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Item Open Access Empirical Evaluation of DSGE Models for Emerging Countries(2009) Garcia Cicco, JavierThis dissertation is the collection of three essays aimed to evaluate the empirical performance of dynamic stochastic general equilibrium (DSGE) models in explaining the behavior of macroeconomic dynamics in emerging countries.
Chapter 1, which is joint work with M. Uribe and R. Pancrazzi, investigates the hypothesis that a real business cycles model driven by permanent and transitory productivity shocks can explain well observed business-cycle fluctuations in emerging countries. The model is estimated using more than a century of Argentine data.
In Chapter 2, a comprehensive real DSGE model of an emerging country is estimated using Bayesian techniques, expanding the data set used in Chapter 1. The goal is to characterize the relative relevance of ten different business cycles' drivers: three sectorial technology shocks, embodied and disembodied non-stationary technology, terms of trade, the world interest rate, trade policy, government expenditures and the country premium.
Finally, Chapter 3 estimates (using Mexican data) a DSGE model of an emerging country containing many frictions, as has been recently argued, that impose non-trivial constraints for monetary-policy design. In particular, the framework features a sectorial decomposition of the productive sector, intermediate inputs, imperfect pass-through, endogenous premium to finance capital accumulation, a liability-dollarization problem, currency substitution, price and wage rigidities, and dynamics driven by eleven shocks.
Item Open Access Essays in Empirical Macroeconomics(2010) Vukotic, MarijaThis dissertation consists of three essays in empirical macroeconomics. In the first essay, I explore the dynamic effects of aggregate news about
future technology improvements on sectoral fundamentals. I document that the durable goods sector responds significantly more to news shocks than the nondurable goods sector. By looking at the behavior of inventories, which have been largely neglected in the news literature, I show that aggregate news propagates the business cycle mainly through the durable goods sector. My theoretical framework is a two-sector, two-factor, real business cycle model augmented with the following three real rigidities: habit persistence in consumption, variable capacity utilization, and investment adjustment costs in both sectors. In addition, I introduce inventories as a factor in the production of durable goods. The model is successful in replicating the empirical responses of the US economy to news shocks. It reproduces the stronger response of the durable goods sector and can perfectly match the responses of inventories.
The second essay, which is joint work with Roberto Pancrazi, evaluates the effects of a change in monetary policy on the decline of the volatility of real macroeconomic variables, and on its redistribution from high to medium frequencies during the post-1983 period. By using a dynamic stochastic general equilibrium model, we find that the monetary policy alone cannot account for the observed changes in the spectral density of output, investment, and consumption. However, when we also consider a change in the exogenous processes, a different monetary policy accounts for $40$ percent of the decline in the high-frequency volatilities and partially accounts for the redistribution of the variance toward lower frequencies.
In the third essay, I study exchange rate dynamics. In particular, I investigate the main features of a rich theoretical model that are necessary to explain exchange rate volatility and persistence. As a theoretical framework, I use a small open economy dynamic stochastic general equilibrium (DSGE hereafter) model. The model is estimated using Bayesian techniques. I use post Bretton-Woods data for the following three countries: Australia, Canada, and the United Kingdom (UK hereafter). The performance of the benchmark model in replicating both real exchange rate persistence and volatility is rather good. I show that the domestic and importing sector price stickiness and indexation parameters are the most important features of the model for a successful replication of the real exchange rate dynamics. The importance of the importing sector price stickiness and indexation parameters is increasing in the share of importing goods in the consumption basket. The most important shocks for explaining the exchange rate volatility at business cycle frequency are the investment specific technology shock, monetary policy shock, and labor supply shock, among domestic economy shocks, and the shock to the interest rate among the foreign shocks.
Item Open Access Essays in Industrial Organization and Econometrics(2010) Blevins, Jason RyanThis 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.
Item Open Access Essays in Law and Economics(2009) Iyavarakul, TongyaiThis dissertation comprises of three essays in law and economics. The first chapter, a joint work with my advisor - Marjorie McElroy, examines the longly debated effect of the liberalized divorce laws in the United States on the divorce rates during 1956-1989. The first and the second chapter are a theoretical and an empirical paper on a cooperative game of bribery.
Item Open Access Essays on Empirical Analysis of Continuous-Time Models of Industrial Organization(2008-04-08) Nekipelov, DenisThe 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.
Item Open Access Essays on Health Economics(2009) Wang, YangIn this dissertation, I discuss two important factors in individuals' decision-making processes: subjective expectation bias and time-inconsistent preferences. In Chapter I, I look at how individuals' own subjective expectations about certain future events are different from what actually happens in the future, even after controlling for individuals' private information. This difference, which is defined as the expectation bias in this paper, is found to have important influence on individuals' choices. Specifically, I look into the relationship between US elderly's subjective longevity expectation biases and their smoking choices. I find that US elderly tend to over-emphasize the importance of their genetic makeup but underestimate the influence of their health-related choices, such as smoking, on their longevity. This finding can partially explain why even though US elderly are found to be more concerned with their health and more forward-looking than we would have concluded using a model which does not allow for subjective expectation bias, we still observe many smokers. The policy simulation further confirms that if certain public policies can be designed to correct individuals' expectation biases about the effects of their genes and health-related choices on their longevity, then the average smoking rate for the age group analyzed in this paper will go down by about 4%.
