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Working Paper
A Robust Method for Microforecasting and Estimation of Random Effects
Giacomini, Raffaella; Lee, Sokbae; Sarpietro, Silvia (2023-08-02)
We propose a method for forecasting individual outcomes and estimating random effects in linear panel data models and value-added models when the panel has a short time dimension. The method is robust, trivial to implement and requires minimal assumptions. The idea is to take a weighted average of time series- and pooled forecasts/estimators, with individual weights that are based on time series information. We show the forecast optimality of individual weights, both in terms of minimax-regret and of mean squared forecast error. We then provide feasible weights that ensure good performance ...
Working Paper Series , Paper WP 2023-26

Working Paper
Liquidity Networks, Interconnectedness, and Interbank Information Asymmetry
Harris, Jeffrey H.; Brunetti, Celso; Mankad, Shawn (2021-03-19)
Network analysis has demonstrated that interconnectedness among market participants results in spillovers, amplifies or absorbs shocks, and creates other nonlinear effects that ultimately affect market health. In this paper, we propose a new directed network construct, the liquidity network, to capture the urgency to trade by connecting the initiating party in a trade to the passive party. Alongside the conventional trading network connecting sellers to buyers, we show both network types complement each other: Liquidity networks reveal valuable information, particularly when information ...
Finance and Economics Discussion Series , Paper 2021-017

Working Paper
A Closer Look at the Behavior of Uncertainty and Disagreement: Micro Evidence from the Euro Area
Tracy, Joseph; Rich, Robert W. (2018-09-28)
This paper examines point and density forecasts of real GDP growth, inflation and unemployment from the European Central Bank?s Survey of Professional Forecasters. We present individual uncertainty measures and introduce individual point- and density-based measures of disagreement. The data indicate substantial heterogeneity and persistence in respondents? uncertainty and disagreement, with uncertainty associated with prominent respondent effects and disagreement associated with prominent time effects. We also examine the co-movement between uncertainty and disagreement and find an ...
Working Papers (Old Series) , Paper 1813

Journal Article
Lockdown Responses to COVID-19
Gutkowski, Violeta A. (2021-04-15)
This article describes the relationship between countries' lockdown responses to the COVID-19 pandemic and those countries' political rights and civil liberties, macroeconomic variables, and vulnerability to the virus. Political rights and civil liberties cannot explain the differences in lockdown timing across countries. Countries with high contagion exposure due to weak water sanitation and weak health systems locked down their economies as fast as possible to reduce contagion. However, countries more vulnerable to COVID-19 due to large fractions of elderly and smokers in the population did ...
Review , Volume 103 , Issue 2 , Pages 127-151

Report
The behavior of uncertainty and disagreement and their roles in economic prediction: a panel analysis
Tracy, Joseph; Rich, Robert W. (2017-02-01)
This paper examines point and density forecasts from the European Central Bank?s Survey of Professional Forecasters. We derive individual uncertainty measures along with individual point- and density-based measures of disagreement. We also explore the relationship between uncertainty and disagreement, as well as their roles in respondents? forecast performance and forecast revisions. We observe substantial heterogeneity in respondents? uncertainty and disagreement. In addition, there is little co-movement between uncertainty and disagreement, and forecast performance shows a more robust ...
Staff Reports , Paper 808

Working Paper
Selecting Primal Innovations in DSGE models
Ferroni, Filippo; León-Ledesma, Miguel A.; Grassi, Stefano (2017-08-01)
DSGE models are typically estimated assuming the existence of certain primal shocks that drive macroeconomic fluctuations. We analyze the consequences of estimating shocks that are "non-existent" and propose a method to select the primal shocks driving macroeconomic uncertainty. Forcing these non-existing shocks in estimation produces a downward bias in the estimated internal persistence of the model. We show how these distortions can be reduced by using priors for standard deviations whose support includes zero. The method allows us to accurately select primal shocks and estimate model ...
Working Paper Series , Paper WP-2017-20

Working Paper
BLP Estimation Using Laplace Transformation and Overlapping Simulation Draws
Hong, Han; Li, Jessie; Li, Huiyu (2019-09-04)
We derive the asymptotic distribution of the parameters of the Berry et al. (1995, BLP) model in a many markets setting which takes into account simulation noise under the assumption of overlapping simulation draws. We show that, as long as the number of simulation draws R and the number of markets T approach infinity, our estimator is ?m = ?min(R,T) consistent and asymptotically normal. We do not impose any relationship between the rates at which R and T go to infinity, thus allowing for the case of R
Working Paper Series , Paper 2019-24

Journal Article
Is the Phillips Curve Still Alive?
Wen, Yi; Reinbold, Brian (2020-05)
A.W. Phillips's discovery that inflation is negatively correlated with unemployment served as a heuristic model for conducting monetary policy; but the flattening of the Phillips curve post-1970 has divided debate on this empirical relation into two camps: "The Phillips curve is alive and well," and "The Phillips curve is dead." However, this dichotomy oversimplifies the issue.
Review , Volume 102 , Issue 2 , Pages 121-144

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
Simpler Bootstrap Estimation of the Asymptotic Variance of U-statistic Based Estimators
Hu, Luojia; Honore, Bo E. (2015-09-15)
The bootstrap is a popular and useful tool for estimating the asymptotic variance of complicated estimators. Ironically, the fact that the estimators are complicated can make the standard bootstrap computationally burdensome because it requires repeated re-calculation of the estimator. In Honor and Hu (2015), we propose a computationally simpler bootstrap procedure based on repeated re-calculation of one-dimensional estimators. The applicability of that approach is quite general. In this paper, we propose an alternative method which is specific to extremum estimators based on U-statistics. ...
Working Paper Series , Paper WP-2015-7

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