dalek2point3

related: https://academic.oup.com/restud/article-abstract/81/2/535/15...

Pounds That Kill: The External Costs of Vehicle Weight

Heavier vehicles are safer for their own occupants but more hazardous for other vehicles. Simple theory thus suggests that an unregulated vehicle fleet is inefficiently heavy. Using three separate identification strategies we show that, controlling for own-vehicle weight, being hit by a vehicle that is 1000 pounds heavier generates a 40–50% increase in fatality risk. These results imply a total accident-related externality that exceeds the estimated social cost of US carbon emissions and is equivalent to a gas tax of $0.97 per gallon ($136 billion annually). We consider two policies for internalizing this external cost, a weight-varying mileage tax and a gas tax, and find that they are similar for most vehicles. The findings suggest that European gas taxes may be much closer to optimal levels than the US gas tax.

here is the full paper in case anyone is interested: http://www.kellogg.northwestern.edu/faculty/jones-ben/htm/Ag...

few interesting findings: > Less active runners influence more active runners, but not the reverse.

Both men and women influence men, while only women influence other women.

seems like Trump is already following in illustrious footsteps. Guess who else really cared about building highways?

absolutely spot on. Differences in distribution is only one way in which you could disprove pg. There are others. For example, different "treatment effects". If conditional on getting selected, VCs pay more attention or are more useful for women, then that would be another reason that we would get the pattern pg proposes, but is not due to bias at selection.

For people who might not be economists, let me give some background.

Paul Romer is a quite influential and famous economist who is one of the creators of modern "endogenous growth theory". Growth theory is about coming up with simple models of how we think economies grow over time. His theory suggests that economic growth occurs because of innovations that come from features inherent to the society that is growing, and each step of growth has a feedback that affects the next phase of growth. So for example, the amount of knowledge in an economy determines the level of growth, and growth dictates the level of knowledge in the next phase. This is against exogenous growth theory where growth is as a result of exogenous technological innovations that arrive randomly and shock the system. He's widely tipped to win the Nobel sometime soon for this and related ideas.

Now, Bob Lucas, another famous macroeconomist and growth theorist (and Nobel Winner) and his co-authors have been in Romer's crosshairs for some time because of what he calls the "mathiness" of their work. He defines mathiness as something that "uses a mixture of words and symbols, but instead of making tight links, it leaves ample room for slippage between statements in natural versus formal language and between statements with theoretical as opposed to empirical content." (http://paulromer.net/mathiness/)

In a relentless series of posts and papers, he's been asking questions at the root of whether macro-economics is a science, how it works and how it could be improved. Hackers might like his "Illustrating Mathiness – Code Analogy" (http://paulromer.net/illustrating-mathiness-code-analogy) where he compares poorly done economic models with bad code.

Here are some more of those posts:

Needs More Math <=> Needs More Cowbell http://paulromer.net/more-cowbell/

Why the Mathiness in Lucas (2009) Matters http://paulromer.net/mathiness-lucas-2009/

The Assumptions in Growth Theory http://paulromer.net/assumptions-of-growth-theory/

can anyone outline what the backstory is? i feel like without knowing Rahul Yadav and what happened at Housing, this piece is hard to follow ...

very basic question. where does the list of startups come from and how do you know what country a startup belongs to? making a list like this is harder than you think, so im curious to hear how these guys address it.

kinda weird that all the timeseries charts have time going backwards. going lower to higher is certainly the standard way to do it. for eg: http://data.jobsintech.io/companies/google-inc

could be a reporting issue -- these things take time to show up in the data?

+1 this was also quite funny: http://sandhill.exchange/blog/sec-analysis

what are the standard apps to replace the google apps?

YC opted out. From the Forbes article: http://www.forbes.com/sites/briansolomon/2015/03/17/the-best...

Those strict criteria kept out one notable program: Y Combinator, which ranked #1 in 2014. Hochberg and Cohen note that Y Combinator, a pioneer whose graduates have included Dropbox, Airbnb, and Reddit, has “evolved” its model into that of a hands-off seed fund.

“Y Combinator is cashing in on the name it made for itself,” says Hochberg. “They’re talking about raising a multi-billion dollar late stage fund to take advantage of their model that selects great entrepreneurs rather than mold them.”

Other accelerators that remain on the rankings are more hands-on than Y Combinator, which by metrics alone would have ranked first again this year. Some entrepreneurs enjoy the relative freedom the program offers, versus highly structured programs elsewhere.

any idea what the soviet copyright policy is on these images? in the US NASA images are always in the public domain ...

any ideas on what this is useful for? I know this probably has thousands of different applications -- but was wondering what people are most excited to use this for?

Any hints for non-physicists as to what this enables? Presumably you could have asked for the data anyway, no? Why is this a big deal?

I'm intrigued -- what countries are we talking about?

I'm curious about the "copyright" field. Do you return the original sources from where Watson learnt the information he is presenting? What are the major sources? Have you faced copyright or legal restrictions to access information and has this affected Watson's ability to answer questions in a certain area?

" salary data from more than 1.2 million work visa applications the US Department of Labor has received between 2009 and 2013."

this seems like a treasure trove. any links to the raw data?

github.com is mostly open source.

Let me also plug this short essay "Entrepreneurs Need Strategy" -- very helpful in thinking about startups. http://mbasys.lingnan.sysu.edu.cn/resource/upload/upkimg/201...

any idea if this plugs into Google Maps or whether it uses some other map data?

In the world of mobile we've always had developers consider different platforms, but in video we have a monopoly, even though its so much easier to "port". I would use a tool that allows me to upload a video and have it be submitted to YouTube, Facebook, Vimeo etc and also have it be licensed freely (CC) for reuse across the internet.

how does python know what map data to use?

"note: it has a free quota of 100 queries per day"

Gee, thanks Google!

"Turn-by-turn directions"

One of the reasons Im guessing it doesnt have this is because the Google Maps API prohibits building turn-by-turn applications quite directly. If only they trusted OSM, they could have this up and running pretty quickly.

anyone have any idea what happens to user experience when one of these guys breaks? is it a big deal? what about islands who are surviving off of one cable connection?

Aaron Schwartz introduced me to Dweck. It has been an integral part of my life ever since: http://www.aaronsw.com/weblog/dweck

Its useful because you can

(1) get a hold of the raw data and then do cool stuff on top of it.

(2) you can contribute your own local area in a way that you want -- doesnt just have to be streets, can also be trails, riverside views etc.

(3) This is good if you're irked that Google has all the interesting street imagery that they hoard for themselves (mostly).

(4) You'd be helping openstreetmap volunteers look at your imagery when then edit the local map thus helping create our only shot at an open, fully flexible map of the world.

There's probably more, but this should be a good start. Yay, mapillary!

Its kinda ironic this notice on the Atlantic website:

"Ghostery found 25 trackers www.theatlantic.com"

25 is a LOT!