2006 Employees’ Earnings Survey

(1)

Directorate-General of Budget, Accounting & Statistics , Executive Yuan

2006 Employees’ Earnings Survey

Study Documentation

July 27, 2016

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專題中心 , DDI文件製作

Production Date July 9, 2015

Version 2.0

版，參考IHSN Nesstar Template修改

Identification AA220020en

(3)

Overview... 4

Scope & Coverage... 4

Producers & Sponsors...4

Sampling...4

Data Collection...5

Data Processing & Appraisal...5

Accessibility... 5

Files Description... 6

salary2006... 6

Variables Group(s)... 7

Demographics...7

The number of employees and payroll...7

Unfilled vacancies...10

The adjustment of regular earnings for this month: (check all that apply)... 11

The payment of irregular earnings for this month: (check all that apply)...11

Number of employees joining and leaving... 11

Off-work days( off work days include weekend, national holidays, employee vocations and company leisure days)... 12

Working hours per person per day...12

Number of employees:__(at the end of last month)...12

Number of leaving employees: ___(at the end of last month)...12

Average daily payment to each skilled construction worker in your organization... 13

Average daily payment to each low-skilled construction worker in your organization... 13

Variables Description...14

salary2006... 15

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2006 Employees’ Earnings Survey

Overview

Type Employees' earnings survey

Identification AA220020en

Version Production Date: 2015-02-09 v1

Abstract

　　Employees' Earnings Survey is to provide information on number of employees, earnings, working hours and turnover

in various industries in Taiwan area. To gain understanding of industrial manpower demand, working hours and earnings level of employees. It's area includes Taiwan Province, Taipei Municipality and Kaohsiung Municipality. According to the current standard industrial classification system of the Republic of China, the survey covers these industries: mining

& quarrying, manufacturing, electricity & gas supply, Construction, wholesale & retail trade, transportation & storage, accommodation & food service activities, communication, finance & insurance activities, real estate activities & rental and leasing, professional, scientific & technical activities, human health activities, cultural, sporting and recreational services and other service activities etc. . Establishments are public and private firms and their employees( excluding the factories owned by the Ministry of National Defense, consumers cooperatives, workshops of schools, relief institutions and prisons).

Personnel shall be sent on location for the purposes of survey by mail and interview, as well as by the Internet.

　　According to the four-digit group of the Standard Industrial Classification System of the Republic of China, a screening

or a stratified cut-off random sampling method is adopted. For government enterprises and large-scale private enterprises (above the cut-off point), the screening is used. For medium and small private enterprises (below the cut-off point), the stratified random sampling is adopted. In principle, the survey period of every sample is confined to one year. The source of data for population is the population files of the latest Industry, Commerce and Service Census. The samples of industrial sub- classifications not exceeding 5 units should be increased to 5 units, and the population of less than 5 units all should be surveyed.

Kind of Data

抽樣調查資料 (Sample survey data)

Scope & Coverage

Countries

台灣 (Taiwan, ROC)

Geographic Coverage

Taiwan Province, Taipei Municipality and Kaohsiung Municipality Universe

Establishments are public and private firms and their employees( excluding the factories owned by the Ministry of National Defense, consumers cooperatives, workshops of schools, relief institutions and prisons).

Producers & Sponsors

Primary Investigator(s)

Directorate-General of Budget, Accounting & Statistics , Executive Yuan

Other Producer(s) Directorate-General of Budget, Accounting & Statistics, Executive Yuan (DGBAS) Funding Agency/ies Directorate-General of Budget, Accounting & Statistics , Executive Yuan (DGBAS)

Sampling

Sampling Procedure

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　　According to the four-digit group of the Standard Industrial Classification System of the Republic of China, a screening

or a stratified cut-off random sampling method is adopted. For government enterprises and large-scale private enterprises (above the cut-off point), the screening is used. For medium and small private enterprises (below the cut-off point), the stratified random sampling is adopted. The number of employees is used as a variable of stratification. The Dalenius-Hodges approximate optimum method is used to determine the boundaries between strata and the Nyman best allocation method in each stratum. In principle, the survey period of every sample is confined to one year. The source of data for population is the population files of the latest Industry, Commerce and Service Census. The samples of industrial sub- classifications not exceeding 5 units should be increased to 5 units, and the population of less then 5 units all should be surveyed.

Data Collection

Data Collection Mode

其他 (Other)

Data Processing & Appraisal

Data Editing

CSR has checked wild codes and out-of-range values, to validate and clean data.

Other Processing

Personnel shall be sent on location for the purposes of survey by mail and interview, as well as by the Internet:

(1) Mining & quarrying: By face-to-face interview.

(2) Manufacturing: The survey is conducted by mail. For the firms not reporting on time, surveying organization shall urge or assist the reporting.

(3) Electricity & gas supply: The same as Manufacturing.

(4) Construction: By face-to-face interview.

(5) Wholesale & retail trade: By face-to-face interview.

(6) Transportation & storage: By face-to-face interview.

(7) Accommodation & food service activities: By face-to-face interview.

(8) Communication: By face-to-face interview.

