Federal Reserve Economic Data

Table Data - 90% Confidence Interval Upper Bound of Estimate of Median Household Income for Santa Clara County, CA

Title 90% Confidence Interval Upper Bound of Estimate of Median Household Income for Santa Clara County, CA
Series ID MHICIUBCA06085A052NCEN
Source U.S. Census Bureau
Release Small Area Income and Poverty Estimates
Seasonal Adjustment Not Seasonally Adjusted
Frequency Annual
Units Dollars
Date Range 1989-01-01 to 2022-01-01
Last Updated 2023-12-14 1:10 PM CST
Notes The U.S. Census Bureau provides annual estimates of income and poverty statistics for all school districts, counties, and states through the Small Area Income and Poverty Estimates (SAIPE) program. The bureau's main objective with this program is to provide estimates of income and poverty for the administration of federal programs and the allocation of federal funds to local jurisdictions. In addition to these federal programs, state and local programs use the income and poverty estimates for distributing funds and managing programs.

Household income includes income of the householder and all other people 15 years and older in the household, whether or not they are related to the householder. Median is the point that divides the household income distributions into two halves: one-half with income above the median and the other with income below the median. The median is based on the income distribution of all households, including those with no income.

A confidence interval is a range of values, from the lower bound to the respective upper bound, that describes the uncertainty surrounding an estimate. A confidence interval is also itself an estimate. It is made using a model of how sampling, interviewing, measuring, and modeling contribute to uncertainty about the relation between the true value of the quantity we are estimating and our estimate of that value. The "90%" in the confidence interval listed above represents a level of certainty about our estimate. If we were to repeatedly make new estimates using exactly the same procedure (by drawing a new sample, conducting new interviews, calculating new estimates and new confidence intervals), the confidence intervals would contain the average of all the estimates 90% of the time. For more details about the confidence intervals and their interpretation, see this explanation.
DATE VALUE
1989-01-01 46125
1990-01-01 .
1991-01-01 .
1992-01-01 .
1993-01-01 51653
1994-01-01 .
1995-01-01 55734
1996-01-01 .
1997-01-01 62126
1998-01-01 65850
1999-01-01 72660
2000-01-01 79606
2001-01-01 77295
2002-01-01 74551
2003-01-01 72103
2004-01-01 72702
2005-01-01 78611
2006-01-01 81955
2007-01-01 85844
2008-01-01 90549
2009-01-01 86797
2010-01-01 86347
2011-01-01 86147
2012-01-01 92442
2013-01-01 93243
2014-01-01 99102
2015-01-01 103512
2016-01-01 112464
2017-01-01 121118
2018-01-01 128585
2019-01-01 135527
2020-01-01 142809
2021-01-01 143490
2022-01-01 153186

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