Part 1 -
To complete this assignment, students should read assigned published articles/papers/ reports and write up short essays on the interpretation and case study.
Readings -
- "Principles on the use of direct age-standardisation in administrative data collections", published by Australian Government (2011)
- "Why do we continue to use standardized mortality ratios" published in Journal of Public Health Medicine (2001) and written by SA. Julious, J. Nicholl and S. George
- "New state and regional population projections for New South Wales," published in People and Place (2008) and written by Torn Wilson.
- "Migration to Australia since federation," published by Parliament of Australia (2010).
Additional readings (if necessary) that may support your answers:
- "Chapter 12: Population Projections and Estimates" as part of "Demographic Methods and Concept" written by Donald T. Rowland (200.3).
- "Understanding and Using Population Projections" published by Population Reference Bureau (2011), Measure Communication.
Q1. Mortality and Standardisation
To answer the following questions refer to the reading: "Principles on the use of direct age-standardisation in administrative data collections". Answer each question with a few paragraphs.
a. Write a brief summary of this reading, focuses on the following points:
- What are the article's main ideas or its key points?
- What is the author's purpose or intention throughout the text?
b. Two types of standardisation methods are mentioned: Direct and Indirect. What are the main differences between those two methods? Also explain why the study prefers to use the direct method rather than the indirect method.
To answer the following question refers to the reading: "Why do we continue to use standardized mortality ratios".
c. The reading emphasizes that the indirect standardisation is inappropriate for the comparison. What are possible explanations for this statement?
Q2. Population Projection
To answer the following questions refer to the reading: "New state and regional population projections for New South Wales." Please answer the following questions:
a. In producing population projections, the reading mentioned some assumptions applied to dealing with the future demographic variables. Discuss how the population projections produced in dealing with the future assumptions for:
- Assumptions for fertility,
- Assumptions for mortality, and
- Assumptions for migration (overseas and internal)
b. Compare and contrast the main characteristics of the population projections for NSW in 2036. Cover at least 3 points, such as population growth, age structure and regional population distribution (migration).
Q3. Australian Migration
To answer the following questions refer to the reading: "Migration to Australia since federation". Answer each question with a few paragraphs.
a. Write a brief summary on the changes in measuring method of permanent migration in Australia. What are its consequences to the trends of NOM (Net Overseas Migration)?
b. Summary the trends and patterns of three main Australian international migration streams (i.e. family, skill and humanitarian) in the last two decades.
c. From the reading, please assess and review Table 7. Summary and comment on the similarities/differences in Australia's population diversity due to migration prior and after the World War II: between the period 1901-1947 and the period 1054¬001. What are possible explanations for such trends?
Part 2 -
Q1. Mortality and Standardisation
The estimated numbers of population by age on 30/6/2015 and the number of death in 2015 for China and for Germany are given in the following table:
|
Age x
|
China
|
Germany
|
|
Population
|
Death (N)
|
Population
|
Death (N)
|
|
0-9
|
158,600,000
|
196,390
|
6,820,000
|
2,830
|
|
10-19
|
161,490,000
|
47,100
|
7,610,000
|
1,120
|
|
20-29
|
229,640,000
|
135,680
|
9,430,000
|
3,090
|
|
30-39
|
193,590,000
|
187,890
|
9,650,000
|
5,660
|
|
40-49
|
236,690,000
|
454,130
|
11,780,000
|
17,500
|
|
50-59
|
174,900,000
|
897,920
|
12,990,000
|
57,600
|
|
60-69
|
127,360,000
|
2,171,550
|
9,490,000
|
100,020
|
|
70-79
|
60,350,000
|
3,010,070
|
8,370,000
|
220,070
|
|
80+
|
24,870,000
|
3,453,080
|
4,710,000
|
535,300
|
|
Total
|
1,367,490,000
|
10,553,810
|
80,850,000
|
943,190
|
Using the mortality data provided previously, answer the following questions:
a. Estimate the age specific death rates (ASDR, per 1000 pop.) and crude death rates (CDR, per 1000 pop.) for Chinese population and for German population in 2015. Note: use 3 decimal places (dcp.) for the ASDR and CDR.
b. Using the 2015 China population as the standard population, calculate the indirectly standardised death rates (I-SDR) for German population and for Chinese population (Note: use 3 dcp. decimal point for I-SDR).
c. If the standardised mortality ratio (SMR) for German population is estimated 2.20 and for Chinese population is estimated 1.00. Using the 2015 Chinese population as the standard population, what are the new values of the indirectly standardised mortality rates (I-SDR) for German population and for Chinese population?
d. Using the results from questions 1.a. and 1.b, discuss and comment on the differences in the mortality parameters (CDR and l-SDR) and patterns of Chinese and German population. Please justify if we do need to use a standardisation method or not and what are the possible reasons for this.
