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...

This paper explores the contagious propagation of jumps among international stock market indices by exploiting a rich panel of stock and options data. We propose a multivariate option pricing model designed to allow for, but not superimpose, time and space amplification of jumps in option...

Parametric production frontier functions are frequently used in stochastic frontier models, but there do not seem to be any empirical test statistics for its plausibility. To bridge the gap in the literature, we develop two test statistics based on local smoothing and an empirical process,...

We propose a Bayesian infinite hidden Markov model to estimate time- varying parameters in a vector autoregressive model. The Markov structure allows for heterogeneity over time while accounting for state-persistence. By modelling the transition distribution as a Dirichlet process mixture model,...

Motivated by Chaudhuri's work (1996) on unconditional geometric quantiles, we explore the asymptotic properties of sample geometric conditional quantiles, defined through kernel functions, in high dimensional spaces. We establish a Bahadur type linear representation for the geometric conditional...

This paper develops a semiparametric estimation method that jointly identifies the probability weighting and utility functions implicit in option prices. Our econometric method avoids direct specification of the objective conditional return distributions, which are instead obtained by...

We propose two robust bootstrap-based simultaneous inference methods for time series models featuring time-varying coefficients and conduct an extensive simulation study to assess their performance. Our exploration covers a wide range of scenarios, encompassing serially correlated,...

We propose a flexible framework that allows for the relationship between housing prices and their determinants to vary over time. Our model incorporates housing-specific characteristics and macroeconomic variables, while accounting for a gradual global trend that reflects the unobserved external...

We apply a partial identification analysis using comprehensive Norwegian register data to investigate the causal effect of father's income on child income. We find a strong association between the incomes of fathers and children. The causal effect, however, equals at least 1% and at most 51% of...