Census population estimates 2011-2019
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Brittain33
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« Reply #375 on: December 20, 2017, 06:53:54 PM »

Are the only *certain* partisan impacts of the change AL -1R, RI -1D, WV -1R?

Is there any reasonable way Ohio actually eliminates another Dem? I have to imagine they are maxed out, the Trump surge in Ryan's district notwithstanding.
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« Reply #376 on: December 21, 2017, 02:01:57 AM »

It's been an hour and Jim hasn't posted his updated spreadsheet yet.
Alabama would have been entitled to 6.737 representatives in 2010, based on use of the harmonic mean. By 2020 (based on exponential projection of 2010-2017 estimated growth rate) it will be entitled to 6.431 representatives. If we wanted to avoid paradoxes associated with ranking methods, we could independently round these numbers, though the total number of representatives would vary from 435. The difference between these two numbers is -0.309. This can be used to guesstimate future changes. For example, Alabama could be around 5.5 in 2050, and would lost its 6th seat in 2050 or 2060. The next columns are the projected number of seats for 2020 and the change from 2010. This does take into account ranking. These projections are unchanged from 2016.

The next columns are the additional change needed to get another seat, and the projected change for 2010-2020. Alabama is projected to increase by 132K from 2010 to 2020. It would need an additional 54K to get seven districts (and stave off the loss of a seat). Alabama has been growing at an annual rate at 0.27% from 2010-2017, and would have to kick it into gear at 0.69% for the last three years to keep a seventh seat.

State               2010    2020   10-20  20  Ch.   Need     Act    Rate    Need
Alabama            6.737   6.431  -0.307   6  -1      54     132   0.27%   0.67%
Alaska             1.117   1.101  -0.016   1   =     332      41   0.56%  14.89%
Arizona            8.999   9.502   0.503  10  +1     -60     877   1.29%   0.99%
Arkansas           4.129   3.998  -0.131   4   =    -406     123   0.41%  -4.69%
California        52.369  52.791   0.422  53   =    -547    3185   0.82%   0.33%
Colorado           7.087   7.644   0.557   8  +1    -157     814   1.51%   0.51%
Connecticut        5.049   4.718  -0.331   5   =    -195      19   0.05%  -1.96%
Delaware           1.358   1.383   0.025   1   =      96      89   0.95%   4.42%
Florida           26.435  28.562   2.127  29  +2    -223    3074   1.53%   1.15%
Georgia           13.627  14.010   0.383  14   =     378    1038   1.02%   2.30%
Hawaii             1.976   1.963  -0.014   2   =    -379      94   0.67%  -9.81%
Idaho              2.260   2.373   0.114   2   =     100     210   1.26%   3.29%
Illinois          18.043  16.705  -1.337  17  -1    -259     -39  -0.03%  -0.77%
Indiana            9.128   8.810  -0.318   9   =    -290     254   0.38%  -1.21%
Iowa               4.312   4.186  -0.126   4   =     242     137   0.44%   3.16%
Kansas             4.042   3.865  -0.176   4   =    -304      83   0.29%  -3.62%
Kentucky           6.120   5.894  -0.226   6   =    -336     159   0.36%  -2.44%
Louisiana          6.392   6.212  -0.180   6   =     223     210   0.45%   2.14%
Maine              1.933   1.818  -0.115   2   =    -264      10   0.08%  -7.61%
Maryland           8.131   8.059  -0.072   8   =     340     388   0.65%   2.64%
Massachusetts      9.217   9.128  -0.089   9   =     287     434   0.64%   2.13%
Michigan          13.902  13.054  -0.848  13  -1     344     109   0.11%   1.35%
Minnesota          7.472   7.436  -0.036   7  -1      50     380   0.69%   1.01%
Mississippi        4.201   3.936  -0.265   4   =    -358      23   0.08%  -4.46%
Missouri           8.433   8.059  -0.375   8   =     340     173   0.28%   2.26%
Montana            1.478   1.489   0.011   1   =       9      85   0.83%   1.13%
Nebraska           2.615   2.603  -0.012   3   =     -96     131   0.69%  -1.12%
Nevada             3.829   4.103   0.274   4   =     307     419   1.45%   4.98%
New Hampshire      1.917   1.836  -0.081   2   =    -278      36   0.27%  -7.78%
New Jersey        12.369  11.874  -0.494  12   =    -358     296   0.33%  -1.12%
New Mexico         2.937   2.785  -0.152   3   =    -238      40   0.19%  -4.09%
New York          27.244  26.154  -1.090  26  -1     269     653   0.33%   0.82%
North Carolina    13.413  13.805   0.392  14  +1    -317    1033   1.03%  -0.08%
North Dakota       1.070   1.145   0.076   1   =     294     117   1.61%  14.02%
Ohio              16.224  15.288  -0.936  15  -1     164     169   0.15%   0.65%
Oklahoma           5.297   5.247  -0.050   5   =     195     250   0.65%   2.41%
Oregon             5.408   5.593   0.185   6  +1    -105     436   1.08%   0.17%
Pennsylvania      17.862  16.775  -1.087  17  -1    -313     143   0.11%  -0.78%
Rhode Island       1.562   1.474  -0.088   1  -1      21      10   0.09%   0.81%
South Carolina     6.521   6.786   0.265   7   =    -260     559   1.15%  -0.73%
South Dakota       1.249   1.267   0.018   1   =     192      78   0.91%   8.32%
Tennessee          8.935   8.971   0.037   9   =    -414     516   0.78%  -1.47%
Texas             35.350  38.649   3.299  39  +3    -351    4459   1.65%   1.21%
Utah               3.917   4.260   0.343   4   =     186     477   1.60%   3.69%
Vermont            1.012   0.955  -0.057   1   =     461      -3  -0.05%  22.25%
Virginia          11.258  11.309   0.051  11   =     148     654   0.79%   1.41%
Washington         9.466  10.040   0.575  10   =     354     957   1.34%   3.01%
West Virginia      2.652   2.405  -0.247   2  -1      75     -51  -0.28%   1.21%
Wisconsin          8.010   7.636  -0.373   8   =    -151     150   0.26%  -0.69%
Wyoming            0.937   0.913  -0.024   1   =     498      22   0.38%  25.57%

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jimrtex
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« Reply #377 on: December 21, 2017, 07:04:25 AM »
« Edited: December 21, 2017, 03:15:21 PM by jimrtex »

