explicitly reproduced in chapter 10 excel file (see sheet "TS10.1DetailsFR", table A4 (2), ratios for top 1% shares). More recent research has also confirmed the changing pattern of differential mortality around that time. See in particular the appendix tables to Piketty-Postel-Vinay-Rosenthal EEH 2014. Differential mortality is a complex issue, and we do not have perfect answers; but we do our best to address this issue in the most transparent way. In particular, we put on line on this web site the large micro files that we have collected in French inheritance archives, so that everybody can reproduce our computations and use this data for their own research. We are currently collecting additional micro files in Parisian and provincial archives, and we will put new data files and updated estimates in the future.
What it find somewhat puzzling in this controversy is the following: (i) the FT journalists evidently did not read carefully the technical research papers and excel files that I have put on-line; (ii) whatever adjustment one makes to correct for differential mortality (and I certainly agree that there are uncertainties left regarding this complex and important issue), it should be clear to everyone that this really has a relatively small impact on the long-run trends in wealth inequality. This looks a little bit like criticism for the sake of criticism.
United States (see figure 10.5)
The FT does point out more substantial disagreements regarding the United States. Their corrected figure actually looks very close to mine regarding the long run evolution, but not for the recent decades, where the FT considers that I overestimate somewhat the rise in wealth inequality (see their figure on United States here). The FT also expresses concerns about some of the adjustments that are made for earlier periods, although they have little impact on the overall patterns.
As I explain in the book (chapter 10, p.347) and in the technical appendix to chapter 10 (available here), there are very large uncertainties regarding US historical sources on wealth inequality, and I certainly agree that the series that are provided in the book can be improved. I try to combine in the most consistent manner the information coming from estate tax statistics (which unfortunately only cover the top few percents of the distribution, and not the entire population like in France) and the information coming from household wealth surveys (fortunately the SCF is known to be of higher quality than most other wealth surveys). In particular, the estimate for year 1970 tries to combine the estimates available for top 10% and top 1% wealth shares for years 1960 and 1980 and the evolution of very top wealth shares between 1960, 1970 and 1980. This has little impact on the overall long-run pattern, but I agree that this is relatively uncertain, and that this could have been explained more clearly.
I should stress however that the more recent and more reliable estimates that were recently produced by Emmanuel Saez (Berkeley) and Gabriel Zucman (LSE) confirm the pattern that I find. See Saez-Zucman 2014. For the recent decades, they actually find a larger rise of top 10% wealth shares and especially top 1% and top 0.1% wealth shares than what I report in my book. So, if anything, my book tends to underestimate the recent rise in US wealth inequality (contrarily to what the FT suggests).
This important work was done after my book was written, so unfortunately I could not use it for my book. Saez and Zucman use much more systematic data than I used in my book, especially for the recent period. Also their series are constructed using a completely different data source and methodology (namely, the capitalization method using capital income flows and income statements by asset class). Now that this work is available, the Saez-Zucman series (which unfortunately the FT article seems to ignore) should be used as reference series for wealth inequality in the United States. In a recent survey chapter that will be published in the Handbook of Income Distribution (HID), we choose to use the Saez-Zucman series (rather than the series reported in my book) in order to describe the long-run evolution of US wealth inequality. See Piketty-Zucman 2014 (see in particular supplementary figure S3.5, p.91 for a comparison between the two series; as one can see, they look very similar).3
Britain (see figure 10.3)
The FT does point out substantial disagreements regarding the recent evolution in Britain. Their corrected figure actually looks very close to mine regarding the long run evolution, but not for the recent decades, where the FT considers that there was no rise at all in wealth inequality, and possibly a decline, whereas I report a rise (see their figure on Britain here). The biggest disagreement comes from the latest data point (c.2010): the FT considers that the right estimate for the top 10% wealth share is around 44% of total wealth (this comes from a recent household survey based upon self-reported data, namely the "wealth and assets survey", which I believe underestimates top wealth groups significantly; see below); whereas I report an estimate with a top 10% wealth share around 71% (this comes from more reliable estate tax statistics). This is a very large difference indeed.
Let me make clear that although I think my estimate is more reliable and rests on better methodological choices, I also believe that this large gap reflects major uncertainties and limitations in our collective ability to measure recent evolution of wealth inequality in developed countries, particularly in Britain. As I explain above, I believe this is a major challenge for our statistical and democratic institutions.
The estimates that I report for wealth inequality in Britain rely primarily on the very careful estimates that were established by Atkinson-Harrison 1978 and Atkinson et al 1989 using estate tax statistics from the 1920s to the 1980s. I updated these series for the 1990-2010 period using official HMRC data that are also based upon estate tax records. I find a rising inequality trend, although a more modest one than for the United States. I think this is the most reasonable estimate one can obtain given available data, but this certainly should be improved in the future.
