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December 07, 2019, 04:39:57 pm
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  Census population estimates 2011-2019
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Author Topic: Census population estimates 2011-2019  (Read 107760 times)
cinyc
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« Reply #625 on: May 23, 2019, 12:54:46 pm »

Here’s the new interactive map with the 18 vintage data. Default is percentage change of 2018 vs the 2010 Estimates base. To change maps, click on 18 Est % and select a year. 2010C-18 is vs. actual census numbers, which doesn’t take into account annexations and the like.

2018 Est # show numerical changes. The prior vintage estimates are in 17/16 %# – though they’re largely irrelevant now except to track changes in how Census estimated.

There’s also an isolate button on the main menu if you want to isolate a particular type of growth, like cities that increased by >20%.

https://cinycmaps.com/index.php/pop-change

Please let me know if you encounter any errors.
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Kevinstat
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« Reply #626 on: May 23, 2019, 07:41:22 pm »
« Edited: August 24, 2019, 04:44:47 pm by Kevinstat »

In the 2010 census, the State House "quotas" of Maine's largest municipalities** (those over 0.9/151 of Maine's population in any one of the three following tables), were as follows (with instances where the "Estimates Base" (EB) yields a different quota than the official census numbers noted in parentheses):

=7.6 (8*0.95) "cutoff"=
Portland city 7.5245 (EB 7.5244) (State Senate quota* 1.7441, between 1.05 and 1.9 "cutoffs")
=7.35 (7*1.05) "cutoff"=
...
=4.2 (4*1.05) "cutoff"=
Lewiston city 4.1596 (EB 4.1595) (State Senate quota* 0.9641, between 0.95 "cutoff" and 1.0 mark)
=4.0 mark=
=3.8 (4*0.95) "cutoff"=
Bangor city 3.7557 (EB 3.7539)
=3.15 (3*1.05) "cutoff"=
=3.0 mark=
=2.85 (3*0.95) "cutoff"=
South Portland city 2.8421 (EB 2.8423)
Auburn city 2.6208 (EB 2.6211)
Biddeford city 2.4186 (EB 2.4185)
Sanford city 2.3642 (EB 2.3634)
Brunswick town 2.3051 (EB 2.3052)
Augusta city 2.1753 (EB 2.1755)
Scarborough town 2.1506 (EB 2.1496)
Saco city 2.1009 (EB 2.1031)
=2.1 (2*1.05) "cutoff"=
=2.0 mark=
Westbrook city 1.9886 (EB 1.9910)
Windham town 1.9326 (EB 1.9321)
=1.9 (2*0.95) "cutoff"=
Gorham town 1.8621 (EB 1.8609)
Waterville city 1.7872 (EB 1.7873)
York town 1.4242 (EB 1.4228)
Falmouth town 1.2714 (EB 1.2709)
Kennebunk town 1.2275 (EB 1.2269)
Orono town 1.1779 (EB 1.1775)
Standish town 1.1224 (EB 1.1222)
Presque Isle city 1.1017
Wells town 1.0900
Kittery town 1.0788 (EB 1.0792)
Brewer city 1.0779 (EB 1.0782)
=1.05 "cutoff"=
Cape Elizabeth town 1.0248 (EB 1.0245)
Lisbon town 1.0241 (EB 1.0250)
=1.0 mark=
Topsham town 0.9985 (EB 0.9988)
Old Orchard Beach town 0.9803 (EB 0.9791)
Skowhegan town 0.9763 (EB 0.9758)
Bath city 0.9678
[Old Town city (0.8912 (EB 0.8919)) + Penobscot Indian Island Reservation (0.0693)] 0.9605 (EB 0.9612)
=0.95 "cutoff"=
Yarmouth town 0.9491 (EB 0.9492)
Caribou city 0.9309
Buxton town 0.9133 (EB 0.9134)
Freeport town 0.8956 (EB 0.8955)
...
Gray town 0.8822 (EB 0.8824)
...
Ellsworth city 0.8799
...
Cumberland town 0.8197 (EB 0.8188)

The largest municipalities as and according to the 2018 estimates and their State House "quotas" are as follows:

