NSSO_53_Schedule_2.41.2_Trade DDI-IND-MOSPI-NSSO-53Rnd-Sch2.41.2-1997

M.RBALAKRISHNAN

Computer Centre 2012-06-05 Nesstar Publisher Version 1.0 (June 2012) Trade Survey: NSS 53rd Round, Schedule 2.41.2, January 1997 - December 1997 Non Directory and Own Account Trading Establishments/Enterprises DDI-IND-MOSPI-NSSO-53Rnd-Sch2dot41dot2-1997 National Sample Survey Office

Governing council and Working Group

Survey Design Reearch Division Field Operations Division Data Processing Division Computer Centre Nesstar Publisher M/o Statistics & Programme Implementation, GOI ADG, SDRD , NSSO Socio-Economic/Household Survey Earlier, NSSO covered own account trading enterprises and non-directory trading establishments for survey in its 41st (1985-86) & 46th (1990-91) rounds. As a follow-up survey of the Third Economic Census which was conducted in the year 1990, National Sample Survey Organ­isation conducted a survey on small trading units in its 53rd round. The objective of the survey was to throw up estimates of some important characteistics like number of enterprises, number of workers, value added and trade margins of commodities sold by the enterprises on the basis of the samples selected. The coverage of the fifty-third round of the NSS was restricted to all non-directory trading establishments(NDTEs) and own ac­count trading enterprises (OATEs) except the public sector trad­ing enterprises/establishments. The term 'enter­prise' meant trading enterprises as well as establishments.The other part, comprising Directory Trading Establishments (DTEs), which employ six or more workers, had been surveyed separately under the technical guidance of the Central Statistical Organisation during October 1 996 to September 1997. As such, information for the entire trade sector becomes available for the period 1996-97. India The survey covered the whole of the Indian Union excepting (i) Ladakh & Kargil districts of J & K (ii) 768 interior villages of Nagaland situated beyond 5 kms. of the bus route and (iii) 195 villages of A & N Islands which remain inaccessible throughout the year. Randomly selected Enterprises/establishments based on sampling procedure The survey used the interview method of data collection from a sample of randomly selected enterprises/establishments Sample survey data [ssd] Trade Survey NSS 53rd Round Schedule 2.41.2 January 1997 - December 1997 Field Operations Division of Naional Sample Survey Office A stratified two-stage sampling design was adopted for the survey. The first stage units (FSUs) were the villages (panchayat wards in case of Kerala) in the rural sector and UFS blocks in the urban sector. The second-stage units were the OATEs and NDTEs for the trade survey. The total all -India sample size of FSUs was allocated to different States/U.Ts in proportion to the number of workers engaged in OATEs/NDTEs in the respective States/U.Ts ( estimated as number of OATE/NDTE as per EC '90 multiplied by estimated number of workers per enterprise based on NSS 46th round) subject to a minimum allocation given to the State/U.Ts depending upon the total number of districts and town classes for the State/U.T. The State/U.T level sample size was again allocated to the rural and urban sectors in proportion to the number of workers. Rural sector design Sampling frame : The list of villages showing number of OATEs and NDTEs as per 1990 Economic Census was used for selection of villages in the States/U.Ts wherever such frame was available. For Kerala, list of Panchayat wards giving count of OATEs /NDTEs has been used as the frame for selecting Panchayat wards f or the the survey instead of villages. For Jammu & Kashmir, the 1981 census lists of villages forms the frame. For Andaman & Nicober islands, Lakshadweep and 5 districts of Madhya Pradesh, 1991 census lists were used as frame. For Andaman & Nicober Islands, villages remaining inaccessible throughout the year were excluded from the frame. For Nagaland, onlyvillages connected by bus or situated within 5 kms of the bus route were included in the frame. Stratification : Each district generally formed a broad stratum. However, for Gujarat, where NSS regions cut across district boundaries, parts of each such part of a district formed a separate stratum. If any district (or part thereof lying in an NSS region in case of Gujarat) had a small number of trading enterprises, it was clubbed with a neighbouring district to form a broad stratum in order to ensure a minimum allocation. To net an adequate number of NDTEs in the sample, each broad stratum was divided into two area types : (i) Area type 1 consisting of villages having at least one NDTE, and (ii) Area type 2 consisting of the remaining villages of the broad stratum. Where population census frames were used for selection of fsus , there was no division as above. In such cases, all the villages were classified in area type 2. Allocation of sample villages among strata and area types : The State/U.T level rural sample size was allocated among the strata in proportion to number of workers. While allocating as above, it was maintained that NSS region level allocation were multiples of 8 and stratum level allocation is at least 4 but in multiples of 2. This was done in order to allocate at least two fsu's to each of the area types. The stratum level allocation was again di stributed between two area types in proportion to number of NDTEs and OATEs taking into consideration that allocation for each area type was in multiples of 2. Selection of fsu's : Villages were selected in the form of two independent sub-sampl es from each broad stratum X area type using circular systematic sampling with probability proportional to size, the size being the number of (OATE NDTE) for area type 1 and the number of OATEs ( after assigning a size of 1 to the fsu's having no tradi ng enterprise) for area type 2. Where population census frame was used, villages were selected using circular systematic sampling with probability proportional to population. For Lakshadweep and A & N Islands, however, equal probability sampling was adopted. Urban sector design : Sampling