It's been an hour and Jim hasn't posted his updated spreadsheet yet.
State               2010    2020   10-20  20  Ch.   Need     Act    Rate    Need
Alabama            6.737   6.431  -0.307   6  -1      54     132   0.27%   0.67%
Alaska             1.117   1.101  -0.016   1   =     332      41   0.56%  14.89%
Arizona            8.999   9.502   0.503  10  +1     -60     877   1.29%   0.99%
Arkansas           4.129   3.998  -0.131   4   =    -406     123   0.41%  -4.69%
California        52.369  52.791   0.422  53   =    -547    3185   0.82%   0.33%
Colorado           7.087   7.644   0.557   8  +1    -157     814   1.51%   0.51%
Connecticut        5.049   4.718  -0.331   5   =    -195      19   0.05%  -1.96%
Delaware           1.358   1.383   0.025   1   =      96      89   0.95%   4.42%
Florida           26.435  28.562   2.127  29  +2    -223    3074   1.53%   1.15%
Georgia           13.627  14.010   0.383  14   =     378    1038   1.02%   2.30%
Hawaii             1.976   1.963  -0.014   2   =    -379      94   0.67%  -9.81%
Idaho              2.260   2.373   0.114   2   =     100     210   1.26%   3.29%
Illinois          18.043  16.705  -1.337  17  -1    -259     -39  -0.03%  -0.77%
Indiana            9.128   8.810  -0.318   9   =    -290     254   0.38%  -1.21%
Iowa               4.312   4.186  -0.126   4   =     242     137   0.44%   3.16%
Kansas             4.042   3.865  -0.176   4   =    -304      83   0.29%  -3.62%
Kentucky           6.120   5.894  -0.226   6   =    -336     159   0.36%  -2.44%
Louisiana          6.392   6.212  -0.180   6   =     223     210   0.45%   2.14%
Maine              1.933   1.818  -0.115   2   =    -264      10   0.08%  -7.61%
Maryland           8.131   8.059  -0.072   8   =     340     388   0.65%   2.64%
Massachusetts      9.217   9.128  -0.089   9   =     287     434   0.64%   2.13%
Michigan          13.902  13.054  -0.848  13  -1     344     109   0.11%   1.35%
Minnesota          7.472   7.436  -0.036   7  -1      50     380   0.69%   1.01%
Mississippi        4.201   3.936  -0.265   4   =    -358      23   0.08%  -4.46%
Missouri           8.433   8.059  -0.375   8   =     340     173   0.28%   2.26%
Montana            1.478   1.489   0.011   1   =       9      85   0.83%   1.13%
Nebraska           2.615   2.603  -0.012   3   =     -96     131   0.69%  -1.12%
Nevada             3.829   4.103   0.274   4   =     307     419   1.45%   4.98%
New Hampshire      1.917   1.836  -0.081   2   =    -278      36   0.27%  -7.78%
New Jersey        12.369  11.874  -0.494  12   =    -358     296   0.33%  -1.12%
New Mexico         2.937   2.785  -0.152   3   =    -238      40   0.19%  -4.09%
New York          27.244  26.154  -1.090  26  -1     269     653   0.33%   0.82%
North Carolina    13.413  13.805   0.392  14  +1    -317    1033   1.03%  -0.08%
North Dakota       1.070   1.145   0.076   1   =     294     117   1.61%  14.02%
Ohio              16.224  15.288  -0.936  15  -1     164     169   0.15%   0.65%
Oklahoma           5.297   5.247  -0.050   5   =     195     250   0.65%   2.41%
Oregon             5.408   5.593   0.185   6  +1    -105     436   1.08%   0.17%
Pennsylvania      17.862  16.775  -1.087  17  -1    -313     143   0.11%  -0.78%
Rhode Island       1.562   1.474  -0.088   1  -1      21      10   0.09%   0.81%
South Carolina     6.521   6.786   0.265   7   =    -260     559   1.15%  -0.73%
South Dakota       1.249   1.267   0.018   1   =     192      78   0.91%   8.32%
Tennessee          8.935   8.971   0.037   9   =    -414     516   0.78%  -1.47%
Texas             35.350  38.649   3.299  39  +3    -351    4459   1.65%   1.21%
Utah               3.917   4.260   0.343   4   =     186     477   1.60%   3.69%
Vermont            1.012   0.955  -0.057   1   =     461      -3  -0.05%  22.25%
Virginia          11.258  11.309   0.051  11   =     148     654   0.79%   1.41%
Washington         9.466  10.040   0.575  10   =     354     957   1.34%   3.01%
West Virginia      2.652   2.405  -0.247   2  -1      75     -51  -0.28%   1.21%
Wisconsin          8.010   7.636  -0.373   8   =    -151     150   0.26%  -0.69%
Wyoming            0.937   0.913  -0.024   1   =     498      22   0.38%  25.57%

Over this decade projections have changed very little.

After 2011, projected gainers were Colorado, Florida, North Carolina, Texas+3, and Virginia.
Projected losers were Alabama, Illinois, Michigan, Minnesota, Ohio, Pennsylvania, and Rhode Island.

In 2011, Arizona and Florida were still shaking off the effects of the housing bubble in 2008, which saw people without jobs upside down on their mortgages, and near-seniors not able to retire and move to Florida.  Oregon has been grasping a 6th seat for a long time, but not quite able to keep up with Washington, Nevada, Utah, Arizona, and Colorado. Mid-decade they had an uptick in population increase.

Meanwhile, New York has dropped from a rate that would have kept them losing a whole seat, to much slower growth. West Virginia went from anemic growth to an actual loss, and Virginia has slowed its growth, as the big government boom of the early Obama years has ended.

By 2011, North Carolina had gained a seat, and Minnesota had lost a seat, and if this were Australia, there would have been a redistribution.

By 2002, there were no changes.

By 2003, West Virginia was projected to lose its 3rd district, and Alabama keep its 7th. At the time West Virginia was at zero growth, and could have kept the district if it could only increase its rate of growth to 0.08%. It wasn't anything Alabama was doing, but simply that West Virginia had spun out.

By 2004, Texas would have gained a seat, and Pennsylvania lost a seat, triggering an Australian redistribution. There were no changes in the projections, but Alabama was getting narrowly close to losing a seat.

By 2005, Florida would have gained a seat, and Illinois lost a seat, triggering redistribution. The projections changed significantly. Arizona was projected to gain a seat, as was Oregon. Mid-decade growth in Oregon is roughly twice that of the early decade. California was also projected to gain a seat, but just barely. Virginia had fallen below (it had grown at a 0.86% rate, but if it increased to 0.89% it could keep the gain. Alabama was again projected to lose a seat, and New York to barely lose a seat.

By 2016, Oregon would have gained a seat, and Michigan lost a seat. Florida was now projected to gain a second seat, while California no longer was.

For 2017, Colorado would have gained a seat, and Texas a second seat. We would be busy speculating on the 8-district map in Colorado and 38-district map in Texas for the 2008 election. Meanwhile, New York and West Virginia would have lost a district.

