The 24 references without contexts in paper Maria Sole Pagliari, Swarnali Ahmed Hannan (2017) “The Volatility of Capital Flows in Emerging Markets: Measures and Determinants” / RePEc:rut:rutres:201710

1
Aghion, P.; Bacchetta, P. & Banerjee, A. (2004), 'Financial development and the instability of open economies', Journal of Monetary Economics 51(6), 1077--1106.
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2
Ahmed S.; Curcuru S. & Warnock, F. (2015), 'Decomposing International Portfolio Flows'
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Alfaro, L.; Kalemli-Ozcan, S. & Volosovych, V. (2007), Capital flows in a globalized world: The role of policies and institutions'Capital Controls and Capital Flows in Emerging Economies: Policies, Practices and Consequences', University of Chicago Press, pp. 19-72.
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Arezki, R., A. Mazarei, and A. Prasad (2015), 'Sovereign wealth funds in the new era of oil', VoxEU.org, 29 November.
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7
Bacchetta, P. & Van Wincoop, E. (1998), 'Capital flows to emerging markets: liberalization, overshooting, and volatility', Technical report, National Bureau of Economic Research.
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10
Boot, J., Feibes, W., & Lisman, J. (1967). Further Methods of Derivation of Quarterly Figures from Annual Data. Journal of the Royal Statistical Society. Series C (Applied Statistics), 16(1), 65-75. doi:10.2307/2985238
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12
Broto, C.; Díaz-Cassou, J. & Erce, A. (2011), 'Measuring and explaining the volatility of capital flows to emerging countries', Journal of Banking & Finance 35(8), 1941-1953.
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15
Chuang, C.-C.; Kuan, C.-M. & Lin, H.-y. (2009), 'Causality in quantiles and dynamic stock return–volume relations', Journal of Banking & Finance 33(7), 1351--1360.
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16
Chudik, Alexander & Pesaran, M. Hashem (2015), "Common correlated effects estimation of heterogeneous dynamic panel data models with weakly exogenous regressors," Journal of Econometrics, Elsevier, vol. 188(2), pages 393-420.
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17
Devereux, Michael B. and Sutherland, A. (2009), 'A portfolio model of capital flows to emerging markets', Journal of Development Economics, Elsevier, vol. 89(2), pages 181-193, July.
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19
Easterly, W.; Islam, R. & Stiglitz, J. E. (2001), 'Shaken and Stirred: Explaining Growth Volatility', The World Bank Washington, DC, 191.
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20
Engle, R. F. & Rangel, J. G. (2008), 'The Spline-GARCH Model for Low-Frequency Volatility and Its Global Macroeconomic Causes', Review of Financial Studies 21(3), 1187-1222.
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21
Forbes, K.; Reinhardt, D. & Wieladek, T. (2016), 'The Spillovers, Interactions, and (Un)Intended Consequences of Monetary and Regulatory Policies'(22307), Technical report, National Bureau of Economic Research.
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24
Ghosh, A. R.; Ostry, J. D. & Qureshi, M. S. (2016), 'When Do Capital Inflow Surges End in Tears?', American Economic Review 106(5), 581-85.
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25
Ghosh, A. R.; Qureshi, M. S.; Kim, J. I. & Zalduendo, J. (2014), 'Surges', Journal of International Economics 92(2), 266-285.
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29
Jinjarak, Y.; Wongswan, J. & Zheng, H. (2011), 'International fund investment and local market returns', Journal of Banking & Finance 35(3), 572--587.
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34
Neumann, R. M.; Penl, R. & Tanku, A. (2009), 'Volatility of capital flows and financial liberalization: Do specific flows respond differently?', International review of economics & finance 18(3), 488--501.
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35
Obstfeld, M. (2012a), 'Does the Current Account Still Matter?', American Economic Review 102(3), 1-23.
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42
Umutlu, M.; Akdeniz, L. & Altay-Salih, A. (2010), 'The degree of financial liberalization and aggregated stock-return volatility in emerging markets', Journal of banking & finance 34(3), 509--521.
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VI. APPENDIX A. Countries and Regions Asia (AS): China, India, Indonesia, Kazakhstan, Malaysia, Philippines, Sri Lanka, Thailand; Europe (EU): Albania, Bulgaria, Croatia, Hungary, Lithuania, Latvia, Poland, Romania, Russia; Latin America (LATAM): Brazil, Chile, Colombia, Costa Rica, Ecuador, El Salvador, Guatemala, Mexico, Peru, Paraguay, Uruguay; Middle East and Africa (MEAF): Egypt, Jordan, Saudi Arabia, South Africa, Turkey.
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B. Data Capital flows: 1970Q1-2016Q4 from International Financial Statistics (IFS); missing quarterly data have been extrapolated from the annual series using the disaggregation technique of Boot et al. (1967). Real GDP: 1970Q1-2016Q4 from IFS; missing quarterly data have been extrapolated from the annual series using the disaggregation technique of Boot et al. (1967); non-seasonally adjusted series have been adjusted using the US Census’ X13 program; growth rates are y-o-y. Nominal GDP: 1970Q1-2016Q4 from IFS; missing quarterly data have been extrapolated from the annual series using the disaggregation technique of Boot et al. (1967); non-seasonally adjusted series have been adjusted using the US Census’ X13 program. CPI: 1970Q1-2016Q4 from IFS; missing quart
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1993. For Euro Area members (Latvia and Lithuania), national exchange rates after the adoption of Euro have been computed by multiplying the fixed national currency/EUR conversion rate, reported by Eurostat, times the EUR/USD exchange rate as reported by the European Central Bank (ECB). Exchange rates are included in the regressions in real terms, i.e.: !"#= %&' ()*&'
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Wu-Xia US Shadow Rate: 1970Q1:2016Q4 from the Federal Reserve Bank of Atlanta. When positive, the shadow rate coincides with the Fed Fund rate. S&P 500 realized returns: 1970Q1:2016Q4 from the FRED database of the Federal Reserve Bank of St. Louis. The rate is annualized. US real GDP: 1970Q1:2016Q4 from IFS. US CPI: 1970Q1:2016Q4 from IFS; 2010=100. US M2: 1970Q1:2016Q4 from the FRED database of the Federal Reserve Bank of St. Louis. US Current Account: 1970Q1:2016Q4 from IFS. Commodity price index: 1970Q1:2016Q4 from the Hamburg Institute of International Economics (HWWI); 2005=100. C. Regression tests Endogeneity In order to check whether the right-end side variables are affected by endogeneity, we first run panel regressions with variables and specificatio
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Instrument Statistic Distribution P-value Total 5.91E-16 F(11,146) 1.00 FDI 3.35E-16 F(11,146) 1.00 Portfolio 7.66E-16 F(11,146) 1.00 Portfolio Debt 9.62E-16 F(11,146) 1.00 Portfolio Equity 2.12E-15 F(11,146) 1.00 Other 1.92E-15 F(11,146) 1.00 Other - private 6.30E-16 F(11,146) 1.00 Other - government 3.36E-16 F(11,146) 1.00 Other - banks 8.57E-16 F(11,146) 1.00 Other - non-banks 7.92E-16 F(11,146) 1.00
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