Development policy needs for data on remittances Valsa Shah Economic Adviser DFID 24 Jan 2005
Page 2 Weakness of existing data Country BoP data - top down Contaminated Definition problems – e.g. contain MTOs and banks? No measure on informal sector Aggregated Pro poor? Average value Frequency Channel
Page 3 Use of data 1: Remittance Country Partnership work Nigeria Ghana Bangladesh Objectives: Improve pro poor financial access Reduce costs and barriers Improve capacity in the financial sector
Page 4 RCP Recommendations - Government Payment systems Macro impact on receiving economy Encourage ID systems Education and awareness E money legislation Tackling competition issues
Page 5 RCP Recommendations: private sector development Improve rural access Improve IT systems investment Encourage corresponding agreements between banks Encourage private sector to provide innovative banking products
Page 6 Use of data 2: Sending end (UK) financial sector Lack of data = entry barrier Awareness raising of market opportunities Influence investment Encourage competition Improve transparency
Page 7 What are we looking for? Household surveys Average value Volumes Frequency Method of flow Reasons for using method Formal/informal split Status of sender/beneficiary + ID End user prices Trends over time
Page 8 Products and price surveys (sending and receiving countries) Comparison of products available Price comparison Consumer information guide Encourage competition and innovation between competitors
Page 9 Verify statements Remittance beneficiaries are poor The poor are more likely to be users of informal methods The value of informal remittance flows is very significant There are significant numbers of illegal migrants sending money back