In Australia, if it is too late to draw a full map, the most populous district is split in half, or the least two populous adjacent districts merged.

The projections for 2020 have not changed. There would be speculative maps for Arizona+1, Florida+2, and Texas+3, as well as Alabama-1, Ohio-1, and Rhode Island -1 (no speculation needed here, except who will win the Democratic primary between two incumbents).
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Brittain33
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« Reply #378 on: December 21, 2017, 08:35:35 AM »

Interesting that a Puerto Rican in-migration can't move the needle further in Florida, but a hurricane-driven bust in Texas *could* cost the third seat if sizable enough.
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Gass3268
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« Reply #379 on: December 21, 2017, 10:27:29 AM »

Interesting that a Puerto Rican in-migration can't move the needle further in Florida, but a hurricane-driven bust in Texas *could* cost the third seat if sizable enough.

I believe these estimates are supposed to be from July, 2017. So they would not take into account the Hurricanes. Like Muon said, it will be interesting if the Puerto Rican hurricane diaspora's impact also on New York, along with Florida.
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Oryxslayer
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« Reply #380 on: December 21, 2017, 10:49:06 AM »

I doubt the NY migration will have much of an effect, probably the greatest impacts will be forcing the lost seat to be upstate and perhaps giving Velazquez an actual HVAP seat. FL movement will probably lock down their second gain, and perhaps direct both seat towards the I-4, rather then one 1-4 and one Miami metro seat.

The Houston hurricane is perhaps the most interesting. While those with flood insurance were probably secure, a bunch of housing in the region is now covered in mold and other flood related issues. It wouldn't take much to push Texas below their third seat, giving it to Montana. The questions is, will the losses from Houston move the needle for one year enough to temporarily slow the rapid growth of the state, 
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Nyvin
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« Reply #381 on: December 21, 2017, 10:55:15 AM »
« Edited: December 21, 2017, 01:59:54 PM by Nyvin »

Montana gaining a second seat really could be a good outcome for democrats,  western Montana has some pretty liberal areas and is actually trending Democratic in some cases.   If the state is split in two that seat just might become competitive.  
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Brittain33
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« Reply #382 on: December 21, 2017, 12:13:54 PM »

Interesting that a Puerto Rican in-migration can't move the needle further in Florida, but a hurricane-driven bust in Texas *could* cost the third seat if sizable enough.

I believe these estimates are supposed to be from July, 2017. So they would not take into account the Hurricanes. Like Muon said, it will be interesting if the Puerto Rican hurricane diaspora's impact also on New York, along with Florida.


Yeah. Never mind, I misread Jim's spreadsheet as saying Florida needed 3m additional people to get a third seat, but obviously that can't be true.
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Strudelcutie4427
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« Reply #383 on: December 21, 2017, 12:47:55 PM »

Montana gaining a second seat really could be a good outcome for democrats,  western Montana has some pretty liberal areas and is actually trending Democratic is cases.   If the state is split in two that seat just might become competitive. 

Drawing a hook from Missoula along the Canadian border and connecting it with East Montana would result in 2 roughly R+11 districts. It'd be interesting to see what they would do
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jimrtex
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« Reply #384 on: December 23, 2017, 07:00:26 AM »

Montana gaining a second seat really could be a good outcome for democrats,  western Montana has some pretty liberal areas and is actually trending Democratic is cases.   If the state is split in two that seat just might become competitive. 

Drawing a hook from Missoula along the Canadian border and connecting it with East Montana would result in 2 roughly R+11 districts. It'd be interesting to see what they would do

Montana has a redistricting commission. It drew two congressional districts in 1980. In the early 1990s when the loss of the 2nd seat was being litigated, the legislature ordered them to draw two districts. They apparently did so, but the final official report only had one district.

You could probably use the 1980 district boundaries, and then adjust them a bit each decade. Great Falls and Billings have probably had enough growth to keep the two districts pretty much in balance, and Silver Bow (Butte) has been in decline.

Maps of historical district boundaries

The numbers in the map names indicate the Congresses they were in effect. The First Congress began in 1789 (and under modern system would have been elected in 1788). The 51st Congress was elected in 1888, and the 101st in 1988.

Montana gained a second representative in 1912, but did not create two districts until 1918. Those districts were frozen until 'Reynolds v Sims' i.e. 66th (1918) through 89th (1964). It is quite possible that these districts were never equal population, since it appears that geography was more significant, following the Rockies.

90 through 92 (1966-1970) was the first equal-population map, and the boundary had to move eastward.

93 through 97 (1972-1980) and the line went further east, wrapping around Great Falls.

98 through 98 (1982) I'm not sure what changed or not changed. Perhaps there was litigation, and the districts had to made even more equal.

99 (1984) through 102 (1990) The boundary moved back west.

103 (1992) through 112 (2010) This is the single district map.

Perhaps there would have been a need for a larger change, and Gallatin (Bozeman) would put in the east, forcing the northern boundary back to the east around Great Falls.

In 1992, the Democratic and Republican representatives, and the Democrat (Pat Williams) won. Williams did not seek re-election in 1996, and the House seat has been Republican ever since.

With the two universities, the state capital, and Butte, the western district might be at least competitive for Democrats.

Historical Shapefiles

The animation on the first page is pretty cool.
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jimrtex
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« Reply #385 on: December 23, 2017, 07:49:14 AM »

Interesting that a Puerto Rican in-migration can't move the needle further in Florida, but a hurricane-driven bust in Texas *could* cost the third seat if sizable enough.
Florida's increase was only enough for a 2nd district, and that after recovery from the housing bubble took hold. Interstate migration has slowed down, and Florida must constantly be replenishing the retirees who move there in their 60s, and die within a few decades. There is more growth if you get younger migrants who are young enough to reproduce.

People who moved because their houses flooded, moved to Dallas and San Antonio and Austin, and did not leave the state. As long as oil holds at $60 there will be jobs in Houston. If you have a job and had flood insurance, you can live in an apartment or hotel, while your house is repaired or a new one is built. If you didn't have flood insurance, but have a job, you are still better off, than moving to where you don't have a job. And getting a job in San Francisco and renting a house in Stockton doesn't have a lot of appeal.
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jimrtex
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« Reply #386 on: December 23, 2017, 07:56:34 AM »

The most annoying thing about the estimates is that they change prior year(s) estimates (which i understand), but don't give you an easy way to see those changes.
On the estimates pages and also the American Fact Finder you can get previous vintages of estimates.

