The Greek Neolithic: A new review

The Greek Neolithic, here divided into five phases, is the oldest in Europe. Geographically, it is the closest to the Near East and has thus long been seen as an impoverished derivative of the latter. However, recent research has tended to emphasize the autochthonous nature of Neolithic development in Europe, including Greece. The Greek Neolithic economy, which was based almost entirely on domesticates, and its densely packed, long-lived villages strongly recall the Near East, as do also the early emphasis on fine, decorated, nonculinary pottery and the wealth of figurines. On the other hand, the evolution of stylistic patterns is specifically Greek, although generally related to trends in the Balkans. Originality in the development of the Greek Neolithic is also seen in its latest phase, with apparent decreases, rather than increases, in site density, social differentiation, and, to some extent, long-distance trade. At the same time, however, the dichotomy became much sharper between the rich agricultural plains of northern Greece and the more pastoral(?) regions of the Peloponnese and Cycladic Islands; this presages similar contrasts during the Bronze Age.     

Improvements in Archaeomagnetic Dating in Western Europe from the Late Bronze to the Late Iron Ages: An Alternative to the Problem of the Hallstattian Radiocarbon Plateau

We present a new curve of the directional secular variation of the geomagnetic field in Western Europe between 1500 bce and 200 ce . Its computation relies on a Bayesian framework. The fast secular variation during the Late Bronze and Early Iron Ages makes archaeomagnetic dating efficient with a respective precision of 150–200 and 60–100 years during these periods. The Bayesian method also provides posterior date distributions that refine the dating of reference data, especially during the period of the Hallstattian radiocarbon plateau. Archaeomagnetism becomes a valuable alternative to radiocarbon and will help to improve the archaeological chronologies.     

Bayesian Spatial Filtering for Hedonic Models: An Application for the Real Estate Market

This article presents a Bayesian method based on spatial filtering to estimate hedonic models for dwelling prices with geographically varying coefficients. A Bayesian Adaptive Sampling algorithm for variable selection is used, which makes it possible to select the most appropriate filters for each hedonic coefficient. This approach explores the model space more systematically and takes into account the uncertainty associated with model estimation and selection processes. The methodology is illustrated with an application for the real estate market in the Spanish city of Zaragoza and with simulated data. In addition, an exhaustive comparison study with a set of alternatives strategies used in the literature is carried out. Our results show that the proposed Bayesian procedures are competitive in terms of prediction; more accurate results are obtained in the estimation of the regression coefficients of the model, and the multicollinearity problems associated with the estimation of the regression coefficients are solved.