House Price, Stock Price and Consumption in South Africa: A Structural VAR Approach
Bibliographic record
Abstract
This paper compares the effects of real house price and real stock price shocks on consumption \ndecisions in South Africa over the period 1966 to 2012 using a Structural Vector Autoregressive \n(SVAR) approach.The sample comprises quarterly, seasonally adjusted South African data on \nconsumption, inflation, real house price, real stock price and the nominal Treasury bill rate. We find \nthat a positive 1 percent shock in stock prices leads to about 0.05 percent increase in consumption, \nwith the effect being short-lived, and declines after 4 quarters to become statistically insignificant. \nWhile, a 1 percent shock in house prices increase consumption by about 0.3 percent at around the 4th \nquarter, but thereafter declines and becomes negative from the 8thquarter. These results show that in \nSouth Africa, house prices play economically, but not statistically, a greater role than stock prices with \nrespect to consumption expenditure.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".