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...

We propose and study a class of regression models, in which the mean function is specified parametrically as in the existing regression methods, but the residual distribution is modeled nonparametrically by a kernel estimator, without imposing any assumption on its distribution. This...

We study a consumer non-sequential search oligopoly model with search cost heterogeneity. We first prove that an equilibrium in mixed strategies always exists. We then examine the nonparametric identification and estimation of the costs of search. We find that the sequence of points on the...

In several scientific fields, like bioinformatics, financial and macro-economics, important theoretical and practical issues exist that involve multimodal data distributions. We propose a Bayesian approach using mixtures distributions to approximate accurately such data distributions. Shape and...

This paper provides an extensive Monte-Carlo comparison of severalcontemporary cointegration tests. Apart from the familiar Gaussian basedtests of Johansen, we also consider tests based on non-Gaussianquasi-likelihoods. Moreover, we compare the performance of these parametrictests with tests...

In a recent paper Hong and Shum [2006. Using price distributions to estimate search costs. Rand Journal of Economics 37, 257–275] present a structural method to estimate search cost distributions. We extend their approach to the case of oligopoly and present a new maximum likelihood method to...

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,...

In several scientific fields, such as finance, economics and bioinformatics, important theoretical and practical issues exist involving multimodal and asymmetric count data distributions due to heterogeneity of the underlying population. For accurate approximation of such distributions we...

The market for commercial properties is characterised by extreme heterogeneity in demand. In this paper, we aim to gain more insight in the heterogeneity in demand for employment agglomeration and size of the rental property using a two-stage hedonic approach following Bajari and Benkard (2005)....

Motivated by the problem of setting prediction intervals in time seriesanalysis, this investigation is concerned with recovering a regression functionm(X_t) on the basis of noisy observations taking at random design pointsX_t.It is presumed that the corresponding observations are corrupted by...