Frame : The latest available list of UFS blocks was used as sampling frame for selection of fsu's for all cities and towns. Stratification : Town classes (broad strata) were formed within each district by grouping cities/towns according to population sizes as per '91 census. To net adequate number of trading enterprises in the sample, each town class was divided into two area types. Area type 1 consisted of the UFS blocks designated as 'bazar area' and area type 2 consisting of the remaining blocks of the town class. Allocation of sample blocks among districts, town classes and area types : The state/u..t. level urban allocation is allocated among the districts and town classes in proportion of the number of workers. It is, however, ensured that NSS region level allocations were in multiples of 8 and town class level allocations were at least 4 and were in multiples of 2. Town class level allocations were further allocated between two area types in such a way that UFS blocks of area type 1 get completely surveyed (central and state samples combined) subject to a maximum of 50% of allocation for town class level. Area type wise allocations were in multiples of 2. Selection of blocks : For both the area types, sample blocks were selected circular systematically in the form of two independent sub-samples with equal probability. Sampling of enterprises : All the OATEs and NDTEs of the selected village/block excluding those in the public sector and which operated for at least 30 days (15 days in case of seasonal enterprises) during the last 365 days preceding the date of survey were considered for sampling. All such, eligible enterprises were classified into three classes termed as 'enterprise class' according to the total number of workers (including hired workers) employed in the enterprises on a regular basis. The classes were as follows : ---------- ------------------------------------------------------------------------ Enterprise Composition of the class class code ------------------------------------------ ---------------------------------------- 1 all OATEs and NDTEs with one worker only. 2 all OATEs and NDTEs with two workers only. 3 all OATEs and NDTEs with three or more workers. ----------------------------------------------------------------------------------- Before selecting enterprises from enterprise classes, all the enterprises within an enterprise class were arranged in ascending order of their NIC codes. The number of enterprises selected from enterprise classes 1, 2 and 3 were 4, 6 and 6 respectively. If there is a shortfall in enterprise class 3, it is made up from enterprise class 2, if possible, otherwise from enterprise class 1. Similarly, if there is a shortfall in enterprise class 2, it is made up from enterprise class 3, failing which from enterprise class 1. The priority order for compensation is 3rd, 2nd and 1st enterprise class. The required number of enterprises were selected from each enterprise class circular systematically with equal probability. There was no deviation from the original sampling design Face-to-face [f2f] Computer Centre Validated unit level data relating to various survey rounds are available on CD-ROMS which can be obtained from the Deputy Director General, Computer Centre, M/O Statistics and PI, East Block No. 10 R.K. Puram, New Delhi-110066 by remitting the price along with packaging and postal charges as well as giving an undertaking duly signed in a specified format.The amount is to be remitted by way of demand draft drawn in favour of Pay & Accounts Officer, Ministry of Statistics & Programme Implementation, payable at New Delhi. The user of the data acknowledges that the original collector of the data, the authorized distributor of the data, and the relevant funding agency bear no responsibility for use of the data or for interpretations or inferences based upon such uses. Block-1-ID Particularts of Enterprises-Records.NSDstat Contains coded identification of sample enterprise 155675 22 Nesstar 200801 NSSO Block-2-Enterprise-Operation-Information-Records.NSDstat 155675 38 Nesstar 200801 NSSO Block-3-Employment-in-enterprise-Records.NSDstat Contains information on employment particulars (fulltime/partitime hired workers and other workers) of enterprise 538701 19 Nesstar 200801 NSSO Block-4-Commodity_purchased-sold-Records.NSDstat Account of commodities purchased and sold during the month by the enterprise inrespect of 73 specified commodity groups are the content of this dataset. 1057492 21 Nesstar 200801 NSSO Block-5-Expenditure-profit-Records.NSDstat This dataset contains expenditures (expenditure incurred on account of the trading activity only)of the enterprise excluding the commodities purchased and Surplus or profit of the enterprise. Payable approach is followed to record the entries 1246918 19 Nesstar 200801 NSSO Block-6-Gross-value-added-enterprise-Records.NSDstat Gross Value Added during the reference month by the enterprise will be calculated and recorded in this dataset 1457527 19 Nesstar 200801 NSSO Block-7-Trade-Margin-commodity-Records.NSDstat The trade margins for the same set of 73 commodity groups specified in Block 4 are the content of this dataset. 908830 19 Nesstar 200801 Block-8-Records.NSDstat This dataset contains particulars of Field Operations. 154281 20 Nesstar 200801 NSSO Key to locate enterprise 155675 0 Key generated using FSU_no and sample enterprise no (B1_q14) to locate a unique enterprise number Record identifier (indicate Block no.) 155675 0 Number to identify the block number of schedule 01 155675 Round Schedule 155675 0 Indicate NSS survey round and schedule 532 NSS 53rd Round schedule 2.41.2 155675 Sector Sector code 155675 0 n the NSS, the domains of study are usually rural and urban areas within a zone, state, region or district. The rural and urban areas of the country are taken as adopted in the latest population census. 