1 00:00:05,960 --> 00:00:08,760 Speaker 1: Welcome to Koby Time, a podcast series on markets and 2 00:00:08,770 --> 00:00:12,500 Speaker 1: economies from Devi Coop Research. I'm chief economist. Welcoming you 3 00:00:12,510 --> 00:00:17,809 Speaker 1: to our 106th episode. Our guest today is Orbin Lush, 4 00:00:17,819 --> 00:00:22,590 Speaker 1: assistant Professor of Finance at the Lion School of Business University. 5 00:00:23,100 --> 00:00:26,299 Speaker 1: Professor Kosh is deeply involved in the financial literacy running 6 00:00:26,309 --> 00:00:29,790 Speaker 1: a program for young adults. He's also the founding principal 7 00:00:29,799 --> 00:00:34,490 Speaker 1: investigator of the quarterly DVSSKBIS index project. We'll talk about 8 00:00:34,500 --> 00:00:38,090 Speaker 1: that in greater detail in the podcast over the past decade. 9 00:00:38,098 --> 00:00:40,869 Speaker 1: Uh Professor Kosher has worked diligently on building surveys and 10 00:00:40,880 --> 00:00:43,939 Speaker 1: models of inflation expectations in Singapore and remains hard at 11 00:00:43,950 --> 00:00:47,189 Speaker 1: work in refining measures of cost of living work is 12 00:00:47,200 --> 00:00:47,490 Speaker 1: very 13 00:00:47,584 --> 00:00:49,715 Speaker 1: timely given the sport and cost of living we have 14 00:00:49,723 --> 00:00:53,153 Speaker 1: seen in past few years worldwide, not just in Singapore. 15 00:00:53,334 --> 00:00:56,775 Speaker 1: One additional point. Professor go along with Amit Helder and 16 00:00:56,784 --> 00:00:59,264 Speaker 1: Kan Poe are the editors of a book that was 17 00:00:59,275 --> 00:01:03,215 Speaker 1: published last year. It is a collection of multidisciplinary essays 18 00:01:03,224 --> 00:01:09,595 Speaker 1: titled Managing Complexity and COVID-19. Life Liberty or The Pursuit 19 00:01:09,605 --> 00:01:11,995 Speaker 1: of happiness. Remember those trade-offs we have to deal with. 20 00:01:12,300 --> 00:01:15,598 Speaker 1: This book is all about that and I recommend it highly. 21 00:01:15,620 --> 00:01:18,050 Speaker 1: Not least because I had the honor of contributing a 22 00:01:18,059 --> 00:01:20,660 Speaker 1: chapter in it as well on that note, or the coach. 23 00:01:20,669 --> 00:01:21,669 Speaker 1: Welcome to Kobe time. 24 00:01:22,080 --> 00:01:24,069 Speaker 2: Thank you so much for having me. 25 00:01:24,669 --> 00:01:27,959 Speaker 1: It's uh great to have you here. Uh Though I 26 00:01:27,970 --> 00:01:31,199 Speaker 1: want to devote a large chunk of our discussion on 27 00:01:31,209 --> 00:01:34,819 Speaker 1: your research on cost of living. And uh I have 28 00:01:34,830 --> 00:01:36,959 Speaker 1: been in D BS for six years when I first joined, 29 00:01:36,970 --> 00:01:39,379 Speaker 1: you reached out to me and that led to this 30 00:01:39,389 --> 00:01:40,819 Speaker 1: partnership between my Bank 31 00:01:40,904 --> 00:01:45,995 Speaker 1: Ds and your institute has in Boon at SMU and John, 32 00:01:46,025 --> 00:01:48,485 Speaker 1: we have been doing this quarterly study of inflation expectations. 33 00:01:48,495 --> 00:01:51,794 Speaker 1: So give us some background. So what was the motivation? 34 00:01:51,995 --> 00:01:54,724 Speaker 1: What made you go ahead with this and give us 35 00:01:54,735 --> 00:01:57,055 Speaker 1: a sense of how you go about doing this survey? 36 00:01:58,129 --> 00:02:00,720 Speaker 2: Sure, I mean, uh thanks for having me once again 37 00:02:00,730 --> 00:02:03,230 Speaker 2: in your, you know, may I say celebrated an insightful 38 00:02:03,239 --> 00:02:06,919 Speaker 2: podcast uh going well past a century of episodes. You know, 39 00:02:06,930 --> 00:02:10,080 Speaker 2: it's a hard thing to capture imagination for a while. 40 00:02:10,089 --> 00:02:12,258 Speaker 2: But if you have done it for over a century episodes, 41 00:02:12,270 --> 00:02:13,000 Speaker 2: that's amazing. 42 00:02:13,240 --> 00:02:15,490 Speaker 2: So an opportunity that of course, you embarked on to 43 00:02:15,500 --> 00:02:19,240 Speaker 2: connect experts to audience and presented, presented in a crisis 44 00:02:19,250 --> 00:02:21,860 Speaker 2: of its own during the pandemic, as you rightly mentioned 45 00:02:21,869 --> 00:02:24,289 Speaker 2: about the book, which was also kind of induced by 46 00:02:24,300 --> 00:02:27,440 Speaker 2: the pandemic lockdown if I may say so. So in 47 00:02:27,449 --> 00:02:30,990 Speaker 2: some sense, you know, sometimes opportunities that comes in, comes 48 00:02:31,000 --> 00:02:33,800 Speaker 2: in the form of crisis. And that's almost, that's exactly 49 00:02:33,809 --> 00:02:36,330 Speaker 2: what happened for the genesis of the Singapore 50 00:02:36,554 --> 00:02:39,725 Speaker 2: of inflation expectations, which we are very happy to have 51 00:02:39,735 --> 00:02:42,883 Speaker 2: D BS supporting over the last, you know, 55 years 52 00:02:42,895 --> 00:02:46,225 Speaker 2: or so since we joined uh D BS as well. 53 00:02:46,235 --> 00:02:49,244 Speaker 2: So indeed, one of the things that happened was goes 54 00:02:49,255 --> 00:02:53,353 Speaker 2: back in time to the global financial crisis in 2020 08, 55 00:02:53,365 --> 00:02:57,494 Speaker 2: 20 09, when inflation rates started climbing up early in 56 00:02:57,505 --> 00:02:59,785 Speaker 2: 2010 to over 5% globally. 57 00:03:00,190 --> 00:03:03,478 Speaker 2: So uh Singapore economy uh could have been very adversely 58 00:03:03,490 --> 00:03:05,820 Speaker 2: affected at that time as there was no real market 59 00:03:05,830 --> 00:03:10,529 Speaker 2: driven measures of inflation expectations like the treasury, inflation protected 60 00:03:10,538 --> 00:03:14,399 Speaker 2: security which is available, the available in the US. And 61 00:03:14,410 --> 00:03:16,740 Speaker 2: uh there was of course a risk of unhinged inflation 62 00:03:16,964 --> 00:03:20,145 Speaker 2: expectations which might have been detrimental to the effectiveness of 63 00:03:20,154 --> 00:03:23,455 Speaker 2: monetary policy in any economy and particularly for a small 64 00:03:23,464 --> 00:03:28,115 Speaker 2: open economy like Singapore which imports most of its consumables 65 00:03:28,125 --> 00:03:31,494 Speaker 2: and follows an exchange rate based monetary policy as opposed 66 00:03:31,505 --> 00:03:33,675 Speaker 2: to an interest rate based monetary policy. 67 00:03:34,020 --> 00:03:38,009 Speaker 2: So the main concern that was highlighted by policymakers back 68 00:03:38,020 --> 00:03:41,199 Speaker 2: in the US Federal Reserve Chairman Ben Bernanke, as well 69 00:03:41,210 --> 00:03:45,899 Speaker 2: as ST Louis Federal Reserve President James Bullard on the 70 00:03:45,910 --> 00:03:50,699 Speaker 2: possibility of unanchored or unhinged inflation expectations relative to the 71 00:03:50,710 --> 00:03:54,199 Speaker 2: forward guidance provided by the central banks. So Sinex Survey 72 00:03:54,210 --> 00:03:57,289 Speaker 2: started not to second guess the inflation rate 73 00:03:57,393 --> 00:04:01,542 Speaker 2: itself that was measured by agencies in Singapore, but to 74 00:04:01,552 --> 00:04:06,302 Speaker 2: measure the impact of anchoring of inflation expectations. So is 75 00:04:06,313 --> 00:04:09,792 Speaker 2: that that that forward guidance landing in the right place, 76 00:04:09,802 --> 00:04:13,233 Speaker 2: are people believing that based on their own experiences? So 77 00:04:13,242 --> 00:04:17,173 Speaker 2: we conduct the online survey. Uh It's interviews which is 78 00:04:17,183 --> 00:04:20,662 Speaker 2: through a well researched questionnaire developed over the last 10 years, 79 00:04:20,765 --> 00:04:23,945 Speaker 2: years or so. A random sample of 400 to 500 80 00:04:23,955 --> 00:04:28,066 Speaker 2: consumers in Singapore who roughly represent the demographic distribution of 81 00:04:28,075 --> 00:04:31,665 Speaker 2: age and gender. The S index survey originated back in 2011, 82 00:04:31,675 --> 00:04:34,984 Speaker 2: as I mentioned in September from uh collaboration at that 83 00:04:34,996 --> 00:04:38,265 Speaker 2: time with mastercard and the Sim Bone Institute of Financial 84 00:04:38,276 --> 00:04:41,996 Speaker 2: Economics to address essentially the problem of how do you 85 00:04:42,005 --> 00:04:44,015 Speaker 2: measure inflation expectations to begin with? 86 00:04:47,000 --> 00:04:50,489 Speaker 1: So how many rounds of the survey have we done 87 00:04:50,500 --> 00:04:50,969 Speaker 1: so far? 88 00:04:51,309 --> 00:04:55,399 Speaker 2: So we have completed 48 quarterly rounds of the survey. 89 00:04:55,410 --> 00:04:58,339 Speaker 2: So that's uh really 12 years of the survey that 90 00:04:58,350 --> 00:05:00,779 Speaker 2: in that sense, it's probably one of the longest survey 91 00:05:00,790 --> 00:05:04,559 Speaker 2: uh that is not funded through the central bank. So 92 00:05:04,570 --> 00:05:07,299 Speaker 2: in a way, a privately run uh survey which is 93 00:05:07,309 --> 00:05:09,399 Speaker 2: of course followed by the central bank for this long. 94 00:05:09,410 --> 00:05:12,010 Speaker 2: So 48 is, is an amazing series of data we 95 00:05:12,019 --> 00:05:14,469 Speaker 2: are waiting for, of course, more and more information to 96 00:05:14,480 --> 00:05:16,920 Speaker 2: come in as well. But the what we have so 97 00:05:16,928 --> 00:05:19,339 Speaker 2: far is a treasure trove of, of data as well. 98 00:05:19,600 --> 00:05:22,558 Speaker 1: Yeah, absolutely. Uh Give us a sense of your key 99 00:05:22,570 --> 00:05:26,618 Speaker 1: impressions from this totality of the work. And also give 100 00:05:26,630 --> 00:05:29,059 Speaker 1: us a sense of your view about how useful have 101 00:05:29,070 --> 00:05:32,980 Speaker 1: these been and who are the uh primary consumers of 102 00:05:32,988 --> 00:05:35,149 Speaker 1: the insights that these surveys generate? 103 00:05:35,839 --> 00:05:36,768 Speaker 2: So, uh 104 00:05:37,619 --> 00:05:40,829 Speaker 2: so let's go back to this idea of inflation expectations 105 00:05:40,839 --> 00:05:45,019 Speaker 2: for a second. Uh So inflation expectation can easily be 106 00:05:45,029 --> 00:05:47,730 Speaker 2: a self fulfilling prophecy, at least in the downside. 107 00:05:48,380 --> 00:05:52,308 Speaker 2: So if there is uh there is some trigger or 108 00:05:52,320 --> 00:05:55,909 Speaker 2: some reasons to believe that inflation will actually go up, 109 00:05:56,589 --> 00:06:01,089 Speaker 2: then individuals will make actually decisions uh to buy big 110 00:06:01,269 --> 00:06:05,589 Speaker 2: ticket items right away, which of course becomes uh something 111 00:06:05,600 --> 00:06:08,750 Speaker 2: uh uh something like a self fulfilling prophecy with prices 112 00:06:08,760 --> 00:06:11,000 Speaker 2: in the short run going up. And similarly, if they 113 00:06:11,010 --> 00:06:13,488 Speaker 2: expect prices to come down, and that might also happen 114 00:06:13,500 --> 00:06:16,540 Speaker 2: to some extent. So what we did at the beginning 115 00:06:16,549 --> 00:06:20,220 Speaker 2: of the study is to survey individuals rather than households. 