Almost all high-income homes online, but just 54% of low-income homes: StatsCan
By Michael Oliveira, The Canadian Press – 4 days ago
TORONTO — An overwhelming 97 per cent of the highest-income households in Canada had access to the Internet last year while just over half of the homes in the lowest income group were online, Statistics Canada reported Wednesday.
Overall, about 80 per cent of all Canadian households had Internet access in 2010, with the highest penetration levels in British Columbia (84 per cent), Alberta (83) and Ontario (81).
Almost all the homes with total incomes above $87,000 were connected, while just 54 per cent of households with incomes under $30,000 had access.
The study also found that 93 per cent of households with three or more members had Internet access, compared to 58 per cent of single-person homes.
Of the households not online, 56 per cent of those surveyed said they had no interest in the web, email or social media; 20 per cent said cost was an issue; 15 per cent said they didn't have a computer; and 12 per cent said they lacked the confidence, knowledge or skills to use the Internet.
The annual survey on Internet use was redesigned for 2010 and cannot be compared with previous reports. A followup study will be released in the late summer or early fall detailing Canadians' individual Internet use.
The survey was retooled last year because the Internet has grown so prevalent in the lives of most Canadians, and some of the old questions posed were too basic, says Statistics Canada's Larry McKeown.
"It was getting to the point that the survey was becoming very difficult to answer because people are doing everything on the Internet now," McKeown says.
"If you think of an analogy of when electricity was first becoming common, (you might've asked): 'What are you using electricity for?' Well, eventually you're using it for everything and you stop asking those questions."
One of the more interesting findings for McKeown was the number of households using more than one device to get online, which was 54 per cent. Desktop and laptop computers were the most common ways that households got online but about a third of the homes also used a "wireless handheld device," like a cellphone or tablet computer, and 20 per cent used a video game console.
The survey also found that only four per cent of wired households were not yet on a high-speed connection.
Copyright © 2011 The Canadian Press. All rights reserved
Sunday, May 29, 2011
Almost all high-income homes online, but just 54% of low-income homes: StatsCan
The Canadian Press: Almost all high-income homes online, but just 54% of low-income homes: StatsCan
Saturday, April 30, 2011
Layton Power: How leadership mattered in the Canadian politics
The rise of NDP is a testament to the star power of Jack Layton, the NDP’s charismatic leader. Where Stephen Harper of Conservatives and Michael Ignatieff of Liberals lagged, Jack Layton lead with style. The issue-less campaign has been galvanized by Mr. Layton and it is paying off handsomely for him.
This perhaps has been the best April of Mr. Layton’s life who surpassed the prime minister in popularity by mid April (see the graph below). An analysis of the web searches conducted using Google from computers located within Canada suggest that Mr. Layton bypassed his competition as of April 13, a day after his stellar performance in the televised debate in English language with the three other party leaders.
While many political pundits did not find the leaders’ debate as a game changer, the graph below suggests otherwise. Mr. Layton did change the game in his two-hour performance on the television. Since April 21, he has been in a comfortable lead over others.
If there were an Emmy for televised political performance, Jack Layton would have won it hands (and one hip) down.
Saturday, April 23, 2011
US leading indicators improve
The Conference Board reported that its Index of Leading Economic Indicators rose 0.4% in March after an upwardly revised February gain of 1.0%, originally reported at 0.8%. Consensus expectations were for a 0.3% increase during last month. The latest was the ninth consecutive monthly increase. The three-month growth in the series of 6.6% (AR) was down from its early-2010 high of 10.8%.
Read more on Haver Analytics.
Sunday, April 17, 2011
Business majors spend less time preparing for class-NYTimes.Com
The Default Major - Skating Through B-School - NYTimes.com
Business majors spend less time preparing for class than do students in any other broad field, according to the most recent National Survey of Student Engagement: nearly half of seniors majoring in business say they spend fewer than 11 hours a week studying outside class. In their new book “Academically Adrift: Limited Learning on College Campuses,” the sociologists Richard Arum and Josipa Roksa report that business majors had the weakest gains during the first two years of college on a national test of writing and reasoning skills. And when business students take the GMAT, the entry examination for M.B.A. programs, they score lower than students in every other major.
This is not a small corner of academe. The family of majors under the business umbrella — including finance, accounting, marketing, management and “general business” — accounts for just over 20 percent, or more than 325,000, of all bachelor’s degrees awarded annually in the United States, making it the most popular field of study.
Brand-name programs — the Wharton School of the University of Pennsylvania, the University of Notre Dame Mendoza College of Business, and a few dozen others — are full of students pulling 70-hour weeks, if only to impress the elite finance and consulting firms they aspire to join. But get much below BusinessWeek’s top 50, and you’ll hear pervasive anxiety about student apathy, especially in “soft” fields like management and marketing, which account for the majority of business majors.
