1 00:00:00,280 --> 00:00:02,599 Speaker 1: So down. Before we get started today, we just wanted 2 00:00:02,600 --> 00:00:05,320 Speaker 1: to take a moment to let everyone know about something 3 00:00:05,440 --> 00:00:07,400 Speaker 1: new from Bloomberg. Do you want to hear what it is? 4 00:00:07,680 --> 00:00:11,520 Speaker 1: Go for it? Well. Starting now, you can actually use 5 00:00:11,560 --> 00:00:15,320 Speaker 1: our Io s app or Bloomberg's Google Chrome extension to 6 00:00:15,480 --> 00:00:20,640 Speaker 1: scan any news story on any website, instantly revealing relevant 7 00:00:20,640 --> 00:00:24,280 Speaker 1: news and market data from Bloomberg and other sources related 8 00:00:24,320 --> 00:00:28,160 Speaker 1: to the companies and the people you're reading about. So really, 9 00:00:28,320 --> 00:00:30,680 Speaker 1: no matter where you're reading the news, you can bring 10 00:00:30,720 --> 00:00:33,680 Speaker 1: the power of Bloomberg's news and data with you. It's 11 00:00:33,720 --> 00:00:37,440 Speaker 1: pretty amazing. Download our Io s app or search for 12 00:00:37,440 --> 00:00:40,599 Speaker 1: the Bloomberg Extension on the Chrome Store to try it out. 13 00:00:41,240 --> 00:00:49,000 Speaker 1: Learn more at Bloomberg dot com. Backslash lands. On the surface, 14 00:00:49,000 --> 00:00:51,559 Speaker 1: America's economy is in pretty good shape. You've got an 15 00:00:51,640 --> 00:00:56,480 Speaker 1: unemployment rate of four point four percent, jobless claims around 16 00:00:56,560 --> 00:01:01,520 Speaker 1: the lowest in three decades, wage is US starting to rise, 17 00:01:02,160 --> 00:01:05,080 Speaker 1: and g d P is growing about as fast as 18 00:01:05,120 --> 00:01:09,039 Speaker 1: economists ps I can go. Right now, That's right, Dan, 19 00:01:09,120 --> 00:01:13,959 Speaker 1: But underneath that veneer of a decent economy, millions of 20 00:01:14,040 --> 00:01:18,319 Speaker 1: middle class Americans face a stressful reality, even if they 21 00:01:18,319 --> 00:01:23,160 Speaker 1: have steady jobs. Their paychecks increasingly have pretty big swings 22 00:01:23,160 --> 00:01:26,360 Speaker 1: for month to month, making it challenging to pay bills, 23 00:01:26,959 --> 00:01:30,800 Speaker 1: not to mention, build up savings, to deal with unexpected expenses, 24 00:01:30,880 --> 00:01:34,039 Speaker 1: and things like that. Today on Benchmark, we're going to 25 00:01:34,120 --> 00:01:37,199 Speaker 1: talk with the two authors of a new book who 26 00:01:37,280 --> 00:01:40,640 Speaker 1: studied the financial habits of more than two hundred families 27 00:01:40,680 --> 00:01:43,840 Speaker 1: for a year. If you think that hard work is 28 00:01:43,880 --> 00:01:46,479 Speaker 1: all you need to achieve the American dream, you are 29 00:01:46,600 --> 00:01:59,680 Speaker 1: in for a surprise. I'm Scott Landman, an economics editor 30 00:01:59,760 --> 00:02:03,480 Speaker 1: with Boomberg in Washington, and I'm Daniel Moss, executive editor 31 00:02:03,560 --> 00:02:07,320 Speaker 1: for Global Economics with Bloomberg in New York. So, Dan, 32 00:02:07,440 --> 00:02:09,720 Speaker 1: I think we've we've both worked at Bloomberg for a 33 00:02:09,720 --> 00:02:13,960 Speaker 1: pretty long time. Uh, eighteen years for me and how 34 00:02:13,960 --> 00:02:17,600 Speaker 1: many is it for you now? Twenty three? Wow? Well, 35 00:02:18,040 --> 00:02:20,680 Speaker 1: I suspect we're both grateful for many of the things 36 00:02:20,760 --> 00:02:24,880 Speaker 1: that Bloomberg provides. But after reading this book, I realized 37 00:02:24,919 --> 00:02:27,600 Speaker 1: that I take something for granted that lots of people 38 00:02:27,800 --> 00:02:32,880 Speaker 1: just don't have, and that's a steady paycheck, which really 39 00:02:32,960 --> 00:02:36,520 Speaker 1: isn't what people who have hourly jobs get, or if 40 00:02:36,520 --> 00:02:39,480 Speaker 1: they work on commissions or get paid by the gig, 41 00:02:40,040 --> 00:02:42,600 Speaker 1: so on and so forth. But hang on, I thought 42 00:02:42,639 --> 00:02:45,600 Speaker 1: the gig economy was the trendy, buzzy thing to do 43 00:02:45,639 --> 00:02:49,040 Speaker 1: these days. It might be trendy and buzzy, but it 44 00:02:49,120 --> 00:02:52,320 Speaker 1: doesn't necessarily help people get a steady income. It just 45 00:02:52,480 --> 00:02:55,960 Speaker 1: kind of maybe works for other kinds of work. Is 46 00:02:55,960 --> 00:02:57,960 Speaker 1: that another way of putting it. Well, I mean the 47 00:02:58,120 --> 00:03:03,959 Speaker 1: idea that as a section of the American workforce that's 48 00:03:04,120 --> 00:03:07,359 Speaker 1: not having such a great time, is that a particularly 49 00:03:07,480 --> 00:03:12,119 Speaker 1: new thing, or is it that posts the global financial crisis, 50 00:03:12,639 --> 00:03:15,080 Speaker 1: all of a sudden, it's getting a level of attention 51 00:03:15,200 --> 00:03:17,880 Speaker 1: it didn't get before. Well, it could be both of 52 00:03:17,919 --> 00:03:21,160 Speaker 1: those things, or