The intensification of production: Archaeological approaches

In this paper I reexamine the Boserup model of agricultural intensification and archaeological reaction to it. Although causes have been extensively debated, little attention has been paid to process, and even those who reject the causal efficacy of population may adopt other aspects of the Boserup model. These unexamined aspects include the assumption that intensification proceeds along a single course, characterized by gradual decreases in the frequency of cropping. I suggest that the course of intensification is complex and variable and that, only by breaking down the process of intensification into its component strategies, can we come to an understanding of both the causes and the courses of intensification.     

Revisiting Kalundu Mound,Zambia: Implications for the Timing of Social and Subsistence Transitions in Iron Age Southern Africa

African Archaeological Review - Novel trajectories of food production, urbanism, and inter-regional trade fueled the emergence of numerous complex Iron Age polities in central and southern Africa....     

Native Californians at the Presidio of San Francisco: Analysis of Lithic Specimens from El Polín Spring

Relatively few archaeological studies have examined the experiences of native people at Spanish colonial military installations. A small flaked lithic assemblage at the Presidio of San Francisco provides insight into the lives and labor of Native Californians there. Technically proficient knappers, making do with poor-quality, locally available material, engaged in freehand core reduction and produced non-symmetrical, bifacially flaked tools through percussion production. These tools were most likely used for cutting during specific tasks. The analysis reveals how Native Californians in colonial institutions maintained flintknapping traditions in social spaces that were likely shared by native people and colonists.     

PANEL DATA MODELS WITH SPATIALLY DEPENDENT NESTED RANDOM EFFECTS

This paper focuses on panel data models combining spatial dependence with a nested (hierarchical) structure. We use a generalized moments estimator to estimate the spatial autoregressive parameter and the variance components of the disturbance process. A spatial counterpart of the Cochrane‐Orcutt transformation leads to a feasible generalized least squares procedure to estimate the regression parameters. Monte Carlo simulations show that our estimators perform well in terms of root mean square error compared to the maximum likelihood estimator. The approach is applied to English house price data for districts nested within counties.