11 June 94, rev. 19 Oct, 13 Dec 94, 10 Feb 95
ChinaA Dataset, County-level Units 1990
Compiled and Generated by G. William Skinner
This dataset contains a record for every county-level unit and every urban ward (qu)
as of 1990. ID numbers contain 6 digits, the first two of which indicate the
province in which the county-level unit falls. The ID numbers for 1990 are, with
minor exceptions, the official guobiao codes; they reflect the administrative
situation that obtained on 1 July 1990, the reference date of the 1990 population
census. ChinaA is organized so that four different datafiles can be selected for
particular analyses. The FD (Fully Differentiated) File includes separate records
for every urban ward (qu) as well as every county-level unit. The MQ (Merged Qu)
File has combined selected urban qu in order to create units large enough to be
mapped at the 1:1 million scale used in the project's companion GIS files. These
mergers have been designed so that the central city of a given municipality is
always intact in a single merged unit. The MQ File also incorporates a few non-
municipal mergers designed to minimize the number of cases where a single unit in
the tabular file corresponds to two or more polygons in the companion GIS file.
The MC (Municipality-Compatible) File attempts to compensate for arbitrary
differences in the administrative geography of municipalities by merging certain
tightly drawn municipalities with their surrounding counties to achieve greater
comparability. These mergers also ensure that, in the course of regional analysis,
the immediate hinterland of a city ends up in the same zones and classes as the
city itself. The RS (Regional Systems) datafile incorporates subdivisions of
counties that our analysis has shown to be divided between regional systems.
The short designation of any variable is a number preceded by a (for "area"),
indicating the ChinaA dataset, which is to be distinguished from the ChinaT (for
"town"), the central-place dataset with records for individual cities and towns.
Blocks of variable numbers are allocated as follows:
a01-a99 Unit-control variables
a101-a999 Raw-data variables
a1001-a9999 Regional-analysis variables
a10001-a10999 Analytical variables
The need for 5-digit numbers stems from the advantage of reserving 4-digit numbers
for the regional-analysis variables. There are nine macroregional systems, numbered
R1 (Manchuria) to R9 (Yungui), many of which have subsystems, and the same variables
are created for each macroregion and subregion separately. It is much easier to keep
things straight when the initial two digits in a 4-digit ID always indicate the
regional system in question; so a5004 is the core-periphery zoning of the Middle
Yangzi treated as a whole, while a5104, 5204, 5304, and 5404 are the core-periphery
zonings of its component subsystems, respectively. The contrast between 3-digit IDs
for raw data and 5-digit IDs for analytical variables serves to distinguish the two
kinds of variables and permits parallel substantive assignments. So, for instance,
a10201-a10299 would be the analytical variables derived from a201-a299.
UNIT-CONTROL VARIABLES
a01 1990 ID number
a02 Chinese name
a03 Pinyin name
a04 Non-Han name
a05 Type of prefectural-level unit to which this unit belongs
a06 County-level administrative status of this unit
a07 Status of this unit's capital (FD file only)
a08 Assignment to China Proper or to Inner Asia
a10 z99 ID no. of 82-85 MC unit to which this unit's territory precisely
corresponds blank if none)
a11-13 z99 ID nos. of 82-85 MC units that were merged to form this unit
a14 z99 ID no. of 82-85 MC unit of which this unit is a subdivision
a15-19 (Cases other than simple mergers or subdivisions) z99 ID nos. of 82-85 MC
units encompassing any part of this unit's territory
a21 1990 datafile control scheme
a22 1982-90 datafile control scheme
a23 MC82-85-90 datafile control scheme
a05 Type of prefectural-level unit to which this county-level unit belongs
1 Municipal province
2 Municipal prefecture whose central city is a provincial capital
3 Municipal prefecture not a provincial capital
4 Prefectural municipality that is a provincial capital
5 Prefectural municipality not a provincial capital
6 District (diqu)
7 Autonomous department (zizhizhou)
8 League (meng)
9 Directly administered by the province; no prefectural unit
a06 County-level administrative/analytical status of this unit
01 Shixiaqu (SXQ) of a stand-alone (county-like) high-order shi
02 SXQ of a high-order shi whose size is intermediate between
(01) and (03) [approximate area 460-750 sq km.]
03 SXQ of a tightly bounded high-order shi (carved out of a xian)
04 SXQ of a high-order shi part of whose territory is detached
05 Central-city subset of SXQ
06 Periurban subset of SXQ
07 Individual qu within SXQ
08 Shi that is a municipal county (county-like)
09 Shi that is a county municipality (tightly bounded: very small area
and/or known to have been carved out of a xian)
10 County (xian)
11 Autonomous county (zizhixian)
12 Banner (qi)
13 Autonomous banner (zizhiqi)
14 Qu other than urban or periurban
15 Feiqu and split mergers
16 Municipal-compatible mergers
17 Subdivision of county-level unit needed for regional analysis
a07 Status of this unit's capital
1 Cc of provincial-level shi
2 Cc of prefectural shi
3 Cc of county-level shi
4 Zhen
5 Xiang seat or other non-zhen
6 "Capital" lies outside the unit in a neighboring shi
0 Doesn't apply (has no county-level or higher capital)
a21 1990 datafile control scheme FD Fully Differentiated
MQ Merged Qu
MC Municipality-compatible
RS Regional Systems
FD MQ MC RS
0 x x x x
1 x x x
2 x x
3 x
4 x
5 x x
6 x x x
7 x x
8 x
9 SXQ not in any datafile
Restsated:
0 FD units unchanged in all datafiles
1 FD units unchanged in MQ and MC files but subdivided to form a21=8 units in
RS file
2 FD units unchanged in MQ file but merged to form a21=7 units in MC and RS files
3 FD units merged to form a21=4,5,6 units in MQ file
4 MQ units (mergers of a21=3 units) merged to form a21=7 units in MC and RS files
5 MQ units (mergers of a21=3 units) unchanged in MC file but subdivided to form
a21=8 units in the RS file
6 MQ units (mergers of a21=3 units) unchanged in MC and RS files
7 MC units (mergers of a21=2,4 units) unchanged in RS file
8 RS units formed through subdivision of a21=1,5 units
9 Shixiaqu more inclusive than a component MC unit and hence not included in
any datafile
Datafiles:
a91 FD (Fully Differentiated) File (all urban qu shown separately; no mergers
of guobiao coded units; no analytical subdivisions) a21=0,1,2,3
a92 MQ (Merged Qu) File (selective mergers of urban qu to get mappable units):
a21=0,1,2,4,5,6
a93 MC (Municipality-Compatible) File (extensive mergers of tightly drawn shi
each with its surrounding xian and of units whose territories are
intertwined, yielding a file suitable for regional analysis): a21=0,1,5,6,7
a94 RS (Regional Systems) File (incorporating subdivisions of counties that are
divided between regional systems) a21=0,6,7,8
In due course, we plan to incorporate into ChinaA the entire dataset already
developed for county-level units in 1982-85. This will permit comparisons of
similarly organized findings at two points in time (1982 vs. 1990 or 1985 vs. 1990),
providing an indication of change. ChinaZ, the county-level dataset for 1982-85,
will be incorporated only when ChinaA qua 1990 dataset has been completed. The
following two variables indicate the proposed design of the combined dataset.