it could really be that the situation 53 00:03:21,280 --> 00:03:24,760 Speaker 1: is changing. But these kinds of issues are at the 54 00:03:24,840 --> 00:03:28,360 Speaker 1: heart of the new book by our guests. It's called 55 00:03:28,560 --> 00:03:32,239 Speaker 1: The Financial Diaries, How American Families Cope in a World 56 00:03:32,280 --> 00:03:35,960 Speaker 1: of Uncertainty. Jonathan more Duck is a professor of public 57 00:03:36,000 --> 00:03:39,680 Speaker 1: policy and economics at New York University, and Rachel Schneider 58 00:03:39,800 --> 00:03:43,160 Speaker 1: is senior vice president at the Center for Financial Services 59 00:03:43,200 --> 00:03:46,840 Speaker 1: Innovation in Chicago, a group that seeks to improve banking 60 00:03:46,880 --> 00:03:50,480 Speaker 1: for low and middle income Americans and full disclosure get 61 00:03:50,560 --> 00:03:53,880 Speaker 1: some funding from companies in the industry, including Bank of 62 00:03:53,920 --> 00:03:57,800 Speaker 1: America and City Group. Jonathan and Rachel, thanks for joining 63 00:03:57,840 --> 00:04:01,440 Speaker 1: us today. Thank you. You just start out and tell 64 00:04:01,520 --> 00:04:04,320 Speaker 1: us a little bit of how this project came about 65 00:04:04,520 --> 00:04:08,880 Speaker 1: and what you set out to accomplish. The project started, 66 00:04:09,520 --> 00:04:13,120 Speaker 1: um we started thinking about around in the wake of 67 00:04:13,160 --> 00:04:16,680 Speaker 1: the Great Recession, and there's a sense that something huge, 68 00:04:16,720 --> 00:04:20,280 Speaker 1: of course, had happened in the American economy, but it 69 00:04:20,320 --> 00:04:23,840 Speaker 1: was hard to see how the pieces were all landing, 70 00:04:24,120 --> 00:04:28,240 Speaker 1: how American families were really doing after the recession, and 71 00:04:28,960 --> 00:04:32,760 Speaker 1: we didn't really have data to sort it out. And 72 00:04:32,760 --> 00:04:35,200 Speaker 1: we figured that the only real way to get to 73 00:04:35,200 --> 00:04:37,880 Speaker 1: know how families were doing was to go out and 74 00:04:37,960 --> 00:04:40,320 Speaker 1: spend a lot of time getting to know them and 75 00:04:41,120 --> 00:04:45,800 Speaker 1: figuring out how families were coping after the crisis, And 76 00:04:45,880 --> 00:04:51,120 Speaker 1: so the project eventually involved getting to know families. We 77 00:04:51,200 --> 00:04:55,279 Speaker 1: spent a full year trying to track every single dollar 78 00:04:55,520 --> 00:04:58,520 Speaker 1: that the families earned and spend and borrowed and saved, 79 00:04:59,080 --> 00:05:01,920 Speaker 1: really their entire financial lives, so we could get a 80 00:05:02,000 --> 00:05:04,919 Speaker 1: lens on what was really happening um to the families 81 00:05:04,920 --> 00:05:08,720 Speaker 1: after the crisis. Well, what's intriguing about this is you've 82 00:05:08,839 --> 00:05:12,560 Speaker 1: based your findings on hard data. I mean you've just 83 00:05:12,640 --> 00:05:17,400 Speaker 1: described this excruciating process of gathering the information rather than 84 00:05:17,440 --> 00:05:19,680 Speaker 1: a lot of these sorts of books which tend to 85 00:05:19,720 --> 00:05:23,240 Speaker 1: be more impressionistic. Would that be a fair comment. Yeah, 86 00:05:23,400 --> 00:05:25,919 Speaker 1: I think that is their right. So those field researchers 87 00:05:25,920 --> 00:05:29,680 Speaker 1: who gathered the data or visiting families every few weeks 88 00:05:29,800 --> 00:05:33,599 Speaker 1: and really trying to gather information about every single dollar 89 00:05:33,720 --> 00:05:37,480 Speaker 1: that the families earned, spent, borrow and saved. And so 90 00:05:37,640 --> 00:05:40,880 Speaker 1: while the heart of our book is really the family stories, 91 00:05:41,600 --> 00:05:45,919 Speaker 1: the heart of our findings is a lot of data. 92 00:05:46,200 --> 00:05:49,840 Speaker 1: And it's worth pointing out the data we gathered, UM, 93 00:05:49,880 --> 00:05:52,160 Speaker 1: and the way we thought about it really changed in 94 00:05:52,200 --> 00:05:54,280 Speaker 1: some ways over time, or at least for some of us. 95 00:05:54,279 --> 00:05:58,160 Speaker 1: I mean, this was a complicated research project where um, 96 00:05:58,240 --> 00:06:00,839 Speaker 1: of course Jonathan and I and a team of researchers 97 00:06:00,839 --> 00:06:04,800 Speaker 1: were working together, but also, as you mentioned, UM, there 98 00:06:04,839 --> 00:06:07,719 Speaker 1: were other funding partners in this case, the City Foundation 99 00:06:08,440 --> 00:06:10,680 Speaker 1: and the Ford Foundation, and then ultimately do a MIDI 100 00:06:10,720 --> 00:06:14,400 Speaker 1: our network. And I pointed out only because you know, 101 00:06:14,400 --> 00:06:18,040 Speaker 1: in describing CSI, you rightly pointed out that TVs I 102 00:06:18,279 --> 00:06:22,240 Speaker 1: has a focus where I work on um on financial services, 103 00:06:22,279 --> 00:06:24,760 Speaker 1: and we do often get funding for