In Chapter II, my co-author, Hanming Fang, and I look at one possible explanation to the under-utilization of preventive health care in the United States: procrastination. Procrastination, the phenomenon that individuals postpone certain decisions which incur instantaneous costs but bring long-term benefits, is captured in economics by hyperbolic discount factors and the corresponding time-inconsistent preferences. This chapter extends the semi-parametric identification and estimation method for dynamic discrete choice models using Hotz and Miller's (1993) conditional choice probability approach to the setting where individuals may have hyperbolic discounting time preferences and may be naive about their time inconsistency. We implement the proposed estimation method to US adult women's decisions of undertaking mammography tests to evaluate the importance of present bias and naivety in the under-utilization of mammography, controlling for other potentially important explanatory factors such as age, race, household income, and marital status. Preliminary results show evidence for both present bias and naivety in adult women's decisions of undertaking mammography tests. Using the parameters estimated, we further conduct some policy simulations to quantify the effects of the present bias and naivety on the utilization of preventive health care in the US.
Item Open Access Essays on Macroeconomics in the Frequency Domain(2010) Pancrazi, RobertoThis dissertation consists of three essays on macroeconomics in the frequency domain. In the first essay, I show that whereas the High-Frequency volatility of the majority of the macroeconomic series declined after the early 1980s, their Medium-Frequency volatility did not. Moreover, the Medium-Frequencies capture a large fraction of the volatility of these variables. In order to formally test whether a set of time-series is characterized by a break in their variance at any frequency, I construct a frequency domain structural break test. After deriving its asymptotic and small sample properties, I apply the test to the main U.S. real macroeconomic variables and conclude that the Great Moderation is just a High-Frequency phenomenon.
In the second essay I compute the welfare cost of the Great Moderation, using a consumption based asset pricing model. The Great Moderation is modeled according to the data properties of the stationary component of consumption, which displays a reduction of the volatility at high frequencies, and an unchanged volatility at medium frequencies. The theoretical model, calibrated to match the average asset pricing variables in the data, relies on the evolution of the habit stock, which depends on the lower frequencies of consumption. These two features generate a modest welfare gain of the Great Moderation (0.6 percent). I show that this result depends mainly on the medium frequency properties of consumption.
The third essay, which is joint work with Marija Vukotic, evaluates the effects of a change in monetary policy on the decline of the volatility of real macroeconomic variables, and on its redistribution from high to medium frequencies during the post-1983 period. By using a dynamic stochastic general equilibrium (DSGE hereafter) model, we find that the
monetary policy alone cannot account for the observed changes in the
spectral density of output, investment, and consumption. However, when we also consider a change in the exogenous processes, a different monetary policy accounts for 40 percent of the decline in the high-frequency volatilities and partially accounts for the redistribution of the variance toward lower frequencies.
Item Open Access Explaining the Effects of Fiscal Shocks(2010) Zubairy, SarahThis dissertation is motivated by the fact that while the literature has had a great deal of success in developing empirical models for monetary policy analysis, the same can not be said for fiscal policy. This work advances our understanding of various issues in identification and modeling of fiscal policy shocks. In particular, the first two chapters work towards building a compelling empirical model for fiscal policy evaluation and the last chapter addresses the importance of fiscal shocks, along with monetary shocks in explaining aggregate macroeconomic fluctuations.
Chapter 1 identifies and explains the effects of a government spending shock. In response to a structural unanticipated government spending shock, output, hours, consumption and wages all rise, whereas investment falls on impact. An estimated dynamic general equilibrium model featuring deep habit formation successfully explains these effects. In particular, deep habits give rise to countercyclical markups and thus act as transmission mechanism for the effects of government spending shocks on private consumption and wages. In addition, I show that deep habits significantly improve the fit of the model compared to a model with habit formation at the level of aggregate goods.
While Chapter 1 considers public spending financed by lump-sum taxes, Chapter 2 further extends the framework to allow for distortionary taxes, and a more careful modeling of the government financing behavior. I use full information Bayesian techniques to estimate this dynamic stochastic equilibrium model, and characterize the dynamics of the economy in the case of both spending and tax changes. I estimate fiscal multipliers and find the multiplier for government spending to be 1.12, and the maximum impact is when the spending shock hits the economy. In addition, the model predicts a positive but small response of private consumption to increased government spending. The multipliers for labor and capital tax on impact are 0.13 and 0.33, respectively. The effects of tax cuts, on the other hand, take time to build, and exceed the stimulative effects of higher spending at horizons of 12-20 quarters. The expansionary effects of tax cuts are primarily driven by the response of investment. I also carry out several counterfactual exercises to show how alternative financing methods and expected monetary policy have consequences for the size of fiscal multipliers. In addition, I simulate the effects of the American Recovery and Reinvestment Act of 2009 in the context of this empirical model.
The final chapter, which is joint work with Barbara Rossi, analyzes the role of government spending shocks along with monetary policy shocks in explaining macroeconomic fluctuations, in a structural vector autoregression (VAR) where both shocks are identified simultaneously. Our main finding is that government spending shocks are relatively more important in explaining medium cycle fluctuations (defined between 32 and 200 quarters) and monetary shocks play a larger role in explaining business cycle frequencies (between 8 and 32 quarters). We also find that failing to recognize that both monetary and fiscal policy simultaneously affect macroeconomic variables might incorrectly attribute fluctuations to the wrong source.