I think the changes are hard to visualize. If the 2016 and 2017 estimates  are the same, but the 2017 estimate is that there was an increase, then the 2016 estimate was revised downward. But that wouldn't be because they had missed a block of people dying or moving, but they overestimated some changes. So the growth curve did not change, but was modified. Perhaps an animation might work.
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« Reply #387 on: December 23, 2017, 12:45:57 PM »

An alternate projection could use just the last two years of estimates to determine the rate of growth for the rest of the decade. That model gives an extra seat to MT at the expense of one from CA.
This would be interesting because it illustrates a paradox in the apportionment method. California would have gained in population share while losing in representation share.

The last two decades there has been an inordinate number of states with fractions under 0.5, that got rounded upward. This benefited larger states, because they can spread their deficit among a large number of districts. So even though California had a bit over 52/435 of the population, they got a 53rd seat. But now the anomaly of states with fractions under 0.5 is disappearing, and though California will be closer to 53/435 of the population they could lose a district.
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« Reply #388 on: December 24, 2017, 04:43:38 AM »

I've been watching the census estimates throughout the decade and I've seen California move around a bit. To those that pay attention more closely, what are the odds or what will it take for the creation of CA-54?
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« Reply #389 on: December 24, 2017, 09:43:26 AM »

I've been watching the census estimates throughout the decade and I've seen California move around a bit. To those that pay attention more closely, what are the odds or what will it take for the creation of CA-54?

Losing a seat is more likely than gaining one. 

 
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« Reply #390 on: December 30, 2017, 05:59:12 PM »

I've been watching the census estimates throughout the decade and I've seen California move around a bit. To those that pay attention more closely, what are the odds or what will it take for the creation of CA-54?
In general terms, California would have to increase from 53/435 of the total population to 54/435 of the population. This means that California would have to increase at 54/53 - 1 or 1.89% faster than the country as a whole. But California is such a large share of the population (almost 1/8), that an 8% increase in California would produce a 1% increase in the total population, even if all the other states were static.

The USA as whole will increase about 7.7% over the decade, and based on projecting the first seven years estimates forward for 10 years, California will grow at 8.5%. But the growth rate in California has dropped the past two years.

In the first five years of the decade, California increased by 345K. 347K, 328K, 354K, and 331K; but in the last two years has only increased by 264K and 240K.

California needed 2.857M increase just to tread water. If the increase for the first five years had been sustained, California would have gained 3.410M, and the surplus of 553K would have gone a long way towards populating another congressional district.

But if we project the growth from the first seven years, then California would only grow 3.156M and the surplus would only be 299K. But if we project the last year's growth over the final three years, California would only have a 2.929M increase and California would just be treading water.

The Census Bureau also estimates the components of change, births, deaths, international migration, and domestic migration. Births and deaths are easy to estimate since most are officially recorded. This is not true for migration. You don't have to tell anyone you are moving, and you might not even know that you are changing residence. You might take a summer vacation, decide you like the location, and find a job.

Births have declined slightly (4%) over the seven years. This might represent a decline in the fertility rate (rate at which women in child-bearing ages have children), or a decline in the number of women of child-bearing ages, or both.

Deaths have increased by about 15% seven years. This is mostly due to aging baby boomers. The oldest baby boomers have aged from 65 to 72 during the first seven years. About 2% of 72-YO die, while only 1% of 65-YO will die.

The combination of the two has meant a decrease in the natural increase (births minus deaths) of about 21%, from 271K to 214K.

International migration has held steady, and actually increased the past three years.

Domestic net migration has increased sharply the last three years. Between 2010 and 2015, 3.2 million Californians left the state, and 2.9 million people moved to the state, for a net outflow of 300K. A lot of these are the same people. It may be exciting to live near the beach, but if the reality is that you have to commute from Barstow or Bakersfield to Los Angeles, you are too tired to go surfing on weekends. Or if you are divorced, you might move back home.

To make a big change in the net, you only need small increases in the inflow and outflow. A 5% decrease in inflow, and 5% increase in outflow, doubles the net flow.

I really don't know the reasons for the change. It could be lower inflows from people who realize that a higher salary does not make California livable if you can't afford housing or face a supercommute. Or perhaps it is retirees, whose home equity has recovered enough since 2008 that they can sell and move to a location where their Social Security and pension will go further.

Western states of WA, OR, ID, NV, MT. UT, and AZ have had their highest domestic inflows in the past two years. It isn't quite true for Colorado, in part because Colorado has had robust inflow throughout the decade. There is also strong inflow along the South Atlantic coastal states from North Carolina to Florida. And there have been small upticks in places like MN, AR, TN, DE, NH, and ME. So there has been an increase in outflow to nearby states.

A more obscure effect is rounding. Imagine that you polled 1000 persons, and 434 said Good, 353 said Bad, and 213 said Otherwise.

So you write an article that says 43% Good, 35% Bad, 21% Otherwise (* percentages do not total 100 because of rounding)

Or perhaps the results were 436 Good, 357 Bad, and 207 Otherwise. This is reported as 44% Good, 36% Bad, and 21% Otherwise. In this case, the percentages add to 101.

It is not because the pollster in one case didn't interview enough people, and in the second case polled too many, it is the effect of rounding error. In other cases, the rounding errors cancel, and the percentages will add to 100 (434 Good, 358 Bad, 208 Otherwise, rounds to 43, 36, 21).

The same thing can happen with the apportionment of representatives, except there are 50 states and 435 representatives. It would be embarrassing for C-SPAN to have vote totals showing *Numbers do not total 435 due to rounding.

One might expect that if you represented each states representation as decimal fraction (e.g. 52.368) 25 of the fractions would be less than 0.500 and 25 would be greater than 0.500, While this is the statistical expectation*, it won't always be true. It is somewhat like flipping a coin 50 times. The most likely outcome is 25 heads and 25 tails, but it can be more or less. It is possible, though extremely improbable that all 50 fractions would be less than 0.5, or all 50 would be more than 0.5.

And even then the total of the fractions might not sum to 25. It is possible for example that the 25 fractions less than 0.5, average 0.4, and sum to 10, while the 25 fractions greater than 0.5 average 0.8 and sum to 20, giving a sum of fractions of 30. If the fractions sum to 30, we have to give an extra seat to 30 states, but only 25 would have fractions greater than 0.5 and "deserve" an extra seat. We would have to give the other five seats to the "least undeserving".

It happens that when "extra" seats are given out, that larger states like California are favored.

On the other hand, it is also possible that the total of the fractions is less than 25, even when there are 25 states with a fraction greater than 0.5. In that case, we don't have enough extra seats to hand out. When this occurs, larger states like California are disfavored.

