Download EMBI
get_embi.RdDownload EMBI of different countries
Examples
get_embi("diario")
#> # A tibble: 4,326 × 21
#> Fecha Global LATINO `REP DOM` Argentina Bolivia Brasil Chile Colombia
#> <date> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 2007-10-29 2.10 2.33 2.28 3.50 NaN 1.75 1.12 1.60
#> 2 2007-10-30 2.09 2.31 2.28 3.41 NaN 1.73 1.13 1.57
#> 3 2007-10-31 2.01 2.20 2.13 3.12 NaN 1.66 1.12 1.48
#> 4 2007-11-01 2.12 2.32 2.23 3.29 NaN 1.78 1.10 1.61
#> 5 2007-11-02 2.20 2.40 2.31 3.41 NaN 1.85 1.15 1.68
#> 6 2007-11-05 2.22 2.42 2.28 3.55 NaN 1.85 1.15 1.66
#> 7 2007-11-06 2.18 2.39 2.25 3.45 NaN 1.83 1.15 1.65
#> 8 2007-11-07 2.25 2.48 2.29 3.60 NaN 1.90 1.16 1.76
#> 9 2007-11-08 2.33 2.58 2.40 3.85 NaN 1.99 1.24 1.85
#> 10 2007-11-09 2.36 2.61 2.44 3.87 NaN 2.02 1.23 1.88
#> # ℹ 4,316 more rows
#> # ℹ 12 more variables: `Costa Rica` <dbl>, Ecuador <dbl>, `El Salvador` <dbl>,
#> # Guatemala <dbl>, Honduras <dbl>, México <dbl>, Paraguay <dbl>, Perú <dbl>,
#> # Panamá <dbl>, Uruguay <dbl>, Venezuela <dbl>, `RD-LATINO` <dbl>
get_embi("semanal")
#> # A tibble: 906 × 21
#> Fecha Global LATINO `REP DOM` Argentina Bolivia Brasil Chile Colombia
#> <date> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 2007-10-28 2.11 2.31 2.25 3.34 NaN 1.75 1.12 1.59
#> 2 2007-11-04 2.27 2.50 2.33 3.66 NaN 1.92 1.19 1.76
#> 3 2007-11-11 2.39 2.65 2.50 3.90 NaN 2.02 1.32 1.91
#> 4 2007-11-18 2.65 2.92 2.78 4.31 NaN 2.26 1.46 2.14
#> 5 2007-11-25 2.73 3.01 2.82 4.31 NaN 2.36 1.49 2.19
#> 6 2007-12-02 2.62 2.88 2.77 3.96 NaN 2.23 1.53 2.01
#> 7 2007-12-09 2.46 2.71 2.66 3.77 NaN 2.08 1.55 1.80
#> 8 2007-12-16 2.51 2.80 2.71 4.06 NaN 2.18 1.53 1.88
#> 9 2007-12-23 2.41 2.69 2.62 3.94 NaN 2.06 1.49 1.80
#> 10 2007-12-30 2.64 2.91 2.91 4.23 NaN 2.26 1.52 2.08
#> # ℹ 896 more rows
#> # ℹ 12 more variables: `Costa Rica` <dbl>, Ecuador <dbl>, `El Salvador` <dbl>,
#> # Guatemala <dbl>, Honduras <dbl>, México <dbl>, Paraguay <dbl>, Perú <dbl>,
#> # Panamá <dbl>, Uruguay <dbl>, Venezuela <dbl>, `RD-LATINO` <dbl>
get_embi("mensual")
#> # A tibble: 210 × 21
#> Fecha Global LATINO `REP DOM` Argentina Bolivia Brasil Chile Colombia
#> <date> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 2007-10-01 2.07 2.28 2.23 3.34 NaN 1.71 1.12 1.55
#> 2 2007-11-01 2.47 2.73 2.57 3.97 NaN 2.11 1.34 1.96
#> 3 2007-12-01 2.51 2.78 2.70 3.94 NaN 2.14 1.53 1.88
#> 4 2008-01-01 2.80 3.06 3.28 4.43 NaN 2.42 1.65 2.41
#> 5 2008-02-01 2.90 3.20 3.75 4.77 NaN 2.56 1.69 2.49
#> 6 2008-03-01 3.14 3.44 4.57 5.29 NaN 2.76 1.69 2.63
#> 7 2008-04-01 2.95 3.22 4.43 5.56 NaN 2.43 1.72 2.16
#> 8 2008-05-01 2.74 2.98 4.02 5.53 NaN 2.04 1.59 1.79
#> 9 2008-06-01 2.74 2.93 4.09 5.62 NaN 1.94 1.66 1.81
#> 10 2008-07-01 3.10 3.35 4.89 6.27 NaN 2.32 1.81 2.17
