14 July 1994, rev 11 Aug 94
ChinaT Dataset, Central Places 1990
This dataset contains a record for every central place in China that was the central
city of a shi (municipality) or classed as a zhen (town) as of 1 July 1990. Point-
in-time data are for mid-year 1990, unless otherwise noted; annual data are for
calendar year 1990. Population data for both kinds of central places are taken from
the 1990 census tables. Economic and other non-demographic data on the shixiaqu of
municipalities are taken from Zhongguo chengshi tongji nianjian 1991 (Statistical
yearbook of China's municipalities. Beijing: State Statistical Bureau, 1991). Data
on the position of central places in the transport grid were coded from Zhonghua
jenmin gonghe jiaotong tu (Beijing, 1991). The dataset contains 12,163 records, of
which 452 are for central cities of municipalities in existence at mid-year 1990 and
15 are for the central cities of municipalities formed during the second half of 1990.
ID numbers contain 8 digits, the first 6 of which correspond to the ID of the
county-level unit in which the central place is located. Municipal central cities
have been assigned 00 as the final two digits of the ID, except for the 15 cases
whose status changed from zhen to shi during July-Dec 1990. Since these cases are
covered by the municipalities yearbook even though they were only zhen at our
reference date, we have flagged their peculiar status with a special code. The
various zhen within a given county-level unit have been assigned final digits
beginning with 01 in the order of their appearance in the census tables.
The short designation of any variable is a number preceded by t (for "town),
indicating the ChinaT dataset, which is to be distinguished from ChinaA (for "area"),
the 1990 dataset with records for county-level administrative units. Blocks of
variable numbers have been assigned as follows:
t01 - t99 Unit-control variables
t101 - t499 Raw-data variables
t501 - t999 Analytical variables
Non-Han names are not entered in ChinaT because they are not available for most of
the zhen in minority areas. When the central city of a municipality has a non-Han
name, it can be found in the record for that municipality in ChinaA.
© G. William Skinner
Department of Anthropology
University of California
Davis CA 95616
UNIT-CONTROL VARIABLES
t01 1990 ID number (8 digits)
t02 Chinese name
t03 Pinyin name of the central place
t04 Pinyin name of the county-level unit in which it falls
t05 Administrative status of the central place
t06 Type of central place
t08 Assignment to China Proper (1) or Inner Asia (0)
t09-93 Provisional macroregional assignments
------------------------------------------------------------------------------------
t05 Administrative status of the central place, 1990
There are 14 values, defined by position in a cross-tabulation of two dimensions.
One has to do with municipal/zhen status, the other with status as a capital.
cc = central city
Province Prefecture County
Not a
capital capital capital
capital
Cc of municipal province 1
Cc of municipal prefecture 2 4
Cc of prefectural municipality 3 5
Cc of municipal county 6 8
Cc of county municipality 7 9
Zhen 10 11
12
Town not designated shi or zhen 13
14
(Even though they may not be used for records in the tabular dataset, values 13 and
14 are needed to code small towns that appear on our vectorized maps.)
t06 Type of central place
1 Cc of shi as of midyear 1990
2 Zhen or qu at midyear but cc of shi by endyear 1990
3 Zhen (usual type with urban residential committee), apart from (2)
4 Formally a zhen but with no P under urban residential cmt.
5 Qu or diqu (counted as zhen)
6 Xiang seat
7 Paichusuo (police station) (counted as zhen)
8 Mine
9 Site of factory or firm
PROVISIONAL MACROREGIONAL ASSIGNMENTS
Since central places along interregional frontiers may be oriented to more than one
regional economy, it is necessary to have separate binary variables for each of the
regions/subregions.
t09 Inner Asia
t11 Manchuria Proper
t12 Manchuria: Tumen Border
t13 Manchuria: Northeast Border
t14 Manchuria: North Border
t21 North China: North
t22 North China: South
t23 North China: East
t31 Northwest China: Wei-Fen
t32 Northwest China: Upper Yellow River
t41 Upper Yangzi Proper
t42 Upper Yangzi: Upper Han Basin
t51 Middle Yangzi Proper
t52 Middle Yangzi: Gan Basin
t53 Middle Yangzi: Yuan Basin
t54 Middle Yangzi: Guilin
t61 Lower Yangzi Proper
t62 Lower Yangzi: Linhai
t63 Lower Yangzi: Wenzhou
t71 Southeast Coast: Min Basin
t72 Southeast Coast: Zhang-Quan
t73 Southeast Coast: Han Basin
t80 Lingnan
t91 Yungui Proper
t92 Yungui: Guiyang
t93 Yungui: South border
t94 Yungui: Southwest Border
RAW-DATA VARIABLES FROM THE 1990 POPULATION CENSUS
H= household(s)
M = male(s)
F = female(s)
P = population (M+F)
t101 City/town residents: No. of H Table 2-11 (zhen) or a151 (shi)
t102 " " : P Table 2-11 or a152
t103 " " : M " or a153
t104 " " : F " or a154
t105 Non-agric. P of SXQ or township: P Table 2-12 or a159
t106 " " " " : M " or a160
t107 " " " " : F " or a161
t108 Excess or deficit of non-agric. P over residents t105 - t102
t109 Approximate non-agricultural urban P
*
* 1) When t105<t102, t109=t105.