a22 1982-90 analytical datafile control scheme
(1982 file is z96; 1990 file is a92)
0 In all three files: Units unchanged in territorial extent from 1982 to 1990
1 Only in 1982 File: 1982 units that had been merged by 1990
2 In 1982-90 and 1990 Files: 1990 units formed through the merger of 1982
units
3 In 1982 and 1982-90 files: 1982 units that had been subdivided by 1990
4 Only in 1990 file: 1990 units formed through subdivision of 1982 units
5 Only in 1982 File: 1982 units that were subdivided and regrouped by 1990
6 Only in 1990 File: 1990 units formed through regrouping subdivided 1982
units
7 Only in 1982-90 File: Combinations of both 1982 and 1990 units to achieve
equivalent territories
Datafiles:
a94 1982 File (equivalent to z96): a22=0,1,3,5
a95 1990 File (equivalent to a92): a22=0,2,4,6
a96 1982-90 File: a22=0,2,3,7
a23 MC82-85-90 datafile control scheme
(1982-85 file is z99, 1990 file is a93)
0 In all three files; Units of identical territorial extent in 1982-85 and
1990
1 Only in MC82-85 File: 82-85 unit is uncomplicated component of 1990 unit
2 In MC82-85-90 and MC90 Files: 1990 unit is a combination of 82-85 units
3 In MC82-85 and MC82-85-90 Files: 82-85 unit is a combination of 1990 units
4 Only in MC90 File: 1990 unit is uncomplicated component of 82-85 unit
5 Only in MC82-85: 82-85 unit in complicated relationship to 1990 units
6 Only in MC90 File: 1990 unit in complicated relationship to 82-85 units
7 Only in MC82-85-90 File: Combinations of both 82-85 and 1990 units to
achieve equivalent territories
Datafiles:
a97 MC82-85 File (equivalent to z99): a23=0,1,3,5
a98 MC90 File (equivalent to a93): a23=0,2,4,6
a99 MC82-85-90 File : a23=0,2,3,7
PROVISIONAL MACROREGIONAL ASSIGNMENTS
a0900 Inner Asia
a1100 Manchuria Proper
a1200 Manchuria: Tumen Border subsystem
a1300 Manchuria: Northeast Border subsystem
a1400 Manchuria: North Border subsystem
a2100 North China: Northern subsystem
a2200 North China: Southern subsystem
a2300 North China: Eastern subsystem
a3100 Northwest China: Wei-Fen subsystem
a3200 Northwest China: Upper Yellow River subsystem
a4100 Upper Yangzi Proper
a4200 Upper Yangzi: Upper Han Basin subsystem
a5100 Middle Yangzi Proper
a5200 Middle Yangzi: Gan Basin subsystem
a5300 Middle Yangzi: Yuan Basin subsystem
a5400 Middle Yangzi: Guilin subsystem
a6100 Lower Yangzi Proper
a6200 Lower Yangzi: Linhai subsystem
a6300 Lower Yangzi: Wenzhou subsystem
a7100 Southeast Coast: Min Basin subsystem
a7200 Southeast Coast: Zhang-Quan subsystem
a7300 Southeast Coast: Han Basin subsystem
a8000 Lingnan
a9100 Yungui Proper
a9200 Yungui: Guiyang subsystem
a9300 Yungui: South Border subsystem
a9400 Yungui: Southwest Border Subsystem
RAW-DATA VARIABLES FROM THE 1990 POPULATION CENSUS
Urban-Rural Residence
a101 Total no. of H Table 2-19
a102 Total P "
a103 Total M H=household(s) "
a104 Total F M=male(s) "
a105 Residents of urban wards: No. of H F=female(s) "
a106 " " " : P P=population (M+F) "
a107 " " " : M "
a108 " " " : F "
a109 Residents of villages: No. of H "
a110 " " : P "
a111 " " : M "
a112 " " : F "
a113 Residents of rural units outside village jurisdiction: No. of H "
a114 " " " " " " " : P "
a115 " " " " " " " : M "
a116 " " " " " " " : F "
a117 Non-agricultural H: P "
a118 " " ": M "
a119 " " ": F "
a120 Agricultural H: P "
a121 " ": M "
a122 " ": F "
a123 Specially designated H and persons outside any H: P "
a124 " " " " " " " ": M "
a125 " " " " " " " ": F "
a126 All residents of all zhen (townships) combined: No. of H Table 2-11
a127 " " " " : P "
a128 " " " " : M "
a129 " " " " : F "
a130 Town residents in all zhen combined: No. of H "
a131 " " " " " : P "
a132 " " " " " : M "
a133 " " " " " : F "
a134 Rural residents in all zhen combined: No. of H "
a135 " " " " : P "
a136 " " " " : M "
a137 " " " " : F "
a138 Non-agricultural H in all zhen combined: P Table 2-12
a139 " " " " " : M "
a140 " " " " " : F "
a141 Agricultural H in all zhen combined: P "
a142 " " " " : M "
a143 " " " " : F "
a144 Specially designated H, etc. in all zhen combined: P "
