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Kiyohiko G. Nishimura Professor of Economics, University of Tokyo Executive Research Fellow, ESRI, Cabinet Office Member, Statistical Council. Using Knowledge to Boost Competitiveness: Comments on Three Presentations. Identify “Success Factors” in competitiveness

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Using knowledge to boost competitiveness comments on three presentations

Kiyohiko G. Nishimura

Professor of Economics, University of TokyoExecutive Research Fellow, ESRI, Cabinet Office

Member, Statistical Council

Using Knowledge to Boost Competitiveness: Comments on Three Presentations


Burgi schmelz s paper

Identify “Success Factors” in competitiveness

Impact of Science and Technology

Measurement: # of patents and R&D share in GDP

Impact of Human Capital

Measurement: Rate of Return on education (private/social)

Suggest positive correlation between success factors and competitiveness

Emphasize importance of the above measured indicators and others (CO2, health care, higher education) in guiding policies in “Knowledge-based economies

Burgi-Schmelz’s Paper


Rosted s presentation

Identify Total Factor Productivity (TFP) or Multi-Factor P (MFP) as one of the most important determinants of competitiveness

Identify factors influencing TFP/MFP and search indicators representing them

Human resources

Knowledge accumulation and networking

ICT capital stocks

Entrepreneurship

Identify the most important policy areas based on the results

Rosted’s Presentation


Murray s presentation

Identify “adult skills” a major determinant of competitiveness.

Propose indicators of these crucial “adult skills” based on educational assessment and household survey methods

Show some success of these indicators in explaining employability and wage differences

Discuss remaining data problems as well as policy-implementation ones based on these indicators

Murray’s Presentation


Three presentations

A wealth of information is found about aggregate indicators of probable determinants of competitiveness

A focus on cross-country performance differences and their determinants

Crucial role of indicators (statistics) to guide public policy

Three presentations


What can be added to them disaggregated micro micro analysis

Complexity of probable determinants of competitiveness

Results based on simple correlation on an aggregate of some indicators of “competitiveness” or “achievement” and that of indicators of “determinants” are suggestive but not entirely convincing

To entangle complexity, disaggregated analysis are needed: industry-level and period-wise

Even further disaggregation may be helpful: firm-level and consumer-level analyses

What can be added to them?Disaggregated/Micro-micro Analysis


Determinants of competitiveness

Supply-side – Push factors of probable determinants of competitiveness

Total Factor Productivity (TFP) (level/growth)

Improved labor inputs

Innovation

Demand-side – Pull factors

Consumer attitude (adjustability)

Changing needs (aging, etc.)

Determinants of Competitiveness


Heterogeneity is a key factor

Wide difference among industries and periods of probable determinants of competitiveness

Nishimura and Shirai, “Can Information and Communication Technology Solve Japan’s Productivity-Slowdown Problem?” Asian Economic Papers 2 (1) (2003), 85-139. TFP Growth

Heterogeneity is a key factor


Firm level competitiveness research

Nishimura and Kurokawa “Total Factor Productivity in Japanese Information Service Industries: Firm-Level Analysis” 2004, available at ESRI website.

Census-like Government Statistics (all firms engaging information services)

Activity-level calculation of Total Factor Productivity of firms

Heterogeneity is properly accounted for (Panel Analysis with Firm-Specific Effect)

Firm-Level Competitiveness Research


Organizational structure matters

To achieve high productivity, firm’s organizational structure should be changed

Seemingly productivity-enhancing outsourcing has in fact negative effects on productivity

Clear indication of a pitfall in “best practice” methodology/policy

Large adjustment costs

Employment adjustment costs on productivity

Organizational adjustment costs on productivity

Organizational structure matters


Consumer and knowledge based economy

Nishimura and Morita “Alienation in the Internet Society: Changes in Car Buyer Attitudes in the Japanese Automobile Industry,” International Journal of Automobile Management and Technology 2 (2) (2002) 190-205

Conduct Interview-based Sample Surveys about Automobile Drivers in 1999 and 2001

Respondents roughly represent the whole Japanese automobile drivers.

The ratio of Internet users to all car owners was doubled between 1999 and 2001, from 16% to 32%

Examine the magnitude of Internet’s influence on car purchasing behavior

Examine changes between 1999 and 2001

Investigate not only Internet users but also non-Internet users

Consumer and Knowledge-Based Economy


Ailenation in internet society

Surprisingly, the major change has occurred among non-Internet users, not in Internet users

New, Internet-driven strategies of manufacturers and dealers ignore non-Internet users

non-Internet users were increasingly disappointed and alienated

losing interests in cars in general and human relations with salespersons

Internet society is likely to leave consumers segmented and diversified. Some are not so happy.

Ailenation in Internet Society


Conclusions

Three papers: a good start in a right direction non-Internet users, not in Internet users

Must be cautious to derive policy conclusions from their results … Competitiveness in a knowledge-based economy is a very complex animal to investigate.

More emphasis on micro-level research to enrich our understanding of competitiveness in knowledge-based economies

Conclusions


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