Item Open Access Indian Toilets and Tanzanian Mosquito Nets: Understanding Households' Environmental Health Decisions in Developing Countries(2008-04-25) Dickinson, Katherine LeeDiarrhea and malaria are two of the most devastating public health threats in the developing world, resulting in millions of childhood deaths each year. Part of the challenge in addressing these threats arises from the fact that many of the causes of and potential remedies for these diseases lie squarely at the intersection of environment, development, and health. In addition, while many environmental, economic, and health-related policies focus on expanding access to new technologies (e.g., latrines, mosquito nets), inadequate attention to factors that affect the use of these technologies often leads to disappointing policy outcomes. This dissertation applies an economic framework to explore the drivers of households' environmental health decisions in two specific contexts. The first study examines sanitation behaviors and child health outcomes in Orissa, India, while the second case involves malaria-related knowledge, prevention, and treatment behaviors in Mvomero, Tanzania. In both cases, theoretical models are developed that focus on the perceived costs and benefits households consider in their decisions to adopt certain behaviors. A key insight is that technologies targeting diarrhea and malaria have characteristics of both private and public goods. For both epidemiological and social reasons, the payoffs to adopting behavior changes such as using a latrine or a mosquito net will depend in part on the behavior of other households in the village or neighborhood. This motivates an examination of the role of social networks and social interactions in influencing households' environmental health choices in both empirical studies. The first empirical case involves a study of a randomized community-level sanitation intervention in Orissa, India. Household survey data were collected before and after the sanitation campaign in 1050 households in 40 rural villages. Impact evaluation analyses indicate that the campaign resulted in large increases in latrine use in the randomly selected "treatment" villages. In addition, some analyses suggest that child health outcomes may have improved as a result of the campaign. To examine the drivers of the observed behavior change, econometric models are run including household and village characteristics as well as indicators of social interactions. Results indicate that households were more likely to adopt latrines when they observed more adoption among their peers. Thus, part of the sanitation campaign's success was likely due to its emphasis on targeting villages rather than individuals and strengthening social pressure to adopt latrines. The second empirical case examines indicators of households' malaria-related knowledge, prevention, and treatment behaviors in Mvomero, Tanzania. Survey data from 408 households in 10 villages shed light on a number of malaria control behaviors, including use of bed nets and anti-malarial medications. Findings suggest that the majority of households (over 80%) in this area own and use mosquito nets. At the same time, malaria continues to impose a significant burden on the study population. Data collected in Mvomero also provide unique information on the patterns of social interaction among households within and across different villages, and additional analyses explore the role of social interactions in influencing households' malaria-related decisions. Results suggest that patterns of interaction are influenced by a number of factors, including physical proximity as well as tribe, religion, and wealth. In addition, social effects may play an important role in influencing households' malaria prevention and treatment decisions. Together, these studies help to shed light on the ways households perceive and respond to two specific environmental health threats. More generally, this study illustrates the potential benefits of applying economic tools and analyses to problems like sanitation and malaria, and expanding the definition of "environmental problems" beyond the typical set of first-world issues (e.g., industrial pollution) to include these pressing issues facing the world's most vulnerable populations.Item Open Access Location Choice and the Value of Spatially Delineated Amenities(2008-04-25) Bishop, Kelly CatherineIn the first chapter of this dissertation, I outline a hedonic equilibrium model that explicitly controls for moving costs and forward-looking behavior. Hedonic equilibrium models allow researchers to recover willingness to pay for spatially delineated amenities by using the notion that individuals "vote with their feet." However, the hedonic literature and, more recently, the estimable Tiebout sorting model literature, has largely ignored both the costs associated with migration (financial and psychological), as well as the forward-looking behavior that individuals exercise in making location decisions. Each of these omissions could lead to biased estimates of willingness to pay. Building upon dynamic migration models from the labor literature, I estimate a fully dynamic model of individual migration at the national level. By employing a two-step estimation routine, I avoid the computational burden associated with the full recursive solution and can then include a richly-specified, realistic state space. With this model, I am able to perform non-market valuation exercises and learn about the spatial determinants of labor market outcomes in a dynamic setting. Including dynamics has a significant positive impact on the estimates of willingness to pay for air quality. In addition, I find that location-specific amenity values can explain important trends in observed migration patterns in the United States.
The second chapter of this dissertation describes a model which estimates willingness to pay for air quality using property value hedonics techniques. Since Rosen's seminal 1974 paper, property value hedonics has become commonplace in the non-market valuation of environmental amenities, despite a number of well-known methodological problems. In particular, recovery of the marginal willingness to pay function suffers from important endogeneity biases that are difficult to correct with instrumental variables procedures [Epple (1987)]. Bajari and Benkard (2005) propose a "preference inversion" procedure for recovering heterogeneous measures of marginal willingness to pay that avoids these problems. However, using cross-sectional data, their approach imposes unrealistic constraints on the elasticity of marginal willingness to pay. Following Bajari and Benkard's suggestion, I show how data describing repeat purchase decisions by individual home buyers can be used to relax these constraints. Using data on ozone pollution in the Bay Area of California, I find that endogeneity bias and flexibility in the shape of the marginal willingness to pay function are both important.
Finally, in the third chapter of this dissertation, I combine the insights of the Bajari-Benkard inversion approach employed in second chapter with more standard estimation techniques (i.e., Rosen (1974)) to arrive at a new hedonic methodology that allows for flexible and heterogeneous preferences while avoiding the endogeneity problems that plague the traditional Rosen two-stage model. Implementing this estimator using the Bay Area ozone data, I again find evidence of considerable heterogeneity and of endogeneity bias. In particular, I find that a one unit deterioration in air quality (measured in days in which ozone levels exceed the state standards) raises marginal willingness to pay by $145.18 per year. The canonical two-stage Rosen model finds, counter-intuitively, that this same change would reduce marginal willingness to pay by $94.24.
