Macro/Finance Group, NIPFP

An exchange market pressure measure for cross country analysis

Patnaik, Ila, Joshua Felman, and Ajay Shah. "An exchange market pressure measure for cross country analysis." Journal of International Money and Finance, 73 (2017): 62-77

Desai, Mohit, Ila Patnaik, Joshua Felman, and Ajay Shah. "A cross-country Exchange Market Pressure (EMP) Dataset." Data in Brief (2017)

EMP measures in the existing literature are oriented towards applications in crisis dating and prediction. We propose a modified EMP measure where cross-country comparisons are possible. This is the sum of the observed change in the exchange rate with an estimated counterfactual of the magnitude of the change in the exchange rate associated with the observed currency intervention. We construct a multi-country dataset for EMP in each month. This opens up many new research possibilities.

Links

Press

Data

Code

To get working with the dataset, here's a short demo R code for loading the dataset and plotting the EMP values for any of the 75 countries in our dataset:

## 1) Read the EMP dataset
library(zoo)
emp.dat <- read.csv("https://macrofinance.nipfp.org.in/FILES/EMP_allcountries_v_2.1.csv")

## 2) Split the dataset by country name
emp.dat.list <- split(emp.dat,emp.dat$country)

## 3) Country names are stored as ISO alpha 2 code of the country followed by ".curr". For example - China is stored as "cn.curr". 
Now we get the 2 letter country code for China
library(ISOcodes)
## Load the dataset of country code
data(ISO_3166_1)
china_cocode <- paste(tolower(ISO_3166_1[grep("^China$",ISO_3166_1$Name),"Alpha_2"]),".curr",sep="")

## 4) Data for EMP values of China
china.emp <- emp.dat.list[[china_cocode]]
china.emp <- zoo(china.emp[,-1],as.Date(china.emp[,1]))

## 5) Plot China EMP
plot(china.emp$curr.emp,ylab="% change in exchange rate",xlab="",type="h",col="midnight blue",ylim=c(-15,15),xaxt = "n")
axis(1, labels = c("1997","2002","2007","2012","2016","2019"), at = c(as.Date("1997-01-01"),as.Date("2002-01-01"),as.Date("2007-01-01"
),as.Date("2012-01-01"),as.Date("2016-01-01"),as.Date("2019-01-01")
))

The above code yields the following graph for China:

Figure 1: Exchange Market Pressure (EMP) values for China

Appendix

The following table lists all the countries and their availability in different EMP data set versions.