=7.6 (8*0.95) "cutoff"=
Portland city 7.4932 (State Senate quota* 1.7368, between 1.05 and 1.9 "cutoffs")
=7.35 (7*1.05) "cutoff"=
...
=4.2 (4*1.05) "cutoff"=
Lewiston city 4.0552 (State Senate quota* 0.9400, below 0.95 "cutoff")
=4.0 mark=
=3.8 (4*0.95) "cutoff"=
Bangor city 3.6099
=3.15 (3*1.05) "cutoff"=
=3.0 mark=
South Portland city 2.8889
=2.85 (3*0.95) "cutoff"=
Auburn city 2.6170
Biddeford city 2.4272
Sanford city 2.3899
Brunswick town 2.3107
Scarborough town 2.2961
Saco city 2.2280
Westbrook city 2.1407
Augusta city 2.1076
=2.1 (2*1.05) "cutoff"=
Windham town 2.0803
=2.0 mark=
Gorham town 1.9914
=1.9 (2*0.95) "cutoff"=
Waterville city 1.8780
York town 1.4837
Falmouth town 1.3809
Kennebunk town 1.3007
Orono town 1.2048
Wells town 1.1896
Standish town 1.1376
Kittery town 1.1108
Cape Elizabeth town 1.0507
=1.05 "cutoff"=
Brewer city 1.0211
Presque Isle city 1.0152
Lisbon town 1.0130
Old Orchard Beach town 1.0050
=1.0 mark=
Topsham town 0.9987
Yarmouth town 0.9610
Freeport town 0.9601
=0.95 "cutoff"=
Bath city 0.9397
Buxton town 0.9375
Skowhegan town 0.9312
Gray town 0.9258
Cumberland town 0.9212
Ellsworth city 0.9080
[Old Town city (0.8415) + Penobscot Indian Island Reservation (0.0660)] 0.9075
...
Caribou city 0.8590

Taking the "Estimates base" from April 1, 2010 (usually within a few people of the official numbers) shown in the same Census Bureau tables showing the above estimates, and adding to it the population gains (negative for losses) from that base to July 1, 2018 multiplied by 10/8.25 (I use a linear progression rather than exponential as it has the benefit of municipal projections being the same as county projections), the following are the projected 2020 State House "quotas" for all municipalities (in descending order) with projected (or 2010) quotas above 0.9000:

=7.6 (8*0.95) "cutoff"=
Portland city 7.4867 (State Senate quota* 1.7353, between 1.05 and 1.9 "cutoffs")
=7.35 (7*1.05) "cutoff"=
...
=4.2 (4*1.05) "cutoff"=
Lewiston city 4.0333 (State Senate quota* 0.9349, below 0.95 "cutoff")
=4.0 mark=
=3.8 (4*0.95) "cutoff"=
Bangor city 3.5797
=3.15 (3*1.05) "cutoff"=
=3.0 mark=
South Portland city 2.8987
=2.85 (3*0.95) "cutoff"=
Auburn city 2.6161
Biddeford city 2.4291
Sanford city 2.3955
Scarborough town 2.3269
Brunswick town 2.3118
Saco city 2.2542
Westbrook city 2.1721
Windham town 2.1115
=2.1 (2*1.05) "cutoff"=
Augusta city 2.0933
Gorham town 2.0188
=2.0 mark=
=1.9 (2*0.95) "cutoff"=
Waterville city 1.8971
York town 1.4965
Falmouth town 1.4041
Kennebunk town 1.3162
Orono town 1.2105
Wells town 1.2105
Standish town 1.1408
Kittery town 1.1175
Cape Elizabeth town 1.0562
=1.05 "cutoff"=
Lisbon town 1.0105
Old Orchard Beach town 1.0105
Brewer city 1.0092
=1.0 mark=
Topsham town 0.9987
Presque Isle city 0.9970
Freeport town 0.9737
Yarmouth town 0.9635
=0.95 "cutoff"=
Cumberland town 0.9427
Buxton town 0.9426
Gray town 0.9349
Bath city 0.9338
Skowhegan town 0.9219
Ellsworth city 0.9139
[Old Town city (0.8309) + Penobscot Indian Island Reservation (0.0653)] 0.8962
...
Caribou city 0.8439

*assuming 35 Senators.  With 33 or 31, Lewiston would be too small for a Senate district even under the 2010 Census figures.  Portland would still be comfortably between 1.05 and 1.9 State Senate quotas.

