COVENANT UNIVERSITYDEPT. OF ECONS & DEV. STUDIES

DEMOGRAPHIC DATA EVALUATION

ASSESSMENT OF DEMOGRAPHIC DATA

Lecturer: Miss Adetoro Gbemisola W.

IntroductionData evaluation is the assessment of the quality of the data. In evaluating the data, sometimes it is adjusted in order to ensure that it is of an acceptable standard. The adjustment is done on the basis of the responses to the following questions, which were asked during the census:

Sex of members of household

Age (in completed years) of members of household

Residential status of household

Children still living (with household or elsewhere), and

Children dead

Concepts and Definitions

Census of Population: Complete enumeration of persons during a specified period in a demarcated geographical area.

Content Error: Mistake made in the recorded information in the census questionnaire either by the respondent or by the interviewer.

Coverage Error: Under or over-enumeration in a population census due to either omission or duplication.

De facto Population: This refers to the usual household members present and visitors who spent the census night at any given household. This however excludes:

(a) Foreign diplomatic personnel accredited to Nigeria; and

(b) Nigerian nationals accredited to foreign embassies and their family members who live with them abroad and , Nigerian migrant workers and students in foreign countries who were not in the country at the time of the census.

De jure Population: This refers to usual household members present and usual household members temporarily absent at the time of the census. These include institutional populations in places such as hospitals/health centers, prisons and academic institutions (universities, colleges, boarding schools).

Thus, the de facto and the de jure population can be diagrammatically represented as follows:

Child-Woman Ratio: Number of children age 0-4 years in a population to every 1000 women age 15-49 years in the same population.

Dependency Ratio: Ratio of children age 0-14 and persons age 65 years and older, per 100 persons in the age-group 15-64 years old.

Digit Preference: Reporting of age by respondents often ending in certain preferred digits. This results in heaping of population in ages ending with certain digits.

Evaluation of Census Data: Measurement of the quality of Census data.

Sex Ratio: Number of males per 100 females in a population.

Type of Population used in Evaluating the Coverage and Content Errors

In the analysis of the coverage and content errors, the de facto population has been used. This is so because we would like to analyse the information obtained from the people who gave us their details and not those we did not talk to or collect the information from.

Methods of Evaluation

During enumeration, checks and controls are instituted to minimize errors in the census. Despite instituting data control measures, there are usually several errors in the census data.

For instance, some people may be completely omitted, others may be enumerated more than once, or some characteristics of an individual such as age, sex, fertility and economic activity of the canvassed individual may be incorrectly reported or tabulated. In general, two approaches are used to evaluate the quality of data, direct and indirect methods.

The direct method basically involves the carrying out of what is referred to as a Post Enumeration Survey (PES). In a PES, a sample of households is revisited after the census and data are again collected but on a smaller scale and later compared with that collected during the actual census. The matching process of the two sets of data can then be used to evaluate the quality of the census data.

Indirect methods usually employ the comparison of data using both internal and external consistency checks. Internal consistency checks compare relationships of data within the same census data, whereas external consistency checks compare census data with data generated from other sources. For instance, one can compare data on education obtained during a census with administrative data maintained by the Ministry of Education.

Detection of Errors in Age DataDemographic data are usually classified by age and sex. Despite

this importance; a variety of irregularities and misstatements have been noted with respect to age-related data. These irregularities must be detected, adjusted or corrected before demographic data could be used for any meaningful analysis.

Common Errors in Age DataDigital preference or aversion

Deliberate misstatement

Ignorance of correct age

Some Indices of Detection of Errors in Age Data• Whipple’s Index

• Myer’s Blended Index

• Un Age-sex Accuracy Index

• Carriag-farrag Index

WHIPPLE’S INDEX

• Essentially designed to detect concentration or heaping in terminal digits 0 and 5

• Applicable when ages are reported in single years

• Designed over the range 23-62 inclusive

• Assumptions of rectangularity (ages are evenly distributed )

Assumption of Rectangularity

• For example, employing again the assumption of rectangularity in a 10-year range, we may measure heaping on terminal digit “0” in the range 23 to 62 very roughly by comparing the sum of the populations at the ages ending in “0” in this range with one-tenth of the total population in the range:

• Similarly, employing either the assumption of rectangularity or of linearity in a 5-year range, we may measure heaping on multiples of five (terminal digits “0” and “5” combined) in the range 23 to 62 by comparing the sum of the populations at the ages in this range ending in “0” or “5” and one-fifth of the total population in the range:

Steps in Computing Whipple’s Index

Terminal digits ‘0’ and ‘5’

Step1: Add all ages ending in terminal digits 0 and 5 over the range 23-62 (Numerator)

(P25+P30+P35+P40+…+P60)

Step2 : Add population in the entire age

range 23-62 inclusive (denominator)

Step 3: Put the sum of the numerator on the one-fifth of the sum of the denominator and express in percentage.

