WEBVTT - Being Black in America and Damp Eco Sentiment

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<v Speaker 1>You're listening to the Bloomberg Opinion podcast counts Saturdays at

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<v Speaker 2>Welcome to Bloomberg Opinion. I'm Lisa Matteo. This week a

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<v Speaker 2>conversation with Lisa Jarvis about Moderna's tough road ahead, Claudia

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<v Speaker 2>Sam with a look at why so many Americans are

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<v Speaker 2>downbeat about the economy, and insight into what the future

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<v Speaker 2>holds for the farming industry with Laura Williams. But first,

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<v Speaker 2>Justin Fox joins us with a look into the homicide

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<v Speaker 2>rate of Black Americans. The title of your opinion piece,

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<v Speaker 2>where It's most Dangerous to Be Black in America, That

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<v Speaker 2>itself is eye catching, but the stat that you give

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<v Speaker 2>right off the top really hits home. I'm going to

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<v Speaker 2>say it for you. Black Americans make up thirteen point

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<v Speaker 2>six percent of the US population in twenty twenty two

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<v Speaker 2>and fifty four point one percent of the victims of

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<v Speaker 2>murder and homicide. Now you check with data from the

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<v Speaker 2>CDC explains what this works out to as far as

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<v Speaker 2>homicide rate, for Black Americans and just the scope.

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<v Speaker 3>Of it, I mean, the homicide rate for Black Americans

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<v Speaker 3>in twenty twenty two. And this data isn't totally completely

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<v Speaker 3>final yet, but I've been checking it for a while

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<v Speaker 3>and it isn't changing much. And this is all on

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<v Speaker 3>the CDC's online Wonder database that anybody can look into,

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<v Speaker 3>although it takes a while to get up to speed

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<v Speaker 3>on it, which I did sadly early in the pandemic. Anyway,

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<v Speaker 3>the homicide rate for Black Americans last year was about

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<v Speaker 3>thirty per one hundred thousand people. For everybody else in

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<v Speaker 3>the country it was about four and four is still

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<v Speaker 3>pretty high by the standards of like other rich countries

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<v Speaker 3>in Europe and East Asia and such. I mean, in Japan,

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<v Speaker 3>it's just zero point two per hundred thousand, but it's

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<v Speaker 3>you know, thirty per hundred thousand is similar to even

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<v Speaker 3>higher than in places like Brazil, Colombia, Mexico that are

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<v Speaker 3>kind of known as being very, very violent. And it's

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<v Speaker 3>also a lot higher than the rate was before the pandemic,

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<v Speaker 3>and especially around twenty fifteen twenty fourteen.

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<v Speaker 2>Right, and you mentioned when the homicide rady goes up,

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<v Speaker 2>black Americans suffer disproportionately.

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<v Speaker 3>Yeah, Like when you look at the increase in homicides,

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<v Speaker 3>especially from twenty nineteen to twenty twenty. I mean, as

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<v Speaker 3>we've said, a little over half of all homicide victims

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<v Speaker 3>in the US are black, but the increase was about

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<v Speaker 3>sixty five percent Black Americans, So it's clear that, Yeah,

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<v Speaker 3>when there's a wave of violence, it's it's Black Americans

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<v Speaker 3>who suffer the most. And when that wave recedes, as

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<v Speaker 3>this one is now doing, it's you know, down a

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<v Speaker 3>bit in the CDC data for last year, and in

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<v Speaker 3>crime statistics from New York, Los Angeles everywhere else, it's

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<v Speaker 3>down a lot so far this year too, So at

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<v Speaker 3>least that news is good. But wow, it went up

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<v Speaker 3>a lot, especially during the pandemic, but there'd also been

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<v Speaker 3>something of a rise in a couple of years before then.

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<v Speaker 2>All Right, and you mentioned when the racial definitions have

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<v Speaker 2>changed recently, you talk about that as more government agencies

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<v Speaker 2>classify Americans as multiracial. So how does this change things

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<v Speaker 2>when you were going through the article.

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<v Speaker 3>I mean, it doesn't change it much. It just makes

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<v Speaker 3>it a pain because basically, in all the data from

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<v Speaker 3>twenty eighteen and earlier, the CDC uses the old racial definitions,

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<v Speaker 3>which are basically sort of are you mostly black, are

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<v Speaker 3>you mostly white? Whatever? With the twenty twenty census, and

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<v Speaker 3>they started doing before then, they're much more open to no,

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<v Speaker 3>I'm multiple, I'm lots of things, which I think in

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<v Speaker 3>a lot of ways is great and very healthy development

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<v Speaker 3>for our country. But it's a pain when you're trying

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<v Speaker 3>to look at developments in long run statistics by race.

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<v Speaker 3>It doesn't make that big a difference on a national

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<v Speaker 3>level in these numbers. The more recent statistics, who were

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<v Speaker 3>for people who identify as Black or African American only,

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<v Speaker 3>but you know in the census and all the people

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<v Speaker 3>who identify themselves as more than one race are sort

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<v Speaker 3>of in this no man's land. It couldn't get great

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<v Speaker 3>per capita statistics on them. With some of the cities

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<v Speaker 3>I looked at, it made a difference, but not enough

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<v Speaker 3>to really change the trajectory in a big way.

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<v Speaker 2>Yeah, and that's what I want to get to. Some

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<v Speaker 2>of those numbers. So the black homicide rates far lower

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<v Speaker 2>in some parts of the country than in other parts.

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<v Speaker 2>And you really broke down that twenty twenty two rates

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<v Speaker 2>for the country's most populous metro areas. So talk about

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<v Speaker 2>who topped the list, who came out at the bottom.

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<v Speaker 2>What did you find out?

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<v Speaker 3>This is among the thirty largest metro areas. And the

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<v Speaker 3>kind of interesting thing with the CDC data is you

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<v Speaker 3>can basically ask it to give really detailed stuff like

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<v Speaker 3>how many people were murdered in some small county in

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<v Speaker 3>Texas in twenty thirteen, and for that it won't tell

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<v Speaker 3>you because it basically won't disclose data if they're fewer

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<v Speaker 3>than ten people involved, because the idea is that that

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<v Speaker 3>would make it possible, and it doesn't really with murder,

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<v Speaker 3>it doesn't really matter, but with other causes of death,

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<v Speaker 3>it would invade people's privacy. It's really helpful to do

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<v Speaker 3>big groups. The CDCED used to publish a lot of

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<v Speaker 3>this data by metropolitan area. You could just click I

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<v Speaker 3>want everything sorted by metropolitinaria. For some reason, they don't

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<v Speaker 3>do that anymore. But you can go in and pick

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<v Speaker 3>all the counties in a metropolitan area and ask it

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<v Speaker 3>to combine all of which is a long excuse for

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<v Speaker 3>why I only did thirty metropolitan areas rather than anymore. Anyway,

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<v Speaker 3>So these thirty biggest metropolitan areas, the worst is Saint Louis,

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<v Speaker 3>which is a bunch of counties in both Missouri and

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<v Speaker 3>across the river in Illinois, and Baltimore is not far behind.

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<v Speaker 3>And then the best are basically New York, San Diego,

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<v Speaker 3>and best of all, Boston. And that's for overall homicide

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<v Speaker 3>right now.

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<v Speaker 2>Did anything surprise you about the results that came out

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<v Speaker 2>from that?

