Calculates Divisia monetary aggregates index as given in Barnett, W. A. (1980).
Usage
# Default S3 method
dmai(.data, method = c("Barnett", "Hancock"), logbase = NULL)References
Barnett, W. A. (1980). Economic Monetary Aggregates: An Application of Aggregation and Index Number Theory. Journal of Econometrics. 14(1):11-48. (https://www.sciencedirect.com/science/article/pii/0304407680900706)
Author
Muhammad Yaseen (myaseen208@gmail.com)
Ahmad Nadeem (Ahmed.Nadeem@sbp.org.pk)
Examples
Data <-
tibble::tibble(
Date = paste(c("Jun", "Dec"), rep(seq(from = 2000, to = 2017, by = 1), each = 2), sep = "-")
, x1 = runif(n = 36, min = 162324, max = 2880189)
, x2 = runif(n = 36, min = 2116, max = 14542)
, x3 = runif(n = 36, min = 92989, max = 3019556)
, x4 = runif(n = 36, min = 205155, max = 4088784)
, x5 = runif(n = 36, min = 6082, max = 186686)
, x6 = runif(n = 36, min = 11501, max = 50677)
, x7 = runif(n = 36, min = 61888, max = 901419)
, x8 = runif(n = 36, min = 13394, max = 347020)
, x9 = runif(n = 36, min = 25722, max = 701887)
, x10 = runif(n = 36, min = 6414, max = 37859)
, x11 = runif(n = 36, min = 11688, max = 113865)
, x12 = runif(n = 36, min = 2311, max = 23130)
, x13 = runif(n = 36, min = 23955, max = 161318)
, r1 = runif(n = 36, min = 0.00, max = 0.00)
, r2 = runif(n = 36, min = 0.00, max = 0.00)
, r3 = runif(n = 36, min = 0.00, max = 0.00)
, r4 = runif(n = 36, min = 0.93, max = 7.43)
, r5 = runif(n = 36, min = 1.12, max = 7.00)
, r6 = runif(n = 36, min = 0.99, max = 7.93)
, r7 = runif(n = 36, min = 1.51, max = 7.42)
, r8 = runif(n = 36, min = 2.20, max = 9.15)
, r9 = runif(n = 36, min = 2.64, max = 9.37)
, r10 = runif(n = 36, min = 2.80, max = 11.34)
, r11 = runif(n = 36, min = 3.01, max = 12.41)
, r12 = runif(n = 36, min = 2.78, max = 13.68)
, r13 = runif(n = 36, min = 3.23, max = 14.96)
)
Data$Date <- as.Date(paste("01", Data$Date, sep = "-"), format = "%d-%b-%Y")
Data
#> # A tibble: 36 × 27
#> Date x1 x2 x3 x4 x5 x6 x7 x8 x9
#> <date> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 2000-06-01 2121643. 12912. 1184412. 1.18e6 3.26e4 18065. 3.36e5 2.42e4 3.68e5
#> 2 2000-12-01 2542557. 13351. 1075745. 1.04e6 1.79e5 27562. 5.11e5 1.00e5 3.76e5
#> 3 2001-06-01 2230571. 9788. 234200. 2.57e6 1.85e5 19189. 5.87e5 3.06e5 5.03e5
#> 4 2001-12-01 2570691. 3781. 1904380. 1.69e6 9.57e4 21663. 2.05e5 2.96e5 5.88e5
#> 5 2002-06-01 1402978. 11836. 2906729. 3.14e6 1.72e5 49518. 1.54e5 1.90e4 6.69e4
#> 6 2002-12-01 614500. 7449. 2009775. 1.68e6 7.33e4 43298. 1.52e5 7.47e4 2.53e5
#> 7 2003-06-01 1045889. 13638. 1586393. 3.29e6 1.55e5 25118. 1.40e5 5.20e4 5.68e5
#> 8 2003-12-01 1546327. 11724. 532261. 3.72e6 1.07e5 48262. 5.11e5 1.73e5 2.17e5
#> 9 2004-06-01 2140129. 5343. 2640413. 4.03e6 1.50e5 17902. 8.14e5 3.30e5 5.77e5
#> 10 2004-12-01 2852295. 6108. 1598537. 2.49e6 6.97e4 17644. 6.58e5 2.89e5 1.71e5
#> # ℹ 26 more rows
#> # ℹ 17 more variables: x10 <dbl>, x11 <dbl>, x12 <dbl>, x13 <dbl>, r1 <dbl>,
#> # r2 <dbl>, r3 <dbl>, r4 <dbl>, r5 <dbl>, r6 <dbl>, r7 <dbl>, r8 <dbl>,
#> # r9 <dbl>, r10 <dbl>, r11 <dbl>, r12 <dbl>, r13 <dbl>
# Divisia monetary aggregates index using Barnett method
DMAIBarnett <- dmai(.data = Data, method = "Barnett", logbase = NULL)
DMAIBarnett
#> # A tibble: 36 × 2
