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Posts Tagged nz

Who are we collaborating with? Shaun Hendy Jul 30

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Our talented intern from MIT has produced another tag cloud.  This time she has taken a look at who we collaborated with in 2008 based on our co-publication preferences in the ISI database.   The resulting map is shown below:

citycity08 copy

It’s clear we like working with Australians.  Those in Auckland, Palmerston North and Christchurch prefer to work with Sydneysiders, while those of us in Wellington prefer Victorians.  Hamiltonians have more exotic tastes with a clear preference for Californians.  And although Dunedin is often said to be the Edinburgh of the South, our southern scientists show a strong preference for London.

What science are we doing? Shaun Hendy Jul 26

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What science are New Zealanders working on?  To help me answer this question, I have an intern from MIT here for her summer break.  Luckily for me, she hadn’t heard about Wellington’s winter.  (Not that our spring or summer are up to much either, although we can put on a decent autumn.)

She is a very bright cookie, and she mastered the ISI bibliometric database and our network analysis software in no time at all.  She is mainly studying the bibliometric performance of the Centres of Research Excellence (CoREs), but she has found time to look into other aspects of New Zealand’s bibliometric record.

Inspired by visualisations of the Twitter universe (such as trendsmap), last week we produced a “tag cloud” of subject areas Kiwis are publishing in across the main centres.  We picked the top five ISI subject areas in each of the main centres, scaling the text by how often it occurred (i.e. by the total volume of papers published in each subject area).  The 2009 cloud is shown below:

whitebackground09 copy

In Auckland and Dunedin, pharmacology dominates, presumably due to their university medical schools.  In Christchurch and Hamilton, environmental science dominates; in Wellington, it is marine biology; and in Palmerston North, it is veterinary science.

The map clearly shows New Zealand’s strong specialisation in health sciences, the environment, and food and agriculture.  As I pointed out in a previous post, the proportion of articles that Kiwis publish in the health sciences is similar to the rest of the world.  Where we differ from the international norm is the high priority we give agricultural and environmental science and the low priority we assign to the physical sciences.

New Zealand’s productivity paradox: Part VI Shaun Hendy Jun 10

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ResearchBlogging.orgThis is the last post in my series on Philip McCann’s paper [1], which considers New Zealand’s productivity paradox: why, despite being ranked very highly for the factors that are normally thought by economists to drive economic growth, is New Zealand’s economy is just an average performer? In the previous post, I discussed why McCann doesn’t see a paradox. In fact:

“In the current era of globalisation, New Zealand’s combined lack of any major home market effect, the lack of major agglomeration effects, and the extreme geographical isolation, breaks the usual link between entrepreneurship, innovation and growth which is evident in other countries.”

McCann’s argument is based on ideas from economic geography, in particular that high spatial transaction costs in knowledge-based activities have lead to the regional agglomeration of high technology industries. New Zealand’s small population base means that we don’t enjoy the benefits of agglomeration in knowledge generation experienced by larger countries and cities.

Do agglomeration benefits exist? My patent data seems to suggest they do, and the continued existence of regional clusters of knowledge-based industries (such as the Nokia cluster of inventors in Helsinki) seems to be further evidence of this.

This may not seem intuitive; we are told every day that the world is flat.  However McCann argues that it is only in low knowledge-intensity activities where the terrain has levelled off.  The landscape for knowledge-intensive activities, McCann’s work suggests, has become more mountainous.  Despite the availability of electronic communications, my personal experience is that face-to-face contact in scientific collaborations remains vital.

Picking winners?

So what can New Zealand do about its economic geography? Are there some silver bullets for Mr English?

One approach discussed by McCann is to reduce spatial transaction costs between New Zealand and Australia (and the rest of the world).  He suggests that we move towards economic union with Australia, invest heavily in broadband, and look to reduce the monopoly that Auckland’s international airport currently enjoys.  I’ll leave it to the reader to rank these in order of political feasibility.

McCann also suggests that government will need to “pick winners” i.e. find mechanisms to grow New Zealand companies to scales at which they can invest and grow offshore rather than simply export.

… finding systems that also encourage New Zealand firms to move from simply exporting to overseas ownership, thereby promoting outward FDI and increasing New Zealand’s global engagement, would appear to be critical. Such an approach can also be allied  with  an  approach  that  targets  particular  types  of  inward  investors. While ‘picking winners’ is widely regarded as having a poor history in much of New  Zealand’s  industrial  policy,  using  inward  FDI-promotion  strategies (Boston Consulting Group, 2001) to help to attract technologies regarded as  critical for New Zealand (and agri-biotechnology technologies would appear to be high on the list) is a pragmatic approach that is freely adopted by almost all of New Zealand’s competitor countries.