a145 " " " " " : M "
a146 " " " " " : F "
a147 Residents outside zhen (townships): No. of H a101-126
a148 " " " : P a102-127
a149 " " " : M a103-128
a150 " " " : F a104-129
a151 Urban residents outside zhen (i.e., in city): No. of H a105-130
a152 " " " " : P a106-131
a153 " " " " : M a107-132
a154 " " " " : F a108-133
a155 Rural residents outside zhen (i.e., in xiang): No. of H a109-134
a156 " " " " : P a110-135
a157 " " " " : M a111-136
a158 " " " " : F a112-137
a159 Non-agricultural H outside zhen (most in city): P a117-138
a160 " " " " " : M a118-139
a161 " " " " " : F a119-140
a162 Agricultural H outside zhen (most in xiang): P a120-141
a163 " " " " : M a121-142
a164 " " " " : F a122-143
a165 Specially designated H, etc. outside zhen: P a123-144
a166 " " " " " : M a124-145
a167 " " " " " : F a125-146
a168 Urban P, cities/towns t109=2000+ only: No. of H ChinaT import
a169 " " " : P " "
a170 " " " : M " "
a171 " " " : F " "
Age-Sex distribution
a181 Total P, all ages and both sexes A1
a182 Total M, all ages A2
a183 Total F, all ages A3
a184 P 0-4 A4
a185 M 0-4 A5
a186 F 0-4 A6
a187 P 5-9 A7
a188 M 5-9 A8
a189 F 5-9 A9
a190 P 10-14 A10
a191 M 10-14 A11
a192 F 10-14 A12
a193 P 15-19 A13
a194 M 15-19 A14
a195 F 15-19 A15
a196 P 20-24 A16
a197 M 20-24 A17
a198 F 20-24 A18
a199 P 25-29 A19
a200 M 25-29 A20
a201 F 25-29 A21
a202 P 30-34 A22
a203 M 30-34 A23
a204 F 30-34 A24
a205 P 35-39 A25
a206 M 35-39 A26
a207 F 35-39 A27
a208 P 40-44 A28
a209 M 40-44 A29
a210 F 40-44 A30
a211 P 45-49 A31
a212 M 45-49 A32
a213 F 45-49 A33
a214 P 50-54 A34
a215 M 50-54 A35
a216 F 50-54 A36
a217 P 55-59 A37
a218 M 55-59 A38
a219 F 55-59 A39
a220 P 60-64 A40
a221 M 60-64 A41
a222 F 60-64 A42
a223 P 65-69 A43
a224 M 65-69 A44
a225 F 65-69 A45
a226 P 70-74 A46
a227 M 70-74 A47
a228 F 70-74 A48
a229 P 75-79 A49
a230 M 75-79 A50
a231 F 75-79 A51
a232 P 80-84 A52
a233 M 80-84 A53
a234 F 80-84 A54
a235 P 85-89 A55
a236 M 85-89 A56
a237 F 85-89 A57
a238 P 90-94 A58
a239 M 90-94 A59
a240 F 90-94 A60
a241 P 95-99 A61
a242 M 95-99 A62
a243 F 95-99 A63
a244 P 100+ A64
a245 M 100+ A65
a246 F 100+ A66
a247 P 0-14 a184+187+190
a248 M 0-14 a185+188+191
a249 F 0-14 a186+189+192
a250 P 20-44 a196+199+202+205+208
a251 M 20-44 a197+200+203+206+209
a252 F 20-44 a198+201+204+207+210
a253 P 75+ a229+232+235+238+241+244
a254 M 75+ a230+233+236+239+242+245
a255 F 75+ a231+234+237+240+243+246
Educational attainment, aged 6+
a261 Total P aged 6+ E1
a262 Total M aged 6+ E2
a263 Total F aged 6+ E3
a264 P university E4
a265 M " E5
a266 F " E6
a267 P technical/junior college E7
a268 M " " " E8
a269 F " " " E9
a270 P secondary technical school E10
a271 M " " " E11
a272 F " " " E12
a273 P senior middle school E13
a274 M " " " E14
a275 F " " " E15
a276 P junior middle school E16
a277 M " " " E17
a278 F " " " E18
a279 P primary school E19
a280 M " " E20
a281 F " " E21
a282 P illiterate/semi-illiterate E22
a283 M " " E23
a284 F " " E24
Illiteracy
a291 Total P 15+ E1
a292 Total M 15+ E2
a293 Total F 15+ E3
a294 P illiterate/semi-illiterate E4
a295 M " " E5
a296 F " " E6
Marital status
a301 Total P 15+ M1
a320 Total M 15+ M2
a303 Total F 15+ M3
a304 P never married M4
a305 M " " M5
a306 F " " M6
a307 P married M7
a308 M " M8
a309 F " M9
a310 P widowed M10
a311 M " M11
a312 F " M12
a313 P divorced M13
a314 M " M14
a315 F " M15
Births 1989-90
a321 All births 1Jan89-30Jun90 B1
a322 M births " " B2
a323 F births " " B3
a324 All births 1Jan89-30Jun89 B4
a325 M births " " B5
a326 F births " " B6
a327 All births 1Jul89-31Dec89 B7
a328 M births " " B8
a329 F births " " B9
a330 All births 1Jan90-30Jun90 B10
a331 M births " " B11
a332 F births " " B12
Deaths 1989-90
a341 All deaths 1Jan89-30Jun90 D1
a342 M deaths " " D2
a343 F deaths " " D3
a344 All deaths 1Jan89-30Jun89 D4
a345 M deaths " " D5
a346 F deaths " " D6
a347 All deaths 1Jul89-31Dec89 D7
a348 M deaths " " D8
a349 F deaths " " D9
a350 All deaths 1Jan90-30Jun90 D10
a351 M deaths " " D11
a352 F deaths " " D12
Inmigrants since 1985
