Jeff Bezos is the anonymous buyer of the biggest house in Washington

By Emily Heil and

Kathy Orton

January 10, 2019

Amazon founder Jeffrey P. Bezos is the new owner of the former Textile Museum, which will be converted into Washington’s largest home. (Courtesy of George Washington University Museum and the Textile Museum)

Washington’s Kalorama neighborhood just keeps getting swankier: Amazon founder and Washington Post owner Jeffrey P. Bezos has bought the former Textile Museum, a 27,000 square-foot property, intending to convert it into a single-family home, according to a person with knowledge of the sale.

Bezos’s neighbors will include President Obama and his family, who are renting a property nearby for their post-White House home, as well as future first daughter Ivanka Trump and her husband, incoming presidential adviser Jared Kushner.

The Washington Post's Kathy Orton held a Facebook Live walking tour of the Kalorama neighborhood, one of the most expensive, exclusive areas in D.C. (The Washington Post)

The home — the largest in Washington — sold Oct. 21 for $23 million in cash (a million over its list price) to a buyer described in public documents as the Cherry Revocable Trust. But word about the identity of the new billionaire next door has been circulating around the enclave that ambassadors and Cabinet secretaries have long called home.

Bezos, his wife, MacKenzie, and their four children live in the Seattle area. When he purchased The Post in 2013, Bezos said he didn’t plan to relocate to “the other Washington.” “I won’t be leading The Washington Post day-to-day,” he told Forbes. There are no indications he will move here permanently.

[Textile Museum sells historic Kalorama properties for $19 million]

The home is expected to be an East Coast pied-à-terre for the family — allowing him to avoid hotel bills — but the ample square footage means there’s plenty of room for entertaining. (Take a tour of the property here.)

The property at 2320-2330 S St. NW spans two historic mansions, which housed the Textile Museum for nearly 90 years until it moved to George Washington University’s campus in 2013. The two mansions were sold together in May 2015 for $19 million, the largest residential sale in the District that year. They were put back on the market in 2016 at $22 million.

The property has drawn interest not just because of its sprawling size but also its architectural pedigree. In 1912, Textile Museum founder George Hewitt Myers hired John Russell Pope, architect of the Jefferson Memorial, to design his home at 2320 S St. A decade later, Myers bought the adjacent mansion, which was designed by noted Washington architect Waddy Butler Wood. Both properties are on the National Register of Historic Places.

Don’t look for moving vans just yet, though. Renovation plans drawn up by prominent local architecture firm Barnes Vanze are under review by the local Advisory Neighborhood Commission.

The Textile Museum was built in 1912. (Amanda Voisard for The Washington Post)

See the neighborhood where the Obamas and Ivanka Trump’s family live

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The former president and first lady, the daughter of President Trump and her husband, and the founder of Amazon.com (and owner of The Washington Post) are residents of the District’s historic Kalorama neighborhood.

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Jeff Bezos announces divorce from MacKenzie Bezos after 25 years together

Amazon.com founder and chief executive Jeffrey P. Bezos and his wife, MacKenzie Bezos, are getting a divorce.

“As our family and close friends know, after a long period of loving exploration and trial separation, we have decided to divorce and continue our shared lives as friends,” the couple said in a statement, which Bezos, 54, shared Wednesday morning on Twitter. “We’ve had such a great life together as a married couple, and we also see wonderful futures ahead, as parents, friends, partners in ventures and projects, and as individuals pursuing ventures and adventures,” it continued.

pic.twitter.com/Gb10BDb0x0

— Jeff Bezos (@JeffBezos) January 9, 2019

Bezos, who owns The Washington Post, has an estimated net worth of $137 billion and topped Forbes’s list last year of the richest Americans (beating out Bill Gates, Warren Buffett and Mark Zuckerberg), as well as the list of billionaires worldwide.

D.C. divorce lawyer Sandy Ain, who has handled his share of splits among the uber-wealthy (although he doesn’t rep either Bezos), notes that Washington state, where the Bezoses reside, is a “community property” state, meaning that all assets and debts accumulated during a marriage are divided equally. Because Bezos is the richest person in the world, a 50/50 agreement would result in the biggest recorded divorce settlement.

