- Email: [email protected]
Constructing housing condition indicator
CONSTRUCTING
HOUSING
CONDITION
INDICATORS
MOSHEHARTMAN
Department of Sociology,
Tel Aviv University, (Received 6 September
Ramat
Aviv, Tel Aviv, Israel
1973)
Two methods are suggested for constructing housing condition indicators in surveys and censuses. The Guttman scale is suggested for combining the different housing condition variables in a survey. A facet design is suggested for constructing questionnaires that have the purpose of measuring the level of housing conditions. Data from Israel’s 1961 census is used to exemplify the use of the two methods.
INTRODUCTION In censuses, housing condition studies and other survevs, various data are collected regarding housing conditions of households, such as: the quality of facilities in the apartment, the size of the apartment, the living density, etc. One of the aims of collecting such data is to enable ranking of households according to their housing standards. In order to obtain a system for ranking households which will utilize a series of various details regarding housing, a method must be found to compute a general housing standard score for each household based upon all the characteristics of the household. Although the researcher generally faces the problem of formulating an index w&h the aid of a list of researched data, it is evident that the following preliminary problem should arise when constructing the questionnaire for the survey or census, namely, how to define the housing characteristics to be studied w&h will make possible the ranking of households. This work deals with the two above-mentioned problems, that is: (a) the ranking of households according to housing standard with the aid of a given list of items;(b) Pn approach to building a questionnaire concerning housing conditions (or that part of the questionnaire dealing with housing conditions), which would enable the formation of an integrated index for scoring the researched units. 1. THE CUTTMAN SCALE FOR RANKING HOL’SEHOLDS OR APARTMENTS* ACCORDING THEIR STANDARD OF FACILITIES
TO
The accepted method of describing the housing conditions of the population is to calculate the proportion of families possessing a particular facility. Sometimes a number of variables are combined, such as the division of Families according to housing density and the * “Apartment’‘-a resides. t For a description
housing
unit in which
quality of facilities in the apartment. This method indeed describes various aspects of household housing conditions, but in order to obtain a general ranking of families according to their housing standard and to analyze the factors related to housing variables, one must sum up the individual housing variables of each family. The importance of the ranking is threefold: (a) Clear information is acquired concerning the distribution of families according to their housing standard. (b) It is possible to measure the relationships between the housing standards and other variables. (c) It makes it possible to compare housing conditions of various populations, and the same population at various times. The ranking system presented below has been constructed with the aid of the Guttman Scale.? The scale was composed with the aid of the variables concerning facilities in the apartment: the existence of a bathtub, the method of water heating in the bathroom, the existence of a W.C. and a flushing device, the existence of a kitchen and the means for food refrigeration, The source of the data used to construct the index is the 1961 Population and housing census in Israel. All data presented below are based upon a sample of 20 per cent of the country’s households (about 107,000 households were included in the sample). This sample represents the popuiation of Israel, except for those residing in institutions and ~~~~~~r~~~~~ and the nomad Bedouin tribes. The latter have not been included due to their special housing conditions, which differ from those of the rest of the country’s residents. In the above-mentioned census, data on housing density, number of rooms in the apartment, and the existence and quality of the various facilities, were collected for each household. Stages
one household
in the preparation
of the ~a~lk~~zg sq?sterns
For the purpose of composing the above-mentioned variables
of the system. see [I]. 155
the grading scale, all were crossclassified.
156
M. HARTMAN
Each cell in the resulting table included those households which were equivalent from the standpoint of the various housing variables. Each cell in the table is defined by a combination of the categories of all the variables employed. Each combination of categories of all the variables will be hereinafter referred to as a ‘profile’. The ranking of households or apartments is in effect an ordering of the various profiles obtained. Out of over 10,000 possible profiles, 70 per cent of households were concentrated among 224 profiles, 25.5 per cent of households were distributed among the rest of the profiles, and 4.5 per cent of households could not be classified into any of the profiles, because at least one of the items had not been recorded. In the first stage an attempt was made to rank the 224 profiles with the aid of the Guttman Scale, but it was discovered that they do not form a scale. A thorough examination of the data showed that the variables ‘apartment size’ and ‘housing density’ confounded the scale formed by the other variables, and hence these were not included in the subsequent classification. The other variables defined a narrower universe of ‘content’ that is ‘the level of facilities in the apartment’ instead of ‘the general level of housing’. These remaining variables are presented in Appendix 1. This narrowing of the number of variables substantially cut down the number of profiles, so that 91 per cent of the households were included in 52 profiles (see Table I), each of which includes 200 families. The remaining profiles formed a ‘Quasi-Scale’, including 15 ranking groups (scores). In the lowest rank, the ‘0’ group, those households have been included which lacked any facilities at all. In the highest rank, the ‘14’ group, those households have been included which had all facilities, including an electric refrigerator and high-standard bath water heating, such as electricity or central/apartment heating (see Table 1). The 15 profiles out of the 52 form a full scale. Sixty-seven per cent of the households are included in these profiles (see Table 2). In the final scale we have added to each of the ‘ideal’ profiles the closer profiles from the ‘Quasi-Scale’. It must be stressed that no significance should be attached to the numerical value of the score, except for marking the profile’s pkice in the ranking. Neither are we able to know anything about the distances between one score and another. The ranking of apartments by the general score can
* The reproduction coefficient measures the extent of proximity of the ‘Quasi-Scale’ to the full scale. It decreases when the deviating profiles increase and when the number of cases included in deviating profiles is large, see [l]. t Except for the deviating profiles. J The purpose of this section is to show a few examples of use of the ranking obtained. Analysis of results of the census in this topic are presented in the introductions of the respective census publications.
be done at three levels of detail, with the most detailed one containing 15 scores (see Table 2). In the more general ranking the following types of apartments were defined:. (a) Apartments with profiles of a low standard of facilities including mainly apartments with a W.C. and no kitchen-about 6 per cent of the total of apartments. (Scores: c-3 in the detailed grading). (b) Apartments with a kitchen and a refrigerator as well. (Scores: 4-8). (c) Apartments with all of the above and a bath as well, but no water heating facility in the bath. (Scores: 9-10). (d) Finally, those apartments having all facilities and the best water heating facility. (Scores: 11-14). Description of the scale obtained. The ‘Quasi-Scale’ obtained has a reproduction coefficient* of 0.92. It should be remembered that if we took into account the low frequency profiles (under 200 cases), we would obtain a lower reproduction level. But we may assume that the deviating profiles are errors in replies or other census errors. An additional criterion for the degree of proximity to a full scale is the percentage of apartments included in the profiles from the full scale out of the total number of apartments whose profiles are in the ‘QuasiScale’-this in our case is 73.6 per cent. (The percentage of apartments in the full scale out of the total number of apartments in Israel reaches 67.2 per cent.) The two indicators of the quality of the scale show that the scale obtained is close enough to the full scale so as to enable its efficient usage. The scores obtained have a clear meaning:t each score denotes, for the majority of the population with that score, the facilities existing in its apartment (from among the six variables included in the scale). For example: the score 6 for an apartment means that it has a W.C. with a flushing device and a kitchen with an ice-box, but it lacks either a bath or a shower, and a water-heater in the bath or shower; an apartment with the score of 12 has all six facilities included in the scale, and the water heating method in the bath is an electric boiler. The scoring of families with the aid of the scale makes it possible to analyze the differential housing conditions of various segments of the population, such as differences between urban and rural populations, differences between veteran families and new immigrants, etc. Several such examples from the Israeli data will be presented below. $ (a) D@rences between rural and urban settlements. A clear picture emerges regarding the differences in the standard of facilities among households in urban and rural settlements. In the rural settlements the standard of facilities is lower than in the urban settlements. It may be shown that this stems from the fact that the majority of the rural populations is non-Jewish. The standard of facilities in the non-Jewish population is relatively low. Within the Jewish population there exists differences in the standard of facilities of
ConstrLicting Table
Rank score
I. Distribution
No. of families
of households
1* 2 2 2* 3% 4 4*
5 5* 6 6. 6*
8 8 8* 9 9 9 9 9 9* 10 10 10 10 10 10 10 10* 11 11 11* 12 12* 13 13* 14* Total
14,555 880 3600 925 4325 3065 5390 3290 1750 7460 1300 3535 1965 1110 2840 2620 I170 6730 1315 7820 1355 4180 535 1060 5385 2680 3510 1065 29,965 4520 1615 1625 6870 4520 2060 3850 4205
W.C.