a361 Total inmigrants R1
a362 Within-province inmigrants: Total R2
a363 " " " : from municipal cities R3
a364 " " " : from zhen (urban townships) R4
a365 " " " : from xiang (rural townships) R5
a366 Inmigrants from other provinces: Total R6
a367 " " " " : from municipal cities R7
a368 " " " " : from zhen R8
a369 " " " " : from xiang R9
a370 Other inmigrants R10
a371 Total inmigrants less "other" a361-370
Industry/Economic activity
a381 Total employed P I1
a382 Total " M I2
a383 Total " F I3
a384 P Agric./forestry/animal husb./fishery/water conservancy I4
a385 M " I5
a386 F " I6
a387 P Industry I7
a388 M " I8
a389 F " I9
a390 P Mining, prospecting I10
a391 M " I11
a392 F " I12
a393 P Construction I13
a394 M " I14
a395 F " I15
a396 P Transport, posts, telecommunications I16
a397 M " I17
a398 F " I18
a399 P Commerce, supply and marketing I19
a400 M " I20
a401 F " I21
a402 P Real estate, utilities, residential services I22
a403 M " I23
a404 F " I24
a405 P Medicine, health care, sports, welfare I25
a406 M " I26
a407 F " I27
a408 P Education, culture, arts, radio, television I28
a409 M " I29
a410 F " I30
a411 P Science, technology I31
a412 M " I32
a413 F " I33
a414 P Finance, insurance I34
a415 M " I35
a416 F " I36
a417 P Government, party, and NGOs I37
a418 M " I38
a419 F " I39
a420 P Other economic activities I40
a421 M " I41
a422 F " I42
Occupation
a431 P Professional and high-level technical personnel O1
a432 M " O2
a433 F " O3
a434 P Officials/managers in gov't, party, business, & NGOs O4
a435 M " O5
a436 F " O6
a437 P Clerical personnel O7
a438 M " O8
a439 F " O9
a440 P Employees in commercial sector O10
a441 M " O11
a442 F " O12
a443 P Employees in service sector O13
a444 M " O14
a445 F " O15
a446 P Workers in agric., forestry, animal husb., fisheries O16
a447 M " O17
a448 F " O18
a449 P Workers in manufacturing, construction, transport, etc. O19
a450 M " O20
a451 F " O21
a452 P Other and misc. occupations O22
a453 M " O23
a454 F " O24
Sources: Official provincial tabulations of 1990 census data
(XX sheng 1990 nian renkou pucha ziliao), most volumes published in 1992 by
Zhonguo tongji chubanshe). In the source column, the letter specifies the table
and the number specifies the column. Most, but not all, of the provincial books
number county-level tables the same. The table numbers given in parentheses below
accord with majority practice.
Table A (1-5) Five-year age classes by sex
Table E (1-6) Educational attainment by sex, P aged 6+
Table L (1-8) Illiteracy by sex, P aged 15+
Table M (1-12) Marital status by sex, P aged 15+
Table B (1-13) Births by half-year and sex, 1989-90
Table D (1-16) Deaths by half-year and sex, 1989-90
Table R (1-17) Inmigrants since 1985 by type of residence in 1985
Table I (1-9) Industrial categories by sex, employed population
Table O (1-10) Occupational categories by sex, employed population
AGRICULTURAL ECONOMICS: RAW-DATA VARIABLES 1990
a601 Rural population (add 0,000) NCJJ
a602 Rural labor force, inclusive (add 0,000) "
a603 Rural labor force in agriculture, forestry, animal
husbandry and fishing (add 0,000) "
a604 Labor force in rural industry (add 0,000) "
a605 Total area under cultivation (hectares) "
a606 All crops sown area (hectares) "
a607 Grain sown area (hectares) "
a608 Cotton sown area (hectares) "
a609 Oil crops sown area (hectares) "
a610 Grain output (tons) "
a611 Cotton output (tons) "
a612 Oil output (tons) "
a613 Meat output (tons) "
a614 Agricultural mechanization (10,000 watts) "
a615 Tractor-plowed area (hectares) "
a616 Irrigated area (hectares) "
a617 Fertilizer used (tons) "
a618 Electricity used (10 million watt-hours) "
a619 Value of collective units' product (10,000 yuan) "
a620 Gross value of agricultural output (10,000 yuan) "
a621 Gross value of rural industrial output (10,000 yuan) "
a622 Net value of agricultural output (10,000 yuan) "
a623 Adjusted GVAO (10,000 yuan) "
a624 Purchased output (10,000 yuan) "
NCJJ: Zhongguo fenxian nongcun jingji tongji gaiyao 1990. Beijing, 1991.
