1 Measuring Network Effects on Trade: Are Japanese Networks Distinctive? Theresa M. Greaney Department of Economics University of Hawai`i May 14-15, 2004

2 Research Questions: Networks w Do foreign affiliates behave differently from US firms in their trade patterns? w Among affiliates, do network effects have a significant impact on trade? w Has the strength of network effects changed over time? w My answers: yes, yes, no

3 Research Questions: Japan Networks w Do J affiliates behave differently from other countries’ affiliates in their trade pattern & participation? w Do J affiliates appear to have particularly strong networks & have these changed over time? w What are the implications for trade policy? w My answers: yes & yes, yes & no, ?

4 Related Literature w Empirical on networks--Gould (1994), Head & Ries (1998), Rauch & Trindade (2002) w Empirical on keiretsu trade effects--Fung (1991), Lawrence (1991), Ueda & Sasaki (1998), Head, Ries & Spencer (2004) w Theoretical on networks--Greif (1993), Rauch (1996), McLaren (1999), Kranton & Minehard (2001), Casella & Rauch (2002), Greaney (2002)

5 Research Methodology w Descriptive, comparative Measuring network effects through trade activities of foreign affiliates in the US…home trade bias w Gravity Model Is a network link between affiliates and their home country significant in predicting bilateral trade?

6 Data w Bureau of Economic Analysis’ survey Foreign Direct Investment in the US (1987, 1992, 1997)-- bilateral trade flows available for 8 countries’ affiliates (Australia, Canada, France, Germany, Japan, Netherlands, Switzerland, UK) w Statistics Canada World Trade Analyzer (1999)-- bilateral trade w IMF’s International Financial Statistics--GDP data

7 Descriptive Analysis w Tables 1-6 show BEA survey data for targeted country affiliates. w Table 7 breaks down US bilateral trade into trade by affiliates vs. trade by US firms. w Table 8 manipulates trade data to examine home bias in affiliates’ trade patterns.

9 Gravity Model Analysis w Basic gravity equation (Feenstra, 2002): w Add network dummy: HomeLink w Add continuous network variable: dist2 distance b/t affiliate’s trade partner and its home country w Add Japan network dummy: Japan

12 Results: Network Effects w Affiliates had much higher tendencies to trade w/their home countries than did US firms trade w/those same countries. w Home country bias was particularly strong for affiliates’ importing. w Affiliates tended to trade 14.2 times more with their home countries than w/other countries, controlling for distance, income & Japan effects.

13 Results: Network Effects, cont. w The distance between an affiliate’s home country & its trade partner is proposed as a new way to measure network effects separately from trade costs. w A 1% increase in this distance lowers trade by 0.35% when a country’s home trade bias is included, or by 0.20% w/out this bias.

14 Results: Japan Network Effects w Japanese affiliates accounted for 81% of US imports from Japan & 39% of US exports to Japan in 1997, much higher than other countries’ affiliates. w Only Canadian affiliates had higher levels of home trade bias in 1997, but several countries’ affiliates had higher home trade bias relative to US firm trade patterns.

15 Results: Japan Network Effects, cont. w Gravity model estimates support assertion that Japanese affiliates have unusually strong home trade bias, trading times more w/Japan, after controlling for distance & income. w No time trends found in networks or Japan networks variables for the period.

16 Possible Links to Trade Policy Research w Noland (1997) finds that Japan is targeted disproportionately (after controlling for country size) in US unilateral trade actions. w Strength of Japanese networks may help in explaining Noland’s result.