Re: [silk] Bangalore Meet, Food Drinks
On Fri, Apr 12, 2013 at 10:33 AM, Andy Deemer andydee...@gmail.com wrote: Okay, we've got a grill arranged, drinks arranged, and even food arranged. Now we just need the conversation! Can I get a show of hands for Bangalore Silk Meet on next Thursday at Naresh's amazing rooftop patio in Richmond Town? Thursday, April 18th @ ~ 7pm FYI, by my count we've got a turnout 12 and perhaps =20 people. Some good meats will be marinating shortly, and many cold beers will be on ice. So make the most of Bangalore while we can still[1] live here, and show those hands! [1] Journalistic hyperbole or rational reality? http://www.firstpost.com/india/will-bangalore-have-to-be-evacuated-by-2023-697649.html
Re: [silk] New York City Silkmeet this week(?)
+1 on NY silk meet details. :) -- Aditya Chadha http://twitter.com/ac On Mon, Apr 15, 2013 at 8:43 PM, John Sundman j...@wetmachine.com wrote: Has one been established? If so, I would appreciate the details. Thanks, jrs
Re: [silk] New York City Silkmeet this week(?)
+1 on NY silk meet details. :) Aditya (http://aditya.sublucid.com/) On Mon, Apr 15, 2013 at 8:43 PM, John Sundman j...@wetmachine.com wrote: Has one been established? If so, I would appreciate the details. Thanks, jrs
Re: [silk] Bangalore Meet, Food Drinks
FYI, by my count we've got a turnout 12 and perhaps =20 people. Some good meats will be marinating shortly, and many cold beers will be on ice. So make the most of Bangalore while we can still[1] live here, and show those hands! Showing 1 more :) I'll be there, looking forward to meeting everyone.
[silk] Is South India Really Richer? | This is Ashok.
The final census data is out anytime now.time For a hackathon?silklisters arise!! Naresh Narasimhan Sent from my Phone http://ashokarao.com/2013/04/15/is-south-india-really-richer/ Is South India Really Richer? | This is Ashok. That South India is more developed than the Hindi-speaking North is a common refrain. Literacy rates and per capita income generally bear this out. Indeed, we worry of the barren villages in Bihar, not fertile landscapes across Tamil Nadu. As per the Human Development Indices across India, the South is just over 25% ahead of the All-India average. And yet, the story is false. Or so is my conclusion after running into a few “Data Stories” of India (looks like Tyler Cowen is interested, too). While the maps give breathtaking life to the real depth of poverty across India, there are fairly rigorous analytics to vindicate my point. While the commonly-used GINI measure of inequality is very intuitive, it’s handcuffed by its inability to decompose the inequality with certain subgroups. A more appropriate measure is the Theil Index, which I talk about in a recent blog post: The math behind the measure (between 0 and 1) requires a fair understanding of information theory but the idea is lower index implies a higher economic “entropy”. Your physics teacher might tell you that this is a bad thing but, economically, it’s a little more complex. As Boltzmann showed, entropy increases as predictability of an event decreases. This means the entropy of a fair coin is higher than a biased one. Similarly, in a very equal economy it is very difficult to distinguish between two earners based only on their income. Indeed in a perfectly equal society this is impossible. However, as society stratifies itself, knowledge of ones income conveys far more information (redundancy), thereby decreasing entropy. Within a system, Theil makes it easy for econometricians to understand the amount of total inequality due to within-group inequality and across-group inequality. If this is a little hard to grasp, think about it this way. If the total differences in economic output remained constant between countries (that is, India is still poor and Norway rich) but income was equally distributed within each country the residual inequality would be the “across-country” inequality. The residual from the converse, where all countries remain as unequal as they were, but world economic output is distributed equally to countries (not people), represents the “within-country” inequality. And the same reasoning can be scaled-down to consider inequality within and across Indian states. And this is just what a few researchers from the University of Texas did. Before we discuss this, it’s worth considering what high” decomposed, across-state inequality is. A good benchmark is definitely America. While the Northeast and California are generally considered to be richer than the rest, the real turmoil of inequality – at least the public’s eye – is definitely between individuals and not states. Further, the economic relationship between various American regions has been highly volatile, with some sign that growth is picking up most rapidly (in no small part due to extractive oil and gas industries) across “middle America”. Here is a decomposed map of inequality in the United States: A few accounting points notes here – while the overall measure can never be negative (greyish or black, in the above figure) individual agents can. A below-zero value here indicates that the given county is actually decreasing overall inequality of the country as a whole. The signal, here, is that American states are, broadly, equal. The real inequality stems from the difference between the rich and poor in Manhattan, not between the New Yorker and Iowan. So back to Galbraith, Chowdhury, and Shrivastava at Texas, we find that across-State inequality in India is pretty low: The dynamics of this graph are fascinating. For one, the purple line (within state inequality) is far more cyclical with overall inequality than the green line (between state inequality). While both do a fair job signalling inflections, the former represents approximately 90% of the change. Indeed, the contribution of between state inequality has been in relative decline since the 1980s. While this chart is too fuzzy to derive any grand conclusions, it’s interesting that the correlation across between state and within state inequalities diminished significantly since the piecemeal reforms of the 1980s. While data isn’t available as far back as the ’50s, I suspect liberalization shifted the onus from the state onto the individual. Further, central bureaucrats weren’t able to throttle State growth in the same uneven manner as the years of Fabian regulation. Of course, this is just mere conjecture. Here’s a graph from the Data
Re: [silk] Is South India Really Richer? | This is Ashok.