financial services, and 104 00:06:24,800 --> 00:06:28,159 Speaker 1: in this case we started out at cbs I anyway, 105 00:06:28,320 --> 00:06:32,040 Speaker 1: and probably the City Foundation did two in their funding 106 00:06:32,040 --> 00:06:35,840 Speaker 1: of this work, thinking that it would really help us 107 00:06:35,839 --> 00:06:40,440 Speaker 1: to better understand what financial services people needed. The reality 108 00:06:40,520 --> 00:06:42,360 Speaker 1: is that and I think Jonathan saw this from the 109 00:06:42,400 --> 00:06:46,640 Speaker 1: get go, that what we were doing in fact gave 110 00:06:46,720 --> 00:06:48,960 Speaker 1: us a broader lens, that it was less about financial 111 00:06:48,960 --> 00:06:52,120 Speaker 1: services and more about the economic ups and downs economic 112 00:06:52,240 --> 00:06:55,520 Speaker 1: lives as people in a broader way, and so we 113 00:06:55,600 --> 00:06:58,359 Speaker 1: really needed the detailed data we gather it over of 114 00:06:58,360 --> 00:07:00,640 Speaker 1: course the course of the year to do that piece 115 00:07:00,640 --> 00:07:05,400 Speaker 1: and to understand what people were experiencing in a holistic 116 00:07:05,440 --> 00:07:08,280 Speaker 1: sense in their financial lives. Tell us a little bit 117 00:07:08,279 --> 00:07:12,440 Speaker 1: more about these regular financial or economic ups and downs 118 00:07:12,480 --> 00:07:15,080 Speaker 1: that people are experiencing. You you write a lot in 119 00:07:15,120 --> 00:07:18,600 Speaker 1: the book about how people's income would would vary a 120 00:07:18,600 --> 00:07:21,240 Speaker 1: lot from month to month. Uh, you know, one month 121 00:07:21,240 --> 00:07:24,400 Speaker 1: it would be above average, and then next month it 122 00:07:24,480 --> 00:07:27,600 Speaker 1: could be below that by the same amount. And I 123 00:07:27,640 --> 00:07:30,080 Speaker 1: found really fascinating one of the stories you tell in 124 00:07:30,120 --> 00:07:33,440 Speaker 1: the book about the family where the father actually quits 125 00:07:33,520 --> 00:07:37,960 Speaker 1: his job fixing trucks on commission for one that's lower 126 00:07:38,040 --> 00:07:43,160 Speaker 1: paying but steady. Uh, you're providing a steady paycheck. How 127 00:07:43,240 --> 00:07:46,440 Speaker 1: common is that? What kinds of forces are at work here? 128 00:07:46,560 --> 00:07:49,000 Speaker 1: And you know, to go back to our broader question, 129 00:07:49,280 --> 00:07:52,360 Speaker 1: is this a new phenomenon or is this just something 130 00:07:52,400 --> 00:07:57,440 Speaker 1: that we're discovering more that's always been there. Yeah, our 131 00:07:57,480 --> 00:08:00,880 Speaker 1: sense is said, what's been in play is a process 132 00:08:00,920 --> 00:08:04,680 Speaker 1: that started around the nies with a shift in jobs. 133 00:08:04,760 --> 00:08:07,400 Speaker 1: And so Jeremy, who was a truck driver in a 134 00:08:07,400 --> 00:08:11,880 Speaker 1: truck mechanic in Ohio, UM, you know, used to be 135 00:08:12,080 --> 00:08:13,920 Speaker 1: in a situation in the context where there were a 136 00:08:13,920 --> 00:08:16,880 Speaker 1: lot of factory jobs. When he was growing up, maybe 137 00:08:16,920 --> 00:08:20,480 Speaker 1: a quarter of us jobs were in manufacturing. UM. But 138 00:08:20,520 --> 00:08:24,360 Speaker 1: of course union jobs and manufacturing jobs has been sliced 139 00:08:24,560 --> 00:08:27,480 Speaker 1: over time. You know, today about ten percent of jobs 140 00:08:27,520 --> 00:08:31,480 Speaker 1: are manufacturing. So Jeremy has fewer choices and he ends 141 00:08:31,560 --> 00:08:34,679 Speaker 1: up as a truck mechanic and he's working on commission. 142 00:08:35,240 --> 00:08:39,679 Speaker 1: And when we first met him, his weekly paychecks were 143 00:08:39,840 --> 00:08:43,200 Speaker 1: very variable because it wasn't clear how many trucks there 144 00:08:43,200 --> 00:08:46,040 Speaker 1: would be to fix, and he was bearing all of 145 00:08:46,080 --> 00:08:49,640 Speaker 1: that risk. And that you're saying at the end of 146 00:08:49,679 --> 00:08:52,520 Speaker 1: the year he just quit his job for a lower 147 00:08:52,559 --> 00:08:56,400 Speaker 1: paying job that was more steady, And we are seeing 148 00:08:56,440 --> 00:09:00,400 Speaker 1: that pretty broadly in our sample. On average, were seeing 149 00:09:00,440 --> 00:09:04,320 Speaker 1: the households spent about five months of the year where 150 00:09:04,360 --> 00:09:09,240 Speaker 1: their income was above their average or below their average. 