1 00:00:00,160 --> 00:00:02,719 Speaker 1: Interesting new insight into the rental market and whether Airbnb 2 00:00:02,800 --> 00:00:04,960 Speaker 1: has had an effect on prices. The answer appy is 3 00:00:05,000 --> 00:00:07,200 Speaker 1: to be no. This comes out of a study done 4 00:00:07,200 --> 00:00:10,080 Speaker 1: by Informetric Chief executive principal economist. Brad Olsen is with 5 00:00:10,160 --> 00:00:14,800 Speaker 1: us on this Brad Morning. Just to clear this up, 6 00:00:15,360 --> 00:00:17,320 Speaker 1: you were commissioned by Airbnb to do this. Did you 7 00:00:17,360 --> 00:00:18,640 Speaker 1: get stitched up? As this legit? 8 00:00:19,920 --> 00:00:22,040 Speaker 2: It is legit, and no, I don't get stitched up, Mike. 9 00:00:22,239 --> 00:00:23,760 Speaker 2: I think a lot more of myself and I think 10 00:00:23,800 --> 00:00:25,759 Speaker 2: others think a lot more of us for this. But 11 00:00:25,800 --> 00:00:27,880 Speaker 2: I think this is probably why Airbnb came to us. 12 00:00:27,920 --> 00:00:31,000 Speaker 2: I said, look, everyone always talks about what the effect 13 00:00:31,000 --> 00:00:33,240 Speaker 2: of Airbnb and similar might be on the rental market. 14 00:00:33,479 --> 00:00:35,479 Speaker 2: No one's actually done the numbers. We sort of just 15 00:00:35,560 --> 00:00:37,559 Speaker 2: talked about it. Can you go and do the figures? 16 00:00:37,600 --> 00:00:39,600 Speaker 2: And we did. We went into it with an open 17 00:00:39,640 --> 00:00:42,000 Speaker 2: mind and what we found was that actually the largest 18 00:00:42,120 --> 00:00:45,520 Speaker 2: influence on the rental and housing markets are fun enough 19 00:00:45,640 --> 00:00:49,479 Speaker 2: population growth, but also the interest rates airbnbs have. Other 20 00:00:49,520 --> 00:00:53,599 Speaker 2: short term rental accommodation doesn't have a particularly big influence 21 00:00:53,760 --> 00:00:56,360 Speaker 2: at all, which makes sense given the sorts of population 22 00:00:56,480 --> 00:00:59,360 Speaker 2: growth and similarly you've had over years, and suggests that again, 23 00:00:59,440 --> 00:01:01,920 Speaker 2: you really just need to increase the supply of houses 24 00:01:01,960 --> 00:01:04,600 Speaker 2: across the board if you want to improve housing outcomes. 25 00:01:04,640 --> 00:01:06,200 Speaker 1: All right, let me pick up on a couple of 26 00:01:06,200 --> 00:01:08,920 Speaker 1: things here. If we didn't have the immigration growth we had, 27 00:01:08,959 --> 00:01:10,200 Speaker 1: would it be different. 28 00:01:11,000 --> 00:01:13,559 Speaker 2: Well, I think it probably would be. But you'd also 29 00:01:13,600 --> 00:01:15,760 Speaker 2: then need to look at other parts of the economy 30 00:01:15,760 --> 00:01:18,160 Speaker 2: in terms of the labor market and similar Would we 31 00:01:18,200 --> 00:01:20,080 Speaker 2: have the right skills, would we have the right people 32 00:01:20,120 --> 00:01:22,080 Speaker 2: to do things? I think it's more that if we're 33 00:01:22,120 --> 00:01:24,440 Speaker 2: going to have migration levels like we've had it, and 34 00:01:24,480 --> 00:01:26,440 Speaker 2: I actually think that's a good thing, we sort of 35 00:01:26,480 --> 00:01:28,640 Speaker 2: also have to resource it well at the right