I would add that government will need work out how to deliver the highly-skilled human capital that these ‘winners’ will require.

A city of four million people

Another obvious approach is to increase our own domestic levels of agglomeration.  As a colleague of mine put it, “New Zealand needs to act like a city of four million people”.

McCann makes several suggestions as to how we might do this:

  1. Take full advantage of our existing spatial agglomerations e.g. Auckland-Hamilton-Tauranga by ensuring their continued growth and by investment in their infrastructure.
  2. Increase knowledge flows between Auckland and the rest of the country.  McCann argues against concentration of resources in the University of Auckland, suggesting that knowledge transfer primarily occurs through the mobility of people between regions rather than through direct spillovers.
  3. Increase competition on domestic airline routes to lower internal airfares.
  4. Reduce the breadth and fragmentation of our RS&T sector. In particular, he cites Rod Oram [2], suggesting that we focus on our agricultural sector.

With regards to point 4, as I have revealed before in this blog, my opinion is that a sole focus on agri-biotechnology for New Zealand is risky and perhaps even misguided.  New Zealand has exceptionally low export diversity, with a heavy reliance on commodity dairy products.  Do we play to our strengths by trying to leverage the existing scale in our dairy sector, or do we try to develop fresh export sectors, building scale from scratch?

This is a question that occupies the minds of many commentators.  A conservative approach would be to play to our perceived strengths.  In New Zealand’s case, these are generally perceived to lie in agriculture, so it is not hard to make a case for putting our brain power to work in this sector.  Yet as McCann points out, our labour productivity in agriculture is only 16th in the OECD, despite the strong agricultural focus of our RS&T system.

The alternative is to develop new sectors of our economy, as small countries as Denmark and Finland have done over recent decades.  As I have noted in my study of Finland’s inventor network, this will require substantial targeted investment in human capital over a sustained period.

The reality is that to maintain our place in the world we will need both to back our existing strengths and to develop new ones, quite simply because other countries are also doing both.

Depth not breadth

The science reforms in the early 1990s were intended to make New Zealand’s RS&T sector more efficient and paid little heed to the idea of building scale.  Institutional financial needs pre-empted wider collaboration and FRST effectively capped the size of the grants it awarded, explicitly acknowledging that it could not manage programmes larger than ~$NZ2m. (Note to overseas readers: this is not as large as it sounds, partly as it is in NZ$ ;-), but mostly as it is full-cost funding rather than marginal funding – in a University or a CRI for instance, it might fully fund 7-8 scientists.)

An early policy response to this problem was the establishment of the Centres of Research Excellence (CoREs), including the MacDiarmid Institute which I work for, and seven other organisations.  In fact, I have come to think of the MacDiarmid Institute as a mechanism that has both reduced spatial transaction costs for collaboration and increased the scale and coherence of the physical sciences in New Zealand.

If we are going to take the economic challenges ahead of us seriously, then I think it is worth carefully studying the way that the CoREs have built scale and collaboration within New Zealand science.  The MacDiarmid Institute experience is that a multi-institutional network of researchers distributed across the country can be an effective way to build scale and increase research productivity and impact.  This is something I am now looking at quantitatively with the Ministry of Education and will no doubt be blogging about soon.

Where to from here?

Most of us would agree that New Zealand must diversify its economy through knowledge intensive-industries to reduce its dependence on low-value commodity exports.  Policies that seek to do this, but that do not take into account our economic geography (scale in particular) will probably not succeed.  Nonetheless, small countries, such as Denmark, Finland and Israel, have overcome the disadvantages of size to build successful high-technology industries with scale in areas unrelated to previous strengths.

I will conclude with an observation that Philip McCann made to me over coffee last year.  We were discussing my study of the Finnish experience, and I was arguing that a similar economic transformation was possible here.  He did not agree, yet his argument was not based on economics, but rather on culture.  His view was essentially that science and technology are so much more deeply embedded in the Scandinavian worldview that their businesses and governments have the ability and confidence to do things that ours cannot.

Unfortunately, it is difficult to disagree with this last statement.  Conventional wisdom in New Zealand politics holds that Kiwis don’t care about science and technology, so good policy and increased spending in this area doesn’t win votes.  We will need to change this, if we are to ensure that New Zealand’s economic geography is not its destiny.

