Hello all,
Please join us at the Applied Statistics workshop this Wednesday, Sept
30th when we will be delighted to have the distinguished Susan Athey,
Professor of Economics here at Harvard presenting on "A Structural
Model of Equilibrium and Uncertainty in Sponsored Search Advertising
Auctions" (joint work with Denis Nekipelov). Susan has passed along
the following abstract:
---
Sponsored links that appear beside internet search results on the
major search engines are sold using real-time auctions, where
advertisers place standing bids that are entered in an auction each
time a user types in a search query. The ranking of advertisements and
the prices paid depend on advertiser bids as well as "quality scores"
that are assigned for each advertisement and user query. Existing
models assume that bids are customized for a single user query and the
associated quality scores; however, in practice that is impossible, as
queries arrive more quickly than advertisers can change their bids,
and advertisers cannot perfectly predict changes in quality scores.
This paper develops a new model where bids apply to many user queries,
while the quality scores and the set of competing advertisements may
vary from query to query. In contrast to existing models that ignore
uncertainty, which produce multiplicity of equilibria, we provide
sufficient conditions for existence and uniqueness of equilibria, and
we provide evidence that these conditions are satisfied empirically.
We show that the necessary conditions for equilibrium bids can be
expressed as an ordinary differential equation.
We then propose a structural econometric model. With sufficient
uncertainty in the environment, the valuations are point-identified,
otherwise, we propose a bounds approach. We develop an estimator for
bidder valuations, which we show is consistent and asymptotically
normal. We provide Monte Carlo analysis to assess the small sample
properties of the estimator. We also develop a tractable computational
approach to calculate counterfactual equilibria of the auctions.
Finally, we apply the model to historical data for several keywords.
We show that our model yields lower implied valuations and bidder
profits than approaches that ignore uncertainty. We find that bidders
have substantial strategic incentives to reduce their expressed demand
in order to reduce the unit prices they pay in the auctions, and in
addition, these incentives are asymmetric across bidders, leading to
inefficient allocation. We show that for the
keywords we study, the auction mechanism used in practice is not only
strictly less efficient than a Vickrey auction, but it also raises
less revenue.
---
We will start at 12 noon with a light lunch, with the presentation
beginning around 12:15. We usually wrap up around 1:30 pm. We hope you
can make it.
Cheers,
matt.
~~~~~~~~~~~
Matthew Blackwell
PhD Candidate
Institute for Quantitative Social Science
Department of Government
Harvard University
email: mblackwell(a)iq.harvard.edu
url: http://people.fas.harvard.edu/~blackwel/
Hello Applied Statistics Community,
Please join us this Wednesday, September 23rd, at the Applied
Statistics Workshop when we will be fortunate to have Marshall Van
Alstyne presenting "Network Structure and Information Advantage: The
Diversity--Bandwidth Tradeoff." Marshall is an Associate Professor at
Boston University in the Department of Management Information Systems
as well as Research Associate at MIT's Center for E-Business. Marshall
passed along the following abstract:
To get novel information, we propose that actors in brokerage
positions face a tradeoff between network diversity and communication
channel bandwidth. As the structural diversity of a network increases,
the bandwidth of communication channels in that network decreases,
creating countervailing effects on the receipt of novel information.
This argument is based on the observation that diverse networks are
typically made up of weaker ties, characterized by narrower
communication channels across which less diverse information is likely
to flow. The diversity-bandwidth tradeoff is moderated by (a) the
degree to which topics are uniformly or heterogeneously distributed
over the alters in a broker’s network, (b) the dimensionality of the
information in a broker’s network (whether the total number of topics
communicated by alters is large or small) and (c) the rate at which
the information possessed by a broker’s contacts refreshes or changes
over time. We test this theory by combining social network and
performance data with direct observation of information content
flowing through email channels at a medium sized executive recruiting
firm. These analyses unpack the mechanisms that enable information
advantages in networks and serve as a ‘proof-of-concept’ for using
email content data to analyze relationships among information flows,
networks, and social capital.
A copy of the paper is also available:
http://isites.harvard.edu/fs/docs/icb.topic646669.files/Diversity_vs_Bandwi…
The Applied Statistics workshop meets each Wednesday in room K-354,
CGIS-Knafel (1737 Cambridge St). We start at 12 noon with a light
lunch, with presentations beginning around 12:15 and we usually wrap
up around 1:30 pm. We hope you can make it.
Cheers,
matt.
