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The Feldstein–Horioka puzzle revisited: Is the home-bias much less?
International Review of Economics and Finance 18 (2009) 341–350
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International Review of Economics and Finance j o u r n a l h o m e p a g e : w w w. e l s ev i e r. c o m / l o c a t e / i r e f
The Feldstein–Horioka puzzle revisited: Is the home-bias much less? George Georgopoulos a,⁎, Walid Hejazi b a b
Economics, York University, Toronto, Canada Rotman School of Management, University of Toronto, Toronto, Canada
a r t i c l e
i n f o
Article history: Received 11 April 2006 Received in revised form 24 April 2007 Accepted 28 August 2007 Available online 20 March 2008 JEL Classification: C23 F30
a b s t r a c t The large correlation between domestic savings and investment is well documented and is known as the Feldstein–Horioka puzzle. We demonstrate that estimates of the FH coefficients using the standard framework are biased upward in the presence of highly positively correlated inward and outward capital flows. Using data for the 14 OECD countries, the analysis shows that the significant home bias documented by FH and others is also consistent with much higher levels of capital mobility when capital outflows and inflows are highly positively correlated. Taking account for these correlations reduces the estimated home bias somewhere between 45% and 90%. © 2008 Published by Elsevier Inc.
Keywords: Feldstein–Horioka puzzle Capital flows
1. Introduction In their seminal contribution, Feldstein and Horioka (1980, henceforth FH) document a significant home-bias in terms of where domestic savings are invested. In regressing the ratio of investment to GDP on the ratio of savings to GDP for 16 OECD countries over the averaged period of 1960 to 1974, FH (1980) find the estimated savings retention coefficient (the fraction of a dollar of increased savings that is invested domestically) to be between 0.8 and 0.9. This result has been interpreted as indicating a low level of international capital mobility, and has been labeled as the Feldstein–Horioka puzzle. This finding has been replicated by several authors, including, Dooley, Frankel and Mathieson (1987), Feldstein and Bacchetta (1989), Frankel (1991), Tesar (1991), and Mussa and Goldstein (1993). There are several published studies that challenge the FH results. The challenges are based on, for example, the presence of productivity shocks which cause both savings and investment rates to rise simultaneously, thus giving the appearance of a home bias (Obstfeld, 1986; Westphal, 1983). Others look at large country influences on world interest rates (Baxter & Crucini, 1993; Dooley et al., 1987). Kraay and Ventura (2000) suggest a high FH coefficient reflects a low proportion of foreign to total assets held by agents due to the presence of high investment risk and weak diminishing returns. Ventura (2003) attributes the high correlation between savings and investment to investment risk and adjustment costs to investment. Despite these extensions, the empirical evidence, for the most part, still implies a significant home bias in terms of where domestic savings are invested. This current paper represents another attempt to shed light on this very important question, but takes a different approach. The current paper extends the analysis of the FH puzzle to incorporate the possibility that the presence of highly correlated outward and inward capital flows may also be a contributing factor to the empirical home bias result. To illustrate, consider the following example. Suppose a country has a $100 increase in domestic savings. These domestic savings can be invested domestically or abroad. The FH result implies that much of these domestic savings are invested locally. But
⁎ Corresponding author. Economics, Atkinson Faculty of Liberal and Professional Studies, 4700 Keele Street, Toronto, Canada, M3J 1P3. Tel.: +1 416 736 2100x30108; fax: +1 416 736 5188. E-mail address: [email protected] (G. Georgopoulos). 1059-0560/$ – see front matter © 2008 Published by Elsevier Inc. doi:10.1016/j.iref.2007.08.004
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to get a clearer picture of the home bias, consideration must be given to capital flows, both inward and outward. It may be the case that the entire $100 increase in savings is invested domestically. Alternatively, it may be the case that $30 of increased domestic savings are invested abroad, and at the same time $30 of foreign savings flow into the domestic country. If such patterns were common, indicating inward and outward capital flows are highly correlated, then the coefficient in the FH regression would equal one, but of course the amount of international capital mobility is very different. This paper estimates the FH coefficients for a sample of 23 developed, 18 emerging, and 21 developing countries over the 1975 to 2004 period. Similar to previous studies, significant home biases are documented. Using the standard FH approach, the home bias is found to be highest for developed countries, lowest for developing, with emerging economies falling in between. The analysis is then extended to allow the home bias coefficient to depend directly on the correlation between inward and outward capital flows, something that has not been done before. The results indicate that accounting for these correlations yields lower home bias estimates for the sample of developed and emerging economies, but not for developing economies. The empirical evidence reported below is therefore consistent with the hypothesis that there can be high levels of capital mobility, yet in the presence of highly correlated capital inflows and outflows, the standard FH regression would not capture this. Furthermore, the standard FH analysis would find a low level of capital mobility. An important contribution of this paper therefore is that it explores whether the Feldstein–Horioka puzzle is present in an environment of large two-way international capital flows, and hence contributes to the recent international finance literature on contemporary financial globalization. This literature brings to attention the fact that for industrialized economies external assets and liabilities increased simultaneously since post-World War II, and significantly so beginning in the 1980s, a result discussed in Obstfeld and Taylor (2004). They argue that these patterns are evidence of risk diversification. The current paper is conceptually related to the work of Kraay and Ventura (2000) and Ventura (2003) who show that the saving-investor correlation is a decreasing function of the extent of national wealth diversification. The format of this paper is as follows. Section 2 provides a brief review of the relevant literature. Section 3 reconsiders tests of the FH hypothesis by explicitly accounting for correlations between inward and outward capital flows. Section 4 describes the capital flow data, including correlations between inward and outward capital flows. Section 5 provides empirical results. Conclusions and policy implications are provided in Section 6. 2. Literature review Although the volume of work on the FH puzzle is substantial, this literature review will focus only on those papers most closely related to the analysis in the current paper. For more extensive literature reviews, see Tesar (1991) and Coakley, Kulasi and Smith (1998). Studies that challenge the FH puzzle suggest this outcome is due to the simultaneous movement in trade deficits, government revenue, and domestic investment (Westphal, 1983), and large country influences on world interest rates (Baxter & Crucini, 1993; Dooley et al., 1987). Not explicitly accounting for these factors gives rise to a positive correlation between domestic investment and domestic savings even in an environment of significant global capital flows. Ventura (2003) and Kraay and Ventura (2000) take another approach, regressing the current account on savings using data from 21 industrial countries over the period 1966–1997, taking into account growth in both productivity and population, two common sources of variation in savings and investment as predicted by Franco Modigliani's life-cycle theory of savings. They find the coefficient on savings to be 0.240, significantly smaller than the value of one which is predicted by the traditional intertemporal theory of the current account. In the context of the Feldstein–Horioka model, this implies a 1% increase in savings leads to a 0.76% rise in investment, suggesting a large home bias. The authors extend the traditional model and provide an alternative theory on why savings and investment would be correlated. They suggest investors in a particular country invest their marginal unit of wealth in a manner similar to the average unit of wealth. This behaviour is more prevalent in the context of high investment risk and weak diminishing returns, as opposed to low investment risk and strong diminishing returns characteristic of the traditional intertemporal model. In the former case a rise in income would lead to a proportional increase in all assets currently held, domestic and foreign. The strong desire for diversification would make investors reluctant to rebalance their portfolios towards any given asset; the size of the portfolio would increase, but not its composition. This is in contrast to the traditional view that predicts that most if not all of the increase in savings should be invested abroad. Kraay and Ventura (2000)'s alternative model relates the FH savings retention coefficient to the proportion of a country's foreign assets to total assets. Specifically, the lower the ratio of foreign assets to total assets, the higher is the savings retention coefficient. This model is therefore related to the issue of national wealth diversification. Kraay and Ventura (2000) use data from 13 industrial countries over the period 1973–1995, and regress the current account on the savings rate interacted with the share of foreign assets to total assets. They find an estimated slope coefficient of 0.95. Their results indicate therefore that the lower the ratio of foreign assets to total assets, the higher is the savings retention coefficient. Ventura (2003) incorporates investment risk and adjustment costs of switching from domestic to foreign assets. He finds that the higher the adjustment costs, the lower the proportion of foreign to total assets held, yielding a high investment-savings correlation. The results of the academic literature discussed above are therefore in contrast to the widely held perception of highly integrated global capital markets that see capital flow to countries that provide investors with the highest risk adjusted rates of return. These high levels of capital mobility certainly played significant roles in the recent Argentine and East Asian financial crises. It therefore remains an open question—to what extent is there global capital market integration? Do the low levels of international capital mobility implied by the FH results truly reflect the reality, or is the academic literature missing something important?
