The Leading Indicator Properties of Surveyed Consumer Attitudes and Buying Intentions
Bibliographic record
Abstract
The author attempts to discover whether the Conference Board of Canada's Survey of Consumer Buying Intentions is a useful leading indicator of consumer durable expenditure. Two aspects of the Survey are considered separately, the overall Index of Consumer Attitudes and the various buying intentions questions. Both are tested using bivariate reduced form Granger techniques and structural models of consumer behaviour. The results of the tests indicate that movements in the Index of Consumer Attitudes do tend to lead movements in durables expenditure by one quarter. This conclusion holds whether one uses the actual published Index, a variant including neutral responses, or a filtered version of the Index, where the filtered version is calculated as in a number of American studies. The relationship is especially significant for expenditures on automobiles and parts. There is little indication, however, that buying intentions as recorded in the Survey are useful leading indicators of subsequent consumer behaviour. Only in the furniture and floor coverings category is there a significant positive relationship between intentions and expenditure, and it is contemporaneous. One reason is that, while the Survey indicates what proportion of households intend to purchase certain items, it does not measure relative values of the intended purchases. Thus, a failure to link buying intentions with future expenditure is not an indictment of the accuracy or the validity of the Survey in its own terms.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 teacher head, 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".