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dc.contributor.authorBhardwaj, Geeteshen_US
dc.contributor.authorCorradi, Valentinaen_US
dc.contributor.authorSwanson, Norman R.en_US
dc.description.abstractThis paper makes two contributions. First, we outline a simple simulation based framework for constructing conditional distributions for multi-factor and multi-dimensional diffusion processes, for the case where the functional form of the conditional density is unknown. The distributions can be used, for example, to form conditional confidence intervals for time period t + Æó , say, given information up to period t. Second, we use the simulation based approach to construct a test for the correct specification of a diffusion process. The suggested test is in the spirit of the conditional Kolmogorov test of Andrews (1997). However, in the present context the null conditional distribution is unknown and is replaced by its simulated counterpart. The limiting distribution of the test statistic is not nuisance parameter free. In light of this, asymptotically valid critical values are obtained via appropriate use of the block bootstrap. The suggested test has power against a larger class of alternatives than tests that are constructed using marginal distributions/densities, such as those in A¡§©Æt-Sahalia (1996) and Corradi and Swanson (2005). The findings of a small Monte Carlo experiment underscore the good finite sample properties of the proposed test, and an empirical illustration underscores the ease with which the proposed simulation and testing methodology can be applied.en_US
dc.publisher|aDep. of Economics, Rutgers, the State Univ. of New Jersey |cNew Brunswick, NJen_US
dc.relation.ispartofseries|aWorking papers // Department of Economics, Rutgers, the State University of New Jersey |x2006,14en_US
dc.subject.keywordBlock bootstrapen_US
dc.subject.keyworddiffusion processesen_US
dc.subject.keywordparameter estimation erroren_US
dc.subject.keywordsimulated GMMen_US
dc.subject.keywordstochastic volatilityen_US
dc.titleA simulation based specification test for diffusion processesen_US
dc.type|aWorking Paperen_US

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