Q2. Fertility and Population Projection
The estimated numbers of females in China and in German by age on 30/6/2015 and age-specific fertility rates-ASFR (per 1000) in 2015 are presented in the following table:
|
Age (x)
|
China
|
Germany
|
|
Number of females
on 30/06/2015
|
ASFR in 2015
(per 1000)
|
Number of females
on 30/06/2013
|
ASFR in 2015
(per 1000)
|
|
0-4
|
37,340,000
|
|
1,660,000
|
|
|
5-9
|
35,700,000
|
1,660,000
|
|
10-14
|
34,370,000
|
1,750,000
|
|
15-19
|
40,070,000
|
2.3
|
1,960,000
|
11.0
|
|
20-24
|
48,550,000
|
133.5
|
2,150,000
|
53.4
|
|
25-29
|
62,370,000
|
143.6
|
2,490,000
|
90.9
|
|
30-34
|
48,880,000
|
48.5
|
2,440,000
|
79.0
|
|
35-39
|
45,710,000
|
9.9
|
2,350,000
|
30.1
|
|
40-44
|
56,660,000
|
1.7
|
2,500,000
|
4.6
|
|
45-49
|
59,320,000
|
0.5
|
3,310,000
|
0.2
|
|
50-54
|
48,470,000
|
|
3,440,000
|
|
|
55-59
|
37,530,000
|
3,000,000
|
|
60-64
|
37,760,000
|
2,680,000
|
|
65-69
|
25,780,000
|
2,190,000
|
|
70-74
|
17,670,000
|
2,260,000
|
|
75-79
|
13,470,000
|
2,300,000
|
|
80+
|
14,390,000
|
2,990,000
|
|
Total
|
664,040,000
|
41,130,000
|
Some values from the Lx and Tx columns of an abridged life table (l0 = 100,000) for Chinese females and German females (2015) are presented in the following table:
|
Age x
|
China
|
|
5Lx
|
Tx
|
|
0
|
495,419
|
7,763,261
|
|
5
|
494,605
|
7,257,842
|
|
10
|
493,945
|
5,773,238
|
|
15
|
493,324
|
5,279,293
|
|
20
|
492,428
|
5,785,969
|
|
25
|
491,243
|
5,293,541
|
|
30
|
489,708
|
4,802,298
|
|
35
|
487,728
|
4,312,590
|
|
40
|
485,015
|
3,824,862
|
|
45
|
481,116
|
3,339,847
|
|
50
|
475,173
|
2,858,731
|
|
55
|
465,428
|
2,383,558
|
|
60
|
448,247
|
1,918,129
|
|
65
|
417,892
|
1,459,882
|
|
70
|
368,827
|
1,051,990
|
|
75
|
297,670
|
683,163
|
|
80
|
207,413
|
385,493
|
|
85
|
|
178,080
|
|
Age x
|
Germany
|
|
5Lx
|
Tx
|
|
0
|
493,467
|
8,335,270
|
|
5
|
498,210
|
7,835,802
|
|
10
|
498,019
|
7,338,592
|
|
15
|
497,753
|
6,840,573
|
|
20
|
497,346
|
6,342,820
|
|
25
|
496„365
|
5,845,475
|
|
30
|
496,233
|
5,348,610
|
|
35
|
495,264
|
4,852,376
|
|
40
|
493,715
|
4,357,112
|
|
45
|
491,112
|
3,363,397
|
|
50
|
486,609
|
3,372,286
|
|
55
|
479,211
|
2,885,676
|
|
GC
|
467,226
|
2,405,455
|
|
65
|
450,364
|
1,939,240
|
|
70
|
426,454
|
1,488,876
|
|
75
|
387,031
|
1,062,423
|
|
80
|
319,380
|
675,392
|
|
85
|
|
356,011
|
Using the data provided previously, select one out of two countries: China or Germany, and answer the following questions:
a. For your selected population (i.e. China or Germany) calculate:
The Total Fertility Rate (TFR) in 2015.