X
x x
X X
x
x
3
x x x x x X
x X X
x
X X
X
X
X
X
X
X
x x
x x
X
X
X
x x x x x x
X
X X
X
x
x x x
X
X
X
x x x
X
X
X X
x
x
x X
x
x
x X
x X
X
X
X
X
X
X
x x x x x x x x x x
x X
x X
X
X
x X
X
X
X
x X
X
X
X
X
x x x x
X
x
x
X
X
X
x
X
X
x X
x
x
X
X
X
X
x
X
X
X
x
X
X
x
x
X X
x
X
x
X
x
x
x
x x x
X
x
X
x x
X
X
x
x
X
x
X
x
X
x x
x x x
X
x
x
x
x
x x
X
x
x
x x
x x x
X X
x
x
x x
x x
x
X
X
X
X
x
X
012345
X
X
x x
X
x x x x x x
012
X
X
x
x
X X
x x x x
x
X
X
x x
X
x
X
X
X
X
x
x
X
X
x
x X
X X
X
x X
x
x
Water heater
Bath
x x x x x x x x x x x
X
x
X
012
x
x x
x
Refrigerator
X
X
I(
X
157
indicators
in Israel (1961) by profiles of level of facilities ‘quasi-scale‘?
x x x x x
1XhO 3505 4185 975 6480 3970 24,370 2870 28,895 37,270 2705 191.825 660 15,470 10.965 487.64%
condition
The facility: Flushing device Kitchen Category1 0 I 012
012
o*
housing
X X
X
X
x x
x x
x x X X
x x
x X
x
x X
x X
x x
* These profiles are part of the full scale (see Table 2). t See definition Cl]. $ See definition in Appendix 1. Q Includes about 90% of households as profiles having less than 200 cases were not included. Source: Population Census of Israel 1961. Central Bureau of Statistics, unpublished data, Israel. 20% of households.
x
Data
on a sample
of
158
M. HARTMAN
urban and rural settlements, but these are much smaller than the differences within the non-Jewish population (see Table 3). (b) Continent of birth und length of’ residence in Israel. Differences may be seen among standards of facilities of households from different countries of origin, 48 per cent of households in which the father was born in Africa possess facilities of high standard, as against 87 per cent of households of natives of EuropeAmerica or 74.6 per cent from among native Israelis (see Table 4). It also appears that within the immigrant groups of both major continental origins-Asia-Africa and Europe-America-there are differences which are related to length of residence in the country. Those who have been in the country for a longer period of time have Table 2. Distribution
Rank score
of households
W.C. 0 1 2
2, of households
up the housing conditions from point of view of services and density, the population may be ranked as follows: Highest: high facilities-low housing density
in Israel (1961) by the profiles
No. of families
0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 Total households
a higher standard than the newer households (see Table 5). (c) Relarion to housing density. The obtained scale does not include all housing variables. The ranking forms one variable describing only the standard of the facilities. The possibility exists of comparing this ranking with the other housing variables, so that a general picture of housing standards may be obtained. A crossclassification of this ranking with housing density shows the relation which exists between the two variables. In general, apartments with high facilities have low housing density, and vice versa. So as to sum
14.555 3600 3065 3290 7460 2620 7820 2680 29,965 3850 24,370 37,270 191,825 15.470 10,965 in full scale 358,805 in full scale 67.27;
The facilities? Flushing device Kitchen Categories? 0 1 0 1 2 Profiles x X x x x x
x X x x x x
3 6 7 7 9 9 9 10 10 10 10 11
0 12
012
012345
x x x
x x x x x x x
x x x x x x x x x
x x ‘X
x x x x x
x x x x x x x x
X
x x x
profiles
Water heater
Bath
Refrigerator
of full scale x X x x X X
x x x x x
. Main deviating
Included
in the full scale* and some of the deviating
profiles
in: 5390 6730 4180 5385 4520 6870 4520 4205 4185 6480 3970 28,895
* For definition see [l]. t For definition see Appendix 1. Source: Population Census of Israel 20% of households.
x x
x x x x x x x x x x x x
1961, Central
X
x x
x
x x
x x x x x x x x x
X
x x x x x x x
Bureau
of Statistics,
x
x
X
x
x x x
x x x x
x
x
x
x x
x x x
x x x x x x
unpublished
x x x x x
x
x
x x
data,
Israel.
x
Data
on a sample
of
ConstrLlcting Table 3. Households
housing
condition
indicators
159
in Israel (1961) by level of facilities, type of locality and Jewish households
Level of facilities*
Jewish households
All households
Rank scores
Urban
Total no. of households
RLlral 79,230
485,145 100.0
o-1
2.5 10.0 12.5 75.0
4-8 9-10 I l--14
for total population
1OO.Q 34.6 22.3 9.5 33.6
Urban
Rural
495.010
49.040
100.0
100.0
1.6 9.2 12.7 76.5
5.0 27.4 15.1 52.5
* By rank score on the scale (see definition of the four cstcgories in text). Source: Population Census of Israel 1961, Central Bureau of Statistics. Israel. Data on a sample of 20% of households.
Table 4. Jewish
households
in Israel (1961) by level of facilities, by continent of residence in Israel Household
Level of facility Rank scores*
Household head born in Israel
No. of households in thousands
Low (O-8) Medium (9-10) High (1 l-14) * See definitions
Total
head born in Asia or Africa Immigrated Immigrated 19481961 before 1948
of birth
Total
unpublished
data,
of head of household
and length
Household head born in Europe or the Americas Immigrated Immigrated before 1948 1948 1961
46.5
160.8
26.4
134.4
2X7.8
138.6
169.2
100.0
100.0
100.0
100.0
100.0
IOO.0
loo.0
8.6
27.4
21.0
28.1
5.8
2.4
9.0
1.1
24.7
16.6
26.3
7.4
3.6
IO.5
74.6
48.0
62.3
45.0
87.0
94.0
x0.5
in text.
Source: Population Census of Israel 1961, Centrai Bureau of Statistics.
trnpublishcd
data.
Israel.
Data
on a sample
of
207: of households.
Medium: high faG~litie~high housing density Low: low facilities-high housing density (see Table 6). Table 5. Households in Israel (1961) by level of facilities and housing
density
Level of facilities in rank scores
High*
Density Low*
Total*
100.0
100.0
O-10 11-14
52.0 48.0
15.4 84.6
* Total number of households 537.4 thousand. Number of households with high density (that is. two or more persons per room) was 308.1 thousand. Source: Population Census of Israel 1961, Central Bureau of Statistics, unpublished data, Israel. Data on a sample of 20% of households.
Along with these advantages one must note the following disadvantages of the resultant ranking. (a) 7-k un~iahles irduded in the SC&. As explained above, the scale includes only variables describing the ‘facilities in the apartment’, and hence we obtained the ranking according to ‘standard of facilities in the apartment’ instead of the general ‘housing standard’. It should be especially noted that housing density and apartment size are not included in the scale of variables. Housing density is considered to be one of the important indicators of housing conditions: still, no way has been found to include it in the scale formed by the other variables and therefore in actual practice one must employ the two indicators for housing standard: the facility scale score and the density rate (see above for the relation between the two). (lo) The profiles which de~iutr,fiom the,fidl scrrk. The scale which has been formed is based upon approxi-
160
M.
