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Mr. Robin Koepke and Simon Paetzold

Front Matter Page Asia & Pacific Department Contents I. Introduction II. Overview of Capital Flow Data A. Key Capital Flow Data Sources B. Balance of Payments Framework: Misconceptions and Limitations III. Capital Flow Data in the Literature A. Meta-Study of Data Sources Used in the Empirical Literature B. Constructing a Monthly Portfolio Flow Dataset Consistent with BoP Principles IV. Real-Time Tracking of Portfolio Flows V. Conclusion Box 1. The Rise of Portfolio Flow Proxies: What Accounts for the Differences

Mr. Robin Koepke and Simon Paetzold

I. Introduction In early 2020, the COVID-19 pandemic triggered one of the sharpest reversals in portfolio flows to emerging markets (EMs) on record. Timely capital flow proxies served as early warning indicators, alerting policymakers to the severity of the shock. While traditional quarterly balance of payments (BoP) data would only become available several months after 2020:Q1, proxy data on monthly, weekly and even daily flows from Emerging Portfolio Fund Research (EPFR) and the Institute of International Finance (IIF) showed as early as March 2020 that

Mr. Robin Koepke and Simon Paetzold
This paper provides an analytical overview of the most widely used capital flow datasets. The paper is written as a guide for academics who embark on empirical research projects and for policymakers who need timely information on capital flow developments to inform their decisions. We address common misconceptions about capital flow data and discuss differences between high-frequency proxies for portfolio flows. In a nowcasting “horse race” we show that high-frequency proxies have significant predictive content for portfolio flows from the balance of payments (BoP). We also construct a new dataset for academic use, consisting of monthly portfolio flows broadly consistent with BoP data.
Mr. Serkan Arslanalp, Dimitris Drakopoulos, Rohit Goel, and Mr. Robin Koepke

. Conclusion References Figures 1. Correlation Coefficients of EM Local Currency Bond Flows 2. Estimates of Benchmark-Driven Investors 3. Portfolio Flows Proxies 4. Portfolio Outflows During COVID-19 and Country Weights in JPM GBI-EM Global Diversified Index 5. Emerging Market Benchmark-Driven versus Unconstrained Investors 6. Some Emerging Market Issuers Receive a Major Boost from BDI Holders due to Index Rules 7. The Rise of Benchmark Investing in Emerging Markets and the Declining Active Share 8. The Financial Accelerator and External Factors 9. The

International Monetary Fund

appreciation. As in most studies, this is proxied by real per capita GDP growth. Openness to capital flows, proxied by the NFA position as a share of GDP. The expected sign is positive . Increased capital inflows cause higher demand for nontradables and hence an appreciation of RER. Openness to trade flows. The expected sign is negative . Trade liberalizing reforms should depreciate the RER. 9. The empirical model is estimated using the multivariate cointegration procedures developped by Johansen (1988) and Johansen and Juselius (1990) . Equation ( 1 ) assumes an

Mr. Bassem M Kamar and Samy Ben Naceur

RER behavior ( Figure 6 ). An insignificant effect of the capital flows proxies may be the result of central bank interventions. Figure 6. Measures of Capital Flows Overall, the different capital flows proxies reveal certain disparities. The TOT variable represents the most harmonized development, with all variables being positively correlated. For the TKF proxy, Bahrain has no correlation with any other country, and some countries exhibit negative correlations. Regarding the CAPF variable, Kuwait is only correlated with Bahrain, while Bahrain is not

Mr. Joong S Kang

V i , t + ɛ i , t where, I is gross capital expenditure, K is capital stock (defined as gross property, plant and equipment less accumulated reserves for depreciation, depletion and amortization), CF is cash flow proxied by post-income tax earnings before depreciation (=EBIT—interest payment—income tax payment), LEV is the leverage ratio calculated by dividing total debt by common equity, and Q is the sum of market capitalization and total debt divided by total assets. We use firm-level data from