Item Open Access Migration, Remittances and Growth(2010) Ukueva, NurgulIn the first chapter of my dissertation I analyze the effect of migration and remittances on a small, open, migrant-sending country in the context of an endogenous growth model with technology transfers. I demonstrate that, due to a dynamic feedback effect from economic conditions to migration and from migration to economic development in an economy exposed to migration, initial conditions can determine its long-run steady state, leading to the rise of vicious or virtuous circles of development. Countries with a low level of technological development may end up in a poverty trap, in which a low level of development results in low wage rates and consequently high migration rates. The high migration and loss of manpower in a general equilibrium setting generates less demand for the adoption of leading technologies, reducing incentives to invest into new technologies. This reduced incentive effect in turn leads to low output and low wages and even higher migration in future periods. Potentially, as in the case of depopulated countries and regions the economy diverges from the world's growth rate and eventually ends up being emptied out. In addition, I show, that altruistic remittances as an important by-product of migration allow people to share the benefits of technological advances developed elsewhere and dampen the negative impact of migration. In particular, remittances remove the limiting case of emptying out of the economy and reduce the chances of ending up in a poverty trap.
In the second chapter of my dissertation, I study the implications of migration and remittances for an economy with financial frictions. I introduce migration and remittances into Schumpeterian endogenous growth model with financial constraints and derive the conditions under which migration and remittances can have positive or negative impacts on the country's growth and convergence. I show that the results depend on the degree of the country's financial development and its distance to the technological frontier. Importantly, I show that if the financial constraint is strong, so that the economy is diverging from the world's growth path, then migration and remittances can have growth effects and can increase the steady state growth rate of the country as well as the likelihood that the country will converge to the world's growth path.
My third chapter uses a new household-level panel dataset from Kyrgyzstan to study the determinants and implications of remittances and inter-household transfers in general in Kyrgyzstan. We find that remittances in Kyrgyzstan are positively correlated with the income of the receiving households and that the remittance-receiving households have a higher probability of purchasing durable goods then households not receiving remittances.
Item Open Access Online Auction Markets(2009) Yao, SongCentral to the explosive growth of the Internet has been the desire
of dispersed buyers and sellers to interact readily and in a manner
hitherto impossible. Underpinning these interactions, auction
pricing mechanisms have enabled Internet transactions in novel ways.
Despite this massive growth and new medium, empirical work in
marketing and economics on auction use in Internet contexts remains
relatively nascent. Accordingly, this dissertation investigates the
role of online auctions; it is composed of three essays.
The first essay, ``Online Auction Demand,'' investigates seller and
buyer interactions via online auction websites, such as eBay. Such
auction sites are among the earliest prominent transaction sites on
the Internet (eBay started in 1995, the same year Internet Explorer
was released) and helped pave the way for e-commerce. Hence, online
auction demand is the first topic considered in my dissertation. The
second essay, ``A Dynamic Model of Sponsored Search Advertising,''
investigates sponsored search advertising auctions, a novel approach
that allocates premium advertising space to advertisers at popular
websites, such as search engines. Because sponsored search
advertising targets buyers in active purchase states, such
advertising venues have grown very rapidly in recent years and have
become a highly topical research domain. These two essays form the
foundation of the empirical research in this dissertation. The third
essay, ``Sponsored Search Auctions: Research Opportunities in
Marketing,'' outlines areas of future inquiry that I intend to
pursue in my research.
Of note, the problems underpinning the two empirical essays exhibits
a common form, that of a two-sided network wherein two parties
interact on a common platform (Rochet and Tirole, 2006). Although
theoretical research on two-sided markets is abundant, this
dissertation focuses on their use in e-commerce and adopts an
empirical orientation. I assume an empirical orientation because I
seek to guide firm behavior with concrete policy recommendations and
offer new insights into the actual behavior of the agents who
interact in these contexts. Although the two empirical essays share
this common feature, they also exhibit notable differences,
including the nature of the auction mechanism itself, the
interactions between the agents, and the dynamic frame of the
problem, thus making the problems distinct. The following abstracts
for these two essays as well as the chapter that describes my future
research serve to summarize these contributions, commonalities and
differences.
Online Auction Demand
With $40B in annual gross merchandise volume, electronic auctions
comprise a substantial and growing sector of the retail economy. For
example, eBay alone generated a gross merchandise volume of $14.4B
during the fourth quarter of 2006. Concurrent with this growth has
been an attendant increase in empirical research on Internet
auctions. However, this literature focuses primarily on the bidder;
I extend this research to consider both seller and bidder behavior
in an integrated system within a two-sided network of the two
parties. This extension of the existing literature enables an
exploration of the implications of the auction house's marketing on
its revenues as well as the nature of bidder and seller interactions
on this platform. In the first essay, I use a unique data set of
Celtic coins online auctions. These data were obtained from an
anonymous firm and include complete bidding and listing histories.
In contrast, most existing research relies only on the observed
website bids. The complete bidding and listing histories provided by
the data afford additional information that illuminates the insights
into bidder and seller behavior such as bidder valuations and seller
costs.
Using these data from the ancient coins category, I estimate a
structural model that integrates both bidder and seller behavior.