**I grouped Old Town city and the Penobscot Indian Island Reservation (big enough for a House district in 2010, although there are a couple census blocks (perhaps with no population) outside those two municipalities in that district, I think because they were entirely surrounded by the Penobscot Reservation) together, as technically Old Town doesn't belong in these tables but I thought it should be included.
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Nyvin
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« Reply #627 on: May 24, 2019, 07:56:34 pm »

What does it say about Louisiana?

Why is Louisiana suffering?

Poverty, poor quality of life, New Orleans being prone to bad weather, a sluggish economy, and a homicide rate ranking in the top 10 of the 50 states

Also thanks to Bobby Jindal's economy.
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Cokeland Saxton
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« Reply #628 on: May 25, 2019, 12:19:33 am »

150 largest cities as of 2018:

1. New York, NY (8,398,748)
2. Los Angeles, CA (3,990,456)
3. Chicago, IL (2,705,994)
4. Houston, TX (2,325,502)
5. Phoenix, AZ (1,660,272)
6. Philadelphia, PA (1,584,138)
7. San Antonio, TX (1,532,233)
8. San Diego, CA (1,425,976)
9. Dallas, TX (1,345,047)
10. San Jose, CA (1,030,149)
11. Austin, TX  (964,254)
12. Jacksonville, FL (903,889)
13. Fort Worth, TX (895,008)
14. Columbus, OH (892,533)
15. San Francisco, CA (883,305)
16. Charlotte, NC (872,498)
17. Indianapolis, IN (867,125)
18. Seattle, WA (744,955)
19. Denver, CO (716,492)
20. Washington, DC (702,455)
21. Boston, MA (694,583)
22. El Paso, TX (682,669)
23. Detroit, MI (672,662)
24. Nashville, TN (669,053)
25. Portland, OR (653,115)
26. Memphis, TN (650,618)
27. Oklahoma City, OK (649,021)
28. Las Vegas, NV (644,644)
29. Louisville, KY (620,118)
30. Baltimore, MD (602,495)
31. Milwaukee, WI (592,025)
32. Albuquerque, NM (560,218)
33. Tucson, AZ (545,975)
34. Fresno, CA (530,093)
35. Mesa, AZ (508,958)
36. Sacramento, CA (508,529)
37. Atlanta, GA (498,044)
38. Kansas City, MO (491,918)
39. Colorado Springs, CO (472,688)
40. Miami, FL (470,914)
41. Raleigh, NC (469,298)
42. Omaha, NE (468,262)
43. Long Beach, CA (467,354)
44. Virginia Beach, VA (450,189)
45. Oakland, CA (429,082)
46. Minneapolis, MN (425,403)
47. Tulsa, OK (400,669)
48. Arlington, TX (398,112)
49. Tampa, FL (392,890)
50. New Orleans, LA (391,006)
51. Wichita, KS (389,255)
52. Cleveland, OH (383,793)
53. Bakersfield, CA (383,579)
54. Aurora, CO (374,114)
55. Anaheim, CA (352,005)
56. Honolulu, HI (347,397)
57. Santa Ana, CA (332,725)
58. Riverside, CA (330,063)
59. Corpus Christi, TX (326,554)
60. Lexington, KY (323,780)
61. Stockton, CA (311,178)
