| Chapter | Data Sources | Measurement and Valuation Issues | Understanding GVCs and Policy Issues |
|---|---|---|---|
| 2. Multinational Firms and Global Innovation | Orbis data (Bundesbank’s MiDi in future work); EPO’s PATSTAT (German firms only) | Merging these two databases provides inventor location to determine whether production and innovation are colocated; patent data provides information on the type (basic, applied product, or applied process) and quality of innovation. | Better understanding of production and innovation location decisions by MNEs; future work can examine changes in IP rights, tax policy, and FDI policy on MNE production and innovation decisions. |
| 3. Tracing Value Added in the Presence of Multinational Firms with an Application to High-Tech Sectors | OECD Analytical AMNE database | Current TiVA analysis misses about 10 percent of FDI-related GVC activity in terms of global GDP; this paper provides a framework for accounting for FDI in GVCs. | Understanding the importance of FDI is important for bilateral trade treaties. |
| Chapter | Data Sources | Measurement and Valuation Issues | Understanding GVCs and Policy Issues |
|---|---|---|---|
| 4. Trade in Services, Intangible Capital, and the Profit-shifting Hypothesis | Italian firm-level data from the Bank of Italy | Highlights need for additional understanding of where intangible capital, such as an intellectual property product, is produced versus assigned. | Tax policy and whether firms are shifting profits to avoid taxes. |
| 5. Talent, Geography, and Offshore R&D | Orbis data merged with PATSTAT data (37 countries) | Highlights the need to identify firms by both nationality and location. | Should countries subsidize domestic innovation or encourage foreign affiliates? Implications for restrictions on immigration and trade on labor productivity within a country. |
| 6. The Nature and Direction of Innovation in Global Value Chains for Wind-Energy Technologies | Wind-energy reports from Navigant; wind-energy needs from IEA | Case study for wind-energy industry, which may help improve official statistics. | Does the location of suppliers affect the temporal component of innovation (in other words, does offshoring innovation decrease long-term innovation)? |
| 7. Economies of Scope and Relational Contracts: Exploring Global Value Chains in the Automotive Industry | U.S. Customs microdata (LFTTD) (U.S. and Japanese automobile manufacturers) | Case study for automobile manufacturers using microdata; ownership identified by manufacturer ID to help understand buyer–supplier links. | Trade policies are partly determined by economies of scope among suppliers. Provides insight into the organizational strategy of firms in the United States versus Japan. These data may help understand the resiliency of GVCs in the wake of supply shocks, such as those resulting from the COVID-19 pandemic. |
| 8. Foreign Direct Investments and Superstar Spillovers: Evidence from Firm-to-Firm Transactions | National Belgian Bank (NBB) business-to-business transaction dataset merged with Central Balance Sheet company accounts data; FDI info from NBB FDI survey; Intrastate trade survey; customs data | Evidence regarding value of superstar value chains. | Informs government policies intended to attract MNEs by providing information about spillovers to the host country from foreign MNEs. |
| 9. Creation and Diffusion of Knowledge in the Global Firm | PATSTAT and USPTO merged with firm and affiliate information from Orbis and Orbis IP databases | Merging IP data from patent offices with Orbis provides information on inventors’ location, gender, and other characteristics. | Provides information about inventor mobility and ability of MNEs to diffuse knowledge across borders; time zone differences and physical distance are barriers to collaborative innovation. |
| 10. Firm Selection and Organizational Choice: Complex Patterns of Global Sourcing | Survey data collected by Statistics Denmark (3 waves) | Manufacturing offshoring surveys provide critical information about type of activities that are offshored and changes in activity over time; provides information on inter-firm versus intrafirm sourcing. | Provides information on complex outsourcing patterns to help understand firms’ make/buy decisions. |
| Chapter | Data Sources | Measurement and Valuation Issues | Understanding GVCs and Policy Issues |
|---|---|---|---|
| 11. Are Customs Records Consistent Across Countries? | U.S. customs import microdata (LFTTD) and Columbian export data | Understanding the accuracy of firm-to-firm transactions data in international trade and GVCs; there is a growing gap in aggregate trade data, especially for smaller value shipments and nonwholesale retailers. | Using firm-to-firm networks and GVCs could find imaginary links in networks and may be not be correctly measuring the duration of relationships. These data are used to enforce commercial policy, but poor data may make it difficult to identify bad actors. |
| 12. Capital Flows in Global Value Chains | BEA Capital Flow Tables and World Input-Output Tables | Understanding capital flows in GVCs. | Gains from trade liberalization may not be captured using existing frameworks. |
| 13. Colocation of Production and Innovation: Evidence from the United States | Longitudinal Business Database (LBD), NAICS classifications and establishment geocodes from the Business Register; LFTTD Database; R&D surveys, USPTO database. | Merging multiple data sources provides location data to help understand trade in IP within firms. | Relationship between production and innovation; can help understand how policy-induced changes to R&D, such as R&D tax credits, affects manufacturing decisions. |
NOTES: AMNE = Activity of Multinational Enterprises; EPO = European Patent Office; FDI = foreign direct investment; GDP = gross domestic product; GVC = global value chain; IEA = International Energy Agency; IP = intellectual property; LFTTD = Longitudinal Foreign Trade Transactions Database; MNE = multinational enterprise; NAICS = North American Industry Classification System; OECD = Organisation for Economic Co-operation and Development; PATSTAT = Patent Statistical database; R&D = research and development; TiVA = trade in value added; USPTO = U.S. Patent and Trademark Office.