(9) Finance & insurance activities: The survey is conducted by investigation with the Internet.

(10) Real estate activities & rental and leasing: By face-to-face interview.

(11) Professional, scientific & technical activities: By face-to-face interview.

(12) Human health activities: By face-to-face interview.

(13) Cultural, sporting and recreational services: By face-to-face interview.

(14) Other service activities: By face-to-face interview.

Accessibility

Contact(s)

學術調查研究資料庫(Survey Research Data Archive) (中央研究院人社中心調查研究專題中

心) ,

https://srda.sinica.edu.tw , [email protected] Distributor(s)

學術調查研究資料庫(Survey Research Data Archive)

Depositor(s) Directorate-General of Budget, Accounting & Statistics, Executive Yuan Access Conditions

會員版(一般會員、院內會員)--申請審核通過後下載

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Files Description

Dataset contains 1 file(s)

salary2006

# Cases 110578

# Variable(s) 71

(7)

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Variables Group(s)

Dataset contains 12 group(s)

Group Demographics

# Name Label Type Format Valid Invalid Question

1 x1 ID code discrete character-15 110578 0 -

2 ym Year/Month continuous numeric-5.0 110578 0 -

3 city County/City discrete numeric-2.0 110578 0 -

4 job Industry continuous numeric-4.0 110578 0 -

5 id Sample ID discrete character-4 110578 0 -

Group The number of employees and payroll

1 a6_11 The number of male salaried professional employees (staff, supervisors and technicians) as of the end of this month: regular employees

continuous numeric-4.0 89709 20869 -

2 a7_11 The number of male salaried professional employees (staff, supervisors and technicians) as of the end of this month: temporary employees

3 a8_11 Total working hours correspond to previous number of male salaried professional employees (staff, supervisors and technicians): regular working hours

4 a9_11 Total working hours correspond to previous number of male salaried professional employees (staff, supervisors and technicians): overtime working hours

5 a10_11 Total gross monthly earnings correspond to previous number of male salaried professional employees (staff, supervisors and technicians): regular earnings (NT$)

6 a11_11 Total gross monthly earnings correspond to previous number of male salaried professional employees (staff, supervisors and technicians): overtime pay(NT$)

7 a12_11 Total gross monthly earnings correspond to previous

(8)

# Name Label Type Format Valid Invalid Question number of male salaried

professional employees (staff, supervisors and technicians): other irregular earnings (NT$)

8 a6_12 The number of female salaried professional employees (staff, supervisors and technicians) as of the end of this month: regular employees

9 a7_12 The number of female salaried professional employees (staff, supervisors and technicians) as of the end of this month: temporary employees

10 a8_12 Total working hours correspond to previous number of female salaried professional employees (staff, supervisors and technicians): regular working hours

11 a9_12 Total working hours correspond to previous number of female salaried professional employees (staff, supervisors and technicians): overtime working hours

12 a10_12 Total gross monthly earnings correspond to previous number of female salaried professional employees (staff, supervisors and technicians): regular earnings (NT$)

13 a11_12 Total gross monthly earnings correspond to previous number of female salaried professional employees (staff, supervisors and technicians): overtime pay(NT$)

14 a12_12 Total gross monthly earnings correspond to previous number of female salaried professional employees (staff, supervisors and technicians): other irregular earnings (NT$)

15 a6_21 The number of male personnel (non-supervisors and non-technicians) as of the end of this month: regular employees

16 a7_21 The number of male personnel (non-supervisors and non-technicians) as of the end of this month:

temporary employees

(9)

- 9 -

17 a8_21 Total working hours correspond to previous number of male personnel (non-supervisors and non- technicians): regular working hours

18 a9_21 Total working hours correspond to previous number of male personnel (non-supervisors and non- technicians) : overtime working hours

19 a10_21 Total gross monthly earnings correspond to previous number of male personnel (non-supervisors and non-technicians): regular earnings(NT$)

20 a11_21 Total gross monthly earnings correspond to previous number of male personnel (non-supervisors and non- technicians): overtime pay(NT$)

21 a12_21 Total gross monthly earnings correspond to previous number of male personnel (non-supervisors and non- technicians): other irregular earnings(NT$)

22 a6_22 The number of female personnel (non-supervisors and non-technicians) as of the end of this month: regular employees

23 a7_22 The number of female personnel (non-supervisors and non-technicians) as of the end of this month:

temporary employees

24 a8_22 Total working hours correspond to previous number of female personnel (non-supervisors and non- technicians): regular working hours

25 a9_22 Total working hours correspond to previous number of female personnel (non-supervisors and non- technicians): overtime working hours

26 a10_22 Total gross monthly earnings correspond to previous number of female personnel (non-supervisors and non-technicians): regular earnings(NT$)

27 a11_22 Total gross monthly earnings correspond to previous number of female personnel

(10)

# Name Label Type Format Valid Invalid Question (non-supervisors and non-

technicians): overtime pay(NT$)

28 a12_22 Total gross monthly earnings correspond to previous number of female personnel (non-supervisors and non- technicians): other irregular earnings(NT$)

