Semiparametric Estimation and Variable Selection for Single‐Index Copula Models

A copula with a flexibly dependence structure can capture complexity and heterogeneity in economic financial time series. Based on the recently proposed single-index copula, we propose simultaneous variable selection estimation procedure. This method allows for choosing most relevant state variables by using penalized large sample properties derived. Simulation results demonstrate good performance of selecting estimating unknown index coefficients parameters. We apply procedure to four states' housing markets US identify six macroeconomic factors that drive their structure.