TREND: International Monetary Fund. Currency Composition of Foreign Exchange Reserves (COFER): Currency Composition of Foreign Exchange Reserves (US Dollars) | Indicator: Total Foreign Exchange Reserves, 1995 - 2017. Data Planet™ Statistical Datasets: A SAGE Publishing Resource Dataset-ID: 056-022-001
Bibliographic record
Abstract
datasets.shared.infosheet.CitationMgr@83b Dataset: Data on the currency composition of official foreign exchange reserves (COFER) are reported in US dollars. Any type of financial instrument that is used to make payments between countries is considered foreign exchange. Examples of foreign exchange assets include foreign currency notes, deposits held in foreign banks, debt obligations of foreign governments and foreign banks, monetary gold, and SDRs. Unallocated Reserves is the difference between the total foreign exchange reserves in the International Financial Statistics (IFS) world table on Foreign Exchange and the total allocated reserves in COFER. It includes foreign exchange reserves of those countries/territories that currently do not report to COFER but whose total foreign exchange reserves are included in the IFS world table. The COFER database offers quarterly and annual data on the currency composition of official foreign exchange reserves reported in US dollars and as percentage of total foreign exchange reserves. As of December 2016, eight currencies are distinguished in COFER data: US dollar; euro; Chinese renminbi; Japanese yen; pound sterling; Australian dollar; Canadian dollar; and Swiss franc. All other currencies are included and indistinguishable in the category “other currencies.” COFER data are reported to the IMF on a voluntary and confidential basis. At present, there are 146 reporters, consisting of IMF member countries, a number of non-member countries/economies, and other entities holding foreign exchange reserves. COFER data are publicly disseminated on a quarterly frequency in aggregate format so as to safeguard individual country information. http://data.imf.org/?sk=E6A5F467-C14B-4AA8-9F6D-5A09EC4E62A4&sId=1408206195757 Category: International Relations and Trade Subject: Money, Assets, External Debt Source: International Monetary Fund Headquartered in Washington, DC, the International Monetary Fund (IMF) was conceived at a United Nations conference convened in Bretton Woods, New Hampshire, United States, in July 1944. The 44 governments represented at that conference sought to build a framework for economic cooperation that would avoid a repetition of the vicious circle of competitive devaluations that had contributed to the Great Depression of the 1930s. As of 2015, the IMF has 188 member countries. Its primary purpose is to ensure the stability of the international monetary system, specifically the system of exchange rates and international payments that enables countries (and their citizens) to transact with one other. This system is essential for promoting sustainable economic growth, increasing living standards, and reducing poverty. The Fund’s mandate has recently been clarified and updated to cover the full range of macroeconomic and financial sector issues that bear on global stability. The IMF is a specialized independent agency of the United Nations but has its own charter, governing structure, and finances. Its members are represented through a quota system broadly based on their relative size in the global economy. http://www.imf.org/
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.009 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.005 | 0.010 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.082 | 0.131 |
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".