PALESTINIAN SOCIETY - Fafo

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Raving thus determined the household sample allocation among PSUs within the strata, the next step is to allocate the various PSU subsamples among PSU cells. The housing unit selection stage is still disregarded. The (conditional) inc1usion probability for an arbitrary household (s,k,c,d) within PSU (s,k) is: (3 6) R ( k ) b (s, k) d (s, k, c) . 5" c B (5, k) D (5, k, c) In order to have a local (within PSU) epsem design, the R(s,k,c) must be a constant, i.e. independent of c. Rowever, having two unspecified variables -b( s,k) and d( s,k,c ) -and only one equation for determining them, we are free to specify any of them independently. To make a proper choice one should, however, appraise both cost and sampling error components. While budgetary constraints rnight suggest that the number of cells to be selected should be "small", considerations of sampling error induce no obvious choice. The sampling error can be split into two components reflecting within eell variations and variations between eells, respeetively (variations refer to the survey variables). In general, preference should be given to the dominating component of variation. Thus, great between cell variations imply a large number of cells (and few households per cell) to be inc1uded, while great within cell variations sugge st a smaller number of cells (and more households per cell). As no prior information about the magnitude of the components of variation was available, further elaboration of sampling error con siderations would obviously have been both speculative and questionable. We thus leave this discussion in order to address a more practical approach. It was decided above that 45 PSUs be inc1uded in the 1st stage sample, implying on average approximately 23 households to be selected within each of the PSUs. To avoid concentration of all PSU interviews to one single area it was also decided to inc1ude at least 2 sample cells in every PSU. An average sample size per cell of 5-10 households was eonvenient for practical reasons as well. Thus the number of cells selected in each of the sample PSUs was for the majority of PSUs 2-5. There are, however, a few exceptions where only 1 or more than 5 cells were selected, depending on both the total number of cells and the household sample size for the PSU. In practice the b( s,k)s are roughly proportionate to the PSU total number of cells, B(s,k). The allocation of sample cells among PSUs is shown in table A.9. 328
Having thus decided the number of sample cells in each of the PSUs it remains to determine the allocation of the PSU household sample among cells. According to (3.6) this allocation obviously has to beproportionate inordertohave alocal(withinPSU) epsemdesign. As stated previously, the latter requires R(s,k,c) to be a constant independent of the cell (c) under consideration. TIms, in R( s,k,e) we may ornit the index c and reformulate (3.6): B (5, k) (3.7) d (5, k, c) = R (5, k) b (5, k) D (5, k, c) In order to calculate R(s,k) foreach of the sample PSUs we take the sum for every (s,k) of both sides of (3.7): b(s.k) B (5, k) b(s. k) (3.8) c� d (5, k, c) = R (5, k) b (5, k) c� D (5, k, c) The left hand side adds to the PSU sample size, d(s)lk(s). On the righ t hand side all statisties are known except for the constant R( s,k). Hence R(s,k) is determined, and the individual d(s,k,c)s can be calculated from (3.7), concluding the sample allocation calculations. The d(s,k,c)s arrived at also determine the number of housing units selected from each celI. The fmal household and cell sample allocation is displayed in table A.9 for the selected PSUs. Before concluding this section, we retum to the overall inclusion probability (3.3), to see how this can be calculated. . 5" c, , - (3 3) P ( k h ) _ k (5) D (5, k) b (5, k) d (5, k, c) 1 D (5) 8 (5, k) H (5, k, c,) D (5, k, c, h) The first fraction on the right hand side is the 1st stage inclusion probability. At the planning stage the numbers of PSU and stratum households, the D(s,k)s and D(s)s, were not available. Instead, the Benvenisti estimates6 of the total population figures were used (equation (3.1» . The second fraction is the 2nd stage inclusion probability which can be calculated from the figures in table A.9. To calculate the third fraetion, the d(s,k,c)s are taken from the fmally observed (net) sample, and the H(s,k,c)s are estimated by formula (2.4) in the Gaza design section. The last fraction - the 4th stage inclusion probability -isdetermined by the sample observations ofthe D(s,k,c,h)s. 329
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Marianne Heiberg and Geir Øvensen
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© Fagbevegelsens senter for forskn
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Chapter 4 Health ..................
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Preface The history of the FAFO liv
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future analyses. We look forward to
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Gaza, colonel Zacharias Backer, gav
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tive effects of economic growth, su
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Demographics: The size and composit
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cally different. For example, Israe
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Interested readers should consult t
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of ten look at their situation in m
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The Fragmentation of Palestinian So
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dunums would be used for subsistenc
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Whole village communities, as well
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planning, the transfer of land acqu
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eginning of 1993. It continues to a
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4 The data in this section is deri
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Chapter 2 Population Characteristic
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British Mandate of Palestine as its
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Table 2.1 Head of household'sfather
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Gaza West Bank centers which remain
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In the present study the Gaza Strip
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egional pyramids can be compared to
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West Bank variations by refugee sta
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Infant and Child Mortality The rest
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ever bom (CEB) and children survivi
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Age Structure The data set represen
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fallirig outside this interval may
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second and the third groups with we
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q(S) durmg the last fIfteen years,
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Concluding Remarks The Brass method
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50 years at the time of the intervi
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in the value for the age group 25-2
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The projections are based on extens
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Mortality u sing F ALCOT 92 results
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Table 2.15 Assumed age structure of
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distribution in three broad age gro
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64. The weakest growth is expected
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Shahin et al. (1989), A Baseline De
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17 Statistical abstract of Israel 1
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Chapter 3 Housing Marianne Heiberg
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ecome underdeveloped due to c1osure
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Table 3.4 Mean squnre meters per ho
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ed households. The survey figures f
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With regard to heating, in Arab Jer
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shift, reflecting increased prosper
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Survey data on fonns of ownership i
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injured, the fewest injuries occurr
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Gaza camps and West Bank camps woul
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All individuals in the sample were
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14 days. The survey included childr
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oth of which are characterized by a
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Variations in Rates and Patterns of
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The rate of acute and chronic illne
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tive of social background. Religios
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in Sweden, and 7.4 in Belgium and 1
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provide family planning assistance.