62. Henderson, NV (310,390)
63. St. Paul, MN (307,695)
64. St. Louis, MO (302,838)
65. Cincinnati, OH (302,605)
66. Pittsburgh, PA (301,048)
67. Greensboro, NC (294,722)
68. Anchorage, AK (291,538)
69. Plano, TX (288,061)
70. Lincoln, NE (287,401)
71. Orlando, FL (285,713)
72. Irvine (282,572)
73. Newark, NJ (282,090)
74. Toledo, OH (274,975)
75. Durham, NC (274,291)
76. Chula Vista, CA (271,651)
77. Fort Wayne, IN (267,633)
78. Jersey City, NJ (265,549)
79. St. Petersburg, FL (265,098)
80. Laredo, TX (261,639)
81. Madison, WI (258,054)
82. Chandler, AZ (257,165)
83. Buffalo, NY (256,304)
84. Lubbock, TX (255,885)
85. Scottsdale, AZ (255,310)
86. Reno, NV (250,998)
87. Glendale, AZ (250,702)
88. Gilbert, AZ (248,279)
89. Winston-Salem, NC (246,328)
90. North Las Vegas, NV (245,949)
91. Norfolk, VA (244,076)
92. Chesapeake, VA (242,634)
93. Garland, TX (242,507)
94. Irving, TX (242,242)
95. Hialeah, FL (238,942)
96. Fremont, CA (237,807)
97. Boise, ID (228,790)
98. Richmond, VA (228,783)
99. Baton Rouge, LA (221,599)
100. Spokane, WA (219,190)
101. Des Moines, IA (216,853)
102. Tacoma, WA (216,279)
103. San Bernardino, CA (215,941)
104. Modesto, CA (215,030)
105. Fontana, CA (213,739)
106. Santa Clarita, CA (210,089)
107. Birmingham, AL (209,880)
108. Oxnard, CA (209,877)
109. Fayetteville, NC (209,468)
110. Moreno Valley, CA (209,050)
111. Rochester, NY (206,284)
112. Glendale, CA (201,361)
113. Huntington Beach, CA (200,641)
114. Salt Lake City, UT (200,591)
115. Grand Rapids, MI (200,217)
116. Amarillo, TX (199,924)
117. Yonkers, NY (199,663)
118. Aurora, IL (199,602)
119. Montgomery, AL (198,218)
120. Akron, OH (198,006)
121. Little Rock, AR (197,881)
122. Huntsville, AL (197,318)
123. Augusta, GA (196,939)
124. Port St. Lucie, FL (195,248)
125. Grand Prairie, TX (194,614)
126. Columbus, GA (194,160)
127. Tallahassee, FL (193,551)
128. Overland Park, KS (192,536)
129. Tempe, AZ (192,364)
130. McKinney, TX (191,645)
131. Mobile, AL (189,572)
132. Cape Coral, FL (189,343)
133. Shreveport, LA (188,987)
134. Frisco, TX (188,170)
135. Knoxville, TN (187,500)
136. Worcester, MA (185,877)
137. Brownsville, TX (183,392)
138. Vancouver, WA (183,012)
139. Fort Lauderdale, FL (182,595)
140. Sioux Falls, SD (181,883)
141. Ontario, CA (181,107)
142. Chattanooga, TN (180,557)
143. Providence, RI (179,335)
144. Newport News, VA (178,626)   
145. Rancho Cucamonga, CA (177,751)
146. Santa Rosa, CA (177,586)
147. Oceanside, CA (176,080)
148. Salem, OR (173,442)
149. Elk Grove, CA (172,886)
150. Garden Grove, CA (172,646)
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DINGO Joe
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« Reply #629 on: May 26, 2019, 05:39:29 pm »