29 a6_70 Number of employees at the end of this month: total number of regular employees

30 a7_70 Number of employees at the end of this month:

total number of temporary employees

31 a8_70 Total working hours correspond to previous number of employees: total number of regular working hours

32 a9_70 Total working hours correspond to previous number of employees: total number of overtime working hours

33 a10_70 Total gross monthly earnings correspond to previous number of employees:

total number of regular earnings(NT$)

34 a11_70 Total gross monthly earnings correspond to previous number of employees: total number of overtime pay(NT

$)

35 a12_70 Total gross monthly earnings correspond to previous number of employees: total number of other irregular earnings(NT$)

Group Unfilled vacancies

1 b6 Unfilled vacancies this month: professional employees, supervisors and technicians

2 b7 Unfilled vacancies this month: other personnel, non-supervisors, non- professionals, and non- technicians

3 b8 Labor outsourcing (including labor dispatching) in the current month: number of people

discrete numeric-1.0 110578 0 -

(11)

- 11 -

4 b9 Labor outsourcing (including labor dispatching) in the current month: expenses (NTD)

5 b10 Comparing of the operating status(productivity or work load ) with previous month

6 b11 Main way of calculating salary for most production workers (or construction workers) in your organization

Group The adjustment of regular earnings for this month: (check all that apply)

1 b12 The adjustment of regular earnings for this month: raise for staff, supervisory and technical employees(check all that apply)

2 b13 The adjustment of regular earnings for this month:

raise for workers and nonsupervisory(check all that apply)

3 b14 The adjustment of regular earnings for this month: pay cut for staff, supervisory and technical employees(check all that apply)

pay cut for workers and nonsupervisory(check all that apply)

none(check all that apply)

Group The payment of irregular earnings for this month: (check all that apply)

1 b17 The payment of irregular earnings for this month:

annual(seasoning) bonus or personal bonus(check all that apply)

irregular working(efficiency) bonus(check all that apply)

none(check all that apply)

Group Number of employees joining and leaving

(12)

# Name Label Type Format Valid Invalid Question 1 c6 Number of accessions: newly

hired

2 c7 Number of accessions: recall continuous numeric-3.0 110578 0 -

3 c8 Number of accessions: others continuous numeric-3.0 110578 0 -

4 c9 Number of separations: quit continuous numeric-3.0 110578 0 -

5 c10 Number of separations: lay off( incl. paid lay off)

6 c11 Number of separations:

retirement( incl. benefited retirement)

7 c12 Number of separations:

others

Group Off-work days( off work days include weekend, national holidays, employee vocations and company leisure days)

1 c13 Staff, supervisory and technical employees off-work days:__days per person

2 c14 Staff, supervisory and technical employees working days:__days per person

3 c15 Non-supervisors and non- technicians off-work days:__days per person

4 c16 Non-supervisors and

non-technicians working days:__days per person

Group Working hours per person per day

1 c17 Staff, supervisory and technical employees:__hours per day

2 c18 Non-supervisors and non- technicians:__hours per day

Group Number of employees:__(at the end of last month)

1 c19 Number of employees:__(at

the end of last month)

Group Number of leaving employees: ___(at the end of last month)

1 c21 Number of leaving

employees: ___(at the end of last month)

(13)

- 13 -

Group Average daily payment to each skilled construction worker in your organization

1 c22 Average daily payment to each skilled construction worker in your organization:

NT$

Group Average daily payment to each low-skilled construction worker in your organization

1 c23 Average daily payment to each low-skilled construction worker in your organization:

NT$

(14)

Variables Description

Dataset contains 71 variable(s)

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#

x1: ID code

Information [Type= discrete] [Format=character] [Missing=*]

Statistics [NW/ W] [Valid=110578 /-] [Invalid=0 /-]

#

ym: Year/Month

Information [Type= continuous] [Format=numeric] [Range= 95001-95012] [Missing=*]

Statistics [NW/ W] [Valid=110578 /-] [Invalid=0 /-] [Mean=95006.555 /-] [StdDev=3.451 /-]

#

city: County/City

Information [Type= discrete] [Format=numeric] [Range= 1-64] [Missing=*]

Value Label Cases Percentage

1 Taipei County 16451 14.9%

2 Yilan County 1802 1.6%

3 Taoyuan County 11205 10.1%

4 Hsinchu County 3143 2.8%

5 Miaoli County 2550 2.3%

6 Taichung County 7739 7.0%

7 Changhua County 4740 4.3%

8 Nantou County 1657 1.5%

9 Yunlin County 1867 1.7%

10 Chiayi County 1544 1.4%

11 Tainan County 5651 5.1%

12 Kaohsiung County 5238 4.7%

13 Pintung County 1765 1.6%

14 Taitung County 751 0.7%

15 Hualien County 1429 1.3%

16 Penghu County 301 0.3%

17 Keelung City 1186 1.1%

18 Hsinchu City 3268 3.0%

19 Taichung City 5574 5.0%

20 Chiayi City 805 0.7%

21 Tainan City 2545 2.3%

63 Taipei City 19432 17.6%

64 Kaohsiung City 9935 9.0%

Warning: these figures indicate the number of cases found in the data file. They cannot be interpreted as summary statistics of the population of interest.