116 00:06:20,230 --> 00:06:23,238 Speaker 2: And this is an online survey because the turnaround time is, 117 00:06:23,250 --> 00:06:24,700 Speaker 2: is is much sooner 118 00:06:24,782 --> 00:06:28,111 Speaker 2: and we had over the last 12 years. Uh We 119 00:06:28,122 --> 00:06:30,820 Speaker 2: have seen several different incidents. I mean, it's important to 120 00:06:30,832 --> 00:06:33,571 Speaker 2: mention that that it was not just a flat uh 121 00:06:33,582 --> 00:06:37,492 Speaker 2: flat uh process of getting the data, but what we 122 00:06:37,502 --> 00:06:40,541 Speaker 2: saw in that particular period is of course a zero 123 00:06:40,552 --> 00:06:43,890 Speaker 2: lower bound existing for a while. And then we also 124 00:06:43,902 --> 00:06:46,432 Speaker 2: saw an even negative interest rate in the eurozone and 125 00:06:46,440 --> 00:06:52,092 Speaker 2: Japan taper tantrums back in 2013 where fed, declaring a 126 00:06:52,101 --> 00:06:52,891 Speaker 2: rate cut 127 00:06:52,973 --> 00:06:56,863 Speaker 2: cut back on the bond bond buying back for quantitative 128 00:06:56,873 --> 00:06:59,484 Speaker 2: easing if you remember that. And then of course, uh 129 00:06:59,493 --> 00:07:03,074 Speaker 2: besides that, you had seen a slump and a revival 130 00:07:03,084 --> 00:07:06,204 Speaker 2: of oil prices and 100 year old, you know, once 131 00:07:06,213 --> 00:07:09,093 Speaker 2: in 100 year pandemic, that that of course kind of 132 00:07:09,104 --> 00:07:11,824 Speaker 2: disrupted life across the board. So all of these things 133 00:07:11,834 --> 00:07:16,384 Speaker 2: means that we have significant variations of inflation expectations. Now, 134 00:07:16,394 --> 00:07:20,813 Speaker 2: our impression going back to your question was that the, 135 00:07:20,824 --> 00:07:21,084 Speaker 2: the the 136 00:07:21,165 --> 00:07:24,165 Speaker 2: the SSKB IC Pix, which is what we call the 137 00:07:24,175 --> 00:07:27,246 Speaker 2: headline inflation expectation has been fairly stable, it has been 138 00:07:27,256 --> 00:07:30,175 Speaker 2: fluctuating but it has been fairly stable and it is 139 00:07:30,186 --> 00:07:33,816 Speaker 2: kind of finding its position, uh you know, similar to 140 00:07:33,825 --> 00:07:38,566 Speaker 2: what a longer term. Uh more I would say, uh 141 00:07:38,585 --> 00:07:42,155 Speaker 2: you know, average value of inflation expectation would be without 142 00:07:42,165 --> 00:07:45,355 Speaker 2: severe fluctuations along the way. And it seems to be 143 00:07:45,365 --> 00:07:49,276 Speaker 2: some somewhat straddling between the outcome that we see 144 00:07:49,358 --> 00:07:52,857 Speaker 2: of the current inflation rate and what the experts in 145 00:07:52,868 --> 00:07:55,947 Speaker 2: this case, the survey of professional forecasters have been, have 146 00:07:55,958 --> 00:07:59,407 Speaker 2: been uh forecasting over, you know, quarterly as well. But 147 00:07:59,417 --> 00:08:02,928 Speaker 2: one of the key impressions that we found out is 148 00:08:02,937 --> 00:08:05,488 Speaker 2: like it does suffer from certain issues like, you know, 149 00:08:05,497 --> 00:08:08,768 Speaker 2: behavioral biases that we will talk about later as well. 150 00:08:08,778 --> 00:08:13,697 Speaker 2: But more importantly, it is identifying the change points quite accurately, 151 00:08:13,708 --> 00:08:17,428 Speaker 2: particularly when uh the the market is seeing sort of 152 00:08:17,458 --> 00:08:17,467 Speaker 2: a 153 00:08:17,709 --> 00:08:20,500 Speaker 2: of inflation. So to say going forward, we are, we 154 00:08:20,510 --> 00:08:23,450 Speaker 2: are finding that that's quite, quite accurate as well going 155 00:08:23,459 --> 00:08:26,200 Speaker 2: forward and looking at the data that is coming out later. 156 00:08:26,209 --> 00:08:30,140 Speaker 2: And also in some sense, the level hasn't been because 157 00:08:30,149 --> 00:08:32,880 Speaker 2: it's quarterly. So in a in a sense, medium term, 158 00:08:32,890 --> 00:08:35,858 Speaker 2: it is not short term or monthly. So we don't 159 00:08:35,869 --> 00:08:39,280 Speaker 2: see that much of fluctuation in the inflation expectations as well. 160 00:08:39,289 --> 00:08:42,200 Speaker 2: It has been to some extent, predictive, I will give 161 00:08:42,210 --> 00:08:45,530 Speaker 2: some examples as well of how 162 00:08:45,932 --> 00:08:49,041 Speaker 2: rate panned out in the next period. Uh But at 163 00:08:49,052 --> 00:08:52,631 Speaker 2: the same time, what it has done is it has 164 00:08:52,642 --> 00:08:57,202 Speaker 2: actually been used as part of a dashboard that the 165 00:08:57,211 --> 00:09:01,211 Speaker 2: central bank also uses it to to come up with, 166 00:09:01,221 --> 00:09:05,910 Speaker 2: with their sort of prediction or, or or policy mechanism 167 00:09:05,921 --> 00:09:09,971 Speaker 2: as well in Singapore. So there has been some differences 168 00:09:09,981 --> 00:09:13,142 Speaker 2: from what we see out there and how the central 169 00:09:13,151 --> 00:09:13,851 Speaker 2: bank has might 170 00:09:13,934 --> 00:09:16,684 Speaker 2: have changed their policy to some extent. But it's very 171 00:09:16,693 --> 00:09:19,864 Speaker 2: hard to identify that every time this inflation expectation goes 172 00:09:19,874 --> 00:09:23,744 Speaker 2: up that will actually have a reaction in uh in 173 00:09:23,823 --> 00:09:26,143 Speaker 2: uh central bank policy as well. So I think it 174 00:09:26,153 --> 00:09:30,814 Speaker 2: has been fairly persistent in that sense as as is 175 00:09:30,823 --> 00:09:35,234 Speaker 2: expected of inflation expectations, but it has not suffered from 176 00:09:35,244 --> 00:09:39,794 Speaker 2: undue fluctuations that uh that would suggest that inflation has 177 00:09:39,804 --> 00:09:42,044 Speaker 2: been unanchored for a while as well. 178 00:09:42,830 --> 00:09:46,619 Speaker 1: So just to expand on your point, you made earlier 179 00:09:46,630 --> 00:09:49,599 Speaker 1: that it is not that useful to sort of take 180 00:09:49,609 --> 00:09:53,789 Speaker 1: the exact point estimate of the survey expectation. So maybe 181 00:09:53,799 --> 00:09:56,569 Speaker 1: people might say, I expect prices to go up by 10% 182 00:09:56,780 --> 00:09:59,599 Speaker 1: to you. More interesting is, are they saying that in 183 00:09:59,609 --> 00:10:02,549 Speaker 1: relationship to the fact that they used to say my 184 00:10:02,559 --> 00:10:06,000 Speaker 1: inflation expectation is eight, meaning it's gone up or if 185 00:10:06,010 --> 00:10:08,539 Speaker 1: they're saying 10 and they're saying going forward my expectations 186 00:10:08,604 --> 00:10:12,574 Speaker 1: is seven. So that rationality is far more informative than 187 00:10:12,585 --> 00:10:14,664 Speaker 1: the actual number which can be subject to, you know, 188 00:10:14,674 --> 00:10:17,585 Speaker 1: all sorts of biases. Um And uh and I think 189 00:10:17,594 --> 00:10:20,375 Speaker 1: that is an important takeaway from the work that you do. 190 00:10:20,414 --> 00:10:23,814 Speaker 1: Um So let's stay with that point. And let's go 191 00:10:23,825 --> 00:10:24,614 Speaker 1: to the more 192 00:10:25,210 --> 00:10:28,590 Speaker 1: results of the recent years of the survey. So how 193 00:10:28,599 --> 00:10:33,219 Speaker 1: have inflation expectations in Singapore evolved in the past few years? 194 00:10:33,229 --> 00:10:35,820 Speaker 1: And what is the latest survey saying? 195 00:10:36,710 --> 00:10:40,140 Speaker 2: So uh so, of course, in the past few years, 196 00:10:40,150 --> 00:10:43,080 Speaker 2: we have seen fluctuations on both sides. So during the 197 00:10:43,090 --> 00:10:47,880 Speaker 2: pandemic period, uh inflation really slumped, inflation expectations also slumped 198 00:10:47,890 --> 00:10:50,659 Speaker 2: together with it. And then it kind of picked up, 199 00:10:50,669 --> 00:10:54,159 Speaker 2: you know what we are seeing that right around after 200 00:10:54,169 --> 00:10:59,349 Speaker 2: the vaccine was essentially discovered and deployed inflation expectations, particularly 201 00:10:59,359 --> 00:11:00,968 Speaker 2: in certain sectors like housing 202 00:11:01,450 --> 00:11:05,200 Speaker 2: and other commodities started going up and picking up as well. 203 00:11:05,210 --> 00:11:08,239 Speaker 2: In Singapore being a small open economy which is affected 204 00:11:08,250 --> 00:11:12,340 Speaker 2: by and imports most of this stuff from elsewhere. There 205 00:11:12,349 --> 00:11:16,450 Speaker 2: has been some impacts that we see that is reflected. 206 00:11:16,460 --> 00:11:18,409 Speaker 2: So a couple of them I will mention so one 207 00:11:18,419 --> 00:11:21,080 Speaker 2: is of course increase in oil prices that has an 208 00:11:21,090 --> 00:11:24,409 Speaker 2: impact and and you see certain increase in the inflation 209 00:11:24,419 --> 00:11:25,909 Speaker 2: expectations in the post 210 00:11:26,330 --> 00:11:29,260 Speaker 2: period as well. And then we see certain pass through 211 00:11:29,270 --> 00:11:34,020 Speaker 2: costs which are also related indirectly where there was restrictions 212 00:11:34,030 --> 00:11:38,440 Speaker 2: on movement of people. So there was certain impact on 213 00:11:38,450 --> 00:11:41,349 Speaker 2: the wage rates that are passed through that go goes 214 00:11:41,359 --> 00:11:44,299 Speaker 2: into the prices as well as you know, uh you know, 215 00:11:44,309 --> 00:11:47,479 Speaker 2: accommodation cost, which has also kind of gone up as well. 216 00:11:47,489 --> 00:11:50,858 Speaker 2: So overall, in the recent period, we found out that well, 217 00:11:50,929 --> 00:11:56,299 Speaker 2: inflation expectations, what what Singaporeans believe uh has gone up, 218 00:11:56,309 --> 00:12:00,510 Speaker 2: but the rate of increase has soft or, or kind 219 00:12:00,520 --> 00:12:02,859 Speaker 2: of mitigated off late. So it is not going up 220 00:12:02,869 --> 00:12:05,820 Speaker 2: as fast as initially about a year back, but it 221 00:12:05,830 --> 00:12:08,819 Speaker 2: is now kind of tempered, it's not going down yet, 222 00:12:08,830 --> 00:12:11,919 Speaker 2: at least from the current survey. But the the rate 223 00:12:11,929 --> 00:12:14,179 Speaker 2: of increase which is sort of the slope has sort 224 00:12:14,190 --> 00:12:15,599 Speaker 2: of dampened to some extent. 225 00:12:16,489 --> 00:12:19,299 Speaker 1: Great. Uh OK. So now you talked a little bit 226 00:12:19,309 --> 00:12:24,169 Speaker 1: about professional analysts and inflation expectations. Uh So let's get 227 00:12:24,179 --> 00:12:31,099 Speaker 1: into that. Um Singapore is full of banks, financial institutions, academics. 