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<v Speaker 3>I mean, this kind of started. I wrote a piece

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<v Speaker 3>a year ago looking at CDC data just to it

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<v Speaker 3>was sort of at the moment when crime in New

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<v Speaker 3>York was really top of mind and lots of people

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<v Speaker 3>around the world seem in the country seemed to think

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<v Speaker 3>New York was just such a dangerous place. And I

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<v Speaker 3>looked at homicides, it's not bad in New York. You

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<v Speaker 3>throw in accident data in New York is like one

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<v Speaker 3>of the safest places in the country. So that didn't

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<v Speaker 3>surprise me. But it's still kind of funny to see

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<v Speaker 3>it down at the bottom here. It kind of remarkable

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<v Speaker 3>how low Boston is. I mean, it's not that surprising

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<v Speaker 3>when you think about it, but it's like another big

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<v Speaker 3>step lower than in New York or it's only two

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<v Speaker 3>per hundred thousand overall, and the nationwide for everybody is

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<v Speaker 3>something like five point seven five point eight, so it's

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<v Speaker 3>a lot lower in Boston. In New York, it's three

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<v Speaker 3>point seven per hundred thousand. Saint Louis, the overall homicide

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<v Speaker 3>rate is fifteen point seven per hundred thousand, But then

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<v Speaker 3>you break it down by race, and it's just it's

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<v Speaker 3>an even bigger gap in some cases.

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<v Speaker 2>Well, I'm glad you mentioned that gap. And you also

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<v Speaker 2>found some regional patterns to this data too.

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<v Speaker 4>Yeah.

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<v Speaker 3>I mean, the worst places, at least in this thirty

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<v Speaker 3>biggest metro area list in both the worstplaces in overall

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<v Speaker 3>homicide rates are pretty much all kind of rust Belt

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<v Speaker 3>or russ I guess Baltimore is not officially in the

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<v Speaker 3>rust Belt, but it kind of feels like it. And

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<v Speaker 3>you know, Saint Louis, Chicago, Philadelphia, Detroit, and then Atlanta's

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<v Speaker 3>pretty high too. When you break it down, what you

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<v Speaker 3>get is really this these old Saint Louis, Pittsburgh, Philadelphia

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<v Speaker 3>stand out, and then this bizarre newcomer Portland, Oregon, which

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<v Speaker 3>wouldn't have been high on this list at all five

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<v Speaker 3>years ago but is just awfully high now. It's more

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<v Speaker 3>dangerous to be black in Portland last year than in

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<v Speaker 3>Detroit or Baltimore or Chicago.

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<v Speaker 5>That's crazy.

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<v Speaker 2>Let's talk about those incidents of police violence that go

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<v Speaker 2>viral a spark protests. We've seen it. They can tend

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<v Speaker 2>to be followed by local increased is in violent crime.

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<v Speaker 2>So talk more about how this affects those homicide rates.

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<v Speaker 3>Obviously, police violence, I mean sometimes it's inevitable. A lot

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<v Speaker 3>of times it's not. People have lots of reasons to

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<v Speaker 3>protest against it and be mad about it and try

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<v Speaker 3>to fix it. At the same time, it's you know,

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<v Speaker 3>black people killed by police officers. It's around two hundred

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<v Speaker 3>and fifty a year as opposed to more than thirteen

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<v Speaker 3>thousand black victims of homicide overall. And it's so it's

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<v Speaker 3>pretty clear that, you know, if the focus is that

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<v Speaker 3>black lives matter, and it should be that it's getting

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<v Speaker 3>down crime rates is the most important thing. And having

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<v Speaker 3>effective policing, which generally means police departments that aren't abusing

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<v Speaker 3>their citizens, but at the same time means police departments

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<v Speaker 3>that are arresting people and fighting crime, is really important

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<v Speaker 3>to save people's.

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<v Speaker 2>Now, justin I think it's important to note that you

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<v Speaker 2>did all of this intense, intense research for this story,

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<v Speaker 2>and you are not black. What motivated you to take

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<v Speaker 2>this on?

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<v Speaker 3>I mean, the initial thing is just as as mentioned,

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<v Speaker 3>I got familiar with these CDC databases early in the

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<v Speaker 3>pandemic and was like looking at all the things that

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<v Speaker 3>were more or less likely to kill you than COVID.

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<v Speaker 3>And one of the things that starts coming out when

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<v Speaker 3>you're looking at younger people is that you know, it's

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<v Speaker 3>mostly not diseases did kill young people. It's accidents, it's suicides,

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<v Speaker 3>it's homicides. And then you start storing it by race

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<v Speaker 3>and especially by gender, and like it's for black young men,

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<v Speaker 3>it's homicide is the number one cause of death most

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<v Speaker 3>of the time. It might not be in twenty twenty

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<v Speaker 3>two for the awful reason that the opioid epidemic is

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<v Speaker 3>sort of moved from rural areas where that are mostly white,

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<v Speaker 3>into cities. And so I mean that's the initial thing.

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<v Speaker 3>It's just this is this thing that I don't think

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<v Speaker 3>it's enough attention. And then I I do think it

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<v Speaker 3>was this frustration with especially the mainstream media coverage of

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<v Speaker 3>police violence and the black Lives Matter movement that I

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<v Speaker 3>just think has underplayed this sort of underlying reality that

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<v Speaker 3>the biggest threat to young men's black lives is not police,

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<v Speaker 3>it's violence in their own communities, and police can make

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<v Speaker 3>that better, can make that worse. But it's just it

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<v Speaker 3>just feels like the focus of the discussion has been

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<v Speaker 3>way too much in one place. And I think it's

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<v Speaker 3>mainly because the mainstream media is full of white journalists

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<v Speaker 3>like me who feel uncomfortable writing about these things. So

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<v Speaker 3>I don't know, I mean, I don't have good answers.

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<v Speaker 3>Here are good explanations of why this problem persists, but

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<v Speaker 3>it does seem really important to note that it was

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<v Speaker 3>much better a few years ago, and it's much better

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<v Speaker 3>in some cities than others. This is not some inevitable thing.

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<v Speaker 2>Bloomberg Opinion columnist justin Fox. Coming up, we'll speak with

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<v Speaker 2>columnist Lisa Jarvist about moderna and vaccine development. This is

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<v Speaker 2>Bloomberg Opinion.

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<v Speaker 1>You're listening to the Bloomberg Opinion Podcast Contest Saturdays at

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<v Speaker 1>one and seven pm Eastern on Bloomberg dot Com, the

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<v Speaker 1>iHeartRadio app, and the Bloomberg Business App, or listen on

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<v Speaker 1>demand wherever you get your podcasts.

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<v Speaker 2>You're listening to Bloomberg Opinion. I'm Lisa Matteo. Let's bring

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<v Speaker 2>an opinion columnist Lisa Jarvis to get her thoughts on

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<v Speaker 2>where Moderna stands among the competition as it expands into

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<v Speaker 2>other infectious diseases. Moderna has had a tough road ahead

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<v Speaker 2>of it. That's the feel from this opinion piece that

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<v Speaker 2>you put together. Now, you mentioned that the company's biggest

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<v Speaker 2>challenge has shifted from proving that it's mrina vaccines and

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<v Speaker 2>products work to convincing the world that they offer something

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<v Speaker 2>better than what's out there. I mean, how tough is

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<v Speaker 2>that a sell?

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<v Speaker 6>I think it's definitely a tougher sell than when they

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<v Speaker 6>had this captive market which just you know, a vac

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<v Speaker 6>seen from them and from Advisor, and everyone was feeling

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<v Speaker 6>very motivated to take it. But the products that they

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<v Speaker 6>have coming up next, and you know, I'll to say

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<v Speaker 6>it's impressive. They have four things that are likely to

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<v Speaker 6>be on the market by twenty twenty five. You know,

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<v Speaker 6>if we're talking about a different biotech company, that might

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<v Speaker 6>feel really impressive. But all of those things already have

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<v Speaker 6>existing products and so so far, what they've shown is

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<v Speaker 6>what they can offer is something that's about the same

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<v Speaker 6>as what's already out there. So they'll have an RSV vaccine,

0:12:33.240 --> 0:12:36.520
<v Speaker 6>a flu vaccine, a vaccine that combines covid and flu,

0:12:36.960 --> 0:12:39.080
<v Speaker 6>you know, to note that is novel, and then they'll

0:12:39.080 --> 0:12:43.560
<v Speaker 6>have a next generation covid vaccine. So you know, RSV

0:12:43.640 --> 0:12:46.960
<v Speaker 6>and flu are really competitive markets. And so the question is,

0:12:47.120 --> 0:12:50.080
<v Speaker 6>you know, are they offering something better? Are the side

0:12:50.120 --> 0:12:52.920
<v Speaker 6>effects worse for their vaccine? You know, how do they

0:12:52.960 --> 0:12:56.600
<v Speaker 6>convince people that they should choose their mRNA vaccine over

0:12:57.080 --> 0:13:00.040
<v Speaker 6>you know what already? You know we're all familiar with.

