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Essays on Empirical Analysis of Continuous-Time Models of Industrial Organization
No full textThe dissertation consists of three essays. The first
essay describes and estimates the model of bidding on eBay.
Internet auctions (such as eBay) differ from the traditional
auction format in that participants 1) typically face a choice
over several simultaneous auctions and 2) often have limited
information about rival bidders. Since existing economic models do
not account for these features of the bidding environment, it
should not be surprising that even casual empiricism reveals a
sharp discrepancy between the predictions of existing theory and
the actual behavior of bidders. In this paper, I show that the
presence of multiple, contemporaneous auctions for similar items
coupled with uncertainty regarding rival entry can explain both
features. I analyze these features in a continuous-time stochastic
auction model with endogenous entry, in which bidder types are
differentiated by their initial information regarding the entry
process. Empirical estimates using eBay auctions of pop-music CDs
confirm my theoretical prediction that the rate of entry depends
on price. I then test my model against alternative explanations of
observed bidding behavior using a detailed field experiment.
The second essay is on empirical analysis of executive
compensation in the continuous-time environment. In this essay, I
develop a methodology for the identification and non-parametric
estimation of a continuous-time principal-agent model. My
framework extends the existing literature on optimal dynamic
contracts by allowing for the presence of unobserved state
variables. To accommodate such heterogeneity, I develop an
estimation method based on numerically solving for the optimal
non-linear manager's response to the restrictions of the contract.
To demonstrate this feature, I apply my methodology to executive
contracts from the retail apparel industry.The third essay provides a tractable methodology for the
construction and structural estimation of continuous time dynamic
models. The specific class of models covered by my framework
includes competitive dynamic games where there are no direct
spillovers between objective functions of players. I develop an
estimation methodology based on the properties of the equilibrium
of the model. The methodology that I design can be applied to
welfare and revenue analysis of large dynamic models. As an
example, I compute the revenue and welfare gains for a
counter-factual exercise in which the eBay auction website changes
the format of its auctions from second-price to a flexible ending.</p
Essays on Multinomial Choice Models
No full textMy dissertation contains three chapters which develop new identification and estimation methods for multinomial choice models in both cross-sectional and paneldata settings. In the first chapter, I propose a new semiparametric identification andestimation approach to multinomial choice models using cross-sectional data. The approach relies on the rank-order property proposed by Manski (1975) and employedby recent studies such as Fox (2007) and Yan (2013), which is a distribution-free restrictionon the random utility framework underlying a multinomial choice model.From the rank-order property, a novel reparameterization provides a multivariatenonlinear least squares (population) criterion identifying the structural parameters.This identification result then motivates a sieve-based estimation procedure, whichis the first in the semiparametric literature to allow joint estimation of regressioncoefficients and reduced-form parameters such as choice probabilities and marginaleffects. Asymptotic properties of two functional estimators are developed. A MonteCarlo study indicates that these functional estimators perform well in finite samples.I illustrate the implementation of the estimation procedure via estimating a modelof college major choice using UCOP data of 1998-2003. As extensions, I also proposeestimators for the model using a choice-based sample and the model with rankinginformation.The estimation problem in the second chapter is motivated by the local nonlinearleast squares (LNLS) estimation of preference parameters (regression coefficients) in the multinomial choice model under uncertainty in which the decision rule is affectedby conditional expectations. I propose a two-stage LNLS estimation procedure forthe preference parameters. In the first stage, conditional expectations are estimatednonparametrically. Then, in the second stage, the preference parameters are estimatedby the LNLS estimator of multinomial choice model, using the choice dataand first-stage estimates. The two-stage estimator has the advantage of being easilyimplementable using standard software packages. In this chapter, I establish consistencyof the two-stage LNLS estimator. Monte Carlo simulation results illustratethat the proposed two-stage LNLS estimator performs well in finite sample.The third chapter is a part of a co-authored project with Shakeeb Khan and ElieTamer. In this work, we consider identification, estimation, and inference on regressioncoefficients in semiparametric multinomial response models. Our identification result is constructive and estimation is based on a localized rank objective function,loosely analogous to that used in Abrevaya et al. (2010). We show this achieves sharpidentification which is in contrast to existing procedures in the literature such as, forexample, Ahn et al. (2015). In that sense, our procedure is adaptive (Khan andTamer (2009)) in the sense that it provides an estimator of the sharp set when point identification does not hold, and a consistent point estimator when it does. Furthermore,our rank procedure extends to panel data settings for inference in modelswith fixed effects, including dynamic panel models with lagged dependent variablesas covariates. A simulation study establishes adequate nite sample properties ofour new procedures.</p
Three Essays on Extremal Quantiles
No full textExtremal quantile index is a concept that the quantile index will drift to zero (or one)as the sample size increases. The three chapters of my dissertation consists of threeapplications of this concept in three distinct econometric problems. In Chapter 2, Iuse the concept of extremal quantile index to derive new asymptotic properties andinference method for quantile treatment effect estimators when the quantile indexof interest is close to zero. In Chapter 3, I rely on the concept of extremal quantileindex to achieve identification at infinity of the sample selection models and proposea new inference method. Last, in Chapter 4, I use the concept of extremal quantileindex to define an asymptotic trimming scheme which can be used to control theconvergence rate of the estimator of the intercept of binary response models.</p
Essays in Industrial Organization and Econometrics
No full textThis dissertation consists of three chapters relating to
identification and inference in dynamic microeconometric models
including dynamic discrete games with many players, dynamic games with
discrete and continuous choices, and semiparametric binary choice and
duration panel data models.