1 Rural 72529 2 Urban 83146 Sub round Sub-Round 155675 0 1 Sub-round-1 46189 2 Sub-round-2 46284 3 Sub-round-3 38319 4 Sub-round-4 24883 Sub sample Sub-sample 155675 0 1 Sub-sample-1 78937 2 Sub-sample-2 76738 State State code 155675 0 States and Union Territories are the broad domains of study in the NSS. They are assigned 2 digited codes, 02 Andhra Pradesh 12109 03 Arunachal Pradesh 386 04 Assam 4443 05 Bihar 12269 06 Goa 359 07 Gujarat 6864 08 Haryana 4031 09 Himachal Pradesh 1033 10 Jammu & Kashmir 768 11 Karnataka 8763 12 Kerala 6794 13 Madhya Pradesh 9722 14 Maharashtra 12464 15 Manipur 671 16 Meghalaya 392 17 Mizoram 367 18 Nagaland 815 19 Orissa 7360 20 Punjab 5807 21 Rajasthan 7458 22 Sikkim 465 23 Tamil Nadu 12214 24 Tripura 749 25 Uttar Pradesh 24443 26 West Bengal 11878 27 A & N Islands 209 28 Chandigarh 384 29 Dadra & Nagar Haveli 193 30 Daman & Diu 285 31 Delhi 1437 32 Lakshdweep 118 33 Pondicherry 425 Region Region code 155675 0 States have been divided into regions by grouping contiguous districts similar in respect of population density and crop pattern. In Gujarat, however, some districts have been split for the purpose of region formation, considering the location of dry areas and the distribution of tribal population in the state. 1 Region-1 45872 2 Region-2 47187 3 Region-3 29639 4 Region-4 24047 5 Region-5 6441 6 Region-6 1480 7 Region-7 1009 District code District code 155675 0 Town class Town class code 83146 0 Town classes (broad strata) were formed within each district by grouping cities/towns according to population sizes as per ‘91 census. 1 All towns with populat ion less than 1 lakh 44269 2 18993 3 7028 4 Each city with population 10 lakhs or more. 12856 Area type Area type code 155675 0 1 Area-1 94273 2 Area-2 61402 FSU srl. no. First Stage Unit Serial no. 155675 0 Enterprise class Enterprise class 155675 0 1 All OATEs and NDTEs with one worker only 70358 2 All OATEs and NDTEs with two worker only 59140 3 All OATEs and NDTEs with 3 workers or more 26177 Sample Ent. no. Sample Enterprise no. 155675 0 01 30036 02 26494 03 23721 04 21442 05 15102 06 13343 07 6830 08 5461 09 4233 10 3178 11 2258 12 1544 13 855 14 591 15 371 16 216 Enterprise type Enterprise type On the basis of the type of workers (hired or others), an enterprise will be classified as OATE or NDTE. If the enterprise has hired at least one worker on a fairly regular basis during the last 365 days and if total no. of workers (hired and others taken together) is less than six then it is an NDTE and code 2 may be recorded against this item.If the enterprise has not hired any worker on regular basis during the last 365 days and worked with household workers only then it is an OATE and code 1 may be recorded against this item. Note that, the enterprise type will be determined on the date of survey and the schedule will be canvassed on the basis of it. 155675 0 1 Own account trading enterprise(OATE) 131195 2 Non-directory trading enterprises (NDTE) 24480 Type of trade Type of trade 155675 0 1 Wholesale 8254 2 Retail 140182 3 Commission Agent 2202 4 Auctioneering services 17 9 Others 5020 Informants' reltation Informants' reltation code The person who is giving most of the information will be treated as informant and his/her relationship to the enterprise will be recorded in terms of code. 155675 0 1 132426 2 Manager 4468 3 Relative 17104 9 1677 Response code Response code 155675 0 1 116912 2 Inform¬ant co-operative but not capable 30114 3 7704 9 945 Survey code Survey code The reason for substitution of the original enterprise may be ascertained and code may be recorded. 155675 0 1 originally selected enterprise surveyed 152745 2 2930 3 0 Reason for substitution Reason for substitution 2930 0 1 159 2 Informant not available in the village/block 1739 3 707 9 325 Multiplier (subsample 1 or 2) (0.00) 155675 0 0.04 65771.57 185.382 530.223 Multiplier to be used for sub-sample wise estimate Multiplier (subsamples combined)(0.00) 155675 0 0.02 32885.79 93.173 265.879 Multiplier to be used for combined estimate Key to locate enterprise Same as given in dataset of Block-1 155675 0 Same as given in dataset of Block-1 Record Identifier Same as given in dataset of Block-1 155675 0 Same as given in dataset of Block-1 02 Block - 2 of schedule 155675 Round Schedule Same as given in dataset of Block-1 155675 0 Same as given in dataset of Block-1 532 NSS 53 Round-schedule 2.41.2 155675 Sector Same as given in dataset of Block-1 155675 0 Same as given in dataset of Block-1 1 Rural 72529 2 Urban 83146 Sub round Same as given in dataset of Block-1 155675 0 Same as given in dataset of Block-1 1 Sub-round-1 46189 2 Sub-round-2 46284 3 Sub-round-3 38319 4 Sub-round-4 24883 Sub sample Same as given in dataset of Block-1 155675 0 Same as given in dataset of Block-1 1 Sub-sample-1 78937 2 Sub-sample-2 76738 State Same as given in dataset of Block-1 155675 0 Same as given in dataset of Block-1 02 Andhra Pradesh 12109 03 Arunachal Pradesh 386 04 Assam 4443 05 Bihar 12269 06 Goa 359 07 Gujarat 6864 08 Haryana 4031 09 Himachal Pradesh 1033 10 Jammu & Kashmir 768 11 Karnataka 8763 12 Kerala 6794 13 Madhya Pradesh 9722 14 Maharashtra 12464 15 Manipur 671 16 Meghalaya 392 17 Mizoram 367 18 Nagaland 815 19 Orissa 7360 20 Punjab 5807 21 Rajasthan 7458 22 Sikkim 465 23 Tamil Nadu 12214 24 Tripura 749 25 Uttar Pradesh 24443 26 West Bengal 11878 27 A & N Islands 209 28 Chandigarh 384 29 Dadra & Nagar Haveli 193 30 Daman & Diu 285 31 Delhi 1437 32 Lakshdweep 118 33 Pondicherry 425 Region Same as given in dataset of Block-1 155675 0 Same as given in dataset of Block-1 1 Region-1 45872 2 Region-2 47187 3 Region-3 29639 4 Region-4 24047 5 Region-5 6441 6 Region-6 1480 7 Region-7 1009 District code Same as given in dataset of Block-1 155675 0 Same as given in dataset of Block-1 01 12362 02 7246 03 5018 04 6290 05 5690 06 6857 07 6568 08 6733 09 5433 10 8880 11 5342 12 7229 13 6740 14 5209 15 4245 16 5898 17 3527 18 3072 19 2688 20 2897 21 2415 22 2254 23 2691 24 1551 25 1489 26 1228 27 1727 28 1244 29 1024 30 940 31 512 32 1283 33 1040 34 873 35 642 36 567 37 983 38 785 39 749 40 846 41 584 42 565 43 1244 44 979 45 1066 46 507 47 433 48 407 49 546 50 516 51 231 52 294 53 370 54 662 55 876 56 249 57 497 58 638 59 386 60 477 61 929 62 280 63 172 Town class Same as given in dataset of Block-1 83146 0 Same