Geography without borders

One of the goals of this blog to is took again geography and to question the taken for given visions of economies. One way of doing this is creating network diagrams (which I have used in my book), other perspectives are available on the Globalisation and World Cities website as they work on the networked nature of inter-city interactions. goto   http://www.lboro.ac.uk/gawc/in_visual.html .

A further way of doing it is by using GIS software. Take for example the image of a Statistics Canada GIS software file that maps city regions in Canada.

Without borders of landmasses and political jurisdicttions, the image is disconcertingly unfamiliar. Where are these islands? This image reveals how isolated many of the cities in Canada are from one another. Although the image reveals a concentration of city regions in Southern Ontario it also shows that some regional towns can be allocated vast territories. Despite the disadvantage that there isn't a coresspondence between population and census areas, I am really attracted to this map as it helps to shift the perceptual lens of nations and economies - to reimage economies. What would be really helpful is a different file that fills in the rest of the space with different industry activities particular fossil resource extraction and forestry.

If we add back in the lines of coasts and political boundaries we become more comfortable that we are again dealing with an image we are familiar with.

Of course with such images that play with the mind some are more valuable that others. For example without the coastal outlines this image of the lower mainland (Vancouver) and Lower Vancouver Is (Victoria etc) is a bit misleading on 'closeness'.

Best wishes for 2010.

City GDP

The other day I had the need to find some GDP data for cities. It surprises me that urban agglomerations are one of the core features of human economic life yet so much of the statistics agenda of national agencies has so little to do with human settlements.

The best source I came across for the data I was seeking was the OECD book (2006) Competitive cities in the world economy, but its cut off was higher than a couple of cities I was after.

For simply population data etc for urban areas there are a couple of websites that are interesting.
OECD http://www.oecd.org/document/41/0,3343,en_2649_34413_42402025_1_1_1_1,00.html
http://www.geohive.com/
http://www.citypopulation.de/

For information on statistical collections and administrative borders http://www.statoids.com/ could be useful.

A new report on Canadian cities

The Conference Board of Canada today released the report:

21st Century Cities in Canada: The Geography of Innovation by David A. Wolfe who is the principal investigator of the Innovation Systems Research Network.

http://www.conferenceboard.ca/documents.aspx?did=3311

Cleaning up a few things

I am bit worried that in my earlier posts I may have come across a bit negative of Nordhaus' project. Although I think with the current methodology it will be hard to design a comparable time series, the project of providing some basic economic geography data is long over due. In doing this it is a remarkable achievment. We know surprisingly little about the global economic landscape and His work is a big start that needs to continue

How that data has been used might be a different matter see World Development Report 2009: Reshaping Economic Geography. goto http://econ.worldbank.org/WBSITE/EXTERNAL/EXTDEC/EXTRESEARCH/EXTWDRS/EXTWDR2009/0,,menuPK:4231145~pagePK:64167702~piPK:64167676~theSitePK:4231059,00.html

If you want to read an interesting review of this report goto:
http://www3.interscience.wiley.com/journal/121683144/abstract Transactions of the Institute of Bristish Geographers (April 2009).

Lastly if you know of relevant economic geography blogs please let me know.

Do networks exclude heirarchies?

Now this post is about an article I don't understand. Recently Peter Taylor has published an article "Urban economics in thrall to Christaller: a misguided search for city hierarchies in external urban relations" Environment and Planning A 2009, volume 41, pages 2550 - 2555 which confuses me.

He opens with:

In my particular intellectual cocoon, I had imagined that the spatial organisation and structure of cities were now generally agreed, crudely, to be a combination of two sets of materialist mechanisms: agglomeration processes creating economic clusters within cities, and connectivity processes creating economic networks between cities. The former has been a very strong research area over recent decades, contrasting with the latter, external urban relations, which has been relatively neglected. By my way of thinking, the two sets of processes are intertwined and between them generate successful, vibrant cities. But, it seems, my cocoon is not particularly encompassing. And it is the focus on networks with their inherent mutuality (horizontal intercity relations) that appears to be far from widely accepted. For some urban scholars, intercity relations can only be understood as hierarchical.

But does a network perspective exclude a hierarchical perspective, are they only merely horizontal?

The article is primarily a critique of the mathematical work of Masahisa Fujita and Jacques-Francios Thisse's (2002) Economics of Agglomeration: Cities, Industrial Location, and Regional Growth (along with the wider work of Krugman) whose agenda is the development of a model city agglomeration and location. There work primarily focusses on central place theory within a nation.