The first chapter provides a framework for estimating large-scale
dynamic discrete choice models (both single- and multi-agent models)
in continuous time. The advantage of working in continuous time is
that state changes occur sequentially, rather than simultaneously,
avoiding a substantial curse of dimensionality that arises in
multi-agent settings. Eliminating this computational bottleneck is
the key to providing a seamless link between estimating the model and
performing post-estimation counterfactuals. While recently developed
two-step estimation techniques have made it possible to estimate
large-scale problems, solving for equilibria remains computationally
challenging. In many cases, the models that applied researchers
estimate do not match the models that are then used to perform
counterfactuals. By modeling decisions in continuous time, we are able
to take advantage of the recent advances in estimation while
preserving a tight link between estimation and policy experiments. We
also consider estimation in situations with imperfectly sampled data,
such as when we do not observe the decision not to move, or when data
is aggregated over time, such as when only discrete-time data are
available at regularly spaced intervals. We illustrate the power of
our framework using several large-scale Monte Carlo experiments.
The second chapter considers semiparametric panel data binary choice
and duration models with fixed effects. Such models are point
identified when at least one regressor has full support on the real
line. It is common in practice, however, to have only discrete or
continuous, but possibly bounded, regressors. We focus on
identification, estimation, and inference for the identified set in
such cases, when the parameters of interest may only be partially
identified. We develop a set of general results for
criterion-function-based estimation and inference in partially
identified models which can be applied to both regular and irregular
models. We apply our general results first to a fixed effects binary
choice panel data model where we obtain a sharp characterization of
the identified set and propose a consistent set estimator,
establishing its rate of convergence under different conditions.
Rates arbitrarily close to n-1/3 are
possible when a continuous, but possibly bounded, regressor is
present. When all regressors are discrete the estimates converge
arbitrarily fast to the identified set. We also propose a
subsampling-based procedure for constructing confidence regions in the
models we consider. Finally, we carry out a series of Monte Carlo
experiments to illustrate and evaluate the proposed procedures. We
also consider extensions to other fixed effects panel data models such
as binary choice models with lagged dependent variables and duration
models.
The third chapter considers nonparametric identification of dynamic
games of incomplete information in which players make both discrete
and continuous choices. Such models are commonly used in applied work
in industrial organization where, for example, firms make discrete
entry and exit decisions followed by continuous investment decisions.
We first review existing identification results for single agent
dynamic discrete choice models before turning to single-agent models
with an additional continuous choice variable and finally to
multi-agent models with both discrete and continuous choices. We
provide conditions for nonparametric identification of the utility
function in both cases.</p
Essays on Econometrics of Network Models
No full textSocial networks affect a broad class of economic activities. The three chapters of my dissertation study social networks from two different lines of research. The first line of research examines the formation process of a social network. In Chapter 2, I introduce a new identification strategy and a semiparametric estimator for the formation process of an undirected network with additive agent-specific fixed effects. In Chapter 3, I analyze the formation process of a directed network with a broader type of unobserved heterogeneity. This heterogeneity is modeled as interactive fixed effects. The second line of my research complements the first approach by exploring the influence that network structures have on different economic activities. In Chapter 4, I recover the endogenous and exogenous social effects in a high-dimensional panel data model with an unobserved network structure.</p
Going Beyond Counting First Authors in Author Co-citation Analysis
Get PDFThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Variations on the Author
Get PDF“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Appropriate Similarity Measures for Author Cocitation Analysis
Get PDFWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
Dispelling the Myths Behind First-author Citation Counts
Get PDFWe conducted a full-scale evaluative citation analysis study of scholars in the XML research field to explore just how different from each other author rankings resulting from different citation counting methods actually are, and to demonstrate the capability of emerging data and tools on the Web in supporting more realistic citation counting methods. Our results contest some common arguments for the continued
use of first-author citation counts in the evaluation of scholars, such as high correlations between author rankings by first-author citation counts and other citation
counting methods, and high costs of using more realistic citation counting methods that are not well-supported by the ISI databases. It is argued that increasingly available digital full text research papers make it possible for citation analysis studies to go beyond what the ISI databases have directly supported and to employ more
sophisticated methods
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