Tuesday, January 12, 2016

What does a million look like?

How many refugees could the USA settle quickly, distributed into communities across the country? This is not a proposal, just a back-of-the-envelope search for some sense of what’s do-able, if we were determined to do something.

Suppose the bishops caught fire and decided they were all going to move as fast as possible to settle refugees. They are all going to put refugee families in every parish. How many parishes are there?

The Official Catholic Directory for 2014 says there are 17,483 parishes in the country. So if every parish takes a family or a group – on average, of four people – that’s about 70,000 refugees settled.

Catholics are about 22% of the nation. So if Catholics can take 70,000, then other religious communities and organized civic groups (colleges, ethical societies), matching that, should be able to raise that by a factor of 5. All religious communities, and organized civic communities, should be able to take 350,000 refugees.  I mean, if people noticed that there’s a war going on, and acted as if wars can cause emergencies, then every parish (or other group) could take a family this afternoon. It would be a little messy for a few weeks – basements, couches, adjustments. But within a month, most people would be in living and dignified circumstances. Given a month to prepare, churches (and similar) could take 350,000 refugees, and provide hospitality that would not be embarrassing.

How about two families? Could your parish/church/synagogue/mosque/college/civic association take two families in a year? That would be a stretch, but is it do-able? There’s a war going on: can you help?

How about three? That would be a million refugees, fed and settled and befriended.

It’s not going to happen any time soon.

Me, I can’t handle a million. I can’t even keep track of all those zeroes: do not have a gut sense of the difference between one million and ten million. But could my parish, if convinced that there was an emergency, care for three families? Gulp. Yes, we can. In fact, we could do this without government help.

That’s what it would look like if we in the USA took our fair share.

Fair share #6 - using EU's approach

A fifth estimate of America’s fair share of Syrian refugees

The allocation plan used the European Union combines four factors: population, GDP (gross domestic product), unemployment, and the number of refugees welcomed in past five years.  Population and GDP are weighted equally. After those factors are combined to get an estimate of the nation’s fair share, there two correctives: unemployment and the history of welcoming refugees are correctives, that reduce a nation’s estimated fair share by up to 25%.

Please note that the EU estimates of fair share for relocating refugees started with a decision that Europe would take only 120,000, or 3% of the total number of Syrian refugees. That was a political decision, not based on any theory of justice.

The World Bank estimated, in 2014, that the GDP for the world was $77.9 trillion, and the GDP for the USA was $17.4 trillion, or 22%. I have not figured out how to use GDP as a means to figure out fair share of refugees. The European method started with the assumption that all EU members would share the burden; that assumption doesn’t work for the world. Syria, for example, will not share the load of refugees from Syria. But approximately: using GDP, the USA’s fair share is 22%, or 880,000 of the four million refugees from Syria.

Using population only, my estimate was that the fair share for the USA would be about 175,000.

Combining GDP and population estimates, weighted equally, the USA’s fair share would about 530,000. I don’t understand how to make the corrections for unemployment and history of welcome. But the largest possible correction would be to subtract a quarter of the total. So let’s take off the maximum until I figure out how to use their method more smoothly: 530,000 minus a quarter is a little under 400,000.

Very roughly, using the EU method of estimating fair share, the USA should take 400,000 Syrian refugees.

Now I have five estimates of the USA’s fair share of Syrian refugees:

1. AREA ONLY: 250,000
2. POPULATION ONLY: 175,000
3. ARABLE LAND ONLY: 750,000
4. “EMPTY BEDS”: 950,000
5. EU method: 400,000

Monday, January 11, 2016

Fair Share Estimate #4 – REAL POPULATION DENSITY

Fair Share Estimate #4 – REAL POPULATION DENSITY

The chart provides one way to estimate what is fair when the nations of the world try to figure out how to help Syrian refugees. How many should go where? This is NOT A POLICY PROPOSAL! This is a sketch to help think.

It’s simply a list of the 25 largest nations, the 25 nations with the most arable land, and the 25 nations with the largest populations. It gives the REAL POPULATION DENSITY of each nation as of 2014 (CIA World Factbook).