As it turns out in 2000 and 2010, there were more extra seats to be handed out than there were states clearly deserving them. One of those was California, which received a 53rd seat when it was still closer to 52 than 53. In the earlier part of this decade, California was approaching actually having 53/435 of the population, but with the recent uptick in domestic outflow, could drop back closer to 52.5 or 52.6. And the distribution of fractions appears to be trending back towards the ordinary, and it might be that California could be apportioned 52 seats, even while its population share increased.

*Not exactly, but within a quibble.
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jimrtex
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« Reply #391 on: December 31, 2017, 05:08:36 PM »

This is a closer look at the states of interest.

State               2010    2020   10-20  20  Ch.   Need     Act    Rate    Need
Alabama            6.737   6.431  -0.307   6  -1      54     132   0.27%   0.67%
Arizona            8.999   9.502   0.503  10  +1     -60     877   1.29%   0.99%
California        52.369  52.791   0.422  53   =    -547    3185   0.82%   0.33%
Colorado           7.087   7.644   0.557   8  +1    -157     814   1.51%   0.51%
Florida           26.435  28.562   2.127  29  +2    -223    3074   1.53%   1.15%
Georgia           13.627  14.010   0.383  14   =     378    1038   1.02%   2.30%
Illinois          18.043  16.705  -1.337  17  -1    -259     -39  -0.03%  -0.77%
Michigan          13.902  13.054  -0.848  13  -1     344     109   0.11%   1.35%
Minnesota          7.472   7.436  -0.036   7  -1      50     380   0.69%   1.01%
Montana            1.478   1.489   0.011   1   =       9      85   0.83%   1.13%
New York          27.244  26.154  -1.090  26  -1     269     653   0.33%   0.82%
North Carolina    13.413  13.805   0.392  14  +1    -317    1033   1.03%  -0.08%
Ohio              16.224  15.288  -0.936  15  -1     164     169   0.15%   0.65%
Oregon             5.408   5.593   0.185   6  +1    -105     436   1.08%   0.17%
Pennsylvania      17.862  16.775  -1.087  17  -1    -313     143   0.11%  -0.78%
Rhode Island       1.562   1.474  -0.088   1  -1      21      10   0.09%   0.81%
Texas             35.350  38.649   3.299  39  +3    -351    4459   1.65%   1.21%
Virginia          11.258  11.309   0.051  11   =     148     654   0.79%   1.41%
West Virginia      2.652   2.405  -0.247   2  -1      75     -51  -0.28%   1.21%


Alabama has only added 89K the first seven years, and is projected to add 43K more, but they would need another 54K beyond that to keep the seventh seat, which would require a better than doubling of the growth rate. It is not going to happen.

Arizona appears to be on the edge, but it really isn't. If an annual growth rate of 1.29% decreased to 0.99%, it could miss out. But the growth rate has been increasing, and was 1.56% last year.

Growth in California has dropped off significantly in the last few years. The projection is now whether California will keep its 53rd seat (it will), not whether it will gain a 54th.

Growth in Colorado has been steady to increasing a bit. To miss out on the 8th seat would mean a total collapse in the growth rate from 1.51 to 0.51%.

Florida has increased its growth rate so that is now pretty solid for a second seat. To miss out, it would have to drop down to 1.15% per year. Last year it was at 1.59%. But Florida is a long way from adding a 3rd seat.

Georgia is matching North Carolina, but it got its 14th seat in 2010 while North Carolina missed out.

Illinois is losing population, but only slightly. To lose a second seat would require a mass exodus. Since Illinois is losing at more than one district per decade (1.337) it would be a prime candidate to lose two districts next decade.

For Michigan to keep its 14th seat would require going from tepid growth to people pouring in.

Minnesota continues to drift away from keeping its 8th seat. Minnesota is projected to gain 7.2% this decade, but the country as a whole is gaining 7.7%. Minnesota has averages a gain of 0.69% this decade. Last year was a good year at 0.93%, but this is still short of the 1.01% it will need to catch up. The states that Minnesota is chasing are Arizona and Florida, and they are unlikely to make it easy.

Montana is expected to add 85K this decade, but need 9K extra. When you are a small as Montana, 9K represents an extra year's growth. Montana did gain 1.14% this year, which is a bit better than what is needed. For the decade, Montana is growing 0.9% faster than the country for the decade. At that rate it takes decades if not centuries to gain a seat. Montana may also suffer a bit from lowered activity in the Williston Basin.

The growth rate for New York has sharply dropped during this decade. While the compounded rate for the decade is calculated at 0.33%, the estimate for 2016 to 2017 was 0.07%. While some of this decline may be attributed to Puerto Ricans retiring to the island, there must be many other factors at work, including the decline of people moving into cities. Puerto Ricans returning to the mainland will want to live with relatives. Some who had moved back to Puerto Rico may have done so because their children had moved elsewhere.

North Carolina had barely missed out on its 14th seat and may have already had received it by the time of the July 2010 estimate base.

Ohio is only projected to grow at 1.5% for the decade, enough to cause it to lose a full seat.

Oregon was dawdling along just below the level needed for a sixth seat until 2013, when net domestic inflow increased dramatically to give it a boost. This must be tied to more people moving north from California, and the number moving south remaining steady or declining.

Pennsylvania will only gain 1.1% for the decade, and will lose a seat.

Rhode Island is only gaining 0.9% for the decade, and will be passed by Montana. Rhode Island is more certain of losing its seat, than Montana gaining one (at least one of these must happen).

Texas is on pace to gain three seats. A 17.7% over the decade, which is 10% faster than the national rate, results in a 10% increase in representation (10% of 36 is 3.6). The only reason that Texas is not gaining a fourth seat is that it got a favorable rounding in 2013. Unemployment is at 3.8%, job growth in percentage term was 2nd in the country, and oil prices are at the highest level since 2014.

Virginia was somewhat close to gaining a seat in the early part of the decade, but since then domestic migration has reversed to an outflow. An 8.2% increase is just slightly ahead of the US rate.

West Virginia is one of three states losing population (Illinois and Vermont are the others), and will lose 2.8% of its population. West Virginia is the only state with a natural population decrease (more deaths than births), a result of an aging population, and potential parents leaving the state, or holding off having babies in uncertain times.
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politicallefty
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« Reply #392 on: January 01, 2018, 08:24:28 AM »

In general terms, California would have to increase from 53/435 of the total population to 54/435 of the population. This means that California would have to increase at 54/53 - 1 or 1.89% faster than the country as a whole. But California is such a large share of the population (almost 1/8), that an 8% increase in California would produce a 1% increase in the total population, even if all the other states were static.

The USA as whole will increase about 7.7% over the decade, and based on projecting the first seven years estimates forward for 10 years, California will grow at 8.5%. But the growth rate in California has dropped the past two years.

In the first five years of the decade, California increased by 345K. 347K, 328K, 354K, and 331K; but in the last two years has only increased by 264K and 240K.

