{"id":33406,"date":"2016-07-26T20:22:46","date_gmt":"2016-07-27T01:22:46","guid":{"rendered":"http:\/\/prefblog.com\/?p=33406"},"modified":"2016-07-26T20:22:46","modified_gmt":"2016-07-27T01:22:46","slug":"july-26-2016","status":"publish","type":"post","link":"https:\/\/prefblog.com\/?p=33406","title":{"rendered":"July 26, 2016"},"content":{"rendered":"

Low returns are finally catching up to American pension plans<\/a>:<\/p>\n

Twenty-year annualized returns for public pensions in the U.S. are poised to decline to 7.47% once fiscal 2016 results are released in coming weeks, according to an estimate from Wilshire Trust Universe Comparison Service, which tracks pension investment returns.<\/p>\n

That would be the lowest-ever annual mark recorded by Wilshire, which began tracking the statistic 16 years ago. In 2001, near the height of the dot-com boom, pensions\u2019 20-year median return was 12.3%, according to Wilshire.
…<\/b>
Weak annual gains for the California Public Employees\u2019 Retirement System and California State Teachers\u2019 Retirement System dropped their 20-year returns below 7.5% investment targets, to 7.03% and 7.1%, respectively. The two funds, known as Calpers and Calstrs, are the largest public pensions in the U.S. by assets and oversee a combined $484 billion for 2.6 million public workers and retirees.
…<\/b>
Ms. Frost\u2019s comments came days before Calpers said that its fiscal 2016 return was 0.6%, the slimmest gain since the 2008-2009 crisis. Calpers has a funding gap of roughly $112 billion, according to the most recent available data. As recently as last year, Calpers Chief Investment Officer Ted Eliopoulos said in an annual letter that the plan was \u201creassured by our 20-year investment return of 7.76%,\u201d which exceeded the internal target of 7.5%.<\/p>\n

Now, \u201cit is a struggle to have a positive return,\u201d Mr. Eliopoulos said in a media call last week.<\/p><\/blockquote>\n

Good old CalPERS, always good for a laugh.<\/p>\n

Meanwhile, a vitriolic attack on Trump by Mary Anastasia O\u2019Grady titled Wharton Grad Trump Fails Economics<\/a> has some useful information and links:<\/p>\n

In the Foreign Affairs magazine essay recently titled \u201cThe Truth About Trade,\u201d economist at Dartmouth Douglas Irwin observed that while the technology has \u201cenabled wide productivity and efficiency improvements,\u201d has \u201calso make a lot of blue-collar jobs obsolete. \u201cMr. Irwin cites a study by the Center for Business and Economic Research at Ball State University, which \u201cfound that productivity growth accounted for more than 85 percent of the jobs lost in manufacturing between 2000 and 2010, a period when employment in the sector fell by 5.6 million. \u201cthis 85% compares, according to the study, with 13% of job loss associated with trading during the same period. In other words, to bring most jobs back, Mr. Trump should prohibit mechanization. Would Mr. Pence broke the news to farmers Indiana?<\/p>\n

In a paper published last summer in the Journal of Economic Perspectives, an economist at MIT David Autor unload automation reason has hit the middle class hard. He observed that to write code for a task, the programmer should be able to \u201csay explicitly \u2018rule\u2019 or procedures\u201d required to do so. But the task is understood by man \u201csecretly\u201d is not easy to automate. Mr. Autor call these obstacles \u201cPolanyi Paradox\u201d after the Hungarian-born chemist and economist who observed that \u201cwe know more than we know.\u201d<\/p>\n

This is the \u201chigher education\u201d and \u201clow-education\u201d work that requires \u201cinterpersonal interaction, flexibility, adaptability and problem-solving\u201d -the most difficult to automate records Mr. Autor. Traditional job-secondary education has become the easiest to replace with technology.<\/p><\/blockquote>\n

The Polanyi Paradox, by the way, was formulated by Michael Polanyi<\/a>, who was the father of UofT’s John Polanyi<\/a>. After a lengthy internet search (I hope you’re grateful!), I have found the CBER Ball State study, by Michael J. Hicks and Srikant Devaraj, titled The Myth and the Reality of Manufacturing in America<\/a>:<\/p>\n