“Real population density” requires a little effort to understand. But consider Antarctica. There aren’t a lot of people at the South Pole. In 2005, there was the largest crowd ever wintering over there: 86 people! With five million square miles to share, that’s over 50,000 square miles apiece. But there’s not a lot of food, not a lot of shelter, not much light for months. So everybody was hanging out at one dinky little station, and it was crowded.

“Real population density,” also called “physiological density,” refers to the population on the arable land. Population is not a useful measure by itself; nor is land by itself; nor is arable land by itself. But real population density is an effort to put these factors together. The measurement has an awful history; it is used in population control presentations all the time. So if you use it, use it carefully.

There are two charts below. The first chart below shows the real population density of 43 nations (the largest, the most populous, and those with the most arable land). Real population density is population divided by arable land. The chart shows population, arable land, real population density, and real density as a percentage of the global average. The final column is “capacity,” the theoretical population of that nation is the real population density matched the global average (arable land X the global average of 463).

# by size
Nation
arable
population
Real density
% of average
 capacity
3
USA
1,650,062
321,368,864
195
42.1%
           763,978,706
7
INDIA
1,451,810
1,251,695,584
862
186.2%
           672,188,030
4
CHINA
1,385,905
1,367,485,388
987
213.1%
           641,674,015
1
RUSSIA
1,174,284
142,423,773
121
26.2%
           543,693,492
5
BRAZIL
586,036
204,259,812
349
75.3%
           271,334,668
6
AUSTRALIA
468,503
22,751,014
49
10.5%
           216,916,889
2
CANADA
415,573
35,099,836
84
18.2%
           192,410,299
46
UKRAINE
324,791
44,429,471
137
29.5%
           150,378,233
32
NIGERIA
300,736
181,562,056
604
130.4%
           139,240,768
8
ARGENTINA
274,490
43,431,886
158
34.2%
           127,088,870
14
MEXICO
243,457
121,736,809
500
108.0%
           112,720,591
37
TURKEY
229,764
79,414,269
346
74.7%
           106,380,732
9
KAZAKHSTAN
221,059
18,157,122
82
17.7%
           102,350,317
43
FRANCE
214,162
66,553,766
311
67.1%
              99,157,006
15
INDONESIA
201,456
255,993,674
1271
274.5%
              93,274,128
18
IRAN
195,600
81,824,270
418
90.4%
              90,562,800
36
PAKISTAN
190,319
199,085,847
1046
225.9%
              88,117,697
25
SOUTH AFRICA
147,609
53,675,563
364
78.5%
              68,342,967
22
NIGER
144,784
18,045,729
125
26.9%
              67,034,992
51
THAILAND
140,941
67,976,405
482
104.2%
              65,255,683
52
SPAIN
135,776
48,146,134
355
76.6%
              62,864,288
16
SUDAN
135,600
36,108,853
266
57.5%
              62,782,800
70
POLAND
122,545
38,562,189
315
68.0%
              56,738,335
63
GERMANY
115,698
80,854,408
699
150.9%
              53,568,174
27
ETHIOPIA
112,080
99,465,819
887
191.7%
              51,893,040
40
BURMA
98,135
56,320,206
574
124.0%
              45,436,505
72
ITALY
77,651
61,855,120
797
172.0%
              35,952,413
95
BANGLADESH
75,690
168,957,745
2232
482.1%
              35,044,470
10
ALGERIA
75,501
39,542,166
524
113.1%
              34,956,963
66
VIETNAM
65,528
94,348,835
1440
311.0%
              30,339,464
11
CONGO, DR
64,853
79,375,136
1224
264.3%
              30,026,939
73
PHILIPPINES
56,652
100,998,376
1783
385.1%
              26,229,876
80
United Kingdom
56,121
64,088,222
1142
246.6%
              25,984,023
62
JAPAN
43,620
126,919,659
2910
628.4%
              20,196,060
24
MALI
37,600
16,955,536
451
97.4%
              17,408,800
13
Saudi Arabia
35,900
27,752,316
773
167.0%
              16,621,700
21
CHAD
35,258
11,631,456
330
71.3%
              16,324,454
23
ANGOLA
33,038
19,625,353
594
128.3%
              15,296,594
30
EGYPT
29,067
88,487,396
3044
657.5%
              13,458,021
20
PERU
28,800
30,444,999
1057
228.3%
              13,334,400
17
LIBYA
18,123
6,411,776
354
76.4%
                8,390,949
19
MONGOLIA
11,816
2,992,908
253
54.7%
                5,470,808
12
GREENLAND
10
57,733
5773
1246.9%
                        4,630





Fair Share Estimate #3 – ARABLE LAND only

Fair Share Estimate #3 – ARABLE LAND only

The chart provides one way to estimate what is fair when the nations of the world try to figure out how to help Syrian refugees. How many should go where? This is NOT A POLICY PROPOSAL! This is a sketch to help think.

