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Regional equations were developed for estimating mean annual and mean seasonal runoff for natural basins of Texas. The equations, which are based on the statistical relation between streamflow and basin characteristics, use streamflow data and basin characteristics from U.S. Geological Survey streamflow-gaging stations within natural basins and with at least 8 years of data during 1961-90. The State was divided into 11 hydrologic regions on the basis of previous studies. The final equations for estimating mean annual and mean seasonal runoff were developed from 228 streamflow-gaging stations. Contributing drainage area and mean annual or mean seasonal precipitation were determined to be the most significant basin characteristics in each region.
Interpreting Official Statistics examines the official statistics produced about the current state of British society. It documents some of the ways in which information has been suppressed, manipulated and misinterpreted since 1979. This invaluable guide is designed to help students know what figures are available, and to discover when and how politicians are misusing statistics. Data sets covered include: * Households below average income * Administrative and survey methods of unemployment and crime * Population census data on ethnicity * Data sources on women and work * Data on the relationship between class and health, and safety at work * New data sources on disability * Labour Force Survey.
Silicon Valley is the most salient example of high-tech industrial clusters. Public policymakersthroughouttheworldwouldliketolearnthesecretsofSiliconValley in order to build their own high-tech economies. The existing literature on ind- trial clusters, which traces back to Marshall (1920), focuses on the way in which ?rms bene?t from locating in a cluster; it suggests that once a cluster comes into existence, it tends to reinforce itself by attracting more ?rms. However, a more important question is how to reach this critical mass in the ?rst place. In contrast to the literature, evidence suggests that entrepreneurs rarely move when they est- lish high-tech start-ups (Cooper and Folta, 2000). This contradicts the notion that location choice analyses lead entrepreneurs to a high-tech cluster. A high-tech industrial cluster such as Silicon Valley is characterized by c- centratedentrepreneurship. FollowingSchumpeter,weemphasizethefactthat“the appearance of one or a few entrepreneurs facilitates the appearance of others” (Schumpeter,1934). Weproposeanagent-basedcomputationalmodeltoshowhow high-tech industrial clusters could emerge in a landscape in which no ?rms existed originally. The model is essentially a spatial version of the Nelson-Winter model: Boundedly rational agents are scattered over an explicitly de?ned landscape. Each agent is endowed with some technology, which determines his ?rm’s productivity (if he has one). During each period of time, an agent with no ?rm would make a decision as to whether he wants to start one. This decision is mostly affected by the behavior of his social contacts, who are all his neighbors.
This book focuses on highlights (species mentioned, locality, geological age, stratigraphic positions, etc.) of nearly 1000 items published between 1821 and 2000, dealing with the remains of vertebrates that lived from about 2 million to 5000 years ago.