151 00:09:09,800 --> 00:09:12,960 Speaker 1: So economic and security in many ways, it wasn't about 152 00:09:12,960 --> 00:09:15,360 Speaker 1: I'm going to lose my job. It was about how 153 00:09:15,400 --> 00:09:17,680 Speaker 1: am I going to navigate the ups and downs that 154 00:09:17,720 --> 00:09:21,280 Speaker 1: are going on in my given job? And how did 155 00:09:21,320 --> 00:09:25,080 Speaker 1: you identify the particular families that you would study. Were 156 00:09:25,080 --> 00:09:29,160 Speaker 1: you after a certain income group, a certain demographic group, 157 00:09:29,320 --> 00:09:34,480 Speaker 1: a certain geographical group. Yeah, our goal was to understand 158 00:09:34,600 --> 00:09:37,240 Speaker 1: a broad cross section of the American experience. So we 159 00:09:37,320 --> 00:09:40,120 Speaker 1: knew that with the level of the depth of the 160 00:09:40,200 --> 00:09:42,840 Speaker 1: data we wanted to collect, we couldn't do a nasting 161 00:09:42,920 --> 00:09:48,280 Speaker 1: representative statistically significant sample, right um, But we could scatter 162 00:09:48,320 --> 00:09:51,640 Speaker 1: our field researchers across the country, and so we gathered 163 00:09:51,679 --> 00:09:56,240 Speaker 1: information from people in California along the Ohio Kentucky border, 164 00:09:56,760 --> 00:10:00,199 Speaker 1: in Mississippi, and in New York. And our goal was 165 00:10:00,240 --> 00:10:03,760 Speaker 1: to understand what it was like for working Americans. So 166 00:10:04,080 --> 00:10:07,640 Speaker 1: about a quarter of the sample is around the area 167 00:10:07,720 --> 00:10:12,800 Speaker 1: meeting income around around middle class in their region, about 168 00:10:12,800 --> 00:10:15,319 Speaker 1: a quarter is close to the poverty line, and then 169 00:10:16,000 --> 00:10:19,760 Speaker 1: the remaining half is in between those two. But the 170 00:10:19,840 --> 00:10:23,800 Speaker 1: common threat is that when we recruited households to join 171 00:10:23,880 --> 00:10:28,120 Speaker 1: the study, every household had somebody in the family who 172 00:10:28,200 --> 00:10:31,720 Speaker 1: was working. And what gave you the idea to pursue 173 00:10:31,840 --> 00:10:34,560 Speaker 1: this study? Well, I feel like I should ask that 174 00:10:34,600 --> 00:10:36,839 Speaker 1: one sinceince it gives me a chance to um to 175 00:10:37,000 --> 00:10:40,120 Speaker 1: Jonathan's horn for prior work. You know, this is really 176 00:10:40,600 --> 00:10:43,480 Speaker 1: um a follow up study to work that was done 177 00:10:43,480 --> 00:10:47,200 Speaker 1: internationally that was also called financial Diaries and as a 178 00:10:47,280 --> 00:10:51,480 Speaker 1: resource methodology that was innovated in the developing world in 179 00:10:51,480 --> 00:10:55,360 Speaker 1: India and South Africa and Bangladesh, and Jonathan and the 180 00:10:55,440 --> 00:10:57,680 Speaker 1: researchers who had done that work wrote a book called 181 00:10:57,720 --> 00:11:01,480 Speaker 1: Portfolios of the Poor and and what was fascinating and 182 00:11:01,520 --> 00:11:07,280 Speaker 1: I first learned about that work maybe um not quite 183 00:11:07,280 --> 00:11:09,400 Speaker 1: ten years ago, on a study trip to South Africa. 184 00:11:09,600 --> 00:11:11,560 Speaker 1: And what was fascinating to me about it when I 185 00:11:11,640 --> 00:11:15,520 Speaker 1: learned about it was that in the US we had 186 00:11:15,559 --> 00:11:18,280 Speaker 1: so much data, right we collect reams and reads of 187 00:11:18,320 --> 00:11:21,200 Speaker 1: financial that you rattled off some of the statistics we 188 00:11:21,280 --> 00:11:25,520 Speaker 1: capture on a regular basic unemployment rate jobless um. Right. 189 00:11:25,559 --> 00:11:29,480 Speaker 1: We we capture all kinds of quantitative data about spending 190 00:11:29,520 --> 00:11:33,199 Speaker 1: and about earning and about savings, and yet this international 191 00:11:33,280 --> 00:11:38,640 Speaker 1: work gave a deeper intuition, a more visceral understanding of 192 00:11:38,640 --> 00:11:42,160 Speaker 1: what was happening in people's financial lives than we had 193 00:11:42,200 --> 00:11:45,199 Speaker 1: in the US, even though we have so much more information, really, 194 00:11:45,960 --> 00:11:48,679 Speaker 1: and so that was a big part of the genesis 195 00:11:48,720 --> 00:11:54,439 Speaker 1: of and inspiration for this project. Our funders, we're really 196 00:11:54,480 --> 00:12:01,200 Speaker 1: interested in replicating that exercise in deepening intuition, opening understanding 197 00:12:01,960 --> 00:12:05,800 Speaker 1: through work that was both quantitative and qualitative. Now, when 198 00:12:05,800 --> 00:12:09,960 Speaker 1: you talk about the ins and outs of people's daily 199 00:12:10,160 --> 00:12:15,520 Speaker 1: monthly finances and the interplay with the broader economy, UH, 200 00:12:15,559 --> 00:12:18,120 Speaker 1: you know, it brings me to think about some of 201 00:12:18,160 --> 00:12:22,040 Speaker 1: the articles we've been recently recently writing I edit our 202 00:12:22,160 --> 00:12:27,880 Speaker 1: u S economy coverage, and a major story for recent months, 203 00:12:27,960 --> 00:12:32,600 Speaker 1: at least from an economic standpoint, has been a slowdown 204 00:12:32,720 --> 00:12:35,680 Speaker 1: in consumer spending in the first quarter. And there have 205 00:12:35,720 --> 00:12:39,040 Speaker 1: been various reasons given for that, but some analysts are 206 00:12:39,040 --> 00:12:43,200 Speaker 1: attributing part of that slow down to UH delays in 207 00:12:43,320 --> 00:12:47,360 Speaker 1: people getting their tax refunds. And it's interesting for me 208 00:12:47,440 --> 00:12:50,920 Speaker 1: to read in your book exactly how important tax refunds 209 00:12:50,960 --> 00:12:55,120 Speaker 1: are for so many families in terms of their annual spending. 