population of heterogeneous consumers. Individual demands are characterized by a nonseparable model which is nonparametric in the …

. However, specification testing of discrete choice models is rarely applied. This paper describes a nonparametric test …. Nonparametric methods require large datasets when the number of independent variables is more than a few. A way to circumvent this …

nonparametric approach opens the door to the examination of potentially different distributed outcomes. When combined with cross …

power than the Breitung (2002) test, and when d is small the asymptotic local power of the proposed nonparametric test is …This paper presents a family of simple nonparametric unit root tests indexed by one parameter, d, and containing … asymptotic distribution depends on d and the test remains consistent for all d>0, it is possible to analyze the power of the test …

nonparametric test is relatively close to the parametric power envelope, particularly in the case with a linear time trend …This paper presents a family of simple nonparametric unit root tests indexed by one parameter, d, and containing … power of the test for different values of d. The usual Phillips-Perron or Dickey-Fuller type tests are characterized by …

In this paper a nonparametric variance ratio testing approach is proposed for determining the cointegration rank in … multiple cointegrating vectors. Since the test is nonparametric, it does not require the specification of a particular model … and integer-based parametric approaches, evidence in favor of the expectations hypothesis is found using the nonparametric …

the model. We use a nonparametric local-linear regression estimator and a nonparametric variable relevance test to conduct …

nonparametric probability function of the observed thresh- old variables. The proposed models generally embrace traditional … threshold models with contaminated threshold variables or heterogeneous threshold values, thus gaining more power in handling … the nonparametric probability function. We utilize the natural connection between penalized splines and hierarchical Bayes …

nonparametric probability function of the observed threshold variables. The proposed models generally embrace traditional threshold … models with contaminated threshold variables or heterogeneous threshold values, thus gaining more power in handling … the nonparametric probability function. We utilize the natural connection between penalized splines and hierarchical Bayes …