Manufacturing has continued to grow, and the sector itself remains a large, important, and growing sector of the U.S. economy. Employment in manufacturing has stagnated for some time, primarily due to growth in productivity of manufacturing production processes.<\/p>\n

Three factors have contributed to changes in manufacturing employment in recent years: Productivity, trade, and domestic demand. Overwhelmingly, the largest impact is productivity. Almost 88 percent of job losses in manufacturing in recent years can be attributable to productivity growth, and the long-term changes to manufacturing employment are mostly linked to the productivity of American factories. Growing demand for manufacturing goods in the U.S. has offset some of those job losses, but the effect is modest, accounting for a 1.2 percent increase in jobs beyond what we would expect if consumer demand for domestically manufactured goods was flat.<\/p>\n

Exports lead to higher levels of domestic production and employment, while imports reduce domestic production and employment. The difference between these, or net exports, has been negative since 1980, and has contributed to roughly 13.4 percent of job losses in the U.S. in the last decade. Our estimate is almost exactly that reported by the more respected research centers in the nation.<\/p>\n

Manufacturing production remains robust. Productivity growth is the largest contributor to job displacement over the past several decades. This leads to a domestic policy consideration.<\/p><\/blockquote>\n

The paper by David Autor is titled Why Are There Still So Many Jobs? The History and Future of Workplace Automation<\/a>:<\/p>\n

Major newspaper stories offer fresh examples daily of technologies that substitute for human labor in an expanding\u2014although still circumscribed\u2014set of tasks. The offsetting effects of complementarities and rising demand in other areas are, however, far harder to identify as they occur. My own prediction is that employment polarization will not continue indefinitely (as argued in Autor 2013). While some of the tasks in many current middle-skill jobs are susceptible to automation, many middle-skill jobs will continue to demand a mixture of tasks from across the skill spectrum. For example, medical support occupations\u2014radiology technicians, phlebotomists, nurse technicians, and others\u2014are a significant and rapidly growing category of relatively well-remunerated, middle-skill employment. Most of these occupations require mastery of \u201cmiddle-skill\u201d mathematics, life sciences, and analytical reasoning. They typically require at least two years of postsecondary vocational training, and in some cases a four-year college degree or more. This broad description also fits numerous skilled trade and repair occupations, including plumbers, builders, electricians, heating\/ventilating\/air-conditioning installers, and automotive technicians. It also fits a number of modern clerical occupations that provide coordination and decision-making functions, rather than simply typing and filing, like a number of jobs in marketing. There are also cases where technology is enabling workers with less esoteric technical mastery to perform additional tasks: for example, the nurse practitioner occupation that increasingly performs diagnosing and prescribing tasks in lieu of physicians.<\/p><\/blockquote>\n

On another note, there is perennial weeping about affordable housing in the big cities, with “affordable” being a euphemism for “subsidized slum”. Bloomberg’s Patrick Clark has written a piece titled Why It\u2019s So Hard to Build Affordable Housing: It\u2019s Not Affordable<\/a>:<\/p>\n

\u201cIf we want to prioritize closing the gap for low-income households, we\u2019re going to need more funding from public subsidy,\u201d said Erika Poethig, director of urban policy initiatives at the Urban Institute, which published an online simulator<\/a> Tuesday for the purpose of illustrating the challenges to building new affordable housing. Our Denver developer above is fictional, but he’s an illustration of what that simulator churns out: No matter how you slice it, creating the affordable housing needed today probably requires government help.<\/p>\n

Playing with the simulator, you quickly learn that there are only a few levers that truly affect a developer\u2019s ability to finance a project. Taking a smaller fee or negotiating a more favorable loan can help at the margins; so can making the project so appealing to residents that no one ever moves out. To really reduce costs or raise revenue, though, there are just these options: Spend less on land, materials, and labor, or bring in more money by raising rents or finding new public financing. But land, materials, and labor can only be cut so much (construction costs are effectively fixed by labor and commodities markets), and raising rents removes the “affordable” from affordable housing.<\/p>\n

That leaves subsidies, the biggest of which is the low-income housing tax credit, which Congress funded to the tune of $7 billion last year. Even so, that program is more useful to developers building for higher wage-earners, said Linda McMahon, chief executive of The Real Estate Council, a trade group for Dallas-area real estate companies. “Below 50 percent of area median income, you’re talking about people who can only afford $500 or so in rent, and you really need another layer of subsidy to pay your [commercial] mortgage,” she said.<\/p><\/blockquote>\n