But, Ain says, the couple could have a prenuptial agreement — or even a postnuptial agreement (meaning it was negotiated after the “I do’s”) — that would trump the law declaring a couple halve everything. And what could be in such an arrangement? “Literally anything they wanted,” Ain said, including a potential provision that property acquired under one party’s name remain theirs.

Ain notes that the couple’s amicable joint statement indicates that the split probably won’t be messy or protracted. “Sounds like they are making an effort to do this the right way and not make it into a public spectacle,” he said.

And even if the couple winds up splitting the fortune — a move that could knock Bezos off the top of the richest list — Ain notes that merely means the couple will each occupy one slot, just further down the ranking.

“They will still be one-percenters,” he said.

The couple wed in 1993, a year after meeting at the hedge fund D.E. Shaw & Co., where MacKenzie (nee Tuttle) was a research associate. In a 2013 interview with Vogue, MacKenzie — who, like Bezos, graduated from Princeton University — said her first interview at the firm was with her future husband, a senior vice president.

“My office was next door to his, and all day long I listened to that fabulous laugh,” she told the magazine. “How could you not fall in love with that laugh?”

At the time, MacKenzie, who counted Pulitzer Prize-winning writer Toni Morrison as one of her mentors at Princeton, was an aspiring novelist. Her debut novel, “The Testing of Luther Albright,” was published in 2005.

Attempts to reach MacKenzie, 48, through her publisher were not immediately returned.

The couple have lived in Seattle since 1994. They have four children.

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Price compare Online Shopping Store

For the greater part of us, web based shopping has rapidly turned into the go-to approach to locate the best arrangements on everything from cosmetics to garments to apparatuses and gems. It's difficult to envision much else advantageous than signing on to your most loved online retailer and finding similar items you would buy at a physical store at a small amount of the cost. Be that as it may, trust it or not, shopping on the web is getting significantly simpler because of value examination applications. 

For some Americans, web based shopping has been synonymous with a couple of huge retail organizations. Be that as it may, as the comfort of Internet shopping permits littler, more distinctive makers to extend their business sectors, web based business is helping individuals discover better and better arrangements on brilliant items. The main issue is that with an ever increasing number of outlets moving to online deals each year, finding as well as can be expected mean investing hours looking through many changed sites. 

With online value correlation devices the inquiry is a great deal less demanding. Rather than opening up many tabs and contrast webpage with webpage, value correlation sites and applications do all the work for you by totaling item data and evaluating information from a huge number of various online retailers and making it effectively accessible. On the off chance that you need to know where to locate the best cost on another calfskin tote, for instance, you should simply choose or enter the hunt terms and look through the postings to perceive what value it is going for at various retail outlets. When you select which retailer you need to buy from, you can get it specifically from that retailer's site. 

Value correlation applications clearly make it less demanding than any time in recent memory to locate the best costs for items, yet they can likewise enable you to wind up a more quick witted customer in different ways. Applications like Yroo offer value history diagrams that let you see the normal cost for any given item after some time, and give you an understanding into how the present value thinks about. In the event that there is a specific item you are keen on following, the application enables you to "top choice" it and get an alarm when it goes marked down. 

As they turn out to be more mainstream, customers are finding better approaches for utilizing value correlation applications. For instance, while online retail is frequently observed as a danger to conventional shops, numerous purchasers see an incentive in both. When looking for apparel, for instance, a client may visit a physical store to attempt on another coat or match of pants to check the size, however buy them from the retailer's online store if there is a lower cost accessible on the web. On the other hand, customers may locate an uncommon deal through a value correlation application, at that point visit the physical store to buy the item face to face.

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Who Will Win the 2018 Elections

When we first idea of beginning this site, our essential objective was to gather all decision related information in one place, clean it, comprehend it, and afterward in the long run utilize it to foresee future race results. Our examination so far has demonstrated that there's now a mind blowing sum and assortment of datasets accessible (though in unique areas) with the fundamental elements for building a decision expectation calculation. What's more, we're not looking at foreseeing which gathering will win races generally speaking. That is significant as well. Be that as it may, what's all the more fascinating, and not done previously, is guaging victors on every one of the 272 National Get together seats up for snatches in the 2018 decisions. This is a definitive objective of the Pakistan Decision Watch venture. We would like to use a wide range of datasets out there, expand them with our own particular surveying and research, and fabricate a strong measurable model that gives significant bits of knowledge into who may win a specific National Get together voting demographic in the up and coming 2018 Pakistan Decisions. 