Bidders choose coins and sellers list them to maximize their
respective profits. I then develop a Markov Chain Monte Carlo (MCMC)
estimation approach that enables me, via data augmentation, to infer
unobserved bidder and seller characteristics and to account for
heterogeneity in these characteristics. My findings indicate that:
i) bidder valuations are affected by item characteristics (e.g., the
attributes of the coin), seller (e.g. reputation), and auction
characteristics (e.g., the characteristics of the listing); ii)
bidder costs are affected by bidding behavior, such as the recency
of the last purchase and the number of concurrent auctions; and iii)
seller costs are affected by item characteristics and the number of
concurrent listings from the seller (because acquisition costs
evidence increasing marginal values).
Of special interest, the model enables me to compute fee
elasticities, even though no variation in historical fees exists in
these data. I compute fee elasticities by inferring the role of
seller costs in their historical listing decision and then imputing
how an increase in these costs (which arises from more fees) would
affect the seller's subsequent listing behavior. I find that these
implied commission elasticities exceed per-item fee elasticities
because commissions target high value sellers, and hence, commission
reductions enhance their listing likelihood. By targeting commission
reductions to high value sellers, auction house revenues can be
increased by 3.9%. Computing customer value, I find that attrition
of the largest seller would decrease fees paid to the auction house
by $97. Given that the seller paid $127 in fees, competition
offsets only 24% of the fees paid by the seller. In contrast,
competition largely in the form of other bidders offsets 81% of the
$26 loss from buyer attrition. In both events, the auction house
would overvalue its customers by neglecting the effects of
competition.
A Dynamic Model of Sponsored Search Advertising
Sponsored search advertising is ascendant. Jupiter Research reports
that expenditures rose 28% in 2007 to $8.9B and will continue to
rise at a 26% Compound Annual Growth Rate (CAGR), approaching half
the level of television advertising and making sponsored search
advertising one of the major advertising trends affecting the
marketing landscape. Although empirical studies of sponsored search
advertising are ascending, little research exists that explores how
the interactions of various agents (searchers,
advertisers, and the search engine) in keyword
markets affect searcher and advertiser behavior, welfare and search
engine profits. As in the first essay, sponsored search constitutes
a two-sided network. In this case, bidders (advertisers) and
searchers interact on a common platform, the search engine. The
bidder seeks to maximize profits, and the searcher seeks to maximize
utility.
The structural model I propose serves as a foundation to explore
these outcomes and, to my knowledge, is the first structural model
for keyword search. Not only does the model integrate the behavior
of advertisers and searchers, it also accounts for advertisers
competition in a dynamic setting. Prior theoretical research has
assumed a static orientation to the problem whereas prior empirical
research, although dynamic, has focused solely on estimating the
dynamic sales response to a single firm's keyword advertising
expenditures.
To estimate the proposed model, I have developed a two-step Bayesian
estimator for dynamic games. This approach does not rely on
asymptotics and also facilitates a more flexible model
specification.
I fit this model to a proprietary data set provided by an anonymous
search engine. These data include a complete history of consumer
search behavior from the site's web log files and a complete history
of advertiser bidding behavior across all advertisers. In addition,
the data include search engine information, such as keyword pricing
and website design.
With respect to advertisers, I find evidence of dynamic
bidding behavior. Advertiser valuation for clicks on their sponsored
links averages about $0.27. Given the typical $22 retail price of
the software products advertised on the considered search engine,
this figure implies a conversion rate (sales per click) of about
1.2%, well within common estimates of 1-2% (gamedaily.com). With
respect to consumers, I find that frequent clickers place a
greater emphasis on the position of the sponsored advertising link.
I further find that 10% of consumers perform 90% of the clicks.
I then conduct several policy simulations to illustrate the effects
of change in search engine policy. First, I find that the
search engine obtains revenue gains of nearly 1.4% by sharing
individual level information with advertisers and enabling them to
vary their bids by consumer segment. This strategy also improves
advertiser profits by 11% and consumer welfare by 2.9%. Second, I
find that a switch from a first to second price auction results in
truth telling (advertiser bids rise to advertiser valuations), which
is consistent with economic theory. However, the second price
auction has little impact on search engine profits. Third, consumer
search tools lead to a platform revenue increase of 3.7% and an
increase of consumer welfare of 5.6%. However, these tools, by
reducing advertising exposure, lower advertiser profits by 4.1%.
Sponsored Search Auctions: Research Opportunities in Marketing
In the final chapter, I systematically review the literature on
keyword search and propose several promising research directions.
The chapter is organized according to each agent in the search
process, i.e., searchers, advertisers and the search engine, and
reviews the key research issues for each. For each group, I outline
the decision process involved in keyword search. For searchers, this
process involves what to search, where to search, which results to
click, and when to exit the search. For advertisers, this process
involves where to bid, which word or words to bid on, how much to
bid, and how searchers and auction mechanisms moderate these
behaviors. The search engine faces choices on mechanism design,
website design, and how much information to share with its
advertisers and searchers. These choices have implications for
customer lifetime value and the nature of competition among
advertisers. Overall, I provide a number of potential areas of
future research that arise from the decision processes of these
various agents.
