Likelihood based estimation of the parameters of state space models can be carried out via a particle filter.  In this paper we show how to make valid inference on such parameters when the model is incorrect.  In particular we develop a simulation strategy for computing sandwich covariance...

Suppose we wish to carry out likelihood based inference but we solely have an unbiased simulation based estimator of the likelihood.  We note that unbiasedness is enough when the estimated likelihood is used inside a Metropolis-Hastings algorithm.  This result has recently been introduced in...

Using village data from Tanzania, we test whether gifts and loans between households are voluntary while correcting for mis-reporting by the giving and receiving households.  Two maintained assumptions underlie our analysis: answers to a question on who people would turn to for help are good...

This paper asks how well a general equilibrium agency cost model describes the dynamic relationship between credit variables and the business cycle. A Bayesian VAR is used to obtain probability intervals for empirical correlations. The agency cost model is found to predict the leading,...

A multinomial choice framework is used to investigate the nature of women`s transitions between full-time employment, part-time employment and non-employment. The stochastic framework allows time varying and time invariant unobserved preferences, and also controls for the possible endogenity of...

This paper investigates the causes of well documented association between part-time employment and low occupational attainment amongst British women. In particular, the relative importance of structural factors and unobserved heterogeneity to the occupational attainment of women who choose to...

This paper discusses and documents the algorithms of SsfPack 2.2. SsfPack is a suite of C routines for carrying out computations involving the statistical analysis of univariate and multivariate models in state space form. The emphasis is on documenting the link we have made to the Ox computing...