California needed 2.857M increase just to tread water. If the increase for the first five years had been sustained, California would have gained 3.410M, and the surplus of 553K would have gone a long way towards populating another congressional district.

I appreciate your answer. I did read it all. The reason I asked is because I recall looking at Census estimates maybe 2 years ago and it seemed like California was on track for a 54th seat and now suddenly it could actually lose a seat. I realize that bigger states are more prone to the potential of gaining or losing a certain number of seats (i.e. muon noting that CA-53 would be seat 433 and CA-54 would be seat 440).

Do you have or know of a spreadsheet where one could input population numbers to determine the overall seat apportionment?

One thing I do wonder about is if certain states might make their own efforts to ensure the accuracy of the overall count.
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« Reply #393 on: January 01, 2018, 08:42:53 AM »

So it's quite likely both MT and RI have just 1 CD?
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Oryxslayer
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« Reply #394 on: January 01, 2018, 12:39:12 PM »

This is a closer look at the states of interest.


Excellent analysis as always, the only comment I would make is on NY. You actually already did a congressional district evaluation a while ago, and we found that ot was the Upstate CDs dropping pop like a stone. I recall the downstate Cds were a wash (some overpopulated, others underpopulated) whereas the upstate CDs were all between .98 and .92 of a CD in their respective year. It rather is not Puerto Ricans moving, but rather the usual Rust Velt decline we see across the great lakes area.


What MT is wishing for is radical change from the Hurricanes. Present growth rates are, as jimrtex has shown, are pretty much locked in. TX will probably experience a small slowdown next year as marginal number of families leave the Gulf Coast for other states (The majority stayed in the state), and as the construction market in the region freezes building new homes to repair and clean up the old damaged ones. Probably won't cause a significant downturn, but might be enough - and MT hopes, that they miss CD #3.

The east coast will also go through a shakeup as Puerto Ricans move to the mainland. The majority will no doubt head to NY and FL, locking in CD #2  fr the Sunshine state, and ensuring the cut CD in NY is upstate - probably NY 22 due to its central location. Some however will hed to areas with Puerto Rican communities like Reading PA.
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Minnesota Mike
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« Reply #395 on: January 01, 2018, 12:44:43 PM »


RI will almost certainly lose a seat but MT will be right on the threshold of gaining a seat. Right now the projection using short term trends has them gaining a seat, the projection using long term trends has them staying at one seat (FWIW I prefer using short term trends).

BTW Congress uses a different method of apportioning seats ( the Huntington–Hill method) than jimrtex does (The Vinton or Hamilton method) that can produce slightly different results.

https://en.wikipedia.org/wiki/United_States_congressional_apportionment
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« Reply #396 on: January 02, 2018, 11:40:41 AM »


RI will almost certainly lose a seat but MT will be right on the threshold of gaining a seat. Right now the projection using short term trends has them gaining a seat, the projection using long term trends has them staying at one seat (FWIW I prefer using short term trends).

BTW Congress uses a different method of apportioning seats ( the Huntington–Hill method) than jimrtex does (The Vinton or Hamilton method) that can produce slightly different results.

https://en.wikipedia.org/wiki/United_States_congressional_apportionment
I use Huntington-Hill. My use of "raw" may have misled you. I used a slightly cooked version.

The divisor methods don't nominally use a quota. We just divide state populations by the successive divisors and rank the quotients.

The divisors for Huntington-Hill are:

sqrt(n*(n+1) = 1.414, 2.449, 3.464, ... 52.498, ...

In 2010, California had a population 37,254,518 (disregarding the overseas population).

For California's 53 seat, we divide the state population by sqrt(52*53) = 52.498

37254518 / 52.498 = 709642.051

If 709642.051 is among the 435 largest quotients then California gets a 53rd seat which it did. But we notice that the quotients near the 435th seat are about equal to the quota for the USA population divided by 435 = 708,408. But for reasons, I'll explain later, I'll divide by 711,428 (Q' adjusted quota).

We divide every state's population by 711,428.

q' = P / Q'

P'(California) = 52.366

We can then divide by the divisors, so 52.366 / 52.498 = 0.997. Values close to one represent states just below or above the 435th seat. We still have to rank these values, to determine which are rounded up or not. If we were doing independent rounding, we could simply look at the value, and since it is less than 1, round down. But if we did independent rounding, we could not guarantee 435 representatives.

Dividing by a positive constant does not change the relationship for ranking purposes:

if a > b and c > 0 then a/c > b/c

For Webster's method, a state with population p is entitled to r representatives, where
Q = PUSA/N, where PUSA is the total population of the 50 states, and N is the number of representatives (435 in this case).

p/Q = r

We can look at the value of R, and say that a state should have r representatives, but that is only true if we are apportioning fractional representatives. But it nonetheless correct for the raw share of the population. If a state has 27.235 / 435 of the population, it should have 27.235 representatives, except for the silly notion that representatives must be whole persons.

For Huntington-Hill

p/Q = sqrt((r-1/2)*(r+1/2))

To simplify our expression, we will use q = p/Q where q is a quotient.

q = sqrt(r-1/2)*(r+1/2))

Squaring both sides and multiplying the two terms under the radical.

q2 = r2 - 1/4

Solving for r,

r = sqrt(q2 +1/4)

This is the raw entitlement under Huntington-Hill. For example, a state with sqrt(2)/435 of the total population is entitled to 1.5 representatives.  1.5 = sqrt(2 + 1/4)

But if we do this for all states, and sum them up, we will end up with 436.841 representatives. But we can adjust our quota, so that it is Q' = PUSA/(435*(435/436.841). This will yield 435.015 representatives. Adjusting to 435/436.856 produces the expected 435 representatives.

So the "raw" numbers

r = sqrt(q'2 +1/4)

Where q' = p/Q'

And Q' is the adjusted quota.

For 2010, it is 711,428. The adjusted quota is dependent on the overall distribution of populations, but it can be calculated easily and converges quite quickly. The adjustment is increasing slightly

436.856/435 for 2010
436.873/435 for 2017 estimate.
436.881/435 for 2020 projected.

This increase indicates a greater small state bias. Not unexpected considering that the 2nd and 3rd most populous states are fast gainers, and the most populous state is an average gainer.

Among states with 3 or fewer representatives:

AK, SD, WY, VT, HI, RI, NH, ME, NM, NE, and WV are losing population share.
MT is staying even
DE, ID, ND* are gaining population share, but ND is quite iffy, and DE is moderate.

While the difference is 0.43%, the cost to California is 0.43% * 52.5 = 0.23 representatives.