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There are two recent studies which establish more capital mobility than the above studies indicate. The first, Georgopoulos and Hejazi (2005), argue that in the presence of relatively high transactions costs associated with investing abroad, a home bias should be expected. They argue that the relevant question is not whether a bias exists, but rather whether the biases are consistent with individual optimizing behaviour.1 That question is not answered. Nevertheless, innovations in financial markets and information technology have resulted in a fall in such transactions costs, and this should lead to a rise in capital mobility, and as a result a fall in the home bias. The empirical evidence presented confirms the intuition that the bias has fallen over the past three decades. The second paper goes further towards explaining the bias. Coakley, Fuertes and Spagnolo (2004) use sophisticated econometric techniques to ensure that a country's intertemporal budget constraint is satisfied, which means that the current account must be stationary. Put differently, this constraint implies that a country's savings and investment rates must cointegrate. Using a mean group regression approach that is robust to persistent innovations and accounts for country heterogeneity and crosssectional dependence, the study finds no evidence of the Feldstein–Horioka puzzle. That is, their evidence is supportive of highly mobile capital across their sample of 12 OECD countries over the period 1980 to 2000. This is the first study to fully account for the FH bias, and hence is an important contribution to this literature. While most of the existing literature has focused on developed countries, there are some studies that consider developing economies. For example, Dooley et al. (1987) find a lower savings coefficient for developing countries relative to OECD countries. They attribute this result to the “country size” factor, where these relatively small developing countries take the world interest rate as given, and as such not yielding an upward bias on the savings–investment correlation typically found in larger countries. Other factors contributing to relatively lower savings coefficients are the existence of foreign aid for these countries (Dooley et al., 1987; Payne & Kumazawa, 2005) and greater capital flow controls (Payne & Kumazawa, 2006). Mamingi (1994) and Payne and Kumazawa (2006) also find a relatively lower savings coefficient on developing countries. Payne and Kumazawa (2006) test the FH puzzle using a sample of 47 developing countries over the period 1980–2003 and find a smaller FH coefficient than for OECD countries. Coakley et al. (2004) call for further study of the FH puzzle using both developing and emerging markets. The analysis undertaken below therefore contributes to the existing literature in two distinct ways. First, the framework for testing for a home bias is extended to allow the FH coefficient to depend directly on the correlation between inward and outward capital flows. Secondly, we estimate the FH regressions using three separate samples: developed economies, developing economies, and emerging economies, and hence work to fill the void noted by Coakley et al. (2004). 3. Reconsidering the FH puzzle: Accounting for capital flow correlations Using a sample of OECD countries over the period 1960 to 1974, Feldstein and Horioka (1980) estimate the following regression: GDIi =GDPi ¼ a0 þ a1 ½GNSi =GDPi þ ui
ð1Þ
where GDI measures gross domestic investment, GNS gross national savings, GDP gross domestic product, and i indexes country. The data for each country were averaged over the 1960 to 1974 sample period, and hence there is one observation per country— that is, the regression is cross sectional. The estimate of α1 captures the FH bias—that is, the bias in terms of where increases in domestic savings are invested. In a world of perfect capital mobility, the savings retention coefficient should be zero: the change in domestic investment would not depend on the change in savings generated in that country because savings would flow to the location with the most productive investment opportunities. In sharp contrast to this scenario, the FH analysis finds a strong bias to invest increases in savings in the home country. For OECD countries, the estimated savings retention coefficient (the fraction of a dollar of increased savings that is invested domestically) is estimated to be between 0.8 and 0.9. The Feldstein–Horioka results have been replicated by several authors, including Frankel (1991) and Mussa and Goldstein (1993). We argue that a positive correlation between inward and outward capital flows will result in an upward bias in the savings retention coefficient. That is, the estimated value of α1 in Eq. (1) above will over-estimate the true home bias. To address this, we extend the standard FH specification to explicitly account for these correlations. Define CORRit as the correlation between inward and outward capital flows for country i. The t subscript indicates that this correlation will be allowed to vary over the sample in a way that is discussed below. The following specification is therefore proposed:2 ðI=Y Þit ¼ b0i þ ðb1 þ b2 CORRit ÞðS=Y Þit þeit
ð2Þ
There is both a subscript for country i and period t as the model will be estimated in a panel where we average observations over time periods, as well as in a cross-section when we average observations over the entire sample, in which case the t subscript would be suppressed and β0i would become β0. This specification links the FH coefficient directly to correlations between inward and outward capital flows. If the relationship between investment and savings rates were unrelated to the correlation between inward and outward flows, then the estimated value of β2 would equal zero, and specification (2) would collapse to a standard 1 To the extent the “home bias” can be explained by a formal model that accounts for such transactionscosts, then they should not be considered as biases. See Georgopoulos and Hejazi (2005) for a discussion of this issue. 2 We thank an anonymous referee for suggesting this specification.
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Table 1 Developed countries I/Y
S/Y
Mean
S.D.
Mean
S.D.
Panel A: Developed countries Australia Austria Canada Cyprus Denmark Finland France Germany Iceland Ireland Israel Italy Japan S. Korea Netherlands New Zealand Norway Portugal Spain Sweden Switzerland United Kingdom USA Full sample
25.68 25.36 25.20 19.70 22.88 28.53 24.28 25.29 25.09 22.82 25.49 23.90 32.81 35.06 23.38 22.42 29.40 22.72 24.77 21.81 29.23 18.86 21.34 25.05
1.88 1.98 1.48 5.95 2.39 5.76 1.65 2.91 4.29 3.82 3.82 2.68 2.70 4.49 2.16 2.02 5.84 3.24 2.14 2.34 2.52 1.30 1.65 4.981
24.29 25.78 26.80 14.03 25.15 31.46 24.44 24.87 24.83 25.58 18.53 24.98 34.49 34.48 27.59 22.08 34.83 14.31 36.30 24.40 32.68 18.00 19.57 25.07
0.22 1.34 2.11 3.95 2.98 3.02 1.41 1.33 3.39 8.01 3.61 1.90 2.46 6.64 1.21 2.02 2.90 2.92 1.20 2.00 1.50 1.36 1.32 6.494
Panel B: Emerging countries Bolivia Chile Colombia Costa Rica Dominican Republic Egypt El Salvador Hungary Jordan Malaysia Mexico Morocco Pakistan Paraguay Thailand Tunisia Uruguay Venezuela Full sample
9.54 18.84 12.71 10.06 12.04 7.99 8.05 19.81 16.35 23.74 19.13 13.41 12.82 13.14 30.21 17.61 14.54 17.61 15.42
3.21 4.29 3.52 1.47 3.09 3.16 2.09 3.63 6.32 7.20 3.26 4.24 1.85 3.80 9.19 5.59 4.69 7.81 7.29
8.41 19.44 11.60 4.99 6.52 −1.42 −1.03 19.77 − 15.90 30.56 19.11 6.81 8.46 4.70 30.04 12.70 14.90 23.56 11.28
6.79 4.52 2.38 3.76 2.89 2.60 5.32 4.09 8.39 5.90 3.18 2.60 1.58 7.37 3.88 4.56 2.98 6.64 12.22
Panel C: Developing countries Bahrain Bangladesh Barbados Benin Botswana Cote d'Ivoire Gabon Guatemala Honduras Jamaica Kenya Kuwait Mauritius Papua New Guinea Saudi Arabia Senegal Seychelles Sri Lanka Swaziland Togo
12.90 9.26 5.17 9.59 20.75 6.31 8.42 7.62 14.51 15.03 11.42 14.70 12.51 8.21 11.62 5.52 11.44 14.83 11.74 11.59
6.09 2.50 1.46 2.70 5.96 4.33 2.35 2.48 3.45 3.77 3.88 8.99 2.18 2.30 3.89 1.37 4.43 4.05 3.15 3.71
13.55 2.57 2.61 −2.33 24.88 10.79 23.57 2.42 7.60 7.94 7.81 24.31 9.33 7.73 25.51 −2.12 0.48 5.43 − 10.43 0.02
8.06 2.79 5.88 5.94 4.81 4.38 11.56 4.11 3.70 5.25 4.53 42.78 4.40 7.74 18.18 3.96 7.40 5.06 13.04 6.26
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Table 1 (continued) I/Y
Panel C: Developing countries Trinidad and Tobago Full sample
S/Y
Mean
S.D.