HARTMAN
mately 67 per cent of the households which formed a full scale, as explained above; the rest of the households deviated somewhat from this scale. Analysis of the deviations shows that they stem from four principal reasons. (1) There is a certain interchange between an electric refrigerator and an electric boiler; there are families which purchase the first before the second, and vice versa. As a result, the score 11 includes the two kinds (see Table 1). From the scale’s point of view, one of the profiles ‘deviates’, but from the point of view of facility standard there is no real difference between the two. (2) A second reason for deviations is the difference made between ‘bath for use with others’ and ‘bath for family’s use only’. This difference gives us an additional rank in the scale (score 7), but causes the inclusion of a large number of households as having a profile which ‘deviates’ from the full scale. (3) The difference between ‘no refrigerator’ and ‘icebox exists’ causes additional deviations. Combination of the proper categories-‘ice-box’ with ‘no refrigerator’ and ‘bath for use with others’ with ‘bath for family’s use only’ yields a ranking of 13 scores only, and the percentage of deviations from a full scale is decreased from 33 to 30 per cent. (4) Analysis of errors in answers in the census regarding the housing questions showed that in the question about the type of heating in the bath, ‘oil, wood, etc.’ and ‘other water heating arrangement’ has no meaning (see Central Bureau of Statistics of Israel, 1969). It may be better to combine these two categories in the scale as well, and thus the number of deviations will decrease. (c) Asymmetric distribution of the population by the scale. Another problem stemming from the nature of the variables included in the scale is related to the distribution of the population by the scores. It appears that the variables from which data were recorded in the census (by which the scale was constructed) bring about a detailed ranking of the low types of housing conditions, and do not differentiate with adequate detail the medium and high ranks. In the accumulated frequency of the number of families according to the various ranks in the scale. the ‘jump’ from score 11 to score 12 is apparent (Fig. I). In order to arrive at a more symmetric division, we must strive to form intermediate scores between these two grades. A method for finding variables which would yield suitable division points is presented in Part 2 of this article. Comparison with other methods for ranking households according to housing conditions A possible method of reaching a compound variable which would rank households by their standard of facilities, is to give a weight to each factor or facility, and to sum up in each household the total weights of all facilities existing in the apartment. The advantage of such a system is that it gives quantitative values to the family’s housing standard, and
Rank
score of level of facilities
Fig. 1. Distribution of households in Israel (1961) (based on data presented in Table 2) included in the full scale by the rank score of level of facilities (accumulating percentages). thus makes it possible, in addition to the ranking of families, to also measure the distances between the various groups. This is especially important when we wish to compare the housing standard at various periods of time (when asking, for example, how have the housing conditions of a certain population improved). The disadvantages of this method (and the reasons for preferring the method which yields an ordinal ranking only) are : (a) There is no accepted method of establishing the weights-not only the absolute weight of the various facilities, but even their relative weight. Every weight system would have the disadvantage of its being arbitrary, and there is no way of examining objectively if the weights express the true ‘value’ of the various facilities. (b) Even should we succeed in forming a system of weights for a number of variables, there is an additional disadvantage: there is no way of adding variables to that system without changing all the existing weights. Therefore, in those cases in which different housing data are available, there will be no possibility of using the same weights. In the scale we formed above, this disadvantage does not exist, since the addition of a variable will not alter the ranking formed by the previous variables. For the same reason we could not by a tieighting method rank the families according to some of the variables (in more limited surveys) and be certain that this ranking would remain the same even if we were to take into account all the housing conditions. These disadvantages apply to every quantitative method requiring weights for the various indices of housing conditions. 2. THE FACETS
OF HOUSING
CONDITiONS
In Part I above. it was found that a scale exists which ranks the population of apartments according to their
Constructing Table 6. Arrangement
housing
of examples
of household
Mobility
Needs
Built in
Shelter Sanitation Eating
Stone building W.C. Kitchen
Body cleanliness
Bathrooms
Clothes’ cleanliness Temperature regulation Privacy
Laundry
Number (4+)
condition
room
of rooms
standard of facilities; this ranking is accomplished with the aid of a number of indicators, i.e. individual ‘facilities’. We found that the standard of facilities in the apartment is determined by the number and quality of facilities out of a limited number of possible facilities which we have surveyed. In this section we shall attempt to analyze the nature of the relationship between the general variable‘standard of facilities’-and the individual facilities in the apartment. The practical purpose of such an analysis is to find a desired method of choosing housing condition indicators in the questionnaires of surveys and censuses. The method For the purpose of this analysis we will employ the concepts of Guttman’s facet analysis [S-S]. Following this approach we assume that the concept of ‘standard of facilities in the apartment’ defines one ‘universe of content’ or a group of variables all of which contribute, one way or another, to the general level of facilities. It is assumed that among the different variables belonging to this group there exists a certain set of relations or a structure. In order to discover the structure of relations among the variables an attempt is made to find abstract concepts through which the variables may be organized or ordered. These different aspects are called facets. Each facet is thus an abstract concept which divides the group of all variables in a certain manner. As an example we shall propose below to subdivide the group of all variables or all facilities in an apartment by the human needs they fulfill. ‘Human needs’ is a more abstract variable, having several categories, such as weather shelter, eating, cleanliness, etc. All facilities may be divided according to the needs they fulfill-those fulfilling the need for food (such as the kitchen, cooking stove, etc) or the need for cleanliness (such as a bath, shower) etc. In search for the structure of the relations among all variables (all facilities), the definition of facets narrows down a large number of variables to a limited number (usually 2-4) of facets which are to be dealt with. The theories regarding the structure of relations among variables
161
indicators facilities within defined facets
of facility Installed Roof Flushing device Wall cupboard in kitchen Bath heating installation Rinsing bowl Air conditioning/ central heating Room separation installations
Appliance Shutters Refrigerator/ cooking oven
Washing Heating
machines device
may be expressed as theories regarding among facets. One of the simple hypotheses regarding the structure of the variables and facets is the hypothesis that the categories of each facet are ordered, and that the order existing in each facet produces at least partial order among the variables. For example, we may assume that the needs fulfilled by the facilities are ordered, so that the eating need is more ‘important’ than the need for cleanliness, the need for cleanliness more important than the need for privacy which the apartment if capable of providing, etc. Each facet is therefore provided with a numerical score which ranks the facet’s categories. Each variable belongs to one of the facet’s categories (every facility fulfills one of the specified ‘needs’) and receives the rank order of that category. That same variable will similarly also receive a rank order regarding the other facets. In accordance with this approach we shall attempt below to relate the group of all facilities in the apartment to the general standard of facilities. The general assumption will be that the relation between each one of the facilities and the general standard of facilities in the apartment is as follows: each facility in the apartment contributes to the general rank of the standard of facilities in the apartment. Each facility may be ‘evaluated’ by several criteria or over a number of ‘facets’; the facility’s combined ‘value’ for all these criteria determines its contribution to the standard of facilities in the apartment. We shall attempt below to arrive at these ‘facets’ (or these evaluation criteria), and to present statistical proof for the resulting rank order. Finally, a number of practical conclusions will be derived, based upon the ordering of the facilities, and their contribution to the standard of facilities in the apartment. The method of examining the ordering of the variables is as follows: (a) A list of facets which are assumed to determine the order of a set of variables is intuitively established. (b) Three requirements are assumed to have been met: (1) a sufficient number of facets were included to explain the order among the variables; (2) each facet
162
M. HARTMAN Table 7. Arrangement
surveyed in census according to facets in the proposed theory
of facilities
Needs
Built in
Sanitation Eating Washing
W.C. Kitchen Bath
Mobility of facility Installation Flushing
of the standard of facilities
device Refrigerator
Heating
has an adequate number of categories; (3) an a priori semantic order was established among the variables according to their ranks on all facets. (c) The correlations among the variables are examined. (d) The order is verified by the fact that the closer two variables are, in the semantic order, the higher the correlation between them. Analysis of facets apartment
Appliance
in the
The assumptions upon which the following analysis is based are: (1) The purpose of the apartment’s facilities is to fulfill a number of the resident’s needs. These needs may be arranged according to their degree of necessity or fundamental importance.* For example, we shall assume that facilities of an apartment should fulfill the residents’ needs of eating and physical cleanliness, and that the eating need is more basic or necessary than cleanliness. ‘Necessity’ here has the following meaning: the requirement that ‘every apartment should enable the residents to prepare their meals within it’ is more acceptable, commonly agreed upon, than the requirement that ‘every apartment must enable the residents to wash themselves’. (2) During the construction of the apartment the order of priorities as to the inclusion of one facility or another is also influenced by the degree of mobility of that facility: at construction time one is more likely to include in the apartment a less mobile facility; e.g. it is not likely that an apartment will be built without a kitchen, with the assumption that it will be added later. At any rate, it is more likely to leave for ‘later’ the addition of warm water installation. The surveyed apartments include in many cases faci-
* The order of necessity of these needs may change from place to place. The need for weather shelter will have a differing importance in different climates (it seems that in Israel, with average weather, this need is less vital regarding heat and cold, and more vital regarding rain shelter). Thus, air conditioning has a low degree of necessity and a high contribution to the standard of facilities. t Home appliances-only home appliances related to the apartment are meant, and not, for example, a camera or a transistor radio. An installation is a facility that is usually related to the apartment, and when moving, it is not usually taken along, while this is not the case regarding home appliances.
lities added after construction.
It may be assumed that the order of addition of the added facilities is influenced to a greater extent by the factors of the facility’s necessity and its cost than by its mobility. The hypothesis about the structure of relationships among all facilities. On the basis of the above mentioned assumptions we propose that each facility’s contribution to the general standard of facilities of an apartment is determined by the facility’s value regarding two criteria or two facets: (a) Necessity (in the above meaning) of the need the facility fulfills. Let us assign the letter x to the facility’s contribution to this facet. (b) Mobility of the facility. Let us assign the letter y to the facility’s contribution to this facet. Each facet, x and y, has categories which may be ordered from the highest to the lowest, so that the order regarding variables may be verified. The orderings within the facets must have a common meaning, and this should also be common to the general variable-inourcase, thestandardoffacilities.Ifwe translate this requirement to our case, the following rules will be obtained. The more basic the need served by the facility, the less the facility contributes to raising the general standard of facilities. The less mobile the facility is, the less it contributes to the apartment’s standard of facilities. Let us define the following categories for each facet: (a) Needs-from more vital to less vital (x may have the value): 1. Shelter 2. Sanitation (W.C.) 3. Eating 4. Cleanliness (body, clothes) 5. Privacy (regarding outside society and among family members). There may exist other ‘needs’ that were not included; about those we assume only that we can always add them and order them with the above, without changing the order of those mentioned: e.g. ‘cleanliness’ may be broken down into body cleanliness (washing) and clothes’ cleanliness (laundry), but this does not upset the order; it only details the above ordering. (b) We assume the following categories regarding mobility-from less mobile to more mobile (y may have the value) facilities: 1. Part of the building 2. An installation installed and adapted to the building 3. Mobile device or home appliances.?
Constructing
housing
Table 8. Intercorrelations*
W.C. W.C. Flushing device Kitchen Refrigerator Bath Bath water heating
Flushing device
Kitchen
0.999
condition among
163
indicators facility variables
Refrigerator
Bath
Bath water heating
0.413
0.437
0.058
0.42
0.423
0.465 0.414
0.042 0.255 0.286 0.391
0.999 0.413 0.437 0.058
0.423 0.465 0.060
0.414 0.453
0.461
0.060 0.453 0.461 -
0.042
0.042
0.255
0.286
0.391
* The correlations were calculated by the formula r = ,/x2/N, that is, ,$ regarding the given table of distributions divided by the number of cases in the table and raised to the power of l/2. Source: Pooulation Census of Israel 1961. Central Bureau of Statistics, unpublished data, Israel. Data on a sample of 20% of households.
