Cost of borrowing indicators (Cost-of-borrowing indicators) - Czech republic statistics

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Cost of borrowing indicators - Latest values

Indicator name. Data from 30.06.2019 Value Previous Change Last Year Change
IND1 Short-term cost of borrowing to non-financial corporations (%) 3.43 3.42 0.29% 2.48 38.31%
IND2 Long-term cost of borrowing to non-financial corporations (%) 4.06 3.40 19.41% 2.52 61.11%
IND3 Short-term cost of borrowing to households for house purchase (%) 3.42 3.39 0.88% 2.79 22.58%
IND4 Long-term cost of borrowing to households for house purchase (%) 2.85 2.89 -1.38% 2.61 9.20%
IND5 Total short-term cost of borrowing (%) 3.43 3.42 0.29% 2.49 37.75%
IND6 Total long-term cost of borrowing (%) 3.07 2.98 3.02% 2.60 18.08%
IND7 Total cost of borrowing to non-financial corporations (%) 3.50 3.41 2.64% 2.49 40.56%
IND8 Total cost of borrowing to households for house purchase (%) 2.88 2.91 -1.03% 2.62 9.92%

Short-term cost of borrowing to non-financial corporations (%)

DateValue
30.06.2019 3.43
31.05.2019 3.42
30.04.2019 3.27
31.03.2019 3.44
28.02.2019 3.29
31.01.2019 3.30
31.12.2018 3.49
30.11.2018 3.27
31.10.2018 3.20
30.09.2018 3.08
Next »
Short-term cost of borrowing to non-financial corporations (%),Cost of borrowing indicators

Long-term cost of borrowing to non-financial corporations (%)

DateValue
30.06.2019 4.06
31.05.2019 3.40
30.04.2019 2.96
31.03.2019 3.79
28.02.2019 2.74
31.01.2019 2.74
31.12.2018 3.01
30.11.2018 3.74
31.10.2018 3.21
30.09.2018 3.18
Next »
Long-term cost of borrowing to non-financial corporations (%),Cost of borrowing indicators

Short-term cost of borrowing to households for house purchase (%)

DateValue
30.06.2019 3.42
31.05.2019 3.39
30.04.2019 3.53
31.03.2019 3.40
28.02.2019 3.33
31.01.2019 3.36
31.12.2018 3.33
30.11.2018 3.23
31.10.2018 3.24
30.09.2018 3.06
Next »
Short-term cost of borrowing to households for house purchase (%),Cost of borrowing indicators

Long-term cost of borrowing to households for house purchase (%)

DateValue
30.06.2019 2.85
31.05.2019 2.89
30.04.2019 2.92
31.03.2019 2.95
28.02.2019 2.96
31.01.2019 2.91
31.12.2018 2.90
30.11.2018 2.81
31.10.2018 2.76
30.09.2018 2.68
Next »
Long-term cost of borrowing to households for house purchase (%),Cost of borrowing indicators

Total short-term cost of borrowing (%)

DateValue
30.06.2019 3.43
31.05.2019 3.42
30.04.2019 3.28
31.03.2019 3.44
28.02.2019 3.29
31.01.2019 3.30
31.12.2018 3.48
30.11.2018 3.27
31.10.2018 3.20
30.09.2018 3.08
Next »
Total short-term cost of borrowing (%),Cost of borrowing indicators

Total long-term cost of borrowing (%)

DateValue
30.06.2019 3.07
31.05.2019 2.98
30.04.2019 2.92
31.03.2019 3.10
28.02.2019 2.92
31.01.2019 2.88
31.12.2018 2.92
30.11.2018 2.97
31.10.2018 2.83
30.09.2018 2.77
Next »
Total long-term cost of borrowing (%),Cost of borrowing indicators

Total cost of borrowing to non-financial corporations (%)

DateValue
30.06.2019 3.50
31.05.2019 3.41
30.04.2019 3.24
31.03.2019 3.49
28.02.2019 3.23
31.01.2019 3.23
31.12.2018 3.43
30.11.2018 3.32
31.10.2018 3.20
30.09.2018 3.09
Next »
Total cost of borrowing to non-financial corporations (%),Cost of borrowing indicators

Total cost of borrowing to households for house purchase (%)

DateValue
30.06.2019 2.88
31.05.2019 2.91
30.04.2019 2.94
31.03.2019 2.97
28.02.2019 2.98
31.01.2019 2.93
31.12.2018 2.92
30.11.2018 2.83
31.10.2018 2.77
30.09.2018 2.70
Next »
Total cost of borrowing to households for house purchase (%),Cost of borrowing indicators

Financial statistics of Czech national bank

CNB economics section of the macroeconomics is a public database of the Czech National Bank's. The database defines unified system for presenting time series of aggregated statistical data from Czech economy. Most of these data derive from statistical processing conducted directly by the CNB. However, data from external sources, for example the Czech Statistical Office (CZSO), are also available. Selected CZSO data are published here with its permission. Data searching is based on hierarchical navigation in specific subject areas. The database is updated periodically using data from more than 100 data tables


 
 

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