2) When t102=0, figure t109 as t105/3.
3) When t105>t102, calculate t105 as follows:
When t105/t102>1.0 but <2, t109= (t102 + t106)/2
" 2.0 " 3 " = ( " + .95 t106)/2
" 3.0 " 4 " = ( " + .90 " )/2
" 4.0 " 5 " = ( " + .85 " )/2
" 5.0 " 6 " = ( " + .80 " )/2
" 6.0 " 7 " = ( " + .75 " )/2
" 7.0 " 8 " = ( " + .70 " )/2
" 8.0 " 9 " = ( " + .65 " )/2
" 9.0 " 10 " = ( " + .60 " )/2
" 10.0 " 11 " = ( " + .55 " )/2
" 11.0 " = ( " + .50 " )/2
RAW-DATA VARIABLES FROM MUNICIPALITIES YEARBOOK
T=Table
C=Column
Indicators of central functions
t201 Travel: Annual no. of person-trips (add 0,000) T34 C2
t202 Total annual freight by land/sea/air, in 10,000 tons T34 C4
t203 Total commodity sales in ¥10,000 T46 C2
t204 Total commodity circulation costs in ¥10,000 T46 C4
t205 Ann. ave. amt. of commercial capital in circ., ¥10,000 T46 C8
t206 Food processing industry: Output value in ¥10,000 T24 C11
t207 Beverage industry: Output value in ¥10,000 T24 C12
t208 NOT USED
t209 Food and beverages: Output value in ¥10,000 t206+t207
t210 Printing industry: Output value in ¥10,000 T24 C21
t211 GNP of tertiary industry in ¥10,000 T14 C8
t212 Transport/communic.: National income in ¥100 million T13 C7
t213 Commerce/food/drink: National income in ¥100 million T13 C8
t214 Posts/telecommunic: annual gross receipts in ¥10,000 T55 C2
t215 No. of post offices at year-end T55 C1
t216 Total bank loans outstanding at year-end in ¥10,000 T52 C2
t217 Bank loans for investment in liquid assets in ¥10,000 T52 C4
t218 Bank loans for investment in fixed assets in ¥10,000 T52 C6
t219 Bank loans for agriculture outstanding year-end, ¥10,000 T52 C8
t220 Total amount of insurance coverage in ¥10,000 T53 C2
t221 Total insurance premiums paid in ¥10,000 T53 C4
t222 Total insurance payments on claims in ¥10,000 T53 C6
t223 No. of institutions of higher education T66 C2
t224 No. of secondary-level vocational schools T66 C4
t225 No. of middle schools T66 C6
t226 Total no. of secondary schools and higher t223+t224+t225
t227 No. of instructors in higher education T67 C2
t228 No. of teachers in secondary vocational schools T67 C4
t229 No. of middle-school teachers T67 C6
t230 Total no. of teachers, secondary and higher t227+t228+t229
t231 Enrolled students in higher education T68 C2
t232 Enrollment in secondary vocational schools T68 C4
t233 Enrollment in middle schools T68 C6
t234 Total enrollments, secondary schools and higher t231+t232+t233
t235 No. of facilities for showing movies T70 C2
t236 No. of movie theaters T70 C4
t237 No. of public libraries T70 C6
t238 Total holdings of public libraries, in 1000 volumes T70 C8
t239 Total no. of health-care agencies T72 C1
t240 No. of hospitals T72 C2
t241 No. of beds in all health-care agencies T72 C3
t242 No. of hospital beds T72 C4
t243 No. of technical health-care personnel T72 C5
t244 No. of medical doctors T72 C6
Other economic variables
t251 No. of telephones at year-end T55 C3
t252 Annual electricity consumption in 100 million kw hrs T55 C5
t253 Residential electricity consumption in 100 m kw hrs T55 C7
t254 Total deposited savings at year-end in ¥10,000 T64 C6
t255 Total national income in ¥100 million T13 C1
t256 Agriculture: National income in ¥100 million T13 C2
t257 Industry: National income in ¥100 million T13 C3
t258 Light industry: National income in ¥100 million T13 C4
t259 Heavy industry: National income in ¥100 million T13 C5
t260 Construction industry: National income in ¥100 million T13 C6
t261 Domestic GNP in ¥100 million T14 C2
t262 GNP of primary industry in ¥100 million T14 C4
t263 GNP of secondary industry in ¥100 million T14 C6
t264 GVIAO in ¥100 million T15 C6
t265 GVIO in ¥100 million T22 C2
t266 GVIO of light industry in ¥100 million T22 C4
t267 GVIO of heavy industry in ¥100 million T22 C6
t268 GVIO of state enterprises in ¥100 million T23 C2
t269 GVIO of collective enterprises in ¥100 million T23 C4