0:13:00.559 --> 0:13:02.920
<v Speaker 2>Right and you spoke with Maderna's CEO. I mean, does

0:13:02.960 --> 0:13:04.559
<v Speaker 2>he like the progress that he's seeing?

0:13:05.000 --> 0:13:07.080
<v Speaker 6>He definitely does. And you know, I think what they're

0:13:07.120 --> 0:13:09.840
<v Speaker 6>trying to pitch to investors right now is that they're

0:13:09.880 --> 0:13:13.160
<v Speaker 6>really transforming, you know, and you know that they have

0:13:13.240 --> 0:13:16.920
<v Speaker 6>a very full pipeline and that they're not going to

0:13:16.960 --> 0:13:19.160
<v Speaker 6>be just a one product company. In fact, they have

0:13:19.200 --> 0:13:22.920
<v Speaker 6>a platform that is delivering. Each of their phase threes

0:13:22.960 --> 0:13:25.280
<v Speaker 6>has been successful, so I have to give them credit

0:13:25.320 --> 0:13:28.160
<v Speaker 6>for that. And they are going to be active in

0:13:28.200 --> 0:13:32.880
<v Speaker 6>three areas infectious diseases, cancer, and then rare diseases, which

0:13:33.040 --> 0:13:35.000
<v Speaker 6>you know that's a little further in the distance when

0:13:35.000 --> 0:13:37.640
<v Speaker 6>we'll start to see products coming out of that. So,

0:13:37.840 --> 0:13:40.679
<v Speaker 6>you know, I think he's basically trying to convince everyone

0:13:40.800 --> 0:13:43.280
<v Speaker 6>to be patient to you know, that it's going to

0:13:43.360 --> 0:13:45.959
<v Speaker 6>cost them some money to get these things to market,

0:13:46.520 --> 0:13:48.480
<v Speaker 6>you know. I think just the question is, you know,

0:13:48.520 --> 0:13:53.760
<v Speaker 6>how they adjust to a different reality than they faced

0:13:53.840 --> 0:13:56.320
<v Speaker 6>during COVID when it comes to marketing their products and

0:13:56.360 --> 0:13:58.439
<v Speaker 6>showing that they have something that is better.

0:13:59.080 --> 0:14:01.439
<v Speaker 2>Now, let's get in to that money. So as MODERNA

0:14:01.480 --> 0:14:04.320
<v Speaker 2>moves into other infectious diseases that you were just talking about,

0:14:04.480 --> 0:14:06.560
<v Speaker 2>it's facing a lot of competition, right, and they've been

0:14:06.640 --> 0:14:09.600
<v Speaker 2>putting a lot of money into late stage clinical studies.

0:14:10.000 --> 0:14:13.400
<v Speaker 2>Can the payoff of its transformation justify the cost?

0:14:13.920 --> 0:14:16.600
<v Speaker 6>That really is the key question that they need to answer.

0:14:16.800 --> 0:14:19.800
<v Speaker 6>I mean they think yes, obviously, I think they're going

0:14:19.840 --> 0:14:22.920
<v Speaker 6>to be putting They said twenty five billion dollars in

0:14:23.080 --> 0:14:26.520
<v Speaker 6>R and D between twenty twenty four and twenty twenty eight.

0:14:26.600 --> 0:14:29.200
<v Speaker 6>That that puts them in the same league, just below

0:14:29.200 --> 0:14:31.840
<v Speaker 6>Gilead Sciences, which obviously has been around for a lot

0:14:31.920 --> 0:14:35.600
<v Speaker 6>longer and has a lot more successful products on the market.

0:14:35.920 --> 0:14:38.240
<v Speaker 6>And so you know, I think what they need to

0:14:38.280 --> 0:14:41.680
<v Speaker 6>prove is that they can be the kind of marketing

0:14:41.720 --> 0:14:43.640
<v Speaker 6>powerhouse that they're going to need to be to get

0:14:43.640 --> 0:14:46.280
<v Speaker 6>these products out there and convince people that they're worthwhile.

0:14:47.240 --> 0:14:49.600
<v Speaker 6>You know, that there really is going to be demand

0:14:49.720 --> 0:14:52.600
<v Speaker 6>for say, a vaccine that combines covid and flu. To me,

0:14:52.720 --> 0:14:55.280
<v Speaker 6>that's the most unique thing that they've got going for them.

0:14:55.720 --> 0:14:59.320
<v Speaker 6>And then I think last is their cancer vaccine that

0:14:59.600 --> 0:15:02.160
<v Speaker 6>could be potentially be on the market by twenty twenty five.

0:15:02.600 --> 0:15:05.520
<v Speaker 6>There's a lot of excitement around that. The you know,

0:15:05.680 --> 0:15:07.840
<v Speaker 6>kind of other issue they have is that right now,

0:15:07.840 --> 0:15:10.320
<v Speaker 6>it's very expensive to make these products, and so they

0:15:10.320 --> 0:15:14.200
<v Speaker 6>need to get down you know, that cost so that yeah,

0:15:14.280 --> 0:15:16.760
<v Speaker 6>that even if they are making you know a lot

0:15:16.800 --> 0:15:19.040
<v Speaker 6>of money off of these vaccines, that you know, there's

0:15:19.080 --> 0:15:20.120
<v Speaker 6>actually a profit there.

0:15:20.480 --> 0:15:23.080
<v Speaker 2>All right, Let's get to the funding, because it really

0:15:23.120 --> 0:15:26.240
<v Speaker 2>depends on the continuing sales of the vaccine. I mean,

0:15:26.360 --> 0:15:30.560
<v Speaker 2>is is the demand strong enough for the vaccine.

0:15:30.680 --> 0:15:33.480
<v Speaker 6>They have no choice but to rely on Americans wanting

0:15:33.560 --> 0:15:35.520
<v Speaker 6>Americans and people around the world wanting to roll up

0:15:35.520 --> 0:15:38.280
<v Speaker 6>their sleeves for this new booster that you know, has

0:15:38.440 --> 0:15:43.280
<v Speaker 6>recently become available. This updated shot to XBB. You know,

0:15:43.560 --> 0:15:46.560
<v Speaker 6>we know that last year only seventeen percent of people

0:15:46.600 --> 0:15:50.880
<v Speaker 6>in the US opted to get that that shot, and

0:15:50.960 --> 0:15:53.320
<v Speaker 6>so I think their hope is this is the first

0:15:53.400 --> 0:15:56.600
<v Speaker 6>year that we're in a actual commercial market. They're the

0:15:56.640 --> 0:15:59.600
<v Speaker 6>ones who are trying to get out there and get

0:15:59.600 --> 0:16:01.680
<v Speaker 6>the word out that they've got this vaccine. It's not

0:16:01.800 --> 0:16:05.640
<v Speaker 6>the government that's providing it. So it's going to be

0:16:06.040 --> 0:16:09.120
<v Speaker 6>interesting to see what happens. I think there's some skepticism that,

0:16:09.560 --> 0:16:12.760
<v Speaker 6>you know, their projections for how many people are willing

0:16:12.880 --> 0:16:15.200
<v Speaker 6>to get their shot, you know, will be matched with

0:16:15.240 --> 0:16:17.720
<v Speaker 6>the reality of some of the hesitancy that's out there

0:16:17.800 --> 0:16:20.480
<v Speaker 6>around you know, whether people feel like they need a

0:16:20.520 --> 0:16:21.480
<v Speaker 6>COVID vaccine or not.