As noted above, every possible facility will receive a certain value on each facet; thus we may mark a kitchen by (x(3), y(l)), a bath’s water heating installation by (x(4), y(3)), etc. The requirement for a common meaning of the order within each facet means that in all facets a higher rank shows a higher contribution to the standard facilities. The above hypothesis may be described by Table 6, which clarifies examples of facilities in an apartment according to the facets and the assumed order within each facet. In a similar way we can arrange the variables surveyed in the Population and Housing Census, 1961, in Israel, according to the facets we established (see Table 7). Using the symbols defined above, we may mark all facilities included in the 1961 Census in Israel: W.C. W.C. flushing device Kitchen Refrigerator Bath Water heating facility
x(2), x(2), x(3), x(3), x(4), x(4),
Y(l) Y(3) Y(1) Y(3) Y(l) Y(2).
We shall define a particular order among the above facilities in the following manner. Let us assume that facility a is of a ‘higher’ standard than facility 6, if the indices of facets x, y in facility a are greater or equal, respectively, to the indices of facility b. For example (XV), Y(l) < (x(2), Y(2))
and the order among some facilities is not yet defined such as (x(%0)) 3 (x(3Ml)). The partial order which is formed may be expressed the following diagram: low x(2) 121) (WC.) x(2) ~(2) (flushing device) x(3) y(l) (kitchen) high x(4) A 1)(bath) x(3) y(3) (refrigerator) x(4) y(2) (bath water heating) when the order among the variables two horizontal lines is undefined.
* The correlations were calculated by the formula Y = ,/x2/N, that is, x2 regarding the given table of distributions, divided by the number of cases in the table and raised to the power of l/2.
between
Testing a hypothesis of the above type, regarding the structure of relations within a given set of variables, may be carried out by a number of multi-variate methods; however, the simplicity of the proposed structure (a simple order among variables) and the small number of variables did not require more than an examination of the correlations among the variables. The order hypothesis will be verified if the correlation between every two variables increases the closer they are on the ranking established by the hypothesis. That is, if the hypothesis establishes that a < b < c then the respective empirical correlations should hold that r,h > rot rbe
The above definition establishes only partial order among the facilities, since as long as we do not establish weights for the various facets, all have equal weight
placed
Testing the hypothesis
or (x(2), Y(l)) < (X(4)?Y(2)).
in
>
r’,c.
Actually, if the hypothesis regarding all variables is true, the correlations may be arranged in a matrix in an order which the hypothesis suggests. In such a matrix the value of the correlations in each row or in each column decreases the further one is from the main diagonal. A matrix of this structure is called a simplex
c91. From the calculation of the appropriate correlations* using the data of the Population and Housing
164
M. HARTMAN
The main deficiency of the results obtained is that they are based upon an analysis of a small number of variables. Six variables were used, one of which causes a deviation from the simplex (actually, if we exclude the refrigerator, the other five variables are a full simplex). In the future, the position of other needs within this ranking structure should be examined by surveying appropriate variables. The large number of variables. even in small samples, will make it possible to examine a theory regarding the existence of additional facets. An additional possible facet is the ‘facility’s cost’, or equivaiently, the area occupied by the facility (if it is a part of the building) or the number of facilities (e.g. a second W.C.). The difficulty in examining this possibility is in the evaluation of the ‘cost’ of various facilities in the apartment. Existing surveys have no indications of cost, quality or size of various facilities; it is therefore now impossible to examine the theory of a three-facet structure. Another question which may arise, regarding the facet structure presented above, is related to the positioning of several general variables on the housing conditions studied in many censuses and surveys. For example, the existence of running water and electricity in an apartment is considered to be one of the basic criteria in evaluating housing standards [I]. These variables are related to several ‘needs’ at the same time (such as running water for cleanliness and cooking needs) and thus may not be classified using the above facets. It seems that according to the proposed structure they should be regarded as additional facets, and not variables at the same level as the other variables. Finally, it should be noted that the order assumed W.C. regarding the necessity of needs in the first facet, Flushing device though compatible with the results obtained, is not sufKitchen ficiently defined. The intuitively-established order Refrigerator among this facet’s categories is generally compatible Bath with the general population of Israel, but it is clear that Bath water heating. in different climates or regarding populations from different cultures, the order of necessity may change. The lack of clarity regarding the order of needs becomes especially evident among the ‘higher’ needs, in which The ordered structure of the components of the stanthe importance ofpersonal taste, or the taste of certain dard of facilities in an apartment makes it possible to sub-populations, increases. For example, privacy for understand the ranking which exists among the variables. The practical use of the order obtained above fOT various members of the family has been mentioned in U.N. proposals to investigate housing conditions in the various variables is in constructing questionnaires the 1970 censuses [lo] as a criterion for standard of which are directed at ranking the population of aparthousing conditions. It may very well be that this is a ments according to their housing facilities-in future need recognized onlv in certain cultures, while in surveys or censuses. others it is not considered to be a need which the It becomes evident from the above order that in apartment should fulfill. order to obtain a more refined ranking than the one we obtained earlier we may follow two methods. (a) To ‘fill-in’ the blank cells in Table 8, above, by examining variables belonging to these cells according to their facet definitions. REFERENCES (b) To define the additional ‘needs’ fulfilled by housing facilities and their place in the ordering within this 1. L. Guttman. The basis ofscalogram analysis. in ,Metrsrrw mrnt and Prediction, Studies in Social Psychology in facet, and afterwards to find the facilities fulfilling these World Wur II, Vol. 4. Princeton University Press (1950). needs.
Census in Israel. 1961, regarding the six housing facilities mentioned above the results shown in Table 8 are obtained. It is evident that the set of correlations has the simplex form, with one deviation (the correlation between a flushing device and a refrigerator is exchanged with the correlation between a kitchen and a flushing device). Thus the proposed order theory may be accepted. In the above-mentioned set of correlations it should be noted that the values of the correlations change significantly when moving from one category to another over the ‘needs’ facet and remain similar within each category from the aspect of this facet. For example, if we look at the first line of the table (Table 8), we will find that the variables within the ‘needs’ facet have a correlation which is close to 1, 0.5 and 0, respectively. The correlation between refrigerator and bath is the only exception. It shouldalso be mentioned that the variables within ‘each category of each facet form simplex structures, with no deviation in their correlations. We may conclude from these relations among the correlations that one facet exerts stronger ‘influence’ upon the order of the variables and we may in effect add a second order rule. The (x) facet, which establishes the necessity of the need fulfilled by the facet, has preference over the (y) facet-the facility’s mobility, so that the second facet only assists in establishing order among those facilities which are at equal ranks on the first facet. Using this rule a complete ordering will be obtained among the variables, i.e. the order in which they are listed in the table of correlations
Constructing housing condition indicators
Central Bureau of Statistics, Eualuuriot~ of thv Crtrsus Data (2 Vols.). Population
and Housing Census Pubiication No. 40, Jerusalem (1969). Central Bureau of Statistics, Hausiq, Part it. Popufation and Housing Census Publication No. 31, Jerusalem (1965). Central Bureau of Statistics, Housing, Part I. Population and Housing Census Publication No. 16, Jerusalem (1963). L. Guttman, Introduction to facet design and analysis. Prucwdinys of the Fifteenth Congress of Psychology, Brussels, pp. 130-132. North Holland, Amsterdam
(1957).
6. L. Guttman,
A structural theory for intergroup beliefs and a&on. Am. socid Rut).24,31&32g (1959). 7. t. Guttman, The structuring of sociologica spaces~ in ~~~~~s~~~~~i~~ uf‘rhr Foiirth World Congress 5~~5c~5~5~~, pp. 31>355 (1961). 8. L. Cuttman, A faceted definition of inteIligence, Scriprn Hirrosolymitana 14, 166-181 (196S). 9. L. Guttman, A new approach to factor analysis: The radex, in Mathematical Thinking in the Social Sciences (Ed. by P. F. Lazarsfeld). Free Press, New York (1954). IO. United Nations, Statistical indicators of housing conditions. Statistical Papers Serial Number M. 37. Statistical Office of the llnited Nations, New York (1962).
APPENDIX
1
The various facilities and their categories (1961 Census of Israel) Facility W.C. Flushing device in WC. Bathtub or shower Method of heating
Kitchen Refrigerator
Possible modalities 2 1 0 1 0 0 2 1 0 5 4 3 2 1 0 2 1 0 2
165
W.C. exists-outside building W.C. exists-inside building No W.C. With flushing device No flushing device No WC. Bathtub or shower exists for family’s use only Bathtub or shower exists for use with others NO bathtub or shower Central or apartmental heating Sun boiler Electric boiler Oil, wood, etc. Other heating arrangement No heating arrangement Kitchen exists Cooking corner or other cooking arrangement No cooking arrangement Electric refrigerator 1 Xeebox 0 No electric refrigerator or ice box
HOUSING
CONDITION
INDICATORS
MOSHEHARTMAN
Department of Sociology,
Tel Aviv University, (Received 6 September
Ramat
Aviv, Tel Aviv, Israel
1973)
Two methods are suggested for constructing housing condition indicators in surveys and censuses. The Guttman scale is suggested for combining the different housing condition variables in a survey. A facet design is suggested for constructing questionnaires that have the purpose of measuring the level of housing conditions. Data from Israel’s 1961 census is used to exemplify the use of the two methods.
