Use Case

1. Population Growth: Understanding details about the population in an area is informative when deciding if it's the right site for expansion. Population growth can be a positive predictor of future sales within a market. 
2. Income: Depending on the product/services offered, the income level of the population may be imperative to the success of the location. Therefore, utilizing this information as you market plan can take some of the guesswork out of market selection in unknown areas. 
3. Market Outlook: Review the potential sales demand of an area based on numerous industries such as groceries, clothing, furniture, etc. Also compare it to the US market averages. 

Methodology For Population Estimates 

1. Estimate Households: PopStats starts their analysis at a highly granular level. Using a proprietary model, this data is correlated with Census household counts to estimate shifts in population quickly and accurately. Automated processes address anomalies, such as data inconsistencies or structural changes, ensuring clean, unbiased results. 
2. Estimate Household Populations: Using stable ratios of persons-to-households derived from Census data, PopStats adjusts these ratios to reflect local trends in household size. These refined figures are applied to the estimated households to calculate the population at a  blockgroup level, offering detailed insight into demographic changes. 
3. Apply Controls: To enhance accuracy, PopStats validates its results against multiple independent data sources, including U.S. Census Bureau estimates, state and federal agency data, and field surveys. Discrepancies are resolved using heuristics and statistical controls, ensuring the estimates remain consistent and credible. 

Methodology for Key Variables 

1. Age and Gender:  Age and gender are determined through a traditional cohort survival analysis. This sub-model to the main model looks at each age distribution within a race category and applies the appropriate birth and survival rates as determined by the NCHS (National Center for Health Statistics). These results are then balanced back to the base population using an iterative approach. 
2. Race/Ethnicity: Combines Census data with high-growth area insights from the Federal Financial Institutions Examination Council (FFIEC) and school demographic data. 
3. Income: Estimates county-level income using the IRS’s Survey of Income, U.S. Census Bureau’s CPS (Current Population Survey) income estimates, and personal income estimates from the BEA (Bureau of Economic Analysis). 
4. Housing Values: Housing Values are determined in a fashion similar to income estimates. Housing and associated values that existed as of April 2000 are updated using data from the OFHEO (Office of Federal Housing Enterprise Oversight).  New home values (homes built after April 2000) are determined by ratio analysis of the FFIEC’s mortgage values and actual selling prices 
5. Group Quarters: Accounts for populations in non-household settings (e.g., colleges, military bases, institutions) using data from the NCES, Department of Defense (DOD), and historical trends from the US Census. 

Data Sources for STI Popstats 

1. United States Census Bureau  
2. United States Postal Service (USPS)  
3. United States Department of Defense (DMDC)  
4. National Center for Education Statistics (NCES)  
5. National Center for Health Statistics (NCHS)  
6. Federal Financial Institutions Examination Council (FFIEC)  
7. Internal Revenue Service (IRS)  
8. Bureau of Economic Analysis (BEA)  
9. Bureau of Labor Statistics (BLS)  
10. Office of Federal Housing Enterprise Oversight (OFHEO)  
11. Department of Defense (DOD) 

Limitations

1. While STI PopStats uses advanced modeling techniques and a comprehensive data set, it's crucial to remember that these are still estimates and should be viewed as such. 

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