0:16:21.720 --> 0:16:23.720
<v Speaker 2>Okay, now you mentioned some of these, but let's kind

0:16:23.720 --> 0:16:25.200
<v Speaker 2>of break it down a little bit talk about the

0:16:25.200 --> 0:16:29.360
<v Speaker 2>other vaccines in development. Let's start with Moderna's RSV vaccine.

0:16:29.560 --> 0:16:32.640
<v Speaker 6>Yeah, so that vaccine, you know, it's a good product.

0:16:32.840 --> 0:16:35.240
<v Speaker 6>It's a year behind. This is their problem. It's a

0:16:35.320 --> 0:16:39.880
<v Speaker 6>year behind vaccines that recently became available from Pfizer and

0:16:39.920 --> 0:16:43.600
<v Speaker 6>Glaxo Smith Cleent. So you know, I think, you know,

0:16:43.640 --> 0:16:46.040
<v Speaker 6>they need to play catch up. What they're trying to

0:16:46.080 --> 0:16:49.360
<v Speaker 6>sell is being differentiated is that they're offering the vaccine

0:16:49.440 --> 0:16:52.200
<v Speaker 6>in a pre loaded pen, so the other two products

0:16:52.240 --> 0:16:54.880
<v Speaker 6>come into vile and the pharmacist has to mix it.

0:16:54.960 --> 0:16:58.920
<v Speaker 6>And they're arguing like, well, in a busy pharmacy environment

0:16:58.960 --> 0:17:02.160
<v Speaker 6>where we know everybody you know is experiencing shortages of

0:17:02.360 --> 0:17:05.879
<v Speaker 6>you know, healthcare workers, having this pre loaded pen is

0:17:05.920 --> 0:17:09.600
<v Speaker 6>going to be attractive. Their flu vaccine, you know, had

0:17:09.600 --> 0:17:12.840
<v Speaker 6>been struggling a little bit. They came out this was

0:17:12.880 --> 0:17:14.639
<v Speaker 6>the other big news. They came out with you know,

0:17:15.160 --> 0:17:19.880
<v Speaker 6>good phase three data on that last week. The question is,

0:17:20.240 --> 0:17:22.880
<v Speaker 6>you know, the side effect profile. All of us who've

0:17:22.920 --> 0:17:25.560
<v Speaker 6>gotten a COVID shop you know, an mRNA shot know

0:17:25.640 --> 0:17:28.399
<v Speaker 6>that the side effects can be a little rough. You know,

0:17:28.520 --> 0:17:31.640
<v Speaker 6>Will people decide that something that's as good as what's

0:17:31.680 --> 0:17:33.679
<v Speaker 6>there is enough? And I think what they need to

0:17:33.720 --> 0:17:36.119
<v Speaker 6>prove is that what they have is something better like that,

0:17:36.320 --> 0:17:39.640
<v Speaker 6>you know, it does better, performs better than the other

0:17:40.160 --> 0:17:42.120
<v Speaker 6>flu vaccines that are out there right now, we only

0:17:42.160 --> 0:17:44.720
<v Speaker 6>have antibody data on that, but having some actual like

0:17:44.920 --> 0:17:47.680
<v Speaker 6>outcomes data, you know, do people do more people live?

0:17:48.520 --> 0:17:50.439
<v Speaker 6>You know, do fewer people get the flu? Or have

0:17:50.480 --> 0:17:52.680
<v Speaker 6>a severe case that would be really helpful for them.

0:17:53.160 --> 0:17:55.439
<v Speaker 6>And then they have this vaccine that they're working on

0:17:55.480 --> 0:17:58.639
<v Speaker 6>where they're going to combine covid in the flu. That

0:17:58.760 --> 0:18:02.280
<v Speaker 6>vaccine incorporates a next generation covid vaccine they've been working

0:18:02.320 --> 0:18:05.520
<v Speaker 6>on that they hope, well, they'll be able to give

0:18:05.520 --> 0:18:08.240
<v Speaker 6>people a smaller dose of and it'll work better than

0:18:08.280 --> 0:18:11.040
<v Speaker 6>what we have now. So you know, again, I think

0:18:11.080 --> 0:18:13.679
<v Speaker 6>the question is what does demand look like in a

0:18:13.760 --> 0:18:15.760
<v Speaker 6>year or two or three years, because we don't really

0:18:15.800 --> 0:18:18.159
<v Speaker 6>know how the pandemic or you know, the kind of

0:18:18.240 --> 0:18:22.480
<v Speaker 6>virus will start to you know, affect people if in

0:18:22.560 --> 0:18:25.199
<v Speaker 6>coming years. So those are their main products. And then,

0:18:25.240 --> 0:18:27.560
<v Speaker 6>as I mentioned, this cancer vaccine is the other one

0:18:27.640 --> 0:18:29.160
<v Speaker 6>that everyone's really excited about.

0:18:29.680 --> 0:18:31.840
<v Speaker 2>Yeah, and what about those ambitions? I mean, what does

0:18:31.880 --> 0:18:34.720
<v Speaker 2>the CEO say it's going to take to get FDA approval?

0:18:35.000 --> 0:18:37.560
<v Speaker 6>This has been the question on investors' mind. I mean

0:18:38.160 --> 0:18:41.760
<v Speaker 6>so many people have been just clamoring for information. When

0:18:41.800 --> 0:18:44.000
<v Speaker 6>are they going to file for approval? I think they

0:18:44.040 --> 0:18:46.119
<v Speaker 6>had really good data that came out on this cancer

0:18:46.240 --> 0:18:51.720
<v Speaker 6>vaccine showing that it could reduce the risk of skin

0:18:51.840 --> 0:18:54.800
<v Speaker 6>cancer as certain kind of skin cancer from returning or

0:18:54.800 --> 0:18:57.520
<v Speaker 6>from people dying by forty four percent, you know, and

0:18:57.560 --> 0:19:00.000
<v Speaker 6>so a lot of investors think, well, that should be

0:19:00.080 --> 0:19:03.359
<v Speaker 6>enough for you to file for approval. The CEO, you know,

0:19:03.520 --> 0:19:06.200
<v Speaker 6>says three things need to happen, you know. One, they

0:19:06.240 --> 0:19:09.359
<v Speaker 6>have to start a phase retrial, which they've done, you know. Two,

0:19:09.640 --> 0:19:11.760
<v Speaker 6>they are going to have some data later this year

0:19:12.280 --> 0:19:15.560
<v Speaker 6>that will kind of show over a longer time horizon

0:19:15.960 --> 0:19:18.360
<v Speaker 6>whether those numbers hold up or if maybe they even

0:19:18.400 --> 0:19:20.919
<v Speaker 6>get a little better in terms of how well that

0:19:21.000 --> 0:19:25.600
<v Speaker 6>vaccine performs. And then three, these are highly personalized products.

0:19:25.960 --> 0:19:29.159
<v Speaker 6>They take, They use of patient's own tumor cells to

0:19:29.640 --> 0:19:32.720
<v Speaker 6>create the vaccine, and so that's very complicated from a

0:19:32.760 --> 0:19:35.280
<v Speaker 6>manufacturing perspective, and they're trying to get all of that

0:19:35.359 --> 0:19:39.600
<v Speaker 6>in place because I do think legitimately his pushback on

0:19:39.960 --> 0:19:42.080
<v Speaker 6>filing for approval now is like, well, we could do that,

0:19:42.080 --> 0:19:44.360
<v Speaker 6>but we couldn't actually treat everybody who's going to want

0:19:44.640 --> 0:19:45.520
<v Speaker 6>the product.