228 00:12:31,109 --> 00:12:33,169 Speaker 1: So there are lots of professional forecasts are out there 229 00:12:33,179 --> 00:12:36,340 Speaker 1: who follow price developments in Singapore and make forecasts. Not 230 00:12:36,349 --> 00:12:38,819 Speaker 1: to mention the government agency do the same. Uh and 231 00:12:38,830 --> 00:12:42,820 Speaker 1: now you have about, you know, 12 years worth of data, 232 00:12:42,830 --> 00:12:43,760 Speaker 1: surveying 233 00:12:44,059 --> 00:12:47,630 Speaker 1: day to day Singaporeans and getting their inflation expectations. What 234 00:12:47,640 --> 00:12:49,150 Speaker 1: is the relationship between these two? 235 00:12:50,169 --> 00:12:52,520 Speaker 2: Yeah, that's, that's a very good question. And the reason 236 00:12:52,530 --> 00:12:56,439 Speaker 2: it's a very good question is that your expectation, you know, 237 00:12:56,619 --> 00:13:00,059 Speaker 2: before any data that you look at would be that 238 00:13:00,070 --> 00:13:04,580 Speaker 2: typically your uh your consumers on so called the the 239 00:13:04,590 --> 00:13:08,179 Speaker 2: the layperson on the street who are making economic decisions 240 00:13:08,190 --> 00:13:11,609 Speaker 2: will be following the experts opinion about where inflation is 241 00:13:11,619 --> 00:13:12,419 Speaker 2: going to head to. 242 00:13:12,710 --> 00:13:16,679 Speaker 2: But we tend to see something slightly different. We find 243 00:13:16,690 --> 00:13:20,319 Speaker 2: out that well, while the professional economists, in this case, 244 00:13:20,330 --> 00:13:22,840 Speaker 2: private sector economists are probably more informed because they are 245 00:13:22,849 --> 00:13:26,239 Speaker 2: closely linked with the bank policies, both the central bank 246 00:13:26,250 --> 00:13:27,669 Speaker 2: as they are, you know what they see in the 247 00:13:27,679 --> 00:13:30,409 Speaker 2: data as well. So they are sort of more in 248 00:13:30,419 --> 00:13:33,369 Speaker 2: line with what what the expectations of the central bank 249 00:13:33,380 --> 00:13:36,700 Speaker 2: would be and you would expect the consumers 250 00:13:36,799 --> 00:13:40,030 Speaker 2: will be less informed of that and they would have 251 00:13:40,039 --> 00:13:43,869 Speaker 2: sort of their own independent movement maybe tracking the what 252 00:13:43,880 --> 00:13:47,140 Speaker 2: the professional economists do now, since the survey that we 253 00:13:47,150 --> 00:13:51,070 Speaker 2: run is actually run about a week after the survey 254 00:13:51,080 --> 00:13:54,650 Speaker 2: of professional forecasters are released, we expected that particular linkage, 255 00:13:54,659 --> 00:13:57,809 Speaker 2: that means that the individual respondents are going to follow 256 00:13:57,820 --> 00:14:00,789 Speaker 2: the experts. But we see a sort of different cycle. 257 00:14:00,890 --> 00:14:04,449 Speaker 2: It seemed like it seems like that actually the experts 258 00:14:04,460 --> 00:14:07,849 Speaker 2: are following the individual respondents. So which is kind of 259 00:14:07,859 --> 00:14:11,429 Speaker 2: strange because you, when you and and I'll give you 260 00:14:11,440 --> 00:14:15,020 Speaker 2: the reasons for it. So back in 2012, so it 261 00:14:15,030 --> 00:14:18,799 Speaker 2: started in 2011. Back in 2012, we looked at the 262 00:14:18,809 --> 00:14:22,950 Speaker 2: quarterly data on the last quarter of 2011, 1 year ahead. 263 00:14:23,140 --> 00:14:24,880 Speaker 2: So that was around 4.6% 264 00:14:24,979 --> 00:14:26,950 Speaker 2: percent. That is as, as I mentioned, the genesis was 265 00:14:26,960 --> 00:14:29,739 Speaker 2: because there was a spike in inflation rate at that time, 266 00:14:29,789 --> 00:14:32,510 Speaker 2: uh global was around 5%. So we saw that it 267 00:14:32,520 --> 00:14:36,159 Speaker 2: was about 4.6% 1 year ahead. And it turned out 268 00:14:36,169 --> 00:14:38,609 Speaker 2: strangely enough, that's the only time it has happened one 269 00:14:38,619 --> 00:14:43,090 Speaker 2: year later. From the actual data, the inflation rate, quarterly 270 00:14:43,099 --> 00:14:45,919 Speaker 2: inflation rate, uh actually the the yearly inflation rate of 271 00:14:45,929 --> 00:14:52,429 Speaker 2: 2012 was 4.6%. It was exact, but the professional forecasters 272 00:14:52,440 --> 00:14:54,650 Speaker 2: actually surveyed at 3.1%. 273 00:14:55,159 --> 00:14:59,250 Speaker 2: So which seems like that well, somehow the expectations that 274 00:14:59,260 --> 00:15:03,369 Speaker 2: consumers had was better anchored and the final outcome one 275 00:15:03,380 --> 00:15:06,609 Speaker 2: year later than the experts. And since then, it seems 276 00:15:06,619 --> 00:15:08,210 Speaker 2: like it was a little bit of catch up for 277 00:15:08,219 --> 00:15:10,669 Speaker 2: the experts to catch up to what the consumers are saying. 278 00:15:10,909 --> 00:15:13,549 Speaker 2: So in some sense, even though we timed it to 279 00:15:13,559 --> 00:15:16,840 Speaker 2: be released, the data is collected after the professional uh 280 00:15:16,849 --> 00:15:19,479 Speaker 2: survey is announced, but it seems like most of the 281 00:15:19,489 --> 00:15:21,700 Speaker 2: time it goes the other way around and the and 282 00:15:21,710 --> 00:15:24,789 Speaker 2: the forecasters. In this case, the survey forecasters tend to 283 00:15:24,799 --> 00:15:27,859 Speaker 2: follow in some cases what the consumers are thinking. 284 00:15:28,119 --> 00:15:32,150 Speaker 2: But obviously, of late when you have uh several rounds 285 00:15:32,159 --> 00:15:35,090 Speaker 2: of monetary tightening. In this case, you know, uh increase 286 00:15:35,099 --> 00:15:39,489 Speaker 2: of the slope of the Singapore dollar exchange rate based policy. 287 00:15:39,500 --> 00:15:43,049 Speaker 2: You you saw that there is a sort of decline 288 00:15:43,059 --> 00:15:44,229 Speaker 2: in expectations of professional 289 00:15:44,309 --> 00:15:47,150 Speaker 2: forecasters quite significantly. This is in line with what is 290 00:15:47,159 --> 00:15:49,380 Speaker 2: going on in the US as we have seen even 291 00:15:49,390 --> 00:15:51,299 Speaker 2: a recent data that was released a couple of days 292 00:15:51,309 --> 00:15:54,010 Speaker 2: back that uh that New York survey is saying that 293 00:15:54,020 --> 00:15:56,919 Speaker 2: the numbers are coming down to closer to 3% going 294 00:15:56,929 --> 00:15:59,719 Speaker 2: for the long term, longer term forward guise of 2%. 295 00:15:59,869 --> 00:16:00,419 Speaker 2: But 296 00:16:00,940 --> 00:16:05,929 Speaker 2: besides those sort of main anchors, we find that uh 297 00:16:05,940 --> 00:16:08,710 Speaker 2: you know, individual respondents seems to be fairly stable, but 298 00:16:08,719 --> 00:16:12,750 Speaker 2: professional forecasters seems to be going uh moving closer to 299 00:16:12,760 --> 00:16:15,900 Speaker 2: them rather than the other way around that individual respondents 300 00:16:15,909 --> 00:16:18,409 Speaker 2: are going towards professional forecasters announcements 301 00:16:19,570 --> 00:16:24,400 Speaker 1: or even though OK, at sometimes professional analysts may do 302 00:16:24,409 --> 00:16:28,059 Speaker 1: better than the average public. And sometimes as you said, 303 00:16:28,070 --> 00:16:31,219 Speaker 1: the average public's expectations seem to be leading them. Putting 304 00:16:31,229 --> 00:16:36,239 Speaker 1: that aside just the nature of inflation expectation. Is it 305 00:16:36,250 --> 00:16:39,280 Speaker 1: largely adaptive? And to those of our audience who don't 306 00:16:39,289 --> 00:16:41,520 Speaker 1: know many of that word in the context of economics, 307 00:16:41,530 --> 00:16:44,369 Speaker 1: is it really that my expectations are basically uh based 308 00:16:44,380 --> 00:16:46,280 Speaker 1: on what has been going on in the last 12 months. 309 00:16:48,049 --> 00:16:52,570 Speaker 2: Well, the the challenge is the way some of the 310 00:16:52,580 --> 00:16:55,900 Speaker 2: data is collected, we have to be cognizant of that. 311 00:16:55,909 --> 00:16:58,679 Speaker 2: So a lot of data that we collect is from 312 00:16:58,690 --> 00:17:02,760 Speaker 2: consumers information, many of their information is based on their 313 00:17:02,770 --> 00:17:05,599 Speaker 2: own past experience. So despite of the fact that we 314 00:17:05,609 --> 00:17:07,969 Speaker 2: try to sort of I I would uh lack of 315 00:17:07,979 --> 00:17:10,699 Speaker 2: a better term, educate them about the current data. Uh 316 00:17:10,709 --> 00:17:14,439 Speaker 2: They might still follow their own instincts more than what 317 00:17:14,449 --> 00:17:17,060 Speaker 2: policymakers are, are are saying 318 00:17:17,135 --> 00:17:20,994 Speaker 2: or the forward guidance which I mentioned is is given. 319 00:17:21,084 --> 00:17:23,964 Speaker 2: So in a way, I think there is some levels 320 00:17:23,974 --> 00:17:28,864 Speaker 2: of adaptive in the if there are significant impact. Like 321 00:17:28,875 --> 00:17:32,833 Speaker 2: for example, with a tightening of monetary policy, there was expectation, 322 00:17:32,844 --> 00:17:35,625 Speaker 2: the prices are not going to be unhinged because uh 323 00:17:35,635 --> 00:17:38,344 Speaker 2: the Singapore Central Bank, in this case, the monetary authority 324 00:17:38,354 --> 00:17:41,915 Speaker 2: will take enough measures to try to curb this uh 325 00:17:41,925 --> 00:17:45,583 Speaker 2: you know, uh exchange rate based policy so that the 326 00:17:45,594 --> 00:17:46,204 Speaker 2: prices don't, 327 00:17:46,280 --> 00:17:50,349 Speaker 2: don't go ahead and become unhinged to some extent. So indeed, 328 00:17:50,359 --> 00:17:53,968 Speaker 2: that part I think sometimes is reflected that people do 329 00:17:53,979 --> 00:17:59,188 Speaker 2: react to those information, particularly we see in announcement of 330 00:17:59,199 --> 00:18:03,379 Speaker 2: macro prudential measures like policies on real estate prices. So 331 00:18:03,390 --> 00:18:07,810 Speaker 2: there is significant decline in their expectations about whether prices 332 00:18:07,819 --> 00:18:10,290 Speaker 2: are going to go up or not based on the 333 00:18:10,300 --> 00:18:14,099 Speaker 2: policies that are announced. But there the the reaction for 334 00:18:14,109 --> 00:18:15,349 Speaker 2: inflation expectations 335 00:18:15,494 --> 00:18:21,274 Speaker 2: is not as responsive. Maybe part of the reason is 336 00:18:21,285 --> 00:18:25,234 Speaker 2: the frequency of, of the, of the announcement that comes 337 00:18:25,244 --> 00:18:27,694 Speaker 2: from the central bank as well. Uh This, there is 338 00:18:27,704 --> 00:18:31,755 Speaker 2: only semi annual uh policy statements that are made. Uh And, 339 00:18:31,765 --> 00:18:35,175 Speaker 2: and so there might not be enough anchors that are 340 00:18:35,185 --> 00:18:39,074 Speaker 2: out there for individual respondents to react to that. So 341 00:18:39,084 --> 00:18:41,114 Speaker 2: I think they are basing it mostly on their own 342 00:18:41,125 --> 00:18:44,494 Speaker 2: experience more than what the policy announcements are, 343 00:18:45,000 --> 00:18:47,680 Speaker 1: which is fair. I mean, I I would not expect 344 00:18:47,689 --> 00:18:51,449 Speaker 1: the average person to spend too much time thinking about 345 00:18:51,459 --> 00:18:55,109 Speaker 1: uh Montreal situational, but to your point earlier that the 346 00:18:55,119 --> 00:18:58,199 Speaker 1: long term inflation expectations certainly are a function of both 347 00:18:58,599 --> 00:19:00,930 Speaker 1: expectations that the central bank is serious about dealing with 348 00:19:00,939 --> 00:19:04,689 Speaker 1: it and which may or may not reflect, reflect past performances. 349 00:19:04,699 --> 00:19:07,770 Speaker 1: But in a way implicitly, it does um 350 00:19:09,229 --> 00:19:14,130 Speaker 1: ma S monetary policy, uh do you see it being 351 00:19:14,140 --> 00:19:19,030 Speaker 1: substantially cognizant of inflation expectations or is it also uh 352 00:19:19,040 --> 00:19:23,109 Speaker 1: looking at sort of past developments and professional forecasts and 353 00:19:23,119 --> 00:19:24,149 Speaker 1: trying to do the best out of 354 00:19:24,160 --> 00:19:24,560 Speaker 2: that? 355 00:19:26,589 --> 00:19:30,040 Speaker 2: Yeah, so I think in the in the current state 356 00:19:30,050 --> 00:19:32,479 Speaker 2: of uh the the of course, as I mentioned, the 357 00:19:32,489 --> 00:19:35,359 Speaker 2: monetary policy which is based on exchange rate as well 358 00:19:35,369 --> 00:19:39,520 Speaker 2: as looking at a trade weighted basket of currencies for the, 359 00:19:39,819 --> 00:19:45,719 Speaker 2: which is essentially the Singapore dollar uh nominal effective exchange rate. Now, 360 00:19:45,729 --> 00:19:46,449 Speaker 2: when you are 361 00:19:46,609 --> 00:19:50,250 Speaker 2: looking at a policy which is exchange rate based there, 362 00:19:50,260 --> 00:19:54,260 Speaker 2: uh and there is no other alternative uh options of 363 00:19:54,270 --> 00:19:57,938 Speaker 2: looking at what the true value, the signal of the 364 00:19:57,949 --> 00:20:01,959 Speaker 2: inflation expectations from the market, then they have to base 365 00:20:01,969 --> 00:20:04,400 Speaker 2: it on survey based measures. So the two survey based 366 00:20:04,410 --> 00:20:06,109 Speaker 2: measures they are looking at is of course the survey 367 00:20:06,119 --> 00:20:06,540 Speaker 2: of 368 00:20:06,630 --> 00:20:09,630 Speaker 2: professional forecasters. But as I mentioned, that that might be 369 00:20:09,640 --> 00:20:13,060 Speaker 2: very closely linked to the signals coming from MA S directly. 