THE CPI MARKET BASKET: A REVIEW OF ECONOMIC AND MARKETING VALIDITY ISSUES
Bibliographic record
Abstract
INTRODUCTION The original impetus for present article came from our School of Business and Economics' Marketing and Entrepreneurship Department (within State University of New York College at Plattsburgh) acceptance, this in summer 2011, to take over Food Market Basket Data collection project. This project had been previously accomplished by a now defunct on-campus federally funded agency. This agency had been in charge of collecting, measuring, and reporting price fluctuations by surveying three (3) conventional supermarkets and one Wal-Mart Supercenter, all located in city of Plattsburgh, a rural setting (population of 22,000 people) in upstate New York, near U.S./Canada border. The survey instrument utilized was composed of forty-one (41) items. In September 2011, a quick perusal of Consumer Price Index (CPI hereafter) at home literature informed us that, within last 20 years, major changes had occurred within at home purchases by U.S. consumers. These changes, as reported by MacDonald (1995), were: 1. Shifts in consumer behavior such as in case of decreased purchases in food-at-home category because of increased purchases at restaurants; 2. Shifts in types of purchases such as purchasing of more fresh fruits and vegetables and less meat products; 3. Shifts in Amount of new products introduced in Supermarkets (for example, number of new products introduced in Supermarkets increased from 5,400 in 1984 to 12,300 in 1992) and 4. Shifts in amount and types of new retail outlets that sell as in case of a growing share of sales occurring outside conventional supermarkets such as at drug stores, at warehouse club stores, at mass merchandisers (or general discount retailers), and at convenience stores as well. Because we were informed that our inherited 41-food item survey instrument dated back to 1978, we suspected that these issues and shifts had not been accounted for. Our team agreed that an assessment of our survey instrument's validity was in order. Our initial quick perusal of CPI literature had equally revealed that there were a number of very important validity issues as to how Bureau of Labor Statistics (BLS hereafter) computed CPI that remained unresolved to this day. We decided that we would conduct an exhaustive literature review of both CPI at home category as well as CPI's other goods and services since CPI validity issues would concern all products surveyed by BLS, federal government agency responsible for computing and publishing CPI on a monthly basis. As we are marketing scholars and had neither previous knowledge nor experience with CPI, we believed this effort would help us, first, to best understand benchmark of price fluctuation indexes in U.S. and, second, help us make improvements to our survey instrument. WHY THE CPI MATTERS As stated by Schultze and Mackie (2002) the Consumer Price Index (CPI) is one of most widely used statistics in United States. As a measure of inflation it is a key economic indicator. It serves as a guide for Federal Reserve Board's monetary policy and is an essential tool in calculating changes in nation's output and living standards. It is used to determine annual cost-of-living allowances for social security retirees and other recipients of federal payments, to index federal income tax system for inflation, and as yardstick for U.S. Treasury inflation-indexed bonds. Invariably, as suggested by Boskin et Al. (1998) CPI impacts U.S. national budget and national debt as well. A DESCRIPTION OF THE CPI Essentially, CPI is a measure of average change in prices paid by urban consumers for a fixed market basket of goods and services including food (MacDonald, 1995). According to Wahl (1982) CPI is simply a fixed-weight index for measuring changes in consumer prices between a base period and a subsequent period, weights being established by typical expenditures of all consumers in base period. …
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.091 | 0.205 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.005 | 0.003 |
| Bibliometrics | 0.030 | 0.037 |
| Science and technology studies | 0.002 | 0.009 |
| Scholarly communication | 0.013 | 0.015 |
| Open science | 0.005 | 0.003 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".