0:19:45.640 --> 0:19:47.639
<v Speaker 2>Right, And the company recently said it's well on the

0:19:47.640 --> 0:19:51.520
<v Speaker 2>way to becoming a big biotech contender. What's your take.

0:19:51.520 --> 0:19:54.920
<v Speaker 6>If they can move their technology a little beyond where

0:19:54.920 --> 0:19:58.160
<v Speaker 6>COVID was. I mean, they showed that mRNA works, if

0:19:58.200 --> 0:20:01.560
<v Speaker 6>they can show works as a therapeutic, if this cancer vaccine,

0:20:01.840 --> 0:20:04.800
<v Speaker 6>you know, continues to progress in the way we'd like

0:20:04.840 --> 0:20:07.679
<v Speaker 6>to see it progress and help people. That will you know,

0:20:07.760 --> 0:20:11.240
<v Speaker 6>certainly show that it's not just like as good as

0:20:11.240 --> 0:20:13.760
<v Speaker 6>the existing technology that's out there, and that it could

0:20:13.760 --> 0:20:16.560
<v Speaker 6>be really transformative. But you know, they've got some work

0:20:16.600 --> 0:20:19.760
<v Speaker 6>on that. We have to be patient and see what happened.

0:20:19.880 --> 0:20:23.919
<v Speaker 2>Bloomberg Opinion columnist Lisa Jarvis there. The Federal Reserve was

0:20:23.960 --> 0:20:26.960
<v Speaker 2>in focus this week when FED Chair J Powell held

0:20:27.040 --> 0:20:30.520
<v Speaker 2>rates unchanged but signaled they'll be higher for longer.

0:20:30.600 --> 0:20:33.560
<v Speaker 5>We're prepared to raise rates further if appropriate, and we

0:20:33.600 --> 0:20:36.280
<v Speaker 5>intend to hold policy at a restrictive level until we're

0:20:36.320 --> 0:20:40.520
<v Speaker 5>confident that inflation is moving down sustainably toward our objective.

0:20:40.680 --> 0:20:43.960
<v Speaker 2>In addition to bringing down inflation, he clearly laid out

0:20:44.000 --> 0:20:45.600
<v Speaker 2>the Fed's objective.

0:20:45.240 --> 0:20:47.439
<v Speaker 5>Soft lending is a primary objective, and I did not

0:20:47.520 --> 0:20:48.200
<v Speaker 5>say otherwise.

0:20:49.240 --> 0:20:51.439
<v Speaker 6>I mean, that's that's what we've been trying to achieve.

0:20:51.520 --> 0:20:55.000
<v Speaker 2>Powell's had success in bringing down inflation this year, and

0:20:55.040 --> 0:20:58.000
<v Speaker 2>the stock markets had a strong twenty twenty three, but

0:20:58.119 --> 0:21:02.480
<v Speaker 2>many Americans are downbeat about the economy. Economist Claudia sam

0:21:02.680 --> 0:21:07.040
<v Speaker 2>joins us to explain why inflation rates falling back toward

0:21:07.119 --> 0:21:09.919
<v Speaker 2>more normal levels. We have the labor market, it's strong.

0:21:10.040 --> 0:21:12.520
<v Speaker 2>It sounds like a good reason to be optimistic about

0:21:12.520 --> 0:21:16.680
<v Speaker 2>the economy, right, But you're saying Americans are still gloomy.

0:21:16.760 --> 0:21:18.800
<v Speaker 2>This is what you put in your opinion piece. Now,

0:21:18.880 --> 0:21:21.960
<v Speaker 2>how bad is sentiment? Put it into perspective for us?

0:21:22.440 --> 0:21:25.760
<v Speaker 5>Well, first of all, it is absolutely appropriate and understandable

0:21:25.880 --> 0:21:27.080
<v Speaker 5>that people are gloomy.

0:21:27.280 --> 0:21:27.359
<v Speaker 4>Right.

0:21:27.440 --> 0:21:29.760
<v Speaker 5>Inflation is high. Yes, the labor market is good, but

0:21:29.800 --> 0:21:32.080
<v Speaker 5>inflation has been high and it's been high too long.

0:21:32.680 --> 0:21:36.160
<v Speaker 5>So then the question is in some of the measures

0:21:36.160 --> 0:21:39.199
<v Speaker 5>that we normally use to gauge overall sentiment across all

0:21:39.280 --> 0:21:43.320
<v Speaker 5>people across the country, these have been really low, like

0:21:43.480 --> 0:21:46.240
<v Speaker 5>lower than you would historically have happened, even if you

0:21:46.280 --> 0:21:48.800
<v Speaker 5>take inflation into account. Right, So this isn't saying people

0:21:48.840 --> 0:21:51.680
<v Speaker 5>are overreacting to inflation. It's just saying their reaction to inflation.

0:21:52.480 --> 0:21:56.800
<v Speaker 5>And then there's more And what's particularly notable about this,

0:21:56.920 --> 0:21:59.280
<v Speaker 5>I mean these are these sentiment go back to the

0:21:59.440 --> 0:22:01.680
<v Speaker 5>nineteen four eight right, So this is a long period

0:22:01.720 --> 0:22:04.439
<v Speaker 5>of time to watch how people. Their views about the

0:22:04.480 --> 0:22:08.679
<v Speaker 5>economy change over time. And what's notable and what I

0:22:08.720 --> 0:22:12.080
<v Speaker 5>write about is the fact that this gap, this unexpected

0:22:12.240 --> 0:22:15.720
<v Speaker 5>gloom extra gloom, it showed up about the same time

0:22:15.760 --> 0:22:18.399
<v Speaker 5>the pandemic did. So we've had this for multiple years

0:22:18.440 --> 0:22:21.080
<v Speaker 5>now and we haven't made up that lost ground.

0:22:22.040 --> 0:22:25.520
<v Speaker 2>Now. Dig into these consumer confidence surveys that we hear about.

0:22:25.760 --> 0:22:26.919
<v Speaker 2>What do they ask people.

0:22:27.880 --> 0:22:30.080
<v Speaker 5>There's a few different surveys, and they ask you know,

0:22:30.480 --> 0:22:32.800
<v Speaker 5>the questions very a little bit, but in general they're

0:22:32.840 --> 0:22:36.159
<v Speaker 5>asking people, how are you doing? Often the survey that

0:22:36.200 --> 0:22:38.040
<v Speaker 5>I look at comes out of the University of Michigan's

0:22:38.040 --> 0:22:39.920
<v Speaker 5>it's like, how are you doing relative to a year ago?

0:22:40.040 --> 0:22:42.600
<v Speaker 5>Is it a good time to go buy? And then

0:22:42.840 --> 0:22:46.239
<v Speaker 5>forward looking questions, how are your finances going to do

0:22:46.280 --> 0:22:49.000
<v Speaker 5>in the next year, get better, get worse? And then

0:22:49.040 --> 0:22:51.240
<v Speaker 5>how do you think more the economy as a whole,

0:22:51.320 --> 0:22:53.520
<v Speaker 5>how businesses are going to do in the next year,

0:22:53.560 --> 0:22:56.800
<v Speaker 5>the next five years. So it's it's a wide range

0:22:56.800 --> 0:23:01.320
<v Speaker 5>of views about the economy and and not surprisingly, every

0:23:01.320 --> 0:23:04.960
<v Speaker 5>single one of these measures plummeted in the COVID recession.

