tpd_splice {PriceIndices} | R Documentation |
Extending the multilateral TPD price index by using window splicing methods.
Description
This function returns a value (or values) of the multilateral TPD price index (Time Product Dummy index) extended by using window splicing methods. Available splicing methods are: movement splice, window splice, half splice, mean splice and their additional variants: window splice on published indices (WISP), half splice on published indices (HASP) and mean splice on published indices (see References
).
Usage
tpd_splice(
data,
start,
end,
window = 13,
splice = "movement",
interval = FALSE
)
Arguments
data |
The user's data frame with information about sold products. It must contain columns: |
start |
The base period (as character) limited to the year and month, e.g. "2019-12". |
end |
The research period (as character) limited to the year and month, e.g. "2020-04". |
window |
The length of the time window (as positive integer: typically multilateral methods are based on the 13-month time window). |
splice |
A character string indicating the splicing method. Available options are: "movement", "window","half","mean", "window_published","half_published","mean_published". |
interval |
A logical value indicating whether the function is to provide the price index comparing the research period defined by |
Value
This function returns a value or values (depending on interval
parameter) of the multilateral TPD price index extended by using window splicing methods. Available splicing methods are: movement splice, window splice, half splice, mean splice and their additional variants: window splice on published indices (WISP), half splice on published indices (HASP) and mean splice on published indices (see References
). The time window starts in start
and should consist of at least two months. To get information about both price index values and corresponding dates, please see functions: price_indices
or final_index
. The function does not take into account aggregating over outlets or product subgroups (to consider these types of aggregating, please use the final_index
function).
References
Chessa, A. G. (2019). A Comparison of Index Extension Methods for Multilateral Methods. Paper presented at the 16th Meeting of the Ottawa Group on Price Indices, 8-10 May 2019, Rio de Janeiro, Brazil.
de Haan, J., van der Grient, H.A. (2011). Eliminating chain drift in price indexes based on scanner data. Journal of Econometrics, 161, 36-46.
de Haan, J. and F. Krsinich (2014). Time Dummy Hedonic and Quality-Adjusted Unit Value Indexes: Do They Really Differ? Paper presented at the Society for Economic Measurement Conference, 18-20 August 2014, Chicago, U.S.
Krsinich, F. (2014). The FEWS Index: Fixed Effects with a Window Splice? Non-Revisable Quality-Adjusted Price Indices with No Characteristic Information. Paper presented at the UNECE-ILO Meeting of the Group of Experts on Consumer Price Indices, 2-4 May 2016, Geneva, Switzerland.
de Haan, J.(2015). A Framework for Large Scale Use of Scanner Data in the Dutch CPI. Paper presented at the 14th Ottawa Group meeting, Tokyo, Japan.
Diewert, W.E., and Fox, K.J. (2017). Substitution Bias in Multilateral Methods for CPI Construction using Scanner Data. Discussion paper 17-02, Vancouver School of Economics, The University of British Columbia, Vancouver, Canada.
Examples
tpd_splice(milk, start="2018-12", end="2020-02",splice="half")