What does it say about Louisiana?

Why is Louisiana suffering?

Poverty, poor quality of life, New Orleans being prone to bad weather, a sluggish economy, and a homicide rate ranking in the top 10 of the 50 states

Louisiana has been number one for homicides for like a decade now or more.  I assumed the recent drop had to do with massive flooding in and around Baton Rouge in 2016 and Baton Rouge proper has lost population when it previously was one of the faster growing areas.  For whatever reason, North Louisiana and the Atchafalaya Basin took total beatdowns last year.  I can understand that the cost of doing business will erode the population in swamp areas (as the swamps erode themselves) but I don't know any particular reason for the hefty drop in the North (save for Vernon Parish which seems to have some military related decline), It's never been economically vibrant up there, but they really can't even claim to be stagnant right now.
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Epaminondas
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« Reply #630 on: July 25, 2019, 02:52:49 am »

Naive question: which states (outside at-large) wouldn't redistrict if their house seat total was unaffected in 2020 ?
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Tintrlvr
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« Reply #631 on: July 25, 2019, 06:55:58 am »

Naive question: which states (outside at-large) wouldn't redistrict if their house seat total was unaffected in 2020 ?

Every state is required to redistrict for OMOV. Even states like Maine will shuffle a few towns around the edges, as in 2010. It is deeply unlikely that any state would have population changes so uniform that no tweaks to the maps were required.
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« Reply #632 on: July 26, 2019, 11:59:57 am »

Naive question: which states (outside at-large) wouldn't redistrict if their house seat total was unaffected in 2020 ?

Every state is required to redistrict for OMOV. Even states like Maine will shuffle a few towns around the edges, as in 2010. It is deeply unlikely that any state would have population changes so uniform that no tweaks to the maps were required.
West Virginia managed to get away without changing WV-01 in 2010.
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Strudelcutie4427
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« Reply #633 on: July 26, 2019, 01:26:21 pm »

Naive question: which states (outside at-large) wouldn't redistrict if their house seat total was unaffected in 2020 ?

If any it’d be one of the smaller ones like NH, ME, or HI
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« Reply #634 on: July 27, 2019, 12:34:55 am »

Naive question: which states (outside at-large) wouldn't redistrict if their house seat total was unaffected in 2020 ?

Every state is required to redistrict for OMOV. Even states like Maine will shuffle a few towns around the edges, as in 2010. It is deeply unlikely that any state would have population changes so uniform that no tweaks to the maps were required.
Estimates for the two New Hampshire districts from the 2017 ACS are that they are about 0.27% of the ideal popoulation. The MOE is about 3 times the deviation, meaning that it is quite possible that NH-2 is the larger rather than smaller district.

I doubt that there is the political will to put Manchester and Nashua in the same district.

It is quite possible that swapping no single town will make the districts more equal, but I suspect that there is some swap of two or three towns that would be. In any case, NH would make an affirmative decision to re-enact the existing districts, rather than not redistricting.
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cinyc
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« Reply #635 on: September 10, 2019, 12:53:43 am »

This is a work in progress in the beta testing stage, but here's an interactive map of the percentage/numerical change in total population by census tract. There are submaps for 2010-"15", 2000-"15" and 2000-10 (click on Tot Est % or Tot Est #, then the year).

The "2015" data is from the 2013-17 American Community Survey (2015 is the midpoint of that data); the 2000 estimates were based on percentage land area from the 2000-10 tract relationship tables.

https://cinycmaps.com/index.php/population-change/tract-population-change

Red is an increase; blue is a decrease.

Let me know if you encounter any errors or something that looks just plain wrong. Like I said, this is in beta.

Jimrtex - would using percentage population from the relationship tables yield a more accurate result? I'm ultimately going to estimate the changes in racial data, too.
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« Reply #636 on: September 10, 2019, 05:19:04 am »

This is a work in progress in the beta testing stage, but here's an interactive map of the percentage/numerical change in total population by census tract. There are submaps for 2010-"15", 2000-"15" and 2000-10 (click on Tot Est % or Tot Est #, then the year).

The "2015" data is from the 2013-17 American Community Survey (2015 is the midpoint of that data); the 2000 estimates were based on percentage land area from the 2000-10 tract relationship tables.

https://cinycmaps.com/index.php/population-change/tract-population-change

Red is an increase; blue is a decrease.

Let me know if you encounter any errors or something that looks just plain wrong. Like I said, this is in beta.

Jimrtex - would using percentage population from the relationship tables yield a more accurate result? I'm ultimately going to estimate the changes in racial data, too.

I would look into graying out low-population census tracts - or possibly any of the form

98xxxx (decimal suppressed).

In Texas, most of the dark blue tracts are of this type, and include tracts with airports or military bases outside base housing. The ACS might not even sample these areas. For the census, hotels are asked to report any persons who are resident - it might even be all guests are asked whether they are reported elsewhere, so as to prevent double counting.
I think that for some persons, "usual residence" means where they sleep most often.

A salesman may not have a conventional domicile, or may have established a base in a hotel. There may only be a handful of such persons. Trying to locate them by sample during the ACS may be impossible. Similarly, I doubt that an effort is made to locate persons sleeping rough or in cars.

The census bureau permits delineation of census tracts for areas that are largely non-residential (I think 98xx.xx is the code for these). This might have been new for 2010.

If there is a hotel in (on the edge of) a residential census tract, it might not be counted by the ACS, but this will have little impact on overall population of the tract. But a hotel on an airport might represent most if not all of the population counted in the census, and not be included in the ACS.