370 00:20:13,209 --> 00:20:16,300 Speaker 2: So they might be looking at their own policy impact 371 00:20:16,310 --> 00:20:21,160 Speaker 2: in the professional forecasters announcement. But this particular survey, which 372 00:20:21,170 --> 00:20:24,040 Speaker 2: is the Synd, you know, D Bs Skbis index survey 373 00:20:24,109 --> 00:20:26,579 Speaker 2: gives a fresh piece of evidence. 374 00:20:27,410 --> 00:20:31,920 Speaker 2: So that might be tempering some parts of their policy. 375 00:20:31,930 --> 00:20:34,939 Speaker 2: Like for example, if they think tightening could wait for 376 00:20:34,949 --> 00:20:36,979 Speaker 2: a little while longer that there are, you know, so 377 00:20:36,989 --> 00:20:40,689 Speaker 2: more or less not that much fluctuation in official expectations, 378 00:20:40,699 --> 00:20:42,979 Speaker 2: they might be able to decide on that based on 379 00:20:42,989 --> 00:20:44,239 Speaker 2: the numbers from the 380 00:20:44,545 --> 00:20:48,694 Speaker 2: expectations that we see uh from, from the survey as well. 381 00:20:48,704 --> 00:20:51,994 Speaker 2: So given there is no market based measures as, as such, 382 00:20:52,005 --> 00:20:55,925 Speaker 2: I think these are the main uh sources of signals 383 00:20:55,935 --> 00:20:59,094 Speaker 2: that the monetary authority actually is getting to make their, 384 00:20:59,104 --> 00:21:01,155 Speaker 2: make their judgment and decisions as well. 385 00:21:02,640 --> 00:21:08,339 Speaker 1: Is there a um distinction between analyzing inflation expectations, which 386 00:21:08,349 --> 00:21:11,589 Speaker 1: is what we've been talking about and analyzing cost of 387 00:21:11,599 --> 00:21:13,770 Speaker 1: living something that I think you have been working on 388 00:21:13,780 --> 00:21:14,589 Speaker 1: quite a bit lately? 389 00:21:15,439 --> 00:21:18,479 Speaker 2: Yes, absolutely. And this is sort of uh one of 390 00:21:18,489 --> 00:21:22,069 Speaker 2: the challenges that uh is not uniquely Singapore but, but 391 00:21:22,079 --> 00:21:26,540 Speaker 2: because most of, of the data on cost of living as, 392 00:21:26,550 --> 00:21:30,750 Speaker 2: as well as inflation is collected from urban centers and 393 00:21:30,760 --> 00:21:33,650 Speaker 2: Singapore of course, is an urban center as well as 394 00:21:33,660 --> 00:21:37,010 Speaker 2: a city state. The two together means that the the 395 00:21:37,020 --> 00:21:41,339 Speaker 2: impact of, of of changes of inflation or will have 396 00:21:41,349 --> 00:21:42,429 Speaker 2: an impact on cost of living. 397 00:21:42,855 --> 00:21:45,666 Speaker 2: But what we found out in the research that, that 398 00:21:45,676 --> 00:21:48,365 Speaker 2: we did together with a couple of my ex students 399 00:21:48,375 --> 00:21:52,845 Speaker 2: and uh and currently uh you know, colleagues at IMF 400 00:21:52,855 --> 00:21:56,845 Speaker 2: uh as well. Uh Miss Cathy Johan, on this particular 401 00:21:56,855 --> 00:22:00,206 Speaker 2: aspect of what uh what exactly is cost of living 402 00:22:00,215 --> 00:22:02,706 Speaker 2: in some sense and uh how is it related to 403 00:22:02,715 --> 00:22:06,625 Speaker 2: inflation and inflation expectations? We found out something quite interesting 404 00:22:06,635 --> 00:22:09,365 Speaker 2: that if we try to replicate a more I would 405 00:22:09,375 --> 00:22:09,505 Speaker 2: say 406 00:22:09,592 --> 00:22:11,722 Speaker 2: well known cost of living index, which is from the 407 00:22:11,732 --> 00:22:15,802 Speaker 2: Economic Intelligence unit, World cost of Living index or W call, 408 00:22:15,811 --> 00:22:18,881 Speaker 2: which is the purpose of that is to see how 409 00:22:18,921 --> 00:22:21,842 Speaker 2: uh professionals can be moved. Executives can be moved from 410 00:22:21,852 --> 00:22:24,712 Speaker 2: different cities of the world around 100 and 40 odd 411 00:22:24,722 --> 00:22:27,862 Speaker 2: cities that are covered and see whether what will be 412 00:22:27,871 --> 00:22:30,952 Speaker 2: the impact on, on that particular move. So they look 413 00:22:30,962 --> 00:22:34,082 Speaker 2: at cost of living from that particular perspective. So they 414 00:22:34,092 --> 00:22:36,581 Speaker 2: look at around over 100 different 415 00:22:36,958 --> 00:22:40,417 Speaker 2: uh sample prices of different, you know, standard baskets that 416 00:22:40,427 --> 00:22:42,696 Speaker 2: they have looked at across the world and they use 417 00:22:42,708 --> 00:22:45,618 Speaker 2: that to measure that which city might be kind of 418 00:22:45,628 --> 00:22:48,777 Speaker 2: declared the most expensive city to live in. But typically 419 00:22:48,787 --> 00:22:52,718 Speaker 2: it's for most expensive city for expats to move in. 420 00:22:52,728 --> 00:22:54,927 Speaker 2: So that's sort of their main purpose. So what we 421 00:22:54,936 --> 00:22:59,108 Speaker 2: did was we used that data and then we recreated 422 00:22:59,118 --> 00:23:02,878 Speaker 2: something similar to uh the the consumer price index, you know, 423 00:23:02,887 --> 00:23:03,657 Speaker 2: kind of close the 424 00:23:03,894 --> 00:23:07,443 Speaker 2: it. And we found something quite uh quite fascinating is 425 00:23:07,453 --> 00:23:11,943 Speaker 2: that even when inflation was near zero or negative, as 426 00:23:11,953 --> 00:23:14,593 Speaker 2: I mentioned during the pandemic times a little before as well, 427 00:23:14,604 --> 00:23:18,203 Speaker 2: inflation actually went a little negative as well. The quarter inflation, 428 00:23:18,354 --> 00:23:20,654 Speaker 2: we found out that the cost of living actually was 429 00:23:20,663 --> 00:23:23,994 Speaker 2: going up even in that scenario. And this is quite 430 00:23:24,004 --> 00:23:26,754 Speaker 2: uh quite unique and peculiar if you can think of 431 00:23:26,763 --> 00:23:29,994 Speaker 2: it that mostly the origin of inflation was to measure 432 00:23:30,004 --> 00:23:30,734 Speaker 2: cost of living 433 00:23:31,189 --> 00:23:34,389 Speaker 2: but to for comparability, you know, if you think of 434 00:23:34,400 --> 00:23:37,639 Speaker 2: comparing apples with apples, they have to fix a basket 435 00:23:37,650 --> 00:23:40,000 Speaker 2: so that we can compare two different points of time. 436 00:23:40,099 --> 00:23:42,839 Speaker 2: That's what CP I is compared to the base period, 437 00:23:42,849 --> 00:23:46,109 Speaker 2: how much is is a particular basket of goods and services? 438 00:23:46,119 --> 00:23:48,439 Speaker 2: How expensive or how dear would it be at that 439 00:23:48,449 --> 00:23:51,719 Speaker 2: particular point? So they're keeping the basket same and finding 440 00:23:51,729 --> 00:23:54,419 Speaker 2: the price differential between them. But there's another way of 441 00:23:54,430 --> 00:23:56,560 Speaker 2: looking at it. It's looking at the standard of living. 442 00:23:56,569 --> 00:23:58,310 Speaker 2: Same and find out how much more you're going to 443 00:23:58,319 --> 00:24:00,760 Speaker 2: spend under certain budget constraints. 444 00:24:00,826 --> 00:24:03,734 Speaker 2: So the second one is the cost of living measure. 445 00:24:03,744 --> 00:24:06,916 Speaker 2: The first one is more than inflation measure. So standard 446 00:24:06,926 --> 00:24:10,706 Speaker 2: of living being same, how much more you spend becomes 447 00:24:10,715 --> 00:24:13,576 Speaker 2: actually a measure, a de facto measure of uh of 448 00:24:13,586 --> 00:24:16,406 Speaker 2: of cost of living. So we looked at that and 449 00:24:16,416 --> 00:24:19,305 Speaker 2: we found out that indeed that even when there is 450 00:24:19,316 --> 00:24:22,475 Speaker 2: a flat inflation rate with a fixed basket, people are 451 00:24:22,484 --> 00:24:27,805 Speaker 2: adaptively choosing a basket that might cost more, which means 452 00:24:27,816 --> 00:24:30,615 Speaker 2: that to keep maybe the standard of living about 453 00:24:30,682 --> 00:24:34,011 Speaker 2: the same or maybe there is some aspirational impact as well. 454 00:24:34,021 --> 00:24:37,061 Speaker 2: So people want a better standard of living and that 455 00:24:37,071 --> 00:24:39,832 Speaker 2: is pro possibly what is causing the cost of living 456 00:24:39,842 --> 00:24:43,462 Speaker 2: to increase even when inflation is flat. Now, that differential 457 00:24:43,472 --> 00:24:46,661 Speaker 2: is something that actually central banks and policy makers should 458 00:24:46,671 --> 00:24:49,352 Speaker 2: be aware of that even when inflation is flat, it 459 00:24:49,362 --> 00:24:51,571 Speaker 2: might seem like cost of living is actually going up. 460 00:24:51,582 --> 00:24:54,691 Speaker 2: So part of it is probably aspirational but part of 461 00:24:54,702 --> 00:24:58,261 Speaker 2: it is generated from the inflation and the similar basket 462 00:24:58,271 --> 00:25:00,452 Speaker 2: that we talked about before. Now, 463 00:25:00,920 --> 00:25:04,800 Speaker 2: what exactly uh can we infer from that that in, 464 00:25:04,810 --> 00:25:09,160 Speaker 2: in a in a city state where everything is being imported? 465 00:25:09,319 --> 00:25:12,910 Speaker 2: There is the transmission can happen through cost of living 466 00:25:12,920 --> 00:25:16,159 Speaker 2: through pass through cost as well as this aspirational cost. 467 00:25:16,170 --> 00:25:16,329 Speaker 2: When you 468 00:25:16,425 --> 00:25:19,165 Speaker 2: see people around you having sort of a better standard 469 00:25:19,175 --> 00:25:22,754 Speaker 2: of living as well. So there are these endogenous choices 470 00:25:22,765 --> 00:25:26,515 Speaker 2: which might actually make this cost of living impact. Uh 471 00:25:26,525 --> 00:25:30,015 Speaker 2: I would say, I would say far worse than, than 472 00:25:30,025 --> 00:25:33,035 Speaker 2: what you see, just the inflation impact. So if inflation 473 00:25:33,045 --> 00:25:36,854 Speaker 2: technically is something like 3% or 4% your cost of 474 00:25:36,864 --> 00:25:39,014 Speaker 2: living increase might be about 7 8% 475 00:25:39,709 --> 00:25:42,280 Speaker 1: right? Or I have a couple of thoughts on this issue. 476 00:25:42,290 --> 00:25:44,569 Speaker 1: So for example, in the context of the US, we 477 00:25:44,579 --> 00:25:48,439 Speaker 1: see cost of living across states very substantially. So you 478 00:25:48,449 --> 00:25:50,530 Speaker 1: argue that in the US over the last one year, 479 00:25:50,540 --> 00:25:54,199 Speaker 1: inflation has come down substantially. But still people from California 480 00:25:54,209 --> 00:25:58,760 Speaker 1: are moving to Texas because of tax differential, home price differential. 