What is troubling about the FT methodological choices is that they use the estimates based upon estate tax statistics for the older decades (until the 1980s), and then they shift to the survey based estimates for the more recent period. This is problematic because we know that in every country wealth surveys tend to underestimate top wealth shares as compared to estimates based upon administrative fiscal data. Therefore such a methodological choice is bound to bias the results in the direction of declining inequality. For instance, as I note in the technical appendix to chapter 10 (available here), the recent wealth surveys undertaken by INSEE in 2004-2010 in France indicate a top decile share just above 50% of the total wealth, whereas fiscal data (inheritance and wealth tax) suggest a top decile share above 60% of the total wealth. The gap seems particularly large for the case of Britain, which could reflect the fact that the "wealth and assets survey" seems particularly bad at measuring the top part of the wealth distribution of the UK. Indeed, according to the latest report by the Office of national statistics (ONS), the response rate for this survey was only 64% in 2010-2012; this is an improvement as compared to the response rate of 55% that was observed during the 2006-2008 wave of the same survey (see ONS 2014, Table 7.1); but it is pretty clear that with such a low response rate, it is hard to claim that one can adequately measure wealth inequality, particularly at the top of the distribution. Also note that a 44% wealth share for the top 10% (and a 12.5% wealth share for the top 1%, according to the FT) would mean that Britain is currently one the most egalitarian countries in history in terms of wealth distribution; in particular this would mean that Britain is a lot more equal that Sweden, and in fact a lot more equal than what Sweden as ever been (including in the 1980s). This does not look particularly plausible.
Of course the estate records based estimates also raise significant methodological concerns, and I do not claim that the resulting estimates are perfectly reliable. In particular, they might also underestimate top wealth levels (because top wealth holders sometime escape the estate tax through sophisticated trust funds or offshore assets). But they definitely seem more plausible than the estimates based upon self-reported survey data.
Note also that in recent years more and more scholars and statisticians have started to recognize the limitations of household wealth surveys and to upgrade the top segments of survey based wealth distributions using other sources. For instance, a recent study undertaken at the research department of the ECB attempts to upgrade in a systematic manner the top tail of the wealth surveys undertaken in Eurozone countries by using the Pareto coefficients that one can estimate using Forbes rankings and other lists of very high wealth individuals in each country. The results indicate that this can lead to very large increases (more than 10 percentage points) in top wealth shares (see Vermeulen 2014). In the United States, although the SCF wealth survey is generally regarded as a very high quality wealth survey, there has been some important work trying to upgrade the top tail by using Forbes ranking and estate tax data (see Johnson-Shreiber 2006 and Raub-Johnson-Newcomb 2010). This is definitely something that should be done for the British "wealth and assets survey".
Regarding the 19th century estimates, the FT expresses concerns with the way I compute the top wealth shares for Britain in 1810 and 1870. Namely, I borrow the top 1% wealth shares estimates from Lindert (54.9% and 61.1%, respectively), and I assume that the next 9% shares shifted from 28% to 26%. Lindert does report a lower estimate for the next 9% share (about 16%). However this would indicate a relatively unusual pattern of Pareto coefficients within the top 10% of the distribution (as compared both to the French 19th century inheritance data, which is a lot more comprehensive than the British probate data, and to the British estate tax statistics for 1911-1913). Given that the probate records used by Lindert seem to provide a better coverage of the top 1% than of the next 9%, I use Pareto interpolation techniques to estimate the next 9% share. This is an issue that should have been explained more clearly and that would definitely deserve further research. This has a limited impact for the long run patterns analyzed here (the pre-World War 1 rise in wealth inequality would be even larger without this adjustment).
European average (see figure 10.6)
Finally, the FT also expresses the following concern: the European average series, which I computed by making a simple arithmetic series between France, Britain and Sweden, should have been computed using population weighted averages. I do agree that population (or GDP) weighted averages are generally superior to simple arithmetic averages. However I should stress that it really does not make much of a difference here, because all three European countries that I use follow fairly similar long run patterns. Namely, all three countries display high and rising top wealth shares during the 19th century and up until World War 1 (with about 90% of total wealth for the top 10% around 1910); then a sharp decline until the 1960s-1970s (with top 10% wealth shares down to 50-60%); and finally a modest rise since the 1980s-1990s. So whether one weights the three countries with equal weights or according to population or GDP does not make a big difference. But in case Britain did follow a markedly different pattern than the other countries in recent decades (with a decline in wealth inequality rather than a rise), then putting more weight on Britain than on Sweden becomes a significant issue. So we are back to the previous question: what happened to wealth inequality in Britain in recent decades? The FT seems to believe it has become more equal; however the way they use self-reported wealth survey data is not convincing. This is nevertheless an interesting debate for the future, and we should all agree that we know too little about it.
Footnotes:
1 See also the other two articles published by the FT on May 23 2014: here and there. See also my short reponse published here in the FT. Unfortunately I was given limited time to submit this response, so I could not address specific points; here is a longer response.
2 Also note that the raw series display a decline in top 1% wealth share between 1908 and 1920, but a sharp rise in the share of the next 9% (resulting into a significant increase in the top 10% share). This does not look entirely plausible and might also be due to a break in raw data sources (unless this is due to sharp short-run variations in the relative price of assets held by these different wealth groups).
3 Note that this HID chapter also includes novel series about the evolution of the share of inheritance in total wealth accumulation. These new series use a different methodology and complement those reported in chapter 11 of my book.