#

job: Industry

0 N/A 0

400 Mining 411 0.4%

600 Quarrying 1540 1.4%

810 Slaughtering 150 0.1%

820 Dairy Product Manufacturing 78 0.1%

(16)

831 Canned Food Manufacturing 53 0.0%

832 Frozen Food Manufacturing 354 0.3%

833 Dehydrated Food Manufacturing 42 0.0%

834 Preserved Food Manufacturing 68 0.1%

841 Sugar Confectionery Manufacturing 47 0.0%

842 Bakery Product Manufacturing 141 0.1%

851 Edible Fat and Oils Manufacturing 90 0.1%

852 Flour Milling 62 0.1%

853 Grain Husking 84 0.1%

860 Sugar Manufacturing 119 0.1%

871 Monosodium Glutamate Manufacturing 47 0.0%

879 Other Seasoning Manufacturing 95 0.1%

880 Beverage and Tobacco Manufacturing 538 0.5%

891 Noodle Manufacturing 69 0.1%

892 Prepared Animal Feeds Manufacturing 139 0.1%

893 Tea Manufacturing 40 0.0%

899 Other Food Manufacturing Not Elsewhere Classified 259 0.2%

1010 Yarn Spinning Mills 430 0.4%

1020 Fabric Mills 1072 1.0%

1040 Rope, Cable, Net, Rug and Carpet Manufacturing 62 0.1%

1050 Printing, Dyeing and Finishing Mills 516 0.5%

1090 Other Textile Mills 322 0.3%

1110 Woven Wearing Apparel Manufacturing 446 0.4%

1120 Apparel Knitting Mills 239 0.2%

1130 Textile Hat Manufacturing 58 0.1%

1190 Other Textile Product Manufacturing 268 0.2%

1201 Leather, Fur Finishing 163 0.1%

1202 Footwear Manufacturing 268 0.2%

1203 Luggage and Bag Manufacturing 52 0.0%

1209 Other Leather, Fur Products Manufacturing 109 0.1%

1301 Lumbering 166 0.2%

1302 Plywood Manufacturing 114 0.1%

1303 Reconstituted Wood Manufacturing 56 0.1%

1304 Wooden Containers Manufacturing 57 0.1%

1305 Bamboo, Rattan Products Manufacturing 21 0.0%

1309 Other Wood Products Manufacturing 193 0.2%

1411 Wood Furniture and Fixtures Manufacturing 154 0.1%

1412 Bamboo, Rattan Furniture and Fixtures Manufacturing 42 0.0%

1419 Other Non-metallic Furniture and Fixtures Manufacturing 46 0.0%

1420 Metallic Furniture and Fixtures Manufacturing 415 0.4%

1510 Pulp Manufacturing 30 0.0%

1521 Paper Mills 402 0.4%

1530 Processed Paper Manufacturing 113 0.1%

(17)

