Depression economies

The global economic recession resulted in massive job losses globally. the decline in manufacturing, services, and other sectors have left many job less and in depression.

A review of the searches conducted on the internet using Google search engine reveals that the searches for depression increased significantly in October 2008. The weeks following October 2008 experienced a decline until early November. The lowest point was observed at the time of US Presidential elections in November 2008.

The see-saw ride for depression continued in November and then declined until Christmas. The anticipation of holidays could have taken the mind off of the grim employment prospect for many unemployed workers. However, as the new year started, the credit card bills poured in in the second week of January when the searches for depression started their upward climb and reached a peak in early March 2009.

From March 2009 to early July 2009, there has been a decline in the searches for the word depression. However, there has been an increase in the search for depression in the past few months, suggesting that the green shoots may be too weak to take root. Are the prospects of even more job losses on the rise?

Another economic bellwether phrase is bankruptcy. The graph below suggests that the searches for bankruptcy increased sharply in September 2008. From September 2008 to May 2009, the search for bankruptcy saw a steady trend. However, the first week of June 2009 saw a huge spike in bankruptcy searches.

The car wars on the Internet

Consumers often research products on the Internet before they make a purchase. This is more common with big-ticket items, such as cars. A review of the searches conducted using the Google search engine reveals some interesting results.

Of the three American car manufacturers, Ford has been the only one to weather the storm that hit the automakers in 2009. The graph below suggests that since 2004, Ford has been the most searched brand of the five presented in the graph below. The other two American car manufacturers, GM and Chrysler, were the least searched manufacturers using Google.

Honda depicts a cyclical trend where the search for the brand peaks during April and May and declines afterwards. Toyota’s net popularity puts it on the third spot. However, of the five brands reviewed, Toyota's popularity remains constant over time.

But are these trends global? Let us compare four markets: the US, Japan, China, and and Germany. The US, presented below, depicts a similar trend as the one seen globally. A key difference is the systematic increase in interest in Ford, Toyota, and Honda from September 2008 to August 2009 when the cash for clunkers program was terminated. Again, ford, Honda, and Toyota saw a bigger increase in the interest in months lading to September 2009 than GM and Chrysler.

Interestingly, the demand for GM was confined only to the Detroit region (see the map below). Whereas the interest in other brands for more uniformly spread over the US.

At the same time the demand for Japanese brands, Toyota and Honda was more pronounced in high density urban centres. The following map presents a spatial distribution of the interest in Honda as captured by Google. I can also see a positive correlation between interest in Japanese vehicles and the democratic leaning of the electorate in the 2008 presidential elections.

The Japanese market shows a different trend. The two Japanese brands, Honda and Toyota, generated the most interest amongst consumers on the internet. Honda and Toyota have experienced a decline in the interest from February 2009 to July 2009.  Interestingly, GM in Japan has enjoyed recent increase in the internet-based interest amongst the Japanese consumers.

China on the other hand has been a GM market, even though the trend for GM is showing a decline in the interest in the brand since October 2004. Chrysler is at the bottom of the interest pyramid. Toyota, Honda, and Ford in a tight race in the Chinese market where the consumer interest does not differentiate the three brands.

The German auto interest landscape is completely different. BMW tops the chart in Germany followed by Mercedes.  Ford appears to be a close third. Honda and Toyota are at the bottom where Honda is mostly in the lead.

The spatial landscape in Germany is of great interest. The popularity of each brand is influenced by the headquarters of the brand. BMW is based in Munich. The internet-based searches from Germany are the highest in Munich for BMW.

Similarly,  has its headquarters in Stuttgart. No wonder that the highest searches for Mercedes in Germany are recorded in Stuttgart.

Toyota and Honda enjoy popularity in Frankfurt and Ford is most popular in Cologne. 

Is Facebook ready for the face off in Canada?

The most common search item googled in the past three months Canada is facebook. Youtube is a distant second.

The fact that Canadians are weary of the weather should come as no surprise since ‘weather’ is the third most searched item by Canadians. And yes, notice in the graph below that hotmail is beating Yahoo big time.

Canadians it appears are big on kjiji than eBay, which didn’t make the list.

Lastly, why would one google Google? Apparently many Canadians have?

Rail link between Union Station and Pearson airport in Toronto

I find it odd that a few years after making the tall claim that the rail link will be financed and operated by the private consortium, the Federal Government and Ontario are now going to subsidize the winning bidder of the three by a billion dollars! See Globe's coverage.

A BRIC smashes through the American dreams to host Olympics

The Olympics Committee has awarded the 2016 Olympics to Rio De Janeiro. This must have shocked the other three 1^st world cities namely Chicago, Madrid, and Tokyo, who were also vying for the same. While the Brazilians are busy celebrating on the beaches in Rio De Janeiro, it appears that a BRIC has smashed through the Olympic dreams of the other three major first-world metropolis.

Given the sense of entitlement, many in Chicago, Madrid, and Tokyo are simply shocked at the outcome where their modern first-world economies have been beaten by an emerging BRIC economy. The decision by the Olympics Committee is in recognition of the changing times where all those who felt entitled should now be able and willing to earn their entitlements.

Also, given the sharp increase in the fading hospitality of many western countries, which now routinely refuse entry to academics and athletes, one should think twice of hosting any major international event in Europe or North America. Consider that the British government refused permission to the Pakistani blind cricket team, who happens to be the world's champion in blind cricket, to visit United Kingdom to play in a tournament. It was only a few years ago that a young academic from India, Manindra Agrawal, was refused entry to the US where he was to be recognized by other leading mathematicians for his breakthrough. It took extensive lobbying by the leading mathematicians in the United States to have the decision overturned. Imagine doing the same for thousands of athletes and other sports staff that accompany every Olympics.

