Bibliometric evidence for empirical trade offs in national funding strategies
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Bibliometric evidence for empirical trade-offs in national funding strategies. Duane Shelton and Loet Leydesdorff. ISSI 2011 Durban. Outline. Modeling of Input-Output Relations Best Models from Correlations and Regression Trade-offs in Allocation of R&D investments

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Bibliometric evidence for empirical trade offs in national funding strategies

Bibliometric evidence for empirical trade-offs in national funding strategies

Duane Shelton and Loet Leydesdorff

ISSI 2011 Durban


Outline
Outline

Modeling of Input-Output Relations

Best Models from Correlations and Regression

Trade-offs in Allocation of R&D investments

Validation by Forecasts from Extrapolations, Regressions, and Individual Country Models

Conclusions


Some prior work
Some prior work

Leydesdorff. A series starting in 1990 with regression of papers with GERD. Most recently a 2009 publication with Wagner on which GERD components are best in encouraging papers .

Shelton. Started in 2006 modeling paper share as a function of GERD share to account for US decline. Recently a 2010 presentation with Foland using GERD components to account for the European Paradox.


Output dependent variables dvs
Output dependent variables (DVs)

  • Papers and Paper Share

    • Science Citation Index

    • Scopus

  • Patents and Patent Share

    • Triadic

    • USPTO

    • PCT

  • The full paper covers all; here we will focus on those in red.


Input variables ivs from oecd
Input variables (IVs) from OECD

Overall GERD (Gross Expenditures on R&D)

GERD source components:

Government

Industry

Abroad (funding from abroad)

Other

GERD spending components:

HERD (higher education sector)

BERD (business sector)

Non-Profit (other than universities)

GOVERD (government labs)

Number of researchers


Shares provide the best national comparisons
Shares provide the best national comparisons

Some indicators are nearly zero-sum: countries compete for a nearly fixed number of slots for paper publications and patent grants. (Paper submissions and patent applications are unbounded.)

The slots do rise slowly with time, and this complicates national comparisons.

Thus, in analyzing relative positions of nations, their share of most outputs is a more relevant indicator.

Modeling of the inputs that cause these output shares is also best done in shares.

Of course, once a model is built for shares, it can easily be used to calculate absolutes.


All inputs and outputs depend on the size of the country, making all country-wise correlations high, and obscuring identification of which variables are most important

One might divide all variables by some measure of size, but stepwise multiple linear regression can also tease out which input IVs are best for predicting output DV.

IVs are added one-by-one in order of which makes the best model for the DV.

The size of nations is a confounding factor


Step-wise regression of 2007 SCI paper share (ps07) vs. three IVs

Government GERD share

HERD share

Overall GERD share

Fit of regression line


Correlations: Papers vs. Inputs three IVs

Red indicates strongest correlation of pair; it will dominate a 2 IV model


Regressions of SCI paper share in 2007 three IVs

For example the best single IV model is:

Papers07 = 0.846 Governments07 + 0.316


Step-wise regression of 2007 triadic patent share (Patents07) vs. three IVs

Industry GERD share

Government GERD share

BERD share

Fit of regression line

Fit is OK, but not as good as paper models


Shelton, R. D. & Leydesdorff, L. (in preparation). (Patents07) vs. three IVs

Publish or Patent: Bibliometric evidence for empirical trade-offs in national funding strategies


Correlations: Patents vs. Inputs (Patents07) vs. three IVs

Red indicates strongest correlation of pair; it will dominate 2 IV model


Regressions for 2007 triadic patent share (Patents07) vs. three IVs

For example the best single IV model is:

Patents07 = 0.941 Industrys07 + 0.058


Regressions show a trade off in allocations
Regressions show a trade-off (Patents07) vs. three IVs in allocations

  • To maximize papers, a country should maximize its government funding of R&D, instead of industry funding

  • To maximize patents, a country should do the opposite: maximize its industrial funding of R&D, which can be encouraged by government

  • Similarly spending in the higher education sector seems to encourage papers, while spending in the business sector more encourages patents

  • Thus these allocations are simply a choice between longer and shorter term benefits of R&D

  • Not surprising, but regressions provide some quantitative confirmation of this logic


Summary of models for paper share
Summary of models for paper share (Patents07) vs. three IVs

Simple extrapolations of trends in output paper share mi provide a reality check for models based on input resource drivers

The Shelton Model based on GERD share works well for big countries. It accounts for the decline in US and EU due to the rise of China's share of GERD wi .

mi = ki wi

The Shelton-Leydesdorff Model based on government share accounts for the EU increase in efficiency in the 1990s, and the long-term US decline.

mi = ki’ wi’ + c’

Adding a second IV, HERD spending share wi’’ works even better. This accounts for the EU passing the US in 1995.

mi = ki’wi’ + ki’’wi’’ + c’’


Validation of paper share models
Validation of paper share models (Patents07) vs. three IVs

Like any theory, models need to be tested to see how well they account for new phenomena.

Scattergrams can show how well regression models fit a year’s data, or perhaps a new data point. They don’t forecast the future so well.

Once key IVs are identified by statistics, individual country models can be built and tested by “forecasting the past.”

Simple extrapolation of output DVs serves as a reality check


Extrapolation of SCI paper shares (Patents07) vs. three IVs

This model forecasts that the PRC will not pass the US until about 2020, and the EU27 until after 2025


Extrapolation of paper share in the Scopus database (Patents07) vs. three IVs

This can be compared to a recent similar forecast by the UK Royal Society.






Performance of Shelton Model in forecasting from 2005 to 2010

Based on forecasts of GERD and its share from 2005 data. Accuracy of US and EU is not bad. PRC is growing slower than forecast.


Performance of Shelton-Leydesdorff model: forecasting from 2005 to 2010

Uses 5-year average of rates of Gov increase. EU and PRC fit well, but US is worse than forecast, because its rate of Gov increase has plummeted to near zero. (Individual models used.)


Conclusions
Conclusions 2005 to 2010

  • Regressions show that investment choices are complementary: some are best for papers and some for patents

  • Models based on these resource inputs have some success in forecasting

  • But a take-away for the professors in the audience: just using HERD share to predict paper share is surprisingly accurate

  • Thus if nations want to excel in papers, they should just give money to professors!


Paper share 2005 to 2010≈ HERD share!

ps07 = 0.027 + 0.930HERD p=0.000

R2 = 98.6%


Performance of HERD as predictor of paper share 2005 to 2010

Forget statistics: Simply predicting paper share with HERD share works well for the US and EU. It also predicts that the EU should lead the US.


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