[1] McCann, P. (2009). Economic geography, globalisation and New Zealand’s productivity paradox New Zealand Economic Papers, 43 (3), 279-314 DOI: 10.1080/00779950903308794

[2] Oram, R. (2007). Reinventing  paradise:  How  New  Zealand  is  starting  to  earn  a  bigger, sustainable living in the world economy. North Shore: Penguin Books.

Scientific collaboration within Australasian cities Shaun Hendy Apr 26

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Does scientific collaboration depend on city size?  And if it does, are smaller cities with fewer institutions and fewer scientists more collaborative?  Or do bigger cities with more specialisation and more opportunities for interaction support more collaboration?

Auckland 2009 To get at this question, I looked at scientific papers published in 2009 listed in the Thompson Reuters Web of Science database that had at least one author in a major Australasian city (Sydney, Melbourne, Brisbane, Perth, Auckland, Adelaide, Canberra).  From the list of co-authors for each city, I constructed the corresponding co-authorship network.

The 2009 Auckland co-authorship network is shown on the right.  In the middle sits the largest connected component of co-authors which contains 72% of the authors in the diagram.  Not all of these authors will be Aucklanders of course – many are in the network because they have collaborated with Aucklanders.  For example, I am in the network (somewhere in the middle)  because I co-authored an article with a colleague from the University of Auckland last year.

In a blog post last year, I constructed the co-author networks for the New Zealand CRIs using the same database.  What I found surprised me:  in 2008, more than 50% of CRI scientists (including me again) were connected through the largest connected co-authorship network (up from about 12% in 1994).  I also looked at the 2008 University co-authors and found that 70% of them could be connected by a single network.  So Auckland looks pretty connected.

To put those Aucklanders in context however, let’s compare them with other major cities in Australasia.  Below I’ve plotted the number of co-authors associated with a selection of the major cities versus the proportion of those co-authors in the largest connected component. Australasia 2009
Auckland is actually at the low end of the scale, along with Perth and Canberra.  At the high end, the largest components in the Melbourne and Sydney co-author networks occupy close to 90%.  Larger cities do seem to exhibit more connectedness amongst researchers.  If you accept connectedness as a proxy for collaboration, the big cities in Australasia were more collaborative in 2009.

Interestingly, when you put New Zealand itself on the plot, you find that it is more connected than Auckland.  This will not surprise many south of the Bombay Hills!

New Zealand’s productivity paradox: Part IV Shaun Hendy Apr 23

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ResearchBlogging.orgIn this post, I will continue my discussion of Philip McCann’s paper, “Economic geography, globalisation and New Zealand’s productivity paradox” [1]. McCann argues that it is New Zealand’s economic geography that is the reason for its poor productivity performance. In this post I’ll try to sketch some of the underlying ideas from economic geography that McCann utilises.

There is a general perception that globalisation is levelling the world economy (see Thomas Friedman’s book “The World is Flat”).  The outsourcing of manufacturing from Europe and the US to parts of Asia certainly receives a lot of attention in the media – even I have blogged about it.  However, McCann argues that the world is not becoming as flat as we might think.  In fact, over the last two decades, he notes that the share of global output, global trade, global foreign direct investment and global R&D, of the three super-regions (the EU, NAFTA and South and East Asia) has grown.

How does McCann reconcile this increasing regionalisation with the idea of globalisation?  The key to McCann’s argument is the relationship between the agglomeration economies (or economies of scale) and the spatial transaction costs involved in trade and manufacturing.

The idea that economies of scale might be important for productivity goes back at least as far as Adam Smith.  In his Inquiry into the Nature and Causes of the Wealth of Nations, Smith observed that division of labour offers advantages in a manufacturing process.  Using the example of a pin factory, he noted that the larger the factory, the more a factory could specialise tasks in pin manufacture among its workers.  Smith argued that if one doubles the size of the factory, the increased opportunities for specialisation meant that the factory was bound to more than double its output.  In other words, the larger the pin factory, the higher the productivity of its workers.

McCann suggests that it is high-value added or knowledge intensive manufacturing that benefit most from this type of specialisation and the division of labour.  Therefore, it is this type of manufacturing that will exhibit economies of scale.

If this is the case, economists have shown that if there are high transportation costs or trade barriers that lead to high spatial transaction costs for trade, then all countries and regions will have similar production patterns and similar levels of productivity. For example, every country will manufacture its own cars as it is too costly to ship them across national borders.