time. 36 00:01:28,680 --> 00:01:31,360 Speaker 2: And I think you know, when we went through this analysis, 37 00:01:31,360 --> 00:01:33,880 Speaker 2: we pulled together a bunch of data on the lights 38 00:01:33,920 --> 00:01:36,160 Speaker 2: of the housing market over a longer period of time, 39 00:01:36,280 --> 00:01:39,160 Speaker 2: growth in the dwellings and similar and it continues to 40 00:01:39,200 --> 00:01:41,399 Speaker 2: suggest every report that we seem to do on the 41 00:01:41,400 --> 00:01:44,520 Speaker 2: housing market suggests that we just need to continually build more. 42 00:01:45,120 --> 00:01:49,280 Speaker 1: Right, So are you suggesting immigration aside that there aren't 43 00:01:49,400 --> 00:01:52,520 Speaker 1: enough AIRB and B houses to affect the price, because 44 00:01:52,560 --> 00:01:55,000 Speaker 1: logic would indicate that if there's a house sitting on 45 00:01:55,000 --> 00:01:57,080 Speaker 1: a street and it's airb and b'd as opposed to 46 00:01:57,120 --> 00:01:59,640 Speaker 1: rent it, that must in some way shape or form 47 00:02:00,080 --> 00:02:01,000 Speaker 1: thick the rental market. 48 00:02:02,120 --> 00:02:04,280 Speaker 2: Well, that was the interesting thing. That was another thing 49 00:02:04,280 --> 00:02:07,080 Speaker 2: that we did tests through the analysis, because there's always 50 00:02:07,120 --> 00:02:09,760 Speaker 2: this idea Mike that if you have an Airbnb, if 51 00:02:09,760 --> 00:02:11,840 Speaker 2: it wasn't in an airbnb, it would definitely be a 52 00:02:11,840 --> 00:02:14,400 Speaker 2: long term rental, and we found that often just wasn't 53 00:02:14,440 --> 00:02:17,480 Speaker 2: the case. Particularly in Queenstown for example, we found a 54 00:02:17,560 --> 00:02:21,040 Speaker 2: number of areas where, even before airbnb was ever a thing, 55 00:02:21,320 --> 00:02:23,440 Speaker 2: yet quite a lot of holiday homes and similar So 56 00:02:23,600 --> 00:02:25,520 Speaker 2: just because the house is there doesn't mean it will 57 00:02:25,560 --> 00:02:28,400 Speaker 2: be a long term rental. And therefore that's where when 58 00:02:28,400 --> 00:02:30,280 Speaker 2: we went through some of those figures, that's where we 59 00:02:30,360 --> 00:02:33,919 Speaker 2: found that actually it wouldn't necessarily be a huge conversion through. 60 00:02:34,200 --> 00:02:36,440 Speaker 2: What we also found, and I think this was sort 61 00:02:36,440 --> 00:02:39,200 Speaker 2: of particularly interesting, is that often I think we sort 62 00:02:39,240 --> 00:02:42,799 Speaker 2: of condense a few different issues together and that's where 63 00:02:42,800 --> 00:02:45,680 Speaker 2: you often get this talk of airbnb's having a greater 64 00:02:45,760 --> 00:02:48,200 Speaker 2: influence than they do. I sort of liking it in 65 00:02:48,200 --> 00:02:50,200 Speaker 2: a sense that if you had a look on a 66 00:02:50,280 --> 00:02:52,080 Speaker 2: cold winter's day, and you saw that there was an 67 00:02:52,120 --> 00:02:55,480 Speaker 2: increasing sale for jackets and an increasing sale for heat pumps. 