REGIONAL ANALYSIS VARIABLES
a901 Fully differentiated configuration of central places (combined t702 data)
a902 Differentiated configuration of central places exclusive of low-order and
suburban centers (t702=1-7 only)
a903 Combined "centrality" of the county's central places estimated by summing
weights assigned to each hierarchical level (Assign weight of 1 to central
towns and use multiplier of 3.5 for weights of higher-order centers)
a904 Combined "centrality" of the county's central places estimated by summing
weights generated by dividing a constant by the number of central places
at each hierarchical level
a903 rationale: The hierarchy of local and regional systems in China generally
accords with Christaller's k=3 or k=4 models or mixtures of the two. This means
that the mean size of hinterlands of central places at a given hierarchical level
are approximately 3.5 times larger than the mean size of hinterlands of central
places at the next lower level. For China as a whole, the results of central-place
analysis show ratios (moving down the hierarchy) of 3.6, 3.4, 4.1, 3.4, and 3.3.
An additional justification for the 3.5 multiplier is that the mean population of
central places at any level are (on this analysis) between 3 and 4 times larger
than that of central places at the next lower level. In terms of operations, ignore
t702=8,9,0 cases and assign weight 1.0 to t702=7 cases (central towns), assign
weight 3.5 to t702=6 cases, 12.25 to t702=5 cases, etc. The upshot is that one
greater city carries the same weight as 3.5 local cities; one local city carries
the same weight as 3.5 central towns, etc. To avoid large 4-digit numbers for the
county-level units containing the five apex metropolises, we assign 999 (rather than
1838) to t702=1 cases.
a904 rationale: The procedure followed here relies solely on the number of central
places at each level to generate weights, thus avoiding any arbitrary or
uniformitarian assumptions. Our analysis indicates that the ChinaT dataset includes
virtually all central places at the local-city level and higher. However, fewer
than half of all central towns are in the dataset. Continuing the progression down
from local cities to central towns, we estimate that there are in fact (or were as
of 1990) approximately 6500 central towns. The a904 procedure generates weights for
each level by dividing a constant by the total number of central places at each
level. It is convenient to take 6500 as the constant in order to give a weight of 1
to central towns. The calculated weight for local cities, of which where are 1976
in all, is 6500/1976=3.29. That for greater cities, numbering 597, is 6500/597=10.
89, etc. Again, to avoid 4-digit numbers for the units containing apex metroplises,
we assign 999 (rather than 1300) to t702=1. We will generate alternative CSIs using
a903 and a904 and see which does best. The weights to be used are as follows:
t702: 1 A 2 C 3 M 4 R 5 G 6 L 7T
a903 999 525 150 42.88 12.25 3.50 1
a904 999 500 151 34.57 10.89 3.29 1
a905 Level of highest-order cnetral place in the county (t702 codes)
a906 Non-agric. P of largest central place in the county
a907 Total non-agric. urban P, central towns and higher only
a908 Total non-agric. urban P, local cities and higher only
ANALYTICAL VARIABLES FROM CENSUS DATA
Sex ratio and H size by residence
a10101 Persons per inclusive H a102/101
02 Sex ratio of total P a103/104
03 Residents of urban wards: Persons per inclusive H a106/105
04 " " " : Sex ratio a107/108
05 Villagers: H size a110/109
06 " : Sex ratio a111/112
07 Other non-urban residents: Persons per inclusive H a114/113
08 " " " : Sex ratio a115/116
09 Non-ag. H: Sex ratio a118/119
a10110 Agric. H: Sex ratio a121/122
11 Other H: Sex ratio a124/125
12 Residents of all urban townships (zhen): H size a127/126
13 " " " " : Sex ratio a128/129
14 " " towns (zhen): H size a131/130
15 Rural residents of urban townships: H size a135/134
16 " " " " : Sex ratio a136/137
17 Non-ag. H, all urban townships: Sex ratio a139/140
18 Agric. H, all urban townships: Sex ratio a142/143
19 Other H, all urban townships: Sex ratio a145/146
a10120 Urban residents outside zhen: Persons per incl. H a152/151
21 " " " " : Sex ratio a153/154
22 Residents of rural townships: H size a156/155
23 " " " : Sex ratio a157/158
24 Non-ag. H outside zhen (mostly in CC): Sex ratio a160/161
25 Agric. H outside zhen (mostly in xiang): Sex ratio a163/164
26 Other H outside zhen: Sex ratio a166/167
27 Urban P 2000+: Persons per inclusive H a169/168
28 " " : Sex ratio a170/171
Urbanization
a10141 Urbanization index, inclusive of all zhen a105/102
42 Urbanization index 2000+ a169/102
43 Urbanization index, central towns and higher a907/101
44 Urbanization index, local cities and higher a908/102
