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Record W6920510416 · doi:10.6068/dp152b840634d89

TREND: International Monetary Fund. Balance of Payments: Direct Investment (Stocks) | Country: Afghanistan, Albania, Angola, Argentina, Armenia, Australia, Azerbaijan, Bahrain, Bangladesh, Belgium, Benin, Bhutan, Bolivia, Botswana, Brazil, Bulgaria, Burundi, Canada, Cape Verde, Chile, China, Colombia, Costa Rica, Cyprus, Czech Republic, Denmark, Dominican Republic, East Timor, Ecuador, Egypt, El Salvador, Estonia, France, Georgia, Germany, Ghana, Guatemala, Honduras, Hong Kong, Hungary, India, Indonesia, Iraq, Japan, Jordan, Kazakhstan, Kuwait, Lithuania, Luxembourg, Macedonia, Malawi, Malaysia, Malta, Marshall Islands, Mauritius, Mexico, Morocco, Mozambique, Namibia, Nepal, Netherlands, New Zealand, Nicaragua, Niger, Nigeria, Norway, Pakistan, Panama, Paraguay, Philippines, Poland, Portugal, Romania, Rwanda, Saudi Arabia, South Africa, South Korea, Spain, Sri Lanka, Tonga, Trinidad and Tobago, Turkey, Ukraine, United Kingdom, United States, Uruguay, Venezuela, Yemen | International Monetary Fund Subject: Direct investment | Code: 8A9999 A A, 8A9999 A A, 8A9999 A A, 8A9999 L A, 8A9999 L A, 1948 - 2014. Data-Planet™ Statistical Datasets by Conquest Systems, Inc. Dataset-ID: 056-006-017

2016· other· en· W6920510416 on OpenAlexaboutno aff

Bibliographic record

VenueData Planet · 2016
Typeother
Languageen
Field
Topic
Canadian institutionsnot available
Fundersnot available
KeywordsBalance of paymentsCurrencyForeign direct investmentInvestment (military)International financeMonetary policyBalance sheetBalance (ability)Investment fund

Abstract

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International Monetary Fund. Balance of Payments: Direct Investment (Stocks) | Country: Afghanistan, Albania, Angola, Argentina, Armenia, Australia, Azerbaijan, Bahrain, Bangladesh, Belgium, Benin, Bhutan, Bolivia, Botswana, Brazil, Bulgaria, Burundi, Canada, Cape Verde, Chile, China, Colombia, Costa Rica, Cyprus, Czech Republic, Denmark, Dominican Republic, East Timor, Ecuador, Egypt, El Salvador, Estonia, France, Georgia, Germany, Ghana, Guatemala, Honduras, Hong Kong, Hungary, India, Indonesia, Iraq, Japan, Jordan, Kazakhstan, Kuwait, Lithuania, Luxembourg, Macedonia, Malawi, Malaysia, Malta, Marshall Islands, Mauritius, Mexico, Morocco, Mozambique, Namibia, Nepal, Netherlands, New Zealand, Nicaragua, Niger, Nigeria, Norway, Pakistan, Panama, Paraguay, Philippines, Poland, Portugal, Romania, Rwanda, Saudi Arabia, South Africa, South Korea, Spain, Sri Lanka, Tonga, Trinidad and Tobago, Turkey, Ukraine, United Kingdom, United States, Uruguay, Venezuela, Yemen | International Monetary Fund Subject: Direct investment | Code: 8A9999 A A, 8A9999 A A, 8A9999 A A, 8A9999 L A, 8A9999 L A, 1948 - 2014. Data-Planet™ Statistical Datasets by Conquest Systems, Inc. Dataset-ID: 056-006-017 Dataset: Direct investment is a category of cross-border investment associated with a resident in one economy having control or a significant degree of influence on the management of an enterprise that is resident in another economy. Here, presented are stocks (or positions) of direct investment assets and liabilities for International Monetary Fund member countries. For each country, jurisdiction, or other reporting entity, the time series are provided as a balance and as assets and liabilities in national currency as available, and in United States dollars. The Balance of Payments Statistics (BOPS) database, published by the International Monetary Fund (IMF), contains time series of quarterly and annual BOPS data for more than 180 countries, jurisdictions, or other reporting entities. For some of these countries, the data have been supplemented by data IMF economists have derived from other sources. BOPS summarizes the economic transactions of a country with the rest of the world. It reports total goods, services, factor income, and current transfers an economy receives from or provides to the rest of the world, as well as capital transfers and changes in each economy’s external financial claims and liabilities. http://data.imf.org/?sk=7A51304B-6426-40C0-83DD-CA473CA1FD52 Entries in the international accounts are either flows or stocks, also called positions. The entries are recorded following a consistent set of accounting principles to ensure a complete integration of flows and positions as well as symmetry of recording between counterparties. Flows refer to economic actions and effects of events within an accounting period, and stocks, or positions, refer to a level of assets or liabilities at a point in time. Flows reflect the creation, transformation, exchange, transfer, or extinction of economic value; they involve changes in the volume, composition, or value of an institutional unit’s assets and liabilities. Generally, positions are shown at the beginning and end of an accounting period. Positions between two periods are connected with flows during that period because changes in positions are caused by transactions and other flows. Category: Banking, Finance, and Insurance, International Relations and Trade Subject: Foreign Investment, Liabilities, Assets, International Economic Organizations, Balance of Payments 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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.008
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Dataset · Consensus signal: Dataset
Teacher disagreement score0.986
Threshold uncertainty score0.585

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.008
Meta-epidemiology (narrow)0.0040.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0040.008
Science and technology studies0.0010.001
Scholarly communication0.0090.007
Open science0.0020.002
Research integrity0.0030.005
Insufficient payload (model declined to judge)0.1750.395

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.

Opus teacher head0.015
GPT teacher head0.260
Teacher spread0.246 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreDataset

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".

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Citations0
Published2016
Admission routes1
Has abstractyes

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