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OECD Working Party on International Trade in Goods and Trade in Services Statistics November 2011 Australian Bureau of Statistics Foreign Affiliate Trade in Services

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OECD Working Party on International Trade in Goods and Trade in Services Statistics November 2011

Australian Bureau of Statistics

Foreign Affiliate Trade in Services

Overview

• BoP covers resident to non-resident activity

• From this perspective, trade by foreign affiliates is considered non-resident

• Trade by foreign affiliates important for trade negotiations and understanding reach of an economy

Overview (continued)

• Service providers can and do establish overseas presence

• The WTO’s General Agreement on Trade in Services (GATS) identifies four “modes of supply”

• Wider definition than BoP

Modes of Supply

Modes of Supply

ABS Studies

• Australian Outward Finance and Insurance Foreign Affiliate Trade, 2009-10 (5485.0)

• Australian Outward Foreign Affiliate Trade, 2002-03 (5495.0)

• Economic Activity of Foreign Owned Businesses in Australia, 2000-01 (5494.0)

SOFI FATS

• Survey of Outward Finance and Insurance Foreign Affiliate Trade in Services (SOFI FATS)

• Survey funded by the Australian Department of Foreign Affairs and Trade (DFAT)

• Limited Resources• No funding for inwards equivalent

SOFI FATS (continued)

• Run in respect of the 2009-10 reference period– only for OUTWARD trade

– only for the finance and insurance industry

• Survey in 2002-03 identified finance and insurance industry as the largest services industry

• Sent to ALL Australian enterprises who may have affiliates overseas that primarily trade in finance and/or insurance

SOFI FATS (continued)

• Only affiliates that were controlled by Australian resident enterprises were included (i.e. greater than 50% ownership)

• Frame created from a question about direct investment in the International Investment survey.

• Direct investment includes all investment where the investor owns 10% or more of total equity capital.

SOFI FATS (continued)

• Survey collected data on:

– Number of affiliates– Employment, wages and salaries– Sales and purchases of services– Equity and profit

• FISIM and GVA data were derived from the data collected

SOFI FATS (continued)

• Processing was done using IPS and Microsoft EXCEL

• Confidentiality – ABS confidentiality rules– Perturbation– Collapsing cells

The Form

• Very detailed

• Large provider burden

• Asked for Balance sheet information, and detailed profit/loss statements

• Electronic and utilised macros

• Split between resident/non-resident was key

The Form (continued)

• Original plan to send to affiliates, but feedback indicated that parents wished to complete themselves

Results

• 30 Australian enterprises with 1,245 finance and insurance affiliates

• 70 Countries

Results (continued)

• 75,919 staff employed– $6.7 billion in wages and salaries

paid.

• $71.1 billion in Australian equity

• $6.5 billion in profit

• New Zealand, United Kingdom and the United States dominated data.

Results (continued)

• $39b in finance & insurance sales• FISIM high proportion of total sales• 96% of sales (mode of supply 3)• Shows most activity in host country

Global Financial Crisis Impacts

• GFC likely to have impacted profits.• Return on equity 6.8%• Difficult to measure impact• Ratio of income earned to stock down.

Global Financial Crisis Impacts (continued)

• Americas only $99 million profit.• Rates of return on equity for each

region:– Americas -0.1%– Europe 2.7%– Asia-Pacific 13.2%

2002-03 2009-10 Comparison

• Number of affiliates rose from 463 to 1245 (169%)

• Sales (excl. FISIM) rose 11%• Purchases (excl. FISIM) rose 150%

Conclusion

• Unlikely for a survey like this to be run in near future

• Prefer to cover all industries

• Prefer to collect both inward and outward

• OECD provided useful comments which will be used in future studies

Discussion points

• Experience of other countries

• Managing expectations from a client-funded survey

• Impact of confidentiality

• Testing data collection from non-residents

• The challenge of presenting asymmetrical views of data