Mean
S.D.
19.18 11.52
6.35 5.74
24.54 8.86
8.32 15.74
Notes: The groupings into developed, emerging, and developing are from the IMF publication “Foreign Direct Investment in Emerging Countries”, September 2003. Note: See notes in Panel A.
(panel-version of the) FH specification (1). Our hypothesis is that the high positive correlation between inward and outward capital flows would bias the FH coefficient upward; that is, by accounting for that correlation, the estimated relationship between investment and savings rates should be lower. That is, we hypothesize that β2 b 0. 4. Describing the data Table 1 provides means and standard deviations on savings and investment rates for the countries in our sample. These data come from the Penn World Table 6.2. These descriptive statistics for developed, emerging, and developing countries are presented in panels A, B, and C respectively. Although these descriptive statistics indicate a wide variation in savings and investment rates within each country grouping, the average investment and savings rates by country tend to be highest in developed countries, lowest in developing, with the rates in the emerging markets falling somewhere in between. Exceptions to this ordering involve the high investment and savings rates seen in the East Asian economies of Malaysia and Thailand. In contrast, there are emerging markets that have average investment and savings that are much lower that those for developing countries, namely Bolivia, Costa Rica, Egypt, and El Salvador. The average savings and investment rates for each country grouping are consistent with the discussion above, as the average is highest for developed countries, lowest for developing countries, with emerging markets in between. Table 1 also provides information on the standard deviation of the savings and investment rates for each country over the sample. In general these variations are lowest for developed countries, highest for developing countries, with the emerging markets in between. The capital flow data that are used here are obtained from the IMF's Balance of Payments database.3 The capital flow data, outward and inward, are the sum of FDI flows, portfolio equity investment and portfolio debt investment. Our analysis focuses on the total flows, outward and inward, and not the sub-components. For an analysis on the determinants of these components, see Alfaro, Kalemli-Ozcan and Volosovych, (2005). Global capital flows are predominantly confined to developed countries, although developing and emerging countries do participate to a limiting degree (Fig. 1). Since the mid-1980s, both capital outflows from developed countries and capital inflows to developed countries have grown significantly. There was a sharp rise in the amount of both capital inflows and outflows over the 1990s, where there were significant dips in the early 1990s and then again around 2001–2002. These graphs indicate that the outward and inward capital flows are highly related (correlated) at this aggregated level. Obstfeld and Taylor (2004) note that since the early 1980s, there have been significant simultaneous inward and outward capital flows for the set of developed countries. They note that countries having the largest stocks of foreign assets also are those having the highest levels of foreign liabilities, pointing out Britain, Canada, Germany, Japan, the Netherlands and the United States as key examples. For these countries there has been a much greater volume of asset swapping for the purpose of mutual diversification, that is risk sharing. Fig. 2 provides correlations between inward and outward capital flows for each country in our sample—panel A for developed economies, panel B for emerging economies, and panel C for developing economies. The average correlation across the developed economies is 0.562, emerging is 0.225, and developing is 0.180. The correlations are large and positive for most developed countries, although there are two countries where the correlations are negative, namely Japan and Israel. For the most part, the correlations for developing countries are lower, and there are many more countries with negative correlations relative to that for developed countries. There are 8 developing countries with negative correlations. The correlations for our sample of emerging markets fall in between those for developed and developing economies. That is, the positive correlations are larger than those reported for developing countries, but for the most part lower than those reported for developed countries. Like the case for developing countries, there are several countries with negative correlations.4 It is important at this point to discuss why inward and outward capital flows would be correlated—that is, why one would expect the existence of both capital inflows and outflows simultaneously. Foreign capital flows can be broken down into three
3 Capital inflow data are from the IMF’s Balance of Payments database. They represent inflows of FDI (IMF label 78bed), portfolio equity investment (78bmd), and portfolio debt investment (78bnd). Capital outflow represent outflow of FDI (78bdd), outward portfolio equity investment (78bkd), and outward portfolio debt investment (78bld). Capital flows are relative to GDP (99b for nominal GDP in local currency; market exchange rate, rf). 4 For each group of countries, there is no pattern in these correlations over time—that is, calculating these correlations over sub samples does not uncover an increasing correlation over time. These sub-period correlations are available upon request.
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Fig. 1. (A) Capital inflows for developed, emerging, and developing countries, 1975–2005; (B) Capital outflow of developed, emerging, and developing countries, 1975–2004.
components: foreign portfolio debt flows, foreign portfolio equity flows, and foreign direct investment (FDI) flows. An economy can experience outward and inward portfolio capital flows simultaneously for portfolio diversification reasons. That is, capital can simultaneously flow into Europe from the US for superior rates of return as well as the desire of US portfolio managers to diversify their portfolios. At the same time, European portfolio managers may forgo superior returns in Europe and invest in the US so as to ensure against unexpected shocks in the home market. As for the simultaneous inflows and outflows of FDI, a motivation can be comparative advantage. For example, there may be outward FDI by European multinationals in some industries and at the same time inflows by foreign multinationals into other industries, each reflecting the home country's comparative advantage. Furthermore, there is also likely to be much bilateral FDI
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Fig. 2. (A) Correlation between inward and outward capital flows in developed countries, 1975–2004; (B) Correlation between inward and outward capital flows in emerging market economies, 1975–2004; (C) Correlation between inward and outward capital flow in developing countries, 1975–2004.
within the same industry. The automotive industry is a classic example of having such a pattern, although there are many others. The available FDI data do indicate that FDI flows for developed countries tend to be intra-industry. The discussion above has shed light on why there may be the simultaneous existence of both outflows and inflows of capital, but not necessarily why these flows would be expected to move together across countries. There are two reasons as to why this may occur. First, to the extent the determinants of capital flows are the same on the inward and the outward side, then as the factors that result in increased outward also drive more inward. Secondly, to the extent the factors that drive capital flows are themselves highly correlated across countries, then an increase in capital flows in any given country may coincide with capital flows from other countries. In any case, the data presented clearly indicate that capital inflows and capital outflows are highly correlated. The next section tests the extent to which these correlations can influence the estimated home bias.
