Methodology for Indiana State and County Population Projections, 2015 to 2050
Prepared by Matt Kinghorn, Senior Demographer
Indiana Business Research Center, Kelley School of Business, Indiana University
The Indiana population projections were produced using the cohort-component method, with the U.S. Census Bureau’s population estimates for 2015 (Vintage 2016) by age and sex for Indiana and its counties serving as the benchmark population figures. This method projects individual age-sex cohorts forward while applying specific mortality and migration rates. In addition, fertility rates are applied to the appropriate female 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 age 85 and above.
Assumptions and Limitations
There is always uncertainty surrounding population trends. For instance, economic conditions or land use decisions can shift migration patterns or medical breakthroughs can increase life expectancy. Migration patterns are particularly subject to large and sudden swings.
This instability in demographic trends has been on display in the years since the Great Recession. Indiana’s fertility rates and migration rates have been very low since 2009, and the state has been growing at its slowest rate since the late 1980s as a result. According to the U.S. Census Bureau’s population estimates, Indiana has added roughly 25,000 residents per year between 2010 and 2017, down significantly from its average annual growth of approximately 40,000 per year between 2000 and 2010.
The most important assumption introduced into these projections is that this slower growth will continue in the short term, but that migration rates and fertility rates will begin to revert back to longer run trends. Specifically, the demographic rates developed from data that represent the 2010 to 2015 period are applied to the first projection cycle ending in 2020. Over subsequent projection cycles, these rates then converge toward rates that are representative of the demographic trends evident in Indiana between 2000 and 2010. Other 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. Projections 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 2030 or 2035.
Finally, it is important to note that these projections are strictly demographic, meaning that they rely exclusively on the recent trends and the assumptions discussed above. No economic, land use, or environmental assumptions are introduced.
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 (ISDH). The IBRC calculated average annual ASFRs for 2013 to 2015 for the state and for each county in order to smooth year-to-year fluctuations. As discussed previously, these ASFRs were applied to the first projection cycle. The IBRC assumes that there will be some rebound in fertility rates in the next decade, so these initial ASFRs were then converged towards average rates from the 2005 to 2008 period over subsequent projection cycles.
While the IBRC does assume some rebound in fertility rates in the near term, the longer run outlook (i.e., 2030 to 2050) is that there will then be a slight decline in fertility. The change in these rates was based on the changes in fertility projected at the national level in a set of population projections produced by the U.S. Census Bureau in 2012. To implement this assumption, total fertility rates (TFR) for the nation were calculated for the population age 10 to 49 for each projection base year beyond 2030. 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 2015 base year.
State and county-specific 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. Life tables were calculated for 2013, 2014 and 2015 using vital statistics data provided by the ISDH and population estimates from the Census Bureau. An average of the survival rates from 2013 to 2015 were used in the projections.
Life expectancy and survival rates improved dramatically throughout the last century and these improvements can be expected to continue. In order to project increased survival rates, we relied on the changes in survival rates 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). Changes in age-sex survival rates from one projection base year to the target year in the national projections were applied to the corresponding projection cycles for the Indiana survival rates.
Age and sex-specific migration rate estimates were calculated using a residual method based on survival probabilities. The age-specific five year survival rates discussed previously were applied to Census Bureau population estimates for 2010 population in the appropriate age-sex groups to estimate an expected population for that same cohort in 2015. These expected population numbers approximate what the 2015 population would be in a given cohort if there was no migration over the five year period and deaths were the only source of population change. The difference between the expected population and the actual 2015 Census Bureau population estimate for that cohort becomes the net migration estimate.
This process is commonly referred to as the forward survival rate method. There is a similar procedure called the reverse survival rate method. Under this approach, the 2015 population counts are divided by the five-year survival rates in order to calculate an expected population in 2010. Again, the difference between the expected and actual population figures for a given cohort is the net migration estimate. These two methods yield similar results but the differences tend to widen for older age groups. For that reason, the migration rates used in these projections are an average of the forward and reverse survival rate methods.
Migration rates in Indiana have been very low in recent years. Indiana had average annual net migrations of roughly 18,000 residents per year in the 1990s and 9,000 per year during the 2000s. Census Bureau estimates suggest that Indiana’s annual net migration is down to 2,300 per year between 2010 and 2017. As with fertility rates, the IBRC applied the 2010 to 2015 migration rates to the first projection cycle. These migration rates then converged towards rates that were used in the last set of IBRC’s population projections published in 2012, which are representative of migration patterns for Indiana and its counties between 2000 and 2010.
Adjustments to the Base Population
Adjustments to the base population were made in counties where college student or prison populations account for a sizeable share of the total. These adjustments were necessary because these populations do not tend to age in place. In these cases, estimates of student or prison populations were removed from the base population before applying the cohort-component method and then added back after the projections were complete. Student or prisoner populations were held constant throughout the projection period.
The counties with adjusted base populations were:
- St. Joseph