Abstract
Researchers have available to them numerous indicators of financial openness and integration, many of which have yielded substantially differing results in past research, for example, on the relationship of financial openness or integration with economic growth. This article reviews the main indicators and finds that de jure vs. de facto indicators yield systematically different growth results. Among de jure indicators, sample differences account for much of the variation in growth results, with a weaker impact found in more recent data and among advanced economies. It also finds that many indicators capture different and useful facets of financial openness, such as intensive vs. extensive measures, and de facto vs. de jure. A small minority of indices suffer weaknesses that make them not useful for rigorous economic analysis, most notably the Investment Freedom Index by the Heritage Foundation.
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Notes
Dell’Ariccia and others (2008); Gourinchas and Jeanne (2006); and Kose, Prasad, and Taylor (2011) provide extensive reviews of the related literature. See also the IMF Staff Papers issue (volume 56) on financial globalization.
The volume year for AREAER reports for the previous calendar year, so, for example, volume 1950 reports for the year 1949.
The Balance of Payments defines residence as the “transactor's center of economic interest” (IMF, 1993, p. 20; see also Balance of Payments Manual, 6th ed., 2008).
See, for example, Table footnote 6 in Volume 1996.
Volume 1997 reports 12 categories. The 13th, “personal capital movements,” was added from volume 1998.
Chinn and Ito (2002, 2006, 2008) also make some necessary simplifying assumptions to construct KAOPEN. KAOPEN can pose an econometric problem, however, when used as a dependent variable in annual models. Because it is constructed as a five-year average, some components of KAOPEN would be endogenous to any independent variable lagged less than five periods. See Karcher and Steinberg (forthcoming) for further discussion of KAOPEN.
Various subindices of this data set have been utilized recently in Binici, Hutchison, and Schindler (2010), Prati, Schindler, and Valenzuela (2009) and See Pandya (2011).
Presumably, subjectivity is also an issue in the construction of the AREAER Tables, since its compilers must decide on whether a country's rules are restrictive or not.
For the period governed by the BoPM3 (1961), the prevailing FDI thresholds were 25 to 75 percent; for BoPM4 (1977), the thresholds were 20 to 50 percent; and since BoPM5 (1993), the threshold was equity investment of 10 percent or more. The OECD suggested a 10 percent threshold in 1990, which most OECD countries adopted, albeit at their own speed: Britain in 1997 and Germany in 1999, for example. China and India are among the more extreme examples. China defines Inward FDI as investment by international investors of at least 25 percent of the firm's equity, while India conforms to the prevailing IMF 10 percent threshold, but excludes certain items from reported FDI, resulting in underreporting of Indian FDI compared to other countries. (See Bajpai and Dasgupta, 2004.)
The above-mentioned problems of the definition of FDI apply, but are avoided when considering the aggregate TOTAL which sums FDI and portfolio equity data.
The correlation of saving and investment is an early hybrid measure by Feldstein and Horioka (1980), based on the notion that domestic savings and investment should be less correlated in more financially integrated markets. They found a high (near 1) correlation in a cross-section of OECD countries, suggesting less than perfect capital markets. Later works, in contrast, found a decoupling of savings and investment in the euro area (Blanchard and Giavazzi, 2002), and lower savings-investment correlations that also diminish over time (Fujiki and Kitamura, 1995).
Because most other indices are annual, annual averages of FORU are used here.
See Binici, Hutchison, and Schindler (2010) for the link between de jure regulations and de facto outcomes.
This section draws on related work in Quinn and Toyoda (2008).
We can rank order these countries since most indicators, except the binary EQUITY, provide some measure of the magnitude of restrictions on financial transactions that are comparable across countries.
These include restrictions imposed on nonresident investment in sensitive areas such as nuclear energy.
See http://www.heritage.org/index/Investment-Freedom.aspx. The subcomponents listed include capital controls, foreign exchange controls, expropriation of investments, sectoral investment restrictions, land ownership restrictions, foreign investment code, and national treatment of foreign investment.
These include some national security investment restrictions, restrictions of commercial activities with selected countries, and certain registration requirements. See IMF (2005, pp. 1023–1025).
