1 00:00:03,680 --> 00:00:07,120 Speaker 1: Hello, and welcome to the Bloomberg Benchmarks podcast. This is 2 00:00:07,160 --> 00:00:09,920 Speaker 1: your host Tory so Well, and I'm an economics reporter 3 00:00:10,080 --> 00:00:13,720 Speaker 1: here in our Washington bureau at Bloomberg News. Right next 4 00:00:13,720 --> 00:00:17,440 Speaker 1: to me is your other host, Dan Moss. Hey, Dan, Hi, Tory, 5 00:00:17,960 --> 00:00:21,960 Speaker 1: I'm the executive editor full Global Economics at Bloomberg. Hey 6 00:00:22,040 --> 00:00:24,279 Speaker 1: with you and d C. That's right. What that basically 7 00:00:24,320 --> 00:00:28,240 Speaker 1: means is he's my boss's boss's boss. But in this 8 00:00:28,360 --> 00:00:31,840 Speaker 1: studio we are equals as co hosts, So we're here 9 00:00:31,840 --> 00:00:34,640 Speaker 1: to talk to you about what exactly we're doing here. 10 00:00:34,920 --> 00:00:36,960 Speaker 1: We sat down one day and and really wanted to 11 00:00:36,960 --> 00:00:40,280 Speaker 1: figure out a way to make economics more relevant to 12 00:00:40,560 --> 00:00:43,080 Speaker 1: everyday people. You know, right now at teams like a 13 00:00:43,120 --> 00:00:46,640 Speaker 1: lot of formulas and equations, and just the word economy 14 00:00:46,720 --> 00:00:49,680 Speaker 1: can make a lot of people's eyes glaze over. We 15 00:00:49,760 --> 00:00:52,479 Speaker 1: would love to bring economics to you guys in a 16 00:00:52,520 --> 00:00:55,680 Speaker 1: more accessible, digestible way and in a fun way that 17 00:00:55,720 --> 00:00:58,720 Speaker 1: won't put you to sleep, right Dan, Not a show 18 00:00:58,960 --> 00:01:03,120 Speaker 1: about statistics, and we're not going to pretend that we 19 00:01:03,200 --> 00:01:06,800 Speaker 1: can fool everyone by clouding it with acronyms. F O, 20 00:01:06,920 --> 00:01:10,160 Speaker 1: m Z, d RP and CDs is we're not going 21 00:01:10,200 --> 00:01:12,520 Speaker 1: to go into all that. We're going to translate for 22 00:01:12,560 --> 00:01:14,679 Speaker 1: you in a way that's interesting, in a way that 23 00:01:14,720 --> 00:01:17,720 Speaker 1: you can probably use in your everyday life, things like 24 00:01:18,040 --> 00:01:21,000 Speaker 1: what are your job prospects looking like, how long will 25 00:01:21,040 --> 00:01:23,960 Speaker 1: it take for that job interview to translate into an 26 00:01:24,000 --> 00:01:27,120 Speaker 1: actual position, how long is it going to take for 27 00:01:27,160 --> 00:01:29,920 Speaker 1: you to see your paycheck increase? All these things economists 28 00:01:29,920 --> 00:01:32,240 Speaker 1: are working on day in and day out, and we 29 00:01:32,280 --> 00:01:34,560 Speaker 1: can provide a little bit of insight on that that 30 00:01:34,680 --> 00:01:37,320 Speaker 1: might help answer some of those questions. We want to 31 00:01:37,440 --> 00:01:40,840 Speaker 1: make economics accessible and really make it relevant to people's 32 00:01:40,840 --> 00:01:43,360 Speaker 1: everyday lives, because it is. What we're trying to convey 33 00:01:43,520 --> 00:01:46,679 Speaker 1: is every day people like you and me are making 34 00:01:46,720 --> 00:01:50,880 Speaker 1: decisions about whether to buy something, what to buy, how 35 00:01:50,960 --> 00:01:53,680 Speaker 1: much do we pay for it, whether to borrow for it, 36 00:01:54,040 --> 00:01:57,880 Speaker 1: and companies and governments around the world are making exactly 37 00:01:58,080 --> 00:02:00,880 Speaker 1: the same decisions each time. We're trying to get under 38 00:02:00,880 --> 00:02:05,040 Speaker 1: the hood here. This is a living, breathing thing. We 39 00:02:05,080 --> 00:02:07,320 Speaker 1: want to bring only the most important trends, you know, 40 00:02:07,520 --> 00:02:11,119 Speaker 1: grounded in great data, and hope that you'll find it interesting, 41 00:02:11,600 --> 00:02:15,560 Speaker 1: grounded in data, not defined by the data exactly so 42 00:02:15,639 --> 00:02:19,000 Speaker 1: We'll be bringing to you topics such as labor force participation, 43 00:02:19,200 --> 00:02:21,520 Speaker 1: which has become a hot topic here in the US. 44 00:02:21,560 --> 00:02:23,880 Speaker 1: Of course, we will be talking about Greece, We'll be 45 00:02:23,919 --> 00:02:26,480 Speaker 1: talking about Japan. We'll be talking about all the major 46 00:02:26,520 --> 00:02:29,640 Speaker 1: economic stories. Will be bringing up little quirks in each 47 00:02:29,680 --> 00:02:33,200 Speaker 1: of them that you didn't know. We're so interesting. What's 48 00:02:33,240 --> 00:02:36,760 Speaker 1: going on with Japan's population, what is going on with 49 00:02:36,919 --> 00:02:40,320 Speaker 1: the housing industry in Australia. Gosh, I guess I'll never 50 00:02:40,320 --> 00:02:43,480 Speaker 1: be able to retire back home right at this rate. 51 00:02:44,320 --> 00:02:46,119 Speaker 1: And you know, one of the things that I've been 52 00:02:46,320 --> 00:02:49,560 Speaker 1: fortunate about here at Bloomberg is the opportunity to work 53 00:02:49,600 --> 00:02:52,200 Speaker 1: in a number of different bureaus and a number of continents. 54 00:02:52,600 --> 00:02:55,880 Speaker 1: I may bring stories to us that reflect interests and 55 00:02:55,919 --> 00:02:59,800 Speaker 1: trans I observed during my times in Malaysia, Japan, and 56 00:03:00,080 --> 00:03:02,600 Speaker 1: not a kingdom. We're here in d C, which has 57 00:03:02,639 --> 00:03:06,400 Speaker 1: this gravitational pool which we are determined to escape. Hectory 58 00:03:06,560 --> 00:03:10,720 Speaker 1: even to North Carolina, right, That's right, That's where I'm from. 59 00:03:10,720 --> 00:03:13,160 Speaker 1: And we'll also be bringing our colleagues from around the 60 00:03:13,200 --> 00:03:15,880 Speaker 1: world to help with this. Bloomberg News reporters who are 61 00:03:15,960 --> 00:03:20,720 Speaker 1: experts in their fields will be weaving in commentary from economists, researchers, 62 00:03:20,800 --> 00:03:23,320 Speaker 1: people who work at think tanks. Obviously, we've got a 63 00:03:23,320 --> 00:03:25,480 Speaker 1: time to talk about and we're really excited about sharing 64 00:03:25,480 --> 00:03:30,959 Speaker 1: it with you. This is Tori still Well. Thanks for 65 00:03:31,040 --> 00:03:33,440 Speaker 1: joining us, and you can follow me on Twitter at 66 00:03:33,480 --> 00:03:37,120 Speaker 1: at Tori Stillwell. I'm Dan Moss and on at Daniel 67 00:03:37,160 --> 00:03:39,200 Speaker 1: Moss d C. See you next time.