#> # Groups: Date [36]
#> Date DMAI
#> <date> <dbl>
#> 1 2000-06-01 NA
#> 2 2000-12-01 4.21
#> 3 2001-06-01 1.04
#> 4 2001-12-01 10.3
#> 5 2002-06-01 -0.777
#> 6 2002-12-01 -21.0
#> 7 2003-06-01 9.94
#> 8 2003-12-01 -1.05
#> 9 2004-06-01 23.1
#> 10 2004-12-01 -9.54
#> # ℹ 26 more rows
DMAIBarnett1 <- dmai(.data = Data, method = "Barnett", logbase = 10)
DMAIBarnett1
#> # A tibble: 36 × 2
#> # Groups: Date [36]
#> Date DMAI
#> <date> <dbl>
#> 1 2000-06-01 NA
#> 2 2000-12-01 4.21
#> 3 2001-06-01 1.04
#> 4 2001-12-01 10.3
#> 5 2002-06-01 -0.777
#> 6 2002-12-01 -21.0
#> 7 2003-06-01 9.94
#> 8 2003-12-01 -1.05
#> 9 2004-06-01 23.1
#> 10 2004-12-01 -9.54
#> # ℹ 26 more rows
DMAIBarnett2 <- dmai(.data = Data, method = "Barnett", logbase = 2)
DMAIBarnett2
#> # A tibble: 36 × 2
#> # Groups: Date [36]
#> Date DMAI
#> <date> <dbl>
#> 1 2000-06-01 NA
#> 2 2000-12-01 14.0
#> 3 2001-06-01 3.45
#> 4 2001-12-01 34.2
#> 5 2002-06-01 -2.58
#> 6 2002-12-01 -69.7
#> 7 2003-06-01 33.0
#> 8 2003-12-01 -3.49
#> 9 2004-06-01 76.8
#> 10 2004-12-01 -31.7
#> # ℹ 26 more rows
DMAIBarnett3 <- dmai(.data = Data, method = "Barnett", logbase = exp(1))
DMAIBarnett3
#> # A tibble: 36 × 2
#> # Groups: Date [36]
#> Date DMAI
#> <date> <dbl>
#> 1 2000-06-01 NA
#> 2 2000-12-01 9.69
#> 3 2001-06-01 2.39
#> 4 2001-12-01 23.7
#> 5 2002-06-01 -1.79
#> 6 2002-12-01 -48.3
#> 7 2003-06-01 22.9
#> 8 2003-12-01 -2.42
#> 9 2004-06-01 53.2
#> 10 2004-12-01 -22.0
#> # ℹ 26 more rows
# Divisia monetary aggregates index using Hancock method
DMAIHancock <- dmai(.data = Data, method = "Hancock")
DMAIHancock
#> # A tibble: 36 × 2
#> # Groups: Date [36]
#> Date DMAI
#> <date> <dbl>
#> 1 2000-06-01 NA
#> 2 2000-12-01 15.3
#> 3 2001-06-01 29.4
#> 4 2001-12-01 112.
#> 5 2002-06-01 19.5
#> 6 2002-12-01 -33.8
#> 7 2003-06-01 37.6
#> 8 2003-12-01 16.2
#> 9 2004-06-01 108.
#> 10 2004-12-01 -13.0
#> # ℹ 26 more rows
library(ggplot2)
ggplot(data = DMAIBarnett, mapping = aes(x = Date, y = DMAI)) +
geom_point() +
geom_line() +
geom_text(aes(label = round(DMAI, 2)), vjust = "inward", hjust = "inward") +
scale_x_date(
date_breaks = "6 months"
, date_labels = "%b-%Y"
, limits = c(min(DMAIBarnett$Date), max = max(DMAIBarnett$Date))) +
theme_bw() +
theme(axis.text.x = element_text(angle = 90))
#> Warning: Removed 1 row containing missing values or values outside the scale range
#> (`geom_point()`).
#> Warning: Removed 1 row containing missing values or values outside the scale range
#> (`geom_line()`).
#> Warning: Removed 1 row containing missing values or values outside the scale range
#> (`geom_text()`).
ggplot(data = DMAIHancock, mapping = aes(x = Date, y = DMAI)) +
geom_point() +
geom_line() +
geom_text(aes(label = round(DMAI, 2)), vjust = "inward", hjust = "inward") +
scale_x_date(
date_breaks = "6 months"
, date_labels = "%b-%Y"
, limits = c(min(DMAIHancock$Date), max = max(DMAIHancock$Date))) +
theme_bw() +
theme(axis.text.x = element_text(angle = 90))
#> Warning: Removed 1 row containing missing values or values outside the scale range
#> (`geom_point()`).
#> Warning: Removed 1 row containing missing values or values outside the scale range
#> (`geom_line()`).
#> Warning: Removed 1 row containing missing values or values outside the scale range
#> (`geom_text()`).
