# **2 Data and Methodology**

## **2.1 Data Description and Variable Construction**

The variables we use for the U.S. economy include first a measure of U.S. monetary policy shocks (MP), as explained in the next section. We also control for domestic credit conditions and financial market liquidity by including the excess bond premium (EBP) from Gilchrist et al. (2021). Other U.S. variables include commodity prices (CP), consumer price index (P), industrial production index (IP), and the 10-year government bond yield (R10).<sup>3</sup> As our main focus is to evaluate the efficacy of capital controls, we begin considering which non-US (“foreign” hereafter) countries to include in the study. We do this based on the availability of data on capital controls. We use the overall capital restriction index (KC) by Fernández, Klein, Rebucci, Schindler & Uribe (2016) (FKRSU hereafter) in our main analysis. This measure covers 99 foreign countries over 1995-2019, ranging from 0-1, with 1 indicating the greatest restriction.<sup>4</sup> For each of these 99 countries, we collect exchange rate per USD (in logs and denoted as S) from the IMF’s International Financial Statistics (IFS) database. We obtain foreign interest rate (R<sup>_∗_</sup> ) and industrial production (IP<sup>_∗_</sup> ) from three data resources: IFS; Federal Reserve Economic Data (FRED); and Haver Analytics. We supplement interest rate data with the BIS policy rates, and also statistics published by countries’ central banks if possible. When multiple interest rate series are<sup>6</sup> available, we choose the one closest to the U.S. 3-month Treasury bill rate.<sup>5</sup> We select data series—and hence countries—based on the criterion that the series has no more than five missing values.<sup>7</sup> Among the 99 countries, we find 44 with sufficient data for all foreign variables, hence are allowed to be included in a “Full” VAR analysis described later. There are 34

> 3The specific series we use are: “Producer Price Index by Commodity: All Commodities”(PPIACO), “Consumer Price Index: Total All Items for the United States”(CPALTT01USM661S), “Industrial Production: Total Index”(INDPRO) and “Long-Term Government Bond Yields: 10-year: Main (Including Benchmark) for the United States”(IRLTLT01USM156N). They are all downloaded from FRED St. Louis and adjusted for seasonality by Fed X-11 routine whenever needed. In computing CP, P and IP, we take the log of each raw series and multiply by 100.

> 4The measure integrates 0/1 indicators of controls in 32 transaction categories. Each of these indicators belongs to one of the 10 _asset_ categories, and represents restrictions either on inflows or outflows. The subset of indicators under each _asset_ category are then averaged to get two indicators - one for outflow, another for inflow. FKRSU then define the overall inflow (outflow) restrictions index - KCI (KCO) - as the average of the 10 inflow (outflow) indices. Our main KC measure is the average of KCI and KCO. We check robustness to use KCI or KCO, or on selected asset categories.

> 5We refer to the IFS World Notes to determine the exact maturities of each interest rate variable for each country. For instance, when there are no series explicitly defined as “3M Tbills”, we search for descriptions like “91-day” or “3-month”, if these do not exist either, we further try “6M”, “9M” etc. We examine robustness to a sub-sample of countries for which only short-term rates with maturities under 1-year are available.

> 6To enlarge sample size, we use interest rate series with the most sufficient data. In subsection 6.3, we also look at specific “policy rate” following the definition of De Leo et al. (2022).

> 7Relaxing this criterion up to 12 enlarges the sample only by retaining small islands or countries with annual GDP less than 20 bil.$; while further restricting the cutoff to below 5 would drop some Latin American countries like Argentina and Chile with interesting capital control histories.

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