- 17 -

#

job: Industry

1540 Paper Container Manufacturing 523 0.5%

1590 Other Paper Products Manufacturing 80 0.1%

1610 Platemaking 134 0.1%

1620 Printing 479 0.4%

1630 Printed Matters Bookbinding and Processing 90 0.1%

1690 Other Printing Support Activities 18 0.0%

1711 Basic Industrial Chemicals 349 0.3%

1712 Petrochemicals Manufacturing 211 0.2%

1713 Fertilizers Manufacturing 154 0.1%

1720 Man-made Fibers Manufacturing 165 0.1%

1731 Synthetic Resin and Plastic Materials Manufacturing 518 0.5%

1732 Synthetic Rubber Manufacturing 41 0.0%

1790 Other Chemical Materials Manufacturing 73 0.1%

1810 Paints, Varnishes, Lacquers, Pigments Manufacturing 282 0.3%

1821 Medicine Source Materials Manufacturing 170 0.2%

1822 Drugs and Medicines Manufacturing 317 0.3%

1823 Biomedicines Manufacturing 42 0.0%

1824 Chinese Medicines Manufacturing 125 0.1%

1825 In-Vitro Diagnostic Reagent Manufacturing 49 0.0%

1826 Pesticides and Herbicides Manufacturing 117 0.1%

1830 Cleaning Preparations Manufacturing 79 0.1%

1840 Cosmetics Manufacturing 120 0.1%

1890 Other Chemical Products Manufacturing 347 0.3%

1910 Petroleum Refineries 264 0.2%

1990 Other Petroleum and Coal Products Manufacturing 59 0.1%

2001 Tires Manufacturing 163 0.1%

2002 Industrial Rubber Products Manufacturing 277 0.3%

2009 Other Rubber Products Manufacturing 178 0.2%

2101 Plastic Sheets, Pipes and Tubes Manufacturing 469 0.4%

2102 Plastic Bags Manufacturing 249 0.2%

2103 Plastic Housewares Manufacturing 475 0.4%

2104 Imitated Leather Products Manufacturing 104 0.1%

2105 Industrial Plastic Products Manufacturing 473 0.4%

2109 Other Plastic Products Manufacturing 773 0.7%

2210 Pottery, China and Earthenware Manufacturing 213 0.2%

2220 Glass and Glass Products Manufacturing 443 0.4%

2231 Cement Manufacturing 102 0.1%

2232 Concrete Mixing Manufacturing 339 0.3%

2233 Cement Products Manufacturing 119 0.1%

2250 Stone Products Manufacturing 169 0.2%

2291 Constructional Clay Products Manufacturing 64 0.1%

2292 Industrial and Grinding Materials Manufacturing 78 0.1%

2299 Other Non-Metallic Mineral Products Manufacturing Not Elsewh 246 0.2%

(18)

2311 Iron and Steel Refining 84 0.1%

2312 Steel Casting 253 0.2%

2313 Steel Rolling and Extruding 599 0.5%

2314 Steel Wires and Cables Manufacturing 112 0.1%

2315 Used Vehicles and Vessels Dismantling and Processing 42 0.0%

2319 Other Steel Basic Industries 430 0.4%

2321 Aluminum Refining and Smelting 48 0.0%

2322 Aluminum Casting 85 0.1%

2323 Aluminum Rolling, Drawing and Extruding 240 0.2%

2331 Copper Refining 33 0.0%

2332 Copper Casting 44 0.0%

2333 Copper Rolling, Drawing and Extruding 141 0.1%

2341 Magnesium Refining 12 0.0%

2342 Magnesium Casting 0

2343 Magnesium Rolling, Drawing and Extruding 6 0.0%

2390 Other Metal Basic Industries 82 0.1%

2410 Metal Forging and Powder Metallurgy 111 0.1%

2420 Cutlery and Handtools Manufacturing 490 0.4%

2430 Metal Structure and Architectural Components Manufacturing 453 0.4%

2440 Metal Container Manufacturing 314 0.3%

2451 Metal Surface Treating 514 0.5%

2452 Metal Heat Treating 199 0.2%

2490 Other Fabricated Metal Products Manufacturing 2302 2.1%

2510 Boilers, Engines and Turbines Manufacturing and Repairing 130 0.1%

2520 Agricultural and Horticulture Machinery Manufacturing and Re 111 0.1%

2531 Machine Tool (Metal Cutting Types) Manufacturing and Repairi 344 0.3%

2532 Machine Tool (Metal Forming Types) Manufacturing and Repairi 408 0.4%

2541 Food and Drink Processing Machinery Manufacturing and Repair 83 0.1%

2542 Textile and Garment Producing Machinery Manufacturing and Re 360 0.3%

2544 Paper Making Machinery Manufacturing and Repairing 99 0.1%

2546 Chemical Process Machinery Manufacturing and Repairing 131 0.1%

2547 Plastic and Rubber Producing Machinery Manufacturing and Rep 168 0.2%

2548 Electronic and Semi-conductors Production Equipment Manufact 196 0.2%

2549 Other Special Production Machinery Manufacturing and Repairi 302 0.3%

2551 Building Machinery Manufacturing and Repairing 38 0.0%

2552 Mining Machinery Manufacturing and Repairing 42 0.0%

2560 Office Machines Manufacturing 36 0.0%

2580 General Machinery Manufacturing and Repairing 835 0.8%

2592 Metal Die Manufacturing and Repairing 1080 1.0%

2599 Other Machinery Manufacturing and Repairing Not Elsewhere Cl 628 0.6%

2610 Computer and Peripheral Equipment Manufacturing 1717 1.6%

2620 Communications Equipment and Apparatus Manufacturing 815 0.7%

2630 Audio and Video Electronic Products Manufacturing 599 0.5%

(19)