Welfare Economics

Posted: 30 May 2014 11:02 AM PDT

Steve Waldman at Interfluidity:

Welfare economics: an introduction (part 1 of a series): Commenters at interfluidity are usually much smarter than the author whose pieces they scribble beneath, and the previous post was no exception. But there were (I think) some pretty serious misconception in the comment thread, so I thought I'd give a bit of a primer on "welfare economics", as I understand the subject. It looks like this will go long. I'll turn it into a series. ...

'Hours Worked, No Change; Output, Up 42%'

Posted: 30 May 2014 08:28 AM PDT

Tim Taylor:

Hours Worked, No Change; Output, Up 42%: Here's one snapshot of how the U.S. economy evolved in the last 15 years: an identical number of total hours worked in 1998 and 2013, even though the population rose by over 40 million people, but a 42% gain in output. Shawn Sprague explains in "What can labor productivity tell us about the U.S. economy?" published as the Beyond the Numbers newsletter from the U.S. Bureau of Labor Statistics for May 2014. ...
A lot can be said about this basic fact pattern. Of course, the comparison years are a bit unfair, because 1998 was near the top of the unsustainably rapid dot-com economic boom, with an unemployment rate around 4.5%, while 2013 is the sluggish aftermath of the Great Recession. The proportion of U.S. adults who either have jobs or are looking for jobs--the "labor force participation rate"--has been declining for a number of reasons: for example, the aging of the population so that more adults are entering retirement, a larger share of young adults pursuing additional education and not working while they do so,  a rise in the share of workers receiving disability payments, and the dearth of decent-paying jobs for low-skilled labor. ...
The more immediate question is what to make of an economy that is growing in size, but not in hours worked, and that is self-evidently having a hard time generating jobs and bringing down the unemployment rates as quickly as desired. I'm still struggling with my own thoughts on this phenomenon. But I keep coming back to the tautology that there will be more good jobs when more potential employers see it as in their best economic interest to start firms, expand firms, and hire employees here in the United States.

May 30, 2014

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Paul Krugman: Cutting Back on Carbon

Posted: 30 May 2014 12:24 AM PDT

The cost of taking action to reduce the threat from global warming isn't as large as you might be led to believe:

Cutting Back on Carbon, by Paul Krugman, Commentary, NY Times: Next week the Environmental Protection Agency is expected to announce new rules designed to limit global warming. Although we don't know the details yet, anti-environmental groups are already predicting vast costs and economic doom. Don't believe them. Everything we know suggests that we can achieve large reductions in greenhouse gas emissions at little cost to the economy.
Just ask the United States Chamber of Commerce.
O.K., that's not the message the Chamber of Commerce was trying to deliver in the report it put out Wednesday. It clearly meant to convey the impression that the E.P.A.'s new rules would wreak havoc. But if you focus on the report's content rather than its rhetoric, you discover that ... the numbers are remarkably small.
Specifically, the report considers a carbon-reduction program that's probably considerably more ambitious than we're actually going to see, and it concludes that between now and 2030 the program would cost $50.2 billion in constant dollars per year. That's supposed to sound like a big deal. ... These days, it's just not a lot of money.
Remember, we have a $17 trillion economy..., and it's going to grow over time. So what the Chamber of Commerce is actually saying is that we can take dramatic steps on climate ... while reducing our incomes by only one-fifth of 1 percent. That's cheap! ...
And ... this is based on anti-environmentalists' own numbers. The real costs would almost surely be smaller...
You might ask why the Chamber of Commerce is so fiercely opposed to action against global warming, if the cost of action is so small. The answer, of course, is that the chamber is serving special interests, notably the coal industry ... and also ... the ever more powerful anti-science sentiments of the Republican Party.
Finally, let me take on the anti-environmentalists' last line of defense — the claim that whatever we do won't matter, because other countries, China in particular, will just keep on burning ever more coal. This gets things exactly wrong. Yes, we need an international agreement... But U.S. unwillingness to act has been the biggest obstacle to such an agreement. ...
Now, we haven't yet seen the details of the new climate action proposal... We can be reasonably sure, however, that the economic costs of the proposal will be small, because that's what the research — even research paid for by anti-environmentalists... — tells us. Saving the planet would be remarkably cheap.