t270 Labor force, state/collective enterprises (add 0,000) T10 C2
t271 Workers in state/coll. primary industry (add 0,000) T10 C4
t272 Workers in state/coll. secondary industry (add 0,000) T10 C6
t273 Workers in state/coll. tertiary industry (add 0,000) T10 C8
t274 Labor force in private sector T11 C2
t275 No. of state industrial enterprises T20 C2
t276 No of collective industrial enterprises T20 C4
Miscellaneous variables
t281 Surface area in sq. km. T09 C2
t282 Built-up area in sq. km. T09 C3
ANALYTICAL VARIABLES: DEMOGRAPHIC
t501 H size of city/town residents t102/t101
t502 Sex ratio of city/town residents t103/t104
t503 Sex ratio of the nonagricultural P t106/t107
t504 Approx. P density of built-up area, persons/sq.km. t102/t282
t505 P density of the SXQ, persons/sq.km. T09 C8
t506 Crude birth rate, 1989-90 T08 C2
t507 Crude death rate, 1989-90 T08 C4
t508 State/collective workers: Primary-ind. pct of total t271/t270
t509 State/collective workers: Secondary-ind. pct of total t272/t270
t510 State-collective workers: Tertiary-ind. pct of total t273/t270
t511 Private-sector as pct of total labor force t274/t274+t270
ANALYTICAL VARIABLES: CONSUMPTION AND SERVICES
t551 Travel: Trips per capita t201/t102
t552 Retail sales per capita t203/t102
t553 Food processing industry: Output value per capita t206/t102
t554 Food/drink industry: Output value per capita t209/t102
t555 Printing industry: Output value per capita t210/t102
t556 Per capita GNP of tertiary industry t211/t102
t557 Commerce/food/drink: National income per capita t213/t102
t558 Posts/Telecomm. business per capita t214/t102
t559 Insurance coverage per capita t220/t102
t560 Higher education: Students per H t231/t101
t561 Higher education: Students per capita t231/t102
t562 Vocational-school students per H t232/t101
t563 Vocational-school students per capita t232/t102
t564 Middle-school students per H t233/t101
t565 Middle-school students per capita t233/t102
t566 Public library holdings: Volumes per capita t238/t102
t567 Health-agency beds per capita t241/t102
t568 Health-care professionals per capita t243/t102
t569 Medical doctors per capita t244/t102
t570 Telephones per 100 persons (cf. T55 C4) t251/t102
t571 Residential electricity consumption per capita t253/t102
t572 Annual income per capita T64 C1
t573 Expenditures per capita T64 C2
t574 Annual outlay for food per capita T64 C3
t575 Annual outlay for clothing per capita T64 C4
t576 Annual outlay for other daily necessities per capita T64 C5
t577 Savings per capita at year-end (cf. T64 C7) t254/t102
ANALYTICAL VARIABLES: ORGANIZATIONAL ECOLOGY
t601 Average receipts per post office t214/t215
t602 Average P served per post office t102/t215
t603 Higher education: Instructors per institution t227/t223
t604 Higher education: Students per institution t231/t223
t605 Higher education: Students per instructor t231/t227
t606 Vocational schools: Teachers per school t228/t224
t607 Vocational schools: Students per school t232/t224
t608 Vocational schools: Students per teacher t232/t228
t609 Middle schools: Teachers per school t229/t225
t610 Middle schools: Students per school t233/t225
t611 Middle schools: Students per teacher t233/t229
t612 Secondary+: Instructors per institution t230/t226
t613 Secondary+: Students per institution t234/t226
t614 Secondary+: Students per instructor t234/t230
t615 Average P served per movie facility t102/t235
t616 Average P served per movie theater t102/t236
t617 Average P served per public library t102/t237
t618 Mean library size (holdings per library) t238/t237
t619 Average P served per health-care agency t102/t239
t620 Mean no. of beds per health-care agency t241/t239
t621 Mean no. of health professionals per health agency t243/t239
t622 Average P served by hospital t102/t240
t623 Mean no. of beds per hospital (hospital size) t242/t240
