Econometric Time Series
http://lists.repec.org/mailman/listinfo/nep-ets
Econometric Time Series2014-10-22Yong YinSpecification Testing in Nonstationary Time Series Models
http://d.repec.org/n?u=RePEc:yor:yorken:14/19&r=ets
In this paper, we consider a specification testing problem in nonlinear time series models with nonstationary regressors and propose using a nonparametric kernel-based test statistic. The nullasymptotics for the proposed nonparametric test statistic have been well developed in the existing literature such as Gao et al (2009b) and Wang and Phillips (2012). In this paper, we study the local asymptotics of the test statistic, i.e., the asymptotic properties of the test statistic under a sequence of general nonparametric local alternatives, and show that the asymptotic distribution depends on the asymptotic behaviour of the distance function which is the local deviation from the parametrically specified model in the null hypothesis. In order to implement the proposed test in practice, we introduce a bootstrap procedure to approximate the critical values of the test statistic and establish a novel result of Edgeworth expansion which is used to justify the use of such an approximation. Based on the approximate critical values, we develop a bandwidth selection method, which chooses the optimal bandwidth that maximises the local power of the test while its size is controlled at a given significance level. The local power is defined as the power of the proposed test for a given sequence of local alternatives. Such a bandwidth selection is made feasible by an approximate expression for the local power of the test as a function of the bandwidth. A Monte-Carlo simulation study is provided to illustrate the finite sample performance of the proposed test.Jia Chen, Jiti Gao, Degui Li, Zhengyan Lin2014-09Asymptotic distribution; Edgeworth expansion; local power function; nonlinear time series; quadratic form; size function; specification testing; unit root.Testing for unit roots in panels with structural changes, spatial and temporal dependence when the time dimension is finite.
http://d.repec.org/n?u=RePEc:not:notgts:14/03&r=ets
Finite T panel data unit root tests allowing for structural breaks, spatial cross section dependence, heteroscedasticity, serial correlation, heterogeneity and non-linear trends are proposed. The structural breaks can be at known or unknown dates. For the latter, analytic probability density functions of the asymptotic distributions of the tests are provided based on a minimum order statistic. The tests can accommodate general forms of spatial dependence for which the spatial weights matrix does not have to be de?ned due to the utilization of a non-parametric estimator. A set of sufficient conditions which determines admissible deterministic trend functions is also provided. Finally, extensive Monte Carlo experiments show the usefulness of the new tests.Yiannis Karavias, Elias TzavalisPanel data; Unit roots; Structural breaks; Spatial dependence; Serial correlation; Fixed T JEL classification: C22, C23Testing weak exogeneity in cointegrated panels
http://d.repec.org/n?u=RePEc:wbk:wbrwps:7045&r=ets
For reason of empirical tractability, analysis of cointegrated economic time series is often developed in a partial setting, in which a subset of variables is explicitly modeled conditional on the rest. This approach yields valid inference only if the conditioning variables are weakly exogenous for the parameters of interest. This paper proposes a new test of weak exogeneity in panel cointegration models. The test has a limiting Gumbel distribution that is obtained by first letting the time dimension of the panel go to infinity and then letting its cross-sectional dimension go to infinity. The paper evaluates the accuracy of the asymptotic approximation in finite samples via simulation experiments. Finally, as an empirical illustration, the paper reports tests of weak exogeneity of disposable income and wealth in an aggregate consumption equation.Moral-Benito, Enrique, Serven, Luis2014-09-01Scientific Research&Science Parks,Science Education,Economic Theory&Research,Statistical&Mathematical Sciences,EconometricsThe $\alpha$-Hypergeometric Stochastic Volatility Model
http://d.repec.org/n?u=RePEc:arx:papers:1409.5142&r=ets
The aim of this work is to introduce a new stochastic volatility model for equity derivatives. To overcome some of the well-known problems of the Heston model, and more generally of the affine models, we define a new specification for the dynamics of the stock and its volatility. Within this framework we develop all the key elements to perform the pricing of vanilla European options as well as of volatility derivatives. We clarify the conditions under which the stock price is a martingale and illustrate how the model can be implemented.Jos\'e Da Fonseca, Claude Martini2014-09