Links for 5-30-14

Posted: 30 May 2014 12:06 AM PDT

Piketty Responds

Posted: 29 May 2014 11:27 AM PDT

Thomas Piketty's response to the FT:

Response to FT: ... I welcome all criticisms and I am very happy that this book contributes to stimulate a global debate about these important issues. My problem with the FT criticisms is twofold. First, I did not find the FT criticism particularly constructive. The FT suggests that I made mistakes and errors in my computations, which is simply wrong, as I show below. The corrections proposed by the FT to my series (and with which I disagree) are for the most part relatively minor, and do not affect the long run evolutions and my overall an alysis , contrarily to what the FT suggests . Next, the FT corrections that are somewhat more important are based upon methodological choices that are quite debatable (to say the least) . In particular, the FT simply chooses to ignore the Saez - Zucman 2014 study, which indicates a higher rise in top wealth shares in the United States during recent decades than what I report in my book (if anything, my book underestimates the rise in wealth inequality). Regarding Britain, the FT seems to put a lot of trust in self - reported wealth survey data that notoriously underestimates wealth inequality. ...

[This is just a snippet -- the full response is 10 pages long.]

'How Highly Educated Immigrants Raise Native Wages'

Posted: 29 May 2014 09:45 AM PDT

From Vox EU:

How highly educated immigrants raise native wages, by Giovanni Peri, Kevin Shih, and Chad Sparber, Vox EU: Immigration to the US has risen tremendously in recent decades. Though media attention and popular discourse often focus on illegal immigrants or the high foreign-born presence among less-educated workers, the data show that immigrants are drawn from both ends of the education spectrum. At the low end, immigrants grew from 5% of workers with a high school degree or less in 1970 to 20.8% in 2010. At the high end, the figure rose from 7.3% to 18.2% for those with graduate degrees over the same period.1
These trends suggest that it is important for economists and policymakers to understand the effects of highly educated immigrant flows. The canonical economic model, based on demand and supply, holds that, all else equal, an increase in labour supply should cause wages to fall. Thus, immigration should depress wages paid to natives. Evidence for such a downward effect in academic work is mixed. For example, Borjas (2003, 2013) find a negative impact of immigration on wages, while Card (2009) and Ottaviano and Peri (2012) do not. For the canonical model to fail and for immigrants to generate wage gains for natives, it must be the case that all else is not equal in the case of immigration. This is because the labour market is more complex than the market for typical goods. Adjustment mechanisms exist to allow natives and firms to respond to immigration without experiencing lower wages or fewer employment opportunities. Immigrants may also generate positive externalities that benefit native workers. This article provides a brief summary of the recent evidence for these phenomena in the context of the market for workers with a college degree.
Immigrants to the US specialise in STEM
The first step in understanding the peculiarities of the labour market is to recognise that native and foreign labour differ in their underlying characteristics. We do not think that the popular refrain claiming that "the US faces a skills shortage" is a useful way to approach this issue. Rather, we recognise the existence of important differences between natives and immigrants. Figure 1 provides a sense of this by describing the college majors of US bachelor's degree recipients. Compared to natives, foreign-born workers are disproportionately likely to have obtained a bachelor's degree in Science, Technology, Engineering, or Mathematics (STEM). 45.5% of college-educated immigrants in the labour force have a STEM degree, whereas only 28% of natives do. Conversely, natives are twice as likely as immigrants to have majored in education (12.2% versus 5.6%) or social sciences (9.5% versus 5%).

Figure 1. Primary degree share by nativity – workers with a bachelor's degree or more education, 2009–2012

Sparber fig1 29 may

Source: American Community Survey.

