Home / Central Data Catalog / PER_2006-2017_ES-P_V01_M / variable [F1]
central

Enterprise Survey 2006-2017, Panel data

Peru, 2006 - 2017
Get Microdata
Reference ID
PER_2006-2017_ES-P_v01_M
Producer(s)
World Bank
Metadata
DDI/XML JSON
Created on
Dec 05, 2019
Last modified
Dec 05, 2019
Page views
16707
Downloads
1039

Total Annual Expenditure For Purchases Of Land And Buildings In Last Fiscal Yr (n5b)

Data file: Peru_2006_2010_2017

Overview

Valid: 1891
Invalid: 744
Minimum: -9
Maximum: 135000000
Type: Discrete
Decimal: 0
Start: 716
End: 724
Width: 9
Range: -9 - 135000000
Format: Numeric

Questions and instructions

Literal question
In fiscal year 2015, how much did this establishment spend on purchases of and buildings, including expansion and renovations of existing structures?
- land and buildings, including expansion and renovations of existing structures?
Categories
Value Category Cases
-9 Don't know (spontaneous) 97
5.1%
-8 12
0.6%
-7 1
0.1%
0 1394
73.7%
35 1
0.1%
4000 1
0.1%
4321 1
0.1%
8000 1
0.1%
10114 1
0.1%
12000 1
0.1%
15000 2
0.1%
18000 1
0.1%
20000 2
0.1%
24000 2
0.1%
25000 3
0.2%
27000 1
0.1%
30000 5
0.3%
32000 2
0.1%
36300 1
0.1%
40000 4
0.2%
42000 1
0.1%
47000 1
0.1%
48000 2
0.1%
50000 9
0.5%
52500 1
0.1%
58000 1
0.1%
60000 6
0.3%
61050 1
0.1%
69000 1
0.1%
70000 2
0.1%
74800 1
0.1%
75000 2
0.1%
76000 1
0.1%
77000 2
0.1%
80000 4
0.2%
86000 1
0.1%
90000 1
0.1%
95000 1
0.1%
97500 1
0.1%
98000 1
0.1%
100000 10
0.5%
104200 1
0.1%
104390 1
0.1%
105000 2
0.1%
110000 3
0.2%
113600 1
0.1%
120000 9
0.5%
122800 1
0.1%
140000 1
0.1%
144000 1
0.1%
145000 1
0.1%
150000 9
0.5%
151200 1
0.1%
157000 1
0.1%
165000 3
0.2%
168000 1
0.1%
170000 1
0.1%
180000 4
0.2%
186000 1
0.1%
188886 1
0.1%
195060 1
0.1%
200000 19
1%
210000 1
0.1%
230000 1
0.1%
240000 3
0.2%
250000 7
0.4%
260000 1
0.1%
270000 2
0.1%
284000 2
0.1%
286000 1
0.1%
300000 26
1.4%
320000 1
0.1%
324000 1
0.1%
325000 1
0.1%
330000 2
0.1%
335000 1
0.1%
350000 4
0.2%
359000 1
0.1%
360000 2
0.1%
371000 1
0.1%
395000 1
0.1%
396000 1
0.1%
400000 6
0.3%
410000 1
0.1%
420000 1
0.1%
427618 1
0.1%
448000 1
0.1%
450000 3
0.2%
480000 1
0.1%
500000 10
0.5%
504000 1
0.1%
520000 1
0.1%
562500 1
0.1%
577000 1
0.1%
580000 1
0.1%
600000 5
0.3%
606000 1
0.1%
650000 1
0.1%
652000 1
0.1%
670000 1
0.1%
700000 13
0.7%
750000 3
0.2%
792000 1
0.1%
800000 4
0.2%
801000 1
0.1%
858000 1
0.1%
870000 1
0.1%
900000 6
0.3%
911031 1
0.1%
1000000 12
0.6%
1010800 1
0.1%
1037000 1
0.1%
1050000 2
0.1%
1100000 1
0.1%
1200000 2
0.1%
1206046 1
0.1%
1300000 3
0.2%
1400000 2
0.1%
1420000 1
0.1%
1450000 1
0.1%
1485000 1
0.1%
1500000 4
0.2%
1600000 1
0.1%
1670000 1
0.1%
1675000 1
0.1%
1704000 1
0.1%
1800000 1
0.1%
1995182 1
0.1%
2000000 8
0.4%
2100000 1
0.1%
2450000 1
0.1%
2500000 2
0.1%
2640000 1
0.1%
2671900 1
0.1%
3000000 11
0.6%
3000100 1
0.1%
3200000 1
0.1%
3400000 1
0.1%
3500000 1
0.1%
3600000 1
0.1%
3750000 1
0.1%
4000000 2
0.1%
4260000 1
0.1%
4500000 3
0.2%
4620000 1
0.1%
5000000 6
0.3%
5025000 1
0.1%
5680000 1
0.1%
5800000 1
0.1%
6000000 6
0.3%
6167000 1
0.1%
7000000 1
0.1%
7392000 1
0.1%
7400000 1
0.1%
8000000 1
0.1%
8500000 1
0.1%
9000000 1
0.1%
9750000 1
0.1%
10000000 1
0.1%
10005000 1
0.1%
15000000 1
0.1%
17000000 1
0.1%
18000000 1
0.1%
19000000 1
0.1%
20000000 4
0.2%
24000000 1
0.1%
30000000 1
0.1%
32000000 1
0.1%
35000000 1
0.1%
40000000 1
0.1%
50000000 1
0.1%
135000000 1
0.1%
Sysmiss 744
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.
Back to Catalog