481 00:25:58,770 --> 00:26:02,219 Speaker 1: And so then the level is also an important 482 00:26:02,314 --> 00:26:06,074 Speaker 1: consideration on on relative scale that you know is my 483 00:26:06,084 --> 00:26:09,954 Speaker 1: neighboring country or neighboring state, offering me a lower cost 484 00:26:09,964 --> 00:26:13,064 Speaker 1: for all those basket of goods that I consume. Assuming 485 00:26:13,074 --> 00:26:15,905 Speaker 1: of course, you know, my income remains same if taxes 486 00:26:15,915 --> 00:26:17,494 Speaker 1: were to play another role, then of course, a net 487 00:26:17,505 --> 00:26:20,724 Speaker 1: of income tax becomes an important consideration as well. So, 488 00:26:20,734 --> 00:26:22,484 Speaker 1: so that's one thing I mean, I I feel that 489 00:26:22,494 --> 00:26:24,324 Speaker 1: you know, sitting here in Singapore, we always talk about 490 00:26:24,334 --> 00:26:26,425 Speaker 1: Hong Kong that the cost of living in Hong Kong 491 00:26:26,435 --> 00:26:28,584 Speaker 1: traditionally has been much higher than Singapore. 492 00:26:28,810 --> 00:26:30,709 Speaker 1: It seems like the tables have turned and the cost 493 00:26:30,719 --> 00:26:32,500 Speaker 1: of living there is actually lower than Singapore. 494 00:26:33,660 --> 00:26:36,760 Speaker 1: Uh The second one is this level versus difference issue 495 00:26:36,770 --> 00:26:39,729 Speaker 1: that you also alluded to, that you could have times 496 00:26:39,739 --> 00:26:43,500 Speaker 1: when inflation, the rate of inflation is low or coming down. 497 00:26:43,550 --> 00:26:46,130 Speaker 1: But that doesn't mean that the level of prices have 498 00:26:46,140 --> 00:26:50,478 Speaker 1: come down. You need this inflation uh deflation for, for, 499 00:26:50,489 --> 00:26:51,849 Speaker 1: you know, the level to come down. It's like, you know, 500 00:26:51,859 --> 00:26:54,380 Speaker 1: Singapore's property prices, it may be flat on a year 501 00:26:54,390 --> 00:26:56,540 Speaker 1: on year basis, but it is up like 25% over 502 00:26:56,550 --> 00:27:00,119 Speaker 1: the last two years. Um So when you start thinking 503 00:27:00,130 --> 00:27:00,739 Speaker 1: about 504 00:27:01,150 --> 00:27:04,380 Speaker 1: the cost of living, not of expats, not of people 505 00:27:04,390 --> 00:27:06,910 Speaker 1: who are looking Singapore versus Hong Kong, but look, but 506 00:27:06,920 --> 00:27:10,300 Speaker 1: looking at just living in Singapore day to day basis 507 00:27:10,540 --> 00:27:12,930 Speaker 1: uh and where we know that, you know, wage growth 508 00:27:12,939 --> 00:27:15,530 Speaker 1: is moderate, you don't have some of the situation we 509 00:27:15,540 --> 00:27:17,958 Speaker 1: have in some other countries where wage growth is very strong. 510 00:27:18,219 --> 00:27:20,619 Speaker 1: So then do you get the feeling looking at your 511 00:27:20,630 --> 00:27:22,859 Speaker 1: surveys and looking at your analysis of cost of living 512 00:27:22,869 --> 00:27:27,449 Speaker 1: that Singaporeans affordability is actually getting pushed back that it's 513 00:27:27,459 --> 00:27:28,659 Speaker 1: not expanding? 514 00:27:30,219 --> 00:27:33,569 Speaker 2: Yeah, I mean, this is definitely a AAA pretty deep 515 00:27:33,579 --> 00:27:36,520 Speaker 2: problem in a multiple fronts. So I'll explain the difference 516 00:27:36,530 --> 00:27:38,660 Speaker 2: between Hong Kong and Singapore. And as you rightly mentioned 517 00:27:38,670 --> 00:27:41,500 Speaker 2: that maybe if, if you look at the the cost 518 00:27:41,510 --> 00:27:45,399 Speaker 2: of living element of it, there is a challenge on 519 00:27:45,410 --> 00:27:49,290 Speaker 2: how how house prices uh accommodation plays a very important 520 00:27:49,300 --> 00:27:51,729 Speaker 2: role in the cost of living as well is actually 521 00:27:51,739 --> 00:27:54,380 Speaker 2: seeping into the cost of living framework. And that's one 522 00:27:54,390 --> 00:27:56,520 Speaker 2: of the things that is causing the cost of living 523 00:27:56,530 --> 00:27:58,729 Speaker 2: to go up. But there is another aspect to it. 524 00:27:58,739 --> 00:28:00,010 Speaker 2: I mean, you can endogenously 525 00:28:00,084 --> 00:28:03,854 Speaker 2: choose, uh, you know, some certain baskets that will fit 526 00:28:03,864 --> 00:28:07,035 Speaker 2: your standard of living. Uh, so you might be able 527 00:28:07,045 --> 00:28:10,034 Speaker 2: to sort of do some kind of a tradeoff between 528 00:28:10,045 --> 00:28:13,675 Speaker 2: two baskets. But having said that, I think there is 529 00:28:13,685 --> 00:28:17,014 Speaker 2: another channel that we are, we are sort of ignoring 530 00:28:17,025 --> 00:28:20,625 Speaker 2: which is the wage rate and the price relationship. So 531 00:28:20,635 --> 00:28:24,655 Speaker 2: when you have wages go up for a variety of reasons, 532 00:28:24,665 --> 00:28:27,594 Speaker 2: could be policy reasons as well. So when wages go up, 533 00:28:27,604 --> 00:28:29,875 Speaker 2: there will be some impact on the prices as well. 534 00:28:30,140 --> 00:28:33,609 Speaker 2: So the question is that is wage going up relative 535 00:28:33,619 --> 00:28:37,889 Speaker 2: to the prices or not, that might also influence how 536 00:28:37,900 --> 00:28:41,060 Speaker 2: movement can occur from one country to another. I mean, 537 00:28:41,069 --> 00:28:43,329 Speaker 2: you are also looking at prospects of what is the 538 00:28:43,339 --> 00:28:46,030 Speaker 2: possibility of the growth. So if there is, uh there 539 00:28:46,040 --> 00:28:49,239 Speaker 2: is significant movement of say talent coming from one part 540 00:28:49,250 --> 00:28:51,630 Speaker 2: to another, you would see there will be an impact 541 00:28:51,640 --> 00:28:52,930 Speaker 2: on housing prices as well 542 00:28:53,290 --> 00:28:56,569 Speaker 2: and that house price together with the higher wages might 543 00:28:56,579 --> 00:28:59,819 Speaker 2: have an adverse impact. So you have to have policy 544 00:28:59,829 --> 00:29:03,369 Speaker 2: which is sort of adaptive to such changes as well. 545 00:29:03,380 --> 00:29:06,180 Speaker 2: So it's kind of very difficult to I would say 546 00:29:06,349 --> 00:29:10,359 Speaker 2: isolate different standards of living because there will be these 547 00:29:10,369 --> 00:29:13,170 Speaker 2: sort of feedback loops between them, but at least be 548 00:29:13,180 --> 00:29:17,219 Speaker 2: cognizant of that. And that might help to uh to 549 00:29:17,229 --> 00:29:20,819 Speaker 2: kind of lower prices which is so having stick in 550 00:29:20,829 --> 00:29:20,920 Speaker 2: it 551 00:29:21,306 --> 00:29:24,926 Speaker 2: in, in in, I would say accommodation costs in some 552 00:29:24,936 --> 00:29:30,206 Speaker 2: cases might also be a contributory factor to this increase 553 00:29:30,215 --> 00:29:32,845 Speaker 2: in in cost of living because the rental has to 554 00:29:32,855 --> 00:29:36,625 Speaker 2: be often passed through to prices. So the question now 555 00:29:36,635 --> 00:29:39,916 Speaker 2: is that compared to Hong Kong are rentals in say 556 00:29:39,926 --> 00:29:45,026 Speaker 2: Singapore are increasing at a lower rate or increasing at 557 00:29:45,036 --> 00:29:47,536 Speaker 2: the same rate. I mean, as you mentioned already and 558 00:29:47,546 --> 00:29:48,635 Speaker 2: and correctly, so 559 00:29:48,781 --> 00:29:52,312 Speaker 2: that when the level is higher and that it doesn't 560 00:29:52,322 --> 00:29:54,612 Speaker 2: seem like prices are going down. So a lot of 561 00:29:54,621 --> 00:29:57,362 Speaker 2: properties are held in this case, say commercial properties are 562 00:29:57,371 --> 00:30:00,802 Speaker 2: held which is in shopping malls which are sort of 563 00:30:00,812 --> 00:30:03,641 Speaker 2: shut down or closed rather than lowering the price. We 564 00:30:03,651 --> 00:30:07,472 Speaker 2: know that if there's excess supply, the prices should follow suit. 565 00:30:07,612 --> 00:30:10,582 Speaker 2: But rather than that, if there are portions which are 566 00:30:10,592 --> 00:30:13,041 Speaker 2: not available in the market, hoping for the market to 567 00:30:13,052 --> 00:30:15,881 Speaker 2: recover that impact will actually go back to the prices 568 00:30:15,891 --> 00:30:16,352 Speaker 2: as well. 569 00:30:16,630 --> 00:30:19,800 Speaker 1: Absolutely. So we are fully cognizant that 570 00:30:20,430 --> 00:30:22,459 Speaker 1: and just like any other part of the world, there 571 00:30:22,469 --> 00:30:24,739 Speaker 1: are parts of Singapore where rents are high and there 572 00:30:24,750 --> 00:30:26,760 Speaker 1: are parts of Singapore where rents are not very high 573 00:30:26,849 --> 00:30:29,790 Speaker 1: and the places where rents are high. The expats are 574 00:30:29,800 --> 00:30:32,099 Speaker 1: competing against each other to rent these places, 575 00:30:33,020 --> 00:30:36,709 Speaker 1: places where rents are not very high, largely local population 576 00:30:36,719 --> 00:30:40,770 Speaker 1: is living. But that's the um rental argument. Do you 577 00:30:40,780 --> 00:30:46,609 Speaker 1: have any insights uh from your, you know, studies to 578 00:30:46,619 --> 00:30:50,560 Speaker 1: tell us beyond rent, if there's heterogeneity or prices in Singapore? 579 00:30:50,569 --> 00:30:52,760 Speaker 1: I mean, if I go to a grocery store, is 580 00:30:52,770 --> 00:30:54,630 Speaker 1: it the same in the northern part of Singapore or 581 00:30:54,640 --> 00:30:56,790 Speaker 1: is the eastern part of Singapore and western part of Singapore? 582 00:30:57,650 --> 00:31:00,369 Speaker 2: Uh This is a fascinating thing because you know, Singapore 583 00:31:00,380 --> 00:31:03,180 Speaker 2: is such a small place. You expect that prices will, 584 00:31:03,189 --> 00:31:07,030 Speaker 2: you know, adaptively change. Yeah. So it will, it will 585 00:31:07,040 --> 00:31:08,800 Speaker 2: not exist because all you have to do is like 586 00:31:08,810 --> 00:31:11,010 Speaker 2: 10 minutes drive away or 10 minutes bus ride or 587 00:31:11,020 --> 00:31:13,310 Speaker 2: between right away, you would be able to buy at 588 00:31:13,319 --> 00:31:16,260 Speaker 2: a cheaper rate and particularly with the pandemic, you would 589 00:31:16,270 --> 00:31:19,400 Speaker 2: expect there will be a more, you know, equalization if 590 00:31:19,410 --> 00:31:22,040 Speaker 2: I may say so of prices. But it turns out 591 00:31:22,050 --> 00:31:23,400 Speaker 2: that is not entirely true. 592 00:31:23,650 --> 00:31:28,170 Speaker 2: So indeed, we probably are sort of uh slaves of 593 00:31:28,180 --> 00:31:30,119 Speaker 2: habit to some extent that we tend to shop in 594 00:31:30,130 --> 00:31:32,989 Speaker 2: the same place rather than shop around, which I think 595 00:31:33,000 --> 00:31:34,880 Speaker 2: would be a better thing to do to figure out 596 00:31:34,890 --> 00:31:38,579 Speaker 2: what is the best price, whether we can actually order online. Now, 597 00:31:38,589 --> 00:31:41,239 Speaker 2: ordering online also have a cost implication, right? So if 598 00:31:41,250 --> 00:31:44,030 Speaker 2: the transport cost goes up or the quantity that is 599 00:31:44,040 --> 00:31:47,420 Speaker 2: being delivered have certain features in it. You might indirectly 600 00:31:47,430 --> 00:31:48,439 Speaker 2: because of the bundling 601 00:31:48,530 --> 00:31:51,849 Speaker 2: might be exposed to a higher cost rather than buying 602 00:31:51,859 --> 00:31:54,619 Speaker 2: something at the point that you need it. So all 603 00:31:54,630 --> 00:31:56,930 Speaker 2: of these things put together, it turns out that indeed 604 00:31:56,939 --> 00:31:59,329 Speaker 2: that you would be able to get a lower price 605 00:31:59,339 --> 00:32:01,890 Speaker 2: in certain parts of Singapore compared to other probably because 606 00:32:01,900 --> 00:32:04,560 