If, however, transaction costs fall, then knowledge intensive manufacturing that exhibits economies of scale will become localised in particular regions.  These regions will exhibit high levels of productivity.  For example, the large number of high technology workers in Silicon Valley gives it an advantage in productivity that other regions can’t match.  Only when spatial transaction costs for generating new knowledge fall to close to zero will this regionalisation disappear and productivity return to being spatially homogenous.  This leads to an inverted U-shaped relationship between agglomeration and spatial transaction costs.

McCann argues that while it’s true spatial transaction costs for low value, low knowledge intensive manufactured goods have fallen dramatically over recent decades, the spatial transaction costs for high value, knowledge intensive activities have increased:

This is because of the increasing importance of timeliness, speed, variety, customisation, and service-quality, in all high knowledge intensive forms of production and service delivery (Disdier & Head, 2008; Duranton & Storper, 2007; McCann, 2007).  The principal reason for this is that the premium associated with face-to-face contact in high knowledge intensive activities appears to have increased (Gaspar & Glaeser, 1998; McCann, 2008; Storper & Venables, 2004), because the spatial transactions costs on the inputs side of the production process, rather than the outputs side, have increased for high value goods (McCann, 2008).

It is this increase in transaction costs for knowledge intensive activities that has led to agglomeration of research and development in places like Silicon Valley and the productivity advantage that large cities enjoy today.  Spatial transaction costs for knowledge intensive activities are sitting near the top of the inverted-U, while the costs for commodity manufacturing have climbed it and are heading down the other side.  So the production of commodities may have become globalised, but the generated and application of new knowledge has not. What does this mean for New Zealand?

Part V
Part VI

[1] McCann, P. (2009). Economic geography, globalisation and New Zealand’s productivity paradox New Zealand Economic Papers, 43 (3), 279-314 DOI: 10.1080/00779950903308794

New Zealand’s million dollar scientists Shaun Hendy Mar 10

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Congratulations to all the winners of the inaugural Prime Minister’s science prizes. I am particularly pleased to know four of the winners personally.

Dr Jeff Tallon and Dr Bob Buckley, from Industrial Research Ltd, are two of New Zealand’s greatest physical scientists.  I discussed some of their work in a blog post last month.  Twenty five years ago, the Jeff and Bob took New Zealand to the forefront of research and development in high temperature superconductivity, and have kept us there ever since.  Their work has not only had immense scientific impact, but has led to the development of a superconductivity industry in New Zealand.  Jeff is a Principal Investigator in the MacDiarmid Institute, and Bob is a member of the Institute’s governance board.  Bob and Jeff have both been important mentors in my career.

Elizabeth Connor is the winner of the Science Communicators Prize.  I taught Elizabeth at Victoria University of Wellington during her BSc(Hons) in physics.  After her honours degree, Elizabeth travelled overseas to pursue further training in science communication, before returning last year.  She has since worked with us at the MacDiarmid Institute on several projects, including our Interface newsletter, and for Radio New Zealand.  You can read some of her work in our newsletter here.  She is one of our up and coming science journalists. I hope that Elizabeth continues to go from strength to strength in her journalism.

John Watt is another winner with MacDiarmid Institute affiliation.  We knew about John’s prize in advance as he was the winner of last year’s MacDiarmid Young Scientist of the Year award, which has now been superseded by the Prime Minister’s Emerging Scientist award.  John submitted his PhD thesis earlier this year and is awaiting his oral exam at the moment.  You can see some of John’s work on palladium nanocrystals here.  After he graduates, he is going to work with a Victoria University spin out company.  The prize will give him an excellent opportunity to become one of New Zealand’s scientific entrepreneurs.

Top patenting organisations in New Zealand: some stats Shaun Hendy Jan 22

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In a post a few weeks ago, there was a discussion on the value of patents. Sciblogs reader Bruce Hamilton pointed out that the value of an abandoned patent could simply be as an output for a funding agency. Could it be then the requirements of funding agencies for outputs is driving patenting activities? Bruce has put together a selection of statistics from IPONZ looking at patenting activity in some of New Zealand’s research organisations, both public and private. Bruce did not intend the list below to be exhaustive, but he has covered a selection of Universities, CRIs, large private companies and smaller start-ups. It’s very interesting to see who some of our top patenting organisations are, and how many of them have patents in progress.

Number Aborted (%) In Progress (%) Completed (%)
Fisher & Paykel 424 60 2 38
Uniservices 388 66 14 21
Industrial Research Limited 374 66 5 29
Agresearch 210 55 12 33
Fletcher 201 41 9 50
Carter Holt Harvey 186 56 9 35
Fonterra 143 43 17 39
Otago University 100 77 4 19
Gallagher Group 83 43 12 48
Massey University 76 55 8 37
Genesis R&D Corp 45 36 11 56
IGNS 37 58 6 36
Otago Innovation 18 50 17 33
Syft Technologies 15 57 0 43
Blis Technologies 13 64 0 36

Aborted = Abandoned + Voided Pre-acceptance
In Progress = Filed, Examination, Accepted
Completed = Granted, Expired or Not Renewed.