as given in dataset of Block-1 1 All towns with populat ion less than 1 lakh 44269 2 18993 3 7028 4 Each city with population 10 lakhs or more. 12856 Area type Same as given in dataset of Block-1 155675 0 Same as given in dataset of Block-1 1 Area-1 94273 2 Area-2 61402 FSU srl. no. Same as given in dataset of Block-1 155675 0 Same as given in dataset of Block-1 Enterprise class Same as given in dataset of Block-1 155675 0 1 All OATEs and NDTEs with one worker only 70358 2 All OATEs and NDTEs with two worker only 59140 3 All OATEs and NDTEs with 3 workers or more 26177 Sample Entprise. no. Same as given in dataset of Block-1 155675 0 01 30036 02 26494 03 23721 04 21442 05 15102 06 13343 07 6830 08 5461 09 4233 10 3178 11 2258 12 1544 13 855 14 591 15 371 16 216 NIC-description-recorded Industry activity description 112752 0 NIC - code Industrial activity code (NIC-1987-4digited code) See NIC-Decscr for details 155675 0 0400 9 0520 1405 0530 68 0540 1229 0590 18 0600 756 0610 1475 0630 9 0690 51 6001 304 6002 669 6011 352 6012 273 6013 154 6014 605 6015 119 6019 206 6021 38 6022 195 6023 2 6024 5 6029 7 6031 33 6032 66 6033 16 6041 70 6049 63 6051 464 6052 24 6061 42 6062 207 6063 68 6064 13 6069 63 6071 79 6072 103 6073 34 6080 12 6091 88 6092 388 6093 60 6094 91 6095 88 6096 9 6099 108 6100 55 6108 49 6109 28 6110 138 6120 144 6130 85 6140 33 6150 496 6160 56 6170 140 6180 75 6191 4 6192 64 6201 40 6202 25 6210 98 6220 34 6231 25 6232 8 6233 18 6234 35 6235 49 6236 1 6300 23 6310 205 6320 111 6330 88 6340 28 6350 27 6360 21 6370 58 6380 376 6391 29 6392 15 6399 455 6400 1392 6410 253 6420 72 6490 485 6500 34663 6510 9786 6520 2338 6530 4787 6540 1233 6550 15314 6560 868 6590 2913 6601 828 6602 841 6603 4272 6609 1709 6611 666 6612 2877 6613 160 6701 565 6702 350 6703 52 6708 350 6709 464 6710 1950 6721 326 6722 306 6730 1762 6740 501 6751 1197 6752 770 6753 265 6754 29 6759 845 6760 1007 6791 139 6792 52 6799 881 6800 2485 6810 1892 6820 493 6830 3447 6840 602 6850 339 6860 2078 6870 3887 6881 636 6882 2766 6883 9870 6884 37 6885 4920 6886 2298 6888 194 6889 1346 6891 861 6892 1121 6893 363 6899 5481 8900 17 Duration-opern Duration of operation 155675 0 1 Perennial 150958 2 Seasonal 4041 3 Casual 676 No. of months Number of months operated during the last 365 days 155675 0 No. of days operated Number of days operated in the last working month 155675 0 Whether accts. maintained 155675 0 1 Yes 20388 2 No 135287 Sex of the owner Sex of the owner is to be recorded here in terms of codes (male - 1, female - 2 ). For partnership enterprises, 'owner' will mean the partner having major share in the enterprise. 155675 0 1 Male 145969 2 Female 9579 9 Invalid 127 Social group Social group of the owner 155675 0 1 5644 2 11783 3 33505 8 Invalid 127 9 Others 104616 Building&others owned value (Rs) of fixed assets owned as on the date of survey 88790 66885 0 9110000 53511.603 Building&others rented value (Rs) of fixed assets owned as on the date of survey See B2_q8 for details 50300 105375 Transport equip owned value (Rs) of fixed assets owned as on the date of survey See B2_q8 for details 54571 101104 Transport equip rented value (Rs) of fixed assets owned as on the date of survey See B2_q8 for details 2554 153121 Other fxd. Aset owned value (Rs) of fixed assets owned as on the date of survey See B2_q8 for details 144471 11204 Other fxd. Aset rented value (Rs) of fixed assets owned as on the date of survey See B2_q8 for details 2362 153313 net addition-building&others owned Net additions to fixed assets during last year 5305 150370 0 3000000 25623.667 87210.771 net addition-building&others rented Net additions to fixed assets during last year See B2_q15 for details 2176 153499 0 2500000 75597.065 133908.073 net addition-transport equip owned Net additions to fixed assets during last year See B2_q15 for details 4508 151167 0 700000 6388.629 30137.097 net addition-transport equip rented Net additions to fixed assets during last year See B2_q15 for details 195 155480 2 154000 7827.251 20676.783 net addition-other fxd. Aset owned Net additions to fixed assets during last year See B2_q15 for details 17580 138095 1 1200000 4004.958 15816.945 net addition-other fxd. Aset rented Net additions to fixed assets during last year See B2_q15 for details 510 155165 0 210969 6490.755 18908.556 status of the enterprise Status of the enterprise over last 3 years 154545 0 1 47960 2 87682 3 enterprise is shrinking gradually in the last 3 years 18903 problems faced Problems faced by the enterprise in its operation This item will record the various problems faced by the enter­prise in its day-to-day operation in terms of 7 codes. 154545 0 1 62339 2 7021 3 19430 4 lack of electricity/lighting facility 599 5 5227 6 13125 8 Invalid 5449 9 41355 Multiplier (subsample 1 or 2) 155675 0 0.04 65771.57 185.382 530.223 Same as given in dataset of Block-1 Multiplier (subsamples combined) 155675 0 0.02 32885.79 93.173 265.879 Same as given in dataset of Block-1 Key to locate enterprise As given in dataset of Block-1 538701 0 As given in dataset of Block-1 Record Identifier As given in dataset of Block-1 538701 0 As given in dataset of Block-1 03 538701 Round Schedule As given in dataset of Block-1 538701 0 As given in dataset of Block-1 532 NSS 65 Round-schedule 2.41.2 538701 Sector As given in dataset of Block-1 538701 0 As given in dataset of Block-1 1 Rural 247281 2 Urban 291420 Sub round As given in dataset of Block-1 538701 0 As given in dataset of Block-1 1 Sub-round-1 161671 2 Sub-round-2 160098 3 Sub-round-3 132565 4 Sub-round-4 84367 Sub sample As given in dataset of Block-1 538701 0 As given in dataset of Block-1 1 Sub-sample-1 273571 2 Sub-sample-2 265130 State As given in dataset of Block-1 538701 0 As given in dataset of Block-1 02 Andhra Pradesh 43902 03 Arunachal Pradesh 1362 04 Assam 15458 05 Bihar 40595 06 Goa 1289 07 Gujarat 23912 08 Haryana 13763 09 Himachal Pradesh 3567 10 Jammu & Kashmir 2506 11 Karnataka 30465 12 Kerala 24211 13 Madhya Pradesh 32793 14 Maharashtra 44952 15 Manipur 2374 16 Meghalaya 1440 17 Mizoram 1332 18 Nagaland 2849 19 Orissa 25084 20 Punjab 