Yicong Lin

Vrije Universiteit Amsterdam | VU · Department of Econometrics and Data Science

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 asymptotic validity of the sieve bootstrap in the presence of autocorrelation is established. The bootstrap automatically produces a consistent estimate of nuisance parameters,...

We develop a Feasible Generalized Least Squares estimator of the date of a structural break in level and/or trend. The estimator is based on a consistent estimation of a T-dimensional inverse autoco-variance matrix. A cubic polynomial transformation of break date estimates can be approximated by a nonstandard yet nuisance parameter free distributio...

We propose a sieve bootstrap framework to conduct pointwise and simultaneous inference for time-varying coefficient regression models based on a nonparametric local linear estimator. The asymptotic validity of the sieve bootstrap in the presence of autocorrelation is established. We find that it automatically produces a consistent estimation of nui...

The environmental Kuznets curve predicts an inverted U-shaped relationship between environmental pollution and economic growth. Current analyses frequently employ models which restrict nonlinearities in the data to be explained by the economic growth variable only. We propose a Generalized Cointegrating Polynomial Regression (GCPR) to allow for an...

This paper develops the asymptotic theory of a Fully Modified Generalized Least Squares estimator for multivariate cointegrating polynomial regressions. Such regressions allow for deterministic trends, stochastic trends and integer powers of stochastic trends to enter the coin-tegrating relations. Our fully modified estimator incorporates: (1) the...

This paper develops the asymptotic theory of a Fully Modified Generalized Least Squares (FMGLS) estimator for multivariate cointegrating polynomial regressions. Such regressions allow for deterministic trends, stochastic trends and integer powers of stochastic trends to enter the cointegrating relations. Our fully modified estimator incorporates: (...

This paper develops the asymptotic theory of a Fully Modified Generalized Least Squares (FMGLS) estimator for multivariate cointegrating polynomial regressions. Such regressions allow for deterministic trends, stochastic trends and integer powers of stochastic trends to enter the cointegrating relations. Our fully modified estimator incorporates: (...