210 00:12:56,200 --> 00:13:00,920 Speaker 1: Why do people intentionally make that decision and to have 211 00:13:01,200 --> 00:13:04,960 Speaker 1: that big lump of money each year instead of kind 212 00:13:04,960 --> 00:13:08,719 Speaker 1: of smoothing it out so they have more stability. It's 213 00:13:08,760 --> 00:13:13,800 Speaker 1: a really interesting question, and the answered the the households 214 00:13:13,800 --> 00:13:16,160 Speaker 1: we met really tried to do both right. They know 215 00:13:16,320 --> 00:13:19,520 Speaker 1: that their lives can be pretty rocky and that they 216 00:13:19,520 --> 00:13:22,160 Speaker 1: ought to save up and borrow to smooth things out. 217 00:13:23,040 --> 00:13:26,280 Speaker 1: But there are also lots of times when they need 218 00:13:26,320 --> 00:13:27,720 Speaker 1: a big chunk of money or they want a big 219 00:13:27,800 --> 00:13:30,320 Speaker 1: chunk of money to do some big things, and so 220 00:13:30,360 --> 00:13:33,360 Speaker 1: they're these sort of competing goals. One is something that 221 00:13:33,400 --> 00:13:36,120 Speaker 1: requires a spike of money and another is something that 222 00:13:36,120 --> 00:13:40,040 Speaker 1: requires smoothing. And so, you know, for example, Jeremy the 223 00:13:40,040 --> 00:13:43,960 Speaker 1: truck driver we were just talking about the truck mechanic UM, 224 00:13:44,000 --> 00:13:51,040 Speaker 1: he over withheld his UM you know, monthly tax withholdings, 225 00:13:51,200 --> 00:13:53,960 Speaker 1: so that by the time tax time came around, he 226 00:13:54,080 --> 00:13:58,160 Speaker 1: got a seven thousand dollar refund, which was big, and 227 00:13:58,200 --> 00:14:01,600 Speaker 1: it allowed them to pay off some debt, pay for 228 00:14:01,640 --> 00:14:05,280 Speaker 1: some Christmas bills, UM and do a bunch of things 229 00:14:05,280 --> 00:14:07,800 Speaker 1: for the home and for their children that wouldn't have 230 00:14:07,840 --> 00:14:12,600 Speaker 1: been possible, um if they just used you know, whatever 231 00:14:12,600 --> 00:14:15,960 Speaker 1: they had each month. So sometimes you need a big 232 00:14:16,040 --> 00:14:20,440 Speaker 1: chunk to do some big things. This increase in income 233 00:14:20,560 --> 00:14:25,400 Speaker 1: volatility that you're describing, how much of that is technology? 234 00:14:25,680 --> 00:14:29,600 Speaker 1: Why do you ask? You know? Um, it's something to 235 00:14:29,680 --> 00:14:33,520 Speaker 1: think this is really a result of the gig economy 236 00:14:34,480 --> 00:14:38,440 Speaker 1: or that it you know, we can blame just technology 237 00:14:38,560 --> 00:14:42,280 Speaker 1: or just globalization. I think it's a combination of factors. 238 00:14:42,320 --> 00:14:46,120 Speaker 1: It's really a broad shift in how work functions. So 239 00:14:46,240 --> 00:14:49,400 Speaker 1: some of it is definitely technology. Um, for a lot 240 00:14:49,440 --> 00:14:53,920 Speaker 1: of people who work hourly, and more than half of 241 00:14:54,000 --> 00:14:58,720 Speaker 1: American workers work hourly, technology makes it far easier to 242 00:14:59,720 --> 00:15:03,160 Speaker 1: si as your workforce to demand for your products and services. 243 00:15:03,240 --> 00:15:06,160 Speaker 1: So a retailer or a restaurant knows what demand is 244 00:15:06,160 --> 00:15:08,440 Speaker 1: going to be on a Wednesday at two and can 245 00:15:08,520 --> 00:15:11,640 Speaker 1: have exactly the right number of workers on site. But 246 00:15:11,720 --> 00:15:14,280 Speaker 1: some of that would happen even with that Without technology, 247 00:15:14,560 --> 00:15:18,040 Speaker 1: restaurants have always noticed low demand and sent waiters home. 248 00:15:18,680 --> 00:15:22,280 Speaker 1: So it's not only technology, it's really a broader phenomenon. 249 00:15:22,720 --> 00:15:26,880 Speaker 1: I think. Let me talk about some of the policy 250 00:15:26,960 --> 00:15:30,400 Speaker 1: prescriptions here. I was struck a little bit how you're 251 00:15:30,480 --> 00:15:35,280 Speaker 1: you're talking about at the beginning, Rachel, about the funding 252 00:15:35,360 --> 00:15:38,480 Speaker 1: behind the project, and you know how in general your 253 00:15:38,560 --> 00:15:43,120 Speaker 1: your group looks for ways to uh improve financial services 254 00:15:43,160 --> 00:15:46,160 Speaker 1: for you know, kinds of lower income, middle income people. 