20358 21 Rajasthan 25560 22 Sikkim 1731 23 Tamil Nadu 43752 24 Tripura 2625 25 Uttar Pradesh 80933 26 West Bengal 40769 27 A & N Islands 781 28 Chandigarh 1513 29 Dadra & Nagar Haveli 751 30 Daman & Diu 1007 31 Delhi 5075 32 Lakshdweep 380 33 Pondicherry 1612 Region As given in dataset of Block-1 538701 0 As given in dataset of Block-1 1 Region-1 161843 2 Region-2 161827 3 Region-3 102349 4 Region-4 82258 5 Region-5 21901 6 Region-6 5126 7 Region-7 3397 District code As given in dataset of Block-1 538701 0 As given in dataset of Block-1 01 44949 02 25448 03 17260 04 21638 05 19783 06 23588 07 23254 08 23622 09 18687 10 31374 11 18685 12 24940 13 22928 14 18056 15 14573 16 20408 17 12263 18 10431 19 9243 20 9907 21 8384 22 7785 23 9320 24 5340 25 5196 26 4194 27 5940 28 4273 29 3481 30 3171 31 1710 32 4318 33 3455 34 2868 35 2072 36 1883 37 3279 38 2690 39 2489 40 2877 41 1985 42 1870 43 4086 44 3258 45 3604 46 1691 47 1419 48 1312 49 1814 50 1696 51 756 52 982 53 1247 54 2235 55 2884 56 817 57 1669 58 2119 59 1260 60 1566 61 3141 62 960 63 568 Town class As given in dataset of Block-1 291420 0 As given in dataset of Block-1 1 All towns with populat ion less than 1 lakh 152907 2 66416 3 25173 4 Each city with population 10 lakhs or more. 46924 Area type As given in dataset of Block-1 538701 0 As given in dataset of Block-1 1 Area-1 333442 2 Area-2 205259 FSU srl. no. As given in dataset of Block-1 538701 0 As given in dataset of Block-1 Enterprise class As given in dataset of Block-1 538701 0 As given in dataset of Block-1 1 All OATEs and NDTEs with one worker only 212365 2 All OATEs and NDTEs with two worker only 213268 3 All OATEs and NDTEs with 3 workers or more 113068 Sample Ent. no. As given in dataset of Block-1 538701 0 As given in dataset of Block-1 Sl no which refer item in col-2 The number of workers per day working full-time or part-time has to be calculated separately for men, women and children for hired workers and other workers. Information on children are to be collected separately for boys and girls. It may be noted that children here will refer to persons who are below 15 years of age(last birth day).Naturally, men and women will refer to adult males and females. While making entries in this block, informa­tion are to be recorded in the reverse process.That means, to arrive at different categories of the no.of hired workers, item 5 may be filled in first. Then items 4, 3, 2 and 1 are to be filled in one by one. The process will be same for collecting informa­tion about the no. of other workers. This reverse process will help the informants to avoid double counting of girls and boys under adult females and males respectively. Items 1 to 5 are provided to collect data on hired workers and items 6 to 10 are provided for other workers. 538701 0 001 Hired workers-Men 23556 002 Hired workers-Women 990 003 Hired workers-children boys 944 004 Hired workers-children girls 68 005 Hired workers-All persons 24889 006 Other workers-Men 147216 007 Other workers-Women 25608 008 Other workers-Children boys 5105 009 Other workers-children girls 930 010 Other workers-All person 154008 011 Total workrs 155387 Av. no. workers-full time 529349 9352 Av. no. workers-part time See B3_col_3 for details 353978 184723 Multiplier (subsample 1 or 2) 538701 0 0.04 65771.57 177.923 511.396 As given in dataset of Block-1 Multiplier (subsamples combined) 538701 0 0.02 32885.79 89.416 256.411 As given in dataset of Block-1 Key to locate enterprise As given in dataset of Block-1 1057492 0 As given in dataset of Block-1 Record Identifier As given in dataset of Block-1 1057492 0 As given in dataset of Block-1 04 1057492 Round Schedule As given in dataset of Block-1 1057492 0 As given in dataset of Block-1 532 NSS 53 Round-schedule2.41.2 1057492 Sector As given in dataset of Block-1 1057492 0 As given in dataset of Block-1 1 Rural 585163 2 Urban 472329 Sub round As given in dataset of Block-1 1057492 0 As given in dataset of Block-1 1 Sub-round-1 310780 2 Sub-round-2 315788 3 Sub-round-3 260703 4 Sub-round-4 170221 Sub sample As given in dataset of Block-1 1057492 0 As given in dataset of Block-1 1 Sub-sample-1 534958 2 Sub-sample-2 522534 State As given in dataset of Block-1 1057492 0 As given in dataset of Block-1 02 Andhra Pradesh 86944 03 Arunachal Pradesh 3318 04 Assam 31935 05 Bihar 73024 06 Goa 3276 07 Gujarat 42676 08 Haryana 32323 09 Himachal Pradesh 9253 10 Jammu & Kashmir 5789 11 Karnataka 65977 12 Kerala 50633 13 Madhya Pradesh 69079 14 Maharashtra 85468 15 Manipur 6675 16 Meghalaya 3047 17 Mizoram 3569 18 Nagaland 8402 19 Orissa 37751 20 Punjab 38713 21 Rajasthan 54441 22 Sikkim 4837 23 Tamil Nadu 94755 24 Tripura 7167 25 Uttar Pradesh 148993 26 West Bengal 73066 27 A & N Islands 2108 28 Chandigarh 2308 29 Dadra & Nagar Haveli 1506 30 Daman & Diu 1633 31 Delhi 5488 32 Lakshdweep 1131 33 Pondicherry 2207 Region As given in dataset of Block-1 1057492 0 As given in dataset of Block-1 1 Region-1 328037 2 Region-2 311085 3 Region-3 195317 4 Region-4 163050 5 Region-5 43139 6 Region-6 10103 7 Region-7 6761 District code As given in dataset of Block-1 1057492 0 As given in dataset of Block-1 Town class As given in dataset of Block-1 472329 0 As given in dataset of Block-1 1 All towns with populat ion less than 1 lakh 265943 2 107064 3 38337 4 Each city with population 10 lakhs or more. 60985 Area type As given in dataset of Block-1 1057492 0 As given in dataset of Block-1 1 Area-1 622650 2 Area-2 434842 FSU srl. no. As given in dataset of Block-1 1057492 0 As given in dataset of Block-1 Enterprise class As given in dataset of Block-1 1057492 0 As given in dataset of Block-1 1 All OATEs and NDTEs with one worker only 426615 2 All OATEs and NDTEs with two worker only 471897 3 All OATEs and NDTEs with 3 workers or more 158980 Sample Ent. no. As given in dataset of Block-1 1057492 0 As given in dataset of Block-1 Commodity group code Code and Description of commodity groups and Unit In col. 2, the descriptions of 73 commodity groups are given. Commodity group 74 is referring to the 'all commodities'. The items in this column are mostly self-explanatory. 