These differences are crucial to understanding how natives might respond to college-educated immigrant flows. Figure 1 indicates that immigrants possess a comparative advantage and specialise in STEM. Thus, we might expect that natives respond to inflows of STEM-dominant immigrants by specialising in non-STEM work. Indeed, Peri and Sparber (2011) provide evidence of this phenomenon – inflows of highly educated immigrants cause natives switch to more communication-intensive occupations.
The contribution of STEM to overall productivity
This comparative advantage and specialisation story is not unique to the market for college-educated labour. Peri and Sparber (2009) document similar behaviour among workers with a high school degree or less education. However, the fact that foreign college-educated immigrants tend to specialise in STEM has an additional implication of paramount importance. Economists have long recognised the significance of innovation in generating economic growth, and the role of scientists and engineers in fostering such knowledge production. The process of innovation generates positive spillovers for the economy as a whole. Thus, by increasing the country's stock of knowledge, foreign-born STEM workers can increase the overall productivity of the economy.
A rather simplistic estimate of the contribution of foreign-born STEM to productivity in the US can be calculated from just two pieces of information. First, Jones (2002) estimates that 50% of US total factor productivity (TFP) growth in recent decades is attributable to scientists and engineers. Second, college-educated STEM workers grew from 2.9% of total employment in 1990 to 3.7% of employment in 2010, and foreign-born workers were responsible for 80% of this growth. By combining immigrants' contributions to STEM growth with STEM's contribution to TFP growth, we can deduce that roughly 40% of aggregate productivity growth may be due to foreign-born college-educated STEM workers.
This is an enormous figure and it is based on data at a very high level of aggregation. In Peri, Shih, and Sparber (2014), we assess whether more thorough economic analysis delivers comparable results. Using cross-city panel regressions to estimate wage and employment responses to foreign STEM, we find a rise in foreign STEM by one percentage point of total employment increases real wages of college-educated natives by 7–8 percentage points and those of non-college-educated natives by 3-4 percentage points. We find no statistically significant effects on native employment growth.
Instrumenting for the growth of foreign STEM workers
Causal identification is driven by three regularities. First, the presence of foreign STEM workers varied substantially across US cities in 1980. Second, the H-1B visa program – which has been the method of entry for highly skilled immigrants in the US since its inception in 1990 – produced national level changes in the number of skilled immigrants in the country that can be seen as exogenous from a city-level perspective. Third, new immigrants are attracted to locations where previous immigrant communities have already been established. By interacting 1980 city-level settlements with subsequent national-level policy, we can predict the number of new foreign STEM workers in each city. This H-1B-driven imputation of future foreign STEM workers is a good predictor of the actual increase in both foreign STEM and overall STEM workers in a city over subsequent decades. However it is not correlated, by construction, with the economic conditions in the city during the subsequent decades. It therefore makes an excellent instrument for the actual growth of foreign STEM workers to obtain causal estimates of the impact of STEM growth on the wages and employment of college and non-college-educated native-born workers.2
From the perspective of the canonical supply and demand model, the positive relationship between foreign labour supply and native wages may appear peculiar, but it is reasonable in the context of STEM-driven economic and productivity growth. The analysis in Peri, Shih, and Sparber (2014) uses an aggregate production model at the city level, to derive the productivity effect implied by the estimated wage and employment effects. We find that foreign STEM workers can explain 30% to 60% of US TFP growth between 1990 and 2010 – in line with the simple calculation cited above.
Discussion of results and policy implications
The large and positive wage and productivity effects from foreign-born STEM labour raise two important issues. The first concerns how, in the presence of these gains, studies sometimes find detrimental effects. Borjas (2013), for example, argues that immigration from 1990–2010 may have reduced wages paid to workers with a bachelor's degree by 3.2%, and for workers with a graduate degree by 4.1%. Similarly, Borjas and Doran (2012) find that the post-1992 inflow of Soviet mathematicians pushed American mathematicians to lower quality institutions and reduced their academic productivity. To understand the conflict between these results and our own, it is important to recognise that our gains arise due to complementarities and positive externalities from innovation. Analyses that ignore occupational adjustment, understate complementarities across skill groups, fail to account for externalities, or analyse markets in which positive spillovers are small, are more likely to miss the gains associated with immigration.
The second is whether foreign STEM workers are truly needed since the US could presumably enact policies to produce its own STEM talent. This is true, but three qualifications are necessary. First, our analysis, as well as that of Kerr and Lincoln (2010), argues that foreign H-1B workers increase innovation and the productivity of US STEM workers without crowding them out. Thus it may be possible to increase both foreign and domestic STEM supply. Second, Hunt and Gauthier-Loiselle (2010) argue that immigrants are more entrepreneurial and innovative than natives, and this may add a further productive complementarity for natives. Third, native STEM development might require extensive and expensive investment, whereas immigration policy could be a more cost-effective way of building the country's STEM workforce.
The comprehensive immigration reform proposed in the US Senate Bill 744 that would increase the annual number of H-1B visas allotted by 50,000 per year. In the light of the results above, it should be obvious that the provision would produce long-run positive effects on US wages and innovation.
References
Borjas, G J (2003), "The labor demand curve is downward sloping: reexamining the impact of immigration on the labor market", Quarterly Journal of Economics, 118(4): 1335–1374.
Borjas, G J (2013), "Immigration and the American Worker: A Review of the Academic Literature", Center for Immigration Studies, April.
Borjas, G J and K B Doran (2012), "The Collapse of the Soviet Union and the Productivity of American Mathematicians", Quarterly Journal of Economics, 127(3): 1143–1203.
Card, D (2009), "Immigration and Inequality", The American Economic Review, 99(2): 1–21.
Hunt, J and M Gauthier-Loiselle (2010), "How Much Does Immigration Boost Innovation?", American Economic Journal: Macroeconomics: 31–56.
Jones, C I (2002), "Sources of US Economic Growth in a World of Ideas", The American Economic Review, 92(1): 220–239.
Kerr, W R and W F Lincoln (2010), "The supply side of innovation: H-1B visa reforms and US ethnic invention", Journal of Labor Economics, 28: 473–508.
Ottaviano, G I P and G Peri (2012), "Rethinking the Effect of Immigration on Wages", Journal of the European Economic Association, 10(1): 152–197.
Peri, G and C Sparber (2009), "Task Specialization, Immigration, and Wages", American Economic Journal: Applied Economics, 1(3): 135–169.
Peri, G and C Sparber (2011), "Highly-Educated Immigrants and Native Occupational Choice", Industrial Relations, 50(3).
Peri, Giovanni, Kevin Shih, and Chad Sparber (2014), "Foreign STEM Workers and Native Wages and Employment in U.S. Cities", NBER Working Papers 20093.
Footnotes
1 Summary statistics are based on Census and American Community Survey (ACS) data.
2 This methodology is not immune to criticism. Persistent city-specific shocks affecting immigration, employment, and wage growth, for example, would challenge the validity of our instrumental variable strategy. However, we perform a series of robustness checks that all point to the same result – foreign-born STEM workers increase wages paid to native-born workers, with larger effects for those with a college degree.

