A re-examination of Wagner's law for ten countries based on cointegration and error-correction modelling techniques
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Bibliographic record
Abstract
Following Mann's (National Tax Journal, 33, 189–201, 1980) study, five different versions of Wagner's law are empirically examined using annual time-series data on ten countries over the period 1951 to 1996. Included are three of the emerging industrialized countries of Asia: South Korea, Taiwan, and Thailand, and seven industrialized countries: Australia, Canada, Japan, New Zealand, USA, the United Kingdom, and South Africa. The analysis is an advance over previous work in two respects. First, the stationarity properties of the data, the order of integration using the Augmented Dickey–Fuller (Journal of American Statistical Association, 74, 427–31, 1979, Econometrica, 49(4), 1057–72, 1981) test and the Kwiatkowski et al. (Journal of Econometrics, 1, 159–78, 1992) test are empirically investigated. Second, the hypothesis of a long-run relationship between income and government spending is tested using bivariate cointegrated systems and by employing the methodology of cointegration analysis as suggested by Johansen and Juselius (Oxford Bulletin of Economics and Statistics, 52, 169–210, 1990) and Johansen (Journal of Policy Modelling, 14, 313–34, 1992). Unidirectional Granger causality is found running from income to government spending for the newly industrialized countries of South Korea and Taiwan, and the industrialized countries of Japan, the United Kingdom, and the United States, supporting Wagner's hypothesis for those countries. For the five remaining countries in this study: Australia, Canada, New Zealand, South Africa, and Thailand, no causal relationship between income and government spending is found.
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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 | 0.000 | 0.000 |
| 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 it