1057492 0 001 Rice(Kg.) 31353 002 Wheat(Kg.) 12278 003 Other Ceeals(Kg.) 13662 004 Arhar(Kg.) 21258 005 Gram(Kg.) 19908 006 Other Pulses(Kg.) 29642 007 Biscuits(Kg.) 43074 008 Bread(kg.) 10265 009 Other Bakery Products and Sugar Confectioneries 44180 010 Sugar(Kg.) 37594 011 Gur, Candy Batasa Etc.(Kg.) 19983 012 Milk(Kg.) 4216 013 Other Dairy Products(Kg.) 6087 014 Edble Oils(Kg.) 34163 015 Meat and Poultry(Kg.) 1078 016 Fish(Kg.) 2598 017 Egg(Dozen) 13947 018 Salt(Kg.) 34332 019 Spices Including 'Garam Niasala'(Gm) 30318 020 Potao and Onion(Kg.) 25674 021 Other Vegetables(Kg.) 14741 022 Fruits(Kg.) 10057 023 Dry Fruits and Nuts(Kg.) 9559 024 Tea, Coffee(Kg.) 35024 025 Pan and Pan Rnasala(No) 24549 026 Bjdj Cigaettes, and Other Tobacco Products(No(00)) 47861 027 Soap, Detergent and Washing Powder(Kg.) 47366 028 Tooth Paste(Gm) 27343 029 Hair Oil and Shampoo(Gm) 29156 030 Other Toilet Preparations(Gm) 13736 031 Leather Footwear(Pair) 1719 032 Non-Leather Footwear(Pair) 3877 033 Other Leather Products(No) 851 034 Cotton Textiles(Mtr) 7623 035 Other Textiles(Mtr) 8581 036 Hosiery Goods(No) 5722 037 Readymade Garments(No) 6087 038 Woolen Goods(No) 898 039 Plastic Goods(No) 4329 040 Other Synthetic Goods(No) 754 041 Jewellery (Gold and Silver)(Gm) 919 042 Precious Stones(Carat) 71 043 Artificial Jewellery(No) 1979 044 Drugs and Pharmacuticals 8301 045 Bulbs and Tubes(No.) 17826 046 Sockets, Switches, Wires Etc.(No.) 3167 047 Fans, Heaters, Ire S Etc.(No.) 1129 048 Tv, Vcp. Vcr(No.) 580 049 Fidge, Washing Machines and Air Conditioners(No.) 226 050 Radio, Transistor and Tape Recorders(No.) 737 051 Digital Watches,Calculators & Other Elec. Appliances(No.) 1237 052 Crockery and Glassware(No.) 1760 053 Potteries(No.) 292 054 Fertilizers(Kg.) 1575 055 Pesticides(Kg.) 1210 056 Utensils and Metal Containers(Kg.) 2825 057 Note Books, Writing and Drawing Materials(No) 13102 058 Books and Periodicals(No) 2434 059 Office Stationeries 7095 060 Wood, Cane and Bamboo Products(No) 739 061 Bicycle(No.) 311 062 Tyre, Tube and Spare Parts 2411 063 Soft Dinks(ml.) 8525 064 Fruit Juice(ml.) 1485 065 Wine and Intoxicants(ml.) 1041 066 Toys and Sports Goods(No) 2210 067 Cement(Kg.) 1651 068 Bricks(No(000)) 250 069 Iron Rods(Qntl) 674 070 Other Building Materials 3139 071 Coal, Coke and Fire Wood(Kg.) 1433 072 Watch, Spectacles, Walking Sticks, Artificial Limbs,Lighter, Sun Glass, Contact Lens Etc.(No) 813 073 Any Other Articles 83301 074 All Commodities 147601 purchased:-qty Purchased:-quantity 634206 423286 0 9999999 4173.741 80626.849 purchased:-val Purchased:-value See B4_C4 for details 982503 74989 0 32422400 8781.484 84674.685 Sold:-qty Sold:-quantity See B4_C4 for details 693634 363858 0 9999999 3822.952 77245.098 Sold:-val Sold:-value See B4_C4 for details 1054775 2717 0 32865000 9103.539 83968.047 Multiplier (subsample 1 or 2) 1057492 0 0.04 65771.57 161.631 340.729 As given in dataset of Block-1 Multiplier (subsamples combined) 1057492 0 0.02 32885.79 81.214 171.125 As given in dataset of Block-1 As given in dataset of Block-1 1246918 0 As given in dataset of Block-1 Record Identifier As given in dataset of Block-1 1246918 0 As given in dataset of Block-1 05 1246918 Round Schedule As given in dataset of Block-1 1246918 0 As given in dataset of Block-1 532 NSS 53 Round-schedule 2.41.2 1246918 Sector As given in dataset of Block-1 1246918 0 As given in dataset of Block-1 1 Rural 548251 2 Urban 698667 Sub round As given in dataset of Block-1 1246918 0 As given in dataset of Block-1 1 Sub-round-1 370872 2 Sub-round-2 372963 3 Sub-round-3 307047 4 Sub-round-4 196036 Sub sample As given in dataset of Block-1 1246918 0 As given in dataset of Block-1 1 Sub-sample-1 632678 2 Sub-sample-2 614240 State As given in dataset of Block-1 1246918 0 As given in dataset of Block-1 02 Andhra Pradesh 93738 03 Arunachal Pradesh 3430 04 Assam 37500 05 Bihar 89684 06 Goa 2923 07 Gujarat 56739 08 Haryana 33873 09 Himachal Pradesh 8917 10 Jammu & Kashmir 5900 11 Karnataka 72446 12 Kerala 59064 13 Madhya Pradesh 73237 14 Maharashtra 111199 15 Manipur 4429 16 Meghalaya 3070 17 Mizoram 1947 18 Nagaland 6339 19 Orissa 45854 20 Punjab 50217 21 Rajasthan 58228 22 Sikkim 3941 23 Tamil Nadu 105001 24 Tripura 5728 25 Uttar Pradesh 189331 26 West Bengal 99359 27 A & N Islands 1770 28 Chandigarh 3241 29 Dadra & Nagar Haveli 1686 30 Daman & Diu 2137 31 Delhi 11496 32 Lakshdweep 896 33 Pondicherry 3598 Region As given in dataset of Block-1 1246918 0 As given in dataset of Block-1 1 Region-1 372308 2 Region-2 377001 3 Region-3 230616 4 Region-4 195582 5 Region-5 52357 6 Region-6 11309 7 Region-7 7745 District code As given in dataset of Block-1 1246918 0 As given in dataset of Block-1 Town class As given in dataset of Block-1 698667 0 As given in dataset of Block-1 1 All towns with populat ion less than 1 lakh 365588 2 159082 3 61850 4 Each city with population 10 lakhs or more. 112147 Area type As given in dataset of Block-1 1246918 0 As given in dataset of Block-1 1 Area-1 791212 2 Area-2 455706 FSU srl. no. As given in dataset of Block-1 1246918 0 As given in dataset of Block-1 Enterprise class As given in dataset of Block-1 1246918 0 As given in dataset of Block-1 1 All OATEs and NDTEs with one worker only 495591 2 All OATEs and NDTEs with two worker only 497945 3 All OATEs and NDTEs with 3 workers or more 253382 Sample Ent. no. As given in dataset of Block-1 1246918 0 As given in dataset of Block-1 01 243162 02 215339 03 191829 04 173272 05 124663 06 110427 07 51702 08 41074 09 31291 10 23494 11 16198 12 10738 13 5780 14 3947 15 2534 16 1468 sl. no. of expenditure 1246918 0 001 Packing materials 97972 002 Other consummable stores 54339 003 Electricity charges 95425 004 Printing and stationary charges 56741 005 Building repair charges 10017 006 Other reparing charges 31861 007 Postal and telephone charges 27849 008 Transport charges (inward and Outward) 100704 009 Rent on assets other than land 41074 010 Taxes,licenses,fees etc to authorities 55369 011 Local rates 41315 012 Any other expenses 115273 013 Trading expenditure (Items 1 to12) 152646 014 Interest 16557 015 Rent on