t624 Mean no. of medical doctors per hospital t244/t240
t625 Average GVIO per state industrial enterprise t268/t275
t626 Average GVIO per collective enterprise t269/t276
t627 Mean no. of workers per state/coll. enterprise t270/t275+t276
ANALYTICAL VARIABLES: ECONOMIC
t651 Annual freight per capita t202/t102
t652 Annual freight in relation to domestic GNP t202/t261
t653 Commodity sales in relation to circulation costs t203/t204
t654 Commodity sales in relation to capital in circ. t203/t205
t655 Commodity circ. costs in relation to capital in circ t204/t205
t656 Food/beverages output value as pct of nat'l income t209/t255
t657 GNP of primary industry as pct of total GNP t262/t261
t658 GNP of secondary indsutry as pct of total GNP t263/t261
t659 GNP of tertiary industry as pct of total GNP t211/t261
t660 Transport/comm. nat'l income as pct of total t212/t255
t661 Commerce/food/drink nat'l income as pct of total t213/t255
t662 Outstanding bank loans in relation to total savings t216/t254
t663 Bank loans in relation to national income t216/t255
t664 Bank loans in relation to domestic GNP t216/t261
t665 Bank loans: ratio of fixed to liquid assets t218/t217
t666 Loans to agriculture as pct of all bank loans t219/t216
t667 Bank loans per capita t216/t102
t668 Insurance: Ratio of premiums to coverage t221/t220
t669 Insurance: Ratio of payments to coverage t222/t220
t670 Insurance: Ratio of payments to premiums t222/t221
t671 Insurance coverage in relation to nat'l income t220/t255
t672 Insurance coverage in relation to domestic GNP t220/t261
t673 No. of telephones in relation to national income t251/t255
t674 Electrcity use in relation to domestic GNP t252/t261
t675 Electricity use in relation to national income t252/t255
t676 Electricity use in relation to GVIAO t252/t264
t677 Residential electricity consumption as pct of total t253/t252
t678 Savings in relation to national income t254/t255
t679 National income from agriculture as pct of total t256/t255
t680 National income from industry as pct of total t257/t255
t681 Nat'l income from light industry as pct of total t258/t255
t682 Nat'l income from heavy industry as pct of total t259/t255
t683 National income from construction as pct of total t260/t255
t684 National income per capita t255/t102
t685 GNP of primary industry as pct of total GNP t262/t261
t686 GNP of secondary industry as pct of total GNP t263/t261
t687 GNP per capita t261/t102
t688 GVIAO per capita t264/t102
t689 GVIO per capita t265/t102
t690 GVIO of light industry as pct of total GVIO t266/t265
t691 GVIO of heavy industry as pct of total GVIO t267/t265
t692 GVIO of state enterprises as pct of total GVIO t268/t265
t693 GVIO of collective enterprises as pct of total GVIO t269/t265
t694 GVIO per worker, state/collective enterprises t268+t269/t270
CONSTRUCTED ANALYTICAL VARIABLES
t701 Municipal centrality index
t702 Level in the central-place hierarchy
T701 Municipal centrality index
Weight Component
.094 t216 Total bank loans outstanding at year end
.093 t244 No. of medical doctors
.093 t239 No. of health-care agencies
.093 t211 GNP of tertiary industry
.092 t210 Output value of the printing industry
.091 t203 Total commodity sales
.089 t230 No. of teachers, secondary schools and higher
.089 t238 Total holdings (volumes) of public libraries
.089 t214 Annual gross receipts of Posts/Telecommunications
.089 t206 Output value of food-processing industry
.088 t202 Total annual freight by land/sea/air
_________
1.000
Each component has a Pearson correlation coefficient of .80 or higher with every
other component.
t702 Level in the central-place hierarchy
1 A Apex metropolis
2 C Central metropolis
3 M Regional metropolis
4 R Regional city
5 G Greater city
6 L Local city
7 T Central town
8 I Intermediate town
9 S Standard market town
0 Suburban center not counted as an independent central place