0:23:05.640 --> 0:23:08.480
<v Speaker 5>That's what they do in recessions. What has happened is

0:23:08.520 --> 0:23:12.000
<v Speaker 5>though they have recovered as economic conditions have improved, Inflation

0:23:12.119 --> 0:23:15.440
<v Speaker 5>is coming down, the labor market has been good, there's

0:23:15.480 --> 0:23:19.760
<v Speaker 5>still this gap and it's one that going back decades

0:23:19.760 --> 0:23:22.800
<v Speaker 5>and decades, we don't we don't see this right. And

0:23:22.880 --> 0:23:25.760
<v Speaker 5>so that's where it raises the question of and And

0:23:25.800 --> 0:23:28.760
<v Speaker 5>to me, what's important as an when I do my

0:23:28.920 --> 0:23:31.200
<v Speaker 5>work as an economist is not to say, oh, well

0:23:31.240 --> 0:23:33.920
<v Speaker 5>you people cheer up. It's to figure out, well, what

0:23:34.119 --> 0:23:38.560
<v Speaker 5>is I havep heer to do that that you try

0:23:38.560 --> 0:23:40.400
<v Speaker 5>to here out what are people trying to tell us?

0:23:40.680 --> 0:23:43.000
<v Speaker 5>Because when you have a pattern that's so at odds

0:23:43.000 --> 0:23:45.240
<v Speaker 5>with what you've seen in the past, there's a reason

0:23:45.800 --> 0:23:48.680
<v Speaker 5>there are lots of different possible explanations. So I don't

0:23:48.680 --> 0:23:51.000
<v Speaker 5>pretend that I know the answer. And yet I know,

0:23:51.119 --> 0:23:54.280
<v Speaker 5>having worked with these data for well over a decade

0:23:54.320 --> 0:23:57.600
<v Speaker 5>at the Federal Reserve, these can be very useful in

0:23:57.640 --> 0:23:59.040
<v Speaker 5>helping us gauge the economy.

0:23:59.240 --> 0:24:02.160
<v Speaker 2>All right, so let's dig into why this sentiment has

0:24:02.200 --> 0:24:04.920
<v Speaker 2>really failed to rebound. Now, you say, the less talked

0:24:04.960 --> 0:24:08.720
<v Speaker 2>about but more likely explanation is COVID.

0:24:09.800 --> 0:24:14.080
<v Speaker 5>The timing, first of all, is somewhat obvious on some level.

0:24:14.760 --> 0:24:18.000
<v Speaker 5>But when I say COVID, it's it's not just the

0:24:18.080 --> 0:24:21.560
<v Speaker 5>virus itself, people who passed away from the virus to

0:24:21.600 --> 0:24:24.640
<v Speaker 5>have long COVID. It's also thinking about the way our

0:24:24.880 --> 0:24:28.320
<v Speaker 5>daily life was upended, the way our institutions changed. And

0:24:28.520 --> 0:24:31.600
<v Speaker 5>at this point it's it's you know, no one wants

0:24:31.640 --> 0:24:35.240
<v Speaker 5>to remember back to March of twenty twenty, we shut

0:24:35.240 --> 0:24:38.480
<v Speaker 5>the US economy down. We sent everyone home. To a

0:24:38.560 --> 0:24:42.120
<v Speaker 5>large extent, that was a huge change in people's lives

0:24:42.200 --> 0:24:45.720
<v Speaker 5>and a huge change in how in their livelihoods. And

0:24:46.200 --> 0:24:51.280
<v Speaker 5>one thing that I argue in the is that you know,

0:24:51.320 --> 0:24:54.240
<v Speaker 5>we're just now seeing the you know, the supply chains

0:24:54.440 --> 0:24:56.720
<v Speaker 5>start to get back on track, right like, And these

0:24:56.760 --> 0:24:59.040
<v Speaker 5>were also very disrupted in twenty twenty we are in

0:24:59.040 --> 0:25:02.719
<v Speaker 5>twenty twenty three, but they're just kind of get people

0:25:02.920 --> 0:25:06.400
<v Speaker 5>take a long time to get back on track too, right.

0:25:06.440 --> 0:25:09.240
<v Speaker 5>So the idea that we still have something that we're

0:25:09.240 --> 0:25:11.440
<v Speaker 5>holding with us, even if it's not on our mind

0:25:11.560 --> 0:25:15.240
<v Speaker 5>every day, that's really impacted our lives, to me, that's

0:25:15.280 --> 0:25:20.000
<v Speaker 5>a very plausible explanation that we're just carrying along extra

0:25:21.440 --> 0:25:24.600
<v Speaker 5>effects of the pandemic. And there were some places in

0:25:24.640 --> 0:25:28.320
<v Speaker 5>the same survey where we like income expectations, I mean

0:25:28.359 --> 0:25:31.400
<v Speaker 5>not in this main measure that showed some after effects

0:25:31.440 --> 0:25:34.080
<v Speaker 5>of the Great Recession for a few years and then

0:25:34.119 --> 0:25:36.800
<v Speaker 5>it popped back up. So this big events can have

0:25:37.400 --> 0:25:40.879
<v Speaker 5>effects like this. Of course, it's hard to prove that

0:25:41.000 --> 0:25:42.440
<v Speaker 5>definitively right.

0:25:42.520 --> 0:25:45.399
<v Speaker 2>And then there's also politics can play a role in this.

0:25:45.480 --> 0:25:47.200
<v Speaker 2>I mean, we're coming up on an election year.

0:25:48.040 --> 0:25:53.520
<v Speaker 5>One of the fascinating and maybe not surprising aspects in

0:25:53.560 --> 0:25:57.080
<v Speaker 5>the survey they have for some time now, not all

0:25:57.080 --> 0:25:59.520
<v Speaker 5>the way back, but for some time ask people about

0:25:59.520 --> 0:26:03.000
<v Speaker 5>their political affiliation, and what you can see in the

0:26:03.119 --> 0:26:07.120
<v Speaker 5>data are these views about the economy, owned finances future.

0:26:08.080 --> 0:26:13.840
<v Speaker 5>They are very much tied with is the is your

0:26:13.920 --> 0:26:17.720
<v Speaker 5>party in the White House? And then when you'll see

0:26:17.720 --> 0:26:21.360
<v Speaker 5>this big divide right now, you know Democrats are much

0:26:21.400 --> 0:26:24.120
<v Speaker 5>more upbeat about you know, they have much higher sentiment

0:26:24.160 --> 0:26:28.760
<v Speaker 5>than Republicans, but under President Trump that was reversed and

0:26:28.800 --> 0:26:32.320
<v Speaker 5>in the last two election cycles, these are big gaps

0:26:32.640 --> 0:26:35.640
<v Speaker 5>now for the overall sentiment. That's what I'm looking at,

0:26:35.680 --> 0:26:38.199
<v Speaker 5>and I argue why this is unlikely to be an

0:26:38.200 --> 0:26:42.560
<v Speaker 5>explanation is they're about the same size and magnitude. They're

0:26:42.600 --> 0:26:46.200
<v Speaker 5>just flipping around and the split in the population is

0:26:46.240 --> 0:26:50.520
<v Speaker 5>pretty similar. So it's unlikely to tell us why we

0:26:50.560 --> 0:26:53.600
<v Speaker 5>have this extra gap. Now, it is informative in thinking

0:26:53.600 --> 0:26:57.560
<v Speaker 5>about how divergent the views are that we have at

0:26:57.560 --> 0:26:59.960
<v Speaker 5>any one point in time about the economy.

0:27:00.920 --> 0:27:03.400
<v Speaker 2>Right and then on top of that, we have negative

0:27:03.560 --> 0:27:06.199
<v Speaker 2>economic news story the things people here, you know, as

0:27:06.480 --> 0:27:10.080
<v Speaker 2>they're listening and watching TV and doing all that. What

0:27:10.280 --> 0:27:13.119
<v Speaker 2>seems that actually seems to be reversing a little bit,

0:27:13.160 --> 0:27:14.119
<v Speaker 2>but it still has an impact.

0:27:14.160 --> 0:27:16.800
<v Speaker 5>Correct the survey, and I think this is really helpful.