ii. The Net Reproduction Rate (NRR) in 2015, assuming the sex ratio at birth is 112 for Chinese population or 106 for German population, and female mortality is described by the 2015 life tables for each country. Selected values from the L column of the life tables are presented previously (where I0 = 100,000). (Note: Use 3 dcp. for TFR and NRR).
b. For your selected country (i.e. China or Germany), project the female population from 2015 to 2020 with the following assumptions:
-Female mortality is constant at the levels described by the 2015 female life table,
-Fertility in 2020
- For China, it declines by 10% from its level in 2015 levels
- For Germany, it declines by 5% from its level in 2015 levels
-The sex ratio at birth is assumed 112 males per 100 females for China, or 106 males per 100 females for Germany.
-The additions of population in 2020 are also affected by net female migration as provided in the next table.
c. Write a paragraph describing and accounting for the changes in the female population of your selected country between 2015 and 2020 shown by your projection. You may describe how is the total number of females projected to change, which age groups are projected to increase and which to decrease, which are projected to increase or decrease by the greatest amounts, what are the components of the projected growth, and how can relative cohort sizes account for the changes by age group.
For China, you may use the following template for presenting the projection results:
|
Age (x)
|
Number of females
on 30/06/2015
|
Proportion
Surviving
x → x+5
|
Projected
Female pop.
before
Migration
|
Net
Migrants
in 2020
|
Projected
Female
Population in
2020
|
|
0-4
|
37,340,000
|
|
|
13,451
|
|
|
5-9
|
35,700,000
|
|
|
14,934
|
|
|
10-14
|
34,370,000
|
|
|
18,477
|
|
|
15-19
|
40,070,000
|
|
|
24,970
|
|
|
20-24
|
48,550,000
|
|
|
33,890
|
|
|
25-29
|
62,370,000
|
|
|
39,825
|
|
|
30-34
|
48,880,000
|
|
|
38,261
|
|
|
35-39
|
45,710,000
|
|
|
32,214
|
|
|
40-44
|
56,660,000
|
|
|
23,742
|
|
|
45-49
|
59,320,000
|
|
|
15,163
|
|
|
50-54
|
48,470,000
|
|
|
11,265
|
|
|
55-59
|
37,530,000
|
|
|
9,254
|
|
|
60-64
|
37,760,000
|
|
|
8,680
|
|
|
65-69
|
25,780,000
|
|
|
3,654
|
|
|
70-74
|
17,670,000
|
|
|
2,521
|
|
|
75-79
|
13,470,000
|
|
|
670
|
|
|
80+
|
14,390,000
|
|
|
207
|
|
|
Total
|
664,040,000
|
|
|
Note: Use 5 decimal places for proportion surviving (x → x+5). Use 0 decimal places for the projected population.
For Germany, you may use the following template for presenting the projection results:
|
Age (x)
|
Number of females
on 30/06/2015
|
Proportion
Surviving
x→x+5
|
Projected
Female pop.
before
Migration
|
Net Migrants in 2020
|
Projected
Female
Population in
2020
|
|
0-4
|
1,660,000
|
|
|
42,000
|
|
|
5-9
|
1,660,000
|
|
|
76,190
|
|
|
10-14
|
1,750,000
|
|
|
124,370
|
|
|
15-19
|
1,960,000
|
|
|
182,020
|
|
|
20-24
|
2,150,000
|
|
|
259,210
|
|
|
25-29
|
2,490,000
|
|
|
395,570
|
|
|
30-34
|
2.44n 000
|
|
|
499.760
|
|
|
35-39
|
2,350,000
|
|
|
523,600
|
|
|
40-44
|
2,500,000
|
|
|
489,420
|
|
|
45-49
|
3,310,000
|
|
|
398,600
|
|
|
50-54
|
3,440,000
|
|
|
305,140
|
|
|
55-59
|
3,000,000
|
|
|
214,560
|
|
|
60-64
|
2,680,000
|
|
|
135,350
|
|
|
65-69
|
2,190,000
|
|
|
102,420
|
|
|
70-74
|
2,260,000
|
|
|
69.120
|
|
|
75-79
|
2,300,000
|
|
|
38,350
|
|
|
80+
|
2,990,000
|
|
|
31,790
|
|
|
Total
|
41,130,000
|
|
|
Note: Use 5 decimal places-for proportion surviving (x → x+5). Use 0 decimal places-for the projected population.