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Keywords:bootstrap 

Working Paper
Poor (Wo)man’s Bootstrap

The bootstrap is a convenient tool for calculating standard errors of the parameters of complicated econometric models. Unfortunately, the fact that these models are complicated often makes the bootstrap extremely slow or even practically infeasible. This paper proposes an alternative to the bootstrap that relies only on the estimation of one-dimensional parameters. The paper contains no new difficult math. But we believe that it can be useful.
Working Paper Series , Paper WP-2015-1

Working Paper
The Uniform Validity of Impulse Response Inference in Autoregressions

Existing proofs of the asymptotic validity of conventional methods of impulse response inference based on higher-order autoregressions are pointwise only. In this paper, we establish the uniform asymptotic validity of conventional asymptotic and bootstrap inference about individual impulse responses and vectors of impulse responses when the horizon is fixed with respect to the sample size. For inference about vectors of impulse responses based on Wald test statistics to be uniformly valid, lag-augmented autoregressions are required, whereas inference about individual impulse responses is ...
Working Papers , Paper 1908

Working Paper
Easy Bootstrap-Like Estimation of Asymptotic Variances

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
Sample Bias Related to Household Role

This paper develops a two-stage statistical analysis to identify and assess the effect of a sample bias associated with an individual's household role. Survey responses to questions about the respondent's role in household finances and a sampling design in which some households have all members take the survey enable the estimation of distributions for each individual's share of household responsibility. The methodology is applied to the 2017 Survey of Consumer Payment Choice. The distribution of responsibility shares among survey respondents suggests that the sampling procedure favors ...
FRB Atlanta Working Paper , Paper 2021-9

Working Paper
Non-linearity in the Inflation-Growth Relationship in Developing Economies: Evidence from a Semiparametric Panel Model

Using data on developing economies, we estimate a flexible semiparametric panel data model that incorporates potentially nonlinear effects of inflation on economic growth. We find that inflation is associated with significantly lower growth only after it reaches about 12 percent, which is notably lower than the comparable estimate obtained from a threshold model. Our results also suggest that models with restrictive functional form assumptions tend to underestimate marginal effects of inflation on economic growth. We also document significant variation in the effect of inflation on growth ...
Finance and Economics Discussion Series , Paper 2014-51

Working Paper
Simpler Bootstrap Estimation of the Asymptotic Variance of U-statistic Based Estimators

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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Honore, Bo E. 3 items

Hu, Luojia 3 items

Baglan, Deniz 1 items

Hitczenko, Marcin 1 items

Inoue, Atsushi 1 items

Kilian, Lutz 1 items

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