Skip to main content

My appearance on BBC World News discussing Net Neutrality


I appeared on the BBC World News program Global with Matthew Amroliwala on February 5th, 2015 and spoke about Net Neutrality and the new FCC proposals. I tried to make the point that Net Neutrality is a symptom and the real issue is (lack of) competition.

The clip below is courtesy the BBC.





Comments

  1. Thanks very much for this great article;this is the stuff that keeps me going through out these day. Best christian news

    ReplyDelete
  2. Very informative article!!
    watch live news bbc on yupptv here watch BBC World News live

    ReplyDelete

Post a Comment

Popular posts from this blog

The business of ZeroRating

ZeroRating conversations are dominating Network Neutrality issues these days, whether it is the FreeBasics controversy  in India, Binge On by T-Mobile, or Verizon's recent announcement of a plan similar to AT&T's sponsored data. Here are a few thoughts to consider about ZeroRating and why it makes no sense (to me). If ISPs Zero Rate content, somebody has to pay for the bandwidth. Suppose the Content provider pays for it. Then there is a pricing problem: ISPs cannot charge the content provider a price above the price they charge consumers. Suppose they charge consumers X per MB of data, and they charge content providers X+Y per MB of data. Then, for sufficient traffic where overheads are accounted for, it is cheaper  for content providers to send recharge coupons back directly to the customers who used their services. Long term, pricing above the consumer price is not sustainable. ISPs cannot  charge the content provider a price below  the price they charge consume

A short tutorial on the Robust Synthetic Control python library, Part 1: counterfactuals

I have posted a couple of blogs on the powerful technique of (multidimensional) Robust Synthetic Control here and here . In this post I will give a short tutorial on how you can use mRSC to perform your own analysis using the python package my collaborator Jehangir has made available on github. This posting will be about counterfactual analysis. We will work with the canonical example of the synthetic control based counterfactual analysis of the impact California's Prop 99 . All the data and code is included in the github repository linked above. I will post the python code as run on a Jupyter Notebook, and the "tslib" library referenced above has been downloaded and is available. Preliminaries: importing the libraries. In [1]: import sys , os sys . path . append ( "../.." ) sys . path . append ( ".." ) sys . path . append ( os . getcwd ()) from matplotlib import pyplot as plt import matplotlib.ticker as ti

mRSC: A new way to answer What Ifs and do time series prediction

Introduction What if the federal minimum wage is raised to 16 dollars an hour? What if Steve Smith bats at number 5 in the Ashes 2019 instead of number 3? What if Australian style gun laws were implemented in the USA - what would be the impact on gun related violence? What if Eden Hazard attacks today instead of winging in the midfield? "What if?” is one of the favorite questions that occupy minds, from sports fans to policymakers to philosophers. Invariably, there is no one answer to the What ifs and everyone remains convinced in their own alternate realities but a new wave of work has been looking at data-driven approaches to answer (at least a subset of) these What If questions. The mathematical tool of (Robust) Synthetic Control examines these What If questions by creating a synthetic version of reality and explore its evolution in time as a counterfactual to the actual reality. Recently, together with my collaborators Jehangir Amjad (MIT/Google) Devavra