Speaker 2: of the discounts that you get. So the stated prices 607 00:32:04,569 --> 00:32:06,900 Speaker 2: might be the same. So when you look at just 608 00:32:06,910 --> 00:32:11,260 Speaker 2: the quoted price from online, uh online platforms might be 609 00:32:11,270 --> 00:32:13,310 Speaker 2: the same. But at the same time, you might, 610 00:32:13,410 --> 00:32:15,239 Speaker 2: I might be able to shop around and see there 611 00:32:15,250 --> 00:32:17,800 Speaker 2: are better discounts that are available. So we don't have 612 00:32:17,810 --> 00:32:20,010 Speaker 2: the data on the transacted price. So if you have 613 00:32:20,020 --> 00:32:22,979 Speaker 2: the data on the transacted price, rather the coded price, 614 00:32:22,989 --> 00:32:25,500 Speaker 2: then we might have a better sense of how much 615 00:32:25,510 --> 00:32:30,069 Speaker 2: different different parts of Singapore are. Obviously property prices are 616 00:32:30,079 --> 00:32:33,329 Speaker 2: very different across different prices. Uh Parts of Singapore rental 617 00:32:33,339 --> 00:32:35,550 Speaker 2: is different, so you can expect that that pass through 618 00:32:35,560 --> 00:32:38,199 Speaker 2: will also be different in different parts of Singapore as well, 619 00:32:39,290 --> 00:32:44,260 Speaker 1: right? Um So we've largely talked about data observations from 620 00:32:44,270 --> 00:32:45,839 Speaker 1: the data. So far, I want to talk a little 621 00:32:45,849 --> 00:32:49,719 Speaker 1: bit about policy. What in your view is the best 622 00:32:49,729 --> 00:32:52,780 Speaker 1: way of dealing with the cost of living increases in 623 00:32:52,790 --> 00:32:55,349 Speaker 1: an open economy like Singapore. And I I underscore the 624 00:32:55,359 --> 00:32:57,579 Speaker 1: point it is not just a Singapore specific problem. I mean, 625 00:32:57,589 --> 00:32:59,680 Speaker 1: I just came back from the UK where 626 00:32:59,944 --> 00:33:02,905 Speaker 1: utility bills are up three times from. They were before 627 00:33:02,915 --> 00:33:05,385 Speaker 1: the war in Ukraine. And the high cost of gas 628 00:33:05,395 --> 00:33:08,234 Speaker 1: and electricity have added to a significant amount of concerns 629 00:33:08,244 --> 00:33:11,125 Speaker 1: around the cost of living. So it's a worldwide phenomenon, 630 00:33:11,135 --> 00:33:12,785 Speaker 1: but you know, we're living in Singapore, we want to 631 00:33:12,795 --> 00:33:14,535 Speaker 1: know about Singapore. What in your view is the best 632 00:33:14,545 --> 00:33:16,084 Speaker 1: way to deal with the cost of living here? 633 00:33:16,829 --> 00:33:19,119 Speaker 2: So let me, let me mention about Singapore, as you mentioned, 634 00:33:19,130 --> 00:33:21,359 Speaker 2: you know, UK might be facing other challenges from uh 635 00:33:21,369 --> 00:33:24,229 Speaker 2: because maybe because of Brexit and other things as well, 636 00:33:24,239 --> 00:33:27,040 Speaker 2: you know. Uh but in Singapore, our main challenge is 637 00:33:27,050 --> 00:33:30,040 Speaker 2: being a small open economy. We actually have a double 638 00:33:30,050 --> 00:33:33,290 Speaker 2: whammy every time there is an increase in say oil 639 00:33:33,300 --> 00:33:37,739 Speaker 2: prices or commodity prices. So the oil price increase together 640 00:33:37,750 --> 00:33:41,060 Speaker 2: with us, maybe a speculative increase of us dollar rate 641 00:33:41,219 --> 00:33:43,520 Speaker 2: uh creates a double whammy. First of all, you have 642 00:33:43,530 --> 00:33:46,290 Speaker 2: to pay more for oil, which has sort of a 643 00:33:46,390 --> 00:33:49,530 Speaker 2: uh uh an uh an impact across the board. And 644 00:33:49,540 --> 00:33:51,030 Speaker 2: then of course, you have to pay up in us 645 00:33:51,040 --> 00:33:55,079 Speaker 2: dollar which might become also more expensive compared to Singapore dollar. So, 646 00:33:55,089 --> 00:33:57,930 Speaker 2: uh so I think the, the, the main challenge for 647 00:33:57,939 --> 00:34:00,469 Speaker 2: policymakers in Singapore is that they have to really do 648 00:34:00,479 --> 00:34:03,680 Speaker 2: catch up on the tightening of the monetary policy. I 649 00:34:03,689 --> 00:34:08,399 Speaker 2: think from my vantage point on looking at the data 650 00:34:08,500 --> 00:34:11,500 Speaker 2: uh and given, you know, how, how the exchange rate 651 00:34:11,510 --> 00:34:15,000 Speaker 2: policy in Singapore works, I think we would probably have 652 00:34:15,010 --> 00:34:15,859 Speaker 2: a better communication 653 00:34:16,389 --> 00:34:20,689 Speaker 2: of what the policy stance of the government is. You know, 654 00:34:20,699 --> 00:34:23,199 Speaker 2: in a, in a more I would say digestible way 655 00:34:23,209 --> 00:34:25,969 Speaker 2: might be better for people to understand that whether to 656 00:34:25,979 --> 00:34:29,799 Speaker 2: spend now or later. And that part like for example, 657 00:34:29,810 --> 00:34:32,750 Speaker 2: are their supply restrictions on certain elements that we would 658 00:34:32,760 --> 00:34:36,009 Speaker 2: have a higher price on something. So they expect how 659 00:34:36,020 --> 00:34:39,919 Speaker 2: to manage their future cost implication. And that might be 660 00:34:39,929 --> 00:34:42,139 Speaker 2: one of the ways that you put the problem back 661 00:34:42,149 --> 00:34:45,419 Speaker 2: to consumers to decide exactly what to buy. And when 662 00:34:46,560 --> 00:34:48,629 Speaker 2: at least from that particular point of view. And then 663 00:34:48,639 --> 00:34:50,759 Speaker 2: the other thing, of course, as I mentioned is that 664 00:34:50,770 --> 00:34:54,030 Speaker 2: maybe some levels of uh you know, 665 00:34:54,479 --> 00:34:59,429 Speaker 2: relaxation on the, the the other aspect of increase in costs, 666 00:34:59,439 --> 00:35:02,570 Speaker 2: which is a tighter labor market might also be uh 667 00:35:02,580 --> 00:35:07,260 Speaker 2: meaningful because, you know, a lot of Singaporeans eat out. 668 00:35:07,360 --> 00:35:10,969 Speaker 2: And because of that, the impact of a tight labor 669 00:35:10,979 --> 00:35:14,839 Speaker 2: market having impacted on FNB sector is also passing through 670 00:35:14,850 --> 00:35:17,040 Speaker 2: their costs. So that is sort of one of the 671 00:35:17,050 --> 00:35:19,370 Speaker 2: things that they cannot really uh you know, adjust it 672 00:35:19,379 --> 00:35:21,589 Speaker 2: as much. And finally, I would say 673 00:35:21,689 --> 00:35:25,799 Speaker 2: that, you know, I wouldn't say deregulation per se. But 674 00:35:25,810 --> 00:35:31,659 Speaker 2: a more competitive rental market for commercial property is probably 675 00:35:31,669 --> 00:35:35,009 Speaker 2: a better option going forward because that also, so I'm 676 00:35:35,020 --> 00:35:38,300 Speaker 2: looking at pass through being one of the things that 677 00:35:38,310 --> 00:35:41,600 Speaker 2: at least to some extent the policies can address. It's 678 00:35:41,610 --> 00:35:44,860 Speaker 2: not really a monetary policy per se because uh to 679 00:35:44,870 --> 00:35:47,888 Speaker 2: some extent monetary policy cannot help in pass through, it 680 00:35:47,899 --> 00:35:48,750 Speaker 2: has to be done in Singa 681 00:35:48,899 --> 00:35:51,229 Speaker 2: per dollar, right? It's not paid in US dollar in India, 682 00:35:51,239 --> 00:35:56,070 Speaker 2: any other currency. So, so somehow policy will have zero 683 00:35:56,080 --> 00:35:59,979 Speaker 2: impact monetary policy, exchange rate policy will have zero if not, 684 00:35:59,989 --> 00:36:02,830 Speaker 2: you know, maybe have very little impact on these past 685 00:36:02,840 --> 00:36:05,699 Speaker 2: through costs. So addressing the pastor costs and communications are, 686 00:36:05,709 --> 00:36:09,709 Speaker 2: I think the two best way of at least going 687 00:36:09,719 --> 00:36:13,850 Speaker 2: through this current phase of possible spike or you know, 688 00:36:13,860 --> 00:36:16,049 Speaker 2: short term spike in prices. 689 00:36:16,639 --> 00:36:18,959 Speaker 1: Well, Armindo, we are recording this on the afternoon on 690 00:36:18,969 --> 00:36:20,870 Speaker 1: the 15th of August and let me read you the 691 00:36:20,879 --> 00:36:24,779 Speaker 1: latest headline from the Straits Times online housekeepers, porters added 692 00:36:24,790 --> 00:36:26,939 Speaker 1: to a list of jobs open to work permit holders 693 00:36:26,949 --> 00:36:29,449 Speaker 1: from more locations. So to your point of, you know, 694 00:36:29,459 --> 00:36:33,520 Speaker 1: liberalizing the labor market, the services side. Um the authorities 695 00:36:33,530 --> 00:36:36,049 Speaker 1: have heard you and they're trying to take some measures 696 00:36:36,439 --> 00:36:38,549 Speaker 1: in that direction. Uh No, I fully agree with you 697 00:36:38,560 --> 00:36:42,379 Speaker 1: but a couple of interesting policy dilemma come in. We 698 00:36:42,389 --> 00:36:45,189 Speaker 1: want a greener city, we want a city that is 699 00:36:45,280 --> 00:36:48,889 Speaker 1: not congested with cars and therefore Singapore has a rather, 700 00:36:48,899 --> 00:36:51,080 Speaker 1: you know, unique, you know, solution for the world in 701 00:36:51,090 --> 00:36:54,290 Speaker 1: terms of, you know, certificate of eligibility for cars, people 702 00:36:54,300 --> 00:36:56,889 Speaker 1: compete to get the right to have their cars on 703 00:36:56,899 --> 00:37:00,319 Speaker 1: the roads of Singapore and price of that has skyrocketed. 704 00:37:00,479 --> 00:37:03,109 Speaker 1: But you could also argue it should skyrocket because we 705 00:37:03,120 --> 00:37:05,379 Speaker 1: want less people to own cars in a country where 706 00:37:05,389 --> 00:37:09,429 Speaker 1: there is first class transportation infrastructure and tens of billions 707 00:37:09,439 --> 00:37:13,530 Speaker 1: of dollars are being spent to actually enhance that transportation infrastructure. 708 00:37:13,540 --> 00:37:13,830 Speaker 1: So 709 00:37:14,699 --> 00:37:17,889 Speaker 1: that substi ability that should I drive a car versus 710 00:37:17,899 --> 00:37:20,639 Speaker 1: should I take the M RT? Sometimes, I guess when 711 00:37:20,649 --> 00:37:22,739 Speaker 1: there is a lot of desire and aspiration to drive 712 00:37:22,750 --> 00:37:25,030 Speaker 1: the car, we will say cost of living is high. 713 00:37:25,360 --> 00:37:27,320 Speaker 1: But if people choose to drive M RT will say 714 00:37:27,330 --> 00:37:30,370 Speaker 1: cost of living is slow. How do you square that? Yeah, 715 00:37:30,379 --> 00:37:34,419 Speaker 2: that's exactly the point, right. So this inherent aspirational aspect 716 00:37:34,429 --> 00:37:38,549 Speaker 2: of it has an impact that goes directly to our pocketbook. 