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Estimating the Impacts of Program Benefits : Using Instrumental Variables with Underreported and Imputed Data

Stephens, Melvin - 2015

Survey non-response has risen in recent years which has increased the share of imputed and underreported values found on commonly used datasets. While this trend has been well-documented for earnings, the growth in non-response to government transfers questions has received far less attention....

Persistent link: https://www.econbiz.de/10013021468

Tests for Unit Roots : a Monte Carlo Investigation

Schwert, G. William - 2021

Recent work by Said and Dickey (1984 ,1985) , Phillips (1987), and Phillips and Perron(1988) examines tests for unit roots in the autoregressive part of mixed autoregressive-integrated-moving average (ARIHA) models (tests for stationarity). Monte Carlo experiments show that these unit root tests...

Persistent link: https://www.econbiz.de/10013240352

Using Wasserstein Generative Adversarial Networks for the Design of Monte Carlo Simulations

Athey, Susan - 2019

their analytic approach to a given setting, and (ii) systematic simulation studies can be helpful for selecting among …

Persistent link: https://www.econbiz.de/10012857741

One-Node Quadrature Beats Monte Carlo : A Generalized Stochastic Simulation Algorithm

Judd, Kenneth L. - 2011

In conventional stochastic simulation algorithms, Monte Carlo integration and curve fitting are merged together and … stochastic simulation approach in which integration and curve fitting are separated. We specifically allow for the use of … achieve accuracy of solutions that is orders of magnitude higher than that of the conventional stochastic simulation …

Persistent link: https://www.econbiz.de/10013131303

DSGE Models in a Data-Rich Environment

Boivin, Jean - 2011

Standard practice for the estimation of dynamic stochastic general equilibrium (DSGE) models maintains the assumption that economic variables are properly measured by a single indicator, and that all relevant information for the estimation is summarized by a small number of data series. However,...

Persistent link: https://www.econbiz.de/10013118075

DSGE Models in a Data-Rich Environment

Boivin, Jean - 2012

Persistent link: https://www.econbiz.de/10013106021

DSGE Models in a Data-Rich Environment

Boivin, Jean - 2007

Persistent link: https://www.econbiz.de/10012778086

Piecewise-Linear Approximations and Filtering for DSGE Models with Occasionally Binding Constraints

Aruoba, S. Borağan; Cuba-Borda, Pablo; Higa-Flores, Kenji - 2022

We develop an algorithm to construct approximate decision rules that are piecewise-linear and continuous for DSGE models with an occasionally binding constraint. The functional form of the decision rules allows us to derive a conditionally optimal particle filter (COPF) for the evaluation of the...

Persistent link: https://www.econbiz.de/10014091400

Trimming for Bounds on Treatment Effects with Missing Outcomes

Lee, David S. - 2021

Empirical researchers routinely encounter sample selection bias whereby 1) the regressor of interest is assumed to be exogenous, 2) the dependent variable is missing in a potentially non-random manner, 3) the dependent variable is characterized by an unbounded (or very large) support, and 4) it...

Persistent link: https://www.econbiz.de/10013235319

Selection in Surveys

Dutz, Deniz; Huitfeldt, Ingrid; Lacouture, Santiago; … - 2022

We evaluate how nonresponse affects conclusions drawn from survey data and consider how researchers can reliably test and correct for nonresponse bias. To do so, we examine a survey on labor market conditions during the COVID-19 pandemic that used randomly assigned financial incentives to...

Persistent link: https://www.econbiz.de/10013311888