At least in this data set, it does look like public organisations abort more of their patents than their private counterparts. However, public research organisations are charged with disseminating their research findings through journal articles or presentations at scientific conferences. Once a piece of research has entered the public domain, it can no longer be patented, so public research organisations may chose to protect their IP by filing a provisional patent prior to publishing or presenting their work. This gives them the option of proceeding with a full patent within the next year should they choose to do so, while allowing them to publish their work. Private research organisations, under less pressure to publish, can simply choose to not release their findings while they decide whether a piece of work is worth the expense of filling a full patent.

Thanks to Bruce for taking the time to extract this interesting data.

Zipf’s law and the distribution of patents among applicants Shaun Hendy Nov 17

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One of the interesting things we can do with the OECD patent database is look at how those patents are distributed among applicants. The applicant for a patent is often the organisation or company that employs the inventors rather than the inventors themselves. By looking at the distribution of patents among applicants we are looking at the size distribution of patent portfolios. Note that an organisation may apply for patents from multiple addresses – in this case I have treated each address as a separate applicant.

Applicant distributionThe plot on the right shows the distribution of European Patent Office patents among applicants from the USA, New Zealand, Australia and Finland. The data is shown on log-log axes – remarkably, the data in all four countries fall roughly on straight lines with slopes close to -2. In other words, the proportion of applicants with p patents is inversely proportional to p squared.

This appears to be yet another example of Zipf’s law, which is a frequency distribution that crops up in all sorts of strange places (none stranger than the popularity of opening moves in chess). One way such distributions can arise is through a process called “preferential attachment” (sometimes called a rich get richer process). In our case, such a distribution could be generated if an applicant’s probability of getting a new patent increases with the number of patents the applicant already has. The value of the exponent generated by such a process (close to -2 in the data shown) depends on the rate at which first-time applicants enter the population versus the rate at which new patents arise amongst existing applicants.

What is interesting is that the exponents are quite similar across the four countries, suggesting that the process that generates the distribution is the same in each. The main difference between countries is the absolute scale of the distribution rather than the slope.

Applicant distribution by BERDWhat determines this scale? The best correlate I have found is the level of business expenditure on research and development (BERD) in each country. If we instead plot the number of applicants per million dollars of BERD, the distributions almost collapse on to one another. Actually, you can see that with this rescaling New Zealand comes out quite well – we get more patents for the dollars we spend than the other countries shown.

Despite the value for money New Zealand businesses appear to get for their R&D spend, the data show that you largely do get what you pay for. Indeed, the similarity of the exponents between countries also suggest that the innovation process itself does not vary widely – it is the amount of research you do rather than the way you do it that is important. Unfortunately in New Zealand, our focus is all too often on how we innovate, rather than how much we innovate.

The University co-author network Shaun Hendy Oct 27

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Uni coauthor networkIn an earlier post I looked at the 2008 CRI co-author network. Now let’s turn to the University network. Using the Thomp­son Reuters Web of Sci­ence again, I found 5116 publications in 2008 with authors from New Zealand universities. In total 13930 authors contributed to these papers. The network is shown on the right.

Again, a remarkably large fraction of authors belong to the giant component. In the 2008 CRI co-author network, 2325 of the of the 4496 authors belonged to the largest connected component. Here, 9771 of the 13930 authors belong to the largest component – that’s a remarkable 70%.

We can make some other comparisons between the CRI  and the university networks. In the university network, on average each author has 8.4 collaborators; in the CRI network, each author has 5.1 collaborators. Apparently, university authors are more collaborative.

Degree distribution However, just comparing the average numbers of co-authors is misleading. I’ve graphed the distribution of co-author numbers for the universities and the CRIs on the left i.e. the proportion of authors with certain numbers of co-authors. From the graph it’s apparent that the difference between the university and CRI networks lie in the tails of the distributions. There are a number of university authors that participate in very large collaborations. For instance, there are a dozen or so authors in the network whose only published work in 2008 was one with 343 co-authors. Big science!

It is probably not surprising that university researchers are more likely than those in a CRI to participate in very large overseas collaborations. This skews the average number of co-authors for university researchers relative to CRI researchers, making the mean number of co-authors larger.