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given assistance in private cIinics
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up to 44% among those above 60 year
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Protective Factors Stress tolerance
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on the frequencies and distribu- Ta
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high degree of distress increases o
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About I out of 3 respond- Table 4.1
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The second question needs further a
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References Feachem RGA. et al. The
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education to the world outside laea
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in a subsequent chapter which deals
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y literacy, but is not the equivale
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It is widely believed that UNRWA an
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Reversely, for those in the bot- Ta
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Religious observance is affected by
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life - the family, the neighbourhoo
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For men and women there seems to be
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The increased propensity, associate
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determine whether or not women are
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wear Western forms of dress (table
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tributes of gen der and age in affe
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political institutions recognized b
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The lower the level of a household'
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In contrast to most developing coun
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Religious affiliation was considere
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etween household weaIth and Head of
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Recent Development of Household Inc
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Figure 6.9 shows thatchanges in hou
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In Arab Jerusalem, one out of five
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income as their only type of in com
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survey. Capital income in the occup
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e said roughly to be associated wit
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As to recentdevelopments in househo
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180
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Labour Force Definitions For measur
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countries. Casual work, unpaid work
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to some extent may be explained by
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tive economic acti vities has been
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The firsteffect(whichresembles Figu
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employment. Invisible underemployme
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hold full-time jobs. Figure 7.9 iII
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older and weU educated persons than
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entry into Israel. 2) Cultural fact
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workers having had only one job dro
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Figure 7.20 shows that the north- F
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tendency to the opposite effect. Mo
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occupied territories employed in Is
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) "activities which do not generate
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tus, and the relatively high rate o
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In conclusion, when engaging in inc
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the total economy' s production of
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where income appears at the timeof
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48 There is no correlation between
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220
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There is, however, little common ag
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occupational prestige categories, o
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opposed to the status categorizatio
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The distribution is grouped into fo
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of their male counterparts, and may
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access to financial support (e.g. N
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economic trends, invoking il greate
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taken individually, dose to half of
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The Role of the Family Based on the
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etween the two extreme categories o
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can be observed. With the emergence
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etween different social groups with
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ackground characteristics. All coef
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248
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eal views in a formally constructed
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These points are further illustrate
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girls far below the age of puberty
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to each other, but the social messa
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played out in the work plaee, an ar
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efugees, regardless of whether they
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Education also seems to impact on t
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While disparities in religious Tabl
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Political Attitudes Because politic
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Islam might be less, survey results
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the trend toward increasing prefere
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premise is that the individual owes
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women seems not to be affected by a
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occupied territories into advanced
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Page 292 and 293: 64 women at ages 43-47. These facto
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Page 296 and 297: Here it becomes dear that Table lO.
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Page 306 and 307: Another interesting point in Table
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Page 316 and 317: would be involved, this was conside
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Page 324 and 325: Sample Allocation In this section t
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Page 334 and 335: 1983 map (other statistical maps ha
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Page 338 and 339: By successively inserting the vario
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Page 342 and 343: Proceeding one step furtherthe stra
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Page 348 and 349: Appendix B Recruitment, Training an
Page 350 and 351: were approached and the purpose and
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Page 354 and 355: which person was chosen as the rand
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Page 362 and 363: A2.2 Distribution of population by
Page 364 and 365: A2.4 Age distribution by religion a
Page 366 and 367: A2.6 Household composition by regio
Page 368 and 369: A2.8 Household composition m occupi
Page 370 and 371: A2.10 Percent of households in whic
Page 372 and 373: A6.2 Household wealth by household
Page 374 and 375: A6.4 Householdwealth in Gaza and th
Page 376 and 377: A6.6 Householdweekly meat consumpti
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A6. JO Head of Household labour inc
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A6. 12 Household income types in Ga
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A6. 14 Distribution ofhousehold inc
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the CBS survey is primarily conceme
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ent both on the definition of "unem
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Table A. 7.3 Labour force participa
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Table A. 7.4 Unemployed persons as
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Table A.7.5 "Discouraged" workers a
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Table A.7.6 (Continued) Full-time a
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Table A. 7.8 Labourforce members by
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Table A. 7. JO Male labour fo rce m
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Table A. 7. 12 Comparative composit
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Table A.7.J3 (Continued) Main emplo
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Table A. 7. 15 Distribution of labo
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Table A.l.Il Main employment of lab
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Table A. 7. 19 Main employment of l
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Table A. 7.20 Main employment of la
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Table A. 7. 22 Comparative composit
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Table A. 7.24 Labourforce members b
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Table A. 7. 26 Labour force members
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Table A. 7.28 Weekly time use for w
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PALESTINIAN SOCIETY in Gaza, West B
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PALESTINIAN SOCIETY - Fafo

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