_ANDR EE_<sup>_ ́_</sup> _AND PAPE_ _SEPTEMBER 5, 2023_ _14_ seeks to track inflation over a long time period using a broad-as-possible food basket, a 25-item version that starts in 2017 that tracks a narrower basket of items that have better data coverage. There are minor item differences in the basket specification and data coverage, see Table 2.

Table 2—Summary of raw food price data in Papua New Guinea.

||Coverage|12-month|Items|Markets|
|---|---|---|---|---|
|2009-2022|36.96%|50.71%|25<sup>_∗_</sup>|8|
|2014-2022|29.17%|52.17%|25<sup>_∗∗_</sup>|8|
|2017-2022|39.01%|55.47%|27<sup>_∗∗∗_</sup>|7|
|FCS average|51.47%||7|27|

_Note:_ The first column reports the study period, the second column reports the data coverage across the full study period, the third column reports the data coverage in the last 12 months, the last columns reports the number of markets modeled out of the total number of markets included in the data snapshot. _∗_ Basket consists of 1 unit of each: _Aibika, Amaranthus-Aupa, Banana-Cooking, Banana-Ripe, Broccoli, Cabbage-English, Capsicum, Carrot, Cassava, Choko-Tips, Cucumber, Ginger, Lemon, Lettuce, Mandarine, Onion Bulb, Orange, Pawpaw, Peanut, Pineapple, Sweet Potato, Pumpkin-Tips, Taro True, Tomato, Watermelon. ∗∗_ Basket consists of 1 unit of each: _Aibika, Amaranthus-Aupa, Banana-Cooking, Banana-Ripe, Broccoli, Cabbage-English, Capsicum, Carrot, Cassava, Choko-Tips, Cucumber, Ginger, Lemon, Lettuce, Onion Bulb, Orange, Pakchoi, Pawpaw, Peanut, Pineapple, Sweet Potato, Pumpkin-Tips, Taro True, Tomato, Watermelon. ∗∗∗_ Basket consists of 1 unit of each: _Aibika, Amaranthus-Aupa, Banana-Cooking, Banana-Ripe, Broccoli, Cabbage-English, Capsicum, Carrot, Cassava, Choko-Tips, Cucumber, Fern, Ginger, Lemon, Lettuce, Onion Bulb, Orange, Pakchoi, Pawpaw, Peanut, Pineapple, Sweet Potato, Pumpkin-Tips, Taro True, Tomato, Watermelon, Wongbok. Source:_ The statistics have been prepared by the author for this paper based on end-of-July (2022) food price data from IFPRI. The FCS average has been reproduced from table A1 in Andr ́ee (2021) who presented identical estimates for 25 FCS countries (excluding PNG).

The first selection tries to optimize for what benefits historical studies and the key challenge is the lower data availability, the third selection tries to optimize for monitoring purposes of current trends and the key challenge is the shorter time dimension which makes trend modeling more difficult. In all cases, the foods are all fresh produce vegetables, and the baskets have strong item overlap. The application keeps the item weights fixed at 1 KG of each item when constructing the basket price. The resulting price index is a Laspeyres index that does not seek to adjust for changing consumption behavior that could in part be induced by relative price rises. This is appropriate in an extreme-poverty or food-insecurity context in which food accounts for the majority of household expenditures and shifts toward less nutritious foods may keep basket prices equal and at the same time create food and nutrition security risks.

Taken together, the data selection simulates the real-world challenge: when a new survey program is deployed, it is possible to design it so that a high number of food items will be tracked but the data will naturally be limited in temporal scope. As the program carries on for longer, it typically becomes more difficult to ensure that the full basket remains observed and so the food basket consisting of items with “good data coverage” narrows. Finally, over long time periods,