Methodology for Indiana State and County Population Projections, 2010 to 2040

Overview

This latest version of the Indiana population projections were produced using the cohort-component method, using the U.S. Census Bureau’s 2005 population estimates by age and sex for Indiana and its counties as the benchmark population figures. This method projects individual age-sex cohorts forward through time while applying specific mortality and migration rates. In addition, fertility rates are applied to the appropriate cohorts to generate the number of births during each projection period. These projections follow the standard format of five-year age cohorts carried over five-year projection periods. The five-year cohorts begin with the 0-4 age group and extend through 80-84, with the final age group including all individuals 85 and above.

These projections are largely an update of the official Indiana population projections produced by the Indiana Business Research Center in 2003 based on the 2000 Census. To provide continuity, many of the assumptions and procedures used in those projections have been adopted in this version.

Limitations

There is always uncertainty surrounding population trends. Future events and human behavior can be difficult to predict. For instance, economic or environmental conditions can shift migration patterns or medical breakthroughs can increase life expectancy. Migration patterns are particularly subject to large and sudden swings. This instability provides one potential source of error.

General assumptions about the future course of demographic trends are introduced into the projections in order to deal with these inevitable shifts over time. Ultimately, the quality of these projections depend largely on the accuracy of these assumptions. Those that miss the mark will result in projections that deviate from future population totals. Assumptions incorporated into this set of projections are based on trends observed in the recent past, 2001 to 2005 in the case of fertility and mortality and 1990 to 2005 for migration. The assumptions for each component of population change are discussed below.

Population projections are susceptible to two other sources of error which should be noted. First, projections for less populous areas will be subject to a greater relative margin of error than more populous areas. Predictions for Indiana, for instance, will be more reliable than projections for one of its smaller counties. Second, for reasons discussed earlier, long-term projections will be more unreliable than near-term projections. It’s advised that data users give greater weight to projections up to 2020 or 2025.

These projections use the 2006 release of the 2005 state and county population estimates from the U.S. Census Bureau as the benchmark. Unlike decennial population counts, annual population estimates are subject to periodic revision as estimates are released in subsequent years. Therefore, it is likely that the 2005 benchmark population reported here will differ somewhat from the revised 2005 population estimate published in later years.

Fertility

Age-specific fertility rates (ASFR) for the age groups 10-14 through 45-49 were calculated for each county using data from the Indiana State Department of Health. The 2001 to 2005 average annual ASFR was then computed for the state and for each county in order to smooth year-to-year fluctuations.

An assumption was made that Indiana’s fertility rates will rise over the next 35 years. The rise in rates were based upon the changes in fertility projected at the national level in the middle series of the 1999 to 2100 national population projections produced by the U.S. Census Bureau (https://www.census.gov/programs-surveys/popproj.html). Total fertility rates (TFR) for the nation were calculated for the population age 10 to 49 for each projection base year beyond 2005. The projected change in TFR from one period to the next at the national level was then applied to Indiana and its counties. The TFR for the state and each county was then disaggregated into ASFRs for each five-year age group, 10-14 to 45-49, based upon the proportion of the TFR that each age group held in the 2005 base year.

This rising trend in fertility rates was applied to each Indiana county with three exceptions. Adams, Daviess, and Lagrange counties currently exhibit fertility rates which are considerably higher than the state’s. This is likely due, in large part, to their sizeable Amish and Mennonite populations, which tend to have higher fertility rates than the general population. It was decided that these already high fertility rates are unlikely to increase over the next 35 years. Therefore, the 2001 to 2005 average ASFR was held constant throughout the projection period for these counties.

One final adjustment was made for Indiana counties where college student enrollments account for a sizeable share of total population in certain age groups. These counties tend to have lower fertility rates due to the student presence. However, as described below in greater detail, college student populations were removed from the projection cycles and then added back. With college students removed, the statewide fertility rate was substituted for the county specific rates.

Mortality

Survival rates for each age-sex group were calculated by constructing abridged life tables with five-year age groups except for the 0-1, 1-4, and 85+ population segments using 2005 vital statistics provided by the Indiana State Department of Health along with 2005 population figures. Rather than calculate unique survival rates for each Indiana county, the statewide survival rate was applied to each county for two primary reasons. First, small population and number of death values in specific age-sex groups in small counties can lead to irregularities. Second, variability of survival rates across counties is likely to be minimal. Exceptions to this practice were made for Marion and Lake counties due to their large non-white populations. Mortality patterns in the United States tend to vary substantially by race. Therefore, unique survival rates were calculated for these counties.

Migration

Age-sex specific net migration rates for the state and each county were developed by averaging net migration rates calculated for 1990 to 2000 with net migration rates determined for 2000 to 2005. The 1990 to 2000 net migration rates were developed for use in the previous set Indiana population projections published in 2003. These rates were derived using a residual method which applied survival probabilities to the 1990 census population counts in order to determine the expected survived population in 2000. These expected population figures were compared with the actual 2000 census population counts with the difference assumed to be net migration.

Because no source for age-sex specific migration rates were available, net migration rates for 2000 to 2005 were determined in a different manner. Data from the 2000 Census on age-sex specific in- and out-migration from 1995 to 2000 was adjusted to conform to total state and county net migration estimates for 2000 to 2005 according to a procedure outlined by Smith, Tayman, and Swanson in State and Local Population Projections. This adjustment procedure applies the same age-sex proportion of total net migration in the 1995 to 2000 dataset to the total net migration estimates for 2000 to 2005.

Migration is the most unstable component of population projections as patterns can be subject to large swings with little warning. According to U.S. Census population estimates, for instance, Indiana experienced a net out-migration of over 280,000 people in the 1980s followed by a sharp reversal with a net in-migration of ever 110,000 people during the 1990s. Net in-migration appears to be continuing in this decade, although at a substantially lesser rate than during the 1990s. The volatile nature of migration trends makes long-term prediction difficult. With this uncertainty in mind, a method was introduced to reduce migration rates after the initial projection cycle. This reduction involved converging all rates, positive or negative, toward zero in a non-linear trend that causes larger increase or decreases to occur in early projection cycles before leveling off in later cycles.

Numerous exceptions to the application of migration rates are required in order to account for unique populations in certain counties. These adjustments are required specifically for counties that are home to colleges, universities, or prisons that account for a sizeable share of the total population. In the case of 15 counties where college or university students account for a large share of total population in specific age groups, the decision was made to remove the estimated student population from the appropriate age groups. These estimates were based on college enrollment by age data from the U.S. Department of Education. The remaining population in these age groups was then projected forward using the statewide migration rates in these age categories in place of the original county specific rates. After the projections were complete, the student populations were added back to the appropriate age-sex cells. Indiana’s 15 college counties are:

• Delaware
• Grant
• Jasper
• Jefferson
• Knox  
• Monroe
• Montgomery
• Porter 
• Putnam
• St. Joseph
• Steuben
• Tippecanoe
• Vanderburgh
• Vigo
• Wabash

Prison population patterns are not quite as predictable as college student populations so a different approach was used for these counties. In these five counties—LaPorte, Miami, Parke, Perry, and Sullivan—the migration rates were held constant over the projection period for the age-sex cells determined to have a substantial prison population.

One final exception was made in the case of Hamilton County, which has experienced exceptional net in-migration in recent decades. It was judged unlikely that migration will continue at this brisk pace so Hamilton County’s migration rates were converged at a slightly greater rate than other counties.

Prepared by Matt Kinghorn, Demographer

Indiana Business Research Center
Kelley School of Business
Indiana University
November 2007