Consistency and asymptotic normality of least squares estimators in generalized STAR models

Space–time autoregressive (STAR) models, introduced by Cliff and Ord [Spatial autocorrelation (1973) Pioneer, London] are successfully applied in many areas of science, particularly when there is prior information about spatial dependence. These models have significantly fewer parameters than vector autoregressive models, where all information about spatial and time dependence is deduced from the data. A more flexible class of models, generalized STAR models, has been introduced in Borovkova et al. [Proc. 17th Int. Workshop Stat. Model. (2002), Chania, Greece] where the model parameters are allowed to vary per location. This paper establishes strong consistency and asymptotic normality of the least squares estimator in generalized STAR models. These results are obtained under minimal conditions on the sequence of innovations, which are assumed to form a martingale difference array. We investigate the quality of the normal approximation for finite samples by means of a numerical simulation study, and apply a generalized STAR model to a multivariate time series of monthly tea production in west Java, Indonesia.     

Civil society organisations' contribution to the anti-corruption movement in Indonesia

Soeharto era concern about corruption was deflected by the establishment of toothless anti-corruption committees, and by suppression of anti-corruption activism and media comment. With Soeharto's demise, activists began to publicise their concerns more openly – at first speaking in general terms, but later making increasingly specific allegations. The sporadic activism of the Soeharto years was consolidated, first through cooperative action among similarly motivated informal groups, and later through establishment of formal civil society organisations (CSOs) intent on rolling back corruption. The CSOs have played a key role in pushing for new laws and institutions to help eradicate corruption, and many corrupt officials have been imprisoned. This paper finds little evidence, however, that corruption has declined significantly. It argues that further progress depends on CSOs gaining a better understanding of the underlying causes of corruption, and that these are to be found in public sector personnel management practices.