Sunday, August 28, 2011

How bad was the recent recession

With a 6% decline in jobs and a 5% contraction in economy, the recession in 2007 was one of the worst in the past 60 years. See the graphical display by the Bloomberg



Monday, August 22, 2011

How declining cities can reverse their fortunes - The Globe and Mail

The Globe and Mail reports that the fastest growing metros in the US are doing so because of lower local and state taxes.
How declining cities can reverse their fortunes - The Globe and Mail

My response:

The correlation between lower taxes and high growth rates in some metropolitan areas in the US is spurious at best. While it may be true that metros with the highest population growth had a slightly lower average tax rate of 9.4% (against 10.6% for the lowest population growth metros), one cannot ignore the fact that the high growth metros are located in the US Sunbelt.

It is, therefore, not the lower tax rates, as Cato Institute would have us all believe, but the cheap air conditioning and oversupply of new housing that enabled rapid growth in metros located in the US Sunbelt.

Professor Edward Glaeser of Harvard University in 2007 observed that while the metros located in the Sunbelt have experienced above average increase in housing supply, the price of new housing increased at a slower pace in the Sunbelt than the rest of the US, which is indicative of an oversupplied housing market.

Furthermore, seven out of 10 highest population growth metros, reported in the Cato Institute’s paper, are located in States with the highest foreclosure rates, i.e., Nevada, California, Arizona, Georgia, and Florida.

"Why Are Some Cities Growing While Others Are Shrinking?," Cato Journal, 31, 2 (Spring/Summer 2011), 285-303.
Enhanced by Zemanta

Saturday, August 20, 2011

Scotia Capital's economist catches the British mistake

The news lifted hopes for a fast recovery in the UK. According to the Office for National Statistics (ONS) the construction activity in the UK had increased by 2.3% in the three months ending in June 2011. This was a manifold increase over 0.5% observed in the previous time periods. Within hours the economists all over the UK revised their estimates for GDP growth from 0.2% to 0.3%.

It was all fine until Alan Clarke, an economist with Scotia Capital noticed that if one averages the construction activity reported for April, May and June 2011, the result is a mere 0.5% increase and not 2.3% as the ONS had initially reported.

It turned out that an arithmetic mistake (i.e., simple addition, subtraction, division) caused the error.

Still not too late to send economists at ONS back for some refreshers in statistics.

ONS construction error moves markets - Telegraph
Enhanced by Zemanta

Friday, August 19, 2011

Warren Buffet in New York Times

From the NY Times:

OUR leaders have asked for “shared sacrifice.” But when they did the asking, they spared me. I checked with my mega-rich friends to learn what pain they were expecting. They, too, were left untouched.
While the poor and middle class fight for us in Afghanistan, and while most Americans struggle to make ends meet, we mega-rich continue to get our extraordinary tax breaks. Some of us are investment managers who earn billions from our daily labors but are allowed to classify our income as “carried interest,” thereby getting a bargain 15 percent tax rate. Others own stock index futures for 10 minutes and have 60 percent of their gain taxed at 15 percent, as if they’d been long-term investors.
These and other blessings are showered upon us by legislators in Washington who feel compelled to protect us, much as if we were spotted owls or some other endangered species. It’s nice to have friends in high places.
Last year my federal tax bill — the income tax I paid, as well as payroll taxes paid by me and on my behalf — was $6,938,744. That sounds like a lot of money. But what I paid was only 17.4 percent of my taxable income — and that’s actually a lower percentage than was paid by any of the other 20 people in our office. Their tax burdens ranged from 33 percent to 41 percent and averaged 36 percent.
If you make money with money, as some of my super-rich friends do, your percentage may be a bit lower than mine. But if you earn money from a job, your percentage will surely exceed mine — most likely by a lot.
To understand why, you need to examine the sources of government revenue. Last year about 80 percent of these revenues came from personal income taxes and payroll taxes. The mega-rich pay income taxes at a rate of 15 percent on most of their earnings but pay practically nothing in payroll taxes. It’s a different story for the middle class: typically, they fall into the 15 percent and 25 percent income tax brackets, and then are hit with heavy payroll taxes to boot.
Back in the 1980s and 1990s, tax rates for the rich were far higher, and my percentage rate was in the middle of the pack. According to a theory I sometimes hear, I should have thrown a fit and refused to invest because of the elevated tax rates on capital gains and dividends.
I didn’t refuse, nor did others. I have worked with investors for 60 years and I have yet to see anyone — not even when capital gains rates were 39.9 percent in 1976-77 — shy away from a sensible investment because of the tax rate on the potential gain. People invest to make money, and potential taxes have never scared them off. And to those who argue that higher rates hurt job creation, I would note that a net of nearly 40 million jobs were added between 1980 and 2000. You know what’s happened since then: lower tax rates and far lower job creation.
Since 1992, the I.R.S. has compiled data from the returns of the 400 Americans reporting the largest income. In 1992, the top 400 had aggregate taxable income of $16.9 billion and paid federal taxes of 29.2 percent on that sum. In 2008, the aggregate income of the highest 400 had soared to $90.9 billion — a staggering $227.4 million on average — but the rate paid had fallen to 21.5 percent.
The taxes I refer to here include only federal income tax, but you can be sure that any payroll tax for the 400 was inconsequential compared to income. In fact, 88 of the 400 in 2008 reported no wages at all, though every one of them reported capital gains. Some of my brethren may shun work but they all like to invest. (I can relate to that.)
I know well many of the mega-rich and, by and large, they are very decent people. They love America and appreciate the opportunity this country has given them. Many have joined the Giving Pledge, promising to give most of their wealth to philanthropy. Most wouldn’t mind being told to pay more in taxes as well, particularly when so many of their fellow citizens are truly suffering.
Twelve members of Congress will soon take on the crucial job of rearranging our country’s finances. They’ve been instructed to devise a plan that reduces the 10-year deficit by at least $1.5 trillion. It’s vital, however, that they achieve far more than that. Americans are rapidly losing faith in the ability of Congress to deal with our country’s fiscal problems. Only action that is immediate, real and very substantial will prevent that doubt from morphing into hopelessness. That feeling can create its own reality.
Job one for the 12 is to pare down some future promises that even a rich America can’t fulfill. Big money must be saved here. The 12 should then turn to the issue of revenues. I would leave rates for 99.7 percent of taxpayers unchanged and continue the current 2-percentage-point reduction in the employee contribution to the payroll tax. This cut helps the poor and the middle class, who need every break they can get.
But for those making more than $1 million — there were 236,883 such households in 2009 — I would raise rates immediately on taxable income in excess of $1 million, including, of course, dividends and capital gains. And for those who make $10 million or more — there were 8,274 in 2009 — I would suggest an additional increase in rate.
My friends and I have been coddled long enough by a billionaire-friendly Congress. It’s time for our government to get serious about shared sacrifice."