land/premises 17054 016 Compensation to workers 26515 017 Total Disbursement(Items 13 to 16) 152825 018 Trader's net earnings/surplus 153382 sign for value -ve/+ve '-' indicates negative value 22 0 - 22 value(Rs) see B5_c1 for details 1246888 30 0 3483222 771.329 5153.562 Multiplier (subsample 1 or 2) 1246918 0 0.04 65771.57 166.274 446.387 As given in dataset of Block-1 Multiplier (subsamples combined) 1246918 0 0.02 32885.79 83.59 223.933 As given in dataset of Block-1 Key to locate enterprise As given in dataset of block-1 1457527 0 As given in dataset of block-1 Record Identifier As given in dataset of block-1 1457527 0 As given in dataset of block-1 06 Block - 6 of schedule 1457527 Round Schedule As given in dataset of block-1 1457527 0 As given in dataset of block-1 532 NSS 53 Round schedule 2.41.2 1457527 Sector As given in dataset of block-1 1457527 0 As given in dataset of block-1 1 Rural 675440 2 Urban 782087 Sub round As given in dataset of block-1 1457527 0 As given in dataset of block-1 1 Sub-round-1 434019 2 Sub-round-2 432104 3 Sub-round-3 358202 4 Sub-round-4 233202 Sub sample As given in dataset of block-1 1457527 0 As given in dataset of block-1 1 Sub-sample-1 738734 2 Sub-sample-2 718793 State As given in dataset of block-1 1457527 0 As given in dataset of block-1 02 Andhra Pradesh 110697 03 Arunachal Pradesh 3699 04 Assam 42819 05 Bihar 115607 06 Goa 3280 07 Gujarat 64765 08 Haryana 37592 09 Himachal Pradesh 10151 10 Jammu & Kashmir 7424 11 Karnataka 81563 12 Kerala 63114 13 Madhya Pradesh 93571 14 Maharashtra 118669 15 Manipur 6647 16 Meghalaya 3734 17 Mizoram 3253 18 Nagaland 8196 19 Orissa 61043 20 Punjab 54606 21 Rajasthan 71274 22 Sikkim 4594 23 Tamil Nadu 114444 24 Tripura 7369 25 Uttar Pradesh 231250 26 West Bengal 109540 27 A & N Islands 2067 28 Chandigarh 3685 29 Dadra & Nagar Haveli 1903 30 Daman & Diu 2499 31 Delhi 13600 32 Lakshdweep 1023 33 Pondicherry 3849 Region As given in dataset of block-1 1457527 0 As given in dataset of block-1 1 Region-1 431775 2 Region-2 437242 3 Region-3 275954 4 Region-4 226738 5 Region-5 62050 6 Region-6 14199 7 Region-7 9569 District code As given in dataset of block-1 1457527 0 As given in dataset of block-1 Town class As given in dataset of block-1 782087 0 As given in dataset of block-1 1 All towns with populat ion less than 1 lakh 417754 2 178419 3 66127 4 Each city with population 10 lakhs or more. 119787 Area type 1457527 0 1 Area-1 886739 2 Area-2 570788 FSU srl. no. As given in dataset of block-1 1457527 0 As given in dataset of block-1 Enterprise class As given in dataset of block-1 1457527 0 As given in dataset of block-1 1 All OATEs and NDTEs with one worker only 650667 2 All OATEs and NDTEs with two worker only 563823 3 All OATEs and NDTEs with 3 workers or more 243037 Sample Ent. no. As given in dataset of block-1 1457527 0 As given in dataset of block-1 01 282617 02 248494 03 221676 04 200257 05 141330 06 124558 07 64038 08 51120 09 39576 10 29726 11 20986 12 14290 13 7929 14 5476 15 3453 16 2001 Sl. no. of items The block has 11 items, the descriptions of which are given in column 2. In column 3, the values are to be recorded in whole no. of rupees. 1457527 0 001 Total commodities purchased(Block-4/item-74/column--5) 142948 002 Trading expenditure (Block-5/item-13) 152646 003 Total trading expenses(item-1+2) 153823 004 Total commodities sold(Block-4/item-74/column-7) 147573 005 Other receipts 43353 006 Trading goods consumed at home 98381 007 Total receipts of the enterprise (Item-4+5+6) 155174 008 Capital locked up in stock at the beginning of the month 134996 009 Capital locked up in stock at the end of the month 136263 010 Change in stock (Item 9-item 8) 136910 011 Gross value added(item7-item3+item10) 155460 Sign for value 42056 0 - negative value 42056 Value(Rs) 1457512 15 0 32865000 21086.842 116365.895 Multiplier (subsample 1 or 2) As given in dataset of block-1 1457527 0 0.04 65771.57 176.073 469.789 Multiplier (subsamples combined) As given in dataset of block-1 1457527 0 0.02 32885.79 88.496 235.687 Key to identify Enterprise As given in dataset of Block-1 908830 0 As given in dataset of Block-1 Record Identifier As given in dataset of Block-1 908830 0 As given in dataset of Block-1 07 Block - 7 of schedule 908830 Round Schedule As given in dataset of Block-1 908830 0 As given in dataset of Block-1 532 NSS 53 Round-schedule 2.41.2 908830 Sector As given in dataset of Block-1 908830 0 As given in dataset of Block-1 1 Rural 517531 2 Urban 391299 Sub round As given in dataset of Block-1 908830 0 As given in dataset of Block-1 1 Sub-round-1 265325 2 Sub-round-2 271358 3 Sub-round-3 225002 4 Sub-round-4 147145 Sub sample As given in dataset of Block-1 908830 0 As given in dataset of Block-1 1 Sub-sample-1 459676 2 Sub-sample-2 449154 State As given in dataset of Block-1 908830 0 As given in dataset of Block-1 02 Andhra Pradesh 75635 03 Arunachal Pradesh 2869 04 Assam 27409 05 Bihar 60058 06 Goa 2947 07 Gujarat 35704 08 Haryana 29491 09 Himachal Pradesh 8412 10 Jammu & Kashmir 5079 11 Karnataka 57774 12 Kerala 43302 13 Madhya Pradesh 60198 14 Maharashtra 74105 15 Manipur 5866 16 Meghalaya 2699 17 Mizoram 3173 18 Nagaland 7511 19 Orissa 32115 20 Punjab 33334 21 Rajasthan 47019 22 Sikkim 4546 23 Tamil Nadu 83740 24 Tripura 6157 25 Uttar Pradesh 125168 26 West Bengal 60965 27 A & N Islands 1922 28 Chandigarh 2001 29 Dadra & Nagar Haveli 1310 30 Daman & Diu 1389 31 Delhi 4114 32 Lakshdweep 1068 33 Pondicherry 1750 Region As given in dataset of Block-1 908830 0 As given in dataset of Block-1 1 Region-1 284874 2 Region-2 265740 3 Region-3 166497 4 Region-4 140494 5 Region-5 36887 6 Region-6 8532 7 Region-7 5806 District code As given in dataset of Block-1 908830 0 As given in dataset of Block-1 Town class As given in dataset of Block-1 391299 0 As given in dataset of Block-1 1 All towns with populat ion less than 1 lakh 222764 2 88647 3 31425 4 Each city with population 10 lakhs or more. 48463 Area type As given in dataset of Block-1 908830 0 As given in dataset of Block-1 1 Area-1 531544 2 Area-2 377286 FSU srl. no. As given in dataset of Block-1 908830 0 As given in dataset of Block-1 Enterprise class As given in dataset of Block-1 908830 0 As given in dataset of Block-1 1 All OATEs and NDTEs with one worker only 359233 2 All OATEs and NDTEs with two worker only 415236 3 All OATEs and NDTEs with 3 workers or more 134361 Sample Ent. no. 908830 0 01 187701 02 155744 03 133375 04 115178 05 85407 06 74482 07 42630 08 33665 09 25987 10 19835 11 13888 12 9129 13 4992 14 3437 15 2259 16 1121 Commodity group code Commod­ity groups and the unit of transaction have been kept as they were in block 4. 