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5. Empirical analysis: Estimating a model of inflows and outflows Before testing our extension to the FH specification, we first replicate the standard FH results. This is done separately for the sample of developed, developing and emerging market economies. The sample period of the analysis is 1975–2004 and all of the specifications we estimate are over this sample period. However, there are three variants in terms of how the data are averaged. First, in the spirit of FH (1980), we estimate a cross section, where the data for each country are averaged over the entire sample period. In that case, there is only one observation per country. Second, we average the data over 5-year periods, resulting in 6 observations for each country, thus yielding a panel. Third, we average the data over 3-year periods, resulting in 10 observations for each country, also yielding a panel. The regressions are done separately for developed countries, developing countries, and emerging market economies. The panels are estimated with fixed effects by country. The first column of results in Table 2 provides regression estimates for a standard FH specification. The home bias (α1) is estimated to be between 0.540 and 0.561 for developed countries, 0.359 and 0.407 for emerging markets, and 0.067 and 0.192 for developing countries. These results are also highly significant, as is noted by the p-values noted in parentheses. There is an interesting pattern that emerges with respect to the relative size of the FH bias. When we use the data set averaged over 3-year periods, the bias is highest for developed countries, lowest for developing countries, and in between for emerging markets. This pattern is also present when we use to the data is averaged over 5-year periods and over the entire sample. The results therefore indicate that the bias is higher for developed countries and lowest for developing countries, with the results for emerging markets falling in between. These results are consistent with previous studies that have also found the home bias lower for developing countries (Dooley et al., 1987; Payne & Kumazawa, 2005; Mamingi, 1994; and Payne & Kumazawa, 2006). Following Coakley et al. (2004), who called for further study of the FH puzzle using both developing and emerging markets, we have now shown that the results for emerging economies tend to fall in between those for developed economies and those for developing economies. This is a new result and has not been documented elsewhere. We next turn to the regression results for our new specification. These regression estimates are given in the second and third column of results of Table 2. The fourth column reports test statistics for heteroskedasticity in the correlation-adjusted regression. In the bottom panel of Table 2, the results are reported for the savings and investment data averaged over the entire sample, and the statistics in the last two columns of that panel are the adjusted R2 statistics and tests for heteroskedasticity for correlationadjusted regression. There now must be some discussion of how the correlations were calculated. When we average over the savings and investment data over the entire sample—the pure cross-sectional regression—the correlation (CORRit) between inward and outward capital flows is measured for each country over the entire sample 1975–2004. In this case, there is one observation per country, including one value for the correlation. In this case, of course, the time subscript t in the regression would be suppressed. When the savings and investment data are averaged over 5-year periods, the correlations between inward and outward capital flows are measured over each 5-year period for each country. In this case therefore, there are six observations per country, and six different correlations, one for each sub period. When the savings and investment data are averaged over 3-year periods, the correlations are measured over each 3-year period for each country. In this case therefore, there are ten observations per country, and ten different correlations, one for each sub period. The estimation is undertaken for each of the country groupings under consideration, namely for developed countries (23 countries), developing countries (21 countries), and emerging markets (18 countries).
Table 2 The standard FH regression [GDIit/GDPit] = α0i + α1[GNSit/GDPit] + ui The correlation adjusted FH regression (I/Y)it = β0i + (β1 + β2 CORRit) (S/Y)it LR test statistic for heteroskedasticity1
α1
β1
β2
0.561 ( b .001) 0.407 ( b .001) 0.067 ( b .001)
0.582 (0.001) 0.347 (0.001) 0.069 (0.001)
−0.016 (0.037) −0.049 (0.081) 0.0014 (0.953)
115.39 (0.001) 81.17 (0.001) 73.37 (0.001)
0.540 (b .001) 0.399 (b .001) 0.080 (0.002)
0.569 (0.001) 0.363 (0.001) 0.084 (0.001)
−0.018 (0.092) −0.067 (0.062) −0.0069 (0.875)
80.42 (0.001) 72.16 (0.001) 50.58 (0.002) Adj. R-squared2
4
3-year averages (GLS estimates) Developed Countries (23 countries; N = 230) Emerging countries (18 countries, N = 180) Developing countries (21 countries, N = 210) 5-year average4 (GLS estimates) Developed countries (23 countries; N = 138) Emerging countries (18 countries; N = 108) Developing countries (21 countries; N = 126) Full sample average Developed countries, OLS (23 countries; N = 23) Emerging countries, GLS (18 countries; N = 18) Developing countries, OLS (21 countries; N = 21)
0.549 (b .001) 0.359 (b .001) 0.192 (b .001)
0.564 (0.001) 0.378 (0.001) 0.198 (0.032)
− 0.163 (0.018) −0.149 (0.495) −0.066 (0.843)
0.750 0.462 0.157
White's hetero test, p-value3 0.248 0.0094 0.750
Notes: N denotes the number of observations. 1. These LR test statistics refer to the correlation-adjusted FH regression. The results are similar for the standard FH regression. Null Hypothesis: no heteroskedasticity. Source:Wooldridge (2002). 2. These Adjusted R-square test statistics refer to the correlation-adjusted regression. The results are similar for the standard FH regression. 3. These White Hetero test statistics refer to the correlation-adjusted FH regression. The results are similar for the standard FH regression. Null hypothesis of no heteroskedasticity. Source: White (1980). 4. The regressions are undertaken using data averaged over 3-year periods, 5-year periods, and averaged over the entire sample. Regression results using the data averaged over 3 and 5-year sample periods include unreported country fixed effects.
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The regression results are reported in Table 2. For developed countries, the results indicate that the higher the correlation between outward and inward capital flows, the lower the home bias. This result is highly significant when the data are averaged over 3-year periods and over the entire 30-year period, and significant at the 10% level when the data are averaged over 5-year periods. For developing countries, the results indicate that the FH bias is unrelated to the correlation between inward and outward capital flows regardless of the empirical model used. The results for emerging economies indicate that at the 10% level, the home bias is negatively related to the correlation between inward and outward capital flows when the data are averaged over 3 and 5year periods, but no statistical relation is found when the data are averaged over the entire 30-year period. An extensive analysis was undertaken to measure whether the results are sensitive to the assumptions made on calculating the correlations. That is, rather than measure correlations over the 3 and 5-year periods when the data are averaged of 3 and 5 years respectively, we re-estimated those specifications using the correlation estimated over the entire 30-year period, and then again using the correlation estimated over 10-year sub-periods and using these correlations in the regressions. The results presented in the paper are robust to these alternative possibilities.5 The analysis presented here therefore supports our hypothesis that the presence of positively correlated inward and outward capital flows can result in an upward bias in the estimate of FH bias. In other words, accounting for the positive correlation between inward and outward capital flows reduces the estimated home-bias coefficient. This evidence is found to hold when using a sample of developed and emerging economies, but not for developing economies. 6. Conclusions and policy implications The FH result implying a low level of international capital mobility has perplexed economists since the seminal paper by Feldstein and Horioka in 1980. These results are in sharp contrast to the widely held view among policy makers and those in the private sector, as well as many academics, that there does indeed exists significant global integration of financial markets. After all, the financial crises in Latin America, East Asia, and elsewhere were driven (in large part) by foreign investors who moved capital to countries with highly productive investment opportunities in the case of FDI and high relative returns for portfolio investors, risk adjusted of course. Herding behavior has on several occasions resulted in an abrupt removal of large amounts of investments, thus reflecting the high level of international capital mobility. Furthermore, in the case of the U.S. and Europe and many other countries and regions, large parts of their government and private debt are held by foreign investors. There are also significant amounts of FDI among developed countries. That is, there is significant evidence of high levels of capital mobility across countries. The standard Feldstein–Horioka analysis indicates a large home bias in where savings are invested. We have argued that it is possible for there to appear to be a large home bias in a situation where there exist large movements of capital coupled with a high correlation between outward and inward flows. Taking this into account, we find that the home bias is much lower than that estimated in the standard framework. As such, our analysis makes more likely the possibility that international capital mobility is indeed much higher than what the FH (1980) empirical results suggested. Although our analysis does make an adjustment for capital inflows and outflows, more work needs to be done to understand why inward and outward capital flows are so highly correlated, and also why these correlations vary widely across countries. To do so, models that explain the movements