Warren E. Buffett is the chairman and chief executive of Berkshire Hathaway.

Enhanced by Zemanta

Wednesday, August 17, 2011

Calculated Risk: New Resource for Tracking Home Sales

Calculated Risk: New Resource for Tracking Home Sales

Housing starts are a non starter

imageThe July 2011 housing starts at around 600,000 suggest that the US housing market is still in critical care. Down from the highs of 2.2 million annualised starts in 2066, the new housing market in the US continues to struggle at annualised 600,000 starts.

The foreclosed homes in the US have dented the housing market big time. With a lackluster economy that refuses to generate jobs for the millions who are now unemployed, the morale of the American consumer is low, thus keeping the housing markets down.

There were some celebrations by speculators since the starts were down by only 1.5% over the last month.  Thus a less than expected decline in housing starts prove to be a good news!

The reality remains as unemployment rate remains consistently high over the years, the housing market continues to perform significantly lower than its historical highs.

“A bloated inventory of unsold homes and a weak economy are weighing down on the housing market, whose collapse was the main catalyst of the 2007-2009 recession. A large foreclosure pipeline also is not helping, leaving builders with little incentive to break ground on new projects.”


Tuesday, August 9, 2011

London riots and Toronto’s suburbs

As violence spread through the immigrant dominated, low income, suburban neighbourhoods in UK, it has raised concerns about a similar violent breakdown in low-income neighbourhoods in Canada.

A recent report by Prof. David Hulchanski of the University of Toronto has pointed out the growing disparities between low- and high-income households in Toronto. In this post I argue that while income disparities have increased in central parts of Toronto, concerns about violent breakdown are largely misplaced for most Canadian cities, including Toronto.

In an earlier post I have argued that Professor’s Hulchanski’s results were influenced by the choice of spatial limits used to define ‘Toronto’. It is true that income disparities have worsened in Metropolitan Toronto, which is home to 2.5 million people and covers an area of 250 square miles. However, the increase in income disparities has resulted from outward migration of Toronto’s middle class to suburban municipalities that constitute the greater Toronto area (GTA).

For details see my earlier postings below:

The good, the bad, and the ugly in Toronto

Where is Toronto’s missing middle class? It has suburbanized out of Toronto

A quick review of the 2006 Census data suggest that neighbourhoods in Toronto’s outer suburbs (municipalities that constitute the GTA along with with Metropolitan Toronto) are more egalitarian than the ones in Metropolitan Toronto. The outer suburbs are now the choice digs for Toronto’s middle class, which is lured by abundant supply of affordable housing and other amenities required by households with children. A large number of recent immigrants have also flocked to the suburban parts of the GTA in pursuit of affordable shelter.