#> # ℹ 200 more rows
#> # ℹ 12 more variables: `Costa Rica` <dbl>, Ecuador <dbl>, `El Salvador` <dbl>,
#> # Guatemala <dbl>, Honduras <dbl>, México <dbl>, Paraguay <dbl>, Perú <dbl>,
#> # Panamá <dbl>, Uruguay <dbl>, Venezuela <dbl>, `RD-LATINO` <dbl>
get_embi("trimestral")
#> # A tibble: 70 × 21
#> Fecha Global LATINO `REP DOM` Argentina Bolivia Brasil Chile Colombia
#> <date> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 2007-10-01 2.46 2.72 2.61 3.91 NaN 2.10 1.41 1.90
#> 2 2008-01-01 2.94 3.23 3.86 4.82 NaN 2.58 1.68 2.51
#> 3 2008-04-01 2.81 3.05 4.18 5.57 NaN 2.14 1.66 1.92
#> 4 2008-07-01 3.38 3.67 5.12 6.97 NaN 2.53 1.81 2.37
#> 5 2008-10-01 7.11 7.60 15.3 17.0 NaN 4.82 3.36 5.40
#> 6 2009-01-01 6.81 7.33 12.4 17.0 NaN 4.30 3.56 4.88
#> 7 2009-04-01 5.03 5.72 8.93 14.6 NaN 3.24 2.40 3.46
#> 8 2009-07-01 3.83 4.18 7.52 9.22 NaN 2.54 1.47 2.70
#> 9 2009-10-01 3.19 3.63 4.66 7.18 NaN 2.16 1.26 2.14
#> 10 2010-01-01 2.97 3.42 4.18 7.33 NaN 2.03 1.23 2.10
#> # ℹ 60 more rows
#> # ℹ 12 more variables: `Costa Rica` <dbl>, Ecuador <dbl>, `El Salvador` <dbl>,
#> # Guatemala <dbl>, Honduras <dbl>, México <dbl>, Paraguay <dbl>, Perú <dbl>,
#> # Panamá <dbl>, Uruguay <dbl>, Venezuela <dbl>, `RD-LATINO` <dbl>
get_embi("anual")
#> # A tibble: 19 × 21
#> Fecha Global LATINO `REP DOM` Argentina Bolivia Brasil Chile Colombia
#> <date> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 2007-01-01 2.46 2.72 2.61 3.91 NaN 2.10 1.41 1.90
#> 2 2008-01-01 4.05 4.37 7.08 8.56 NaN 3.01 2.12 3.04
#> 3 2009-01-01 4.70 5.20 8.35 12.0 NaN 3.05 2.16 3.28
#> 4 2010-01-01 3.01 3.44 3.77 6.89 NaN 2.02 1.29 1.89
#> 5 2011-01-01 3.42 3.53 4.42 6.87 NaN 1.95 1.39 1.68
#> 6 2012-01-01 3.42 3.45 4.63 9.89 3.41 1.83 1.51 1.48
#> 7 2013-01-01 3.18 3.40 3.77 10.7 3.06 2.09 1.54 1.58
#> 8 2014-01-01 3.30 3.44 3.39 7.86 2.55 2.35 1.43 1.67
#> 9 2015-01-01 4.15 4.33 3.85 5.89 2.98 3.61 1.85 2.50
#> 10 2016-01-01 4.09 4.48 4.15 4.75 1.67 3.94 2.00 2.78
#> 11 2017-01-01 3.25 3.62 3.14 4.12 1.73 2.64 1.30 1.94
#> 12 2018-01-01 3.59 3.90 3.14 5.47 2.41 2.65 1.33 1.84
#> 13 2019-01-01 3.56 3.96 3.31 13.1 2.83 2.35 1.36 1.84
#> 14 2020-01-01 4.07 4.65 4.88 22.4 5.40 3.18 1.98 2.62
#> 15 2021-01-01 3.21 3.63 3.52 15.8 4.75 2.82 1.41 2.62
#> 16 2022-01-01 4.05 4.46 4.25 21.8 5.62 2.97 1.78 3.95
#> 17 2023-01-01 3.70 4.11 3.26 22.3 13.1 2.29 1.40 3.58
#> 18 2024-01-01 3.18 4.15 2.20 13.7 20.2 2.11 1.25 3.10
#> 19 2025-01-01 2.92 4.18 2.04 6.56 20.4 2.24 1.24 3.24
#> # ℹ 12 more variables: `Costa Rica` <dbl>, Ecuador <dbl>, `El Salvador` <dbl>,
#> # Guatemala <dbl>, Honduras <dbl>, México <dbl>, Paraguay <dbl>, Perú <dbl>,
#> # Panamá <dbl>, Uruguay <dbl>, Venezuela <dbl>, `RD-LATINO` <dbl>