Showing 1 - 10 of 421
Researchers often rely on the t-statistic to make inference on parameters in statistical models. It is common practice to obtain critical values by simulation techniques. This paper proposes a novel numerical method to obtain an approximately similar test. This test rejects the null hypothesis...
Persistent link: https://www.econbiz.de/10011485576
This article generalizes and extends the kernel block bootstrap (KBB) method of Parente and Smith (2018, 2021) to provide a comprehensive treatment of its use for GMM estimation and inference in time-series models formulated in terms of moment conditions. KBB procedures that employ bootstrap...
Persistent link: https://www.econbiz.de/10014520806
We investigate a model in which we connect slowly time varying unconditional long-run volatility with short …-run conditional volatility whose representation is given as a semi-strong GARCH (1,1) process with heavy tailed errors. We focus on … robust estimation of both long-run and short-run volatilities. Our estimation is semiparametric since the long-run volatility …
Persistent link: https://www.econbiz.de/10009719116
estimation strategy is applicable to both parametric and nonparametric stochastic volatility models, and can handle both jumps …A two-step estimation method of stochastic volatility models is proposed. In the first step, we nonparametrically … estimate the (unobserved) instantaneous volatility process. In the second step, standard estimation methods for fully observed …
Persistent link: https://www.econbiz.de/10010487528
This paper is concerned with developing uniform confidence bands for functions estimated nonparametrically with instrumental variables. We show that a sieve nonparametric instrumental variables estimator is pointwise asymptotically normally distributed. The asymptotic normality result holds in...
Persistent link: https://www.econbiz.de/10003869256
This paper considers semiparametric efficient estimation of conditional moment models with possibly nonsmooth residuals in unknown parametric components (Θ) and unknown functions (h)of endogenous variables. We show that: (1) the penalized sieve minimum distance(PSMD) estimator (ˆΘ, ˆh) can...
Persistent link: https://www.econbiz.de/10003869261
Persistent link: https://www.econbiz.de/10003454059
This paper is concerned with developing uniform confidence bands for functions estimated nonparametrically with instrumental variables. We show that a sieve nonparametric instrumental variables estimator is pointwise asymptotically normally mental variables estimator is pointwise asymptotically...
Persistent link: https://www.econbiz.de/10003990115
Persistent link: https://www.econbiz.de/10003671278
Standard approaches to constructing nonparametric confidence bands for functions are frustrated by the impact of bias, which generally is not estimated consistently when using the bootstrap and conventionally smoothed function estimators. To overcome this problem it is common practice to either...
Persistent link: https://www.econbiz.de/10009554351