I don't understand your last question.
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cinyc
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« Reply #637 on: September 10, 2019, 10:38:28 am »
« Edited: September 10, 2019, 01:50:12 pm by cinyc »

What minimum population threshold would you suggest? 10? 25? 50? 100?

My other question is this: The 2000-10 Census Relationship file compares the 2000 census tracts to fit into the 2010 a number of ways. One way is by comparing percentage of land area in a given tract, AREALANDPCT00PT. Another is by comparing population, POPPCT00. Which should I be using when guestimating 2000 in the 2010 tracts?

So far in the beta, I’ve been using land area. Does Pop make more sense? Eventually, I’m going to guestimate change in Hispanic and Non-Hispanic White, etc. populations, too. Neither will be perfect there.
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jimrtex
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« Reply #638 on: September 11, 2019, 10:27:34 am »

What minimum population threshold would you suggest? 10? 25? 50? 100?

My other question is this: The 2000-10 Census Relationship file compares the 2000 census tracts to fit into the 2010 a number of ways. One way is by comparing percentage of land area in a given tract, AREALANDPCT00PT. Another is by comparing population, POPPCT00. Which should I be using when guestimating 2000 in the 2010 tracts?

So far in the beta, I’ve been using land area. Does Pop make more sense? Eventually, I’m going to guestimate change in Hispanic and Non-Hispanic White, etc. populations, too. Neither will be perfect there.
So for a census tract that had a simple division,

POPPCT00 would show the percentage of the 2010 population that was in a particular 2000 Census Tract???

If a 2000 tract was divided, the 2010 tracts might have similar population since the goal would be to create tracts near the target population of 4000. But that might not reflect the situation in 2000. In an area of rapid development one of the 2010 tracts might have been largely built out by 2000, and the other was newly built.

But using area might be even worse. The more developed area may be ready to be placed in an essentially permanent tract. There is no more space that can be developed, and the newly developed areas also include undeveloped land from when the area was part of a rural census tract.

But there are census tracts of 10,000 that could have or should have been divided in 2010, that only have 12,000 persons in 2015, and if divided for 2020 would to some degree  match the 2010 distribution.

The closer the 2000 population of an old 2000 tract matches the combined 2010 population of the new for 2010 tracts, the better the distribution is going to be.

Probably more work than you want to do, but you could use 2000 census blocks with 2010 tract boundaries, but the census blocks have been renumbered, and might not match the 2010 tract boundaries.
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cinyc
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« Reply #639 on: September 11, 2019, 07:39:33 pm »

POPPCT00 would show the percentage of the 2010 population that was in a particular 2000 Census Tract???

It shows the PCT Of 2000 population in the new 2010 census tract. I've changed the maps to be based on that instead of land area.

The interactive maps are now all there at the above link - though I might change one thing:

Maps under the “Tot Pop” tab show change over time in Total Pop, “NH Wh” change over time in the Non-Hispanic White population, etc. Within those tabs, the default maps set a minimum tract population size to get colored – it’s currently 100 for Total Pop and 50 of the type for races/Hispanic origin. I will probably lower these to 70/35 to solve a problem in Loving County, TX over the next few days.

Within each of those tabs, the maps are sorted by “PCT” Change or “NUM”erical change, then by year. “Min” maps have the minimum threshold; “All” maps color all tracts without the 100/50 min threshold.

The 10th tab, Pop PCT, contains maps of the overall percentage share of each race. The “Top” maps show the top race in each tract & PCT for the 8 racial/Hispanic groups. The “Race PCT” maps map the percentage of the selected race in each tract. The “Rel CHG” maps map the change from one cycle to another. Unfortunately, I was only able to map NH White, Hispanic, NH Black and NH Asian in the Rel CHG maps due to the size of the data file.

Let me know if you encounter any errors. If some maps aren’t appearing, you might have to clear your browser cache.
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« Reply #640 on: September 29, 2019, 10:54:10 pm »

The 2018 1-year ACS came out last Thursday. The top 10 CDs by population as of 7/1/18 are:

MT-AL 1,062,305
DE-AL 967,171
TX-22 935,386
ID-01 912,950
FL-09 902,812
TX-03 899,784
TX-10 896,798
TX-26 894,192
TX-31 883,347
SD-AL 882,235

RI-01 and 02 are the smallest, followed by WV-03 and WY-AL. RI and WV will likely lose a seat after 2020. MT was estimated to be larger than RI as of 7/1/18 - but we knew that last December.