0:27:17.000 --> 0:27:19.280
<v Speaker 5>You can do a lot of let's measure the media,

0:27:19.400 --> 0:27:22.160
<v Speaker 5>let's put it on some kind of positive negative scale,

0:27:22.600 --> 0:27:25.359
<v Speaker 5>and yet you don't really like what are people listening to?

0:27:25.760 --> 0:27:25.920
<v Speaker 1>Right?

0:27:25.960 --> 0:27:28.760
<v Speaker 5>Like that That's where what kind of gets in gets

0:27:28.760 --> 0:27:33.000
<v Speaker 5>in the head. So the survey ask people about the economy,

0:27:33.040 --> 0:27:36.760
<v Speaker 5>what economic news have you heard lately? And they will

0:27:36.960 --> 0:27:39.680
<v Speaker 5>is this positive? Is this negative? They ask about specifically

0:27:39.680 --> 0:27:45.960
<v Speaker 5>what is this and it again, just like with sentiment overall,

0:27:46.000 --> 0:27:48.760
<v Speaker 5>we would expect it to be negative, you know, more

0:27:48.800 --> 0:27:51.920
<v Speaker 5>negative than before COVID, just because inflation is high and

0:27:51.960 --> 0:27:54.360
<v Speaker 5>there are problems in the economy that weren't with us

0:27:54.400 --> 0:28:01.680
<v Speaker 5>before COVID, but the news media, this balance between positive

0:28:01.680 --> 0:28:06.480
<v Speaker 5>news and negative news has rebounded more. It's not back

0:28:06.520 --> 0:28:09.480
<v Speaker 5>to before COVID levels, and it's also moved a lot

0:28:09.520 --> 0:28:14.800
<v Speaker 5>more with the economic conditions. So it's a little harder

0:28:14.800 --> 0:28:16.399
<v Speaker 5>to gauge with this one. But when you look at

0:28:16.400 --> 0:28:20.719
<v Speaker 5>these responses from households about what they're hearing, it doesn't

0:28:20.760 --> 0:28:22.680
<v Speaker 5>line up in the same way as when you ask

0:28:22.760 --> 0:28:25.240
<v Speaker 5>them what do you think about the economy in terms

0:28:25.280 --> 0:28:27.719
<v Speaker 5>of the gloominess. So there could be a piece of it,

0:28:27.800 --> 0:28:32.040
<v Speaker 5>but it's not. It's not that it noted like, there's

0:28:32.119 --> 0:28:34.560
<v Speaker 5>not a sign of a clear bias in what people

0:28:34.640 --> 0:28:37.520
<v Speaker 5>say they have heard. That's setting aside what's out there

0:28:37.520 --> 0:28:38.200
<v Speaker 5>in the news.

0:28:38.760 --> 0:28:41.200
<v Speaker 2>Got it now? Based on all that we've talked about,

0:28:41.640 --> 0:28:42.960
<v Speaker 2>Is the data still useful?

0:28:43.880 --> 0:28:49.880
<v Speaker 5>Yes, we have to There are many relationships that in

0:28:49.960 --> 0:28:51.920
<v Speaker 5>terms of the economy, in terms of the kind of

0:28:52.000 --> 0:28:55.640
<v Speaker 5>data that economists look to, that have broken down in

0:28:55.680 --> 0:28:59.200
<v Speaker 5>this pandemic. So sentiment does not stand out in that regard.

0:29:00.240 --> 0:29:04.560
<v Speaker 5>I there is an argument that has been made that's like, well,

0:29:04.600 --> 0:29:06.840
<v Speaker 5>if you look, you know, we ask people and they're

0:29:06.920 --> 0:29:10.200
<v Speaker 5>very gloomy, But if you look at consumers, they're spending,

0:29:10.240 --> 0:29:12.280
<v Speaker 5>they're out there, and we should just look at their behavior,

0:29:12.840 --> 0:29:15.840
<v Speaker 5>and you know, who knows why they're saying what they're saying.

0:29:16.200 --> 0:29:19.160
<v Speaker 5>I disagree with that. I think, you know, again, people

0:29:19.160 --> 0:29:22.320
<v Speaker 5>can tell us something that the regular data can't, and

0:29:22.680 --> 0:29:24.800
<v Speaker 5>we don't have complete data on what they're spending and

0:29:24.840 --> 0:29:26.960
<v Speaker 5>all of that. So I think there's an important trying

0:29:27.000 --> 0:29:28.840
<v Speaker 5>to figure out what people are telling us. And it

0:29:28.880 --> 0:29:31.240
<v Speaker 5>has been the case in the past, and this is

0:29:31.480 --> 0:29:34.920
<v Speaker 5>difficult given the break in the series or how the

0:29:35.000 --> 0:29:37.200
<v Speaker 5>data has been acting. But the sentiment data in the

0:29:37.240 --> 0:29:39.960
<v Speaker 5>past have been helpful in seeing a little bit around

0:29:40.000 --> 0:29:43.640
<v Speaker 5>the corner in terms of a recession coming or a contraction,

0:29:43.920 --> 0:29:47.600
<v Speaker 5>so potentially we can still get some signs from that.

0:29:48.000 --> 0:29:51.440
<v Speaker 2>Claudia Sam thanks for joining us. Coming up why most

0:29:51.480 --> 0:29:55.160
<v Speaker 2>corn grown doesn't end up on our plates. Bloomberg's Laura

0:29:55.160 --> 0:29:58.520
<v Speaker 2>Williams has a look into farming's climate friendly future. And

0:29:58.600 --> 0:30:01.360
<v Speaker 2>don't forget We're available at It's a podcast on Apple,

0:30:01.440 --> 0:30:06.320
<v Speaker 2>Spotify or your favorite podcast platform. This is Bloomberg Opinion.

0:30:13.920 --> 0:30:17.760
<v Speaker 1>You're listening to the Bloomberg Opinion podcast. Count us Saturdays

0:30:17.760 --> 0:30:20.920
<v Speaker 1>at one and seven pm. Eastern on Bloomberg dot Com,

0:30:21.000 --> 0:30:24.080
<v Speaker 1>the iHeartRadio app and the Bloomberg Business app, or listen

0:30:24.160 --> 0:30:26.400
<v Speaker 1>on demand wherever you get your podcasts.

0:30:28.360 --> 0:30:32.280
<v Speaker 2>You're listening to Bloomberg Opinion. I'm Lisa Matteo. What lies

0:30:32.280 --> 0:30:36.240
<v Speaker 2>ahead for the future of farming Bloomberg Opinions. Lara Williams

0:30:36.320 --> 0:30:38.720
<v Speaker 2>joined in to talk about a problem with our global

0:30:38.800 --> 0:30:41.720
<v Speaker 2>food systems. Lara, thank you for joining me. You start

0:30:41.720 --> 0:30:45.080
<v Speaker 2>off your Bloomberg Opinion piece about farming's climate friendly future

0:30:45.520 --> 0:30:47.959
<v Speaker 2>by really setting the scene. Now, you say how our

0:30:48.000 --> 0:30:52.640
<v Speaker 2>global food systems have become incredibly dysfunctional. What exactly do

0:30:52.680 --> 0:30:53.200
<v Speaker 2>you mean by that?

0:30:53.760 --> 0:30:57.800
<v Speaker 4>So what I mean is that's loads of really healthy produce.