DBRS has announced<\/a> publication of a paper titled DBRS: Basel Capital Requirements \u2013 What\u2019s Changing?<\/a>:<\/p>\n

The Basel Committee on Banking Supervision (BCBS) has been active in recent months, finalising the minimum capital requirements for market risk (published in January 2016), while also publishing proposed revisions to the standardised approach (December 2015) and the internal model approach for credit (March 2016) and the standardised approach for operational risk (March 2016). These actions are part of the Committee\u2019s efforts to reform global regulatory standards, and reduce the variability of risk-weighted assets (RWAs) across banks and jurisdictions. While DBRS expects that these efforts will improve comparability across the global banking peer group, further transparency would also be valuable in better understanding the risk profile of banks. In particular, DBRS would view positively the standardized disclosure of RWA calculations and components. DBRS also notes that the full implementation of these new requirements is likely to result in a significant amount of operational work for banks, and is expected to lead to a sizeable increase in RWAs.<\/p>\n

With full implementation expected to be required from 2019 (the market risk requirements are to be fully implemented from January 2019 and DBRS expects the time period for implementation to be similar for both credit and operational risk requirements once finalised) this will likely add to the already heavy expense burden associated with regulatory compliance, and result in further pressure for those banks that are currently challenged by limited internal capital generation.<\/p><\/blockquote>\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n
HIMIPref™ Preferred Indices
These values reflect the December 2008 revision of the HIMIPref™ Indices<\/strong>
Values are provisional and are finalized monthly<\/td>\n<\/tr>\n
Index<\/td>\nMean
Current
Yield
(at bid)<\/td>\n		Median
YTW<\/td>\n		Median
Average
Trading
Value<\/td>\n		Median
Mod Dur
(YTW)<\/td>\n		Issues<\/td>\nDay’s Perf.<\/td>\nIndex Value<\/td>\n<\/tr>\n
Ratchet<\/td>\n0.00 %<\/td>\n0.00 %<\/td>\n0<\/td>\n0.00<\/td>\n0<\/td>\n0.5055 %<\/td>\n1,674.7<\/td>\n<\/tr>\n
FixedFloater<\/td>\n0.00 %<\/td>\n0.00 %<\/td>\n0<\/td>\n0.00<\/td>\n0<\/td>\n0.5055 %<\/td>\n3,059.2<\/td>\n<\/tr>\n
Floater<\/td>\n4.90 %<\/td>\n4.69 %<\/td>\n88,107<\/td>\n16.05<\/td>\n4<\/td>\n0.5055 %<\/td>\n1,763.1<\/td>\n<\/tr>\n
OpRet<\/td>\n4.83 %<\/td>\n-2.58 %<\/td>\n46,681<\/td>\n0.10<\/td>\n1<\/td>\n0.1975 %<\/td>\n2,856.0<\/td>\n<\/tr>\n
SplitShare<\/td>\n5.12 %<\/td>\n5.31 %<\/td>\n99,842<\/td>\n2.30<\/td>\n5<\/td>\n-0.0482 %<\/td>\n3,365.8<\/td>\n<\/tr>\n
Interest-Bearing<\/td>\n0.00 %<\/td>\n0.00 %<\/td>\n0<\/td>\n0.00<\/td>\n0<\/td>\n-0.0482 %<\/td>\n2,626.1<\/td>\n<\/tr>\n