INTRODUCTION In censuses, housing condition studies and other survevs, various data are collected regarding housing conditions of households, such as: the quality of facilities in the apartment, the size of the apartment, the living density, etc. One of the aims of collecting such data is to enable ranking of households according to their housing standards. In order to obtain a system for ranking households which will utilize a series of various details regarding housing, a method must be found to compute a general housing standard score for each household based upon all the characteristics of the household. Although the researcher generally faces the problem of formulating an index w&h the aid of a list of researched data, it is evident that the following preliminary problem should arise when constructing the questionnaire for the survey or census, namely, how to define the housing characteristics to be studied w&h will make possible the ranking of households. This work deals with the two above-mentioned problems, that is: (a) the ranking of households according to housing standard with the aid of a given list of items;(b) Pn approach to building a questionnaire concerning housing conditions (or that part of the questionnaire dealing with housing conditions), which would enable the formation of an integrated index for scoring the researched units. 1. THE CUTTMAN SCALE FOR RANKING HOL’SEHOLDS OR APARTMENTS* ACCORDING THEIR STANDARD OF FACILITIES
TO
The accepted method of describing the housing conditions of the population is to calculate the proportion of families possessing a particular facility. Sometimes a number of variables are combined, such as the division of Families according to housing density and the * “Apartment’‘-a resides. t For a description
housing
unit in which
quality of facilities in the apartment. This method indeed describes various aspects of household housing conditions, but in order to obtain a general ranking of families according to their housing standard and to analyze the factors related to housing variables, one must sum up the individual housing variables of each family. The importance of the ranking is threefold: (a) Clear information is acquired concerning the distribution of families according to their housing standard. (b) It is possible to measure the relationships between the housing standards and other variables. (c) It makes it possible to compare housing conditions of various populations, and the same population at various times. The ranking system presented below has been constructed with the aid of the Guttman Scale.? The scale was composed with the aid of the variables concerning facilities in the apartment: the existence of a bathtub, the method of water heating in the bathroom, the existence of a W.C. and a flushing device, the existence of a kitchen and the means for food refrigeration, The source of the data used to construct the index is the 1961 Population and housing census in Israel. All data presented below are based upon a sample of 20 per cent of the country’s households (about 107,000 households were included in the sample). This sample represents the popuiation of Israel, except for those residing in institutions and ~~~~~~r~~~~~ and the nomad Bedouin tribes. The latter have not been included due to their special housing conditions, which differ from those of the rest of the country’s residents. In the above-mentioned census, data on housing density, number of rooms in the apartment, and the existence and quality of the various facilities, were collected for each household. Stages
one household
in the preparation
of the ~a~lk~~zg sq?sterns
For the purpose of composing the above-mentioned variables
of the system. see [I]. 155
the grading scale, all were crossclassified.
156
M. HARTMAN
Each cell in the resulting table included those households which were equivalent from the standpoint of the various housing variables. Each cell in the table is defined by a combination of the categories of all the variables employed. Each combination of categories of all the variables will be hereinafter referred to as a ‘profile’. The ranking of households or apartments is in effect an ordering of the various profiles obtained. Out of over 10,000 possible profiles, 70 per cent of households were concentrated among 224 profiles, 25.5 per cent of households were distributed among the rest of the profiles, and 4.5 per cent of households could not be classified into any of the profiles, because at least one of the items had not been recorded. In the first stage an attempt was made to rank the 224 profiles with the aid of the Guttman Scale, but it was discovered that they do not form a scale. A thorough examination of the data showed that the variables ‘apartment size’ and ‘housing density’ confounded the scale formed by the other variables, and hence these were not included in the subsequent classification. The other variables defined a narrower universe of ‘content’ that is ‘the level of facilities in the apartment’ instead of ‘the general level of housing’. These remaining variables are presented in Appendix 1. This narrowing of the number of variables substantially cut down the number of profiles, so that 91 per cent of the households were included in 52 profiles (see Table I), each of which includes 200 families. The remaining profiles formed a ‘Quasi-Scale’, including 15 ranking groups (scores). In the lowest rank, the ‘0’ group, those households have been included which lacked any facilities at all. In the highest rank, the ‘14’ group, those households have been included which had all facilities, including an electric refrigerator and high-standard bath water heating, such as electricity or central/apartment heating (see Table 1). The 15 profiles out of the 52 form a full scale. Sixty-seven per cent of the households are included in these profiles (see Table 2). In the final scale we have added to each of the ‘ideal’ profiles the closer profiles from the ‘Quasi-Scale’. It must be stressed that no significance should be attached to the numerical value of the score, except for marking the profile’s pkice in the ranking. Neither are we able to know anything about the distances between one score and another. The ranking of apartments by the general score can
* The reproduction coefficient measures the extent of proximity of the ‘Quasi-Scale’ to the full scale. It decreases when the deviating profiles increase and when the number of cases included in deviating profiles is large, see [l]. t Except for the deviating profiles. J The purpose of this section is to show a few examples of use of the ranking obtained. Analysis of results of the census in this topic are presented in the introductions of the respective census publications.
be done at three levels of detail, with the most detailed one containing 15 scores (see Table 2). In the more general ranking the following types of apartments were defined:. (a) Apartments with profiles of a low standard of facilities including mainly apartments with a W.C. and no kitchen-about 6 per cent of the total of apartments. (Scores: c-3 in the detailed grading). (b) Apartments with a kitchen and a refrigerator as well. (Scores: 4-8). (c) Apartments with all of the above and a bath as well, but no water heating facility in the bath. (Scores: 9-10). (d) Finally, those apartments having all facilities and the best water heating facility. (Scores: 11-14). Description of the scale obtained. The ‘Quasi-Scale’ obtained has a reproduction coefficient* of 0.92. It should be remembered that if we took into account the low frequency profiles (under 200 cases), we would obtain a lower reproduction level. But we may assume that the deviating profiles are errors in replies or other census errors. An additional criterion for the degree of proximity to a full scale is the percentage of apartments included in the profiles from the full scale out of the total number of apartments whose profiles are in the ‘QuasiScale’-this in our case is 73.6 per cent. (The percentage of apartments in the full scale out of the total number of apartments in Israel reaches 67.2 per cent.) The two indicators of the quality of the scale show that the scale obtained is close enough to the full scale so as to enable its efficient usage. The scores obtained have a clear meaning:t each score denotes, for the majority of the population with that score, the facilities existing in its apartment (from among the six variables included in the scale). For example: the score 6 for an apartment means that it has a W.C. with a flushing device and a kitchen with an ice-box, but it lacks either a bath or a shower, and a water-heater in the bath or shower; an apartment with the score of 12 has all six facilities included in the scale, and the water heating method in the bath is an electric boiler. The scoring of families with the aid of the scale makes it possible to analyze the differential housing conditions of various segments of the population, such as differences between urban and rural populations, differences between veteran families and new immigrants, etc. Several such examples from the Israeli data will be presented below. $ (a) D@rences between rural and urban settlements. A clear picture emerges regarding the differences in the standard of facilities among households in urban and rural settlements. In the rural settlements the standard of facilities is lower than in the urban settlements. It may be shown that this stems from the fact that the majority of the rural populations is non-Jewish. The standard of facilities in the non-Jewish population is relatively low. Within the Jewish population there exists differences in the standard of facilities of
ConstrLicting Table
Rank score
I. Distribution
No. of families
of households
1* 2 2 2* 3% 4 4*
5 5* 6 6. 6*
8 8 8* 9 9 9 9 9 9* 10 10 10 10 10 10 10 10* 11 11 11* 12 12* 13 13* 14* Total
14,555 880 3600 925 4325 3065 5390 3290 1750 7460 1300 3535 1965 1110 2840 2620 I170 6730 1315 7820 1355 4180 535 1060 5385 2680 3510 1065 29,965 4520 1615 1625 6870 4520 2060 3850 4205
W.C.