of portfolio and direct investments, both into and out of countries, would need to be considered. In doing so, the correlations between outward and inward flows could then be attributed to FDI flows and portfolio flows, and hence shed light on why the correlations vary by country. We leave that for future research. Acknowledgements We would like to thank the referees at the International Review of Finance and Economics for helpful comment. We would also like to thank the Committee on Research at Atkinson, York University, for the financial support towards this project. References Alfaro, L., Kalemli-Ozcan, S., & Volosovych, V. (2005). Capital flows in a globalized world: The role of policies and institutions, Working paper 11696. Cambridge, Massachusetts National Bureau of Economic Research. Baxter, M., & Crucini, M. (1993). Explaining saving/investment correlations. The American Economic Review, V83(3), 416−436 June. Coakley, Jerry, Fuertes, Ana-Maria, & Spagnolo, Fabio (2004). Is the Feldstein–Horioka puzzle history? The Manchester School, 72(5), 569−590. Coakley, Jerry, Kulasi, Farida, & Smith, Ron (1998). The Feldstein–Horioka puzzle and capital mobility: A review. International Journal of Finance and Economics, V3, 169−188. Dooley, M., Frankel, J., & Mathieson, D. J. (1987). International capital mobility: What do saving–investment correlations tell us?IMF Staff Papers, 34(3), 503−531 September. Feldstein, M., & Bacchetta, P. (1989). National saving and international investment, National Bureau of Economic Research Working Paper: 3164, November. Feldstein, M., & Horioka, C. (1980). Domestic savings and international capital flows. Economic Journal, 90, 314−329. Frankel, J. (1991). Quantifying international capital mobility in the 1980s. National saving and economic performance (pp. 227−260). Georgopoulos, George, & Hejazi, Walid (2005). Feldstein–Horioka meets a time trend. Economics Letters, 86, 353−357. Kraay, A., & Ventura, J. (2000). Current accounts in debtor and creditor countries. Quarterly Journal of Economics, XCV (2000), 1137−1166. Mamingi, N. (1994). Savings–investment correlations and capital mobility in developing countries, The World Bank Policy Research Working Paper Number 1211.
5
These results are available upon request.
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Mussa, M., & Goldstein, M. (1993). The integration of international capital markets. International Monetary Fund Working Paper: WP/93/95, December 1993, 37. Obstfeld, M. (1986). How integrated are world capital markets? Some new tests. National Bureau of Economic Research Working Paper: 2075, November. Obstfeld, M., & Taylor, A. M. (2004). Global capital markets: Integration, crisis, and growth. Cambridge University Press. Payne, J., & Kumazawa, R. (2005). Capital mobility, foreign aid, and openness: Further panel data evidence from sub-Saharan Africa. Journal of Economics and Finance, 29(1), 123−127. Payne, J., & Kumazawa, R. (2006). Capital mobility and the Feldstein–Horioka puzzle: Re-examination of less developed countries. The Manchestor School, vol. 74, No.5. (pp. 610−616). Tesar, L. (1991). Saving, investment and international capital flows. Journal of International Economics, XXXI, 55−78. Ventura, J. (2003). Towards a theory of current accounts. The World Economy, 26(4), 483−512 April 2003, (30). Westphal, U. (1983). Domestic saving and international capital movements in the long run and the short run by M. Feldstein: Comment. European Economic Review, 21(1–2), 157−159 March-April. White, H. (1980). A heteroskedasticity-consistent covariance matrix estimator and a direct test for heteroskedasticity. Econometrica, 48, 817−838. Wooldridge, J. (2002). Econometric analysis of cross section and panel data. MIT Press.
Contents lists available at ScienceDirect
International Review of Economics and Finance j o u r n a l h o m e p a g e : w w w. e l s ev i e r. c o m / l o c a t e / i r e f
The Feldstein–Horioka puzzle revisited: Is the home-bias much less? George Georgopoulos a,⁎, Walid Hejazi b a b
Economics, York University, Toronto, Canada Rotman School of Management, University of Toronto, Toronto, Canada
a r t i c l e
i n f o
Article history: Received 11 April 2006 Received in revised form 24 April 2007 Accepted 28 August 2007 Available online 20 March 2008 JEL Classification: C23 F30
a b s t r a c t The large correlation between domestic savings and investment is well documented and is known as the Feldstein–Horioka puzzle. We demonstrate that estimates of the FH coefficients using the standard framework are biased upward in the presence of highly positively correlated inward and outward capital flows. Using data for the 14 OECD countries, the analysis shows that the significant home bias documented by FH and others is also consistent with much higher levels of capital mobility when capital outflows and inflows are highly positively correlated. Taking account for these correlations reduces the estimated home bias somewhere between 45% and 90%. © 2008 Published by Elsevier Inc.
Keywords: Feldstein–Horioka puzzle Capital flows
1. Introduction In their seminal contribution, Feldstein and Horioka (1980, henceforth FH) document a significant home-bias in terms of where domestic savings are invested. In regressing the ratio of investment to GDP on the ratio of savings to GDP for 16 OECD countries over the averaged period of 1960 to 1974, FH (1980) find the estimated savings retention coefficient (the fraction of a dollar of increased savings that is invested domestically) to be between 0.8 and 0.9. This result has been interpreted as indicating a low level of international capital mobility, and has been labeled as the Feldstein–Horioka puzzle. This finding has been replicated by several authors, including, Dooley, Frankel and Mathieson (1987), Feldstein and Bacchetta (1989), Frankel (1991), Tesar (1991), and Mussa and Goldstein (1993). There are several published studies that challenge the FH results. The challenges are based on, for example, the presence of productivity shocks which cause both savings and investment rates to rise simultaneously, thus giving the appearance of a home bias (Obstfeld, 1986; Westphal, 1983). Others look at large country influences on world interest rates (Baxter & Crucini, 1993; Dooley et al., 1987). Kraay and Ventura (2000) suggest a high FH coefficient reflects a low proportion of foreign to total assets held by agents due to the presence of high investment risk and weak diminishing returns. Ventura (2003) attributes the high correlation between savings and investment to investment risk and adjustment costs to investment. Despite these extensions, the empirical evidence, for the most part, still implies a significant home bias in terms of where domestic savings are invested. This current paper represents another attempt to shed light on this very important question, but takes a different approach. The current paper extends the analysis of the FH puzzle to incorporate the possibility that the presence of highly correlated outward and inward capital flows may also be a contributing factor to the empirical home bias result. To illustrate, consider the following example. Suppose a country has a $100 increase in domestic savings. These domestic savings can be invested domestically or abroad. The FH result implies that much of these domestic savings are invested locally. But
⁎ Corresponding author. Economics, Atkinson Faculty of Liberal and Professional Studies, 4700 Keele Street, Toronto, Canada, M3J 1P3. Tel.: +1 416 736 2100x30108; fax: +1 416 736 5188. E-mail address: [email protected] (G. Georgopoulos). 1059-0560/$ – see front matter © 2008 Published by Elsevier Inc. doi:10.1016/j.iref.2007.08.004
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to get a clearer picture of the home bias, consideration must be given to capital flows, both inward and outward. It may be the case that the entire $100 increase in savings is invested domestically. Alternatively, it may be the case that $30 of increased domestic savings are invested abroad, and at the same time $30 of foreign savings flow into the domestic country. If such patterns were common, indicating inward and outward capital flows are highly correlated, then the coefficient in the FH regression would equal one, but of course the amount of international capital mobility is very different. This paper estimates the FH coefficients for a sample of 23 developed, 18 emerging, and 21 developing countries over the 1975 to 2004 period. Similar to previous studies, significant home biases are documented. Using the standard FH approach, the home bias is found to be highest for developed countries, lowest for developing, with emerging economies falling in between. The analysis is then extended to allow the home bias coefficient to depend directly on the correlation between inward and outward capital flows, something that has not been done before. The results indicate that accounting for these correlations yields lower home bias estimates for the sample of developed and emerging economies, but not for developing economies. The empirical evidence reported below is therefore consistent with the hypothesis that there can be high levels of capital mobility, yet in the presence of highly correlated capital inflows and outflows, the standard FH regression would not capture this. Furthermore, the standard FH analysis would find a low level of capital mobility. An important contribution of this paper therefore is that it explores whether the Feldstein–Horioka puzzle is present in an environment of large two-way international capital flows, and hence contributes to the recent international finance literature on contemporary financial globalization. This literature brings to attention the fact that for industrialized economies external assets and liabilities increased simultaneously since post-World War II, and significantly so beginning in the 1980s, a result discussed in Obstfeld and Taylor (2004). They argue that these patterns are evidence of risk diversification. The current paper is conceptually related to the work of Kraay and Ventura (2000) and Ventura (2003) who show that the saving-investor correlation is a decreasing function of the extent of national wealth diversification. The format of this paper is as follows. Section 2 provides a brief review of the relevant literature. Section 3 reconsiders tests of the FH hypothesis by explicitly accounting for correlations between inward and outward capital flows. Section 4 describes the capital flow data, including correlations between inward and outward capital flows. Section 5 provides empirical results. Conclusions and policy implications are provided in Section 6. 