S.No. Country Version 1.1 Version 2.0 Version 2.1
1 Algeria Yes Yes No
2 Angola Yes Yes No
3 Antigua & Barbuda Yes Yes No
4 Argentina Yes Yes Yes
5 Armenia Yes Yes Yes
6 Aruba Yes Yes No
7 Australia Yes Yes Yes
8 Austria Yes Yes Yes
9 Azerbaijan Yes Yes No
10 Bahamas Yes Yes No
11 Bahrain Yes Yes No
12 Bangladesh Yes Yes No
13 Barbados Yes Yes No
14 Belarus Yes Yes Yes
15 Belgium Yes Yes Yes
16 Belize Yes Yes No
17 Bhutan Yes Yes No
18 Bolivia Yes Yes Yes
19 Bosnia & Herzegovina Yes Yes No
20 Botswana Yes Yes No
21 Brazil Yes Yes Yes
22 Brunei Yes Yes No
23 Bulgaria Yes Yes Yes
24 Cambodia Yes Yes No
25 Canada Yes Yes Yes
26 Central African Republic Yes Yes No
27 Chile Yes Yes Yes
28 China Yes Yes Yes
29 Colombia Yes Yes Yes
30 Comoros Yes Yes No
31 Congo - Kinshasa Yes Yes No
32 Costa Rica Yes Yes Yes
33 Cote d'Ivoire Yes Yes No
34 Croatia Yes Yes Yes
35 Cyprus Yes Yes Yes
36 Czechia Yes Yes Yes
37 Denmark Yes Yes Yes
38 Djibouti Yes Yes No
39 Dominican Republic Yes Yes Yes
40 Egypt Yes Yes Yes
41 El Salvador Yes Yes Yes
42 Eritrea Yes Yes No
43 Estonia Yes Yes Yes
44 Eswatini Yes Yes No
45 Fiji Yes Yes No
46 Finland Yes Yes Yes
47 France Yes Yes Yes
48 Gambia Yes Yes No
49 Georgia Yes Yes Yes
50 Germany Yes Yes Yes
51 Greece Yes Yes Yes
52 Guatemala Yes Yes Yes
53 Guinea Yes Yes No
54 Guyana Yes Yes No
55 Haiti Yes Yes No
56 Honduras Yes Yes Yes
57 Hong Kong Yes Yes Yes
58 Hungary Yes Yes Yes
59 Iceland Yes Yes Yes
60 India Yes Yes Yes
61 Indonesia Yes Yes Yes
62 Iraq Yes Yes No
63 Ireland Yes Yes Yes
64 Israel Yes Yes Yes
65 Italy Yes Yes Yes
66 Jamaica Yes Yes Yes
67 Japan Yes Yes Yes
68 Jordan Yes Yes Yes
69 Kazakhstan Yes Yes Yes
70 Kenya Yes Yes No
71 Kuwait Yes Yes No
72 Kyrgyzstan Yes Yes Yes
73 Laos Yes Yes No
74 Lebanon Yes Yes No
75 Liberia Yes Yes No
76 Libya Yes Yes No
77 Lithuania Yes Yes Yes
78 Luxembourg Yes Yes Yes
79 Macao Yes Yes No
80 Madagascar Yes Yes No
81 Malawi Yes Yes No
82 Malaysia Yes Yes Yes
83 Maldives Yes Yes No
84 Malta Yes Yes Yes
85 Mauritania Yes Yes No
86 Mauritius Yes Yes Yes
87 Mexico Yes Yes Yes
88 Moldova Yes Yes No
89 Mongolia Yes Yes Yes
90 Morocco Yes Yes Yes
91 Mozambique Yes Yes No
92 Myanmar (Burma) Yes No No
93 Nepal Yes Yes No
94 Netherlands Yes Yes Yes
95 New Zealand Yes Yes Yes
96 North Macedonia Yes Yes Yes
97 Norway Yes Yes Yes
98 Oman Yes Yes No
99 Pakistan Yes Yes No
100 Peru Yes Yes Yes
101 Philippines Yes Yes Yes
102 Poland Yes Yes Yes
103 Portugal Yes Yes Yes
104 Qatar Yes Yes No
105 Romania Yes Yes Yes
106 Russia Yes Yes Yes
107 Rwanda Yes Yes No
108 Samoa Yes Yes No
109 Saudi Arabia Yes Yes Yes
110 Serbia Yes Yes No
111 Seychelles Yes Yes Yes
112 Sierra Leone Yes Yes No
113 Singapore Yes Yes Yes
114 Slovakia Yes Yes Yes
115 Slovenia Yes Yes Yes
116 Solomon Islands Yes Yes No
117 South Africa Yes Yes Yes
118 South Korea Yes Yes Yes
119 Sri Lanka Yes Yes Yes
120 Suriname Yes No No
121 Sweden Yes Yes Yes
122 Switzerland Yes Yes Yes
123 Syria Yes Yes No
124 Tajikistan Yes Yes No
125 Tanzania Yes Yes No
126 Thailand Yes Yes Yes
127 Tonga Yes Yes No
128 Trinidad & Tobago Yes No No
129 Turkey Yes Yes Yes
130 Uganda Yes Yes No
131 Ukraine Yes Yes Yes
132 United Arab Emirates Yes Yes No
133 United Kingdom Yes Yes Yes
134 Uruguay Yes Yes Yes
135 Vanuatu Yes Yes No
136 Venezuela Yes Yes No
137 Vietnam Yes Yes No
138 Yemen Yes No No
139 Zambia Yes Yes No