X
x x
X X
x
x
3
x x x x x X
x X X
x
X X
X
X
X
X
X
X
x x
x x
X
X
X
x x x x x x
X
X X
X
x
x x x
X
X
X
x x x
X
X
X X
x
x
x X
x
x
x X
x X
X
X
X
X
X
X
x x x x x x x x x x
x X
x X
X
X
x X
X
X
X
x X
X
X
X
X
x x x x
X
x
x
X
X
X
x
X
X
x X
x
x
X
X
X
X
x
X
X
X
x
X
X
x
x
X X
x
X
x
X
x
x
x
x x x
X
x
X
x x
X
X
x
x
X
x
X
x
X
x x
x x x
X
x
x
x
x
x x
X
x
x
x x
x x x
X X
x
x
x x
x x
x
X
X
X
X
x
X
012345
X
X
x x
X
x x x x x x
012
X
X
x
x
X X
x x x x
x
X
X
x x
X
x
X
X
X
X
x
x
X
X
x
x X
X X
X
x X
x
x
Water heater
Bath
x x x x x x x x x x x
X
x
X
012
x
x x
x
Refrigerator
X
X
I(
X
157
indicators
in Israel (1961) by profiles of level of facilities ‘quasi-scale‘?
x x x x x
1XhO 3505 4185 975 6480 3970 24,370 2870 28,895 37,270 2705 191.825 660 15,470 10.965 487.64%
condition
The facility: Flushing device Kitchen Category1 0 I 012
012
o*
housing
X X
X
X
x x
x x
x x X X
x x
x X
x
x X
x X
x x
* These profiles are part of the full scale (see Table 2). t See definition Cl]. $ See definition in Appendix 1. Q Includes about 90% of households as profiles having less than 200 cases were not included. Source: Population Census of Israel 1961. Central Bureau of Statistics, unpublished data, Israel. 20% of households.
x
Data
on a sample
of
158
M. HARTMAN
urban and rural settlements, but these are much smaller than the differences within the non-Jewish population (see Table 3). (b) Continent of birth und length of’ residence in Israel. Differences may be seen among standards of facilities of households from different countries of origin, 48 per cent of households in which the father was born in Africa possess facilities of high standard, as against 87 per cent of households of natives of EuropeAmerica or 74.6 per cent from among native Israelis (see Table 4). It also appears that within the immigrant groups of both major continental origins-Asia-Africa and Europe-America-there are differences which are related to length of residence in the country. Those who have been in the country for a longer period of time have Table 2. Distribution
Rank score
of households
W.C. 0 1 2
2, of households
up the housing conditions from point of view of services and density, the population may be ranked as follows: Highest: high facilities-low housing density
in Israel (1961) by the profiles
No. of families
0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 Total households
a higher standard than the newer households (see Table 5). (c) Relarion to housing density. The obtained scale does not include all housing variables. The ranking forms one variable describing only the standard of the facilities. The possibility exists of comparing this ranking with the other housing variables, so that a general picture of housing standards may be obtained. A crossclassification of this ranking with housing density shows the relation which exists between the two variables. In general, apartments with high facilities have low housing density, and vice versa. So as to sum
14.555 3600 3065 3290 7460 2620 7820 2680 29,965 3850 24,370 37,270 191,825 15.470 10,965 in full scale 358,805 in full scale 67.27;
The facilities? Flushing device Kitchen Categories? 0 1 0 1 2 Profiles x X x x x x
x X x x x x
3 6 7 7 9 9 9 10 10 10 10 11
0 12
012
012345
x x x
x x x x x x x
x x x x x x x x x
x x ‘X
x x x x x
x x x x x x x x
X
x x x
profiles
Water heater
Bath
Refrigerator
of full scale x X x x X X
x x x x x
. Main deviating
Included
in the full scale* and some of the deviating
profiles
in: 5390 6730 4180 5385 4520 6870 4520 4205 4185 6480 3970 28,895
* For definition see [l]. t For definition see Appendix 1. Source: Population Census of Israel 20% of households.
x x
x x x x x x x x x x x x
1961, Central
X
x x
x
x x
x x x x x x x x x
X
x x x x x x x
Bureau
of Statistics,
x
x
X
x
x x x
x x x x
x
x
x
x x
x x x
x x x x x x
unpublished
x x x x x
x
x
x x
data,
Israel.
x
Data
on a sample
of
ConstrLlcting Table 3. Households
housing
condition
indicators
159
in Israel (1961) by level of facilities, type of locality and Jewish households
Level of facilities*
Jewish households
All households
Rank scores
Urban
Total no. of households
RLlral 79,230
485,145 100.0
o-1
2.5 10.0 12.5 75.0
4-8 9-10 I l--14
for total population
1OO.Q 34.6 22.3 9.5 33.6
Urban
Rural
495.010
49.040
100.0
100.0
1.6 9.2 12.7 76.5
5.0 27.4 15.1 52.5
* By rank score on the scale (see definition of the four cstcgories in text). Source: Population Census of Israel 1961, Central Bureau of Statistics. Israel. Data on a sample of 20% of households.
Table 4. Jewish
households
in Israel (1961) by level of facilities, by continent of residence in Israel Household
Level of facility Rank scores*
Household head born in Israel
No. of households in thousands
Low (O-8) Medium (9-10) High (1 l-14) * See definitions
Total
head born in Asia or Africa Immigrated Immigrated 19481961 before 1948
of birth
Total
unpublished
data,
of head of household
and length
Household head born in Europe or the Americas Immigrated Immigrated before 1948 1948 1961
46.5
160.8
26.4
134.4
2X7.8
138.6
169.2
100.0
100.0
100.0
100.0
100.0
IOO.0
loo.0
8.6
27.4
21.0
28.1
5.8
2.4
9.0
1.1
24.7
16.6
26.3
7.4
3.6
IO.5
74.6
48.0
62.3
45.0
87.0
94.0
x0.5
in text.
Source: Population Census of Israel 1961, Centrai Bureau of Statistics.
trnpublishcd
data.
Israel.
Data
on a sample
of
207: of households.
Medium: high faG~litie~high housing density Low: low facilities-high housing density (see Table 6). Table 5. Households in Israel (1961) by level of facilities and housing
density
Level of facilities in rank scores
High*
Density Low*
Total*
100.0
100.0
O-10 11-14
52.0 48.0
15.4 84.6
* Total number of households 537.4 thousand. Number of households with high density (that is. two or more persons per room) was 308.1 thousand. Source: Population Census of Israel 1961, Central Bureau of Statistics, unpublished data, Israel. Data on a sample of 20% of households.
Along with these advantages one must note the following disadvantages of the resultant ranking. (a) 7-k un~iahles irduded in the SC&. As explained above, the scale includes only variables describing the ‘facilities in the apartment’, and hence we obtained the ranking according to ‘standard of facilities in the apartment’ instead of the general ‘housing standard’. It should be especially noted that housing density and apartment size are not included in the scale of variables. Housing density is considered to be one of the important indicators of housing conditions: still, no way has been found to include it in the scale formed by the other variables and therefore in actual practice one must employ the two indicators for housing standard: the facility scale score and the density rate (see above for the relation between the two). (lo) The profiles which de~iutr,fiom the,fidl scrrk. The scale which has been formed is based upon approxi-
160
M.
