Enterprise Survey 2017
Peru, 2017 - 2018
Get MicrodataCreated on
Mar 29, 2019
Last modified
Mar 29, 2019
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4725
- Data files
- peru_2017_full_data
Net Book Value Of Machinery Vehicles, And Equipment In Last Fiscal Year (n6a)
Data file: peru_2017_full_data
Overview
Valid:
550
Invalid:
453
Type:
Discrete
Decimal:
0
Start:
2247
End:
2256
Width:
10
Range:
-
Format:
Questions and instructions
Literal question
From this establishment’s Balance Sheet for fiscal year 2015, what was the net book value, that is the value of assets after depreciation, of the following:
- Machinery, vehicles, and equipment
- Machinery, vehicles, and equipment
Categories
| Value | Category |
|---|---|
| -9 | Don't know (spontaneous) |
| 0 | |
| 6000 | |
| 9000 | |
| 10000 | |
| 12000 | |
| 15000 | |
| 16000 | |
| 17663 | |
| 20000 | |
| 30000 | |
| 34560 | |
| 37600 | |
| 40000 | |
| 50000 | |
| 54230 | |
| 59634 | |
| 60000 | |
| 68000 | |
| 75966 | |
| 78660 | |
| 80000 | |
| 88000 | |
| 90000 | |
| 93284 | |
| 100000 | |
| 107000 | |
| 113000 | |
| 120000 | |
| 135000 | |
| 140000 | |
| 143708 | |
| 150000 | |
| 180000 | |
| 185000 | |
| 200000 | |
| 217800 | |
| 225000 | |
| 229976 | |
| 230000 | |
| 242000 | |
| 250000 | |
| 300000 | |
| 308984 | |
| 313297 | |
| 329938 | |
| 330000 | |
| 332104 | |
| 360000 | |
| 368443 | |
| 400000 | |
| 406318 | |
| 435000 | |
| 440000 | |
| 450000 | |
| 480000 | |
| 490000 | |
| 490584 | |
| 500000 | |
| 512860 | |
| 515000 | |
| 520933 | |
| 535724 | |
| 550000 | |
| 583000 | |
| 600000 | |
| 638000 | |
| 644000 | |
| 650000 | |
| 696077 | |
| 700000 | |
| 750000 | |
| 800000 | |
| 830000 | |
| 900000 | |
| 982656 | |
| 1000000 | |
| 1157000 | |
| 1241695 | |
| 1250000 | |
| 1330000 | |
| 1359233 | |
| 1402500 | |
| 1500000 | |
| 1600000 | |
| 1644649 | |
| 1706000 | |
| 1711784 | |
| 1737387 | |
| 1800000 | |
| 1827000 | |
| 1852122 | |
| 1900000 | |
| 1920380 | |
| 2000000 | |
| 2201542 | |
| 2264000 | |
| 2420000 | |
| 2500000 | |
| 2600000 | |
| 2800000 | |
| 2850000 | |
| 3000000 | |
| 3025596 | |
| 3028000 | |
| 3100000 | |
| 3200000 | |
| 3500000 | |
| 3600000 | |
| 3625000 | |
| 3657000 | |
| 3789000 | |
| 3900000 | |
| 4000000 | |
| 4344292 | |
| 4533000 | |
| 4800000 | |
| 5000000 | |
| 5160000 | |
| 5222000 | |
| 5427560 | |
| 5500000 | |
| 5604570 | |
| 6000000 | |
| 6221115 | |
| 6264000 | |
| 6388000 | |
| 6924063 | |
| 7000000 | |
| 7400000 | |
| 7451304 | |
| 7484781 | |
| 7608834 | |
| 8000000 | |
| 9000000 | |
| 9800000 | |
| 10000000 | |
| 10238700 | |
| 10500000 | |
| 10862670 | |
| 10971961 | |
| 11399000 | |
| 12000000 | |
| 12258480 | |
| 12573000 | |
| 12628000 | |
| 13000000 | |
| 13500000 | |
| 13527000 | |
| 13636000 | |
| 15000000 | |
| 16000000 | |
| 16100000 | |
| 17000000 | |
| 19000000 | |
| 20000000 | |
| 21561000 | |
| 23520000 | |
| 24000000 | |
| 24600000 | |
| 28000000 | |
| 30000000 | |
| 32000000 | |
| 32500000 | |
| 33320600 | |
| 35000000 | |
| 37000000 | |
| 39000000 | |
| 40000000 | |
| 47000000 | |
| 48000000 | |
| 50000000 | |
| 50250000 | |
| 60000000 | |
| 62000000 | |
| 65732000 | |
| 70000000 | |
| 83620000 | |
| 95000000 | |
| 100000000 | |
| 102000000 | |
| 105000000 | |
| 150000000 | |
| 184000000 | |
| 190000000 | |
| 202000000 | |
| 215000000 | |
| 226000000 | |
| 247000000 | |
| 557000000 | |
| 600000000 | |
| 725760000 | |
| 800000000 | |
| 1050000000 | |
| Sysmiss |
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.