Foremost among these potential areas of future research are i) the
role of alternative consumer search strategies for information
acquisition and clicking behavior, ii) the effect of advertiser
placement alternatives on long-term profits, and iii) the measure of
customer lifetime value for search engines. Regarding the first
area, a consumer's search strategy (i.e., sequential search and
non-sequential search) affects which sponsored links are more likely
to be clicked. The search pattern of a consumer is likely to be
affected by the nature of the product (experience product vs. search
product), the design of the website, the dynamic orientation of the
consumer (e.g., myopic or forward-looking), and so on. This search
pattern will, in turn, affect advertisers payments, online traffic,
sales, as well as the search engine's revenue. With respect to the
second area, advertisers must ascertain the economic value of
advertising, conditioned on the slot in which it appears, before
making decisions such as which keywords to bid on and how much to
bid. This area of possible research suggests opportunities to
examine how advertising click-through and the number of impressions
differentially affect the value of appearing in a particular
sponsored slot on a webpage, and how this value is moderated by an
appearance in a non-sponsored slot (i.e., a slot in the organic
search results section). With respect to the third area of future
research, customer value is central to the profitability and
long-term growth of a search engine and affects how the firm should
allocate resources for customer acquisition and retention.
Organization
This dissertation is organized as follows. After this brief
introduction, the essay, ``Online Auction Demand,'' serves as a
basis that introduces some concepts of auctions as two-sided
markets. Next, the second essay, ``A Dynamic Model of Sponsored
Search Advertising,'' extends the first essay by considering a
richer context of bidder competition and consumer choice behavior.
Finally, the concluding chapter, which outlines my future research
interests, considers potential extensions that pertain especially to
sponsored search advertising.
Item Open Access Optimal Monetary and Fiscal Policy for Small Open and Emerging Economies(2010) Fasolo, Angelo MarsigliaThis dissertation computes the optimal monetary and fiscal policy for small open and emerging economies in an estimated medium-scale model. The model departs from the conventional approach as it encompasses all the major nominal and real rigidities normally found in the literature in a single framework. After estimating the model using Bayesian techniques for one small open economy and one emerging economy, the Ramsey solution for the optimal monetary and fiscal policy is computed. Results show that foreign shocks have a strong influence in the dynamics of emerging economies, when compared to the designed optimal policy for a developed small open economy. For both economies, inflation is low, but very volatile, while taxes follow the traditional results in the literature with high taxes over labor income and low taxes for capital income.
Item Open Access Optimal Monetary Policy and Oil Price Shocks(2008-04-25) Kormilitsina, AnnaThis dissertation is comprised of two chapters. In the first chapter, I investigate the role of systematic U.S. monetary policy in the presence of oil price shocks. The second chapter is devoted to studying different approaches to modeling energy demand.
In an influential paper, Bernanke, Gertler, and Watson (1997) and (2004) argue that systematic monetary policy exacerbated the recessions the U.S. economy experienced in the aftermath of post World War II oil price shocks. In the first chapter of this dissertation, I critically evaluate this claim in the context of an estimated medium-scale model of the U.S. business cycle. Specifically, I solve for the Ramsey optimal monetary policy in the medium-scale dynamic stochastic general equilibrium model (henceforth DSGE) of Schmitt-Grohe and Uribe (2005). To model the demand for oil, I use the approach of Finn (2000). According to this approach, the utilization of capital services requires oil usage. In the related literature on the macroeconomic effects of oil price shocks, it is common to calibrate structural parameters of the model. In contrast to this literature, I estimate the parameters of my DSGE model. The estimation strategy involves matching the impulse responses from the theoretical model to responses predicted by an empirical model. For estimation, I use the alternative to the classical Laplace type estimator proposed by Chernozhukov and Hong (2003). To obtain the empirical impulse responses, I identify an oil price shock in a structural VAR (SVAR) model of the U.S. business cycle. The SVAR model predicts that, in response to an oil price increase, GDP, investment, hours, capital utilization, and the real wage fall, while the nominal interest rate and inflation rise. These findings are economically intuitive and in line with the existing empirical evidence. Comparing the actual and the Ramsey optimal monetary policy response to an oil price shock, I find that the optimal policy allows for more inflation, a larger drop in wages, and a rise in hours compared to those actually observed. The central finding of this Chapter is that the optimal policy is associated with a smaller drop in GDP and other macroeconomic variables. The latter results therefore confirm the claim of Bernanke, Gertler and Watson that monetary policy was to a large extent responsible for the recessions that followed the oil price shocks. However, under the optimal policy, interest rates are tightened even more than what is predicted by the empirical model. This result contrasts sharply with the claim of Bernanke, Gertler, and Watson that the Federal Reserve exacerbated recessions by the excessive tightening of interest rates in response to the oil price increases. In contrast to related studies that focus on output stabilization, I find that eliminating the negative response of GDP to an oil price shock is not desirable.
In the second chapter of this dissertation, I compare two approaches to modeling energy sector. Because the share of energy in GDP is small, models of energy have been criticized for their inability to explain sizeable effects of energy price increases on the economic activity. I find that if the price of energy is an exogenous AR(1) process, then the two modeling approaches produce the responses of GDP similar in size to responses observed in most empirical studies, but fail to produce the timing and the shape of the response. DSGE framework can solve the timing and the shape of impulse responses problem, however, fails to replicate the size of the impulse responses. Thus, in DSGE frameworks, amplifying mechanisms for the effect of the energy price shock and estimation based calibration of model parameters are needed to produce the size of the GDP response to the energy price shock.
Item Open Access Preventive Health Behaviors among the Elderly(2008-07-07) Ayyagari, PadmajaThis dissertation consists of three essays that study preventive health behaviors among the elderly U.S. population.