Age-sex structure
a10151 Total P: Sex ratio a182/183
52 P 0-4/total P a184/181
53 M 0-4/total M a185/182
54 F 0-4/total F a186/183
55 P 0-4: Sex ratio a185/186
a10156 P 5-9/total P a187/181
57 M 5-9/total M a188/182
58 F 5-9/total F a189/183
59 P 5-9: Sex ratio a188/189
a10160 P 10-14/total P a190/181
61 M 10-14/total M a191/182
62 F 10-14/total F a192/183
63 P 10-14: Sex ratio a191/192
a10164 P 15-19: total P a193/181
65 M 15-19: total M a194/182
66 F 15-19: total F a195/183
67 P 15-19: Sex ratio a194/195
a10168 P 20-24: total P a196/182
69 M 20-24: total M a197/182
70 F 20-24: total F a198/183
71 P 20-24: Sex ratio a197/198
a10172 P 25-29: total P a199/181
73 M 25-29: total M a200/182
74 F 25-29: total F a201/183
75 P 25-29: Sex ratio a200/201
a10176 P 30-34: total P a202/181
77 M 30-34: total M a203/182
78 F 30-34: total F a204/183
79 P 30-34: Sex ratio a203/204
a10180 P 35-39: total P a205/181
81 M 35-39: total M a206/182
82 F 35-39: total F a207/183
83 P 35-39: Sex ratio a206/207
a10184 P 40-44: total P a208/181
85 M 40-44: total M a209/182
86 F 40-44: total F a210/183
87 P 40-44: Sex ratio a209/210
a10188 P 45-49: total P a211/181
89 M 45-49: total M a212/182
90 F 45-49: total F a213/183
91 P 45-49: Sex ratio a212/213
a10192 P 50-54: total P a214/181
93 M 50-54: total M a215/182
94 F 50-54: total F a216/183
95 P 50-54: Sex ratio a215/216
a10196 P 55-59: total P a217/181
97 M 55-59: total M a218/182
98 F 55-59: total F a219/183
99 P 55-59: Sex ratio a218/219
a10200 P 60-64: total P a220/181
01 M 60-64: total M a221/182
02 F 60-64: total F a222/183
03 P 60-64: Sex ratio a221/222
a10204 P 65-69: total P a223/181
05 M 65-69: total M a224/182
06 F 65-69: total F a225/183
07 P 65-69: Sex ratio a224/225
a10208 P 70-74: total P a226/181
09 M 70-74: total M a227/182
10 F 70-74: total F a228/183
11 P 70-74: Sex ratio a227/228
a10212 P 75-79: total P a229/181
13 M 75-79: total M a230/182
14 F 75-79: total F a231/183
15 P 75-79: Sex ratio a230/231
a10216 P 80-84: total P a232/181
17 M 80-84: total M a233/182
18 F 80-84: total F a234/183
19 P 80-84: Sex ratio a233/234
a10220 P 85-89: total P a235/181
21 M 85-89: total M a236/182
22 F 85-89: total F a237/183
23 P 85-89: Sex ratio a236/237
a10224 P 90-94: total P a238/181
25 M 90-94: total M a239/182
26 F 90-94: total F a240/183
27 P 90-94: Sex ratio a239/240
a10228 P 95-99: totalP a241/181
29 M 95-99: total M a242/182
30 F 95-99: total F a243/183
31 P 95-99: Sex ratio a242/243
a10232 P 100+/total P a244/181
33 M 100+/total M a245/182
34 F 100+/total F a246/183
35 P 110+: Sex ratio a245/246
a10236 P 0-9: total P a184+187/181
37 M 0-9: total M a185+188/182
38 F 0-9: total Fa 186+189/183
39 P 0-9: Sex ratio a185+188/186+189
a10240 P 0-14: total P a247/181
41 M 0-14: total M a248/182
42 F 0-14: total F a249/183
43 P 0-14: Sex ratio a248/249
a10244 P 0-19: total P a247+193/181
45 M 0-19: total M a248+194/182
46 F 0-19: total F a249+195/183
47 P 0-19: Sex ratio a248+194/249+195
a10248 P 15-45: total P a193+250/181
49 M 15-45: total M a194+251/182
50 F 15-45: total F a195+252/183
51 P 15-45: Sex ratio a194+251/195+252
a10252 P 15-55: total P a193+250+211+214/181
53 M 15-55: total M a194+251+212+215/182
54 F 15-55: total F a195+252+213+216/183
55 P 15-55: Sex ratio a194+251+212+215/195+252+213+216
a10256 P 20-60: total P a250+211+214+217/181
57 M 20-60: total M a251+212+215+218/182
58 F 20-60: total F a252+213+216+219/183
59 P 20-60: Sex ratio a251+212+215+218/252+213+216+219
a10260 P 60+: total P a220+223+226+253/181
61 M 60+: total M a221+224+227+254/182
62 F 60+: total F a222+225+228+255/183
63 P 60+: Sex ratio a221+224+227+254/222+225+228+255
a10264 P 65+: total P a223+226+253/181
65 M 65+: total M a224+227+254/182
66 F 65+: total F a225+228+255/183
67 P 65+: Sex ratio a224+227+254/225+228+255
a10268 P 70+: total P a226+253/181
69 M 70+: total M a227+254/182
70 F 70+: total F a228+255/183
71 P 70+: Sex ratio a227+254/228+255
a10272 P 75+/total P a253/181
73 M 75+/total M a254/182
74 F 75+/total F a255/183
75 P 75+: Sex ratio a254/a255
a10276 Ratio P 0-4 to P 5-9 a184/187
77 Ratio P 0-4 to P 10-14 a184/190
78 Ratio P 0-4 to P 5-14 a184/187+189
79 Ratio P 5-9 to P 10-14 a187/190
80 Ratio P 0-9 to P 10-14 a184+187/190
Educational attainment
a10281 P 6+: Sex ratio a262/263
a10282 P university educated/P 6+ a264/261
83 M " " /M 6+ a265/262
84 F " " /F 6+ a266/263
85 P " " : Sex ratio a265/266
a10286 P jr. college educated/P 6+ a267/261
87 M " " " /M 6+ a268/262
88 F " " " /F 6+ a269/263
89 P " " " : Sex ratio a268/269
a10290 P secondary technical school educated/P 6+ a270/261
91 M " " " " /M 6+ a271/262
92 F " " " " /F 6+ a272/263
93 P " " " " : Sex ratio a271/272
a10294 P senior middle school educated/P 6+ a273/261
