We propose a sieve bootstrap framework to conduct pointwise and simultaneous inference
for time-varying coefficient regression models based on a local linear estimator. The …

High dimensional predictive regressions are useful in wide range of applications. However,
the theory is mainly developed assuming that the model is stationary with time invariant …

This paper considers nonparametric additive models that have a deterministic time trend
and both stationary and integrated variables as components. The diverse nature of the …

Estimation for single-index and partially linear single-index integrated models Page 1 The
Annals of Statistics 2016, Vol. 44, No. 1, 425–453 DOI: 10.1214/15-AOS1372 © Institute of …

The paper focuses on the smooth and sharp structural changes in crude oil futures volatility
and singles out the flexible Fourier form (FFF) and the modified ICSS algorithm to detect …

We propose a panel data model for nonstationary variables with interactive fixed effects and
coefficients that may vary over time and use it to examine time variation in the income …

GARCH-type models have been widely used for forecasting crude oil price volatility, but
often ignore the structural changes of time series, which may lead to spurious volatility …

This paper analyzes the cointegration of electricity consumption, prices, and GDP as well as
the long-run price and income elasticities for a sample of European Union (EU) countries …

The common practice in cointegrating polynomial regressions (CPRs) often confines
nonlinearities in the variable of interest to stochastic trends, thereby overlooking the …

This paper studies nonlinear cointegrating models with time-varying coefficients and
multiple nonstationary regressors using classic kernel smoothing methods to estimate the …