I am no fan of the Olympics, but I feel that this decision is good for the sports and athletes around the world. Also, there's no place on the planet like Rio.

Krugman on how Economists got it wrong

Paul Krugman has done it again. He has used the popular press to explain the intricacies of the modern day economic thought. In his op-ed contribution to The New York Times Paul Krugman explain what s wrong with the mainstream economic thought. Paul Krugman writing in the New York Times on Sunday offers a succinct review of the contemporary economic thought and the motivations behind it.

Krugman does not shy away from finding faults with the works of his contemporaries including Milton Freidman, Eugene Fama and Robert Lucas, while at the same time offering praise for Robert Schiller and Rughuram Rajan.

This article will most likely be debated for years as it has exposed the differences in opinion amongst the economists in a language accessible to an average newspaper reader. I, for one, has benefitted tremendously from this article. I hope you will find it informative as well.

From The Economist:

Cause and defect

Aug 13th 2009
From The Economist print edition

Instrumental variables help to isolate causal relationships. But they can be taken too far

Illustration by Jac Depczyk

“LIKE elaborately plumed birds…we preen and strut and display our t-values.” That was Edward Leamer’s uncharitable description of his profession in 1983. Mr Leamer, an economist at the University of California in Los Angeles, was frustrated by empirical economists’ emphasis on measures of correlation over underlying questions of cause and effect, such as whether people who spend more years in school go on to earn more in later life. Hardly anyone, he wrote gloomily, “takes anyone else’s data analyses seriously”. To make his point, Mr Leamer showed how different (but apparently reasonable) choices about which variables to include in an analysis of the effect of capital punishment on murder rates could lead to the conclusion that the death penalty led to more murders, fewer murders, or had no effect at all.

In the years since, economists have focused much more explicitly on improving the analysis of cause and effect, giving rise to what Guido Imbens of Harvard University calls “the causal literature”. The techniques at the heart of this literature—in particular, the use of so-called “instrumental variables”—have yielded insights into everything from the link between abortion and crime to the economic return from education. But these methods are themselves now coming under attack.

Instrumental variables have become popular in part because they allow economists to deal with one of the main obstacles to the accurate estimation of causal effects—the impossibility of controlling for every last influence. Mr Leamer’s work on capital punishment demonstrated that the choice of controls matters hugely. Putting too many variables into a model ends up degrading the results. Worst of all, some relevant variables may simply not be observable. For example, the time someone stays in school is probably influenced by his innate scholastic ability, but this is very hard to measure. Leaving such variables out can easily lead econometricians astray. What is more, the direction of causation is not always clear. Working out whether deploying more policemen reduces crime, for example, is confused by the fact that more policemen are allocated to areas with higher crime rates.

Instrumental variables are helpful in all these situations. Often derived from a quirk in the environment or in public policy, they affect the outcome (a person’s earnings, say, to return to the original example) only through their influence on the input variable (in this case, the number of years of schooling) while at the same time being uncorrelated with what is left out (scholastic ability). The job of instrumental variables is to ensure that the omission of factors from an analysis—in this example, the impact of scholastic ability on the amount of schooling—does not end up producing inaccurate results.

In an influential early example of this sort of study, Joshua Angrist of the Massachusetts Institute of Technology (MIT) and Alan Krueger of Princeton University used America’s education laws to create an instrumental variable based on years of schooling. These laws mean that children born earlier in the year are older when they start school than those born later in the year, which means they have received less schooling by the time they reach the legal leaving-age. Since a child’s birth date is unrelated to intrinsic ability, it is a good instrument for teasing out schooling’s true effect on wages. Over time, uses of such instrumental variables have become a standard part of economists’ set of tools. Freakonomics, the 2005 bestseller by Steven Levitt and Stephen Dubner, provides a popular treatment of many of the techniques. Mr Levitt’s analysis of crime during American election cycles, when police numbers rise for reasons unconnected to crime rates, is a celebrated example of an instrumental variable.

Two recent papers—one by James Heckman of Chicago University and Sergio Urzua of Northwestern University, and another by Angus Deaton of Princeton—are sharply critical of this approach. The authors argue that the causal effects that instrumental strategies identify are uninteresting because such techniques often give answers to narrow questions. The results from the quarter-of-birth study, for example, do not say much about the returns from education for college graduates, whose choices were unlikely to have been affected by when they were legally eligible to drop out of school. According to Mr Deaton, using such instruments to estimate causal parameters is like choosing to let light “fall where it may, and then proclaim[ing] that whatever it illuminates is what we were looking for all along.”

IV leagues

This is too harsh. It is no doubt possible to use instrumental variables to estimate effects on uninteresting subgroups of the population. But the quarter-of-birth study, for example, shone light on something that was both interesting and significant. The instrumental variable in this instance allows a clear, credible estimate of the return from extra schooling for those most inclined to drop out from school early. These are precisely the people whom a policy that sought to prolong the amount of education would target. Proponents of instrumental variables also argue that accurate answers to narrower questions are more useful than unreliable answers to wider questions.

A more legitimate fear is that important questions for which no good instrumental variables can be found are getting short shrift because of economists’ obsession with solving statistical problems. Mr Deaton says that instrumental variables encourage economists to avoid “thinking about how and why things work”. Striking a balance between accuracy of result and importance of issue is tricky. If economists end up going too far in emphasising accuracy, they may succeed in taking “the con out of econometrics”, as Mr Leamer urged them to—only to leave more pressing questions on the shelf.