On January 6, 2016, the Ali Institute released alibaba Shopping Price Index-core items (aSPI-core) and also alibaba Shopping Price Index (aSPI) of December in 2015.
Online Shopping Price Level (aSPI-core)
In December 2015, aSPI-core which is used to measure the price level variation of mainstream online shopping commodities slightly dropped by 0.07%, demonstrating that the price level of mainstream online shopping commodities continued to drop slightly compared with the previous month. The year-on-year growth rate of aSPI-core of this month remains under zero, dropping by 1.67% which is 0.01 percentage point higher than the previous period.
According to the contribution rate to the aSPI-core of the commodities under the major categories, it was the decline of the traffic and communication commodities' price that caused the slight drop of the month-on-month growth rate of the aSPI-core. And the communication commodities encountered a general decline of the price. (Figure 1)
Figure 1 aSPI-core (%)
Month-on-month rate classification (aSPI-core):
Month-on-month rate classification:
Figure 2 Month-on-month rate classification variation of aSPI-core (%)
Year-on-year rate classification (aSPI-core):
Year-on-year rate classification
Figure 3 Year-on-year rate classification variation of aSPI-core (%)
Average Price Variation of Alibaba's Expense (aSPI)
The aSPI that is used to measure the average price variation of Alibaba's expense has seen an increase in month-on-month growth rate this month, with a rising volume of 2.68% in terms of Alibaba's expense; the year-on-year increasing rate of aSPI continues going up. The Alibaba's expense average price enjoys an increasing rate of 6.34% year-on-year which is 0.39 percentage point lower compared with the previous month. (Figure 4)
Figure 4 Alibaba Shopping Price Index (%)
Month-on-month rate classification (aSPI):
In terms of the average price of expense, among the aSPI of ten major categories, the average price of expense of nine major categories of commodities has risen. Among them, the classification of entertainment, educational and cultural articles and services has risen to the greatest extent, with a month-on-month increasing rate of 4.14%; only the price levels of traffic and communication commodities have decreased with a month-on-month decreasing rate of 0.57%. (Figure 5)
Month-on-month rate classification
Figure 5 Month-on-month rate classification variation of aSPI (%)
In terms of the average price of expense, among the aSPI of ten major categories, the average expense price of nine major categories of commodities has risen compared with the previous period in 2014. Among them, the classification of hobby investment commodities has risen to the greatest extent with a year-on-year increasing rate of 17.80%; only the price levels of clothing commodities have decreased with a year-on-year decreasing rate of 2.31%. (Figure 6)
Note: In order to show promptly the variation of the composing of the basic commodity categories on the Alibaba online retail platform, the selection and the weight of the basic categories adopted to calculate the aSPI-core index will be updated in January 2016.
Classification of the aSPI series
In order to establish authentic and reliable price index with the application of big data, all the transactions of commodities covered by the aSPI online shopping price index series are remapped as a four-level classification aSPI structure on the basis of the nine classifications on Taobao, with a reference to the classification structure applied in the retail price and the consumer price surveys.
Under this framework, the undividable smallest subcategories on the Taobao platform correspond to the basic categories in the fixed basket price index. The different commodities under same subcategories can be highly substituted for each other, while commodities under different subcategories enjoy a comparative less flexibility to do so; and the commodity-level SKU (stock per unit) corresponds to “product by specifications”, which means that different commodity items with the same SKU correspond to one same category defined by various attributes and specifications. And there is no difference in the actual use for consumers.
Currently, the Alibaba shopping price index series include two sets of index (Figure 7), one of which is the Alibaba Shopping Price Index where the life consumption theory is applied, called aSPI for short that is used to show the average expenditure price variations on the Alibaba online shopping platform. The other is the Alibaba Shopping Price Index (core-items) which is put forward on the basis of the fixed basket theory, called aSPI-core for short that shows the changes of the general price level of the mainstream online shopping commodities.
The two sets of indexes both consist of ten sub-indexes, namely food, cigarettes and wine, clothing, home appliances tools and maintenance services, medical care and personal care, traffic and communication, entertainment, educational and cultural articles and services, accommodations, office supplies and services, as well as hobby investment. Under the ten sub-indexes, there also includes price indexes for nearly 500 basic classifications.
Figure 7 aSPI vs. aSPI-core
The aSPI-core (Alibaba Shopping Price Index-core) refers to the fixed basket price index which picks out nearly 100,000 core commodities under the 500 basic categories on the Ali online retail platform as fixed baskets through innovative filtering algorithm. It keep tracks every month of the actual online transaction price changes of the commodities and services in the representative “broad fixed basket” of the current month to reflect the fluctuations in the general price level of the mainstream online shopping commodities and services so as to show the macro price trend through the picture of the online retail channels.
Alibaba shopping price index (aSPI) is calculated on the basis of the monthly variations of the average VWAP price of the commodities under the smallest undividable subcategories, with the transaction shares in the last month as the weight. It is used to reflect the changes of the overall online purchase price level. At the same time, it contains the information of the general price changes on the level of goods and of the consumption structure variations under the undividable subcategories.
ASPI vs. aSPI-core
The aSPI-core is based on the transaction price of the strictly comparable products by specifications. It has small data errors and is highly consistent with the generally applied macro price index in terms of basic methodology. Therefore, it can be easily understood.
However, due to the frequent product replacement in modern society, the sale and prices of many products have a life-cycle characteristic, that is, when one product is first released, it can enjoy a relatively high premiums because there are little similar products, thus little alternatives on the market; however, as time goes on, more and more alternative products as well as technical updating products will show up and compete in the market, and the premium will be lower and lower. This characteristic brought by technological progress and market competition will bring a natural trend of falling prices, and consequently the fixed basket index in the long term are likely to underestimate the rising trend of the cost of consumption spending. As new products emerge and spread faster in the online retailing, the problem may be even more obvious.
Theoretically speaking, the Alibaba shopping price index (aSPI) based on the life consumption theory can overcome this limitation that the fixed basket index faces. What this price index is measuring is the change of the minimum spending levels brought by substitution effect on the consumption amount resulted from the relative price changes of products, with the prerequisite that the utility for consumers remains unchanged. If we consider the Taobao subcategories as collections of products highly substituted for each other, then the monthly changes in the average VWAP prices can be approximately seen as the reflection of the alternative spending choices of online customers under the circumstances that the price of products of the subcategories changes. Meanwhile, changes on the selection of quality caused by variation of incomes and expected revenues are also included.