But as Taylor says, Globalisation makes this task more difficult. 'As well as this geographical scalar challenge, their focus on a simple hierarchical spatial structure privileges interurban competitive relations, which means that the inherent subtleties of urban external relations cannot be reached through their urban economics research agenda. Once it is accepted that cities are both competitive and cooperative, then the question arises as to the circumstances in which one intercity relation dominates the other' (p2554).

Then returning to his theme Taylor finishes with 'Breaking free from this pedagogic power, the initial decision in trying to understand cities is whether they are considered to be primarily organised as markets, hierarchies, or networks' .

I don't claim to be an expert in central place theory but what I find interesting about this view of networks is that avoids the issue that even in networks you can have power and hierarchy. Toyata uses a network of suppliers that are co-dependent but Toyota is itself the primary hub - the coordinator and architect. Work on Global Production Networks indicates that in Electronics one company has to be the 'flagship' (Ernst) that takes the lead in design the complex architectiure of the product. Networks don't exclude power relationships they just map them differently.

Anyway I thought this was an interesting recent article that was relevant to the blog. There is probably some nuiance in this paper and as I wonder about it in the earlier work of Taylor that I am missing.

Constant Prices or Share of GDP or ....

The question of how to represent economic structures will be an ogoing discussion in this blog but one of the key aspects of this issue are the methodologies adopted for comparisions.

So for example current prices are virtually useless for anything other than comparing economic phenomena for a single time period for a single nation because it has the same currency. This is because inflation, exchange rates etc cause serious difficulties for anything more than this. You can use calculations like purchasing power parities (PPP) which are better than exchange rates for cross currency comparisons to improve the analysis. By way of example, Nordhaus uses current PPP dollars in his economic geography project. This is fair enough for a single year but once you have a time series this doesn't work.

Constant pricing methodologies improve the utility of time series but they don't capture quality changes or technological changes limiting the benefits;. They are also difficult to use in cross country comparisons.

Typically then, share of GDP has become the standard for international analyses. Publications emerging from organisations such as the OECD almost exclusively use share of national GDP. This is an excellent approach for revealing differing relative specialisations. For example industry X might represent # % in Sweden or ## in the USA. You can even use these comparisions for time series analyses comparing the share of GDP acoss time. This is often done, for example, to highlight the rise of services relative to manufacturing.

But there is a problem. GDP isn't some absolute measure (and there isn't one), obviously GDP can rise and fall and the rates at which it does so differs between economies. The implication is that although this doesn't damage the measure's status as useful for relative specialisations it hides from readers (or blinds them) to the significance of growth. So using our example above in time 1 Sweden's industry represents # % but perhaps the whole economy grows fast but relatively evenly so at time 2 it is still # %. But in comarison to the USA that perhaps grew slowly during the same period - the Swedish industry has actually caught up to some degree on the scale of the industry in the USA.

This is particularly important for our analysis of East Asian economies over the last twenty years and comes to the forefront as we consider how to analyse the BRICS (Brazil, Russia, India, Chin and South Africa) over coming years. We need a complementary measure that captures change better.

What, I have been thinking about is creating a measure based on a basket of economies. Data on the world economy is too problematic, but a basket of economies (say approx 15 or so) where we have good data reaching back to the early 1960s would be workable. Your measure of interest - R&D, industry output etc could then be calculated against this basket of economies. If you wanted to, by the same logic you could create sectoral groups - something that is currently not possible. Over time you would be able to capture the changing dynamics of the world economy. For example, if you created a sectoral group (perhaps auto), in the early 1960s you would probably find that a small group of countries (mostly inside your basket of economies) accounted for a high share of the sectoral bechmark G15 Gross Sectoral Product. However, today, by keeping the basket of economies the same, you would probably find that fewer economies (inside the basket) account for a high share of G15 sectoral product but a significant amount of sectoral product would fall outside the basket.

In this methodology, if a sectoral product basis was calculated we would find that over time "shares" would grow beyond 100%. To me this is not a conceptual but a communication problems in terms of teaching people how to interpret the new measure. For the forseeable future using a basket of GDPs measure wouldn't have this problem, but it will eventually emerge.  We could call the measure something like the Benchmark International Product.

The only genuine challenge to this measure is that of perceived 'western bias'. The first benchmark group would have to have a western' OECD economy bias, which governments in China and East Asia may not like. However if the measure is to be really useful it has to reach back in time to a point where there are only few economies with really good data.

Econscapes

More on the Nordhaus project in a later blog but in this one I want to go back to one of the themes of this blog - interdependencies and geographies. One of the key data sources for information on the workings of modern economies comes from input-output data. Simply put this data is based on the concept that industries both produce and consume commodities. These interactions can then be developed as a matrix alongside others inputs such as labour etc as well as outputs that leave the system e.g. finished goods and exports.