On a slightly tangential note, is the census data available for free. I was once told that if one wants to buy the complete set of census data, the cost runs into crores. Last year, the government published a National Open Data Policy under which the government promised to release datasets as open data. Is census data now available as open data? For those interested, I can send the PDF copy of the Open Data Policy. Regards, Venky On Wed, Apr 17, 2013 at 9:48 AM, Udhay Shankar N ud...@pobox.com wrote: On Wed, Apr 17, 2013 at 9:18 AM, Naresh nar...@vagroup.com wrote: The final census data is out anytime now.time For a hackathon?silklisters arise!! I think tomorrow's meetup is ideal to expand on your ideas on what can be done with the raw census data. Udhay
Re: [silk] Is South India Really Richer? | This is Ashok.
Satellite images of light pollution in India show the most uniformly polluted sky of any developing country. In contrast, China is mostly only polluted with light haze along the coast. The few dark regions of India are the most revealing: Dantewada (maoists who tear down the few electricity poles that the establishment installs), Arunachal Pradesh (mountains and state policy of burnt earth economics on sensitive borders), Ladakh (ditto), and pockets of Rajasthan. That's it. Every other area of India is lit up. http://mnras.oxfordjournals.org/content/328/3/689.full.pdf On Apr 17, 2013 9:19 AM, Naresh nar...@vagroup.com wrote: The final census data is out anytime now.time For a hackathon?silklisters arise!! Naresh Narasimhan Sent from my Phone http://ashokarao.com/2013/04/15/is-south-india-really-richer/ Is South India Really Richer? | This is Ashok. That South India is more developed than the Hindi-speaking North is a common refrain. Literacy rates and per capita income generally bear this out. Indeed, we worry of the barren villages in Bihar, not fertile landscapes across Tamil Nadu. As per the Human Development Indices across India, the South is just over 25% ahead of the All-India average. And yet, the story is false. Or so is my conclusion after running into a few “Data Stories” of India (looks like Tyler Cowen is interested, too). While the maps give breathtaking life to the real depth of poverty across India, there are fairly rigorous analytics to vindicate my point. While the commonly-used GINI measure of inequality is very intuitive, it’s handcuffed by its inability to decompose the inequality with certain subgroups. A more appropriate measure is the Theil Index, which I talk about in a recent blog post: The math behind the measure (between 0 and 1) requires a fair understanding of information theory but the idea is lower index implies a higher economic “entropy”. Your physics teacher might tell you that this is a bad thing but, economically, it’s a little more complex. As Boltzmann showed, entropy increases as predictability of an event decreases. This means the entropy of a fair coin is higher than a biased one. Similarly, in a very equal economy it is very difficult to distinguish between two earners based only on their income. Indeed in a perfectly equal society this is impossible. However, as society stratifies itself, knowledge of ones income conveys far more information (redundancy), thereby decreasing entropy. Within a system, Theil makes it easy for econometricians to understand the amount of total inequality due to within-group inequality and across-group inequality. If this is a little hard to grasp, think about it this way. If the total differences in economic output remained constant between countries (that is, India is still poor and Norway rich) but income was equally distributed within each country the residual inequality would be the “across-country” inequality. The residual from the converse, where all countries remain as unequal as they were, but world economic output is distributed equally to countries (not people), represents the “within-country” inequality. And the same reasoning can be scaled-down to consider inequality within and across Indian states. And this is just what a few researchers from the University of Texas did. Before we discuss this, it’s worth considering what high” decomposed, across-state inequality is. A good benchmark is definitely America. While the Northeast and California are generally considered to be richer than the rest, the real turmoil of inequality – at least the public’s eye – is definitely between individuals and not states. Further, the economic relationship between various American regions has been highly volatile, with some sign that growth is picking up most rapidly (in no small part due to extractive oil and gas industries) across “middle America”. Here is a decomposed map of inequality in the United States: A few accounting points notes here – while the overall measure can never be negative (greyish or black, in the above figure) individual agents can. A below-zero value here indicates that the given county is actually decreasing overall inequality of the country as a whole. The signal, here, is that American states are, broadly, equal. The real inequality stems from the difference between the rich and poor in Manhattan, not between the New Yorker and Iowan. So back to Galbraith, Chowdhury, and Shrivastava at Texas, we find that across-State inequality in India is pretty low: The dynamics of this graph are fascinating. For one, the purple line (within state inequality) is far more cyclical with overall inequality than the green line (between state inequality). While both do a fair job signalling inflections, the former represents approximately 90% of the change. Indeed, the contribution of between state inequality has been in