Whipple’s Index (Terminals 0 & 5)

This gives the relative preference for terminal digits ‘0’ and ‘5’

Steps for Terminal Digit ‘0’

Step1: Add all population with ages ending in terminal digits 0 over the range 23-62 (Numerator)

(P30+P40+ 50+P60)

Step2 : Add population in the entire age

range 23-62 inclusive (denominator)

Step 3: Put the sum of the numerator on the one-tenth of the sum of the denominator and express in percentage.

Whipple’s Index (Terminal digit 0)

• This gives the relative preference for terminal digit ‘0’ only

Single Year Age Data

Age Population Age Population Age Population Age Population Age Population

23 151516 32 61964 41 7507 50 9504 59 806

24 152246 33 67462 42 9036 51 4660 60 1352

25 135126 34 35401 43 4208 52 1794 61 468

26 117309 35 40350 44 6890 53 2357 62 958

27 134419 36 31804 45 3472 54 2041 63

28 114918 37 21473 46 4930 55 1892 64

29 89920 38 22659 47 2447 56 693 65

30 74376 39 10185 48 3487 57 1130 66

31 51188 40 15658 49 2860 58 819

Check the Whipple’s Index for:

• Terminal Digits 0 and 5 =100.5

• Terminal Digit 0 only = 72.0

• Terminal Digit 5 only = 129.0

INTERPRETATION OF WHIPPLE’S INDEX

• Whipple’s index varies from 0 to 500.

• Index=0 digits ‘0’ and ‘5’ are not reported,

• Index =100 no preference for ‘0’ or ‘5’,

• Index=500 only the digits ‘0’ and ‘5’ are reported in the age data.

• Index<105 highly accurate age data

• Index 105-109.9 = fairly accurate

• Index 110-124.9= approximate

• Index=125-174.5 Rough

• Index>=175 very Rough Age Data

MYERS BLENDED INDEX

• Designed for evaluating single - year age – sex data.

• It can give the extent of digit preference for all the digits 0, 1, 2, 3... 9. It can be used to report errors for all ages 10 – 99 years.

• Based on the assumption of rectangularity.

Steps in Computing Myers Index

• Sum all the populations ending in each digit over the whole range i.e. 10 - 99

• Sum figures between ages 20 - 99.

• Multiply the sums in (1) by coefficients; 1, 2, 3,4,5,6,7,8,9 and 10.

• Multiply the sums in (2) by coefficients from 9 descending to 0 i.e. 9 ,8 ,7, 6 , 5 ,4 ,3 ,2 ,1 ,0.

• Add the product of (3) and (4) , to obtain the blended sum

Steps Cont’d

• Add up the blended sum in (5).

• Find the percent (%) of the total blended sum at different digit ends.

• Take the deviations of each % in (7) from 10.0. This result indicates the extent of concentration or avoidance of a particular digit.

• A summary index of preference for all terminal digits is derived as one half of the sum of the deviations from 10.0%, each without regard to signs

Example: Myers Index

DigitSum(10 – 99)

Coefficient Product

Sum(20 – 99)

Coefficient Product Blended

Sum%Dist

DevFrom 10%

0 18242207 1 18242201 14867241 9 133805169 152047370 30.69 20.69

1 3388656 2 6777312 1878533 8 15028264 21805576 4.4 - 5.6

2 5649259 3 16947777 3008239 7 21057673 38005450 7.67 - 2.33

3 3691276 4 14765104 1833977 6 11003862 25768966 5.20 - 4.8

4 3236865 5 16184325 1471586 5 7357930 23542255 4.75 - 5.25

5 11352382 6 68114292 8728659 4 34914636 103028928 20.79 10.79

6 3391820 7 23673440 1731508 3 5194524 28867964 5.83 - 4.17

7 3372952 8 26983616 1915205 2 3830410 30814026 6.22 - 3.78

8 5063911 9 45575199 2611985 1 2611985 48187184 9.72 - 0.28

9 2343462 10 23434620 1191482 0 0 23434620 4.73 - 5.27

INTERPRETATION• If the sum at any given digit exceeds 10% of the

total blended population, it indicates over selection of ages ending in that digit (i.e. digit preference).

• On the other hand, a negative deviation or sum that is less than 10% of the total blended population indicates an under selection of the ages ending in that digit (i.e. digit avoidances).

• If age heaping is non-existent, the index would be approximately zero.

• Theoretically Myers index can vary from 0 to 180. If ages are reported accurately, all “blended” sums are very nearly equal and deviations from 10 percent are negligible, resulting in an index of almost zero. If all ages were reported with the same terminal digit (for example digit 0), then 100 per cent of the “blended” total would be at this digit; the absolute sum of deviations from 10 percent would then amount to 180.

• In the present example, they are markedly unequal and, by adding together irrespective of sign, the deviations from 10 percent of the grand total an index of 62.96 was obtained.

UN AGE –SEX ACCURACY INDEX

• This method consists essentially in the computation of sex-ratios and age –ratios for five-years groups of ages, up to age 70. in the case of sex- ratios, successive differences between one age group and the next are noted, and their average is taken, irrespective of sign. In the case of age-ratios, for either sex, deviations from 100 are noted and averaged irrespective of sign. Three times the average of sex-ratio differences is then added to the two averages of deviations of age ratios from 100, to compute the index.

