Toll Index July 2017 – descending to the seasonal valley of August

So here is a fresh Toll Index spaghetti graph showing we are on our way to the seasonal August deep but setting a record month of July for border crossing lorry activity. I expect good Industrial Production news will be announced by the BMWi for the month of July in about a month from now.

The data is available at the Data Repository of the IDSC – Research Data Center of IZA. The paper we first studied the properties of these data is published at the Journal of Forecasting.

The Toll Index has been widely covered in national and international press (selection):

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Explaining Opinion Polarization with Opinion Copulas

Opinions are important in economics just as they are in social sciences in general. Bubbles, manias and information cascades form in opinion spaces about expectations and they evolve in a self-organizing manner. They are the outgrowth of adaptive dynamics whose understanding is of pressing significance. Clustering and polarisation, even without artificial communication obstacles, appear to persist and abound even as we are able to communicate information to each other without geographic, temporal or medial obstacles. In fact it is, perhaps paradoxically perhaps not, in this time of ease of communication that we are witnessing a pronounced misalignment of perception and fact or such utterly illogical phenomena as “post-truth politics”. We are thus reminded of the importance of social psychology in opinion formation.

The appearance of the first speculative bubbles coincides with the advent of the newspapers (“Irrational Exuberance” Shiller (p. 101)), the volatility of the stock market in the 1920s with the proliferation of the telephone (“Irrational Exuberance” Shiller pp. 181- 182), the stock market boom of the 1990 and the subsequent collapse of the new economy is related to the widespread adoption of the internet, and the emergence of social media after 2000 lead us to the collapse of 2008.

The World Economic Forum in its 2013 report identified “digital wildfires in a hyperconnected world” as one of the major global economic risks.

The more enhanced the capacity for interpersonal communication becomes the more accelerated the “contagion of ideas” and the more prominent their role in the formation of speculative bubbles.

Which, if any, aspects of our internet-centred society might help explain the observed opinion cleavages given that there is no longer an exogenous structure (e.g. distance or access) obstructing or limiting the exchange of ideas?

Besides decreasing the diameter of the graph of connections among economic agents, technological innovation increases the ability to communicate on more than one topics at the same time and this is what my new paper is about (forthcoming in PLOS ONE).

It discusses opinions dynamics in the presence of more than one “topics” or “issues” and gives shape to the thought that whether we will agree with each other on a given topic is certainly not completely immune to our differences on other issues, a fact which is well documented in Social Psychology. Our opinions are influenced by the context in which we formulate them and are some times influenced by what we erroneously think others think, thus often producing unexpected aggregate effects (e.g. pluralistic ignorance). So it is natural to conjecture that the more opinions we reveal to each other the more likely it becomes to get cross-topic contamination or to reveal an opinion gap too large to bridge.

In Social Media, where Shiller proposes that the contagion of ideas now takes place, we are more than just our opinion on whether stock or housing prices will go up. We reveal just about everything to the other making issue spill-over possible and its study relevant. I propose therefore that while in the hyper-connected world the diameter of the information graph decreases, the distances in opinion space increases in tandem with the fact that we turn agents from opinion scalars to opinion vectors. Ie highlight the role of heterogeneous priors in opinion dynamics and show how “dimensionality” matters and in fact appears to be an elusive confounding factor which might help explain the persistence of opinion cleavages.

By using the idea of opinion copulas (which formalizes topic spill-over and topic contagion i.e. covariance of opinions on different topics) I show theoretically, by example, analytically and by simulation that in a world of uniform, univariate opinion distributions, polarization arises if agents reveal, care about and are able to track more than one topics at a time something which becomes more likely in the context of Social Media and an increasingly algorithm-driven society.

The toy example opinion copula which demonstrates the idea is given in the figure below. it depicts two uniform, univariate opinion distributions (the marginals shown in the attached histograms) joined with a copula known as the ordinal sum copula. Notice how the marginals are uniform and hence under stochastic homophily will produce consensus but the opinion copula is almost polarized and in fact will produce polarization i.e. at least bimodal distribution under stochastic homophily with the same parameters. What this example shows is that in a world of uniform distributions polarization emerges spontaneously via opinion copulas. This example might appear artificial at first but it is less so than one thinks. It simply says that people keep on the same side of the center on two topics but are otherwise uniformly free to choose where they stand. This requirement appears mild and in fact it can be empirically verified in many contexts.

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Sketching the origins of “Made in Germany” with ngrams

Two quick takeaways:

  1. The origins of German manufacturing prowess are in protectionist policies with import tarifs in the 1870s.
  2. Made In Germany mutated from marking lower quality German imports to Britain to marking premium quality German goods within 50 years or so.

Quoting from the Wikipedia article “Made In Germany”:

The label was originally introduced in Britain by the Merchandise Marks Act 1887,[1] to mark foreign produce more obviously, as foreign manufactures had been falsely marking inferior goods with the marks of renowned British manufacturing companies and importing them into the United Kingdom. Most of these were found to be originating from Germany, whose government had introduced a protectionist policy to legally prohibit the import of goods in order to build up domestic industry (Merchandise Marks Act – Oxford University Press).[2]

According to Professor Asaf Zussman, Department of Economics, Hebrew University in “The Rise of German Protectionism in the 1870s: A Macroeconomic Perspective∗”, the “Rye and Iron” tariffs introduced by Bismarck’s Germany in 1879 caused a major reduction of imports in order to protect Germany’s industries. As a response, the Free-trade Liberal government in the UK introduced the Merchandise Marks act to allow consumers to be able to choose whether or not they would continue to purchase goods from protectionist economies.

In this context tracing “Made in Germany” in English vs German text is informative:

 

English text:

German text:

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The “ifo Geschäftsklimaindex” – a humble comment

Month after month on a given day the “ifo Geschäftsklimaindex” is being published, commented upon by the Ifo president and picked up by the press. Yesterday was such a day and Clemens Fuest commented “Die Stimmung in den deutschen Chefetagen ist euphorisch” and “„Die deutsche Wirtschaft steht unter Volldampf“” as the index climbed for the 3rd time in a row.

Not everybody shares the belief that the index tells us what it is supposed to but I don’t want to go into the details of this. I just have a humble comment with all due respect. I understand the need to pimp up one’s own products, after all public attention is a scarce good. Commenting it though, as is usually the case, introduces Heisenberg uncertainty making the index not a neutral measurement of the economic process but one of its determining factors.

I wanted to check this out in reality and gauge in some way what the demand for the index is to begin with. In the Ifo Institute’s own words “Das ifo Geschäftsklima ist ein vielbeachteter Frühindikator für die konjunkturelle Entwicklung Deutschlands”. How true is this?

I know of one way to gauge demand for digital documents and that is Google Trends. So when I check for the intensity of search for “ifo Geschäftsklimaindex” or “ifo index” I get similar time series, without pronounced monthly seasonality: and indication of low demand.

 


You might say that people don’t search for the Ifo Index because they know where to find it but if I look at searches for “Konjunktur” then I have annual seasonality and the Ifo index search interest becomes almost non detectable. This means there is a crowd searching for konjunktur which is not searching for the Ifo Index…


Moreover if I look at the distribution of the searches they come exclusively from Germany



and in fact they come mostly from Bavaria. In East Germany only Berlin is half as interested as Bavaria.


Where in Bavaria do the searches come from?



Munich. Exclusively!

My point? Ein bisschen Bescheidenheit bitte. If there is interest in the Ifo Index it does not register in Google Search and I do not know of many things which do this…

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