State governments are ultimately competitors in their economic policies when people, products and capital are free to move across state borders. Nowhere is this competition more apparent than in the United States where individual states compete to promote economic growth by attracting industry with tax holidays, outright grants, subsidized financing and other means. Yet, the arguably greater influence of state fiscal policy on investment decisions has largely been ignored. This book redresses that deficiency by providing a collection of chapters which discuss the theoretical and practical linkage between investment strategy and state economic policy. Specifically, it uses changes in relative state burdens as a measure of state fiscal policy and shows that by altering the incentives to work, save and invest, changes in a state's tax burden relative to other states influence decisions on whether, how much and where to invest. The book is divided into three parts. The first section provides the theoretical framework for the book and discusses application of the basic model to explain the persistent differences in observed real income across states; the level of economic activity; and business starts and failures. The second section discusses, among other things, the implications of changes in state economic policy for investments in real estate; common stocks of small capitalization firms; and state general obligation bonds. The third section of the book, which examines the political dimensions of state economic policy, begins with a discussion of the effect of state economic policy on relative population shifts and reapportionment and ends with a proposal for a flat tax.
Agent-based modelling on a computer appears to have a special role to play in the development of social science. It offers a means of discovering general and applicable social theory, and grounding it in precise assumptions and derivations, whilst addressing those elements of individual cognition that are central to human society. However, there are important questions to be asked and difficulties to overcome in achieving this potential. What differentiates agent-based modelling from traditional computer modelling? Which model types should be used under which circumstances? If it is appropriate to use a complex model, how can it be validated? Is social simulation research to adopt a realist epistemology, or can it operate within a social constructionist framework? What are the sociological concepts of norms and norm processing that could either be used for planned implementation or for identifying equivalents of social norms among co-operative agents? Can sustainability be achieved more easily in a hierarchical agent society than in a society of isolated agents? What examples are there of hybrid forms of interaction between humans and artificial agents? These are some of the sociological questions that are addressed.
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