2. Literature review Although the volume of work on the FH puzzle is substantial, this literature review will focus only on those papers most closely related to the analysis in the current paper. For more extensive literature reviews, see Tesar (1991) and Coakley, Kulasi and Smith (1998). Studies that challenge the FH puzzle suggest this outcome is due to the simultaneous movement in trade deficits, government revenue, and domestic investment (Westphal, 1983), and large country influences on world interest rates (Baxter & Crucini, 1993; Dooley et al., 1987). Not explicitly accounting for these factors gives rise to a positive correlation between domestic investment and domestic savings even in an environment of significant global capital flows. Ventura (2003) and Kraay and Ventura (2000) take another approach, regressing the current account on savings using data from 21 industrial countries over the period 1966–1997, taking into account growth in both productivity and population, two common sources of variation in savings and investment as predicted by Franco Modigliani's life-cycle theory of savings. They find the coefficient on savings to be 0.240, significantly smaller than the value of one which is predicted by the traditional intertemporal theory of the current account. In the context of the Feldstein–Horioka model, this implies a 1% increase in savings leads to a 0.76% rise in investment, suggesting a large home bias. The authors extend the traditional model and provide an alternative theory on why savings and investment would be correlated. They suggest investors in a particular country invest their marginal unit of wealth in a manner similar to the average unit of wealth. This behaviour is more prevalent in the context of high investment risk and weak diminishing returns, as opposed to low investment risk and strong diminishing returns characteristic of the traditional intertemporal model. In the former case a rise in income would lead to a proportional increase in all assets currently held, domestic and foreign. The strong desire for diversification would make investors reluctant to rebalance their portfolios towards any given asset; the size of the portfolio would increase, but not its composition. This is in contrast to the traditional view that predicts that most if not all of the increase in savings should be invested abroad. Kraay and Ventura (2000)'s alternative model relates the FH savings retention coefficient to the proportion of a country's foreign assets to total assets. Specifically, the lower the ratio of foreign assets to total assets, the higher is the savings retention coefficient. This model is therefore related to the issue of national wealth diversification. Kraay and Ventura (2000) use data from 13 industrial countries over the period 1973–1995, and regress the current account on the savings rate interacted with the share of foreign assets to total assets. They find an estimated slope coefficient of 0.95. Their results indicate therefore that the lower the ratio of foreign assets to total assets, the higher is the savings retention coefficient. Ventura (2003) incorporates investment risk and adjustment costs of switching from domestic to foreign assets. He finds that the higher the adjustment costs, the lower the proportion of foreign to total assets held, yielding a high investment-savings correlation. The results of the academic literature discussed above are therefore in contrast to the widely held perception of highly integrated global capital markets that see capital flow to countries that provide investors with the highest risk adjusted rates of return. These high levels of capital mobility certainly played significant roles in the recent Argentine and East Asian financial crises. It therefore remains an open question—to what extent is there global capital market integration? Do the low levels of international capital mobility implied by the FH results truly reflect the reality, or is the academic literature missing something important?
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There are two recent studies which establish more capital mobility than the above studies indicate. The first, Georgopoulos and Hejazi (2005), argue that in the presence of relatively high transactions costs associated with investing abroad, a home bias should be expected. They argue that the relevant question is not whether a bias exists, but rather whether the biases are consistent with individual optimizing behaviour.1 That question is not answered. Nevertheless, innovations in financial markets and information technology have resulted in a fall in such transactions costs, and this should lead to a rise in capital mobility, and as a result a fall in the home bias. The empirical evidence presented confirms the intuition that the bias has fallen over the past three decades. The second paper goes further towards explaining the bias. Coakley, Fuertes and Spagnolo (2004) use sophisticated econometric techniques to ensure that a country's intertemporal budget constraint is satisfied, which means that the current account must be stationary. Put differently, this constraint implies that a country's savings and investment rates must cointegrate. Using a mean group regression approach that is robust to persistent innovations and accounts for country heterogeneity and crosssectional dependence, the study finds no evidence of the Feldstein–Horioka puzzle. That is, their evidence is supportive of highly mobile capital across their sample of 12 OECD countries over the period 1980 to 2000. This is the first study to fully account for the FH bias, and hence is an important contribution to this literature. While most of the existing literature has focused on developed countries, there are some studies that consider developing economies. For example, Dooley et al. (1987) find a lower savings coefficient for developing countries relative to OECD countries. They attribute this result to the “country size” factor, where these relatively small developing countries take the world interest rate as given, and as such not yielding an upward bias on the savings–investment correlation typically found in larger countries. Other factors contributing to relatively lower savings coefficients are the existence of foreign aid for these countries (Dooley et al., 1987; Payne & Kumazawa, 2005) and greater capital flow controls (Payne & Kumazawa, 2006). Mamingi (1994) and Payne and Kumazawa (2006) also find a relatively lower savings coefficient on developing countries. Payne and Kumazawa (2006) test the FH puzzle using a sample of 47 developing countries over the period 1980–2003 and find a smaller FH coefficient than for OECD countries. Coakley et al. (2004) call for further study of the FH puzzle using both developing and emerging markets. The analysis undertaken below therefore contributes to the existing literature in two distinct ways. First, the framework for testing for a home bias is extended to allow the FH coefficient to depend directly on the correlation between inward and outward capital flows. Secondly, we estimate the FH regressions using three separate samples: developed economies, developing economies, and emerging economies, and hence work to fill the void noted by Coakley et al. (2004). 3. Reconsidering the FH puzzle: Accounting for capital flow correlations Using a sample of OECD countries over the period 1960 to 1974, Feldstein and Horioka (1980) estimate the following regression: GDIi =GDPi ¼ a0 þ a1 ½GNSi =GDPi þ ui
ð1Þ
where GDI measures gross domestic investment, GNS gross national savings, GDP gross domestic product, and i indexes country. The data for each country were averaged over the 1960 to 1974 sample period, and hence there is one observation per country— that is, the regression is cross sectional. The estimate of α1 captures the FH bias—that is, the bias in terms of where increases in domestic savings are invested. In a world of perfect capital mobility, the savings retention coefficient should be zero: the change in domestic investment would not depend on the change in savings generated in that country because savings would flow to the location with the most productive investment opportunities. In sharp contrast to this scenario, the FH analysis finds a strong bias to invest increases in savings in the home country. For OECD countries, the estimated savings retention coefficient (the fraction of a dollar of increased savings that is invested domestically) is estimated to be between 0.8 and 0.9. The Feldstein–Horioka results have been replicated by several authors, including Frankel (1991) and Mussa and Goldstein (1993). We argue that a positive correlation between inward and outward capital flows will result in an upward bias in the savings retention coefficient. That is, the estimated value of α1 in Eq. (1) above will over-estimate the true home bias. To address this, we extend the standard FH specification to explicitly account for these correlations. Define CORRit as the correlation between inward and outward capital flows for country i. The t subscript indicates that this correlation will be allowed to vary over the sample in a way that is discussed below. The following specification is therefore proposed:2 ðI=Y Þit ¼ b0i þ ðb1 þ b2 CORRit ÞðS=Y Þit þeit
ð2Þ
There is both a subscript for country i and period t as the model will be estimated in a panel where we average observations over time periods, as well as in a cross-section when we average observations over the entire sample, in which case the t subscript would be suppressed and β0i would become β0. This specification links the FH coefficient directly to correlations between inward and outward capital flows. If the relationship between investment and savings rates were unrelated to the correlation between inward and outward flows, then the estimated value of β2 would equal zero, and specification (2) would collapse to a standard 1 To the extent the “home bias” can be explained by a formal model that accounts for such transactionscosts, then they should not be considered as biases. See Georgopoulos and Hejazi (2005) for a discussion of this issue. 2 We thank an anonymous referee for suggesting this specification.
