Measuring success in the global economy - W.E. Upjohn Institute for ...
Measuring success in the global economy - W.E. Upjohn Institute for ...
Measuring success in the global economy - W.E. Upjohn Institute for ...
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work will cont<strong>in</strong>ue on <strong>the</strong> causes and mean<strong>in</strong>g of <strong>in</strong>ter-<strong>in</strong>dustry trade.<br />
But <strong>the</strong>re are limits to what can be learned from trade statistics alone.<br />
4. Us<strong>in</strong>g adm<strong>in</strong>istrative and micro-data resources to<br />
understand <strong>global</strong> value cha<strong>in</strong>s<br />
L<strong>in</strong>k<strong>in</strong>g trade statistics to o<strong>the</strong>r datasets can enhance <strong>the</strong>ir<br />
usefulness. Through careful match<strong>in</strong>g, or by tak<strong>in</strong>g advantage of<br />
especially rich adm<strong>in</strong>istrative data, 7 researchers can sometimes push<br />
beyond <strong>the</strong> limitations of published statistics. A host of government<br />
programs collect detailed economic data. Typically more detailed<br />
“micro-data” underlie what is ultimately made available to <strong>the</strong> public.<br />
While <strong>the</strong>se data are usually confidential, researchers who ga<strong>in</strong> security<br />
clearance and have <strong>the</strong>ir proposals accepted by data collection agencies<br />
can ga<strong>in</strong> access, as along as government personnel screen <strong>the</strong> results<br />
be<strong>for</strong>e <strong>the</strong> research is published. Some micro-data sets have also been<br />
assembled by data agencies and released, with confidential <strong>in</strong><strong>for</strong>mation<br />
removed, as public-use files. Over <strong>the</strong> past decade, a burgeon<strong>in</strong>g body of<br />
research has relied on government-collected micro-data. In this section,<br />
we provide a few examples.<br />
Feenstra and Hanson (2004, 2005) take advantage of adm<strong>in</strong>istrative<br />
data from Ma<strong>in</strong>land Ch<strong>in</strong>a and Hong Kong (Ch<strong>in</strong>a) to reveal new<br />
<strong>in</strong><strong>for</strong>mation about <strong>the</strong> work<strong>in</strong>gs of GVCs. Specifically, <strong>the</strong> data conta<strong>in</strong><br />
re-export values <strong>for</strong> Hong Kong and <strong>in</strong><strong>for</strong>mation about factory and<br />
<strong>in</strong>put ownership <strong>in</strong> Ch<strong>in</strong>a. These data allow <strong>the</strong> authors to estimate <strong>the</strong><br />
mark-up charged by Hong Kong-based GVC “<strong>in</strong>termediaries” such<br />
as Li and Fung, a trad<strong>in</strong>g company. The authors also use <strong>the</strong>se data to<br />
calculate <strong>the</strong> share of Ch<strong>in</strong>a’s exports to Hong Kong that are re-exported<br />
(45.4% <strong>in</strong> 1998), an <strong>in</strong>dicator of <strong>the</strong> important coord<strong>in</strong>ation role that<br />
companies like Li and Fung play <strong>in</strong> GVCs, especially <strong>in</strong> apparel and<br />
o<strong>the</strong>r consumer-goods <strong>in</strong>dustries. By tak<strong>in</strong>g advantage of data that<br />
describe <strong>the</strong> ownership of factories export<strong>in</strong>g from Ch<strong>in</strong>a, <strong>the</strong> authors<br />
are able to show that <strong>in</strong>dependent suppliers work<strong>in</strong>g under “export<br />
process<strong>in</strong>g” arrangements (i.e., suppliers that are provided with <strong>in</strong>puts<br />
by <strong>in</strong>termediaries and <strong>the</strong>ir customers) are much more likely to send<br />
goods through Hong Kong <strong>for</strong> re-export than export<strong>in</strong>g factories that are<br />
wholly owned by non-Ch<strong>in</strong>ese firms.<br />
Feenstra and Spencer (2005) use <strong>the</strong> same Ch<strong>in</strong>ese data, from<br />
1998 through 2000, to explore <strong>the</strong> relationship between outsourc<strong>in</strong>g<br />
7 Governments collect data <strong>for</strong> <strong>the</strong> purpose of adm<strong>in</strong>ister<strong>in</strong>g <strong>the</strong>ir programs such<br />
as tax collection, compliance with environmental protection laws, and <strong>the</strong> like. For this<br />
reason such data is typically referred to as “adm<strong>in</strong>istrative data”.<br />
14 Transnational Corporations, Vol. 18, No. 2 (August 2009)