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Economics Ph.D.: Publications since January 2019

List all publications in the database.    :chronological  alphabetical  combined listing:
%% Abrahams, Scott   
@article{fds352483,
   Author = {Abrahams, S},
   Title = {Officer differences in traffic stops of minority
             drivers},
   Journal = {Labour Economics},
   Volume = {67},
   Pages = {101912-101912},
   Publisher = {Elsevier BV},
   Year = {2020},
   Month = {December},
   url = {http://dx.doi.org/10.1016/j.labeco.2020.101912},
   Abstract = {© 2020 Elsevier B.V. This paper uses a finite mixture model
             to demonstrate that some police officers are more likely
             than others to stop black drivers. The conclusion is one
             that though widely believed has proven challenging to
             establish empirically. By doing so, the paper makes two
             contributions, one conceptual and one statistical. First, it
             more closely aligns with the understanding of racial
             profiling as signifying that black individuals experience
             more frequent interaction with the police. While
             disproportional susceptibility to vehicle searches also
             exemplifies profiling, being pulled over is a much more
             common margin for potential profiling, which this paper
             models a tractable way of identifying. Second, studies of
             secondary decisions such as searches frequently assume that
             there is no bias in the initial stop decision. An analysis
             of traffic stops across eight states questions this
             assumption, concluding that stopped drivers constitute a
             selected sample. Although bias is theoretically continuous,
             average behavior actually fits well into two distinct
             groups, with 30–40% of officers in the group that exhibits
             a relatively high propensity to stop black drivers. The
             implication is that race-based policing is more prevalent
             than the “rotten apples” theory might
             suggest.},
   Doi = {10.1016/j.labeco.2020.101912},
   Key = {fds352483}
}

@article{fds352484,
   Author = {Wiemers, EE and Abrahams, S and AlFakhri, M and Hotz, VJ and Schoeni,
             RF and Seltzer, JA},
   Title = {Disparities in vulnerability to complications from COVID-19
             arising from disparities in preexisting conditions in the
             United States.},
   Journal = {Research in Social Stratification and Mobility},
   Volume = {69},
   Pages = {100553},
   Year = {2020},
   Month = {October},
   url = {http://dx.doi.org/10.1016/j.rssm.2020.100553},
   Abstract = {The COVID-19 pandemic has magnified U.S. health disparities.
             Though disparities in COVID-19 hospitalization by
             race-ethnicity are large, disparities by income and
             education have not been studied. Using an index based on
             preexisting health conditions and age, we estimate
             disparities in vulnerability to hospitalization from
             COVID-19 by income, education, and race-ethnicity for U.S.
             adults. The index uses estimates of health condition and age
             effects on hospitalization for respiratory distress prior to
             the pandemic validated on COVID-19 hospitalizations. We find
             vulnerability arising from preexisting conditions is nearly
             three times higher for bottom versus top income quartile
             adults and 60 % higher for those with a high-school degree
             relative to a college degree. Though non-Hispanic Blacks are
             more vulnerable than non-Hispanic Whites at comparable ages,
             among all adults the groups are equally vulnerable because
             non-Hispanic Blacks are younger. Hispanics are the least
             vulnerable. Results suggest that income and education
             disparities in hospitalization are likely large and should
             be examined directly to further understand the unequal
             impact of the pandemic.},
   Doi = {10.1016/j.rssm.2020.100553},
   Key = {fds352484}
}


%% Aleti, Saketh   
@article{fds352585,
   Author = {Aleti, S and Mizrach, B},
   Title = {Bitcoin Spot and Futures Market Microstructure},
   Journal = {Journal of Futures Markets},
   Year = {2020},
   Month = {October},
   Abstract = {We study Bitcoin (BTC) trading at the Chicago Mercantile
             Exchange (CME) and four settlement spot exchanges that
             transact $146 million per day in the BTC/USD pair. Spot
             market median trade sizes are under $1,300 but exceed
             $18,000 on the CME. Bid‐ask spreads average 0.0298%. Trade
             sizes of over $1 million move markets by less than 1%. 2.5%
             of trades and 15.5% of cancellations on Coinbase take place
             within 50 ms. Bid‐ask spreads exceed 0.8% for only
             226 s. Most executions trade‐through better quotes, with
             estimated losses of $36 million. The CME leads price
             discovery. BTC leads Ethereum price adjustment.},
   Key = {fds352585}
}

@article{fds352185,
   Author = {Aleti, S and Hochman, G},
   Title = {Non-Constant Elasticity of Substitution and Intermittent
             Renewable Energy},
   Journal = {Agricultural and Resource Economics Review},
   Volume = {49},
   Number = {2},
   Pages = {321-359},
   Publisher = {Cambridge University Press (CUP)},
   Year = {2020},
   Month = {August},
   url = {http://dx.doi.org/10.1017/age.2020.7},
   Abstract = {In this article, we present a model of the electricity
             sector where generation technologies are intermittent. The
             economic value of an electricity generation technology is
             given by integrating its production profile with the market
             price of electricity. We use estimates of the consumer's
             intertemporal elasticity of substitution for electricity
             consumption while parameterizing the model empirically to
             numerically calculate the elasticity between renewables and
             fossil energy. We find that there is a non-constant
             elasticity of substitution between renewable and fossil
             energy that depends on prices and intermittency. This
             suggests that the efficacy and welfare effects of carbon
             taxes and renewable subsidies vary geographically.
             Subsidizing research into battery technology and tailoring
             policy for local energy markets can mitigate these
             distributional side effects while complementing traditional
             policies used to promote renewable energy.},
   Doi = {10.1017/age.2020.7},
   Key = {fds352185}
}


%% League, Riley   
@article{fds349572,
   Author = {Fitz, D and League, R},
   Title = {The impact of early-life shocks on adult welfare in Brazil:
             Questions of measurement and timing},
   Journal = {Economics and Human Biology},
   Volume = {37},
   Pages = {100843-100843},
   Publisher = {Elsevier BV},
   Year = {2020},
   Month = {May},
   url = {http://dx.doi.org/10.1016/j.ehb.2019.100843},
   Doi = {10.1016/j.ehb.2019.100843},
   Key = {fds349572}
}


%% Salim Saker Chaves, Leonardo   
@article{fds350084,
   Author = {Bollerslev, T and Li, J and Chaves, LSS},
   Title = {Generalized Jump Regressions for Local Moments},
   Journal = {Journal of Business & Economic Statistics},
   Year = {2020},
   Month = {January},
   url = {http://dx.doi.org/10.1080/07350015.2020.1753526},
   Abstract = {© 2020, © 2020 American Statistical Association. We
             develop new high-frequency-based inference procedures for
             analyzing the relationship between jumps in instantaneous
             moments of stochastic processes. The estimation consists of
             two steps: the nonparametric determination of the jumps as
             differences in local averages, followed by a
             minimum-distance type estimation of the parameters of
             interest under general loss functions that include both
             least-square and more robust quantile regressions as special
             cases. The resulting asymptotic distribution of the
             estimator, derived under an infill asymptotic setting, is
             highly nonstandard and generally not mixed normal. In
             addition, we establish the validity of a novel bootstrap
             algorithm for making feasible inference including
             bias-correction. The new methods are applied in a study on
             the relationship between trading intensity and spot
             volatility in the U.S. equity market at the time of
             important macroeconomic news announcement.},
   Doi = {10.1080/07350015.2020.1753526},
   Key = {fds350084}
}


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