255 00:15:46,280 --> 00:15:49,920 Speaker 1: And yet you know, the people in your book struck 256 00:15:50,040 --> 00:15:55,200 Speaker 1: me as being reasonably savvy about the financial services and 257 00:15:55,240 --> 00:15:58,840 Speaker 1: banking services that are offered, and kind of on top 258 00:15:58,880 --> 00:16:04,200 Speaker 1: of things, how how can financial services be improved for 259 00:16:04,680 --> 00:16:07,440 Speaker 1: the kinds of people that were the research subjects in 260 00:16:07,440 --> 00:16:10,200 Speaker 1: your book or do you think they're kind of at 261 00:16:10,480 --> 00:16:13,160 Speaker 1: their you know, at a sort of optimal stage and 262 00:16:13,200 --> 00:16:18,240 Speaker 1: it's really you know, the broader government policy uh prescriptions 263 00:16:18,280 --> 00:16:22,720 Speaker 1: that would need to be modified somewhat to help deal 264 00:16:22,760 --> 00:16:25,880 Speaker 1: with some of these situations. Yeah, I have a guess 265 00:16:25,960 --> 00:16:28,440 Speaker 1: and respond to that. You know, I'm really glad that 266 00:16:28,440 --> 00:16:30,320 Speaker 1: the people we wrote about seem to you like they 267 00:16:30,320 --> 00:16:34,200 Speaker 1: were financially savvy. That to me says we accurately represented 268 00:16:34,240 --> 00:16:37,720 Speaker 1: them because they were right. People are, especially when they 269 00:16:37,720 --> 00:16:41,400 Speaker 1: have less money, really smart and thoughtful often about how 270 00:16:41,400 --> 00:16:44,920 Speaker 1: to make that money stretch. But I think often the 271 00:16:45,000 --> 00:16:48,240 Speaker 1: strategies they were using to make that money stretch show 272 00:16:48,320 --> 00:16:52,080 Speaker 1: us gaps in how financial services are are not serving them. So, 273 00:16:52,160 --> 00:16:55,240 Speaker 1: for example, we tell a story in the book about 274 00:16:55,320 --> 00:16:58,880 Speaker 1: a woman we call Janice who had the savings account 275 00:16:59,040 --> 00:17:02,880 Speaker 1: and a checking account, but she cut up her check 276 00:17:02,920 --> 00:17:05,439 Speaker 1: book from her checking account, right, she cut up her 277 00:17:05,480 --> 00:17:08,520 Speaker 1: ATM card from her savings account. She intentionally has those 278 00:17:08,520 --> 00:17:11,240 Speaker 1: two accounts in different institutions, and the savings account is 279 00:17:11,280 --> 00:17:14,040 Speaker 1: an hour's drive away from her home and has hours 280 00:17:14,119 --> 00:17:17,160 Speaker 1: that she thinks, you know, are not so convenient relative 281 00:17:17,200 --> 00:17:20,639 Speaker 1: to when she works. And she does all that on purpose. 282 00:17:20,720 --> 00:17:23,160 Speaker 1: And now it would be easy to say, hey, that's 283 00:17:23,160 --> 00:17:26,119 Speaker 1: a mistake. She's not using those products right. She's paying 284 00:17:26,119 --> 00:17:28,960 Speaker 1: seas at check cashers and fees to get money orders 285 00:17:29,000 --> 00:17:32,200 Speaker 1: to pay her bills instead of using her checking feature. 286 00:17:32,680 --> 00:17:35,600 Speaker 1: So she's doing it wrong. But I think you have 287 00:17:35,640 --> 00:17:37,280 Speaker 1: to look at it the other way and say, okay, well, 288 00:17:37,320 --> 00:17:40,960 Speaker 1: what's broken about that product design for her? What's broken 289 00:17:40,960 --> 00:17:44,040 Speaker 1: about that product design is she actually wants some wall 290 00:17:44,240 --> 00:17:47,280 Speaker 1: between herself and her spending and her savings, So she 291 00:17:47,359 --> 00:17:50,960 Speaker 1: actually wants it to be hard to withdraw. She actually 292 00:17:51,000 --> 00:17:54,320 Speaker 1: wants it to be hard to um. She's cut up 293 00:17:54,320 --> 00:17:56,560 Speaker 1: her checkbook in particular because she didn't want to have 294 00:17:56,560 --> 00:17:59,200 Speaker 1: any temptation to use payday loans, but she'd had trouble 295 00:17:59,280 --> 00:18:01,480 Speaker 1: within the past, and to get it paid a long 296 00:18:01,520 --> 00:18:04,080 Speaker 1: you've got to turn over assigned to check, post stated 297 00:18:04,119 --> 00:18:09,320 Speaker 1: signed check. So she's you know, you could say she's 298 00:18:09,520 --> 00:18:11,760 Speaker 1: using their products wrong. Where you could say, all right, 299 00:18:11,880 --> 00:18:16,000 Speaker 1: how do you adjust UM transactional services that are available 300 00:18:16,040 --> 00:18:19,800 Speaker 1: to enable her to still pay her bills conveniently electronically 301 00:18:20,359 --> 00:18:24,600 Speaker 1: but not have any risk of using payday or shaves, 302 00:18:24,920 --> 00:18:28,280 Speaker 1: but not have be able to access her funds when 303 00:18:28,320 --> 00:18:30,960 Speaker 1: she needs them. So how do you do how do 304 00:18:31,040 --> 00:18:35,120 Speaker 1: you do that? Well? UM? One thing you could think 305 00:18:35,160 --> 00:18:39,840 Speaker 1: about is UM savings products that have a commitment feature 306 00:18:40,040 --> 00:18:43,600 Speaker 1: or it's harder to withdraw the money. In a funny way, 307 00:18:43,720 --> 00:18:46,479 Speaker 1: UM savings products make it really easy to get your 308 00:18:46,480 --> 00:18:50,879 Speaker 1: money worse of optimizing our financial products for