- 19 -

#

job: Industry

2640 Data Storage Media Units Manufacturing and Reproducing 254 0.2%

2710 Semi-conductors Manufacturing 1308 1.2%

2720 Electronic passive devices Manufacturing 1156 1.0%

2730 Bare Printed Circuit Boards Manufacturing 1065 1.0%

2790 Other Electronic Parts and Components Manufacturing 1619 1.5%

2811 Power Generation, Transmission and Distribution Machinery Ma 963 0.9%

2812 Electric Wires and Cables Manufacturing 570 0.5%

2820 Electrical Appliances and Housewares Manufacturing 533 0.5%

2830 Lighting Equipment Manufacturing 309 0.3%

2840 Batteries Manufacturing 197 0.2%

2890 Other Electronic and Appliances Manufacturing and Repairing 661 0.6%

2911 Ship Building and Repairing 143 0.1%

2912 Ship Machinery and Parts Manufacturing 87 0.1%

2913 Floating Structures Building and Repairing 0

2921 Tramway Cars Manufacturing and Repairing 23 0.0%

2922 Tramway Car Parts Manufacturing and Repairing 24 0.0%

2931 Motor Vehicles Manufacturing 111 0.1%

2932 Motor Vehicle Parts Manufacturing 1189 1.1%

2941 Motorcycles Manufacturing 122 0.1%

2942 Motorcycle Parts Manufacturing 263 0.2%

2951 Bicycles Manufacturing 125 0.1%

2952 Bicycles Parts Manufacturing 415 0.4%

2961 Aircraft Manufacturing and Repairing 72 0.1%

2962 Aircraft Parts Manufacturing 66 0.1%

2990 Other Transport Equipment and Parts Manufacturing and Repair 48 0.0%

3011 Measuring Instruments and Controlling Equipment Manufacturin 266 0.2%

3019 Other Precision Instruments Manufacturing 43 0.0%

3020 Photographic and Optical Equipment Manufacturing 427 0.4%

3030 Medical Materials and Equipment Manufacturing 125 0.1%

3040 Watches and Clocks Manufacturing 67 0.1%

3111 Sporting and Athletic Articles Manufacturing 333 0.3%

3112 Toys Manufacturing 122 0.1%

3113 Musical Instruments Manufacturing 100 0.1%

3114 Stationery Articles Manufacturing 157 0.1%

3191 Jewelry and Related Articles Manufacturing 49 0.0%

3199 Other Industrial Products Manufacturing Not Elsewhere Classi 494 0.4%

3300 Electricity, Gas and Water 911 0.8%

3801 General Civil Engineering Construction 2793 2.5%

3900 Buildings Construction 1508 1.4%

4000 Mechanics, Telecommunications, Electricity, and Pipe Lines C 3231 2.9%

4100 Building Maintenance and Upholstery 1436 1.3%

4200 Other Construction 1512 1.4%

4400 Wholesale Trade 6869 6.2%

(20)

4600 Retail Trade 3216 2.9%

4751 Department Stores 203 0.2%

4759 Retail Sale of Other General Merchandise 734 0.7%

5000 Accommodation Service 621 0.6%

5100 Eating and Drinking Places 1786 1.6%

5310 Railway Transportation and Motor Bus Transportation 739 0.7%

5333 General Bus Transportation 718 0.6%

5340 Truck Freight Transportation 2020 1.8%

5410 Ocean Water Transportation and Harbor Services 420 0.4%

5500 Air Transportation 338 0.3%

5600 Storage and Distribution 281 0.3%

5790 Other Supporting Services to Transportation 1907 1.7%

5800 Warehousing and Storage 396 0.4%

5900 Postal Services and Telecommunications 708 0.6%

5920 Courier Services 365 0.3%

6212 Domestic Banks 505 0.5%

6213 Foreign Banks 401 0.4%

6220 Credit Cooperatives 323 0.3%

6230 Credit Departments of Farmers and Fishermen Associations 3271 3.0%

6240 Trust and Investment 84 0.1%

6290 Other Financing and Auxiliary Financing 824 0.7%

6410 Personal Insurance 348 0.3%

6420 Property and Liability Insurance 252 0.2%

6600 Real Estate 1954 1.8%

6700 Rental and Leasing 433 0.4%

6910 Legal Services 220 0.2%

6920 Accounting Services 384 0.3%

7000 Architectural And Engineering Technical Services 674 0.6%

7100 Specialized Design Services 947 0.9%

7200 Computer Systems Design Services 1365 1.2%

7300 Data Processing and Information Supply Services 399 0.4%

7400 Consultation Services 1041 0.9%

7600 Advertising Services 1115 1.0%

7700 Other Professional, Scientific and Technical Services 406 0.4%

8100 Health Care Services 3111 2.8%

8400 Publishing Industries 1103 1.0%

8500 Motion Picture Industries 342 0.3%

8600 Radio and Television Broadcasting 1197 1.1%

8700 Arts and Sporting Services 630 0.6%

9000 Recreational Services 1263 1.1%

9201 Personnel Supply Services 1081 1.0%

9202 Security Services 853 0.8%

9204 Cleaning Services of Buildings 773 0.7%

(21)

- 21 -

#

job: Industry

9209 Other Support Services 519 0.5%

9300 Sanitary and Pollution Controlling Services 648 0.6%

9500 Repair and Maintenance Services 1660 1.5%

9620 Barber and Beauty Shops 941 0.9%

9690 Other Personal Services 597 0.5%

#

id: Sample ID

Information [Type= discrete] [Format=character] [Missing=*]

#

a6_11: The number of male salaried professional employees (staff, supervisors and technicians) as of the end of this month: regular employees

#

a7_11: The number of male salaried professional employees (staff, supervisors and technicians) as of the end of this month: temporary employees

#

a8_11: Total working hours correspond to previous number of male salaried professional employees (staff, supervisors and technicians): regular working hours

#

a9_11: Total working hours correspond to previous number of male salaried professional employees (staff, supervisors and technicians): overtime working hours

#

a10_11: Total gross monthly earnings correspond to previous number of male salaried professional employees (staff, supervisors and technicians): regular earnings (NT$)

#

a11_11: Total gross monthly earnings correspond to previous number of male salaried professional employees (staff, supervisors and technicians): overtime pay(NT$)

