Enterprise Survey 2017
Peru, 2017 - 2018
Get MicrodataCreated on
Mar 29, 2019
Last modified
Mar 29, 2019
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4709
- Data files
- peru_2017_full_data
Cost For Establishment To Re-Purchase All Of Its Machinery (n7a)
Data file: peru_2017_full_data
Overview
Valid:
551
Invalid:
452
Type:
Discrete
Decimal:
0
Start:
2257
End:
2266
Width:
10
Range:
-
Format:
Questions and instructions
Literal question
Hypothetically, if this establishment were to purchase the assets it uses now, in their current condition and regardless of whether the establishment owns them or not, how much would they cost, independently of whether they are owned, rented or leased?
- Machinery, vehicles, and equipment
- Machinery, vehicles, and equipment
Categories
| Value | Category |
|---|---|
| -9 | Don't know (spontaneous) |
| 0 | |
| 6000 | |
| 10000 | |
| 17000 | |
| 20000 | |
| 25000 | |
| 30000 | |
| 32500 | |
| 40000 | |
| 50000 | |
| 60000 | |
| 65000 | |
| 70000 | |
| 74132 | |
| 80000 | |
| 90000 | |
| 100000 | |
| 104000 | |
| 120000 | |
| 130000 | |
| 136000 | |
| 140000 | |
| 150000 | |
| 160000 | |
| 170000 | |
| 180000 | |
| 190000 | |
| 195000 | |
| 200000 | |
| 208000 | |
| 220000 | |
| 229000 | |
| 240000 | |
| 250000 | |
| 270000 | |
| 280000 | |
| 294000 | |
| 300000 | |
| 324000 | |
| 325000 | |
| 326000 | |
| 330000 | |
| 350000 | |
| 370000 | |
| 384000 | |
| 400000 | |
| 450000 | |
| 487500 | |
| 490000 | |
| 500000 | |
| 504570 | |
| 525000 | |
| 550000 | |
| 560000 | |
| 568000 | |
| 574874 | |
| 600000 | |
| 640000 | |
| 650000 | |
| 660000 | |
| 700000 | |
| 796250 | |
| 800000 | |
| 820000 | |
| 850000 | |
| 900000 | |
| 1000000 | |
| 1100000 | |
| 1200000 | |
| 1300000 | |
| 1320000 | |
| 1500000 | |
| 1680000 | |
| 1700000 | |
| 1800000 | |
| 1825000 | |
| 2000000 | |
| 2400000 | |
| 2500000 | |
| 2600000 | |
| 2625000 | |
| 2640000 | |
| 2700000 | |
| 3000000 | |
| 3025596 | |
| 3500000 | |
| 4000000 | |
| 4500000 | |
| 4875000 | |
| 4950000 | |
| 5000000 | |
| 6000000 | |
| 7000000 | |
| 8000000 | |
| 9000000 | |
| 9853500 | |
| 10000000 | |
| 10862670 | |
| 12000000 | |
| 12683301 | |
| 12800000 | |
| 14000000 | |
| 14500000 | |
| 15000000 | |
| 16500000 | |
| 16800000 | |
| 17000000 | |
| 17500000 | |
| 18000000 | |
| 19000000 | |
| 19800000 | |
| 20000000 | |
| 23000000 | |
| 24600000 | |
| 25000000 | |
| 27000000 | |
| 30000000 | |
| 32000000 | |
| 32500000 | |
| 40000000 | |
| 40320000 | |
| 50000000 | |
| 52000000 | |
| 60000000 | |
| 65000000 | |
| 70000000 | |
| 84000000 | |
| 87500000 | |
| 90000000 | |
| 100000000 | |
| 140000000 | |
| 150000000 | |
| 153650000 | |
| 155000000 | |
| 220000000 | |
| 250000000 | |
| 260000000 | |
| 300000000 | |
| 329000000 | |
| 350000000 | |
| 557000000 | |
| 600000000 | |
| 800000000 | |
| 1000000000 | |
| 1050000000 | |
| 1500000000 | |
| 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.