Differences between PovcalNet and LogNormal methods in 2013

	B	C	D	E	F	G	H	J	K	L	M	N	O	P	Q	R	S	T	U	V	W	X	Y	Z	AA	AB	AC	AD
1															11.50%
2	This is part of the documentaiont of Gapminder's estimation of number of people on different income levels in the dataset Income Mountains														12.80%
3															46.30%
4	Below we compare shares of populaiotns on different levels, from three different methods of estimating it.														28.40%
5															12.50%
6		PovcalNet		Explained here: http://iresearch.worldbank.org/PovcalNet/home.aspx
7		LogNormal		Common practic when generating distributions of people over income levels is to use the assumption that they distribute like a log normal curve.														11.30%	11.30%	12.50%	46.40%	28.60%	12.50%
8		LogNormalTopping		We found that the fit with PovcalNet is better if assume a slightly peakier shape than log normal, where we put a narrow lognormal curve on top of a broader lognormal curve at the bottom, assuming more people are in the center of the distribution.														12.50%
9																		46.40%
10		The below table show a comparison of the three methods for year 2013,																28.60%
11		which motivates our choise of the LogNormalTopping method, as it fits better with PovcalNet than the LogNormal assumption does.																12.50%
12
13	Comparing LogNormal vs PovCalNet							Comparing LogNormalTopping vs PovCalNet
14
15	Globally		Extreme poverty	Level 1 < $2	Level 2 >$2, < $8	Level 3 >$8, < $32	Level 4 >$32	Globally		Extreme poverty	Level 1 < $2	Level 2 >$2, < $8	Level 3 >$8, < $32	Level 4 >$32
16	PovcalNet		10.7%	12.0%	48.2%	27.6%	12.2%	PovcalNet		10.7%	12.0%	48.2%	27.6%	12.2%
17	LogNormal		13.2%	14.6%	45.8%	28.1%	11.4%	LogNormalTopping		11.3%	12.5%	46.4%	28.6%	12.5%		Absolute difs used for caclulating the average abs dif								Absolute difs used for caclulating the average abs dif
18	Difference = LogNormal - PovcalNet		2.5%	2.6%	-2.4%	0.5%	-0.8%	Difference = LogNormal - PovcalNet		0.6%	0.5%	-1.8%	1.0%	0.3%		3%	3%	2%	1%	1%				1%	1%	2%	1%	0%
19
20	Regional							Regional
21	PovcalNet							PovcalNet		Same numbers as to the left
22		The Americas	3.4%	3.7%	24.2%	39.8%	32.3%		The Americas	3.4%	3.7%	24.2%	39.8%	32.3%
23		Europe	0.4%	0.4%	10.0%	51.7%	37.9%		Europe	0.4%	0.4%	10.0%	51.7%	37.9%
24		Africa	32.0%	34.3%	54.0%	10.8%	0.9%		Africa	32.0%	34.3%	54.0%	10.8%	0.9%
25		Asia	8.1%	9.7%	61.4%	24.5%	4.4%		Asia	8.1%	9.7%	61.4%	24.5%	4.4%
26		China Urban	0.5%	0.6%	37.2%	58.8%	3.4%		China Urban	0.5%	0.6%	37.2%	58.8%	3.4%
27		China Rural	3.4%	4.3%	74.4%	20.9%	0.4%		China Rural	3.4%	4.3%	74.4%	20.9%	0.4%
28		India Urban	13.4%	15.6%	72.9%	11.4%	0.2%		India Urban	13.4%	15.6%	72.9%	11.4%	0.2%
29		India Rural	24.8%	28.60%	68.7%	2.2%	0.5%		India Rural	24.8%	28.6%	68.7%	2.2%	0.5%
30
31	LogNormal							LogNormalTopping
32		The Americas	3.4%	3.9%	23.3%	41.7%	31.0%		The Americas	3.9%	4.5%	23.4%	40.5%	31.6%
33		Europe	0.2%	0.3%	10.9%	55.4%	33.4%		Europe	0.1%	0.1%	8.9%	52.7%	38.3%
34		Africa	36.9%	40.5%	48.3%	10.5%	0.7%		Africa	32.1%	35.5%	51.3%	12.6%	0.7%
35		Asia	10.5%	12.9%	58.6%	24.4%	4.1%		Asia	8.6%	10.7%	59.1%	25.3%	4.9%
36		China Urban	0.9%	1.1%	39.5%	56.0%	3.4%		China Urban	0.8%	1.0%	37.2%	58.6%	3.2%
37		China Rural	5.9%	7.1%	70.8%	21.9%	0.1%		China Rural	4.4%	5.4%	71.1%	23.4%	0.1%
38		India Urban	16.0%	18.1%	66.4%	15.3%	0.2%		India Urban	12.8%	14.9%	72.0%	13.1%	0.1%
39		India Rural	24.10%	27.50%	69.30%	3.20%	0.00%		India Rural	24.9%	28.4%	69.2%	2.4%	0.0%
40
41		Difference = LogNormal - PovcalNet							Difference = LogNormalTopping - PovcalNet							Absolute difs used for caclulating the average abs dif								Absolute difs used for caclulating the average abs dif
42		The Americas	0.0%	0.2%	-0.9%	1.9%	-1.3%		The Americas	0.5%	0.8%	-0.8%	0.7%	-0.7%		0%	0%	1%	2%	1%				1%	1%	1%	1%	1%
43		Europe	-0.2%	-0.1%	0.9%	3.7%	-4.5%		Europe	-0.3%	-0.3%	-1.1%	1.0%	0.4%		0%	0%	1%	4%	5%				0%	0%	1%	1%	0%
44		Africa	4.9%	6.2%	-5.7%	-0.3%	-0.2%		Africa	0.1%	1.2%	-2.7%	1.8%	-0.2%		5%	6%	6%	0%	0%				0%	1%	3%	2%	0%
45		Asia	2.4%	3.2%	-2.8%	-0.1%	-0.3%		Asia	0.5%	1.0%	-2.3%	0.8%	0.5%		2%	3%	3%	0%	0%				0%	1%	2%	1%	1%
46		China Urban	0.4%	0.5%	2.3%	-2.8%	0.0%		China Urban	0.3%	0.4%	0.0%	-0.2%	-0.2%		0%	0%	2%	3%	0%				0%	0%	0%	0%	0%
47		China Urban	2.5%	2.8%	-3.6%	1.0%	-0.3%		China Rural	1.0%	1.1%	-3.3%	2.5%	-0.3%		3%	3%	4%	1%	0%				1%	1%	3%	3%	0%
48		India Urban	2.6%	2.5%	-6.5%	3.9%	0.0%		India Urban	-0.6%	-0.7%	-0.9%	1.7%	-0.1%		3%	3%	7%	4%	0%				1%	1%	1%	2%	0%
49		India Rural	-0.7%	-1.1%	0.6%	1.0%	-0.5%		India Rural	0.1%	-0.2%	0.5%	0.2%	-0.5%		1%	1%	1%	1%	1%				0%	0%	0%	0%	1%
50
51		Global
52		Average absolut dif	1.8%						Global
53		Max dif	2.6%						Average absolut dif	0.8%
54									Max dif	1.8%
55		Regional
56		Average absolut dif	1.9%						Regional
57		Max dif	6.5%						Average absolut dif	0.8%
58									Max dif	3.3%
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100