Empirical Exercise yup, Assignments of Economics

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Typology: Assignments

2022/2023

Uploaded on 10/09/2023

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Q1: 100/20 and 80/20 Ratios
Argentina Bolivia Brazil
100/20 9.29 8.81 17.42
80/20 4.45 4.23 5.94
Q2: Lorenz Curve Data
Cumulative % Share of Income Argentina Bolivia Brazil
0% 0 0 0
20% 5.1 5.3 3.3
40% 15 15.7 10.8
60% 30 31 22.9
80% 52.7 53.4 42.5
100% 100 100 100
Q3: Per Capita Income
GDP/Capita ($) 20%
Argentina 13,686 697.99
Bolivia 3,523 186.72
Brazil 8,917 294.26
China 12,720 852.24
Egypt 4,295 386.55
Indonesia 4,788 349.52
Mozambique 541 22.72
Per Capita Income for each
Person in Country (Poorest
to Wealthiest, $):
0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%
0
10
20
30
40
50
60
70
80
90
100
Lorenz Curve
Argentina Bolivia Brazil China Egypt
Indonesia Mozambique Russian Fed. LoQ Linear (LoQ)
% Households by income distribution
% cumulative share of income
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Q1: 100/20 and 80/20 Ratios Argentina Bolivia Brazil 100/20 9.29 8.81 17. 80/20 4.45 4.23 5. Q2: Lorenz Curve Data Cumulative % Share of Income Argentina Bolivia Brazil 0% 0 0 0 20% 5.1 5.3 3. 40% 15 15.7 10. 60% 30 31 22. 80% 52.7 53.4 42. 100% 100 100 100 Q3: Per Capita Income GDP/Capita ($) 20% Argentina 13,686 697. Bolivia 3,523 186. Brazil 8,917 294. China 12,720 852. Egypt 4,295 386. Indonesia 4,788 349. Mozambique 541 22. Per Capita Income for each Person in Country (Poorest to Wealthiest, $): 0% 10% 20% 30% 40% 50% 0 10 20 30 40 50 60 70 80 90 100

Lorenz Curve

Argentina Bolivia Brazil Indonesia Mozambique Russian Fed. % Households by income distribu % cumulative share of income

Russina Fed. 15,345 1150. Q4: Variance Income GDP ($) 20% Argentina 68,430 3489. Bolivia 17,615 933. Brazil 44,585 1471. China 63,600 4261. Egypt 21,475 1957. Indonesia 23,940 1747. Mozambique 2705 113. Russian Fed. 76,725 5754. Q6: Discussing the Rankings of the two different Theories Variance Income per Person (Poorest to Wealthiest, $): The income variables for Q5 were not calculated due to time constraints. I suspect that by setting all GDPs/capita GDP/capita will lose any influence for the final results. The focus of the calculation is turned to the share of incom population. As a result, by setting the GDP/capita equal between the two countries, the model becomes an effectiv share of income, which more easily demonstrates evidence of inequal wealth distribution in that country. I suspect Q4, countries with a lower GDP/capita will experience extra inequality for shares of income.

me 40% 60% 80% 100% 6774.57 10264.5 15533.61 32435. 1831.96 2695.1 3945.76 8226. 3343.88 5394.79 8738.66 25636. 6805.2 9667.2 13992 28810. 2783.36 3500.95 4522.96 8980. 2633.4 3591 5027.4 10964. 205.58 302.96 470.67 1609. 8900.1 11892.38 16419.15 337590 o different Theories t that by setting all GDPs/capita to an equal $100,000, on is turned to the share of income for each percentile of the s, the model becomes an effective way to measure just the ibution in that country. I suspect that in the initial data from of income.

  1. Egypt
    1. Russian Fed.
  2. Indonesia
  3. China
  4. Bolivia
  5. Argentina
  6. Mozambique
  7. Brazil
  8. Egypt 2. Russian Fed. 3. Indonesia 4. China 5. Mozambique
  9. Bolivia
  10. Argentina
  11. Brazil