However, the core industry X industry matrix can tell us a lot about the uniqueness of each economy

Input-output data is now available for a very wide range of countries and spanning a number of decades in some instances.

There are many ways that I-O data can be mapped or developed (there is an entire journal devoted to this data (Economic Systems Research), however I have my own favourite which I developed about 18 years ago. I call these images econscapes.

You can see in this image that Australia has large industry complexes in both the resource based activities (agriculture, minerals and food) in the bottom left of the diagram as well as services (top right).

In contrast we could compare Australia with a country like Germany. In this diagram you can se much more activity across the middle diagonal line (manufacturing clusters).

Such diagrams are useful as there allows us to visualise the differences between countries so they are like economic structure fingerprints.

But there is a problem, these are done as a share of national GDP so although they are comparable in terms of relativities they are not directly comparable. More on this in the next post.

Mapping mega-regions in a spiky world

While Garreau's book is a fun read it always was a stylistic/ impressionistic interpretation of the similarities between areas particularly of the US. His understanding of Canada even back then reads as being thin and times have certainly changed. For one thing there is more data avaialable than ever before, so it is now beginning to be possible to conduct more rigorous analysis.

Two authors that I have been reading lately are John Short (2007) and Nordhaus (2009). Short's book "Liquid City" is a detailed analysis of the North East conurbation encompassing Boston to Washinton. His maps and analysis is very interesting.

On the other hand Nordhaus who is a professor at Yale and mostly writes on climate change has been working for several years on developing economic geography data for realtively small geographic spaces (not administrative regions such as states or provinces) and then maps the the data with GIS software. His work truly shows how skiky the world really is. His work is the basis for a substantial part of the recent World Development report and he has a journal article in The B.E. Journal of Economic Analsis and Policy (2009 Vol 9 iss 2 p1-12). A substantial part of the project, it seems, is on the web. If your interested take a look at the graphic for Canada. http://gecon.yale.edu/Canada.htm the atoll nature of the Canadian economy is clearly observable.

Macro-regions similarity or interdependencies

In the course of analysing the international geography of innovation I keep an eye on the literature focussing on macro-regions. Macro regions at their most simplistic can basically be defined as economic or social regions which ignore conventional jurisdical borders.

A classic in this vein is Joel Garreau's Nine Nations of North America (1981) http://www.garreau.com/main.cfm?action=book&id=3 a very easy read.

An interesting comparison of geographies of similarity is the beyond borders project http://www.beyondbordersbook.com/index.html

Another in a similar vein is Richard Florida 'mega-regions' http://cjres.oxfordjournals.org/cgi/content/abstract/1/3/459.

These take a somewhat similar perspective by looking for regions that can be grouped either by mainly geographic and social characterisitcs (Garreau) or by agglomerations of activity, measured for example by Florida with light emissions data.

But what of interdependencies? Typically ignored because it is data intensive or isn't within the established construct. However, there are obvious examples. The North American auto complex is a 'corridor' that streches from southern Ontario down to Mexico following important highways and railway lines. But that is an easy eaxample because it is largely contiguous. For other sectors California and New York may be more closely linked than regions surrounding New York.

Identifying regions of similarity and continuous geography is something we are familar with, define a piece of land and draw a border around it (which can have significant value in itself) but we are less familiar with network geography.

Thinking about geography

In my first post I mentioned the idea this this blog will be in part aimed at teasing out definitions of geography.

My interest in this is driven by my primary interest in what is called 'innovation systems'. Essentially innovation systems are 'places' where it is apparent that there are greater levels of innovation (particularly technology creation) occurring. But how do we define geography?

Taking just one easy high profile example.

Is silicon valley a cluster that should be treated by itself.
Should silcon valley be considered a part of California, which by itself is one of the world's major economies? What about it being part of a national innovation system (the USA). Alternatively is the silicon valley bit part of a large region that stretches from California to Alaska - Ecotopia - to use a term also used by Garreau in his The Nine Nations of North America.

These questions are in part philosophical and in some part empirical. Yet it is hard to build a dataset that can answer the deepst questions. However, I have tried to capture some of them in my book Innovation System Frontiers.

Why is any of this important? We define areas of landscape and allocate them to various polictical jurisdictions and level of political action. So policy is effective for particular places but an innovation system may functionally extend across a political border. Then what?

Introducing this blog

This blog will be about various rather academic interests to do with both better understanding the geography of real economies and also with how we can better depict the shape of economies. Of course these two interests are highly inter-related.