From 1995 to 2007, the 22 “traditional” OECD members averaged a score of 94 (out of 100) on CAPITAL but 69.5 (out of 90) on IF_Heritage. For 96 emerging markets, the scores were 63 on CAPITAL and 52 on IF_Heritage.
However, the theoretical link may not be quite that clear either, as Henry (2007) points out. Theory predicts only temporary growth effects on a country's transition to a new steady state, helping to understand why tests for permanent growth effects may not come out significantly.
Cline (2010) undertakes a meta-analysis of existing studies and interprets the evidence as supportive of financial integration having a large positive effect on growth. Edison and others (2004) replicate a series of specifications in a cross-section and find only cautious and qualified support for a positive effect. Quinn and Toyoda (2008) replicate six prior studies, including Edison and others (2004) and Rodrik (1998), but using only CAPITAL as the capital account indicator, with a positive and statistically significant association of CAPITAL with growth in all cases.
Kose, Prasad, and Taylor (2011) use a set of control variables that is, roughly speaking, a convex combination of those used in BHL (2005) and QT (2008). Klein and Olivei (2008) are another recent study considering the effects of capital account liberalization on growth. They, however, focus on its interaction with financial depth and consider cross-sections only—by contrast, we are particularly interested in examining the time variation in the various indices and thus focus more on the studies based on panel datasets. Another strand of literature is more microeconomic: Chari and Henry (2004), using firm-level data, find evidence that liberalization brings risk-sharing benefits; using an event-study approach around equity market liberalizations. Also using firm-level data, Prati, Schindler, and Valenzuela (2009) find that capital market liberalizations can provide firms with broader access to credit.
The GMM-SYS models explicitly treat independent variables as endogenous, and use internal instruments and fixed effects to account for these endogenous relationships. The GMM-SYS estimation combines transformed and level equations. The instruments for the transformed equation are lag 3 of the right-hand-side variables plus some instrument (global democracy). The instruments for the levels equations are lag one of the right-hand side variables and the country fixed effects. We also use global averages of world democratization (net of home country democracy lagged two periods) as an external instrument for home country capital account liberalization in both equations. Eichengreen and Leblang (2008) find the causal chain runs from democratization to capital account liberalization.
The PCA transformation will produce as high a variance as possible for the first component. The necessary assumption is that the data are normally distributed.
See model 6 in Table A2, and model 6 in Table A3 in the supplemental appendix. In the five-year models (Tables A2 and A3), TOTAL nonbanking has a negative and statistically significant coefficient estimate.
The PCA loadings are 0.7 for ΔCapital; 0.69 for ΔKAOPEN; 0.636 for ΔFOI; 0.303 for ΔeGLOBE; and 0.041 for ΔTOTAL.
Edison and others (2004) also test Rodrik's (1998) conjecture that capital account liberalization is a proxy for government reputation (as measured in Knack and Keefer, 1995) and find support for it. An important methodological point raised by Cline (2010, pp. 165–6), however, is that the Government Reputation variable is endogenous to rater expectations about future growth based upon past growth. In results not reported here, we find strong evidence supporting Cline's supposition of the endogeneity of government reputation to economic growth.
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Additional information
Supplementary Information accompanies the paper on IMF Economic Review website (http://www.palgrave.com/imfer)
*Dennis P. Quinn is Professor at the McDonough School of Business, Georgetown University; Martin Schindler is Senior Economist at the Joint Vienna Institute and the International Monetary Fund; A. Maria Toyoda is Associate Professor at Villanova University. Funding was provided by the Georgetown University McDonough School of Business; the Graduate School of Arts and Science at Georgetown University; and the National Science Foundation (SBR-9729766, SBR-9810410). The authors are grateful to the editor and two anonymous referees for valuable comments that improved the paper. For comments on a previous draft, the authors also thank Menzie Chinn, Stijn Classens, Axel Dreher, Alexandra Guisinger, Hiro Ito, Philip Lane, Keith Ord, Erica Owen, Sergio Schmuckler, and David Steinberg. Heather Leigh Ba provided research assistance. All errors are the authors’ own.