The Approach 

Our initial move toward building such a model will be to order every one of the 272 National Get together seats as either "Safe" seats or "Swing" seats in view of various components. A protected seat here is characterized as a body electorate with a high probability of being won by a specific gathering or applicant that has a solid vote bank there. A swing seat then again is one where either no single gathering has clear predominance, or where assessments and inclinations host moved far from the overwhelming get-together/applicant after some time. Foreseeing a champ on a swing seat will in this way include promote examination looking more inside and out into attributes of the voting demographic (e.g. statistics socioeconomics, supposition surveying, competitor quality, and so on). In the area beneath we share a portion of the elements and information highlights we'll use to influence the sheltered versus to swing arrangements, and for foreseeing which way a swing seat may go. 

Anticipating Variables 

Our displaying approach is driven by the theory that specific components accessible in the information are great indicators of whether a supporters is a sheltered seat or a swing seat (as characterized previously). A portion of the elements we'll be investigating are the accompanying: 

Winning Streaks: By breaking down the last three races (2002, 2008, and 2013), we can detach seats where a specific gathering or applicant won the seat in each of the three (dash of 3) or the latest two (dash of 2) races. Such winning streak would show the nearness of a solid vote bank in that body electorate that is faithful to the gathering/hopeful. 

Triumph Edge: The edge of votes by which an applicant won a seat, both in outright and rate terms, is an essential metric. A seat where the triumph edge was path over the normal could be thought of as a sheltered seat, while a the other way around circumstance (triumph edge < 5%) would show a conceivable swing seat. We will likewise break down the pattern in triumph edges in the course of the last three decision cycles. Seats where edges are retreating could point to a swing in voter inclinations. 

Turnout Rate: Pakistan has truly had a reliably low turnout rate. We will audit turnout rates by every body electorate, uncovering territories where both triumph edges and turnouts were low in 2013 - basically swing seats where gatherings could swing brings about their support by expanding turnout among their voters. 

Hopeful Quality: We may host numerous political gatherings, yet the quality of "electables" in our decisions stays more grounded than at any other time. These are identities whose vote bank is attached to them instead of any political gathering they are a piece of. Their forces comes from their primitive or ancestral families, in light of the fact that medieval lordship or innate loyalties holds more influence in the rustic heartland of Pakistan than arrangement positions and declarations. We will track who these "electables", and factor that into who may win a voting public they are challenging in. 

Statistic Moves: These are energizing circumstances on the information front since Pakistan just experienced a registration practice after very nearly 20 years. The most recent enumeration comes about, once discharged, will guide us toward territories where socioeconomic have changed impressively with time. To foresee how these socioeconomic movements will affect voter inclinations, we'll make utilization of sentiment surveys that break out voting inclinations by socioeconomic. 

These are only a couple of numerous highlights we intend to investigate and use toward building our race expectation demonstrate. 

Difficulties and Admonitions 

We'd be delinquent on the off chance that we didn't bring up the numerous difficulties and provisos that accompany building a model with the grand point of anticipating electorate shrewd decision comes about. 

Results 

Utilizing the components laid out over, our model will appoint to every NA voting demographic a Seat Security Score showing the probability of the seat being won by a similar gathering that won it the last time round in 2013 

Anticipated Victor Gathering, demonstrating which of the three noteworthy political gatherings (PML-N, PPP, and PTI) is the feasible champ of the seat in 2018 Likelihood/Certainty Score which is a measure of how sure we are in expectation of who will win this seat in this up and coming decision 

While this is the inevitable objective, en route we'll investigate each factor we need to incorporate into our model and perceive how great of an indicator that element is. The following are connections to posts enumerating our discoveries and taking a profound jump on every individual factor.

Who Will Win the 2018 Elections
Election 2018 Pakistan
election 2018 Pakistan predictions
Pakistan election 2018 date
Next prime minister of Pakistan 2018

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