Federal Reserve Economic Data

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

Title 90% Confidence Interval Lower Bound of Estimate of Median Household Income for Santa Clara County, CA
Series ID MHICILBCA06085A052NCEN
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 2023-01-01
Last Updated 2024-12-20 2:33 AM 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 42496
1990-01-01 .
1991-01-01 .
1992-01-01 .
1993-01-01 47927
1994-01-01 .
1995-01-01 51234
1996-01-01 .
1997-01-01 57138
1998-01-01 60732
1999-01-01 64803
2000-01-01 70106
2001-01-01 68697
2002-01-01 66132
2003-01-01 64551
2004-01-01 65187
2005-01-01 74762
2006-01-01 79595
2007-01-01 82686
2008-01-01 86500
2009-01-01 83182
2010-01-01 82907
2011-01-01 83335
2012-01-01 89948
2013-01-01 90443
2014-01-01 95336
2015-01-01 100870
2016-01-01 109222
2017-01-01 115818
2018-01-01 123281
2019-01-01 129361
2020-01-01 136115
2021-01-01 138832
2022-01-01 147818
2023-01-01 151645

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