Functional Coefficient Models under Unit Root Behavior
نویسندگان
چکیده
Abstract. We analyze the statistical properties of nonparametrically estimated functions in a functional-coefficient model if the data has a unit root. We show that the estimated function converges at a faster rate than under the stationary case. However, the estimator has a mixed normal distribution so that point-wise confidence intervals are calculated using the usual normal distribution theory rather than a Dickey-Fuller distribution. We illustrate the estimation procedure using U.S. unemployment and interest rate data.
منابع مشابه
Seasonality and Forecasting of Monthly Broiler Price in Iran
The objective of this study was to model seasonal behavior of broiler price in Iran that can be used to forecast the monthly broiler prices. In this context, the periodic autoregressive (PAR), the seasonal integrated models, and the Box-Jenkins (SARIMA) models were used as the primary nominates for the forecasting model. It was shown that the PAR (q) model could not be considered as an appropri...
متن کاملSemiparametric Profile Likelihood Estimation of Varying Coefficient Models with Nonstationary Regressors
We study a partially linear varying coefficient model where the regressors are generated by the multivariate unit root I(1) processes. The influence of the explanatory vectors on the response variable satisfies the semiparametric partially linear structure with the nonlinear component being functional coefficients. The profile likelihood estimation methodology with the first-stage local polynom...
متن کاملSemiparametric Quantile Regression Estimation in Dynamic Models with Partially Varying Coefficients∗
We study quantile regression estimation for dynamic models with partially varying coefficients so that the values of some coefficients may be functions of informative covariates. Estimation of both parametric and nonparametric functional coefficients are proposed. In particular, we propose a three stage semiparametric procedure. Both consistency and asymptotic normality of the proposed estimato...
متن کاملSieve Instrumental Variable Quantile Regression Estimation of Functional Coefficient Models∗
In this paper, we consider sieve instrumental variable quantile regression (IVQR) estimation of functional coefficient models where the coefficients of endogenous regressors are unknown functions of some exogenous covariates. We approximate the unknown functional coefficients by some basis functions and estimate them by the IVQR technique. We establish the uniform consistency and asymptotic nor...
متن کاملUnit Root Model Selection*
Some limit properties for information based model selection criteria are given in the context of unit root evaluation and various assumptions about initial conditions. Allowing for a nonparametric short memory component, standard information criteria are shown to be weakly consistent for a unit root provided the penalty coefficient Cn ! 1 and Cn/n ! 0 as n ! 1. Strong consistency holds when Cn/...
متن کامل