One way of comparing Toronto to its neighbouring suburbs is to deploy the same income typology as was used by Professor Hulchanski to categorise neighbourhoods in Toronto. He categorised neighbourhoods (Census Tracts) as follows:

Income quintiles Neighbourhoods Percent
Less than 40% average CMA income 134 13.36
Between 20% and 40% below average CMA income 276 27.52
Between 20% above and 20% below average CMA income 398 39.68
Between 20% and 40% above average CMA income 75 7.48
More than 40% above average CMA income 120 11.96
Total 1,003 100


CMA in the above table stands for the Census Metropolitan Area that comprises Toronto and most of its suburban municipalities. Toronto CMA has  a population of about 5 million. The above table suggests that in 2006 over 40% neighbourhoods in Toronto region reported average household income below 20% of the regional average.

I produce below tabulations between immigrant population and income quintiles. To account for the impact of recent immigrant concentration on the socio-economics of a neighbourhood, I categorise neighbourhoods based on what percentage of immigrants within a neighbourhood arrived in Canada between 1995 and 2006. Furthermore, I produce two tabulations, one for Metropolitan Toronto, and one for all other municipalities that are part of the Toronto CMA.

The tabulation for Metropolitan Toronto is presented below. Similar to what Professor Hulchanski found, I report that 46% neighbourhoods falling under the highest recent immigrant concentration (category 4) belonged to lowest income category. In comparison, only 4% of the neighbourhoods that were categorised as having the lowest concentration of recent immigrants belonged to the lowest income category. Furthermore, the highest income neighbourhoods were predominantly the ones with lowest concentration of recent immigrants.


However, the situation is quite reversed when the same tabulation is generated for outer suburbs in the Toronto region. Consider the following table where 48% neighbourhoods with the highest recent immigrant concentration corresponded to middle or higher than middle income categories. Only 8% of the highest recent immigrant concentration neighbourhoods fell in the lowest income category in suburban Toronto.


Furthermore, across all concentrations of recent immigrants, i.e., from lowest to the highest, the most frequent income category was the mid income range, i.e., between 20% above and 20% below average CMA income.

In summary, a quick review of Census data from 2006 reveals that Toronto’s outer suburbs are home to the middle class where recent immigrants are enjoying the benefits of affordable housing and other amenities that are not available in Metropolitan Toronto. In addition, Metropolitan Toronto continues to experience higher income disparities that adversely affects recent immigrants at an increasing rate.

Wednesday, August 3, 2011

Are students' teaching evaluations influenced by instructors' looks?

Are students' teaching evaluations influenced by instructors' looks? ggplot2 may help find the answer.

The recent release of RcmdrPlugin.KMggplot2 has made ggplot2 available to those who prefer GUI to the command line interface. With the new plugin for Rcmdr, one can simply point and click and within seconds can have an amazing publish-quality graph.

I test drove the plugin and liked it very much accept the glaring omission: it does not provide for faceting for scatter plots, which is a key strength of ggplot2. Let me illustrate this with an example.

I use the Teaching Ratings data from the AER package. The data set was used in a study to determine if students were influenced by the instructor's good looks or otherwise while evaluating the instructor's teaching performance.

Using Rcmdr and the ggplot2 plug-in I quickly draw the graph, which is presented to the right. The blue triangles represent women and the red dots represent male instructors. The Y-axis is a normalized measure of instructor's looks and teaching evaluations are presented on the x-axis.

It appears from the scatter plot that  good looks are correlated with higher teaching evaluations.

Now let's add two more dimensions to account for the following. First, is there a difference in teaching evaluations for tenured instructors versus the non-tenured instructors. And second, do students evaluate instructors belonging to visible minorities groups any different from the rest.

Using faceting in ggplot2, I draw the new graph that is presented to the right. Notice that the graph has four quadrants capturing the 2 x 2 possible combination for tenured (yes/no) and minority group (yes/no).

Let's focus on the top right quadrant, which shows that non-tenured, visible minority faculty members happen to be exclusively males receiving low beauty evaluations, but higher teaching evaluations.

The bottom right quadrant however shows that most tenured visible minority instructors are females who receive a higher teaching and beauty evaluation.

The second graph was produced by tweaking the command generated by the plug-in to illustrate that with faceting one can quickly plot multi-dimensional graphs. I hope that the next version of the plug-in  incorporates faceting for scatter plots.

Below is the code used to generate the second graph.

data(TeachingRatings, package="AER")

.df <- data.frame(x = tr$eval,y = tr$beauty,z = tr$gender, z1=tr$tenure, z2=tr$minority)

.plot1 <- ggplot(data = .df, aes(x = x, y = y, colour = z, shape = z)) + geom_point() +
  scale_colour_brewer(palette="Set1") +facet_wrap(z1~z2) + xlab("eval") + ylab("beauty") + labs(colour = "gender", shape = "gender") + kmg2_theme_gray(10, "sans") + opts(legend.position =
rm(.df, .plot1)