HARTMAN
mately 67 per cent of the households which formed a full scale, as explained above; the rest of the households deviated somewhat from this scale. Analysis of the deviations shows that they stem from four principal reasons. (1) There is a certain interchange between an electric refrigerator and an electric boiler; there are families which purchase the first before the second, and vice versa. As a result, the score 11 includes the two kinds (see Table 1). From the scale’s point of view, one of the profiles ‘deviates’, but from the point of view of facility standard there is no real difference between the two. (2) A second reason for deviations is the difference made between ‘bath for use with others’ and ‘bath for family’s use only’. This difference gives us an additional rank in the scale (score 7), but causes the inclusion of a large number of households as having a profile which ‘deviates’ from the full scale. (3) The difference between ‘no refrigerator’ and ‘icebox exists’ causes additional deviations. Combination of the proper categories-‘ice-box’ with ‘no refrigerator’ and ‘bath for use with others’ with ‘bath for family’s use only’ yields a ranking of 13 scores only, and the percentage of deviations from a full scale is decreased from 33 to 30 per cent. (4) Analysis of errors in answers in the census regarding the housing questions showed that in the question about the type of heating in the bath, ‘oil, wood, etc.’ and ‘other water heating arrangement’ has no meaning (see Central Bureau of Statistics of Israel, 1969). It may be better to combine these two categories in the scale as well, and thus the number of deviations will decrease. (c) Asymmetric distribution of the population by the scale. Another problem stemming from the nature of the variables included in the scale is related to the distribution of the population by the scores. It appears that the variables from which data were recorded in the census (by which the scale was constructed) bring about a detailed ranking of the low types of housing conditions, and do not differentiate with adequate detail the medium and high ranks. In the accumulated frequency of the number of families according to the various ranks in the scale. the ‘jump’ from score 11 to score 12 is apparent (Fig. I). In order to arrive at a more symmetric division, we must strive to form intermediate scores between these two grades. A method for finding variables which would yield suitable division points is presented in Part 2 of this article. Comparison with other methods for ranking households according to housing conditions A possible method of reaching a compound variable which would rank households by their standard of facilities, is to give a weight to each factor or facility, and to sum up in each household the total weights of all facilities existing in the apartment. The advantage of such a system is that it gives quantitative values to the family’s housing standard, and
Rank
score of level of facilities
Fig. 1. Distribution of households in Israel (1961) (based on data presented in Table 2) included in the full scale by the rank score of level of facilities (accumulating percentages). thus makes it possible, in addition to the ranking of families, to also measure the distances between the various groups. This is especially important when we wish to compare the housing standard at various periods of time (when asking, for example, how have the housing conditions of a certain population improved). The disadvantages of this method (and the reasons for preferring the method which yields an ordinal ranking only) are : (a) There is no accepted method of establishing the weights-not only the absolute weight of the various facilities, but even their relative weight. Every weight system would have the disadvantage of its being arbitrary, and there is no way of examining objectively if the weights express the true ‘value’ of the various facilities. (b) Even should we succeed in forming a system of weights for a number of variables, there is an additional disadvantage: there is no way of adding variables to that system without changing all the existing weights. Therefore, in those cases in which different housing data are available, there will be no possibility of using the same weights. In the scale we formed above, this disadvantage does not exist, since the addition of a variable will not alter the ranking formed by the previous variables. For the same reason we could not by a tieighting method rank the families according to some of the variables (in more limited surveys) and be certain that this ranking would remain the same even if we were to take into account all the housing conditions. These disadvantages apply to every quantitative method requiring weights for the various indices of housing conditions. 2. THE FACETS
OF HOUSING
CONDITiONS
In Part I above. it was found that a scale exists which ranks the population of apartments according to their
Constructing Table 6. Arrangement
housing
of examples
of household
Mobility
Needs
Built in
Shelter Sanitation Eating
Stone building W.C. Kitchen
Body cleanliness
Bathrooms
Clothes’ cleanliness Temperature regulation Privacy
Laundry
Number (4+)
condition
room
of rooms
standard of facilities; this ranking is accomplished with the aid of a number of indicators, i.e. individual ‘facilities’. We found that the standard of facilities in the apartment is determined by the number and quality of facilities out of a limited number of possible facilities which we have surveyed. In this section we shall attempt to analyze the nature of the relationship between the general variable‘standard of facilities’-and the individual facilities in the apartment. The practical purpose of such an analysis is to find a desired method of choosing housing condition indicators in the questionnaires of surveys and censuses. The method For the purpose of this analysis we will employ the concepts of Guttman’s facet analysis [S-S]. Following this approach we assume that the concept of ‘standard of facilities in the apartment’ defines one ‘universe of content’ or a group of variables all of which contribute, one way or another, to the general level of facilities. It is assumed that among the different variables belonging to this group there exists a certain set of relations or a structure. In order to discover the structure of relations among the variables an attempt is made to find abstract concepts through which the variables may be organized or ordered. These different aspects are called facets. Each facet is thus an abstract concept which divides the group of all variables in a certain manner. As an example we shall propose below to subdivide the group of all variables or all facilities in an apartment by the human needs they fulfill. ‘Human needs’ is a more abstract variable, having several categories, such as weather shelter, eating, cleanliness, etc. All facilities may be divided according to the needs they fulfill-those fulfilling the need for food (such as the kitchen, cooking stove, etc) or the need for cleanliness (such as a bath, shower) etc. In search for the structure of the relations among all variables (all facilities), the definition of facets narrows down a large number of variables to a limited number (usually 2-4) of facets which are to be dealt with. The theories regarding the structure of relations among variables
161
indicators facilities within defined facets
of facility Installed Roof Flushing device Wall cupboard in kitchen Bath heating installation Rinsing bowl Air conditioning/ central heating Room separation installations
Appliance Shutters Refrigerator/ cooking oven
Washing Heating
machines device
may be expressed as theories regarding among facets. One of the simple hypotheses regarding the structure of the variables and facets is the hypothesis that the categories of each facet are ordered, and that the order existing in each facet produces at least partial order among the variables. For example, we may assume that the needs fulfilled by the facilities are ordered, so that the eating need is more ‘important’ than the need for cleanliness, the need for cleanliness more important than the need for privacy which the apartment if capable of providing, etc. Each facet is therefore provided with a numerical score which ranks the facet’s categories. Each variable belongs to one of the facet’s categories (every facility fulfills one of the specified ‘needs’) and receives the rank order of that category. That same variable will similarly also receive a rank order regarding the other facets. In accordance with this approach we shall attempt below to relate the group of all facilities in the apartment to the general standard of facilities. The general assumption will be that the relation between each one of the facilities and the general standard of facilities in the apartment is as follows: each facility in the apartment contributes to the general rank of the standard of facilities in the apartment. Each facility may be ‘evaluated’ by several criteria or over a number of ‘facets’; the facility’s combined ‘value’ for all these criteria determines its contribution to the standard of facilities in the apartment. We shall attempt below to arrive at these ‘facets’ (or these evaluation criteria), and to present statistical proof for the resulting rank order. Finally, a number of practical conclusions will be derived, based upon the ordering of the facilities, and their contribution to the standard of facilities in the apartment. The method of examining the ordering of the variables is as follows: (a) A list of facets which are assumed to determine the order of a set of variables is intuitively established. (b) Three requirements are assumed to have been met: (1) a sufficient number of facets were included to explain the order among the variables; (2) each facet
162
M. HARTMAN Table 7. Arrangement
surveyed in census according to facets in the proposed theory
of facilities
Needs
Built in
Sanitation Eating Washing
W.C. Kitchen Bath
Mobility of facility Installation Flushing
of the standard of facilities
device Refrigerator
Heating
has an adequate number of categories; (3) an a priori semantic order was established among the variables according to their ranks on all facets. (c) The correlations among the variables are examined. (d) The order is verified by the fact that the closer two variables are, in the semantic order, the higher the correlation between them. Analysis of facets apartment
Appliance
in the
The assumptions upon which the following analysis is based are: (1) The purpose of the apartment’s facilities is to fulfill a number of the resident’s needs. These needs may be arranged according to their degree of necessity or fundamental importance.* For example, we shall assume that facilities of an apartment should fulfill the residents’ needs of eating and physical cleanliness, and that the eating need is more basic or necessary than cleanliness. ‘Necessity’ here has the following meaning: the requirement that ‘every apartment should enable the residents to prepare their meals within it’ is more acceptable, commonly agreed upon, than the requirement that ‘every apartment must enable the residents to wash themselves’. (2) During the construction of the apartment the order of priorities as to the inclusion of one facility or another is also influenced by the degree of mobility of that facility: at construction time one is more likely to include in the apartment a less mobile facility; e.g. it is not likely that an apartment will be built without a kitchen, with the assumption that it will be added later. At any rate, it is more likely to leave for ‘later’ the addition of warm water installation. The surveyed apartments include in many cases faci-
* The order of necessity of these needs may change from place to place. The need for weather shelter will have a differing importance in different climates (it seems that in Israel, with average weather, this need is less vital regarding heat and cold, and more vital regarding rain shelter). Thus, air conditioning has a low degree of necessity and a high contribution to the standard of facilities. t Home appliances-only home appliances related to the apartment are meant, and not, for example, a camera or a transistor radio. An installation is a facility that is usually related to the apartment, and when moving, it is not usually taken along, while this is not the case regarding home appliances.
lities added after construction.
It may be assumed that the order of addition of the added facilities is influenced to a greater extent by the factors of the facility’s necessity and its cost than by its mobility. The hypothesis about the structure of relationships among all facilities. On the basis of the above mentioned assumptions we propose that each facility’s contribution to the general standard of facilities of an apartment is determined by the facility’s value regarding two criteria or two facets: (a) Necessity (in the above meaning) of the need the facility fulfills. Let us assign the letter x to the facility’s contribution to this facet. (b) Mobility of the facility. Let us assign the letter y to the facility’s contribution to this facet. Each facet, x and y, has categories which may be ordered from the highest to the lowest, so that the order regarding variables may be verified. The orderings within the facets must have a common meaning, and this should also be common to the general variable-inourcase, thestandardoffacilities.Ifwe translate this requirement to our case, the following rules will be obtained. The more basic the need served by the facility, the less the facility contributes to raising the general standard of facilities. The less mobile the facility is, the less it contributes to the apartment’s standard of facilities. Let us define the following categories for each facet: (a) Needs-from more vital to less vital (x may have the value): 1. Shelter 2. Sanitation (W.C.) 3. Eating 4. Cleanliness (body, clothes) 5. Privacy (regarding outside society and among family members). There may exist other ‘needs’ that were not included; about those we assume only that we can always add them and order them with the above, without changing the order of those mentioned: e.g. ‘cleanliness’ may be broken down into body cleanliness (washing) and clothes’ cleanliness (laundry), but this does not upset the order; it only details the above ordering. (b) We assume the following categories regarding mobility-from less mobile to more mobile (y may have the value) facilities: 1. Part of the building 2. An installation installed and adapted to the building 3. Mobile device or home appliances.?
Constructing
housing
Table 8. Intercorrelations*
W.C. W.C. Flushing device Kitchen Refrigerator Bath Bath water heating
Flushing device
Kitchen
0.999
condition among
163
indicators facility variables
Refrigerator
Bath
Bath water heating
0.413
0.437
0.058
0.42
0.423
0.465 0.414
0.042 0.255 0.286 0.391
0.999 0.413 0.437 0.058
0.423 0.465 0.060
0.414 0.453
0.461
0.060 0.453 0.461 -
0.042
0.042
0.255
0.286
0.391
* The correlations were calculated by the formula r = ,/x2/N, that is, ,$ regarding the given table of distributions divided by the number of cases in the table and raised to the power of l/2. Source: Pooulation Census of Israel 1961. Central Bureau of Statistics, unpublished data, Israel. Data on a sample of 20% of households.