The Great Recession's 'Biggest Policy Mistake'

Posted: 29 May 2014 08:16 AM PDT

At MoneyWatch:

The Great Recession's "biggest policy mistake", by Mark Thoma, CBS News: Two recent books, Timothy Geithner's "Stress Test: Reflections on Financial Crises" and "House of Debt" by Atif Mian and Amir Sufi, have reignited a discussion over the Obama administration's policies and attitude on mortgage debt relief.
In contrast with the former New York Fed president and later Treasury Secretary's account about the efforts to save the U.S. economy from the collapsing housing market, others say the administration -- more particularly the Geithner-led Treasury -- did not push aggressively for mortgage debt relief .
As a result, very little was done to help households struggling with mortgage debt. Indeed, Mian and Sufi argue that "The fact that Secretary Geithner and the Obama administration did not push for debt write-downs more aggressively remains the biggest policy mistake of the Great Recession."
Who is correct? ...[continue]...

Links for 5-29-14

Posted: 29 May 2014 12:06 AM PDT

May 29, 2014

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'Don't Raise Rates'

Posted: 28 May 2014 03:17 PM PDT

I can't watch this, so have no idea how foolish I look, or not, or what parts of the interview they chose to include:

A Wedge in the Dual Mandate: Monetary Policy and Long-Term Unemployment

Posted: 28 May 2014 01:15 PM PDT

Glenn Rudebusch and John Williams:

A Wedge in the Dual Mandate: Monetary Policy and Long-Term Unemployment, by Glenn D. Rudebusch and John C. Williams, Federal Reserve Bank of San Francisco: Abstract In standard macroeconomic models, the two objectives in the Federal Reserve's dual mandate -- full employment and price stability -- are closely intertwined. We motivate and estimate an alternative model in which long-term unemployment varies endogenously over the business cycle but does not a ect price in ation. In this new model, an increase in long-term unemployment as a share of total unemployment creates short-term tradeoffs for optimal monetary policy and a wedge in the dual mandate. In particular, faced with high long-term unemployment following the Great Recession, optimal monetary policy would allow inflation to overshoot its target more than in standard models.

I'll believe the Fed will allow *intentional overshooting* of its inflation target when I see it.

'Unemployment Insurance and Disability Insurance in the Great Recession'

Posted: 28 May 2014 11:24 AM PDT

From the NBER Digest:

Unemployment Insurance and Disability Insurance in the Great Recession: At the end of 2012, 8.8 million American adults were receiving Social Security Disability Insurance (SSDI) benefits. The share of the American public receiving SSDI has more than doubled since 1990. This rapid growth has prompted concerns about SSDI's sustainability: recent projections suggest that the SSDI trust fund will be exhausted in 2016.
SSDI recipients tend to remain in the program, and out of the labor market, from the time they are approved for benefits until they reach retirement age. This means that if unemployed individuals turn to disability insurance as a source of benefits when they exhaust their unemployment insurance (UI), the long-term program costs can be substantial. Some have suggested that the savings from avoided SSDI cases could help to finance the cost of extending UI benefits, but little is known about the interaction between SSDI and UI.
In Unemployment Insurance and Disability Insurance in the Great Recession, (NBER Working Paper No. 19672), Andreas Mueller, Jesse Rothstein, and Till von Wachter use data from the last decade to investigate the relationship between UI exhaustion and SSDI applications. They take advantage of the variability of UI benefit durations during the recent economic downturn. The duration of these benefits was as long as 99 weeks in 2009, remained protracted for several years, then was shortened substantially in 2012. The authors focus on the uneven extension of UI benefits during and after the Great Recession to isolate variation in the duration of these benefits that is not confounded by variation in economic conditions more broadly.
The authors find very little interaction between UI benefit eligibility and SSDI applications, and conclude that SSDI applications do not appear to respond to UI exhaustion. While the authors cannot rule out small effects, they conclude that SSDI applications do not respond strongly enough to contribute meaningfully to a cost-benefit analysis of UI extensions or to account for the cyclical behavior of SSDI applications.
The authors suggest that the tendency for the number of SSDI applications to grow when the economy is weak may reflect variation in the potential reemployment wages of displaced workers, or changes in the employment opportunities of the marginally disabled that influence the evaluation of an SSDI applicant's employability. These channels are not linked to the generosity or duration of UI benefits, and they imply that more stringent functional capacity reviews of SSDI applicants may not reduce recession-induced SSDI claims if these claims reflect examiners' judgments that the applicants are truly not employable in the existing labor market.

May 28, 2014

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Fed Watch: Policy Induced Mediocrity?