spend, not 309 00:18:51,000 --> 00:18:55,399 Speaker 1: for safe and so I've been encouraged to see if this. 310 00:18:55,480 --> 00:18:59,919 Speaker 1: I in general have been encouraged by financial technology products 311 00:19:00,280 --> 00:19:04,400 Speaker 1: that are more greered towards helping people to save flexibly, 312 00:19:04,560 --> 00:19:08,320 Speaker 1: helping people to identify the goal they're saving for UM 313 00:19:08,400 --> 00:19:11,719 Speaker 1: and walling that savings off in a creative way, so 314 00:19:11,760 --> 00:19:15,440 Speaker 1: it makes it easier for people to their objectives. Yeah, 315 00:19:15,480 --> 00:19:19,560 Speaker 1: there's kind of a fundamental opposition which is really interesting 316 00:19:19,560 --> 00:19:22,760 Speaker 1: and difficult, and families are dealing with in different ways, 317 00:19:23,000 --> 00:19:29,960 Speaker 1: and that is distension between needing structure structured financial products. Um. 318 00:19:30,000 --> 00:19:33,159 Speaker 1: You know, like a savings account where all the money 319 00:19:33,359 --> 00:19:37,119 Speaker 1: gets put into an account which you can't access for 320 00:19:37,119 --> 00:19:39,359 Speaker 1: a long time. It's like a retirement account or a 321 00:19:39,400 --> 00:19:42,240 Speaker 1: Christmas club or something like that. But at the same time, 322 00:19:42,359 --> 00:19:46,320 Speaker 1: in a world of volatility and instability, you need some flexibility, 323 00:19:46,400 --> 00:19:50,240 Speaker 1: and so getting the balance between flexibility and structure is 324 00:19:50,320 --> 00:19:54,080 Speaker 1: really hard with the available products. And that's why Janice, 325 00:19:53,960 --> 00:19:56,840 Speaker 1: you know, open this account an hour away. Um, that 326 00:19:57,000 --> 00:20:00,960 Speaker 1: was her way of getting that balance, But it's hard 327 00:20:01,000 --> 00:20:06,640 Speaker 1: to get that in the commercial marketplace. Now. The working class, 328 00:20:06,800 --> 00:20:11,600 Speaker 1: particularly the white working class in certain geographic areas of 329 00:20:11,600 --> 00:20:14,480 Speaker 1: the country, has had a lot of attention paid to 330 00:20:14,560 --> 00:20:19,959 Speaker 1: it since last November. Is there or what kind of 331 00:20:20,080 --> 00:20:24,800 Speaker 1: intersection did you find between the politics of the moment 332 00:20:25,320 --> 00:20:30,520 Speaker 1: in the respective groups that you've studied and wage volatility. 333 00:20:30,880 --> 00:20:34,160 Speaker 1: I guess what I'm asking is, does the phenomenon that 334 00:20:34,200 --> 00:20:40,040 Speaker 1: you've detailed describe the Trump effect. One of the things 335 00:20:40,119 --> 00:20:46,920 Speaker 1: that we see is that today workers without college degrees 336 00:20:47,880 --> 00:20:50,359 Speaker 1: are struggling in lots of ways, and we see that 337 00:20:50,400 --> 00:20:53,320 Speaker 1: in the labor market in terms of wages. What our 338 00:20:53,480 --> 00:20:55,760 Speaker 1: data and related data are showing is that it's not 339 00:20:55,880 --> 00:21:00,880 Speaker 1: just average wages. They also are facing much more instability 340 00:21:01,320 --> 00:21:04,920 Speaker 1: than other workers. And so there's a group of workers 341 00:21:04,920 --> 00:21:08,920 Speaker 1: out there, white, black, Hispanic black and Hispanic workers actually 342 00:21:09,720 --> 00:21:13,240 Speaker 1: have a harder time, but white workers as well, um, 343 00:21:13,960 --> 00:21:18,280 Speaker 1: who are living fairly precarious lives even though they have jobs. 344 00:21:19,000 --> 00:21:23,240 Speaker 1: So there's economic anxiety even for people with jobs. And 345 00:21:23,280 --> 00:21:25,520 Speaker 1: that's the great puzzle in America that people have been 346 00:21:25,520 --> 00:21:27,560 Speaker 1: trying to sort out. I think the answer is that 347 00:21:27,640 --> 00:21:31,160 Speaker 1: once you spend time and followed people a month by month, 348 00:21:31,240 --> 00:21:34,840 Speaker 1: you can see exactly why there's so much anxiety in 349 00:21:34,840 --> 00:21:38,560 Speaker 1: the sense that the system really isn't working for them. 350 00:21:38,600 --> 00:21:42,880 Speaker 1: So I'm trying to figure out if that's a year's well, 351 00:21:42,920 --> 00:21:46,520 Speaker 1: I'll take a crack at it too. I think, um, 352 00:21:46,760 --> 00:21:49,320 Speaker 1: you know, there's lots of explanations for Trump. I don't 353 00:21:49,320 --> 00:21:53,080 Speaker 1: think we're the best positions to explain everything that happened there. 354 00:21:53,200 --> 00:21:55,959 Speaker 1: I do think what what our data suggests is that 355 00:21:56,000 --> 00:21:58,199 Speaker 1: when you look at or not just suggest what our 356 00:21:58,320 --> 00:22:01,399 Speaker 1: data shows you with when you look us at unemployment rates, 357 00:22:01,480 --> 00:22:05,760 Speaker 1: just the GDP growth, just at big picture numbers for 358 00:22:05,840 --> 00:22:09,760 Speaker 1: what's happening economically in our country, you miss a huge 359 00:22:09,760 --> 00:22:13,480 Speaker 1: amount of economic insecurity that people feel. Now, is that 360 00:22:13,520 --> 00:22:16,399 Speaker 1: the economic insecurity that drove people to vote for Trump? 