Asia‐Pacific Economic History Review最新文献

This research considers the current New Zealand conventional wisdom of a Māori contact-era population of 100,000 circa-1770 using a variety of population density analogues. The first set of analogues examines estimated population densities of six districts in early-contact period New Zealand for which reasonable population estimates can be constructed using methods of historical demography. The second set examines estimated population densities of pre-industrial societies on large, relatively isolated temperate islands outside of New Zealand. The density research indicates that a contact-era Māori population in excess of 200,000 is a distinct possibility. Based on this density analysis the current conventional wisdom's figure of 100,000 appears to be—considerably—on the low side, and suggesting considerable catastrophic early post-contact population decline.

US military sources document more than 1800 conflicts of varying intensity between the United States and tribes from 1830 to 1897. Negative binomial and Tobit regressions both show that hostilities follow political and economic cycles. Politically, conflicts increased in recessionary election years, however, conflicts in non-election recessionary years lack significant changes. The second major trend is the influence of three economic factors. After western states began to mine gold conflicts drastically increased. Conflicts likewise increased with the expansion of the railroad and with buffalo extinctions at the state level. While nineteenth century Americans had perpetual anti-Indigenous sentiment, tribal persecution followed political and economic rationales.

In the colonisation of Queensland, Australia it is commonly accepted that large numbers of Indigenous people were killed in the second half of the nineteenth century. Calculations of violent mortality have recently been revised radically upwards. We suggest that the methodology deployed in these new studies is unreliable, reflecting errors in counting and calculation, as well as underestimating the selection bias of the samples. We caution against projecting aggregate violent mortality where the underlying data are so imperfect and emphasise the value of more detailed local and regional studies to inform better understanding of colonisation's impact on First Peoples.

While there have been many attempts to calculate pre-contact Aboriginal population sizes for Tasmania, estimates have varied from as little as 800 to as many as 20,000. We adapt a technique employed by Noel Butlin to model Australian continental populations in 1788 to the peculiar circumstances of Tasmania. We conclude that higher, rather than lower, pre-contact populations are likely. While the direct and indirect consequences of conflict were a serious contributor to the collapse in population, introduced disease played a significant role. This included sexually transmitted disease (a cause of declining fertility), as well as pulmonary disorders and crusted scabies.

The Economics and the Dreamtime was a landmark in Australian Economic History where Noel Butlin elevated awareness of the central importance of Indigenous economic history. It was a sprawling inter-disciplinary work that used economic tools to understand Indigenous society before first contact and in the early colonial period. This article revisits that book to provide a critical evaluation of the major contributions of Butlin's research on Indigenous Australians. His primary contribution was to make Indigenous people more visible in the Australian economy in the early colonial period. He created a unique backcasting methodology that allowed Indigenous population to be estimated in the first six decades of the colony based on depopulation from disease, resource loss and frontier violence. I argue that the two main shortcomings of Butlin's research is that his method used colonial estimates of the population and that the population estimates are not sufficiently geographically differentiated. The main criticism of Butlin's research in the literature is that it is too speculative. However, his methodological innovation allows considerable transparency in the assumptions used and can create a range of plausible estimates that give us a sense of the unreliability of the existing population estimates. Alternative methodologies based on estimating population densities in 1788 from anthropological evidence are historically point estimates, which do not provide a sense of how uncertain the estimates might be. The way forward for this debate is to combine Butlin's demographic backcast methodology with population density estimates that take into account the selective mortality from disease and frontier violence. Finally, in order to create a truly Australian Economic History, it is necessary to also augment the methodology to incorporate Indigenous perspectives into the analysis and to utilise a local geography that acknowledges the diversity of Indigenous Australia.

Immigration to Hawai‘i between 1870 and 1930 led to a more than six-fold increase in population and high and rapidly varying sex ratios in the Chinese, Japanese, Korean, Filipino, and Caucasian populations of marriageable age. Using complete populations of the 1910, 1920, and 1930 Territorial Censuses of Hawai‘i, we estimate how male-biased ethnic sex ratios affected choices of second-generation men and women of marriageable age. Econometric results indicate that within-group and extra-group sex ratios impact the likelihood of males and females to marry, to marry a spouse from another ethnic group, to have children, and to live in larger households.

This is a first focused examination of age misreporting in military recruitment. We take advantage of an original dataset comprised of New Zealand military personnel records in the Second Boer War matched with birth historical records. First, we find that age misrepresentation is common: about one third of soldiers on our dataset misreport their ages. Second, we find that soldiers the estimated age-specific mean heights do not change significantly when we change from using reported ages to using true ages. Researchers can prioritise the investigation of true ages on those reporting to be 21 or younger.