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Record W4293090565 · doi:10.4324/9780203015292-4

Globalization and economic development

2006· book-chapter· en· W4293090565 on OpenAlexaboutno aff
Masahiro Kawai

Bibliographic record

Venuenot available
Typebook-chapter
Languageen
FieldEconomics, Econometrics and Finance
TopicIndian Economic and Social Development
Canadian institutionsnot available
FundersInter-American Development BankAfrican Development Bank Group
KeywordsPovertyCreditorSustainable developmentBusinessInternational developmentPoverty reductionEconomic growthDevelopment economicsFinancial systemEconomyPolitical scienceDebtFinanceEconomics

Abstract

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There are a number of multilateral development banks (MDBs) in the world. The World Bank is a global MDB, while the Asian Development Bank (ADB), the Inter-American Development Bank (IDB), the African Development Bank (AfDB), and the European Bank for Reconstruction and Development (EBRD) are major regional MDBs (see Table 2.1). 1 These MDBs typically have two groups of members: one group includes developing countries that need external official financing for their economic development and, hence, are potential borrowers from the MDBs; another group consists of developed countries that have the capacity to finance the development needs of the former group and, hence, are potential creditors. Table 2.1 Organization of multilateral development banks (as of December 2001) https://www.niso.org/standards/z39-96/ns/oasis-exchange/table"> Organization World Bank Group Asian Development Bank Inter-American Development Bank Group African Development Bank European Bank for Reconstruction and Development Reference: IMF IBRD IDA IFC MIGA OCR ADF IDB IIC AfDB AfDF OC FSO MIF Year Established Dec. 1945 Sept. 1960 July 1956 April 1988 Aug. 1966 June 1974 Dec. 1959 Dec. 1959 Jan. 1993 Mar. 1986 Sep. 1964 June 1973 April 1991 Dec. 1945 Head Office Washington, DC (USA) Manila (Philippines) Washington, DC (USA) Abidjan (Cote d’Ivoire) London (UK) Washington, DC Objectives Sustainable economic development and poverty reduction through concessional loans and technical assistance (TA). Economic development through investment and loans to the private sector. Promoting private FDI through guarantees against noncommercial risks. Poverty reduction with focus on sustainable economic development, social development and good governance through loans and technical assistance. Economic and social developments of central and south American countries through concessional loans. Promoting private investment through assistance to small sized firms. Economic development through investment and loans to private SMEs. Economic development and social progress of African member countries through loans. Economic transition of the central and eastern European countries through loans, investment, guarantees and TA to private firms and privatizing SOEs. Monetary cooperation, exchange rate stability, ST financing for BOP imbalances. Membership Number 183 162 175 155 60 46 28 38 77 26 plus AfDB 60 plus EC and EIB 183 Eligibility IMF members IBRD members ESCAP members and non-regional developed UN members IOA members, and non-regional IMF members Capital (million) $189,505 SDR 8,647 $2,450 $1,957 $43,834 $19,963 $100,959 $9,480 $1,231 $704 $28,495 $14,231 EUR 20,000 SDR 213,700 Shareholders (%) USA 16.9 20.9 24.1 16.5 15.9 16.7 30.0 50.8 40.6 25.8 6.9 12.2 10.0 17.4 Japan 8.1 18.7 6.0 6.8 15.9 37.6 5.0 5.6 40.6 3.5 5.7 14.2 8.5 6.2 Germany 4.6 11.0 5.5 3.8 4.4 6.5 1.9 2.4 2.4 2.0 4.3 10.0 8.5 6.1 England 4.4 7.3 5.1 4.6 2.1 4.3 1.0 1.8 – – 1.8 3.6 8.5 5.0 France 4.4 7.3 5.1 5.1 2.4 4.8 1.9 2.2 1.2 3.2 4.8 2.8 8.5 5.0 Canada 5.3 7.1 4.0 3.1 Loans Annual (million) $10,487 $6,764 $5,357 $2,000 $3,977 $1,362 $7,411 $443 – $128 $1,099 $1,472 EUR 3,656 SDR 7,680 Outstanding (m) $118,866 $86,572 $10,909 $5,179 $28,659 $14,832 $44,951 $6,637 – $381 $8,554 $7,602 EUR 6,327 SDR 50,300 Terms of Lending Interest Rate LIBOR + 75-80 bp zero Market rate LIBOR + 60 bp 1.0% (grace period)/1.5% 6.38% 1-2% Market rate 7.16% zero LIBOR + - SBA, EFF: 50-600 bp 3.07% - PRGF: 0.5% – SBA, EFF: 3–10 PRGF: 10 (5.5) Maturity (years) 15-25 LLDC & IDA-only: 40 Others: 35 8-12 Within 15 15-30 24 or 32 15-30 25-40 Case by case 5-12 20 50 5-15 (grace period) (3-5) (10) (20) (3-7) (8) (4-5) (5-10) (5) (Max 5) (10) Service Charge – 0.75% – 0.50-1.25% 0.75% Commitment fee 0.75-0.85% – 0.50-1.00% 0.75% 0.75% 0.5% 0.50-1.00% 1.00% No. Professionals 3,436 825 65 749 1,243 53 587 613 1,799 Source: Ministry of Finance, Japan.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.844
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.006

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 head0.018
GPT teacher head0.180
Teacher spread0.161 · 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; both teacher heads agree on what is shown here.

Study designTheoretical or conceptual
Domainnot available
GenreOther

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".

Quick stats

Citations0
Published2006
Admission routes1
Has abstractyes

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