AGE ACCURACY INDEX

In the absence of extreme fluctuations in the past vital events, the age ratios for all age groups should be about equal to 100. The sum of the deviations from 100 of the age ratios for males divided by number of age groups gives the mean deviation for males and the same procedure also gives the mean deviation for females.

The average of the mean deviations of males and females is a measure of the overall accuracy of the age data, i.e., age accuracy index.

UN AGE-SEX ACCURACY INDEX• This index which was proposed by the United Nation is used for the

evaluation of five-years age-sex data. The index is also referred to as Joint Score. It has three components;

COMPONENT (1)

• This score is obtained by first calculating the sex ratio at each age group. Successive differences irrespective of sign are added and averaged.

• Age – specific sex ratio = 5Pxm X 100

5PXf

• 5Pxm =males aged x to x + 5

• 5Pxf = females aged x to x + 5

COMPONENT 2

Average male age ratio

• For each age group for males, calculate the age ratios computed as

• Age ratio = 5Px X 100

½ (5Px – 5 + 5Px + 5)

• The deviations from unity irrespective of sign are added and averaged (M).

• NOTE THE AGE RATIO FORMULA HERE!

COMPONENT 3

Average female age ratio score (F)

• For each age group for females, the age ratios are calculated using the same formulae as for males. The deviations from unity irrespective of sign are added and averaged (F).

• The index is then computed as:

UN INDEX = 3(S) + average male age ratio + Average Female Age Ratio.

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Age-Sex Data 1991 Census Nigeria

Age Group

Male Population

FemalePopulation

0 - 4 7344454 6999435

5 – 9 7374314 7126144

10 – 14 5812538 5336143

15 – 19 4528811 4806977

20 – 24 3314303 4357267

25 – 29 3304739 4006932

30 - 34 2808629 3105298

35 – 39 2206871 2008062

40 – 44 1971197 1874721

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Age-Sex Data 1991 Census Nigeria

Age Group

Male Population

FemalePopulation

45 – 49 1355101 1061602

50 – 54 1388650 1182149

55 – 59 638375 481394

60 – 64 898801 791573

65 – 69 406540 357400

70 – 74 492186 394116

75 – 79 195455 156368

80+ 488644 41703133

UN AGE-SEX ACCURACY INDEX NIGERIA 1991

AgeGroup

MalePopulation

FemalePopulation

SexRatio

Successive difference

Male Age Ratio

Dev from 100

Female Age Ratio

Dev from 100

0 - 4 7344454 6999435 104.93 - - - - -

5 - 9 7374314 7126144 103.48 1.45 112.10 12.1 115.54 15.54

10 - 14 5812538 5336143 108.93 - 5.45 97.66 - 2.34 89.43 - 10.57

15 - 19 4528811 4806977 94.21 14.72 99.24 - 0.76 99.18 - 0.82

20 - 24 3314303 4357267 76.06 18.15 84.62 - 15.38 98.87 - 1.13

25 - 29 3304739 4006932 82.48 - 6.42 107.95 7.95 107.39 7.39

30 - 34 2808629 3105298 90.45 - 7.97 101.92 1.92 103.25 3.25

35 - 39 2206871 2008062 109.90 -19.45 92.34 - 7.66 80.65 - 19.35

40 - 44 1971197 1874721 105.15 4.75 110.68 10.68 122.14 22.14

45 - 49 1355101 1061602 127.65 - 22.5 80.66 - 19.34 69.46 - 30.54 34

UN AGE-SEX ACCURACY INDEX NIGERIA 1991

AgeGroup

MalePopulation

FemalePopulation

SexRatio

FirstDifference

Male Age Ratio

Dev from 100

Female Age Ratio

Dev from 100

50 - 54 1388650 1182149 117.47 10.18 139.32 39.32 153.23 53.23

55 - 59 638375 481394 132.61 -15.14 55.82 - 44.18 48.78 - 51.22

60 - 64 898801 791573 113.55 19.06 172.03 72.03 188.74 88.74

65 - 69 406540 357400 113.75 - 0.20 58.45 - 41.55 60.29 - 39.71

70 - 74 492186 394116 124.88 - - - - -Total (irrespective of sign) 145.44 275.21 343.63

Mean (Total divided by 13) 11.19 21.17 26.43

Index (3 times mean diff. of SR +

MASRm + MASRf)

58.79

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INTERPRETATION

• The reported age-sex data for a given population is presumed to be accurate if the age-sex accuracy index is between 0 and 19.9, inaccurate if the index is between 20 and 39.9, and highly inaccurate if the index is above 40.

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References

• Demographic Methods and Concepts by Donald T. Rowland.

• Methods and Materials of Demography by Shryock and Siegel

• UN Manuals IV by the United Nations.

• Population Handbook (PRB) published by Arthur Haupt and Thomas T. Kane (2004). Population Reference Bureau’s, 5th Edition, Washington D.C.

• Essentials of Demographic Analysis for West Africa by G.M. Kpedekpo.

• Techniques of Population Analysis by D. W. Baclays

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