It’s simply a list of the 25 largest nations, the 25 nations with the most arable land, and the 25 nations with the largest populations. It gives the arable land of each nation as of 2014 (CIA World Factbook, charted conveniently in Wikipedia). It calculates what percentage of the world’s arable land that nation has (divide by 15,750,000 square kilometers, the world total). Then it provides an estimated “fair share” (multiplying the percentage times the number of Syrian refugees at the end of 2015, about 4 million).

“Arable land” is a slippery idea. The term is useful to the FAO (the Food and Agriculture Organization of the UN). It refers to land that is being used for agriculture. It excludes deep deserts, steep mountainsides, and frozen tundra, giving some measure of land usable for human habitation. But it also roads and urban areas – which is a nuisance. Further, it does not include land that could be used for agriculture (war zones in Sudan, wildlife habitat all over southern Africa). Should it include deforested land in the Amazon basin? Despite the flaws, it gives some hints of what’s out there.

(The CIA World Factbook says that Greenland has 0 arable land. I assigned it 10, so my charts wouldn’t go nuts.)

This is a flawed method. If you go by arable land only, China and India are near the top. Japan is supposed to take more than Egypt. But Greenland looks about right.

In this (flawed) sketch, the fair share for the USA would be over 400,000.

# by size
Nation
Arable
% of total
fair share
3
USA
1,650,062
10.5%
        419,063
7
INDIA
1,451,810
9.2%
        368,714
4
CHINA
1,385,905
8.8%
        351,976
1
RUSSIA
1,174,284
7.5%
        298,231
5
BRAZIL
586,036
3.7%
        148,835
6
AUSTRALIA
468,503
3.0%
        118,985
2
CANADA
415,573
2.6%
        105,542
46
UKRAINE
324,791
2.1%
           82,487
32
NIGERIA
300,736
1.9%
           76,377
8
ARGENTINA
274,490
1.7%
           69,712
14
MEXICO
243,457
1.5%
           61,830
37
TURKEY
229,764
1.5%
           58,353
9
KAZAKHSTAN
221,059
1.4%
           56,142
43
FRANCE
214,162
1.4%
           54,390
15
INDONESIA
201,456
1.3%
           51,163
18
IRAN
195,600
1.2%
           49,676
36
PAKISTAN
190,319
1.2%
           48,335
25
SOUTH AFRICA
147,609
0.9%
           37,488
22
NIGER
144,784
0.9%
           36,771
51
THAILAND
140,941
0.9%
           35,795
52
SPAIN
135,776
0.9%
           34,483
16
SUDAN
135,600
0.9%
           34,438
70
POLAND
122,545
0.8%
           31,123
63
GERMANY
115,698
0.7%
           29,384
27
ETHIOPIA
112,080
0.7%
           28,465
40
BURMA
98,135
0.6%
           24,923
72
ITALY
77,651
0.5%
           19,721
95
BANGLADESH
75,690
0.5%
           19,223
10
ALGERIA
75,501
0.5%
           19,175
66
VIETNAM
65,528
0.4%
           16,642
11
CONGO, DR
64,853
0.4%
           16,471
73
PHILIPPINES
56,652
0.4%
           14,388
80
United Kingdom
56,121
0.4%
           14,253
62
JAPAN
43,620
0.3%
           11,078
24
MALI
37,600
0.2%
             9,549
13
Saudi Arabia
35,900
0.2%
             9,117
21
CHAD
35,258
0.2%
             8,954
23
ANGOLA
33,038
0.2%
             8,391
30
EGYPT
29,067
0.2%
             7,382
20
PERU
28,800
0.2%
             7,314
17
LIBYA
18,123
0.1%
             4,603
19
MONGOLIA
11,816
0.1%
             3,001
12
GREENLAND
10
0.0%
                     3