Perpetual-Premium<\/td>\n5.48 %<\/td>\n0.81 %<\/td>\n81,619<\/td>\n0.27<\/td>\n12<\/td>\n0.0746 %<\/td>\n2,685.4<\/td>\n<\/tr>\n
Perpetual-Discount<\/td>\n5.20 %<\/td>\n5.18 %<\/td>\n101,603<\/td>\n15.07<\/td>\n26<\/td>\n0.4483 %<\/td>\n2,848.9<\/td>\n<\/tr>\n
FixedReset<\/td>\n4.99 %<\/td>\n4.34 %<\/td>\n150,392<\/td>\n7.12<\/td>\n88<\/td>\n0.0893 %<\/td>\n2,035.8<\/td>\n<\/tr>\n
Deemed-Retractible<\/td>\n5.00 %<\/td>\n4.17 %<\/td>\n123,530<\/td>\n0.09<\/td>\n33<\/td>\n0.2234 %<\/td>\n2,778.3<\/td>\n<\/tr>\n
FloatingReset<\/td>\n2.96 %<\/td>\n4.53 %<\/td>\n32,176<\/td>\n5.13<\/td>\n11<\/td>\n-0.3188 %<\/td>\n2,138.2<\/td>\n<\/tr>\n<\/table>\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n
Performance Highlights<\/strong><\/td>\n<\/tr>\n
Issue<\/td>\nIndex<\/td>\nChange<\/td>\nNotes<\/td>\n<\/tr>\n
BNS.PR.D<\/td>\nFloatingReset<\/td>\n-3.13 %<\/td>\nYTW SCENARIO
\nMaturity Type : Hard Maturity
\nMaturity Date\t: 2022-01-31
\nMaturity Price : 25.00
\nEvaluated at bid price : 18.60
\nBid-YTW : 7.16 %<\/td>\n<\/tr>\n
TRP.PR.H<\/td>\nFloatingReset<\/td>\n-1.35 %<\/td>\nYTW SCENARIO
\nMaturity Type : Limit Maturity
\nMaturity Date\t: 2046-07-26
\nMaturity Price : 10.25
\nEvaluated at bid price : 10.25
\nBid-YTW : 4.40 %<\/td>\n<\/tr>\n
IFC.PR.C<\/td>\nFixedReset<\/td>\n-1.33 %<\/td>\nYTW SCENARIO
\nMaturity Type : Hard Maturity
\nMaturity Date\t: 2025-01-31
\nMaturity Price : 25.00
\nEvaluated at bid price : 17.86
\nBid-YTW : 8.09 %<\/td>\n<\/tr>\n
BMO.PR.Q<\/td>\nFixedReset<\/td>\n-1.23 %<\/td>\nYTW SCENARIO
\nMaturity Type : Hard Maturity
\nMaturity Date\t: 2022-01-31
\nMaturity Price : 25.00
\nEvaluated at bid price : 20.00
\nBid-YTW : 6.29 %<\/td>\n<\/tr>\n
BMO.PR.Y<\/td>\nFixedReset<\/td>\n-1.20 %<\/td>\nYTW SCENARIO
\nMaturity Type : Limit Maturity
\nMaturity Date\t: 2046-07-26
\nMaturity Price : 20.52
\nEvaluated at bid price : 20.52
\nBid-YTW : 4.28 %<\/td>\n<\/tr>\n
PWF.PR.I<\/td>\nPerpetual-Premium<\/td>\n-1.04 %<\/td>\nYTW SCENARIO
\nMaturity Type : Call
\nMaturity Date\t: 2016-08-25
\nMaturity Price : 25.00
\nEvaluated at bid price : 25.80
\nBid-YTW : -30.73 %<\/td>\n<\/tr>\n
GWO.PR.N<\/td>\nFixedReset<\/td>\n-1.03 %<\/td>\nYTW SCENARIO
\nMaturity Type : Hard Maturity
\nMaturity Date\t: 2025-01-31
\nMaturity Price : 25.00
\nEvaluated at bid price : 14.40
\nBid-YTW : 9.52 %<\/td>\n<\/tr>\n
POW.PR.G<\/td>\nPerpetual-Premium<\/td>\n1.08 %<\/td>\nYTW SCENARIO
\nMaturity Type : Call
\nMaturity Date\t: 2020-04-15
\nMaturity Price : 25.25
\nEvaluated at bid price : 26.17
\nBid-YTW : 4.55 %<\/td>\n<\/tr>\n
MFC.PR.I<\/td>\nFixedReset<\/td>\n1.18 %<\/td>\nYTW SCENARIO
\nMaturity Type : Hard Maturity
\nMaturity Date\t: 2025-01-31
\nMaturity Price : 25.00
\nEvaluated at bid price : 20.65
\nBid-YTW : 6.42 %<\/td>\n<\/tr>\n
SLF.PR.J<\/td>\nFloatingReset<\/td>\n1.38 %<\/td>\nYTW SCENARIO