68 00:02:55,680 --> 00:02:58,480 Speaker 2: You could make the influence that higher jacket sales influence 69 00:02:58,560 --> 00:03:01,760 Speaker 2: higher heat pump sales, not really that there's actually a 70 00:03:01,880 --> 00:03:05,639 Speaker 2: common factor, which is this temperature. For airbnbs, there's more 71 00:03:05,680 --> 00:03:09,000 Speaker 2: airbnbs over time, as well as higher rental prices because 72 00:03:09,000 --> 00:03:11,280 Speaker 2: there's more population. That is what it boiled down to. 73 00:03:11,280 --> 00:03:13,280 Speaker 2: When we sort of looked at all of the figures together, 74 00:03:13,560 --> 00:03:15,239 Speaker 2: we put them all into our model and we said, 75 00:03:15,240 --> 00:03:18,200 Speaker 2: what is the biggest influence on these outcomes on rents 76 00:03:18,200 --> 00:03:21,680 Speaker 2: and house prices? Population growth came out of a country 77 00:03:21,680 --> 00:03:24,680 Speaker 2: bile ahead. I mean for Queenstown, for example. We estimate 78 00:03:24,720 --> 00:03:27,440 Speaker 2: that broadly, over the last six years, the likes of 79 00:03:27,639 --> 00:03:30,680 Speaker 2: population growth contributed about a one hundred and one dollar 80 00:03:30,760 --> 00:03:34,400 Speaker 2: per week increase in rents. Airbnb did around eleven dollars. 81 00:03:34,680 --> 00:03:37,480 Speaker 1: Right, would you as Queenstown unique though, because there'd be 82 00:03:37,520 --> 00:03:39,880 Speaker 1: a lot of flash houses in Queenstown that yes, you'd 83 00:03:40,040 --> 00:03:42,600 Speaker 1: higher out for five nights in a year at two 84 00:03:42,640 --> 00:03:46,520 Speaker 1: thousand dollars a night versus having some ski bum hang 85 00:03:46,560 --> 00:03:49,240 Speaker 1: out for fifteen hundred dollars. We can wreck your house. 86 00:03:50,600 --> 00:03:52,760 Speaker 2: Quite possible, and I think the thing with Queenstown, that's 87 00:03:52,760 --> 00:03:54,680 Speaker 2: why we did spend a bit more time on it 88 00:03:54,720 --> 00:03:58,000 Speaker 2: because it does have a much larger concentration of short 89 00:03:58,080 --> 00:04:01,720 Speaker 2: term rental accommodation, so we did have a bit of 90 00:04:01,720 --> 00:04:03,000 Speaker 2: a look at that. That's why I just gave you 91 00:04:03,040 --> 00:04:05,320 Speaker 2: those numbers to try and highlight that figure. When we 92 00:04:05,320 --> 00:04:07,080 Speaker 2: looked at other areas though, So we looked at the 93 00:04:07,160 --> 00:04:10,720 Speaker 2: likes of Auckland, Wellington christ Church are much much bigger areas. 94 00:04:10,800 --> 00:04:13,720 Speaker 2: The concentration of airbnbs in those areas is quite a 95 00:04:13,720 --> 00:04:16,719 Speaker 2: bit smaller, so they just don't really have any discernible effect. 96 00:04:16,720 --> 00:04:19,320 Speaker 2: I mean talking, I think it's since per week, since 97 00:04:19,360 --> 00:04:22,680 Speaker 2: per month difference airbnbs do, so it's just not a 98 00:04:22,720 --> 00:04:23,760 Speaker 2: significant influence. 99 00:04:23,920 --> 00:04:25,520 Speaker 1: Good insight, mate, Nice to have you on the program. 100 00:04:25,600 --> 00:04:27,720 Speaker 1: Has always Brad Olson infor Metric's chief executive. 101 00:04:28,279 --> 00:04:31,200 Speaker 2: For more from the mi Casking Breakfast, listen live to 102 00:04:31,279 --> 00:04:34,359 Speaker 2: news talks that'd be from six am weekdays, or follow 103 00:04:34,400 --> 00:04:35,960 Speaker 2: the podcast on iHeartRadio.