717 00:37:38,580 --> 00:37:40,549 Speaker 2: But then again, I mean, you shouldn't say that you 718 00:37:40,560 --> 00:37:43,000 Speaker 2: should not drive a car because if car is your 719 00:37:43,010 --> 00:37:46,919 Speaker 2: access to a particular social circle, then that might be 720 00:37:46,929 --> 00:37:49,409 Speaker 2: causing it. But there is another aspect to it as well. 721 00:37:49,500 --> 00:37:52,310 Speaker 2: The the certificate of entitlement going up, you know, 722 00:37:52,376 --> 00:37:54,707 Speaker 2: because of pro possibly limited supply as well as a 723 00:37:54,717 --> 00:37:58,666 Speaker 2: much higher demand from, you know, people moving into Singapore 724 00:37:58,727 --> 00:38:02,027 Speaker 2: might have other unintended consequence. So I will give one 725 00:38:02,036 --> 00:38:07,616 Speaker 2: example first, you might be able to sort of justify 726 00:38:07,626 --> 00:38:10,767 Speaker 2: through the, you know, more sustainability moves as well that 727 00:38:10,777 --> 00:38:14,126 Speaker 2: you don't want as many cars in Singapore. But then again, 728 00:38:14,136 --> 00:38:17,267 Speaker 2: commercial cars, you know, the ones which are carrying goods 729 00:38:17,277 --> 00:38:19,326 Speaker 2: and services around also have a higher 730 00:38:19,393 --> 00:38:24,803 Speaker 2: cost to pay for the certificates. If you look at, uh, the, the, the, the, 731 00:38:24,813 --> 00:38:28,303 Speaker 2: you know, the shared, uh, you know, uh, car sharing 732 00:38:28,333 --> 00:38:32,674 Speaker 2: and other, uh, uh drivers which are, which are, uh, 733 00:38:32,694 --> 00:38:37,323 Speaker 2: you know, grab and other, uh other facilities that are available. 734 00:38:37,333 --> 00:38:40,243 Speaker 2: One of the challenges for that is that they might 735 00:38:40,253 --> 00:38:43,354 Speaker 2: also be the one who are bidding for the coe. 736 00:38:43,393 --> 00:38:46,343 Speaker 2: So which means that you are automatically increasing. 737 00:38:46,910 --> 00:38:49,700 Speaker 2: So, because maybe more people are going into the gig 738 00:38:49,710 --> 00:38:53,180 Speaker 2: work space and they are using that, well, let's buy 739 00:38:53,190 --> 00:38:56,010 Speaker 2: a car and then use it to, to earn sort 740 00:38:56,020 --> 00:38:59,500 Speaker 2: of a, a secondary income that might also be having 741 00:38:59,510 --> 00:39:02,361 Speaker 2: an impact. So I think maybe once, which are right, 742 00:39:02,371 --> 00:39:05,551 Speaker 2: sharing cars might be put in a slightly different category 743 00:39:05,561 --> 00:39:09,341 Speaker 2: than coes because uh or different form, I mean, I'm 744 00:39:09,351 --> 00:39:11,270 Speaker 2: not going to go ahead and create more coes for 745 00:39:11,281 --> 00:39:13,361 Speaker 2: that matter, but I think uh 746 00:39:13,830 --> 00:39:16,129 Speaker 2: they should be cognizant of that as well because this 747 00:39:16,139 --> 00:39:19,340 Speaker 2: might be causing this change. So there is one is 748 00:39:19,350 --> 00:39:22,359 Speaker 2: earning a uh you know, earning a living which should 749 00:39:22,370 --> 00:39:26,679 Speaker 2: be encouraged. But the other one is possibly more conspicuous consumption, 750 00:39:26,689 --> 00:39:30,199 Speaker 2: conspicuous consumption can be taxed more, but earning a living, 751 00:39:30,209 --> 00:39:32,560 Speaker 2: it is taxed more then that has other impacts on 752 00:39:32,570 --> 00:39:33,580 Speaker 2: the society as well. 753 00:39:34,219 --> 00:39:36,290 Speaker 1: Fair enough for the longest time, I have felt that, 754 00:39:36,300 --> 00:39:38,590 Speaker 1: you know, there should be a, a regulation related to 755 00:39:38,600 --> 00:39:41,760 Speaker 1: the number of cars a household can have or the 756 00:39:41,770 --> 00:39:44,448 Speaker 1: number of cars the household can have under certain COV regime. 757 00:39:44,459 --> 00:39:47,219 Speaker 1: So the first car at a reasonable rate and the 758 00:39:47,229 --> 00:39:50,649 Speaker 1: second and the third car progressively more steep. But I 759 00:39:50,659 --> 00:39:53,229 Speaker 1: also realized that these things are easy for me to say, 760 00:39:53,239 --> 00:39:56,250 Speaker 1: sitting in the armchair. Uh It's not that easy to implement, 761 00:39:56,260 --> 00:39:59,040 Speaker 1: you know, what is a nuclear family and how many 762 00:39:59,050 --> 00:39:59,489 Speaker 1: cars 763 00:39:59,580 --> 00:40:02,409 Speaker 1: to the nuclear family need. Can the authorities decide on 764 00:40:02,419 --> 00:40:05,209 Speaker 1: that on behalf of families or not? Uh Maybe not 765 00:40:05,219 --> 00:40:07,969 Speaker 1: that straightforward, although it seems to me that might be 766 00:40:07,979 --> 00:40:11,669 Speaker 1: a reasonable solution. Uh Let me come back to this 767 00:40:11,679 --> 00:40:14,080 Speaker 1: uh study as you have pointed out earlier that, you know, 768 00:40:14,090 --> 00:40:16,110 Speaker 1: this has been going on for more than a decade. 769 00:40:16,120 --> 00:40:19,989 Speaker 1: You have uh four dozen rounds of survey. Uh Have 770 00:40:20,000 --> 00:40:23,509 Speaker 1: you modified the study? And do you have plans to 771 00:40:23,520 --> 00:40:24,850 Speaker 1: refine it further? 772 00:40:25,649 --> 00:40:29,050 Speaker 2: Uh Yes, we have. So in 2018, we actually did a, 773 00:40:29,060 --> 00:40:33,100 Speaker 2: did a study to figure out, you know, uh effectively, 774 00:40:33,110 --> 00:40:37,100 Speaker 2: how can we make these respondents who are basically consumers, 775 00:40:37,110 --> 00:40:39,439 Speaker 2: uh you know, a cross section of Singapore population 776 00:40:39,669 --> 00:40:42,850 Speaker 2: to make them more professional. So they have more information, 777 00:40:42,860 --> 00:40:45,760 Speaker 2: more data that they can use to make better judgments 778 00:40:45,770 --> 00:40:48,839 Speaker 2: about what to expect in future. So indeed, we did 779 00:40:48,850 --> 00:40:51,500 Speaker 2: a randomized control trial to figure out, you know how 780 00:40:51,510 --> 00:40:53,870 Speaker 2: we can do that. So this was back in 2018 781 00:40:53,879 --> 00:40:57,270 Speaker 2: in a collaboration with the Monetary Authority of Singapore and 782 00:40:57,280 --> 00:40:59,919 Speaker 2: the Behavioral Insights team, which is essentially part of the 783 00:40:59,929 --> 00:41:04,320 Speaker 2: British cabinet office, which incidentally had among other people, Richard Thaler, 784 00:41:04,330 --> 00:41:08,399 Speaker 2: who is uh a Nobel laureate uh for uh for 785 00:41:08,409 --> 00:41:09,250 Speaker 2: his work on 786 00:41:09,534 --> 00:41:13,645 Speaker 2: finance. Uh We, so we use this behavioral insights into 787 00:41:13,655 --> 00:41:16,404 Speaker 2: developing the questionnaire. So that's one part, you know how 788 00:41:16,415 --> 00:41:20,014 Speaker 2: we our, our questionnaire has developed and adjust these biases 789 00:41:20,024 --> 00:41:22,564 Speaker 2: that can be there when we are asking questions to 790 00:41:22,574 --> 00:41:25,824 Speaker 2: consumers who are possibly not primed in a particular way 791 00:41:26,054 --> 00:41:28,754 Speaker 2: uh the other. So that is one part and of course, 792 00:41:28,764 --> 00:41:31,445 Speaker 2: we have a quarterly survey as as you mentioned, which 793 00:41:31,455 --> 00:41:34,094 Speaker 2: has four dozen quarters, but we have other data as 794 00:41:34,104 --> 00:41:36,534 Speaker 2: well that we collect. We haven't really completely released all 795 00:41:36,544 --> 00:41:38,965 Speaker 2: the data as well. Uh Because we need a certain 796 00:41:38,975 --> 00:41:39,104 Speaker 2: number 797 00:41:39,199 --> 00:41:41,610 Speaker 2: amount of the data to make it more predictive to 798 00:41:41,620 --> 00:41:45,860 Speaker 2: address the time series fluctuations and nature of the, you know, 799 00:41:45,870 --> 00:41:49,810 Speaker 2: differences of regimes as well that can entail. So all 800 00:41:49,820 --> 00:41:52,040 Speaker 2: these data are available. So we are looking at things 801 00:41:52,050 --> 00:41:56,669 Speaker 2: like implications as you as you alluded to different locations, 802 00:41:56,679 --> 00:41:58,989 Speaker 2: whether that has an impact on cost of living on 803 00:41:59,000 --> 00:42:03,110 Speaker 2: inflation expectations or expectations of house price increases. We have 804 00:42:03,120 --> 00:42:07,239 Speaker 2: looked at balance sheets of how they are managing their debt. 805 00:42:07,250 --> 00:42:08,870 Speaker 2: Uh Of course, these are 806 00:42:08,965 --> 00:42:12,024 Speaker 2: health reported. We don't have access to their bank data 807 00:42:12,034 --> 00:42:15,455 Speaker 2: as of now. But uh but you know, for research purpose, 808 00:42:15,465 --> 00:42:17,405 Speaker 2: it it might be a useful thing to also look 809 00:42:17,415 --> 00:42:21,254 Speaker 2: at that how they're managing uh cost of living in 810 00:42:21,264 --> 00:42:24,254 Speaker 2: a a sort of a higher interest environment. Are they 811 00:42:24,264 --> 00:42:28,524 Speaker 2: actually investing smartly to try to address to, to sort 812 00:42:28,534 --> 00:42:31,844 Speaker 2: of hedge some impacts of the cost of living? That 813 00:42:31,854 --> 00:42:34,985 Speaker 2: might be another way of solving that problem of, of 814 00:42:34,995 --> 00:42:37,745 Speaker 2: higher cost of living that we see out here obviously, 815 00:42:37,754 --> 00:42:38,635 Speaker 2: because interest rate has been 816 00:42:38,729 --> 00:42:42,209 Speaker 2: quite high as well of late now. So there are 817 00:42:42,219 --> 00:42:46,669 Speaker 2: other aspects and and impact of say macroprudential policies on 818 00:42:46,679 --> 00:42:50,319 Speaker 2: how and why people are using real estate as sort 819 00:42:50,330 --> 00:42:53,110 Speaker 2: of one of their main investment vehicles rather than going 820 00:42:53,120 --> 00:42:56,040 Speaker 2: into the stock market for that matter. Uh That would 821 00:42:56,050 --> 00:42:58,100 Speaker 2: mean that the volume of trade in the stock market, 822 00:42:58,110 --> 00:43:00,169 Speaker 2: of course, there are a lot of different instruments that 823 00:43:00,179 --> 00:43:03,070 Speaker 2: are available as well. Are there more people in Singapore 824 00:43:03,080 --> 00:43:06,779 Speaker 2: actually who are buying stocks either through the Singapore Exchange 825 00:43:06,790 --> 00:43:08,399 Speaker 2: or internationally through other 826 00:43:08,495 --> 00:43:12,385 Speaker 2: other channels or are they buying more robo advising services 827 00:43:12,395 --> 00:43:14,445 Speaker 2: or some other services? You know, how much they are 828 00:43:14,455 --> 00:43:17,925 Speaker 2: contributing to CPF uh whether they're topping it up because 829 00:43:17,935 --> 00:43:20,154 Speaker 2: of course, you know, one of the ways that they 830 00:43:20,165 --> 00:43:23,854 Speaker 2: can also hedge against inflation is to put money into 831 00:43:23,864 --> 00:43:27,475 Speaker 2: CPF as well, which is giving uh 2.5% or 4% 832 00:43:27,485 --> 00:43:29,645 Speaker 2: in the, in the special account. So all of these 833 00:43:29,655 --> 00:43:33,104 Speaker 2: things are possible ways of looking at how they're managing 834 00:43:33,114 --> 00:43:37,104 Speaker 2: their finances would be a good direction to take, to, 835 00:43:37,114 --> 00:43:38,014 Speaker 2: to cut off. 836 00:43:38,570 --> 00:43:41,659 Speaker 2: I would say enhance the data that we have with 837 00:43:41,669 --> 00:43:44,620 Speaker 2: the information that we have at that particular point of 838 00:43:44,629 --> 00:43:47,659 Speaker 2: time because of the quarterly announcement that comes in the 839 00:43:47,669 --> 00:43:51,020 Speaker 2: market conditions, you know, whether there's any global events going on, 840 00:43:51,030 --> 00:43:54,459 Speaker 2: all these things are, you know, research that are ongoing 841 00:43:54,469 --> 00:43:57,340 Speaker 2: and we hope to answer some more challenging questions in 842 00:43:57,350 --> 00:43:58,000 Speaker 2: future too. 843 00:43:58,979 --> 00:44:01,409 Speaker 1: A couple of times during this conversation, you have mentioned 844 00:44:01,419 --> 00:44:05,549 Speaker 1: the term behavioral economics, behavioral finance and also behavioral bias. 845 00:44:05,560 --> 00:44:09,659 Speaker 1: Uh explain for our listeners a little bit about why 846 00:44:09,669 --> 00:44:12,270 