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    Home / Central Data Catalog / ENTERPRISE_SURVEYS / PER_2017_ES_V01_M / variable [F2]
enterprise_surveys

Enterprise Survey 2017

Peru, 2017 - 2018
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Reference ID
PER_2017_ES_v01_M
DOI
https://doi.org/10.48529/h5v0-1k57
Producer(s)
World Bank
Collection(s)
Enterprise Surveys
Metadata
Documentation in PDF DDI/XML JSON
Study website
Created on
Nov 27, 2018
Last modified
Nov 27, 2018
Page views
33987
Downloads
2558
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  • 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: -9 - 1500000000
Format: Numeric

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
Categories
Value Category Cases
-9 Don't know (spontaneous) 174
31.6%
0 3
0.5%
6000 1
0.2%
10000 2
0.4%
17000 1
0.2%
20000 2
0.4%
25000 1
0.2%
30000 2
0.4%
32500 1
0.2%
40000 6
1.1%
50000 2
0.4%
60000 2
0.4%
65000 1
0.2%
70000 4
0.7%
74132 1
0.2%
80000 3
0.5%
90000 1
0.2%
100000 11
2%
104000 1
0.2%
120000 2
0.4%
130000 2
0.4%
136000 1
0.2%
140000 1
0.2%
150000 6
1.1%
160000 2
0.4%
170000 2
0.4%
180000 3
0.5%
190000 2
0.4%
195000 1
0.2%
200000 13
2.4%
208000 1
0.2%
220000 2
0.4%
229000 1
0.2%
240000 1
0.2%
250000 5
0.9%
270000 1
0.2%
280000 1
0.2%
294000 1
0.2%
300000 16
2.9%
324000 1
0.2%
325000 1
0.2%
326000 1
0.2%
330000 1
0.2%
350000 4
0.7%
370000 1
0.2%
384000 1
0.2%
400000 7
1.3%
450000 2
0.4%
487500 1
0.2%
490000 1
0.2%
500000 11
2%
504570 1
0.2%
525000 1
0.2%
550000 2
0.4%
560000 1
0.2%
568000 1
0.2%
574874 1
0.2%
600000 8
1.5%
640000 1
0.2%
650000 1
0.2%
660000 2
0.4%
700000 3
0.5%
796250 1
0.2%
800000 4
0.7%
820000 1
0.2%
850000 1
0.2%
900000 4
0.7%
1000000 10
1.8%
1100000 1
0.2%
1200000 3
0.5%
1300000 1
0.2%
1320000 1
0.2%
1500000 10
1.8%
1680000 1
0.2%
1700000 1
0.2%
1800000 2
0.4%
1825000 1
0.2%
2000000 13
2.4%
2400000 2
0.4%
2500000 3
0.5%
2600000 3
0.5%
2625000 1
0.2%
2640000 1
0.2%
2700000 1
0.2%
3000000 15
2.7%
3025596 1
0.2%
3500000 5
0.9%
4000000 4
0.7%
4500000 2
0.4%
4875000 1
0.2%
4950000 2
0.4%
5000000 7
1.3%
6000000 6
1.1%
7000000 6
1.1%
8000000 4
0.7%
9000000 2
0.4%
9853500 1
0.2%
10000000 6
1.1%
10862670 1
0.2%
12000000 3
0.5%
12683301 1
0.2%
12800000 1
0.2%
14000000 2
0.4%
14500000 1
0.2%
15000000 7
1.3%
16500000 1
0.2%
16800000 1
0.2%
17000000 1
0.2%
17500000 1
0.2%
18000000 1
0.2%
19000000 1
0.2%
19800000 1
0.2%
20000000 9
1.6%
23000000 1
0.2%
24600000 1
0.2%
25000000 5
0.9%
27000000 1
0.2%
30000000 2
0.4%
32000000 1
0.2%
32500000 1
0.2%
40000000 2
0.4%
40320000 1
0.2%
50000000 3
0.5%
52000000 1
0.2%
60000000 2
0.4%
65000000 1
0.2%
70000000 1
0.2%
84000000 1
0.2%
87500000 1
0.2%
90000000 2
0.4%
100000000 5
0.9%
140000000 1
0.2%
150000000 2
0.4%
153650000 1
0.2%
155000000 1
0.2%
220000000 1
0.2%
250000000 1
0.2%
260000000 1
0.2%
300000000 6
1.1%
329000000 1
0.2%
350000000 1
0.2%
557000000 1
0.2%
600000000 1
0.2%
800000000 1
0.2%
1000000000 1
0.2%
1050000000 1
0.2%
1500000000 1
0.2%
Sysmiss 452
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.
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