#

a12_11: Total gross monthly earnings correspond to previous number of male salaried professional employees (staff, supervisors and technicians): other irregular earnings (NT$)

Information [Type= continuous] [Format=numeric] [Range= -4293-1469810808] [Missing=*]

#

a6_12: The number of female salaried professional employees (staff, supervisors and technicians) as of the end of this month: regular employees

(22)

month: regular employees

#

a7_12: The number of female salaried professional employees (staff, supervisors and technicians) as of the end of this month: temporary employees

#

a8_12: Total working hours correspond to previous number of female salaried professional employees (staff, supervisors and technicians): regular working hours

#

a9_12: Total working hours correspond to previous number of female salaried professional employees (staff, supervisors and technicians): overtime working hours

#

a10_12: Total gross monthly earnings correspond to previous number of female salaried professional employees (staff, supervisors and technicians): regular earnings (NT$)

#

a11_12: Total gross monthly earnings correspond to previous number of female salaried professional employees (staff, supervisors and technicians): overtime pay(NT$)

#

a12_12: Total gross monthly earnings correspond to previous number of female salaried professional employees (staff, supervisors and technicians): other irregular earnings (NT$)

#

a6_21: The number of male personnel (non-supervisors and non-technicians) as of the end of this month: regular employees

#

a7_21: The number of male personnel (non-supervisors and non-technicians) as of the end of this month: temporary employees

#

a8_21: Total working hours correspond to previous number of male personnel (non-supervisors and non- technicians): regular working hours

(23)

- 23 -

#

a9_21: Total working hours correspond to previous number of male personnel (non-supervisors and non- technicians) : overtime working hours

#

a10_21: Total gross monthly earnings correspond to previous number of male personnel (non-supervisors and non- technicians): regular earnings(NT$)

#

a11_21: Total gross monthly earnings correspond to previous number of male personnel (non-supervisors and non- technicians): overtime pay(NT$)

#

a12_21: Total gross monthly earnings correspond to previous number of male personnel (non-supervisors and non- technicians): other irregular earnings(NT$)

#

a6_22: The number of female personnel (non-supervisors and non-technicians) as of the end of this month: regular employees

#

a7_22: The number of female personnel (non-supervisors and non-technicians) as of the end of this month:

temporary employees

#

a8_22: Total working hours correspond to previous number of female personnel (non-supervisors and non- technicians): regular working hours

#

a9_22: Total working hours correspond to previous number of female personnel (non-supervisors and non- technicians): overtime working hours

#

a10_22: Total gross monthly earnings correspond to previous number of female personnel (non-supervisors and non- technicians): regular earnings(NT$)

#

a11_22: Total gross monthly earnings correspond to previous number of female personnel (non-supervisors and non- technicians): overtime pay(NT$)

(24)

technicians): other irregular earnings(NT$)

#

a6_70: Number of employees at the end of this month: total number of regular employees

#

a7_70: Number of employees at the end of this month: total number of temporary employees

#

a8_70: Total working hours correspond to previous number of employees: total number of regular working hours

#

a9_70: Total working hours correspond to previous number of employees: total number of overtime working hours

#

a10_70: Total gross monthly earnings correspond to previous number of employees: total number of regular earnings(NT$)

#

a11_70: Total gross monthly earnings correspond to previous number of employees: total number of overtime pay(NT$)

#

a12_70: Total gross monthly earnings correspond to previous number of employees: total number of other irregular earnings(NT$)

#

b6: Unfilled vacancies this month: professional employees, supervisors and technicians

#

b7: Unfilled vacancies this month: other personnel, non-supervisors, non-professionals, and non-technicians

#

b8: Labor outsourcing (including labor dispatching) in the current month: number of people

0 110578 100.0%

(25)

- 25 -

#

b9: Labor outsourcing (including labor dispatching) in the current month: expenses (NTD)

0 110578 100.0%

#

b10: Comparing of the operating status(productivity or work load ) with previous month

0 1 0.0%

1 Better 16897 15.3%

2 Unchanged 71617 64.8%

3 Worse 21082 19.1%

4 Termination of business (termination of production or non-un 980 0.9%

6 1 0.0%

#

b11: Main way of calculating salary for most production workers (or construction workers) in your organization

0 N/A 55240 50.0%

1 Monthly pay 37279 33.7%

2 Daily pay 15307 13.8%

3 Hourly pay 902 0.8%

4 Piece rate pay 1850 1.7%

#

b12: The adjustment of regular earnings for this month: raise for staff, supervisory and technical employees(check all that apply)

0 No 107161 96.9%

1 Yes 3417 3.1%

#

b13: The adjustment of regular earnings for this month: raise for workers and nonsupervisory(check all that apply)

0 No 107311 97.0%

2 Yes 3267 3.0%

(26)

employees(check all that apply)

0 No 110263 99.7%

3 Yes 314 0.3%

5 1 0.0%

#

b15: The adjustment of regular earnings for this month: pay cut for workers and nonsupervisory(check all that apply)

0 No 110259 99.7%

4 Yes 318 0.3%

5 1 0.0%

(27)