Speaker 1: you need to worry about behavioral bias when you do 847 00:44:12,280 --> 00:44:15,330 Speaker 1: a consumer survey or inflation expectation survey like this 848 00:44:15,850 --> 00:44:19,699 Speaker 2: very important point. Uh as I mentioned, if you are 849 00:44:19,709 --> 00:44:23,860 Speaker 2: a professional forecaster or who is a public sector economist 850 00:44:23,870 --> 00:44:28,100 Speaker 2: or private sector economist, you actually have access to information 851 00:44:28,270 --> 00:44:30,659 Speaker 2: and you can look at it in a very objective 852 00:44:30,669 --> 00:44:32,590 Speaker 2: way that these are the information coming in and you 853 00:44:32,600 --> 00:44:34,739 Speaker 2: have had your experience in the past and you know, 854 00:44:34,750 --> 00:44:37,739 Speaker 2: this has this particular impact. So this is what we 855 00:44:37,750 --> 00:44:40,399 Speaker 2: expect rationally in some sense, what are 856 00:44:40,497 --> 00:44:44,977 Speaker 2: our forecasts of inflation next year would be? But individuals 857 00:44:44,987 --> 00:44:50,027 Speaker 2: who are mostly focused on their own personal buying, uh consuming, 858 00:44:50,036 --> 00:44:53,645 Speaker 2: saving investment decisions. They don't have that privilege as much 859 00:44:53,656 --> 00:44:55,645 Speaker 2: because of their day to day life and so on. 860 00:44:55,757 --> 00:44:58,427 Speaker 2: So they, as we mentioned, might be more adaptive to 861 00:44:58,437 --> 00:45:01,906 Speaker 2: their own experience, their own perception as well. Now, that 862 00:45:01,916 --> 00:45:04,406 Speaker 2: has some challenges. Now, the main challenge is when you 863 00:45:04,416 --> 00:45:05,047 Speaker 2: are serving, 864 00:45:05,563 --> 00:45:08,593 Speaker 2: you are averaging across a wide cross section of people. 865 00:45:08,604 --> 00:45:12,714 Speaker 2: Some of them might have much higher say so-called financial 866 00:45:12,724 --> 00:45:16,732 Speaker 2: literacy or sophistication. So to say about understanding data, others 867 00:45:16,743 --> 00:45:19,434 Speaker 2: might not have as much. There is quite a few 868 00:45:19,444 --> 00:45:22,493 Speaker 2: people who say the inflation rate will be 100%. Now, 869 00:45:22,503 --> 00:45:24,513 Speaker 2: that is very hard to imagine that the prices will 870 00:45:24,523 --> 00:45:27,664 Speaker 2: double unless you have a hyper inflation scenario. I don't 871 00:45:27,674 --> 00:45:29,694 Speaker 2: think that is very common place in most 872 00:45:29,791 --> 00:45:33,000 Speaker 2: parts of the world. So given that we have to 873 00:45:33,010 --> 00:45:38,180 Speaker 2: find out that whether these factors are influencing in some 874 00:45:38,190 --> 00:45:41,980 Speaker 2: certain behavioral ways, their decision, current study, in fact, that 875 00:45:41,989 --> 00:45:46,430 Speaker 2: was uh presented recently in academic conferences as well, says 876 00:45:46,440 --> 00:45:50,841 Speaker 2: that whether you're exposed to grocery shopping in a household 877 00:45:50,851 --> 00:45:53,970 Speaker 2: might have an impact on what you expect. Inflation expectation 878 00:45:53,980 --> 00:45:54,381 Speaker 2: would be 879 00:45:55,340 --> 00:45:57,729 Speaker 2: as opposed to someone who is not actively doing grocery 880 00:45:57,739 --> 00:46:00,610 Speaker 2: shopping because of course, food prices are more volatile and 881 00:46:00,620 --> 00:46:03,709 Speaker 2: that might be having this impact as well. So we 882 00:46:03,719 --> 00:46:06,840 Speaker 2: have to adjust for that. So we are giving both versions. 883 00:46:06,850 --> 00:46:08,560 Speaker 2: So one is what is called a radio button option, 884 00:46:08,570 --> 00:46:13,050 Speaker 2: giving them certain choices typically to avoid problem of people 885 00:46:13,060 --> 00:46:16,060 Speaker 2: picking the center choice, which is called anchoring in a 886 00:46:16,070 --> 00:46:16,580 Speaker 2: slightly different 887 00:46:16,679 --> 00:46:20,229 Speaker 2: way. Anchoring bias means that somehow they think that someone 888 00:46:20,239 --> 00:46:22,540 Speaker 2: something in the middle would be the right choice because 889 00:46:22,550 --> 00:46:26,080 Speaker 2: that's what the interviewer intends them to do. Uh That 890 00:46:26,090 --> 00:46:28,629 Speaker 2: is one bias. There are other bias. As I mentioned, 891 00:46:28,639 --> 00:46:31,510 Speaker 2: the grocery shopping bias in some sense, it's basically a 892 00:46:31,520 --> 00:46:35,090 Speaker 2: a frequency bias. People do something more frequently. So it 893 00:46:35,100 --> 00:46:38,529 Speaker 2: turns out that mostly women uh does 894 00:46:38,870 --> 00:46:42,199 Speaker 2: shopping. So they might have certain features that they see 895 00:46:42,209 --> 00:46:44,379 Speaker 2: more often and they think prices are going up for 896 00:46:44,389 --> 00:46:47,159 Speaker 2: the basket that they are consuming or they are buying, 897 00:46:47,169 --> 00:46:49,739 Speaker 2: not consuming per se, they are probably buying for the household. 898 00:46:49,790 --> 00:46:53,928 Speaker 2: When men, these are us study actually buys gasoline or 899 00:46:53,939 --> 00:46:57,840 Speaker 2: petrol more often and prices a change of petrol prices 900 00:46:57,850 --> 00:47:00,799 Speaker 2: have more impact on their perception of inflation. 901 00:47:01,370 --> 00:47:04,419 Speaker 2: So when we change rules of men doing grocery store shopping, 902 00:47:04,429 --> 00:47:08,359 Speaker 2: the study with by Michael Weber and others in Chicago 903 00:47:08,399 --> 00:47:11,340 Speaker 2: in both school of business, they actually found out that 904 00:47:11,350 --> 00:47:15,149 Speaker 2: if you change the rules, exactly the the the expectation 905 00:47:15,159 --> 00:47:17,489 Speaker 2: of inflation reverses as well, which means that there are 906 00:47:17,500 --> 00:47:18,000 Speaker 2: these behaviors 907 00:47:18,084 --> 00:47:20,685 Speaker 2: biases which can creep in in those responses. What we 908 00:47:20,695 --> 00:47:23,895 Speaker 2: are trying to do is to adjust the behavioral biases 909 00:47:23,905 --> 00:47:26,955 Speaker 2: with both a free response as well as a radio 910 00:47:26,965 --> 00:47:30,074 Speaker 2: button response. So we can have a better feeling of 911 00:47:30,084 --> 00:47:33,034 Speaker 2: how these biases are and how to adjust or minimize 912 00:47:33,044 --> 00:47:34,715 Speaker 2: or mitigate those biases. 913 00:47:35,729 --> 00:47:38,600 Speaker 1: Ok. Not easy. But I'm glad that you're cognizant of 914 00:47:38,610 --> 00:47:41,020 Speaker 1: it and, and then you're taking, you know, measures to 915 00:47:41,030 --> 00:47:44,439 Speaker 1: deal with that. This is a very rich data set. 916 00:47:44,820 --> 00:47:48,199 Speaker 1: 12 years worth of data. You have tried various things 917 00:47:48,209 --> 00:47:50,629 Speaker 1: on the margin as well. What do you plan to 918 00:47:50,639 --> 00:47:51,340 Speaker 1: do with this data? 919 00:47:52,389 --> 00:47:54,679 Speaker 2: So I think the best thing to do for our 920 00:47:54,689 --> 00:47:57,330 Speaker 2: data to do is to have more researchers working on it. 921 00:47:57,750 --> 00:48:00,179 Speaker 2: That's sort of how we can get insights into different 922 00:48:00,189 --> 00:48:03,860 Speaker 2: areas as well. But having said that we want to see, 923 00:48:03,870 --> 00:48:05,899 Speaker 2: you know how this can be used for research purposes 924 00:48:05,909 --> 00:48:09,770 Speaker 2: to get insights and particularly to I would say in 925 00:48:09,780 --> 00:48:13,219 Speaker 2: some sense, educate better decision making as well 926 00:48:13,419 --> 00:48:17,330 Speaker 2: individuals and how and what are the, you know, how 927 00:48:17,340 --> 00:48:20,340 Speaker 2: do you hedge against certain types of risk that we 928 00:48:20,350 --> 00:48:23,779 Speaker 2: can do? You know whether people are taking in, for example, 929 00:48:23,790 --> 00:48:26,750 Speaker 2: a lot of informal debt or informal loans. And that 930 00:48:26,760 --> 00:48:29,790 Speaker 2: has an impact on this total debt service ratio, which 931 00:48:29,800 --> 00:48:33,100 Speaker 2: is one of the criteria that is used to try 932 00:48:33,110 --> 00:48:34,310 Speaker 2: to reduce uh 933 00:48:35,120 --> 00:48:39,540 Speaker 2: you know, possible insolvency of borrowers, you know, those, those 934 00:48:39,550 --> 00:48:42,780 Speaker 2: are things that are important policy impact as well. If 935 00:48:42,790 --> 00:48:45,209 Speaker 2: there are more, it it also is an important concern 936 00:48:45,219 --> 00:48:47,590 Speaker 2: for banks, you know, how do you evaluate risk? Uh 937 00:48:47,600 --> 00:48:50,120 Speaker 2: What exactly is a credit risk for an individual who 938 00:48:50,129 --> 00:48:53,610 Speaker 2: has never borrowed before in their life. You know, are they, 939 00:48:53,620 --> 00:48:56,770 Speaker 2: uh you know, are they able to save enough money 940 00:48:56,780 --> 00:48:58,709 Speaker 2: to pay back or are they going to get 941 00:48:58,794 --> 00:49:01,294 Speaker 2: into more and more debt troubles? So these are sort 942 00:49:01,304 --> 00:49:05,534 Speaker 2: of behavioral questions about how they deal with debt, how 943 00:49:05,544 --> 00:49:08,444 Speaker 2: they deal with investment, how they deal with consumption. All 944 00:49:08,455 --> 00:49:10,465 Speaker 2: of these things can, we can actually look at it 945 00:49:10,475 --> 00:49:14,125 Speaker 2: carefully and look at their uncertainty and levels of trust 946 00:49:14,135 --> 00:49:17,104 Speaker 2: they have in the system to also help them understand 947 00:49:17,114 --> 00:49:20,674 Speaker 2: better how to make better financial decisions, both in terms 948 00:49:20,685 --> 00:49:22,384 Speaker 2: of consumption as well as investment 949 00:49:23,379 --> 00:49:26,090 Speaker 1: or even though I have to say, I think SMU 950 00:49:26,100 --> 00:49:29,189 Speaker 1: in general and sme in particular are lucky to have 951 00:49:29,199 --> 00:49:32,709 Speaker 1: such an energetic and curious researcher like you. So, you know, 952 00:49:32,719 --> 00:49:36,350 Speaker 1: keep the, you know, work going. Uh We, we appreciate 953 00:49:36,360 --> 00:49:40,280 Speaker 1: your insights very much and thanks for coming to this podcast. 954 00:49:40,290 --> 00:49:41,169 Speaker 1: This has been great. 955 00:49:41,530 --> 00:49:44,229 Speaker 2: Thank you so much for having me. And indeed, you know, 956 00:49:44,239 --> 00:49:46,679 Speaker 2: I mean, all the discussions we have are very helpful 957 00:49:46,689 --> 00:49:48,659 Speaker 2: in taking this forward as well. So thanks for the 958 00:49:48,669 --> 00:49:52,179 Speaker 2: support and, and all the frequent discussions we have. Thanks again, 959 00:49:52,570 --> 00:49:55,459 Speaker 1: we look forward to continuing to do that. Uh Thank 960 00:49:55,469 --> 00:49:58,489 Speaker 1: you to our listeners as well. COVID time is for 961 00:49:58,500 --> 00:49:59,839 Speaker 1: information only and 962 00:49:59,935 --> 00:50:04,104 Speaker 1: does not represent any trade recommendations. All 106 episodes of 963 00:50:04,114 --> 00:50:07,245 Speaker 1: the podcast are available on youtube and on all major 964 00:50:07,254 --> 00:50:11,735 Speaker 1: podcast platforms including Apple Google and Spotify. As for our 965 00:50:11,745 --> 00:50:14,405 Speaker 1: research publications, webinars and live streams, you can find them 966 00:50:14,415 --> 00:50:18,263 Speaker 1: all by Googling B BS research Library. Have a great day.