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Jel Classification:C15 

Working Paper
Measuring Transaction Costs in the Absence of Timestamps
Zikes, Filip (2017-04-06)
This paper develops measures of transaction costs in the absence of transaction timestamps and information about who initiates transactions, which are data limitations that often arise in studies of over-the-counter markets. I propose new measures of the effective spread and study the performance of all estimators analytically, in simulations, and present an empirical illustration with small-cap stocks for the 2005-2014 period. My theoretical, simulation, and empirical results provide new insights into measuring transaction costs and may help guide future empirical work.
Finance and Economics Discussion Series , Paper 2017-045

Working Paper
Complementarity and Macroeconomic Uncertainty
Plante, Michael D.; Atkinson, Tyler; Throckmorton, Nathaniel A.; Richter, Alexander W. (2020-03-31)
Macroeconomic uncertainty—the conditional volatility of the unforecastable component of a future value of a time series—shows considerable variation in the data. A typical assumption in business cycle models is that production is Cobb-Douglas. Under that assumption, this paper shows there is usually little, if any, endogenous variation in output uncertainty, and first moment shocks have similar effects in all states of the economy. When the model departs from Cobb-Douglas production and assumes capital and labor are gross complements, first-moment shocks have state-dependent effects and ...
Working Papers , Paper 2009

Working Paper
Improved Estimation of Poisson Rate Distributions through a Multi-Mode Survey Design
Hitczenko, Marcin (2021-02-03)
Researchers interested in studying the frequency of events or behaviors among a population must rely on count data provided by sampled individuals. Often, this involves a decision between live event counting, such as a behavioral diary, and recalled aggregate counts. Diaries are generally more accurate, but their greater cost and respondent burden generally yield less data. The choice of survey mode, therefore, involves a potential tradeoff between bias and variance of estimators. I use a case study comparing inferences about payment instrument use based on different survey designs to ...
FRB Atlanta Working Paper , Paper 2021-10

Working Paper
Mobility and Engagement Following the SARS-Cov-2 Outbreak
Koenig, Evan F.; Koch, Christoffer; Dolmas, Jim; Murphy, Anthony; Mertens, Karel; Yi, Kei-Mu; Atkinson, Tyler (2020-05-21)
We develop a Mobility and Engagement Index (MEI) based on a range of mobility metrics from Safegraph geolocation data, and validate the index with mobility data from Google and Unacast. We construct MEIs at the county, MSA, state and nationwide level, and link these measures to indicators of economic activity. According to our measures, the bulk of sheltering-in-place and social disengagement occurred during the week of March 15 and simultaneously across the U.S. At the national peak of the decline in mobility in early April, localities that engaged in a 10% larger decrease in mobility than ...
Working Papers , Paper 2014

Working Paper
Easy Bootstrap-Like Estimation of Asymptotic Variances
Hu, Luojia; Honore, Bo E. (2018-06-29)
The bootstrap is a convenient tool for calculating standard errors of the parameter estimates of complicated econometric models. Unfortunately, the bootstrap can be very time-consuming. In a recent paper, Honor and Hu (2017), we propose a ?Poor (Wo)man's Bootstrap? based on one-dimensional estimators. In this paper, we propose a modified, simpler method and illustrate its potential for estimating asymptotic variances.
Working Paper Series , Paper WP-2018-11

Working Paper
A staggered pricing approach to modeling speculative storage: implications for commodity price dynamics
Dabbous, Amal; Gospodinov, Nikolay; Assa, Hirbod (2013-09-01)
This paper embeds a staggered price feature into the standard speculative storage model of Deaton and Laroque (1996). Intermediate goods inventory speculators are added as an additional source of intertemporal linkage, which helps us to replicate the stylized facts of the observed commodity price dynamics. Incorporating this type of friction into the model is motivated by its ability to increase price stickiness which, gives rise to a higher degree of persistence in the first two conditional moments of commodity prices. The structural parameters of our model are estimated by the simulated ...
FRB Atlanta Working Paper , Paper 2013-08

Working Paper
Empirical Bayes Control of the False Discovery Exceedance
Basu, Pallavi; Fu, Luella; Saretto, Alessio; Sun, Wenguang (2021-11-18)
In sparse large-scale testing problems where the false discovery proportion (FDP) is highly variable, the false discovery exceedance (FDX) provides a valuable alternative to the widely used false discovery rate (FDR). We develop an empirical Bayes approach to controlling the FDX. We show that for independent hypotheses from a two-group model and dependent hypotheses from a Gaussian model fulfilling the exchangeability condition, an oracle decision rule based on ranking and thresholding the local false discovery rate (lfdr) is optimal in the sense that the power is maximized subject to FDX ...
Working Papers , Paper 2115

Working Paper
High-Dimensional DSGE Models: Pointers on Prior, Estimation, Comparison, and Prediction∗
Shin, Minchul; Tan, Fei; Chib, Siddhartha (2020-09-15)
Working Papers , Paper 20-35

Working Paper
Explaining Machine Learning by Bootstrapping Partial Marginal Effects and Shapley Values
Cook, Thomas R.; Modig, Zach; Palmer, Nathan M. (2024-09-20)
Machine learning and artificial intelligence are often described as “black boxes.” Traditional linear regression is interpreted through its marginal relationships as captured by regression coefficients. We show that the same marginal relationship can be described rigorously for any machine learning model by calculating the slope of the partial dependence functions, which we call the partial marginal effect (PME). We prove that the PME of OLS is analytically equivalent to the OLS regression coefficient. Bootstrapping provides standard errors and confidence intervals around the point ...
Finance and Economics Discussion Series , Paper 2024-075

Working Paper
A moment-matching method for approximating vector autoregressive processes by finite-state Markov chains
Gospodinov, Nikolay; Lkhagvasuren, Damba (2013-09-01)
This paper proposes a moment-matching method for approximating vector autoregressions by finite-state Markov chains. The Markov chain is constructed by targeting the conditional moments of the underlying continuous process. The proposed method is more robust to the number of discrete values and tends to outperform the existing methods for approximating multivariate processes over a wide range of the parameter space, especially for highly persistent vector autoregressions with roots near the unit circle.
FRB Atlanta Working Paper , Paper 2013-05

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