The first essay studies the effect of Medicare coverage on demand for the influenza vaccine. I use a propensity score matching estimator to look at the effect of the 1993 Medicare part B coverage of the flu shot on demand. Using data from the Medicare Current Beneficiary survey, I find that the coverage increases demand by 12.4%. I also find that this effect varies by smoking status and by the presence chronic respiratory illnesses such as COPD, Asthma or Emphysema.
The second essay examines the effect of disease specific health shocks on risk perceptions and demand for the pneumonia vaccine. I find strong evidence of learning - individuals who experience a health shock are less likely to believe that they are not at risk of infection, conditional on prior beliefs. This change in beliefs is accompanied by a corresponding change in demand. Individuals who contract pneumonia or influenza are 60% more likely to vaccinate by the end of next year as compared to those who are not infected.
The third essay studies the relationship between education and health for a sample of elderly diabetics. We identify various mechanisms through which more education leads to improved health. We find that part of the strong positive correlation between educational attainment and health can be explained through differences in cognitive status, self-control and parental characteristics. However, some part of this relationship still remains unexplained.
Item Open Access Research and Development Competition in the Chemicals Industry(2008-04-24) Finger, Stephen RThis dissertation is composed of two related chapters dealing with research and development. I evaluate the effects of the Research and Experimentation Tax Credit on the Chemicals Industry and then examine the determinants of research joint ventures and technological licenses. The first chapter evaluates the equilibrium effects of the Research and Experimentation Tax Credit, taking into consideration firm interactions. The tax credit was put into place to counteract the underinvestment in private R&D caused by firms not internalizing the benefits of technological spillovers from their research. However, this rationale ignored the impact of product market competition. I propose and estimate a structural dynamic oligopoly model of competition in intellectual assets to capture the impact of interactions between firms in the industry. I estimate the dynamic parameters of the model using methods from Bajari, Benkard, and Levin (2007). I build upon previous estimators by incorporating unobserved firm-level heterogeneity using techniques from Arcidiacono and Miller (2007). I use publicly available panel data on firms' R&D expenditures and their patenting activities to measure innovations. In the data, I observe firms that persistently invest more in research and generate more innovations than other firms that are observationally similar. I model this heterogeneity as an unobserved state that raises a firm's research productivity. In my analysis, I find that increased investment in R&D by more advanced firms due to the subsidy, was largely offset by decreases by smaller firms because of the substitutability of knowledge in product market. This greatly reduced the effectiveness of the policy to spur innovation and limited its impact on social welfare. The second chapter examines the cooperation between innovating firms either through technology licensing or research joint ventures. Both of these types of arrangements help to facilitate the dissemination of productive knowledge permitting the increased application of beneficial innovations. As opposed to the first chapter which considers how untargeted, and unintended transfers of knowledge in the form of spillovers, effected an industry, this chapter examines directed transfers of knowledge. I analyze a cross industry data set of joint ventures and technology licensing deals to examine how industry features affect the manner in which knowledge is shared and how the sharing effects research capabilities of deal participants.Item Open Access Social Thought and Social Change: Methodological Dilemmas at the Intersection of Science and Ethics(2010) English, William EdwardI argue that ethical convictions are crucial to the maintenance and transformation of social institutions. Moreover, since ethical convictions are sometimes corrigible and open to persuasive transformation, ethical persuasion can be a powerful source of social change. However, I observe that the dominant analytic techniques of the social sciences are ill equipped to understand the nature and import of ethical convictions, and even less well equipped to inform ethical persuasion. I argue this, in part, explains why social science research has often proved of little value in trying to address prominent social concerns.
This diagnosis raises a puzzle and a challenge. The puzzle is why some social scientists would wholly commit themselves to methods that cannot adequately deal with important dimensions of social structure. I show this is due to a misguided conception of science, one which seeks an "absolute perspective" that requires reducing or explaining away ethical convictions.
The challenge, once this vision of science is rejected in favor of a more pragmatic one, is 1) to understand the systematic limits of different methodological approaches and 2) to see how an account of ethics, rightly understood, can complement social scientific knowledge in service of better social outcomes.
I evaluate three dominant methodological approaches in the social sciences, namely, statistical modeling, formal modeling, and biological-behavioral research. Although all are useful within certain domains, I show that each has systematic limits relating to the dynamism of ethical convictions. I demonstrate how these methods can fail on their own terms and can blind researchers to important resources for social change, such as possibilities for persuasion.
Finally, I develop an account of the relationship between ethics, rationality, and persuasion drawing on the work of Hans-Georg Gadamer, Alasdair MacIntyre, and Charles Taylor. This account rejects prominent "scientific" attempts to explain ethical allegiances as biologically hardwired or structurally determined, and it further challenges accounts of ethical naturalism and pluralistic neutrality.
I conclude by illustrating the constructive role that ethical persuasion has played in a number of development projects, which help demonstrate my thesis that debates about visions of "the good" matter profoundly for human flourishing.
Item Open Access The Microfoundations of Housing Market Dynamics(2008-04-24) Murphy, Alvin DenisThe goal of this dissertation is to provide a coherent and computationally feasible basis for the analysis of the dynamics of both housing supply and demand from a microeconomics perspective. The dissertation includes two papers which incorporate unique micro data with new methodological approaches to examine housing market dynamics. The first paper models the development decisions of land owners as a dynamic discrete choice problem to recover the primitives of housing supply. The second paper develops a new methodology for dynamically estimating the demand for durable goods, such as housing, when the choice set is large.