Posted: 28 May 2014 12:15 AM PDT

Tim Duy:

Policy Induced Mediocrity?, by Tim Duy: Why did the Federal Reserve lean against their optimistic 2014 forecast? It seems that monetary policy over the past year can be summarized as a missed opportunity to supercharge the recovery, thereby locking the US economy into a suboptimal growth path.
Last week's speech by New York Federal Reserve President William Dudley noted the reasons monetary policymakers expected the economy to improve this year:
Since the downturn ended in mid-2009, real GDP growth has averaged only 2.2 percent per year despite a very accommodative monetary policy. This performance reflects three major factors—the significant headwinds resulting from the bursting of the housing bubble, the shift of fiscal policy from expansion toward restraint, especially in 2012 and 2013, and a series of shocks from abroad—most notably the European crisis.
The good news is that all three of these factors have abated. With respect to the headwinds resulting from the financial crisis, they are gradually becoming less severe. In particular, the sharp decline in household wealth due to the decline in housing prices and the weakness in equity prices has been largely reversed...On the fiscal side, the amount of restraint has diminished sharply. For 2014, the projected drag is about ½ percent of GDP, roughly half the level of 2013. Moreover, much of this restraint was frontloaded into the beginning of the year...In terms of the outlook abroad, the circumstances are more mixed.
The Federal Reserve could have chosen to lean into this generally upbeat forecast. Yet instead they chose to lean against it by turning to tapering and setting the stage for interest rate hikes. And the data so far suggests that once again the turn toward policy normalization was premature. The weak first quarter report is more suggestive of holding the recent pace of growth over the next year rather than an acceleration of activity. What is remarkable is that the Federal Reserve understood that their forecasts have tended toward optimism. Dudley again:
But, there remains considerable uncertainty about that forecast and, given the persistent over-optimism about the growth outlook by Federal Reserve officials and others in recent years, we shouldn't count our chickens before they hatch.
Yet they choose to act prior to data confirmation. Why? I really don't quite know. Sure, we can tell a story about the declining unemployment rate and expected subsequent inflation pressures, but ultimately the turn toward less policy accommodation never made sense in the context of the Fed's own forecasts and questions about the degree of slack in the economy. It makes me wonder how seriously the Fed is truly interested in closing the output gap:

REALPOT051114

It seems reasonable to believe that if the economy regains potential output by the end of at best 2016, it will be attributable only to further downward revisions to potential output. And I even wonder whether the Fed would act to achieve their current growth forecasts or ultimately be content to continue along the current trend. The economy appears to be already molding itself around the lower output path. Despite the housing troubles and related weak rebound in construction, and the declines in government hiring, job growth is, on average, plugging along at a rate roughly consistent to that during the housing boom:

NFP051114

With that growth labor slack gradually steadily declines by any measure, the Fed appears reasonably comfortable with the resulting path. To be sure, arguably there still remains substantial slack. The failure of wage gains to accelerate is consistent with that story. But the Fed seems content to use that story only to justify its current policy path rather than justify an even easier policy to more quickly reduce slack.
Given the generally consistent overall reaction of the labor market to the current growth path, it is reasonable to believe that the faster pace of growth in the Fed's forecast would accelerate the pace of labor utilization and thus place upward pressure on inflation forecasts. In this case, we would expect the Fed to pull forward and steepen the pace of rate hikes to moderate the pace of activity. Thus, ultimately the Fed's commitment to regaining potential output could be even less than we have come to believe.
But even more telling would be the monetary policy reaction if growth continues along its current path. The weak first quarter results already place the forecast at risk, and the housing recovery is not progressing as smoothly as initially believed. Yet neither event prevented the Fed from continuing to cut asset purchases at the last FOMC meeting. Moreover, I still can't see any reason to expect the Fed will slow the tapering process unless the economy falls decisively off its current path. It could be that by the time they are sufficiently convinced growth will continue to fall short of forecast, asset purchases will be almost complete anyway. And I think the bar to restarting asset purchases would be very high. They want out of that business.
And if neither fiscal or monetary policy makers are interested in accelerating the pace of growth, should we really expect the pace of growth to accelerate? In other words, it appears to me that monetary policy largely amounts to setting expectations that reinforce the current growth path. Which was a recent topic of Bloomberg's Rich Miller who, reporting on the Fed's diminished expectations, quotes me:
By lowering its assessment of how fast the economy can expand and conducting policy accordingly, the Fed runs the risk of locking the U.S. into a slow-growth path, said Tim Duy, a former Treasury Department economist who is now a professor at the University of Oregon in Eugene...
..."They offset fiscal austerity on the downside but then arguably also offset the upside," Duy said. "They seem to have lost interest in speeding the pace of the recovery."
Bottom Line: The Federal Reserve has set reasonably clear expectations that rates will remain low for a long time. That path, however, seems to be a consequence of doing too little now to ensure a stronger recovery. In other words, the Fed seems to be taking a lower-rate future as a given rather than as a result of insufficient policy. Instead of acting to ensure a stronger forecast, they seem more interesting in acting to lock-in the lower path of activity. And that in turn will tend to lock in a low level of long-term rates. This, I think, is the best explanation for the inability of markets to sustain higher rates. It is simply reasonable to expect that the conditions which justify higher long rates will be met with tighter policy sufficient to contain growth to something closer to the current path of output than to current estimates of potential output.