361 00:22:16,480 --> 00:22:19,000 Speaker 1: I don't know. I do know it is the kind 362 00:22:19,000 --> 00:22:22,439 Speaker 1: of economic insecurity it's easy for us to miss and 363 00:22:22,480 --> 00:22:26,960 Speaker 1: therefore easy to fail to address. But if the big 364 00:22:27,000 --> 00:22:33,120 Speaker 1: picture is improving economically, does that reduce this kind of 365 00:22:33,200 --> 00:22:37,000 Speaker 1: income volatility on the micro level that you're seeing or 366 00:22:37,160 --> 00:22:40,320 Speaker 1: do we need to do more research to really determine 367 00:22:40,840 --> 00:22:44,400 Speaker 1: if that's the case. I'm certain that this kind of 368 00:22:44,480 --> 00:22:48,719 Speaker 1: economic insecurity deserves its own responses. So it's not going 369 00:22:48,760 --> 00:22:51,639 Speaker 1: to be enough just to expect wages to rise or 370 00:22:51,720 --> 00:22:55,760 Speaker 1: productivity to grow fast enough and then magically people won't 371 00:22:55,840 --> 00:23:00,480 Speaker 1: have this kind of insecurity. I think that the volatility 372 00:23:00,520 --> 00:23:04,320 Speaker 1: is a distinct issue on its own. Um. You know, 373 00:23:04,440 --> 00:23:06,920 Speaker 1: you could argue that if incomes right to a certain level, 374 00:23:06,960 --> 00:23:08,960 Speaker 1: then you don't need to worry about faltility. People will 375 00:23:09,000 --> 00:23:11,080 Speaker 1: just manage it on their own, but at the pretty 376 00:23:11,119 --> 00:23:14,400 Speaker 1: high income level before that's going to be the case. Yeah, 377 00:23:14,440 --> 00:23:16,280 Speaker 1: I think you know, what we've seen has been a 378 00:23:16,280 --> 00:23:20,199 Speaker 1: real shift in bargaining power toward management away from labor. 379 00:23:21,080 --> 00:23:26,720 Speaker 1: And if that fundamental bargaining balance doesn't change, then I 380 00:23:26,760 --> 00:23:31,640 Speaker 1: don't see any reason why. Yeah, this pattern would change, 381 00:23:32,240 --> 00:23:36,160 Speaker 1: all right. Well, many issues that we continue to explore 382 00:23:36,200 --> 00:23:40,040 Speaker 1: in our economic coverage on our Benchmark podcast. Jonathan Morduck 383 00:23:40,080 --> 00:23:42,639 Speaker 1: f n y U and Rachel Schneider from the Center 384 00:23:42,720 --> 00:23:46,280 Speaker 1: for Financial Services Innovation, thank you so much for coming 385 00:23:46,320 --> 00:23:49,159 Speaker 1: on the program with us to discuss your book. Thank you, 386 00:23:49,720 --> 00:23:53,040 Speaker 1: thank you, and we hope you'll keep coming back to 387 00:23:53,200 --> 00:23:55,760 Speaker 1: describe the data that you collect. I gather this is 388 00:23:55,800 --> 00:23:58,840 Speaker 1: an ongoing project, or at least you're doing more work 389 00:23:58,960 --> 00:24:03,760 Speaker 1: based on the result some face. Oh, I have to say, actually, um, yes, 390 00:24:03,840 --> 00:24:05,919 Speaker 1: both of us are continue to think about these issues. 391 00:24:05,960 --> 00:24:10,040 Speaker 1: But the data gathering from the diaries, um is concluded 392 00:24:10,080 --> 00:24:13,080 Speaker 1: for the moment. But I think there's still more learning 393 00:24:13,119 --> 00:24:15,439 Speaker 1: from even the data we collected, and so yes, you 394 00:24:15,480 --> 00:24:19,399 Speaker 1: will see more ideas from each of us over time. Well, 395 00:24:19,440 --> 00:24:22,439 Speaker 1: look forward to the financial Diaries to the Revenge of 396 00:24:22,520 --> 00:24:26,560 Speaker 1: Income Volatility. Yeah, really, thank you so much. We really 397 00:24:26,560 --> 00:24:29,920 Speaker 1: appreciate the conversation. Benchmark will be back next week and 398 00:24:30,000 --> 00:24:32,200 Speaker 1: until then, you can find us on the Bloomberg terminal, 399 00:24:32,240 --> 00:24:35,040 Speaker 1: Bloomberg dot com, or Bloomberg App, as well as on 400 00:24:35,119 --> 00:24:39,160 Speaker 1: Apple Podcasts, Podetcast, Stitcher, or wherever you prefer to listen 401 00:24:39,160 --> 00:24:41,880 Speaker 1: to podcasts. While you're there, taking a minute to rate 402 00:24:41,880 --> 00:24:44,240 Speaker 1: and review the show so more listeners can find us 403 00:24:44,600 --> 00:24:46,400 Speaker 1: and let us know what you thought at the show. 404 00:24:46,560 --> 00:24:50,359 Speaker 1: You can follow me on Twitter at Scott Landman Dan 405 00:24:50,560 --> 00:24:54,760 Speaker 1: you are at Moss Underscore Echo, and our guests are 406 00:24:54,840 --> 00:24:57,199 Speaker 1: at at j M O R g U c H 407 00:24:57,280 --> 00:25:01,359 Speaker 1: and at Rachel Schneider. Ben Mark is produced by Sarah 408 00:25:01,400 --> 00:25:04,800 Speaker 1: Patterson and the head of Bloomberg Podcast is Alec McCabe. 409 00:25:05,200 --> 00:25:06,960 Speaker 1: Thanks for listening, See you next time.