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Abstract:
The past decade has witnessed great progress in the development of nonlinear cointegrating regression. Unlike linear cointegration and nonlinear regression with stationarity where the traditional and classical methods are widely used in practice, estimation and inference theory in nonlinear cointegrating regression produce new mechanisms involving local time, a mixture of normal distributions and stochastic integrals. This talk aims to introduce the machinery of the theoretical developments, providing up-to-date results in nonlinear cointegrating regression.