As noted above, every possible facility will receive a certain value on each facet; thus we may mark a kitchen by (x(3), y(l)), a bath’s water heating installation by (x(4), y(3)), etc. The requirement for a common meaning of the order within each facet means that in all facets a higher rank shows a higher contribution to the standard facilities. The above hypothesis may be described by Table 6, which clarifies examples of facilities in an apartment according to the facets and the assumed order within each facet. In a similar way we can arrange the variables surveyed in the Population and Housing Census, 1961, in Israel, according to the facets we established (see Table 7). Using the symbols defined above, we may mark all facilities included in the 1961 Census in Israel: W.C. W.C. flushing device Kitchen Refrigerator Bath Water heating facility
x(2), x(2), x(3), x(3), x(4), x(4),
Y(l) Y(3) Y(1) Y(3) Y(l) Y(2).
We shall define a particular order among the above facilities in the following manner. Let us assume that facility a is of a ‘higher’ standard than facility 6, if the indices of facets x, y in facility a are greater or equal, respectively, to the indices of facility b. For example (XV), Y(l) < (x(2), Y(2))
and the order among some facilities is not yet defined such as (x(%0)) 3 (x(3Ml)). The partial order which is formed may be expressed the following diagram: low x(2) 121) (WC.) x(2) ~(2) (flushing device) x(3) y(l) (kitchen) high x(4) A 1)(bath) x(3) y(3) (refrigerator) x(4) y(2) (bath water heating) when the order among the variables two horizontal lines is undefined.
* The correlations were calculated by the formula Y = ,/x2/N, that is, x2 regarding the given table of distributions, divided by the number of cases in the table and raised to the power of l/2.
between
Testing a hypothesis of the above type, regarding the structure of relations within a given set of variables, may be carried out by a number of multi-variate methods; however, the simplicity of the proposed structure (a simple order among variables) and the small number of variables did not require more than an examination of the correlations among the variables. The order hypothesis will be verified if the correlation between every two variables increases the closer they are on the ranking established by the hypothesis. That is, if the hypothesis establishes that a < b < c then the respective empirical correlations should hold that r,h > rot rbe
The above definition establishes only partial order among the facilities, since as long as we do not establish weights for the various facets, all have equal weight
placed
Testing the hypothesis
or (x(2), Y(l)) < (X(4)?Y(2)).
in
>
r’,c.
Actually, if the hypothesis regarding all variables is true, the correlations may be arranged in a matrix in an order which the hypothesis suggests. In such a matrix the value of the correlations in each row or in each column decreases the further one is from the main diagonal. A matrix of this structure is called a simplex
c91. From the calculation of the appropriate correlations* using the data of the Population and Housing
164
M. HARTMAN
The main deficiency of the results obtained is that they are based upon an analysis of a small number of variables. Six variables were used, one of which causes a deviation from the simplex (actually, if we exclude the refrigerator, the other five variables are a full simplex). In the future, the position of other needs within this ranking structure should be examined by surveying appropriate variables. The large number of variables. even in small samples, will make it possible to examine a theory regarding the existence of additional facets. An additional possible facet is the ‘facility’s cost’, or equivaiently, the area occupied by the facility (if it is a part of the building) or the number of facilities (e.g. a second W.C.). The difficulty in examining this possibility is in the evaluation of the ‘cost’ of various facilities in the apartment. Existing surveys have no indications of cost, quality or size of various facilities; it is therefore now impossible to examine the theory of a three-facet structure. Another question which may arise, regarding the facet structure presented above, is related to the positioning of several general variables on the housing conditions studied in many censuses and surveys. For example, the existence of running water and electricity in an apartment is considered to be one of the basic criteria in evaluating housing standards [I]. These variables are related to several ‘needs’ at the same time (such as running water for cleanliness and cooking needs) and thus may not be classified using the above facets. It seems that according to the proposed structure they should be regarded as additional facets, and not variables at the same level as the other variables. Finally, it should be noted that the order assumed W.C. regarding the necessity of needs in the first facet, Flushing device though compatible with the results obtained, is not sufKitchen ficiently defined. The intuitively-established order Refrigerator among this facet’s categories is generally compatible Bath with the general population of Israel, but it is clear that Bath water heating. in different climates or regarding populations from different cultures, the order of necessity may change. The lack of clarity regarding the order of needs becomes especially evident among the ‘higher’ needs, in which The ordered structure of the components of the stanthe importance ofpersonal taste, or the taste of certain dard of facilities in an apartment makes it possible to sub-populations, increases. For example, privacy for understand the ranking which exists among the variables. The practical use of the order obtained above fOT various members of the family has been mentioned in U.N. proposals to investigate housing conditions in the various variables is in constructing questionnaires the 1970 censuses [lo] as a criterion for standard of which are directed at ranking the population of aparthousing conditions. It may very well be that this is a ments according to their housing facilities-in future need recognized onlv in certain cultures, while in surveys or censuses. others it is not considered to be a need which the It becomes evident from the above order that in apartment should fulfill. order to obtain a more refined ranking than the one we obtained earlier we may follow two methods. (a) To ‘fill-in’ the blank cells in Table 8, above, by examining variables belonging to these cells according to their facet definitions. REFERENCES (b) To define the additional ‘needs’ fulfilled by housing facilities and their place in the ordering within this 1. L. Guttman. The basis ofscalogram analysis. in ,Metrsrrw mrnt and Prediction, Studies in Social Psychology in facet, and afterwards to find the facilities fulfilling these World Wur II, Vol. 4. Princeton University Press (1950). needs.
Census in Israel. 1961, regarding the six housing facilities mentioned above the results shown in Table 8 are obtained. It is evident that the set of correlations has the simplex form, with one deviation (the correlation between a flushing device and a refrigerator is exchanged with the correlation between a kitchen and a flushing device). Thus the proposed order theory may be accepted. In the above-mentioned set of correlations it should be noted that the values of the correlations change significantly when moving from one category to another over the ‘needs’ facet and remain similar within each category from the aspect of this facet. For example, if we look at the first line of the table (Table 8), we will find that the variables within the ‘needs’ facet have a correlation which is close to 1, 0.5 and 0, respectively. The correlation between refrigerator and bath is the only exception. It shouldalso be mentioned that the variables within ‘each category of each facet form simplex structures, with no deviation in their correlations. We may conclude from these relations among the correlations that one facet exerts stronger ‘influence’ upon the order of the variables and we may in effect add a second order rule. The (x) facet, which establishes the necessity of the need fulfilled by the facet, has preference over the (y) facet-the facility’s mobility, so that the second facet only assists in establishing order among those facilities which are at equal ranks on the first facet. Using this rule a complete ordering will be obtained among the variables, i.e. the order in which they are listed in the table of correlations
Constructing housing condition indicators
Central Bureau of Statistics, Eualuuriot~ of thv Crtrsus Data (2 Vols.). Population
and Housing Census Pubiication No. 40, Jerusalem (1969). Central Bureau of Statistics, Hausiq, Part it. Popufation and Housing Census Publication No. 31, Jerusalem (1965). Central Bureau of Statistics, Housing, Part I. Population and Housing Census Publication No. 16, Jerusalem (1963). L. Guttman, Introduction to facet design and analysis. Prucwdinys of the Fifteenth Congress of Psychology, Brussels, pp. 130-132. North Holland, Amsterdam
(1957).
6. L. Guttman,
A structural theory for intergroup beliefs and a&on. Am. socid Rut).24,31&32g (1959). 7. t. Guttman, The structuring of sociologica spaces~ in ~~~~~s~~~~~i~~ uf‘rhr Foiirth World Congress 5~~5c~5~5~~, pp. 31>355 (1961). 8. L. Cuttman, A faceted definition of inteIligence, Scriprn Hirrosolymitana 14, 166-181 (196S). 9. L. Guttman, A new approach to factor analysis: The radex, in Mathematical Thinking in the Social Sciences (Ed. by P. F. Lazarsfeld). Free Press, New York (1954). IO. United Nations, Statistical indicators of housing conditions. Statistical Papers Serial Number M. 37. Statistical Office of the llnited Nations, New York (1962).
APPENDIX
1
The various facilities and their categories (1961 Census of Israel) Facility W.C. Flushing device in WC. Bathtub or shower Method of heating
Kitchen Refrigerator
Possible modalities 2 1 0 1 0 0 2 1 0 5 4 3 2 1 0 2 1 0 2
165
W.C. exists-outside building W.C. exists-inside building No W.C. With flushing device No flushing device No WC. Bathtub or shower exists for family’s use only Bathtub or shower exists for use with others NO bathtub or shower Central or apartmental heating Sun boiler Electric boiler Oil, wood, etc. Other heating arrangement No heating arrangement Kitchen exists Cooking corner or other cooking arrangement No cooking arrangement Electric refrigerator 1 Xeebox 0 No electric refrigerator or ice box