Links for 5-28-14

Posted: 28 May 2014 12:06 AM PDT

'Don't Buy the 'Sharing Economy' Hype'

Posted: 27 May 2014 09:50 AM PDT

Dean Baker:

Don't buy the 'sharing economy' hype: Airbnb and Uber are facilitating rip-offs: The "sharing economy" – typified by companies like Airbnb or Uber, both of which now have market capitalizations in the billions – is the latest fashion craze among business writers. But in their exuberance over the next big thing, many boosters have overlooked the reality that this new business model is largely based on evading regulations and breaking the law. ...

This downside of the sharing needs to be taken seriously, but that doesn't mean the current tax and regulatory structure is perfect. Many existing regulations should be changed, as they were originally designed to serve narrow interests and/or have outlived their usefulness. But it doesn't make sense to essentially exempt entire classes of business from safety regulations or taxes just because they provide their services over the Internet.

Going forward, we need to ensure that the regulatory structure allows for real innovation, but doesn't make scam-facilitators into billionaires. For example, rooms rented under Airbnb should be subject to the same taxes as hotels and motels pay. Uber drivers and cars should have to meet the same standards and carry the same level of insurance as commercial taxi fleets.

If these services are still viable when operating on a level playing field they will be providing real value to the economy. As it stands, they are hugely rewarding a small number of people for finding a creative way to cheat the system.

Agree about the level playing field, but perhaps it will serve as a catalyst for changing regulations that "were originally designed to serve narrow interests and/or have outlived their usefulness"?

'The Share of Borrowers with High Student Loan Balances is Rising'

Posted: 27 May 2014 09:03 AM PDT

We need to provide more support for education if we want it to be a vehicle for enhanced opportunity rather than a means of promoting existing inequities:

The Share of Borrowers with High Student Loan Balances is Rising, On the Economy, St. Louis Fed: It's not just the total number of student loan borrowers that is going up. The average balance per borrower is going up as well. And, in particular, the fraction of borrowers with more than $10,000 in student debt is rising.

In a recent Economic Synopses essay, Alexander Monge-Naranjo, research officer and economist with the Federal Reserve Bank of St. Louis, examined the recent growth in student loan debt in the U.S. over the period 2005-2012. As of March 2012, student loan debt stood at $870 billion and had surpassed total credit card debt ($693 billion) and total auto loan debt ($730 billion).

In addition, Monge-Naranjo found that the distribution of student loans by debt levels had shifted, with the share of borrowers with loan balances in excess of $10,000 increasing. Increases were greater at higher levels of debt:

  • Only 3 percent of borrowers in 2005 owed more than $100,000. By 2012, that fraction reached 6.2 percent.
  • The share of borrowers who owed between $150,000 and $175,000 rose from 1.7 percent to 3.7 percent.
  • The share who owed between $175,000 and $200,000 went up from 0.6 percent to 1.5 percent.
  • The share of those owing more than $200,000 went up from 0.2 percent to 0.6 percent.

While Monge-Naranjo noted that "high levels of student loan debt pose no problems as long as the investment in education has high returns and the loans are repaid," he also indicated that some borrowers may suffer adverse effects in the future, such as difficulty obtaining other forms of credit.

The FT is on a Roll. Not.

Posted: 27 May 2014 08:55 AM PDT

Kevin O'Rourke:

The FT is on a roll: In an otherwise unremarkable editorial about the upshot of the elections, the FT comes up with this quite remarkable statement:

The only viable path for France is to press ahead with tax cuts and spending reductions that can sustain growth.

Is the FT really saying that in a Keynesian short run, such as we find ourselves in just now, the balanced budget multiplier is negative? Really? Or that the spending multiplier is negative? Or is it perhaps denying that the Eurozone currently finds itself in such a Keynesian short run, in which a lack of demand is the key constraint on growth? (Let's not even get into the debate about the long run relationship between growth and the size of the state in Europe, although I can't help writing down one word: Scandinavia.)

And is the FT really claiming that continuing with this programme would make all those FN voters switch to the socialists and UMP?

Really?

Global Income Distribution Since 1988

Posted: 27 May 2014 08:21 AM PDT

From Vox EU:

Global income distribution: From the fall of the Berlin Wall to the Great Recession, by Christoph Lakner and Branko Milanovic, Vox EU: Since 1988, rapid growth in Asia has lifted billions out of poverty. Incomes at the very top of the world income distribution have also grown rapidly, whereas median incomes in rich countries have grown much more slowly. This column asks whether these developments, while reducing global income inequality overall, might undermine democracy in rich countries.