In the first paper, using the new data set discussed above, I develop and estimate the first dynamic microeconometric model of supply. Parcel owners maximize the discounted sum of expected per-period profits by choosing the optimal time and nature of construction. In addition to current profits, the owners of land also take into account their expectations about future returns to development, balancing expected future prices against expected future costs. This forward looking behavior is crucial in explaining observed aggregate patterns of construction. Finally, the outcomes generated by the parcel owners' profit maximizing behavior, in addition to observable sales prices, allow me to identify the parameters of the per-period profit function at a fine level of geography.
By modeling the optimal behavior of land owners directly, I can capture important aspects of profits that explain both market volatility and geographic differences in construction rates. In particular, the model captures both the role of expectations and of more abstract costs (such as regulation) in determining the timing and volatility of supply in way that would not be possible using aggregate data. The model returns estimates of the various components of profits: prices, variable costs, and the fixed costs of building, which incorporate both physical and regulatory costs.
Estimates of the model suggest that changes in the value of the right-to-build are the primary cause of house price appreciation, that the demographic characteristics of existing residents are determinants of the cost environment, and that physical and regulatory costs are pro-cyclical. Finally, using estimates of the profit function, I explain the role of dynamics in determining the timing of supply by distinguishing the effects of expected future cost changes from the effects of expected future price changes. A counterfactual simulation suggest that pro-cyclical costs, combined with forward looking behavior, significantly dampen construction volatility. These results sheds light on one of the empirical puzzles of the housing market - what determines the volatility of housing construction?
In the second paper, I outline a tractable model of neighborhood choice in a dynamic setting along with a computationally straightforward estimation approach. The approach allows the observed and unobserved features of each neighborhood to evolve in a completely flexible way and uses information on neighborhood choice and the timing of moves to recover semi-parametrically: (i) preferences for housing and neighborhood attributes, (ii) preferences for the performance of the house as a financial asset, and (iii) moving costs. In order to accommodate a number of important features of housing market, this approach extends methods developed in the recent literature on the dynamic demand for durable goods in a number of key ways. The model and estimation approach are applicable to the study of a wide set of dynamic phenomena in housing markets and cities. These include, for example, the analysis of the microdynamics of residential segregation and gentrification within metropolitan areas. More generally, the model and estimation approach can be easily extended to study the dynamics of housing and labor markets in a system of cities.
Item Open Access Three Essays on Analyses of Marine Resources Management with Micro-data(2009) Huang, LingChapter 1: Although there are widely accepted theoretical explanations for overexploitation of common-pool resources, empirically we have limited information about the micro-level mechanisms that cause individually efficient exploitation to result in macro inefficiency. This paper conducts the first empirical investigation of common-pool resource users' dynamic and strategic behavior at the micro level. With an application to the North Carolina shrimp fishery, we examine fishermen's strategies in a fully dynamic game that accounts for latent resource dynamics and other players' actions. Combining a simulation-based Conditional Choice Probability estimator and a Pseudo Maximum Likelihood estimator, we recover the profit structure of the fishery from fishermen's repeated choices. Using the estimated structural parameters, we compare the fishermen's actual exploitation path to the socially optimal one under a time-specific limited entry system with transferrable permits, and then quantify the dynamic efficiency costs of common-pool resource use. We find that individual fishermen respond to other users by exerting a higher level of exploitation effort than what is socially optimal. Based on our counterfactual experiments, we estimate the efficiency costs of this behavior to be 17.39\% of the annual revenues from the fishery, which translates into 31.4\% of the rent without deducting the cost of capital.
Chapter 2: Although hypoxia is a threat to coastal ecosystems, policy makers have limited information about the potential economic impacts on fisheries. Studies using spatially and temporally aggregated data generally fail to detect statistically significant fishery effects of hypoxia. Limited recent work using disaggregated fishing data (microdata) reports modest effects of hypoxia on catches of recreationally harvested species. These prior studies have not accounted for important spatial and temporal aspects of the system, however. For example, the effects of hypoxia on catches may not materialize instantaneously but instead may involve a lagged process with catches reflecting cumulative past exposure to environmental conditions. This paper develops a differenced bioeconomic model to account for the lagged effects of hypoxia on the North Carolina brown shrimp fishery. It integrates high-resolution oxygen monitoring data with fishery-dependent microdata from North Carolina's trip ticket program to investigate the detailed spatial and temporal relationships of hypoxia to commercial fishery harvest. The main finding is that hypoxia potentially resulted in a 12.9\% annual decrease in brown shrimp harvest from 1999-2005. The paper also develops two alternative models---a non-differenced model and a polynomial distributed lag model---and results are consistent with the main model.
Chapter 3: The emergence of ecosystem-based management suggests that traditional fisheries
management and protection of environmental quality are increasingly interrelated. Fishery managers, however, have limited control over most sources of marine and estuarine pollution and at best can only adapt to environmental conditions. We develop a bioeconomic model of optimal harvest of an annual species that is subject to an environmental disturbance. We parameterize the model to analyze the effect of hypoxia (low dissolved oxygen) on the optimal harvest path of brown shrimp, a commercially important species that is fished in hypoxic waters in the Gulf of Mexico and in estuaries in the southeastern United States. We find that hypoxia alters the qualitative pattern of optimal harvest and shifts the season opening earlier in the year; more severe hypoxia leads to even earlier season openings. However, the quantitative effects of adapting fishery management to hypoxia in terms of fishery rents are small. This suggests that it is critical for other regulatory agencies to control estuarine pollution, and fishery managers need to generate value from the fishery resources through other means such as rationalization.