Going over the speed limit
My data set (used for the test results reported below) comprised an ordinal dependant variable [5 categories] and categorical explanatory variables with 63,122 observations. I used a computer running Windows 7 Professional on Intel Core 2 Quad CPU Q9300 @ 2.5 GHz with 8 GB of RAM. Further details about the tests are listed in the following Table.
| Software Routines | Stata 11 (duo core) | R (2.12.0) [32-bit] | R x64 2.13.0 | NLogit/Limdep |
| Commercial license price | US$2,495 | Free | Free | $1,395 |
| Multinomial Logit | mlogit, 9.06 seconds (2.89 seconds with the “quietly” option") | multinom, 50.59 sec + 52.29 sec zelig (mlogit), 77.89 sec VGLM (multinomial), 64.4 sec | multinom, 32.7 sec + 49.8 sec zelig (mlogit), 69.92 sec VGLM (multinomial), 63.76 sec | Logit; 36.72 sec |
| Proportional odds model | ologit, 1.69 sec 0.91 sec [quietly] oprobit, 0.91 sec [quietly] | VGLM (parallel = T), 16.26 sec polr, 22.62 sec [o.logit] | VGLM (parallel = T), 14.94 sec polr, 13.49 sec [o.logit] polr, 14.94 sec [o.probit] | Ordered [Logit] 18.50 sec Ordered [Probit] 36.33 sec |
| Generalized Logit | gologit2, 18.67 sec (15.1 seconds with the “quietly” option") | VGLM (parallel = F), 64.71 sec | VGLM (parallel = F), 64.86 sec |
Stata is even faster
When I reran the models using the quietly option (which supresses terminal output ) in Stata, I obtained the actual algorithm convergence times. For the multinomial logit model, Stata took fewer than 3 seconds to converge, making it 10-times faster than R. Similar reductions in execution times for Stata were observed for other algorithms reported in the table above.
64-bit version of R is faster, sometimes
The 64-bit version of R (2.13.0) reported faster execution times. The same was observed for the 64-bit version of R (2.12.0). Notice in the table above the dramatic reduction in the convergence times for the multinomial logit model (using multinom). R 2.13.0 [64-bit] took 35.4% less time to converge than R 2.12.0 [32-bit]. However, Zelig and VGLM based algorithms reported very modest improvements in execution times.
The ordered logit and ordered probit models (executed using the polr algorithm) also reported significant improvements in execution times.The ordered logit model took 40.3% less time in converging for R 2.13.0 [64-bit] than R 2.12.0 [32-bit].
I still do not understand why the summary(multinomial logit model) still takes an additional 49.8 seconds on top of 32.7 seconds to report summary results for the multinomial logit model. When I do not use summary() and instead use coef(multinomial logit model), I get instantaneous output.
In summary, it appears that not all algorithms would converge faster in the updated 64-bit version of R 2.13.0.
R is faster than Limdep/NLogit
In comparison, R [2.13.0] offered faster convergence times than NLogit for multinomial and ordered logit models and for ordered probit models. This puts R in the middle of two popular econometrics software. Stata is significantly faster than R, and R offers faster execution times than NLogit (see the difference for ordered logit in the table above).
What R Pros are saying about my post
If you were to scroll down to the comments section of my last post [Speeding tickets for R and Stata], you’ll notice some advice from experienced users of R. I have been advised to re-run the tests by first obtaining the optimised version of BLAS and LAPACK libraries. I am not sure how much difference would that make. However, it would be a little difficult for ordinary users of R (such as myself) to be able to determine what BLAS and LAPACK libraries to choose and install that are appropriate for their computer systems.
If significant speed gains could be achieved by using optimised BLAS and LAPACK libraries, the R installation routines may then be improved so that these libraries are made available to the novice end users of R.
Saturday, April 16, 2011
New Economists Scour Urban Data for Trends - WSJ.com
Ted Egan, chief economist in the San Francisco Controller's Office, said he could wait six months for California to release the detailed sales-tax data he needs for city revenue projections. But it's quicker to look at passenger tallies from the station closest to the Union Square shopping district, which generates roughly 10% of the city's sales-tax revenue. The Bay Area Rapid Transit District releases the data within three days, he said: "Why should I have to wait?"
New Economists Scour Urban Data for Trends - WSJ.com
Friday, April 15, 2011
Hungry for justice
From the Economist:
A paper in the Proceedings of the National Academy of Sciences describes how Shai Danziger of Ben-Gurion University of the Negev and his colleagues followed eight Israeli judges for ten months as they ruled on over 1,000 applications made by prisoners to parole boards. The plaintiffs were asking either to be allowed out on parole or to have the conditions of their incarceration changed. The team found that, at the start of the day, the judges granted around two-thirds of the applications before them. As the hours passed, that number fell sharply (see chart), eventually reaching zero. But clemency returned after each of two daily breaks, during which the judges retired for food. The approval rate shot back up to near its original value, before falling again as the day wore on.
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