908830 0 001 Rice(Kg.) 31418 002 Wheat(Kg.) 12558 003 Other Ceeals(Kg.) 13981 004 Arhar(Kg.) 21442 005 Gram(Kg.) 20299 006 Other Pulses(Kg.) 29676 007 Biscuits(Kg.) 42902 008 Bread(kg.) 10777 009 Other Bakery Products and Sugar Confectioneries 43745 010 Sugar(Kg.) 37153 011 Gur, Candy Batasa Etc.(Kg.) 20379 012 Milk(Kg.) 4909 013 Other Dairy Products(Kg.) 5652 014 Edble Oils(Kg.) 33751 015 Meat and Poultry(Kg.) 1181 016 Fish(Kg.) 2549 017 Egg(Dozen) 14042 018 Salt(Kg.) 34014 019 Spices Including 'Garam Niasala'(Gm) 30085 020 Potao and Onion(Kg.) 25606 021 Other Vegetables(Kg.) 14872 022 Fruits(Kg.) 10158 023 Dry Fruits and Nuts(Kg.) 9780 024 Tea, Coffee(Kg.) 34562 025 Pan and Pan Rnasala(No) 24845 026 Bjdj Cigaettes, and Other Tobacco Products(No(00)) 47620 027 Soap, Detergent and Washing Powder(Kg.) 46989 028 Tooth Paste(Gm) 27616 029 Hair Oil and Shampoo(Gm) 29082 030 Other Toilet Preparations(Gm) 13871 031 Leather Footwear(Pair) 1930 032 Non-Leather Footwear(Pair) 3857 033 Other Leather Products(No) 918 034 Cotton Textiles(Mtr) 7683 035 Other Textiles(Mtr) 8630 036 Hosiery Goods(No) 5767 037 Readymade Garments(No) 6110 038 Woolen Goods(No) 993 039 Plastic Goods(No) 4249 040 Other Synthetic Goods(No) 772 041 Jewellery (Gold and Silver)(Gm) 922 042 Precious Stones(Carat) 76 043 Artificial Jewellery(No) 1910 044 Drugs and Pharmacuticals 8325 045 Bulbs and Tubes(No.) 17596 046 Sockets, Switches, Wires Etc.(No.) 3146 047 Fans, Heaters, Ire S Etc.(No.) 1140 048 Tv, Vcp. Vcr(No.) 598 049 Fidge, Washing Machines and Air Conditioners(No.) 245 050 Radio, Transistor and Tape Recorders(No.) 753 051 Digital Watches,Calculators & Other Elec. Appliances(No.) 1221 052 Crockery and Glassware(No.) 1797 053 Potteries(No.) 316 054 Fertilizers(Kg.) 1603 055 Pesticides(Kg.) 1249 056 Utensils and Metal Containers(Kg.) 2829 057 Note Books, Writing and Drawing Materials(No) 13111 058 Books and Periodicals(No) 2625 059 Office Stationeries 7062 060 Wood, Cane and Bamboo Products(No) 751 061 Bicycle(No.) 319 062 Tyre, Tube and Spare Parts 2416 063 Soft Dinks(ml.) 8497 064 Fruit Juice(ml.) 1491 065 Wine and Intoxicants(ml.) 1036 066 Toys and Sports Goods(No) 2189 067 Cement(Kg.) 1640 068 Bricks(No(000)) 255 069 Iron Rods(Qntl) 694 070 Other Building Materials 3094 071 Coal, Coke and Fire Wood(Kg.) 1391 072 Watch, Spectacles, Walking Sticks, Artificial Limbs,Lighter, Sun Glass, Contact Lens Etc.(No) 861 073 Any Other Articles 81249 074 All Commodities 0 sign for trade margin 100 0 - Negative 100 Trade margin(whole number) 908761 69 0 942 15.229 13.378 Multiplier (subsample 1 or 2) 908830 0 0.04 65771.57 160.224 317.275 As given in dataset of Block-1 Multiplier (subsamples combined) 908830 0 0.02 32885.79 80.501 159.381 As given in dataset of Block-1 Key to identify Enterprise As given in dataset of Block-1 154281 0 As given in dataset of Block-1 Record Identifier As given in dataset of Block-1 154281 0 As given in dataset of Block-1 08 Block -8 of schedule 154281 Round Schedule As given in dataset of Block-1 154281 0 As given in dataset of Block-1 532 NSS 53 Round -schedule 2.41.2 154281 Sector As given in dataset of Block-1 154281 0 As given in dataset of Block-1 1 Rural 72300 2 Urban 81981 Sub round As given in dataset of Block-1 154281 0 As given in dataset of Block-1 1 Sub-round-1 45758 2 Sub-round-2 46061 3 Sub-round-3 37920 4 Sub-round-4 24542 Sub sample As given in dataset of Block-1 154281 0 As given in dataset of Block-1 1 Sub-sample-1 78305 2 Sub-sample-2 75976 State As given in dataset of Block-1 154281 0 As given in dataset of Block-1 02 Andhra Pradesh 12006 03 Arunachal Pradesh 384 04 Assam 4436 05 Bihar 12237 06 Goa 359 07 Gujarat 6854 08 Haryana 4019 09 Himachal Pradesh 1018 10 Jammu & Kashmir 767 11 Karnataka 8758 12 Kerala 6779 13 Madhya Pradesh 9696 14 Maharashtra 12427 15 Manipur 665 16 Meghalaya 391 17 Mizoram 361 18 Nagaland 813 19 Orissa 7262 20 Punjab 5786 21 Rajasthan 7424 22 Sikkim 464 23 Tamil Nadu 12067 24 Tripura 744 25 Uttar Pradesh 23715 26 West Bengal 11846 27 A & N Islands 209 28 Chandigarh 384 29 Dadra & Nagar Haveli 192 30 Daman & Diu 245 31 Delhi 1434 32 Lakshdweep 118 33 Pondicherry 421 Region As given in dataset of Block-1 154281 0 As given in dataset of Block-1 1 Region-1 45436 2 Region-2 46846 3 Region-3 29393 4 Region-4 23784 5 Region-5 6344 6 Region-6 1475 7 Region-7 1003 District code As given in dataset of Block-1 154281 0 As given in dataset of Block-1 Town class As given in dataset of Block-1 81981 0 As given in dataset of Block-1 1 All towns with populat ion less than 1 lakh 43603 2 18684 3 6945 4 Each city with population 10 lakhs or more. 12749 Area type As given in dataset of Block-1 154281 0 As given in dataset of Block-1 1 Area-1 93494 2 Area-2 60787 FSU srl. no. As given in dataset of Block-1 154281 0 As given in dataset of Block-1 Enterprise class As given in dataset of Block-1 154281 0 As given in dataset of Block-1 1 All OATEs and NDTEs with one worker only 69744 2 All OATEs and NDTEs with two worker only 58628 3 All OATEs and NDTEs with 3 workers or more 25909 Sample Ent. no. As given in dataset of Block-1 154281 0 As given in dataset of Block-1 no. of visits made to canvass 151351 2930 0 69 1 73774 2 55414 3 16951 4 3712 5 919 6 360 7 70 8 51 9 31 Sysmiss 2930 time taken to canvass 152823 1458 0 980 106.79 52.527 date of survey(ddmmyy) 153505 776 0 921197 186773.633 76715.075 date of despatch(ddmmyy) 151041 3240 0 972611 208181.867 91820.541 Multiplier (subsample 1 or 2) 154281 0 0.04 65771.57 185.786 532.157 Multiplier (subsamples combined) 154281 0 0.02 32885.79 93.378 266.85