95 M " " " " /M 6+ a274/262
96 F " " " " /F 6+ a275/263
97 P " " " " : Sex ratio a274/275
a10298 P junior middle school educated/P 6+ a276/261
99 M " " " " /M 6+ a277/262
300 F " " " " /F 6+ a278/263
01 P " " " " : Sex ratio a277/278
a10302 P primary school educated/P 6+ a279/261
03 M " " " /M 6+ a280/262
04 F " " " /F 6+ a281/263
05 P " " " : Sex ratio a280/281
a10306 P illiterate/semi-illiterate/P 6+ a282/261
07 M " " /M 6+ a283/262
08 F " " /F 6+ a284/263
09 P " " : Sex ratio a283/284
a10310 P with advanced education/P 6+ a264+267/261
11 M " " " /M 6+ a265+268/262
12 F " " " /F 6+ a266+269/263
13 P " " " : Sex ratio a265+268/266+269
a10314 P educated at least to sr-mid. school/P 6+ a264+267+270+273/261
15 M " " " " " " /M 6+ a265+268+271+274/262
16 F " " " " " " /F 6+ a266+269+272+275/263
17 P " " " " " " : Sex ratio
a265+268+271+274/266+269+272+275
a10318 P uneducated or only primary educ./P 6+ a279+282/261
19 M " " " " " /M 6+ a280+283/262
20 F " " " " " /F 6+ a281+284/263
21 P " " " " " : Sex ratio a280+283/a281+284
Illiteracy
a10331 P 15+: Sex ratio a292/293
32 P 15+: Illiteracy rate a294/291
33 M 15+: Illiteracy rate a295/292
34 F 15+: Illiteracy rate a296/293
35 P illiterates 15+: Sex ratio a295/296
Marital status
a10341 P 15+: Sex ratio a302/303
a10342 P 15+ never married/P 15+ a304/301
43 M 15+ " " /M 15+ a305/302
44 F 15+ " " /F 15+ a306/303
45 P 15+ " " : Sex ratio a305/306
a10346 P 15+ married/P 15+ a307/301
47 M 15+ " /P 15+ a308/302
48 F 15+ " /P 15+ a309/303
49 P 15+ " : Sex ratio a308/309
a10350 P 15+ widowed/P 15+ a310/301
51 M 15+ " /P 15+ a311/302
52 F 15+ " /P 15+ a312/303
53 P 15+ " : Sex ratio a311/312
a10354 P 15+ divorced/P 15+ a313/301
55 M 15+ " /P 15+ a314/302
56 F 15+ " /P 15+ a315/303
57 P 15+ " : Sex ratio a314/315
a10358 P 15+ currently married/P 15+ ever married a307/307+310+313
59 M 15+ " " /M 15+ ever married a308/308+311+314
60 F 15+ " " /F 15+ ever married a309/309+312+315
a10361 P 15+ widowed/P 15+ ever married a310/307+310+313
62 M 15+ " /M 15+ ever married a311/308+311+314
63 F 15+ " /F 15+ ever married a312/309+312+315
a10364 P 15+ divorced/P 15+ ever married a313/307+310+313
65 M 15+ " /M 15+ ever married a314/308+311+314
66 F 15+ " /F 15+ ever married a315/309+312+315
Births and fertility
a10371 Sex ratio, births: 1Jan89-30Jun90 a322/323
72 " " " : 1Jan89-30Jun89 a325/326
73 " " " : 1Jul89-31Dec89 a328/329
74 " " " : 1Jan90-30Jun90 a331/332
75 " " " : 1989 a325+328/326+329
76 " " " : 1Jul89-30Jun90 a328+331/329-332
a10377 Gen'l fertility rate: 1989-90 2/3 x a321/195+252
78 Gen'l fertility rate: 1989 a324+327/195+252
79 Gen'l fertility rate: 1Jul89-30Jun90 a327+330/195+252
a10380 Ratio 1Jan89-30Jun90 births to P 0-4 a321/184
81 " " " to P 5-9 a321/187
82 " " " to P 10-14 a321/190
83 " " " to P 0-9 a321/184+187
84 " " " to P 0-14 a321/247
Deaths and mortality
a10391 Sex ratio, deaths: 1Jan89-30Jun90 a342/343
92 " " " : 1Jan89-30Jun89 a345/346
93 " " " : 1Jul89-31Dec89 a348/349
94 " " " : 1Jan90-30Jun90 a351/352
95 " " " : 1989 a345+348/346+349
96 " " " : 1Jul89-30Jun90 a348+351/349+352
a10397 Crude death rate : 1989-90 2/3 x a341/102
98 Crude death rate : 1989 a344+347/102
99 Crude death rate : 1Jul89-30Jun90 a347+350/102
In-migration
a10401 In-migrants (IM) as pct of adult P a361/181-247
02 Same-prov. IM as pct of adult P a362/181-247
03 IM from same-prov. shi as pct of adult P a363/181-247
04 IM from same-prov. zhen as pct of adult P a364/181-247
05 IM from same-prov. xiang as pct of adult P a365/181-247
a10406 IM from other provinces as a pct of adult P a366/181-247
07 IM from diff-prov. shi as pct of adult P a367/181-247
08 IM from diff-prov. zhen as pct of adult P a368/181-247
09 IM from diff-prov. xiang as pct of adult P a369/181-247
a10410 IM from all shi as pct. of adult P a363+367/181-247
11 IM from all zhen as pct of adult P a364+368/181-247
12 IM from all xiang as pct of adult P a365+369/181-247
a10413 Same-prov. IM as pct of all known IM a362/371
14 IM from same-prov. shi as pct of all IM a363/371
15 IM from same-prov. zhen as pct of all IM a364/371
16 IM from same-prov. xiang as pct of all IM a365/371
a10417 IM from diff-prov. shi as pct of all IM a367/371
18 IM from diff-prov. zhen as pct of all IM a368/371
19 IM from diff-prov. xiang as pct. of all IM a369/371
a10420 IM from all shi as pct of all IM a363+367/371
21 IM from all zhen as pct of all IM a364+368/371
22 IM from all xiang as pct of all IM a365+369/371
Industry/Economic activity
10431 SR (sex ratio) of total LF (labor force) a382/383
32 P in agricultural sector as pct of LF a384/381
33 M in " " " M LF a385/382
34 F in " " " F LF a386/383
35 SR of " " a385/386
10436 P in industrial sector as pct of LF a387/381
37 M " " " M LF a388/382
38 F " " " F LF a389/383
