Budget deficits and money creation: Exploring their relation before Bretton Woods. Replication data.
Bibliographic record
Abstract
PROJECT DESCRIPTION: <br>Replication package for Sabate, Marcela; Fillat, Carmen; Escario, Regina: “Budget deficits and money creation: Exploring their relation before Bretton Woods”, to be published in Explorations in Economic History (accepted December 2018). <br>Panel of seventeen countries from 1870 to 1938. Ten countries are sometimes-floaters before the WWI: Argentina, Bulgaria, Brazil, Chile, Greece, Italy, Japan, Portugal, Romania and Spain. Seven countries are never-floaters before the WWI: Canada, Finland, the Netherlands, Norway, Sweden, the UK and the USA. <br><br> Equation8.dta (Stata format): Data of public budget, monetary base and nominal GDP. <br><br>Replication program Equation 8 offers a dynamic heterogeneous estimation of variations in the monetary base on the budget balance. <br><br>Equation9.dta (Stata format): Data of variations in the monetary base, real GDP per capita( in 1990 Geary-Khamis dollars), average of public spending level , standard deviation of public spending levels, ratio of debt to nominal GDP and number of cabinet changes per year. <br><br>Replication program Equation 9 offers a dynamic panel estimation of variations in the monetary base on the rest of variables. <br><br>Abstract of the paper: The sovereign debt crisis in the Eurozone has rekindled the use of the North-South (core-periphery) terminology to refer to the heterogeneity of countries belonging to the Economic and Monetary Union (EMU). In the gold standard literature, this geographical partition had already been employed to oppose the fiscal profligacy and subsequent problems of convertibility of southern countries against the fiscal probity and long convertibility records of their northern counterparts. We provide statistical evidence that the group of countries that, with available data for 1870-1938, exhibited convertibility problems during the classical gold standard, for this reason called the pre-WWI sometimes-floaters, shared a pattern of fiscal dominance. This finding for the sometimes-floaters (southern European and South American countries plus Japan) differs from the non-fiscal dominance pattern that we obtain for the pre-WWI never-floaters (northern Europe and North America countries) when the Great War and its aftermath years are omitted. We also show that the presence of fiscal dominance was partly due to the lower levels of tax efficiency and political stability in the South. <br><br><br><br>
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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 | 0.005 | 0.053 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.006 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.115 | 0.040 |
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".