Net Migration as a Factor Affecting Metropolitan Growth in Utah: 1950 to 1970
Net Migration as a Factor Affecting Metropolitan Growth in Utah: 1950 to 1970 by Kooros M. Mahmoudi, Doctor of Philosophy Utah State University, 1973 Major Professor: Dr. Yun Kim Department: Sociology The objectives of this study were to measure net inor out-migration to or from the Standard Metropolitan Areas of Utah between 1950-60 and 1960-70, and to study selected socio-economic factors relating to migration and the growth of SMSA 's. Specifically, the factors of migration and natural population increase were central in an analysis of population redistribution. Selected demographic characteristics of the migrants such as sex and age were also studied to establish their impact upon the SMSA population structure. The relationship between population change in the SMSA ' s and economic factors of labor force supply and employment were also reviewed. Net intercensal migration for the SMSA 's of Ogden, Provo-Orem, and Salt Lake City were derived through indirect methods of estimating net migration: L. The Census Survival Ratio Method and the Life Table Survival Ratio Method. An analysis of the findings indicated that most migrants were in the younger age groups of 20-34 years and females outnumbered the males in the migrating population. These trends held for all three SMSA 's throughout the 1950-60 and
A Historical Study of the Demographic Aspects of Urbanization in Utah, 1900-1960
A Historical Study of the Demographic Aspects of Urbanization in Utah, 1900-1960 by Kooros M. Mahmoud!, Master of Science Utah State University, 1969 Major Professor: Dr . Yun Kim Department: Sociology In a historical frame of reference, this is a study of rural-urban migration to demonstrate the process of urbanizat ion in Utah between 1900 and 1960. This study estimates the amount of internal migration for the state of Utah. Se l ected demographic variables such as size, age, and sex of the migrating population are studied. Changes in the population composition of t he sending and receiving areas as a complement of ruralurban migration constitute the crux of this study. The indirect methods of estimating the net intercensal migration, census survival and life table survival ratio me t hods, are used in t abu l ations. Li mitat ions wer e imposed, as fo r availability of the data , in usage of any direct methods of migration measurement. The survival ratio me t hods used, however, are the most reliable in this
Complexity, Network-Decisions And Alternative Risk Premia: Some New Theories Of Structural Change And Portfolio Decisions.
Structural Change is the basis for many decisions such as government fiscal and monetary policies, government interventions, corporate-expenditure decisions, corporate strategic decisions, portfolio management decisions in finance; household allocation decisions, etc.. Structural change in industries and national economies is increasingly more difficult to detect partly because of the growth and dominance of Complex Systems and “Networks” in modern industries and economies – such Networks and Complex Systems include GVCs (global value chains), retail store networks; franchising networks; internet networks; services networks; credit-chains in industries; online social networks; etc.. The relationship between Complexity and Structural Change is well established in the physics, applied math and economic dynamics literatures. Traditional definitions and modeling of structural change have erroneously focused on changes in labor, technological progress, market share, and or capital – which are grossly inadequate in the new economy and post- global financial crisis (as confirmed by changes in the global retailing and housing industries and other industries). Also the modeling of structural change seems to be constrained by the availability of data, and often omits the relationship between structural change on one hand, and globalization, financial stability and international financial contagion. This article: i) introduces the Operations Strategy Model of structural change, explains how it differs from the Lewis Model of Structural Change; and explains the often omitted relationship between operations strategy (of companies and government agencies) and structural change; ii) introduces other new Complexity-based models/theories of Structural Change in industries; iii) reviews the relationships among Operations Research, Complexity and Structural Change; iv) explains the symbiotic relationship between structural change on one hand, and economic growth, financial stability, financial contagion and globalization; v) discusses the significant gap between academic research and practice and explains some issues and factors that should be considered in the development and testing of structural change models; vi) explains how alternative risk premia can be generated from new models of Structural Change.