39 SR of " " a388/389
10440 P in mining sector as pct of LF a390/381
41 M " " " M LF a391/382
42 F " " " F LF a392/383
43 SR of " " a391/392
10444 P in construction sector as pct of LF a393/381
45 M " " " M LF a394/382
46 F " " " F LF a395/383
47 SR of " " a394/395
10448 P in transport/communication sector as pct of LF a396/381
49 M " " " M LF a397/382
50 F " " " F LF a398/383
51 SR of " " a397/398
10452 P in commercial sector as pct of LF a399/381
53 M " " " M LF a400/382
54 F " " " F LF a401/383
55 SR of " " a400/401
10456 P in utilities/services sector as pct of LF a402/381
57 M " " " M LF a403/382
58 F " " " F LF a404/383
59 SR of " " a403/404
10460 P in health/welfare sector as pct of LF a405/381
61 M " " " M LF a406/382
62 F " " " F LF a407/383
63 SR of " " a406/407
10464 P in education/entertainment sector as pct of LF a408/381
65 M " " " M LF a409/382
66 F " " " F LF a410/383
67 SR of " " a409/410
10468 P in science/technology sector as pct of LF a411/381
69 M " " " M LF a412/382
70 F " " " F LF a413/383
71 SR of " " a412/413
10472 P in financial sector as pct of LF a414/381
73 M " " " M LF a415/382
74 F " " " F LF a416/383
75 SR of " " a415/416
10476 P in government/organizational sector as pct of LF a417/381
77 M " " " M LF a418/382
78 F " " " F LF a419/383
79 SR of " " a418/419
10480 P in miscellaneous sector as pct of LF a420/381
81 M " " " M LF a421/382
82 F " " F LF a422/383
83 SR of " " a421/422
Occupation (LF=labor force)
a10491 All professional/technical personnel as pct of LF a431/381
92 M " " " M LF a432/382
93 F " " " F LF a433/383
94 SR of " " a432/433
a10495 All officials/officers/managers as pct of LF a434/381
96 M " " M LF a435/382
97 F " " F LF a436/393
98 SR of " a435/436
a10499 All clerical personnel as pct of LF a437/381
a10500 M " " " M LF a438/382
01 F " " F LF a439/383
02 SR of " " a438/439
a10503 All commercial employees as pct of LF a440/381
04 M " " " M LF a441/382
05 F " " " F LF a442/383
06 SR of " " a441/442
a10507 All service employees as pct of LF a443/381
08 M " " " M LF a444/382
09 F " " " F LF a445/383
10 SR of " " a444/445
a10511 All agricultural workers as pct of LF a446/381
12 M " " " M LF a447/382
13 F " " " F LF a448/383
14 SR of " " a447/448
a10515 All industrial workers as pct of LF a449/381
16 M " " " M LF a450/382
17 F " " " F LF a451/383
18 SR of " " a450/451
a10519 All personnel in other/misc occupations as pct of LF a452/381
20 M " " " " M LF a453/382
21 F " " " " F LF a454/383
22 SR of " " " a453/454
Agriculture
a10601 Rural P as pct of total P [persons per ha.] a601/102
a10602 Rural P density " a601/625
a10603 Nutritional density (P/cultivated area) " a601/605
a10604 P/sown area " a601/606
a10605 Rural labor force (LF)/cultivated area " a602/605
a10606 Agricultural LF/cultivated area " a603/605
a10607 Agricultural LF/sown area " a603/606
a10608 Rural LF as pct of total LF a602/381
a10609 Agricultural LF as pct of total LF a603/381
a10610 LF in rural industry as pct of total LF a604/381
a10611 LF in rural industry as pct of total rural LF a604/602
a10612 Cultivated area as pct of total surface area a605/625
a10613 Sown area/cultivated area a606/605
a10614 Grain sown area as pct of all-crops sown area a607/606
a10615 Cotton sown area as pct of all-crops sown area a608/606
a10616 Oil crops sown area as pct of all-crops sown area a609/606
a10617 Grain yields [tons per ha.] a610/607
a10618 Cotton yields " a611/608
a10619 Oil-crop yields " a612/609
a10620 Grain output per capita [tons per 10,000 persons] a610/102
a10621 Grain output per rural capita " a610/601
a10622 Meat output per capita " a613/102
a10623 Meat output per rural capita " a613/601
a10624 Mechanization [10,000 watts per ha. of cultivated land] a614/605
a10625 Tractor-plowed as a pct of cultivated area a615/605
a10626 Irrigated area as a pct of cultivated area a616/605
a10627 Fertilizer per unit of sown area [tons per ha.] a617/606
a10628 Electricity used [10m watt-hours] per ha. of cult. land a618/605
a10629 Per-capitized electr. use [watt-hours per rural person] a618/601
a10630 Per-capitized collective units' product in ¥ (rural P) a619/601
a10631 Per-capitized GVAO in ¥ (rural P) a620/601
a10632 Per-capitized GVAO in ¥ (rural LF) a620/602
a10633 Agricultural productivity [¥ per agricultural LF] a620/603
a10634 Per-capitized adjusted GVAO in ¥ (rural P) a623/601
a10635 Per-capitized adjusted GVAO in ¥ (rural LF) a623/602
a10636 Adjusted agricultural productivity [¥/agric. LF] a623/603
a10637 Per-capitized net VAO in ¥ (rural P) a622/601
a10638 Per-capitized net VAO in ¥ (rural LF) a622/602
a10639 Net agricultural productivity [¥ per agricultural LF] a622/603
a10640 Per-capitized purchased output (rural P) a624/601
a10641 Per-capitized purchased output (rural LF) a624/602