- 27 -

0 No 5190 4.7%

1 1 0.0%

5 Yes 105387 95.3%

#

b17: The payment of irregular earnings for this month: annual(seasoning) bonus or personal bonus(check all that apply)

0 No 98855 89.4%

1 Yes 11723 10.6%

#

b18: The payment of irregular earnings for this month: irregular working(efficiency) bonus(check all that apply)

0 No 99720 90.2%

2 Yes 10858 9.8%

#

b19: The payment of irregular earnings for this month: none(check all that apply)

0 No 21525 19.5%

3 Yes 89053 80.5%

#

c6: Number of accessions: newly hired

#

c7: Number of accessions: recall

#

c8: Number of accessions: others

#

c9: Number of separations: quit

(28)

#

c11: Number of separations: retirement( incl. benefited retirement)

#

c12: Number of separations: others

#

c13: Staff, supervisory and technical employees off-work days:__days per person

#

c14: Staff, supervisory and technical employees working days:__days per person

#

c15: Non-supervisors and non-technicians off-work days:__days per person

#

c16: Non-supervisors and non-technicians working days:__days per person

#

c17: Staff, supervisory and technical employees:__hours per day

#

c18: Non-supervisors and non-technicians:__hours per day

Information [Type= continuous] [Format=numeric] [Range= 0-80.8] [Missing=*]

#

c19: Number of employees:__(at the end of last month)

#

c21: Number of leaving employees: ___(at the end of last month)

#

c22: Average daily payment to each skilled construction worker in your organization: NT$

#

2006 Employees’ Earnings Survey

Directorate-General of Budget, Accounting & Statistics , Executive Yuan

2006 Employees’ Earnings Survey

Study Documentation

July 27, 2016

Production Date July 9, 2015

Version 2.0

Identification AA220020en

Overview... 4

Scope & Coverage... 4

Producers & Sponsors...4

Sampling...4

Data Collection...5

Data Processing & Appraisal...5

Accessibility... 5

Files Description... 6

salary2006... 6

Variables Group(s)... 7

Demographics...7

The number of employees and payroll...7

Unfilled vacancies...10

The adjustment of regular earnings for this month: (check all that apply)... 11

The payment of irregular earnings for this month: (check all that apply)...11

Number of employees joining and leaving... 11

Off-work days( off work days include weekend, national holidays, employee vocations and company leisure days)... 12

Working hours per person per day...12

Number of employees:__(at the end of last month)...12

Number of leaving employees: ___(at the end of last month)...12

Average daily payment to each skilled construction worker in your organization... 13

Average daily payment to each low-skilled construction worker in your organization... 13

Variables Description...14

salary2006... 15

2006 Employees’ Earnings Survey

2006 Employees’ Earnings Survey

Overview

Type Employees' earnings survey

Identification AA220020en

Version Production Date: 2015-02-09 v1

Abstract

Personnel shall be sent on location for the purposes of survey by mail and interview, as well as by the Internet.<br/>

Kind of Data

Scope & Coverage

Countries

Geographic Coverage

Taiwan Province, Taipei Municipality and Kaohsiung Municipality Universe

Establishments are public and private firms and their employees( excluding the factories owned by the Ministry of National Defense, consumers cooperatives, workshops of schools, relief institutions and prisons).

Producers & Sponsors

Primary Investigator(s)

Directorate-General of Budget, Accounting & Statistics , Executive Yuan

Other Producer(s) Directorate-General of Budget, Accounting & Statistics, Executive Yuan (DGBAS) Funding Agency/ies Directorate-General of Budget, Accounting & Statistics , Executive Yuan (DGBAS)

Sampling

Sampling Procedure

Data Collection

Data Collection Mode

Data Processing & Appraisal

Data Editing

CSR has checked wild codes and out-of-range values, to validate and clean data.

Other Processing

(1) Mining & quarrying: By face-to-face interview.<br/>

(2) Manufacturing: The survey is conducted by mail. For the firms not reporting on time, surveying organization shall urge or assist the reporting.<br/>

(3) Electricity & gas supply: The same as Manufacturing.<br/>

(4) Construction: By face-to-face interview.<br/>

(5) Wholesale & retail trade: By face-to-face interview.<br/>

(6) Transportation & storage: By face-to-face interview.<br/>

(7) Accommodation & food service activities: By face-to-face interview.<br/>

(8) Communication: By face-to-face interview.<br/>

(9) Finance & insurance activities: The survey is conducted by investigation with the Internet.<br/>

(10) Real estate activities & rental and leasing: By face-to-face interview.<br/>

(11) Professional, scientific & technical activities: By face-to-face interview.<br/>

(12) Human health activities: By face-to-face interview.<br/>

(13) Cultural, sporting and recreational services: By face-to-face interview.<br/>

(14) Other service activities: By face-to-face interview.<br/>

Accessibility

Contact(s)

https://srda.sinica.edu.tw , [email protected] Distributor(s)

Depositor(s) Directorate-General of Budget, Accounting & Statistics, Executive Yuan Access Conditions

Files Description

Dataset contains 1 file(s)

salary2006

# Cases 110578