There are many bootstrap methods that can be used for econometric analysis. In certain circumstances, such as … regression models with independent and identically distributed error terms, appropriately chosen bootstrap methods generally work … very well. However, there are many other cases, such as regression models with dependent errors, in which bootstrap methods …

(2005). At the same time, I calculate the confidence intervals for the microdecomposition estimations with a bootstrap …

methods for selecting bandwidths that under- or oversmooth. This paper extends the bootstrap method of Hall and Horowitz (2013 …) for conditional mean functions to conditional quantile functions. The paper also shows how the bootstrap method can be … used to obtain uniform confidence bands. The bootstrap method uses only bandwidths that are selected by standard methods …

estimation, especially, when researchers use bootstrap to estimate standard errors, which may be wrong without a global estimator …

the distribution of a suitable estimator theta_n, its bootstrap approximation, and the Bayesian posterior for theta all … distribution of g(theta) and the bootstrap distribution of theta_n coincide asymptotically. One implication is that Bayesians can … interpret bootstrap inference for g(theta) as approximately valid posterior inference in a large sample. Another implication …

the AIC, BIC, or HQIC, and to implement a bootstrap procedure to compute p-values and critical values. …

In this study, we developed an inference procedure for the neural network using the bootstrap approach, and applied it …

-temporal changes in poverty from year 1978 to 2003. Results are decomposed by region and household types, and the bootstrap method is …