Anyhow, the raw numbers provide an estimate of how many representatives a state should have if independent rounding were done and the distribution is based on Huntington-Hill. It is particularly useful for seeing temporal trends (e.g New Jersey is losing about 1/2 a representative per decade).

I do use it as an estimate of the number of seats a state should have. If a state is entitled to n.xxx representatives (as represented by a mixed decimal fraction), then it should have either n or n+1 (with a minimum of one). Summing the values of n, I can calculate the number of guaranteed seats without rounding. For 2020 projections this is 412 seats, leaving 23 seats (435-412) to be apportioned by rounding. I then divide the projected population of each state by the divisor for the next seat; sqrt(n*(n+1)) and assign the 23 final seats based on the largest quotients. This does not determine the 413th-435th seats assigned, but rather that a state will be in the top 435.

Note that the divisor methods do not not guarantee an apportionment of between n and n+1 seats. It may be outside that range, for example n-1 or n+2. This is known as a quota violation, and is a known flaw of Huntington-Hill and other divisor methods. This requires an unusual (rare) distribution of fractions, and modeling for the US indicates that it will be quite rare for the USA, because of the large number (50) of entities getting seats.

It may be quite common when there are only a few entities, and one is relatively quite large. An example is the British House of Commons, where there are only four apportionment entities (England, Scotland, Wales, and Northern Ireland), and England has 80%+ of the population.
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jimrtex
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« Reply #397 on: January 02, 2018, 11:50:38 AM »

Interesting that a Puerto Rican in-migration can't move the needle further in Florida, but a hurricane-driven bust in Texas *could* cost the third seat if sizable enough.

I believe these estimates are supposed to be from July, 2017. So they would not take into account the Hurricanes. Like Muon said, it will be interesting if the Puerto Rican hurricane diaspora's impact also on New York, along with Florida.


Interstate migration estimates for 2016 show that a very large share of Puerto Rican migration flow is to Florida (40%). Texas was second, slightly ahead of New York and Pennsylvania.

Florida is solidly gaining its 2nd seat, up from early in the decade when it was projected to only gain one. But it is a long way off from a third seat.
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Minnesota Mike
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« Reply #398 on: January 02, 2018, 12:44:24 PM »


RI will almost certainly lose a seat but MT will be right on the threshold of gaining a seat. Right now the projection using short term trends has them gaining a seat, the projection using long term trends has them staying at one seat (FWIW I prefer using short term trends).

BTW Congress uses a different method of apportioning seats ( the Huntington–Hill method) than jimrtex does (The Vinton or Hamilton method) that can produce slightly different results.

https://en.wikipedia.org/wiki/United_States_congressional_apportionment
I use Huntington-Hill. My use of "raw" may have misled you. I used a slightly cooked version.

The divisor methods don't nominally use a quota. We just divide state populations by the successive divisors and rank the quotients.

The divisors for Huntington-Hill are:

sqrt(n*(n+1) = 1.414, 2.449, 3.464, ... 52.498, ...

In 2010, California had a population 37,254,518 (disregarding the overseas population).

For California's 53 seat, we divide the state population by sqrt(52*53) = 52.498

37254518 / 52.498 = 709642.051

If 709642.051 is among the 435 largest quotients then California gets a 53rd seat which it did. But we notice that the quotients near the 435th seat are about equal to the quota for the USA population divided by 435 = 708,408. But for reasons, I'll explain later, I'll divide by 711,428 (Q' adjusted quota).

We divide every state's population by 711,428.

q' = P / Q'

P'(California) = 52.366

We can then divide by the divisors, so 52.366 / 52.498 = 0.997. Values close to one represent states just below or above the 435th seat. We still have to rank these values, to determine which are rounded up or not. If we were doing independent rounding, we could simply look at the value, and since it is less than 1, round down. But if we did independent rounding, we could not guarantee 435 representatives.

Dividing by a positive constant does not change the relationship for ranking purposes:

if a > b and c > 0 then a/c > b/c

For Webster's method, a state with population p is entitled to r representatives, where
Q = PUSA/N, where PUSA is the total population of the 50 states, and N is the number of representatives (435 in this case).

p/Q = r

We can look at the value of R, and say that a state should have r representatives, but that is only true if we are apportioning fractional representatives. But it nonetheless correct for the raw share of the population. If a state has 27.235 / 435 of the population, it should have 27.235 representatives, except for the silly notion that representatives must be whole persons.

For Huntington-Hill

p/Q = sqrt((r-1/2)*(r+1/2))

To simplify our expression, we will use q = p/Q where q is a quotient.

q = sqrt(r-1/2)*(r+1/2))

Squaring both sides and multiplying the two terms under the radical.

q2 = r2 - 1/4

Solving for r,

r = sqrt(q2 +1/4)

This is the raw entitlement under Huntington-Hill. For example, a state with sqrt(2)/435 of the total population is entitled to 1.5 representatives.  1.5 = sqrt(2 + 1/4)

But if we do this for all states, and sum them up, we will end up with 436.841 representatives. But we can adjust our quota, so that it is Q' = PUSA/(435*(435/436.841). This will yield 435.015 representatives. Adjusting to 435/436.856 produces the expected 435 representatives.

So the "raw" numbers

r = sqrt(q'2 +1/4)

Where q' = p/Q'

And Q' is the adjusted quota.

For 2010, it is 711,428. The adjusted quota is dependent on the overall distribution of populations, but it can be calculated easily and converges quite quickly. The adjustment is increasing slightly

436.856/435 for 2010
436.873/435 for 2017 estimate.
436.881/435 for 2020 projected.

This increase indicates a greater small state bias. Not unexpected considering that the 2nd and 3rd most populous states are fast gainers, and the most populous state is an average gainer.

Among states with 3 or fewer representatives:

AK, SD, WY, VT, HI, RI, NH, ME, NM, NE, and WV are losing population share.
MT is staying even
DE, ID, ND* are gaining population share, but ND is quite iffy, and DE is moderate.

While the difference is 0.43%, the cost to California is 0.43% * 52.5 = 0.23 representatives.

Anyhow, the raw numbers provide an estimate of how many representatives a state should have if independent rounding were done and the distribution is based on Huntington-Hill. It is particularly useful for seeing temporal trends (e.g New Jersey is losing about 1/2 a representative per decade).

I do use it as an estimate of the number of seats a state should have. If a state is entitled to n.xxx representatives (as represented by a mixed decimal fraction), then it should have either n or n+1 (with a minimum of one). Summing the values of n, I can calculate the number of guaranteed seats without rounding. For 2020 projections this is 412 seats, leaving 23 seats (435-412) to be apportioned by rounding. I then divide the projected population of each state by the divisor for the next seat; sqrt(n*(n+1)) and assign the 23 final seats based on the largest quotients. This does not determine the 413th-435th seats assigned, but rather that a state will be in the top 435.

