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<br /> <br />~ >, <br /> <br />VOLUME 3, NUMBER 3, SUMMER 1974 <br />DIVISION OF PLANNING <br /> <br />,"-n-c '-.. . <br />1C Cf t/[O <br /> <br />OCT 23 1974 <br />COLO. WATER <br />CONSERVATION BOARD <br /> <br />COLORADO <br />POPU LA TION <br />TRENDS <br /> <br /> <br /> <br />Regional and County Estimates-1970 to 1980 <br /> <br />DAVID E. MONARCH! <br /> <br />INTRODUCTION <br />Society is becoming increasingly complex and its goals <br />more interrelated and conflicting. As a result, there is an <br />increased need for careful planning based on accurate <br />data and objective and explicit predictive mechanisms rath- <br />er than human intuition alone in order to attain, insofar <br />as possible, these competing aspirations. The planning <br />process is of critical importance in both the public and <br />private sectors because it often results in the commitment <br />of large sums of money for extended periods of time. <br />Thus, it seems imperative that those involved in the plan- <br />ning process utilize analytical techniques to the greatest <br />extent possible to provide estimates and projections that, <br />tempered with judgment and reflection, can provide vital <br />information for that process. The research described in <br />this issue is a result of the importance that the Colorado <br />Division of Planning attaches to the development of such <br />population and employment estimates for the State and <br />its 13 planning regions. (A complete discussion of the <br />research and results is contained in Colorado Regional and <br />County Population Estimatas-1970 to 1980: Methods <br />and Results, July 1974.) <br /> <br />COLORADO PLANNING AND MANAGEMENT REGIONS <br />The 13 planning and management regions for Colo. <br />rado are shown on the map on the following page. In this <br />map the heavy lines indicate the planning regions and the <br />dash (.u) lines indicate the counties within the regions. <br />Also shown for each county is the county seat. The number <br />of counties within each region varies from two in Region <br />2 to eight in Region 3. The planning regions follow exist- <br /> <br />Dr. David Monarchi is Assistant Professor of Manage. <br />ment Science and Assistant Director of the Business <br />Research Division, College of Business and Administra- <br />tion, University of Colorado. <br /> <br />ing county boundaries but, subject to that limitation, are <br />intended to be relatively homogeneous, both geographi- <br />cally and economically. Regions 2, 3, and 4, are the prin- <br />cipal metropolitan regions in the State. Regions 1, 5, 6, <br />7, 8, 9, and 10 are essentially rural regions with farming <br />as the pdncipal activity, although the type of farming and <br />crops varies among the regions. Region 11 is an area <br />of potential economic impact from the oil shale develop- <br />ment that may take place on the Western Slope. Region <br />10, by its proximity to Region 11, may share in growth <br />from that development. In the past, Region 12 has been <br />an intensive winter recreation area containing most of <br />the major ski areas within the State. It, tOO, may receive <br />some derived growth from any oil shale development. <br />Region 13 is a high country area whose principal activity <br />is mineral extraction. <br /> <br />METHODOLOGY <br />During the past year, the projected population and <br />employment growth of the State and each of the 13 plan- <br />ning regions was simulated under a variety of alternative <br />hypotheses about the future fot 1974 to 1980. The re- <br />gional population projections were then allocated to the <br />counties within each region. <br />The annual projections were made using the previous. <br />ly developed Colorado Population and Employment model, <br />which was extensively revised during this year's research. <br />In all, 14 versions of the model were created, one for <br />the State and for each planning region. The models were <br />all parameterized to take into account, insofar as possible, <br />the unique characteristics of each study area. In addition, <br />an attempt was made to "interlock" the areas through the <br />use of an employment commuting factor across regional <br />lines. The model provided annual estimates of population <br />by age, race, and sex cohorts and employment by nine <br />major industry classifications. Certain other information <br />was extracted from the model, such as births, deaths, eID- <br /> <br />0781 <br />