\nMaturity Type : Hard Maturity
\nMaturity Date\t: 2025-01-31
\nMaturity Price : 25.00
\nEvaluated at bid price : 12.50
\nBid-YTW : 11.23 %<\/td>\n<\/tr>\n
MFC.PR.L<\/td>\nFixedReset<\/td>\n1.42 %<\/td>\nYTW SCENARIO
\nMaturity Type : Hard Maturity
\nMaturity Date\t: 2025-01-31
\nMaturity Price : 25.00
\nEvaluated at bid price : 18.53
\nBid-YTW : 7.49 %<\/td>\n<\/tr>\n
MFC.PR.K<\/td>\nFixedReset<\/td>\n1.57 %<\/td>\nYTW SCENARIO
\nMaturity Type : Hard Maturity
\nMaturity Date\t: 2025-01-31
\nMaturity Price : 25.00
\nEvaluated at bid price : 18.08
\nBid-YTW : 7.73 %<\/td>\n<\/tr>\n
BAM.PR.S<\/td>\nFloatingReset<\/td>\n1.75 %<\/td>\nYTW SCENARIO
\nMaturity Type : Limit Maturity
\nMaturity Date\t: 2046-07-26
\nMaturity Price : 14.50
\nEvaluated at bid price : 14.50
\nBid-YTW : 4.89 %<\/td>\n<\/tr>\n
TRP.PR.F<\/td>\nFloatingReset<\/td>\n2.70 %<\/td>\nYTW SCENARIO
\nMaturity Type : Limit Maturity
\nMaturity Date\t: 2046-07-26
\nMaturity Price : 13.71
\nEvaluated at bid price : 13.71
\nBid-YTW : 4.47 %<\/td>\n<\/tr>\n<\/table>\n\n\n\n\n\n\n\n\n\n\n
Volume Highlights<\/strong><\/td>\n<\/tr>\n
Issue<\/td>\nIndex<\/td>\nShares
Traded<\/td>\n		Notes<\/td>\n<\/tr>\n
TRP.PR.J<\/td>\nFixedReset<\/td>\n277,914<\/td>\nYTW SCENARIO
\nMaturity Type : Call
\nMaturity Date\t: 2021-05-31
\nMaturity Price : 25.00
\nEvaluated at bid price : 26.50
\nBid-YTW : 4.34 %<\/td>\n<\/tr>\n
TRP.PR.D<\/td>\nFixedReset<\/td>\n144,700<\/td>\nYTW SCENARIO
\nMaturity Type : Limit Maturity
\nMaturity Date\t: 2046-07-26
\nMaturity Price : 17.99
\nEvaluated at bid price : 17.99
\nBid-YTW : 4.43 %<\/td>\n<\/tr>\n
RY.PR.Q<\/td>\nFixedReset<\/td>\n113,497<\/td>\nYTW SCENARIO
\nMaturity Type : Call
\nMaturity Date\t: 2021-05-24
\nMaturity Price : 25.00
\nEvaluated at bid price : 26.70
\nBid-YTW : 3.86 %<\/td>\n<\/tr>\n
TRP.PR.B<\/td>\nFixedReset<\/td>\n101,900<\/td>\nYTW SCENARIO
\nMaturity Type : Limit Maturity
\nMaturity Date\t: 2046-07-26
\nMaturity Price : 12.02
\nEvaluated at bid price : 12.02
\nBid-YTW : 4.15 %<\/td>\n<\/tr>\n
TRP.PR.A<\/td>\nFixedReset<\/td>\n100,885<\/td>\nYTW SCENARIO
\nMaturity Type : Limit Maturity
\nMaturity Date\t: 2046-07-26
\nMaturity Price : 15.00
\nEvaluated at bid price : 15.00
\nBid-YTW : 4.56 %<\/td>\n<\/tr>\n
MFC.PR.O<\/td>\nFixedReset<\/td>\n84,230<\/td>\nYTW SCENARIO
\nMaturity Type : Call
\nMaturity Date\t: 2021-06-19
\nMaturity Price : 25.00
\nEvaluated at bid price : 26.50
\nBid-YTW : 4.39 %<\/td>\n<\/tr>\n
There were 26 other index-included issues trading in excess of 10,000 shares.<\/td>\n<\/tr>\n<\/table>\n\n\n\n\n\n\n\n\n\n
Wide Spread Highlights<\/strong><\/td>\n<\/tr>\n
Issue<\/td>\nIndex<\/td>\nQuote Data and Yield Notes<\/td>\n<\/tr>\n
PWF.PR.I<\/td>\nPerpetual-Premium<\/td>\nQuote: 25.80 – 26.15
\nSpot Rate : 0.3500
\nAverage : 0.2213<\/p>\n