~~~~~~~~~~~
Matthew Blackwell
PhD Candidate
Institute for Quantitative Social Science
Department of Government
Harvard University
email: mblackwell(a)iq.harvard.edu
url: http://people.fas.harvard.edu/~blackwel/
Hello Applied Stats Community,
Please join us tomorrow, September 16th when we are excited to have
Ben Goodrich (Government/Social Policy) presenting "Bringing
Rank-Minimization Back In: An Estimator of the Number of Inputs to a
Data-Generating Process." The workshop will start with a light lunch
at 12 noon and the presentation will start at 12:15.
You will find a copy of the paper attached and Ben has provided the
following abstract:
This paper derives and implements an algorithm to infer the number of
inputs to a data-generating process from the outputs. Previous working
dating back to the 1930s proves that this inference can be made in
theory, but the practical difficulties have been too daunting to
overcome. These obstacles can be avoided by looking at the problem
from a different perspective, utilizing some insights from the study
of economic inequality, and relying on modern computer technology.
Now that there is a computational algorithm that can estimate the
number of variables that generated observed outcomes, the scope for
applications is quite large. Examples are given showing its use for
evaluating the reliability of measures of theoretical concepts,
empirically testing formal models, verifying whether there is an
omitted variable in a regression, checking whether proposed
explanatory variables are measured without error, evaluating the
completeness of multiple imputation models for missing data, and
facilitating the construction of matched pairs in randomized
experiments. The algorithm is used to test the main hypothesis in
Esping-Andersen (1990), which has been influential in the political
economy literature, namely that various welfare-state outcomes are a
function of only three underlying variables.
We hope you can make it.
Best regards,
matt.
~~~~~~~~~~~
Matthew Blackwell
PhD Candidate
Institute for Quantitative Social Science
Department of Government
Harvard University
email: mblackwell(a)iq.harvard.edu
url: http://people.fas.harvard.edu/~blackwel/
Hello Applied Statistics Community,
Please join us tomorrow, September 9th for our first workshop of the
year when we are happy to have Justin Grimmer presenting joint work
with Gary King entitled "Quantitative Discovery from Qualitative
Information: A General-Purpose Document Clustering Methodology." The
workshop will start with a light lunch at 12 noon and the presentation
will start at 12:15.
Justin and Gary have provided the following abstract for their paper:
Many people attempt to discover useful information by reading large
quantities of unstructured text, but because of known human
limitations even experts are ill-suited to succeed at this task. This
difficulty has inspired the creation of numerous automated cluster
analysis methods to aid discovery. We address two problems that plague
this literature. First, the optimal use of any one of these methods
requires that it be applied only to a specific substantive area, but
the best area for each method is rarely discussed and usually
unknowable ex ante. We tackle this problem with mathematical,
statistical, and visualization tools that define a search space built
from the solutions to all previously proposed cluster analysis methods
(and any qualitative approaches one has time to include) and enable a
user to explore it and quickly identify useful information. Second, in
part because of the nature of unsupervised learning problems, cluster
analysis methods are not routinely evaluated in ways that make them
vulnerable to being proven suboptimal or less than useful in specific
data types. We therefore propose new experimental designs for
evaluating these methods. With such evaluation designs, we demonstrate
that our computer-assisted approach facilitates more efficient and
insightful discovery of useful information than either expert human
coders using qualitative or quantitative approaches or existing
automated methods. We (will) make available an easy-to-use software
package that implements all our suggestions.
You can find a copy of the paper here:
http://gking.harvard.edu/files/discov.pdf
We hope you can make it.
Best regards,
matt.
~~~~~~~~~~~
Matthew Blackwell
PhD Candidate
Institute for Quantitative Social Science
Department of Government
Harvard University
email: mblackwell(a)iq.harvard.edu
url: http://people.fas.harvard.edu/~blackwel/
Hello all,
I wanted to pass along a few details about the Applied Statistics
Workshop this Fall.
The workshop will meet on Wednesdays starting at 12 noon in room K354
of the CGIS Knafel Building, 1737 Cambridge St. We will serve a light
lunch at each workshop. Our first meeting will be on Wed Sept 9th,
when we will be happy to have Justin Grimmer and Gary King speaking.
Note that the workshop will *not* meet on Wed Sept 2nd.
You can see the full schedule for the Fall term at the course website:
http://isites.harvard.edu/icb/icb.do?keyword=k64817
I hope your summer is treating you well.
Cheers,
Matt.
~~~~~~~~~~~
Matthew Blackwell
PhD Candidate
Institute for Quantitative Social Science
Department of Government
Harvard University
email: mblackwell(a)iq.harvard.edu
url: http://people.fas.harvard.edu/~blackwel/