0:30:58.120 --> 0:31:01.360
<v Speaker 4>Is that saying diverted away from people plates? So if

0:31:01.360 --> 0:31:06.120
<v Speaker 4>you imagine a big American corn field, I naively thought

0:31:06.200 --> 0:31:08.680
<v Speaker 4>that lots of that food would end up on people's plates,

0:31:08.840 --> 0:31:12.400
<v Speaker 4>but actually thirty nine percent ends up being fed to livestock,

0:31:12.880 --> 0:31:17.520
<v Speaker 4>thirty seven percent is used to produce ethanol for fuel,

0:31:17.880 --> 0:31:21.440
<v Speaker 4>fourteen percent is exported, and then it's just ten percent

0:31:22.160 --> 0:31:24.120
<v Speaker 4>of the porn which is eaten. And then half of

0:31:24.160 --> 0:31:28.000
<v Speaker 4>that is a sweetener, so like highst corn syrup. So

0:31:28.240 --> 0:31:31.840
<v Speaker 4>that's not a healthy way of eating. And it's also

0:31:31.960 --> 0:31:34.880
<v Speaker 4>so this isn't this isn't working for us. More than

0:31:34.920 --> 0:31:38.840
<v Speaker 4>eight hundred and twenty million people lack sufficient food. Unhealthy

0:31:38.880 --> 0:31:42.000
<v Speaker 4>diets now pose a greater risk of morbidity and mortality

0:31:42.040 --> 0:31:46.520
<v Speaker 4>than unsafe sets, alcohol, dread, and tobacco used combined. So

0:31:46.560 --> 0:31:48.120
<v Speaker 4>it's not good for human health, but it's also not

0:31:48.160 --> 0:31:51.840
<v Speaker 4>good for the for the planet. Food production contributes about

0:31:51.840 --> 0:31:55.240
<v Speaker 4>a third of global greenhouse gas emissions. It's the way

0:31:55.320 --> 0:31:59.040
<v Speaker 4>that we use pesticides and fertilizer and change the use

0:31:59.040 --> 0:32:03.640
<v Speaker 4>of the lands of facilitated tatastrophic declines and biodiversity. It

0:32:03.960 --> 0:32:07.640
<v Speaker 4>really draws on fresh water, like use the seventy percent

0:32:07.640 --> 0:32:11.800
<v Speaker 4>of the fresh waters available worldwide. And you know, as

0:32:11.880 --> 0:32:14.680
<v Speaker 4>the global population grows, it just at the moment seems

0:32:14.760 --> 0:32:16.480
<v Speaker 4>like it's only going to get worse.

0:32:16.720 --> 0:32:19.080
<v Speaker 2>So let's dig into this new study was published in

0:32:19.080 --> 0:32:22.400
<v Speaker 2>the scientific journal plast Climate. Now, this looks into several

0:32:22.440 --> 0:32:25.600
<v Speaker 2>elements that can combine to help reduce emissions, diet shift,

0:32:25.800 --> 0:32:28.480
<v Speaker 2>waste reduction, those are really a big focus of this.

0:32:29.000 --> 0:32:31.200
<v Speaker 4>Yeah, exactly, And so I think the important thing to

0:32:31.240 --> 0:32:34.080
<v Speaker 4>take away from this is the study was really about

0:32:34.120 --> 0:32:37.719
<v Speaker 4>how to pull all the levers. We have to create

0:32:37.760 --> 0:32:41.360
<v Speaker 4>something that works much better. And actually, you know, food

0:32:41.400 --> 0:32:43.920
<v Speaker 4>production is one of the only industries where we get

0:32:43.960 --> 0:32:48.280
<v Speaker 4>to negative emission, so it's drawing down more carbon dioxide

0:32:48.280 --> 0:32:50.840
<v Speaker 4>than it's emitting into the atmosphere, and that's a that

0:32:50.880 --> 0:32:53.680
<v Speaker 4>could be a really really powerful thing moving forward, and

0:32:53.800 --> 0:32:58.400
<v Speaker 4>you know, helping offset other polluting industries and kind of

0:32:58.480 --> 0:33:00.680
<v Speaker 4>you know, cleaning up the mess that we made up there.

0:33:00.800 --> 0:33:04.520
<v Speaker 2>Okay, there's the importance also production efficiency and technology to.

0:33:04.920 --> 0:33:07.440
<v Speaker 4>Yeah, so basically if you take a look at the

0:33:07.600 --> 0:33:11.440
<v Speaker 4>non tech interventions, and that's so that sunds like adopting

0:33:11.600 --> 0:33:15.600
<v Speaker 4>a healthier flexitarian diet where you eat mainly plant based

0:33:15.640 --> 0:33:18.720
<v Speaker 4>foods and you can have still a little meat and

0:33:18.840 --> 0:33:22.720
<v Speaker 4>reducing food waste. That actually half global food emissions. But

0:33:22.720 --> 0:33:26.120
<v Speaker 4>that'll be a massive progress. But it can't actually tat

0:33:26.200 --> 0:33:28.840
<v Speaker 4>used to net zero because if we're producing food, we're

0:33:28.840 --> 0:33:32.360
<v Speaker 4>producing emissions at the moment. So if we improve production

0:33:32.400 --> 0:33:37.080
<v Speaker 4>efficiency and so that is reducing the gap between what

0:33:37.320 --> 0:33:41.000
<v Speaker 4>agricultural areas can deliver and what's produced. If we close

0:33:41.040 --> 0:33:43.040
<v Speaker 4>that adapt all our fields are as productive as they

0:33:43.040 --> 0:33:46.600
<v Speaker 4>can be. Then also use these novel technologies, and so

0:33:46.680 --> 0:33:48.880
<v Speaker 4>that can be things like you know, helping reduce emissions.

0:33:48.920 --> 0:33:51.880
<v Speaker 4>Further By, there's food additives you can give to cows

0:33:51.960 --> 0:33:57.280
<v Speaker 4>to stop them burpinged up methane. There's also technology to

0:33:57.480 --> 0:34:02.320
<v Speaker 4>use to help farmland absorb AMOSPHERICIO two. And if you

0:34:02.440 --> 0:34:05.200
<v Speaker 4>use all four of these things together, you can reach

0:34:05.640 --> 0:34:10.200
<v Speaker 4>negative emissions. But the trick is the second to using

0:34:10.200 --> 0:34:12.759
<v Speaker 4>those novel technologies will really help us take it to

0:34:12.800 --> 0:34:14.760
<v Speaker 4>the negative and net zero zone.

0:34:14.960 --> 0:34:17.680
<v Speaker 2>Easier said than done. What challenges still exist for this?

0:34:18.000 --> 0:34:21.719
<v Speaker 4>One important factor is that lots of these novel technologies

0:34:21.760 --> 0:34:23.920
<v Speaker 4>are novel, they're really new, and so there's lots of

0:34:24.080 --> 0:34:26.279
<v Speaker 4>knowledge aapps we need to address. We need to know

0:34:26.560 --> 0:34:28.839
<v Speaker 4>about how much these things are doing a cost, We

0:34:28.880 --> 0:34:31.080
<v Speaker 4>need to know if they work at the huge scale

0:34:31.080 --> 0:34:33.640
<v Speaker 4>that they'll need to. There's also obviously going to be

0:34:33.719 --> 0:34:37.520
<v Speaker 4>you know, challenges in actually even you know, convincing Pete

0:34:37.560 --> 0:34:40.759
<v Speaker 4>enough people to adopt more flagetarian diet, because there's lots

0:34:40.760 --> 0:34:45.000
<v Speaker 4>of personal and cultural reasons behind diet choices people make.

0:34:45.480 --> 0:34:48.359
<v Speaker 4>There's challenges in every kind of zone, which is why

0:34:48.400 --> 0:34:50.759
<v Speaker 4>we kind of need to use each of the four

0:34:50.880 --> 0:34:53.720
<v Speaker 4>kind of methods to remove carbon from the food production,

0:34:53.880 --> 0:34:56.400
<v Speaker 4>because we'll get the match benefits without putting all our

0:34:56.520 --> 0:34:57.960
<v Speaker 4>edits in one bastiff.

0:34:57.600 --> 0:35:01.160
<v Speaker 2>Bloomberg Opinion, Lara Williams, there does it. For this week's Opinion,

0:35:01.280 --> 0:35:04.480
<v Speaker 2>we're produced by Eric Molow. Stay with us. Today's top

0:35:04.520 --> 0:35:08.160
<v Speaker 2>stories and global business headlines are coming up right now.