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Table 1 Developed countries I/Y
S/Y
Mean
S.D.
Mean
S.D.
Panel A: Developed countries Australia Austria Canada Cyprus Denmark Finland France Germany Iceland Ireland Israel Italy Japan S. Korea Netherlands New Zealand Norway Portugal Spain Sweden Switzerland United Kingdom USA Full sample
25.68 25.36 25.20 19.70 22.88 28.53 24.28 25.29 25.09 22.82 25.49 23.90 32.81 35.06 23.38 22.42 29.40 22.72 24.77 21.81 29.23 18.86 21.34 25.05
1.88 1.98 1.48 5.95 2.39 5.76 1.65 2.91 4.29 3.82 3.82 2.68 2.70 4.49 2.16 2.02 5.84 3.24 2.14 2.34 2.52 1.30 1.65 4.981
24.29 25.78 26.80 14.03 25.15 31.46 24.44 24.87 24.83 25.58 18.53 24.98 34.49 34.48 27.59 22.08 34.83 14.31 36.30 24.40 32.68 18.00 19.57 25.07
0.22 1.34 2.11 3.95 2.98 3.02 1.41 1.33 3.39 8.01 3.61 1.90 2.46 6.64 1.21 2.02 2.90 2.92 1.20 2.00 1.50 1.36 1.32 6.494
Panel B: Emerging countries Bolivia Chile Colombia Costa Rica Dominican Republic Egypt El Salvador Hungary Jordan Malaysia Mexico Morocco Pakistan Paraguay Thailand Tunisia Uruguay Venezuela Full sample
9.54 18.84 12.71 10.06 12.04 7.99 8.05 19.81 16.35 23.74 19.13 13.41 12.82 13.14 30.21 17.61 14.54 17.61 15.42
3.21 4.29 3.52 1.47 3.09 3.16 2.09 3.63 6.32 7.20 3.26 4.24 1.85 3.80 9.19 5.59 4.69 7.81 7.29
8.41 19.44 11.60 4.99 6.52 −1.42 −1.03 19.77 − 15.90 30.56 19.11 6.81 8.46 4.70 30.04 12.70 14.90 23.56 11.28
6.79 4.52 2.38 3.76 2.89 2.60 5.32 4.09 8.39 5.90 3.18 2.60 1.58 7.37 3.88 4.56 2.98 6.64 12.22
Panel C: Developing countries Bahrain Bangladesh Barbados Benin Botswana Cote d'Ivoire Gabon Guatemala Honduras Jamaica Kenya Kuwait Mauritius Papua New Guinea Saudi Arabia Senegal Seychelles Sri Lanka Swaziland Togo
12.90 9.26 5.17 9.59 20.75 6.31 8.42 7.62 14.51 15.03 11.42 14.70 12.51 8.21 11.62 5.52 11.44 14.83 11.74 11.59
6.09 2.50 1.46 2.70 5.96 4.33 2.35 2.48 3.45 3.77 3.88 8.99 2.18 2.30 3.89 1.37 4.43 4.05 3.15 3.71
13.55 2.57 2.61 −2.33 24.88 10.79 23.57 2.42 7.60 7.94 7.81 24.31 9.33 7.73 25.51 −2.12 0.48 5.43 − 10.43 0.02
8.06 2.79 5.88 5.94 4.81 4.38 11.56 4.11 3.70 5.25 4.53 42.78 4.40 7.74 18.18 3.96 7.40 5.06 13.04 6.26
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Table 1 (continued) I/Y
Panel C: Developing countries Trinidad and Tobago Full sample
S/Y
Mean
S.D.
Mean
S.D.
19.18 11.52
6.35 5.74
24.54 8.86
8.32 15.74
Notes: The groupings into developed, emerging, and developing are from the IMF publication “Foreign Direct Investment in Emerging Countries”, September 2003. Note: See notes in Panel A.
(panel-version of the) FH specification (1). Our hypothesis is that the high positive correlation between inward and outward capital flows would bias the FH coefficient upward; that is, by accounting for that correlation, the estimated relationship between investment and savings rates should be lower. That is, we hypothesize that β2 b 0. 4. Describing the data Table 1 provides means and standard deviations on savings and investment rates for the countries in our sample. These data come from the Penn World Table 6.2. These descriptive statistics for developed, emerging, and developing countries are presented in panels A, B, and C respectively. Although these descriptive statistics indicate a wide variation in savings and investment rates within each country grouping, the average investment and savings rates by country tend to be highest in developed countries, lowest in developing, with the rates in the emerging markets falling somewhere in between. Exceptions to this ordering involve the high investment and savings rates seen in the East Asian economies of Malaysia and Thailand. In contrast, there are emerging markets that have average investment and savings that are much lower that those for developing countries, namely Bolivia, Costa Rica, Egypt, and El Salvador. The average savings and investment rates for each country grouping are consistent with the discussion above, as the average is highest for developed countries, lowest for developing countries, with emerging markets in between. Table 1 also provides information on the standard deviation of the savings and investment rates for each country over the sample. In general these variations are lowest for developed countries, highest for developing countries, with the emerging markets in between. The capital flow data that are used here are obtained from the IMF's Balance of Payments database.3 The capital flow data, outward and inward, are the sum of FDI flows, portfolio equity investment and portfolio debt investment. Our analysis focuses on the total flows, outward and inward, and not the sub-components. For an analysis on the determinants of these components, see Alfaro, Kalemli-Ozcan and Volosovych, (2005). Global capital flows are predominantly confined to developed countries, although developing and emerging countries do participate to a limiting degree (Fig. 1). Since the mid-1980s, both capital outflows from developed countries and capital inflows to developed countries have grown significantly. There was a sharp rise in the amount of both capital inflows and outflows over the 1990s, where there were significant dips in the early 1990s and then again around 2001–2002. These graphs indicate that the outward and inward capital flows are highly related (correlated) at this aggregated level. Obstfeld and Taylor (2004) note that since the early 1980s, there have been significant simultaneous inward and outward capital flows for the set of developed countries. They note that countries having the largest stocks of foreign assets also are those having the highest levels of foreign liabilities, pointing out Britain, Canada, Germany, Japan, the Netherlands and the United States as key examples. For these countries there has been a much greater volume of asset swapping for the purpose of mutual diversification, that is risk sharing. Fig. 2 provides correlations between inward and outward capital flows for each country in our sample—panel A for developed economies, panel B for emerging economies, and panel C for developing economies. The average correlation across the developed economies is 0.562, emerging is 0.225, and developing is 0.180. The correlations are large and positive for most developed countries, although there are two countries where the correlations are negative, namely Japan and Israel. For the most part, the correlations for developing countries are lower, and there are many more countries with negative correlations relative to that for developed countries. There are 8 developing countries with negative correlations. The correlations for our sample of emerging markets fall in between those for developed and developing economies. That is, the positive correlations are larger than those reported for developing countries, but for the most part lower than those reported for developed countries. Like the case for developing countries, there are several countries with negative correlations.4 It is important at this point to discuss why inward and outward capital flows would be correlated—that is, why one would expect the existence of both capital inflows and outflows simultaneously. Foreign capital flows can be broken down into three
3 Capital inflow data are from the IMF’s Balance of Payments database. They represent inflows of FDI (IMF label 78bed), portfolio equity investment (78bmd), and portfolio debt investment (78bnd). Capital outflow represent outflow of FDI (78bdd), outward portfolio equity investment (78bkd), and outward portfolio debt investment (78bld). Capital flows are relative to GDP (99b for nominal GDP in local currency; market exchange rate, rf). 4 For each group of countries, there is no pattern in these correlations over time—that is, calculating these correlations over sub samples does not uncover an increasing correlation over time. These sub-period correlations are available upon request.
