# Currency Crises Prediction Using Deep Neural Decision Trees
## 3 Data and Variables  
The sample used in this study comprised 162 developed, emerging, and developing countries with information for the period 1970-2017 (Appendix A). The granularity of the data was annual, following the format data of previous works [1,12,38]. The dataset of the present study had 7708 observations, being 236 crisis observations. Specifically, a set of 32 explanatory variables chosen from the existing literature on the prediction of currency crises was obtained. Of these, 23 corresponded to factors related to debt exposure, the external sector, domestic macroeconomy, and the banking sector [1,14,15,17,19]. This information was sourced from the International Monetary Fund (IMF) International Financial Statistics, World Bank Development Indicators, World Economic Outlook, and the World Bank Global Financial Database. The nine remaining variables refer to political factors and have been extracted from the database of the Polity IV Project of Center for Systemic Peace, selecting the variables used in Reference [39]. The dependent variable was constructed based on the definition in Reference [38]: \"a currency crisis is defined as a nominal depreciation of the currency with respect to the US dollar by at least 30% and at least 10 percentage points higher than the depreciation rate for the previous year\". This dependent variable was 1 for the years in which currency crises occurred and 0 otherwise. The choice of countries was mainly guided by the availability of data, covering four main regions: Africa and the Middle East, South and East Asia, Latin America, and Europe. Table 1 shows the independent variables used in this research.  
\begin{table}
\begin{tabular}{c c c c} \hline \hline
**Category** & **Code** & **Definition** & **Expected Sign 1** \\ \hline \multirow{4}{*}{**Debt Exposure**} & Total Debt & gross external debt as \% of GDP & + \\ \cline{2-4}  & Short-Term Debt & gross short-term external debt as \% of GDP & + \\ \cline{2-4}  & Real Interest Rate & lending interest rate adjusted for inflation & + \\ \hline \multirow{4}{*}{**External Sector**} & Foreign Exchange & \multirow{2}{*}{total reserves (without gold) as \% of GDP} & \multirow{2}{*}{–} \\  & Reserves & & \\ \cline{2-4}  & Trade Openness & ratio of exports plus imports to GDP & +/– \\ \cline{2-4}  & Imports & imports of goods and services at current prices in USD & +/– \\ \cline{2-4}  & Exports & exports of goods and services at current prices in USD & – \\ \cline{2-4}  & Current Account & current account balance as \% of GDP & – \\ \cline{2-4}  & Portfolio Investments & portfolio investment net at current USD & – \\ \cline{2-4}  & FDI & net FDI inflows as \% of GDP & – \\ \hline \multirow{4}{*}{**Domestic Macroeconomic**} & Real GDP & annual real GDP at current USD & – \\ \cline{2-4}  & Real GDP Growth & annual growth of real GDP & – \\ \cline{2-4}  & Inflation & rate of change in CPI & + \\ \cline{2-4}  & M2 Multiplier Growth & annual growth of M2 & + \\ \cline{2-4}  & M2/Reserves & ratio of M2 to foreign exchange reserves & + \\ \cline{2-4}  & REER Overall & deviation of real effective exchange rate from 5 year rolling mean & – \\ \cline{2-4}  & Government Spending & general government final spending as \% of GDP & +/– \\ \cline{2-4}  & Fixed Capital Formation & gross fixed capital formation at current USD & – \\ \cline{2-4}  & Unemployment & unemployment total as \% of total labor force & + \\ \cline{2-4}  & Contagion & event of a currency crisis in any country of the same region (t \(-\) 1) & + \\ \hline \multirow{4}{*}{Soft Peg 2} & exchange rate regime applied to currency to keep its value stable & \multirow{2}{*}{+} \\  & against a reserve currency & & \\ \cline{1-1} \cline{2-4}  & Peg 2 & exchange rate regime in which a currency’s value is fixed against & \multirow{2}{*}{+} \\ \cline{1-1} \cline{2-4}  & & either the value of another country’s currency & \\ \hline \hline \end{tabular}
\end{table}
Table 1: Independent variables.