WEBVTT 1 00:00:00.404 --> 00:00:02.987 (upbeat music) 2 00:00:09.559 --> 00:00:13.227 line:15% Did you know that one third of all food produced 3 00:00:13.227 --> 00:00:15.327 line:15% is either lost or wasted 4 00:00:15.327 --> 00:00:18.586 line:15% as estimated by the Food and Agricultural Organization 5 00:00:18.586 --> 00:00:20.603 of the United Nations? 6 00:00:20.603 --> 00:00:23.472 In fact, if food waste was a country, 7 00:00:23.472 --> 00:00:27.021 it would be the third largest greenhouse gas contributor 8 00:00:27.021 --> 00:00:30.150 next to China and the United States. 9 00:00:30.150 --> 00:00:33.263 Unfortunately though, much of this food waste 10 00:00:33.263 --> 00:00:37.364 in developed countries simply comes from a consumer's desire 11 00:00:37.364 --> 00:00:40.049 to have aesthetically-pleasing produce. 12 00:00:40.049 --> 00:00:42.290 This results in blemished produce, 13 00:00:42.290 --> 00:00:44.961 or produce that is nutritionally OK, 14 00:00:44.961 --> 00:00:47.758 but it does not meet the aesthetic standards needed 15 00:00:47.758 --> 00:00:50.840 to go to the market, to be discarded. 16 00:00:50.840 --> 00:00:53.611 For example, because this tomato 17 00:00:53.611 --> 00:00:56.823 does not meet the USDA's highest standard 18 00:00:56.823 --> 00:00:59.690 of being perfectly round and unscarred, 19 00:00:59.690 --> 00:01:01.382 it would not go to the market 20 00:01:01.382 --> 00:01:04.669 because consumers would be less likely to purchase it, 21 00:01:04.669 --> 00:01:07.469 and it's ending up being discarded. 22 00:01:07.469 --> 00:01:11.541 Therefore, my project uses a non-hypothetical option 23 00:01:11.541 --> 00:01:14.866 to ask consumers their maximum willingness to pay, 24 00:01:14.866 --> 00:01:17.780 or their maximum bid, for sweet potatoes 25 00:01:17.780 --> 00:01:20.607 with five different skinning level injuries. 26 00:01:20.607 --> 00:01:25.179 We had 88 participants of varying demographic backgrounds 27 00:01:25.179 --> 00:01:28.393 and asked them each their maximum willingness to pay 28 00:01:28.393 --> 00:01:30.840 for each of these five different sweet potatoes 29 00:01:30.840 --> 00:01:34.964 before and after a set of information was given. 30 00:01:34.964 --> 00:01:37.222 This information varied depending upon 31 00:01:37.222 --> 00:01:38.943 the group you were in. 32 00:01:38.943 --> 00:01:41.152 Group one received information 33 00:01:41.152 --> 00:01:44.929 on how aesthetic preferences contribute to food waste. 34 00:01:44.929 --> 00:01:47.990 Group two received the same information 35 00:01:47.990 --> 00:01:49.706 and received information 36 00:01:49.706 --> 00:01:53.232 on the environmental impacts of food waste. 37 00:01:53.232 --> 00:01:55.411 From this graph, it appears 38 00:01:55.411 --> 00:01:57.964 that giving consumers information 39 00:01:57.964 --> 00:02:02.375 on how aesthetic preferences contribute to food waste alone 40 00:02:02.375 --> 00:02:05.458 creates a 17 cents per pound premium. 41 00:02:06.410 --> 00:02:07.657 Adding this information 42 00:02:07.657 --> 00:02:10.800 about the environmental impacts of food waste 43 00:02:10.800 --> 00:02:14.876 creates approximately a 33 cents per pound premium. 44 00:02:14.876 --> 00:02:18.405 While these numbers are based upon average bids alone, 45 00:02:18.405 --> 00:02:22.039 we are currently estimating econometric models to determine 46 00:02:22.039 --> 00:02:24.795 if these are statistically significant 47 00:02:24.795 --> 00:02:27.831 and what demographic backgrounds contribute 48 00:02:27.831 --> 00:02:30.544 to the demand for these products. 49 00:02:30.544 --> 00:02:32.354 My research has implications 50 00:02:32.354 --> 00:02:34.583 for the economic research service 51 00:02:34.583 --> 00:02:37.738 as they continue to further investigate methods 52 00:02:37.738 --> 00:02:40.481 and opportunities to mitigate food waste. 53 00:02:40.481 --> 00:02:42.108 Thank you. 54 00:02:42.108 --> 00:02:44.691 (upbeat music)