I'm working on an interactive CD mapping tool. It currently shows estimated population change, racial and ancestry characteristics of each CD. I will eventually add election maps. They're on my website, here.
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« Reply #641 on: September 29, 2019, 11:20:36 pm »

Great job on the website cinyc!

I was looking at the population change map for Norfolk, Va.   I saw what I thought must have been a mistake for Census tract 38, a 87% decrease in a nice area that's been pretty stable. Looked around a bit and found this:
https://data.census.gov/cedsci/table?q=virginia%20population&hidePreview=true&table=P1&tid=DECENNIALSF12010.P1&g=0400000US51_1400000US51710003800&vintage=2018&layer=censustract&cid=DP05_0001E&lastDisplayedRow=15
has a note with the revised count and mentions the 2010 Census Count Question Resolution - which is where cities and towns can question what the count was, and the census makes a revision.   I don't know if there is data anywhere that incorporates all the revised counts from this.
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« Reply #642 on: September 29, 2019, 11:32:18 pm »
« Edited: September 29, 2019, 11:35:35 pm by cinyc »

Great job on the website cinyc!

I was looking at the population change map for Norfolk, Va.   I saw what I thought must have been a mistake for Census tract 38, a 87% decrease in a nice area that's been pretty stable. Looked around a bit and found this:
https://data.census.gov/cedsci/table?q=virginia%20population&hidePreview=true&table=P1&tid=DECENNIALSF12010.P1&g=0400000US51_1400000US51710003800&vintage=2018&layer=censustract&cid=DP05_0001E&lastDisplayedRow=15
has a note with the revised count and mentions the 2010 Census Count Question Resolution - which is where cities and towns can question what the count was, and the census makes a revision.   I don't know if there is data anywhere that incorporates all the revised counts from this.

Yeah - there will be errors in the 2010 Census data that have since been corrected. I downloaded the data from the actual 2010 Census, so the CCQR program has not been taken into account (it probably has in some of my incorporated place pop change maps of using Census' population estimates program maps where I used the 10 Estimates Base, instead of 10 Census).

There's also a known error in some Ancestry tracts that I need to fix because I used the 10 Census CBS 500k tract map, and Census changed the GEOIDs after 2010 to relect mistakes. The 2013-17 ACS uses the corrected GEOIDs. I made all the necessary changes for the Pop Change/Racial CD maps, but not the Ancestry CD maps - yet.

The other minor issue is that the legend/popup says Votes instead of Population/NH Whites/Hispanics, etc. in some places. That's a legacy coding issue (the code was written for election maps) that's on my to-do list to fix- along with allowing you to choose what minimum pop/votes you want to grey out. The latter is going to be a bit more difficult to implement, since it involves math.

The final issue is that I didn't break down tracts that are split between CDs, so the total pop will appear in both. It's not clear to me how to fix that without spending way more time than I'd want to.
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« Reply #643 on: September 30, 2019, 12:01:04 am »

I don't know if there is data anywhere that incorporates all the revised counts from this.

I found Census' 2010 errata notes.The reason for the errors in Norfolk (and San Diego, Groton, CT, Portsmouth, NH, Pascagoula, MS & Everett, WA) was... a systematic mistake in determining the placement of Navy vessels.

I'll put a fix on my to-do list.
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« Reply #644 on: October 02, 2019, 04:30:46 am »

I don't know if there is data anywhere that incorporates all the revised counts from this.

I found Census' 2010 errata notes.The reason for the errors in Norfolk (and San Diego, Groton, CT, Portsmouth, NH, Pascagoula, MS & Everett, WA) was... a systematic mistake in determining the placement of Navy vessels.

I'll put a fix on my to-do list.
This is another instance of uncertainty/ambiguity of residence for census purposes.

Even if the ships had been located correctly, it would not reflect the domicile of those assigned to the ship.
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« Reply #645 on: October 19, 2019, 05:04:26 am »

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