YTW SCENARIO
\nMaturity Type : Call
\nMaturity Date\t: 2016-08-25
\nMaturity Price : 25.00
\nEvaluated at bid price : 25.80
\nBid-YTW : -30.73 %<\/td>\n<\/tr>\n

BNS.PR.A<\/td>\nFloatingReset<\/td>\nQuote: 23.01 – 23.45
\nSpot Rate : 0.4400
\nAverage : 0.3340<\/p>\n

YTW SCENARIO
\nMaturity Type : Hard Maturity
\nMaturity Date\t: 2022-01-31
\nMaturity Price : 25.00
\nEvaluated at bid price : 23.01
\nBid-YTW : 4.09 %<\/td>\n<\/tr>\n

BNS.PR.D<\/td>\nFloatingReset<\/td>\nQuote: 18.60 – 18.96
\nSpot Rate : 0.3600
\nAverage : 0.2554<\/p>\n

YTW SCENARIO
\nMaturity Type : Hard Maturity
\nMaturity Date\t: 2022-01-31
\nMaturity Price : 25.00
\nEvaluated at bid price : 18.60
\nBid-YTW : 7.16 %<\/td>\n<\/tr>\n

W.PR.K<\/td>\nFixedReset<\/td>\nQuote: 25.70 – 26.00
\nSpot Rate : 0.3000
\nAverage : 0.1976<\/p>\n

YTW SCENARIO
\nMaturity Type : Call
\nMaturity Date\t: 2021-01-15
\nMaturity Price : 25.00
\nEvaluated at bid price : 25.70
\nBid-YTW : 4.62 %<\/td>\n<\/tr>\n

IFC.PR.C<\/td>\nFixedReset<\/td>\nQuote: 17.86 – 18.17
\nSpot Rate : 0.3100
\nAverage : 0.2141<\/p>\n

YTW SCENARIO
\nMaturity Type : Hard Maturity
\nMaturity Date\t: 2025-01-31
\nMaturity Price : 25.00
\nEvaluated at bid price : 17.86
\nBid-YTW : 8.09 %<\/td>\n<\/tr>\n

CM.PR.Q<\/td>\nFixedReset<\/td>\nQuote: 20.35 – 20.74
\nSpot Rate : 0.3900
\nAverage : 0.2985<\/p>\n

YTW SCENARIO
\nMaturity Type : Limit Maturity
\nMaturity Date\t: 2046-07-26
\nMaturity Price : 20.35
\nEvaluated at bid price : 20.35
\nBid-YTW : 4.29 %<\/td>\n<\/tr>\n<\/table>\n","protected":false},"excerpt":{"rendered":"

Low returns are finally catching up to American pension plans: Twenty-year annualized returns for public pensions in the U.S. are poised to decline to 7.47% once fiscal 2016 results are released in coming weeks, according …<\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[15],"tags":[],"class_list":["post-33406","post","type-post","status-publish","format-standard","hentry","category-market-action"],"_links":{"self":[{"href":"https:\/\/prefblog.com\/index.php?rest_route=\/wp\/v2\/posts\/33406","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/prefblog.com\/index.php?rest_route=\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/prefblog.com\/index.php?rest_route=\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/prefblog.com\/index.php?rest_route=\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/prefblog.com\/index.php?rest_route=%2Fwp%2Fv2%2Fcomments&post=33406"}],"version-history":[{"count":0,"href":"https:\/\/prefblog.com\/index.php?rest_route=\/wp\/v2\/posts\/33406\/revisions"}],"wp:attachment":[{"href":"https:\/\/prefblog.com\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=33406"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/prefblog.com\/index.php?rest_route=%2Fwp%2Fv2%2Fcategories&post=33406"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/prefblog.com\/index.php?rest_route=%2Fwp%2Fv2%2Ftags&post=33406"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}