Note that the divisor methods do not not guarantee an apportionment of between n and n+1 seats. It may be outside that range, for example n-1 or n+2. This is known as a quota violation, and is a known flaw of Huntington-Hill and other divisor methods. This requires an unusual (rare) distribution of fractions, and modeling for the US indicates that it will be quite rare for the USA, because of the large number (50) of entities getting seats.

It may be quite common when there are only a few entities, and one is relatively quite large. An example is the British House of Commons, where there are only four apportionment entities (England, Scotland, Wales, and Northern Ireland), and England has 80%+ of the population.

Got it.
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jimrtex
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« Reply #399 on: January 02, 2018, 08:41:15 PM »

In general terms, California would have to increase from 53/435 of the total population to 54/435 of the population. This means that California would have to increase at 54/53 - 1 or 1.89% faster than the country as a whole. But California is such a large share of the population (almost 1/8), that an 8% increase in California would produce a 1% increase in the total population, even if all the other states were static.

The USA as whole will increase about 7.7% over the decade, and based on projecting the first seven years estimates forward for 10 years, California will grow at 8.5%. But the growth rate in California has dropped the past two years.

In the first five years of the decade, California increased by 345K. 347K, 328K, 354K, and 331K; but in the last two years has only increased by 264K and 240K.

California needed 2.857M increase just to tread water. If the increase for the first five years had been sustained, California would have gained 3.410M, and the surplus of 553K would have gone a long way towards populating another congressional district.

I appreciate your answer. I did read it all. The reason I asked is because I recall looking at Census estimates maybe 2 years ago and it seemed like California was on track for a 54th seat and now suddenly it could actually lose a seat. I realize that bigger states are more prone to the potential of gaining or losing a certain number of seats (i.e. muon noting that CA-53 would be seat 433 and CA-54 would be seat 440).

Do you have or know of a spreadsheet where one could input population numbers to determine the overall seat apportionment?

One thing I do wonder about is if certain states might make their own efforts to ensure the accuracy of the overall count.
These are based on the actual estimates for each year (July) for 2010 through 2017, and projected forward to 2020.

Year   Estimate  Projection
2010   52.594   52.781
2011   52.689   53.389
2012   52.778   53.426
2013   52.858   53.416
2014   52.947   53.431
2015   52.999   53.370
2016   52.968   53.195
2017   52.914   53.037
2018   52.860   52.918
2019   52.752   52.766
2020   52.590   52.590

In July 2010, California was estimated to have 52.594/435 of the US population. This was up from the 52.589 from the Census. Projected forward for the remainder of the decade this would be projected to reach 52.781 in 2020 (the first estimate was only for one quarter). Through about 2014, the increase in share was about 0.090/435 per year, or about 0.900/435 per decade, enough to likely gain the 54th seat, or put it in the realm of possibility.

The population share increase in 2015 declined to 0.052 in 2016, and the projected 2020 population declined. In 2016 and 2017, California's population share declined. It was growing slightly slower than the country as whole (0.1%). But the projected share for 2020 was greater than the estimate for 2017 which could only happen if the short term trend reversed itself.

Imagine you are on a roller coaster. You are going up the first rise, and have risen 400 feet in four seconds. You project that after 10 seconds you will rise 1000 feet.

You are entering the crest of the rise, and are at 450 feet after five seconds. You quickly calculate 450/5 * 10 = 900 feet after 10 seconds (you can't reach your smartphone and people are screaming, so you don't realize your assumption that the increase is constant and not slowing is wrong).

After you have begun to drop you are at 350 feet after seven seconds, and calculate 350/7 * 10 equals 500 feet after 10 seconds. You don't realize that you are projecting an increase because the projection is decreasing.

That is what is happening in California.

The projected estimates for 2018, 2019, and 2020 assume that the 2016-2017 decline will be repeated, which would get you back to the share in 2010 (i.e. California grew slightly faster than the USA in the first half of the decade, and slightly slower in the second half).

This might not be accurate. The growth rate began to decline in 2015, turned negative in 2016, and became even stronger in 2017. The net domestic outflow which is triggering the decline in share appears to be accelerating.

California had a massive influx of population after WWII, caused by people moving west (and exposure to more of the country during the war). Good economic times, and pent-up demand caused the baby boom. The boomers are now reaching retirement age. Social security is portable, and California has extreme housing costs. If you own a home, now is a good time to cash out (tax free) and move to Arizona/Nevada/Utah/Idaho.

It may also be too expensive for middle or low income persons to live in California. If you live in Kansas and are making $10/hour at Walmart, moving to California and making $15/hour is not an upgrade.

It is also possible that there is chain migration of aliens from California to other states. Many immigrants first move to live with relatives, even if they are somewhat distant. If you don't speak English, living with a second cousin-once removed-in-law, will provide support. If all your relatives live in California, you will locate in California. But over time, people may find jobs elsewhere, and with a bit of English, you might be able to find work in Phoenix or Las Vegas or Salt Lake, and recognize a small community that speaks your native language.

Also, the question that the Census Bureau asks is whether a person had a different residence one year ago. This is not the same as a citizenship question. Someone stationed in Germany with their family who is transferred to the United States, will be living in a new residence, and show up as an international transfer.

In 2016 top domestic interstate inflows were:

Florida 605K
Texas 532K
California 515K
North Carolina 331K
Georgia 305K
Arizona 273K
Virginia 264K
New York 261K
Washington 257K
Pennsylvania 252K
Colorado 223K
Illinois 204K

In 2016 domestic interstate outflows were:

California 658K
New York 450K
Texas 444K
Florida 433K
Illinois 346K
Virginia 275K
Georgia 258K
Pennsylvania 257K
North Carolina 256K
New Jersey 227K
Ohio 212K

Once migration is established it may become two-way. People move to a different state, get homesick, divorced, lose a job, and move home. A couple retires to Florida, after the husband dies, and the widow breaks her hip, she moves back to New York to live with her daughter (23 years later).

In 2016, California had 1173K domestic migrants (in and out), but only 143K net outflow. Small changes in inflow or outflow can have big changes in the net.

If we look at the ratio of inflow to outflow in 2016:

Arizona 1.42
Florida 1.40
Washington 1.34
Nevada 1.33
Oregon 1.30
North Carolina 1.29
South Carolina 1.29
Idaho 1.28
Utah 1.25
Alabama 1.22
Texas 1.20
Montana 1.20

New York 0.58
Illinois 0.59
New Jersey 0.64
Connecticut 0.67
Alaska 0.74
California 0.78
North Dakota 0.79

So California had 4 persons moving in, for every 5 moving out.
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