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Fig. 1. (A) Capital inflows for developed, emerging, and developing countries, 1975–2005; (B) Capital outflow of developed, emerging, and developing countries, 1975–2004.
components: foreign portfolio debt flows, foreign portfolio equity flows, and foreign direct investment (FDI) flows. An economy can experience outward and inward portfolio capital flows simultaneously for portfolio diversification reasons. That is, capital can simultaneously flow into Europe from the US for superior rates of return as well as the desire of US portfolio managers to diversify their portfolios. At the same time, European portfolio managers may forgo superior returns in Europe and invest in the US so as to ensure against unexpected shocks in the home market. As for the simultaneous inflows and outflows of FDI, a motivation can be comparative advantage. For example, there may be outward FDI by European multinationals in some industries and at the same time inflows by foreign multinationals into other industries, each reflecting the home country's comparative advantage. Furthermore, there is also likely to be much bilateral FDI
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Fig. 2. (A) Correlation between inward and outward capital flows in developed countries, 1975–2004; (B) Correlation between inward and outward capital flows in emerging market economies, 1975–2004; (C) Correlation between inward and outward capital flow in developing countries, 1975–2004.
within the same industry. The automotive industry is a classic example of having such a pattern, although there are many others. The available FDI data do indicate that FDI flows for developed countries tend to be intra-industry. The discussion above has shed light on why there may be the simultaneous existence of both outflows and inflows of capital, but not necessarily why these flows would be expected to move together across countries. There are two reasons as to why this may occur. First, to the extent the determinants of capital flows are the same on the inward and the outward side, then as the factors that result in increased outward also drive more inward. Secondly, to the extent the factors that drive capital flows are themselves highly correlated across countries, then an increase in capital flows in any given country may coincide with capital flows from other countries. In any case, the data presented clearly indicate that capital inflows and capital outflows are highly correlated. The next section tests the extent to which these correlations can influence the estimated home bias.
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5. Empirical analysis: Estimating a model of inflows and outflows Before testing our extension to the FH specification, we first replicate the standard FH results. This is done separately for the sample of developed, developing and emerging market economies. The sample period of the analysis is 1975–2004 and all of the specifications we estimate are over this sample period. However, there are three variants in terms of how the data are averaged. First, in the spirit of FH (1980), we estimate a cross section, where the data for each country are averaged over the entire sample period. In that case, there is only one observation per country. Second, we average the data over 5-year periods, resulting in 6 observations for each country, thus yielding a panel. Third, we average the data over 3-year periods, resulting in 10 observations for each country, also yielding a panel. The regressions are done separately for developed countries, developing countries, and emerging market economies. The panels are estimated with fixed effects by country. The first column of results in Table 2 provides regression estimates for a standard FH specification. The home bias (α1) is estimated to be between 0.540 and 0.561 for developed countries, 0.359 and 0.407 for emerging markets, and 0.067 and 0.192 for developing countries. These results are also highly significant, as is noted by the p-values noted in parentheses. There is an interesting pattern that emerges with respect to the relative size of the FH bias. When we use the data set averaged over 3-year periods, the bias is highest for developed countries, lowest for developing countries, and in between for emerging markets. This pattern is also present when we use to the data is averaged over 5-year periods and over the entire sample. The results therefore indicate that the bias is higher for developed countries and lowest for developing countries, with the results for emerging markets falling in between. These results are consistent with previous studies that have also found the home bias lower for developing countries (Dooley et al., 1987; Payne & Kumazawa, 2005; Mamingi, 1994; and Payne & Kumazawa, 2006). Following Coakley et al. (2004), who called for further study of the FH puzzle using both developing and emerging markets, we have now shown that the results for emerging economies tend to fall in between those for developed economies and those for developing economies. This is a new result and has not been documented elsewhere. We next turn to the regression results for our new specification. These regression estimates are given in the second and third column of results of Table 2. The fourth column reports test statistics for heteroskedasticity in the correlation-adjusted regression. In the bottom panel of Table 2, the results are reported for the savings and investment data averaged over the entire sample, and the statistics in the last two columns of that panel are the adjusted R2 statistics and tests for heteroskedasticity for correlationadjusted regression. There now must be some discussion of how the correlations were calculated. When we average over the savings and investment data over the entire sample—the pure cross-sectional regression—the correlation (CORRit) between inward and outward capital flows is measured for each country over the entire sample 1975–2004. In this case, there is one observation per country, including one value for the correlation. In this case, of course, the time subscript t in the regression would be suppressed. When the savings and investment data are averaged over 5-year periods, the correlations between inward and outward capital flows are measured over each 5-year period for each country. In this case therefore, there are six observations per country, and six different correlations, one for each sub period. When the savings and investment data are averaged over 3-year periods, the correlations are measured over each 3-year period for each country. In this case therefore, there are ten observations per country, and ten different correlations, one for each sub period. The estimation is undertaken for each of the country groupings under consideration, namely for developed countries (23 countries), developing countries (21 countries), and emerging markets (18 countries).
Table 2 The standard FH regression [GDIit/GDPit] = α0i + α1[GNSit/GDPit] + ui The correlation adjusted FH regression (I/Y)it = β0i + (β1 + β2 CORRit) (S/Y)it LR test statistic for heteroskedasticity1
α1
β1
β2
0.561 ( b .001) 0.407 ( b .001) 0.067 ( b .001)
0.582 (0.001) 0.347 (0.001) 0.069 (0.001)
−0.016 (0.037) −0.049 (0.081) 0.0014 (0.953)
115.39 (0.001) 81.17 (0.001) 73.37 (0.001)
0.540 (b .001) 0.399 (b .001) 0.080 (0.002)
0.569 (0.001) 0.363 (0.001) 0.084 (0.001)
−0.018 (0.092) −0.067 (0.062) −0.0069 (0.875)
80.42 (0.001) 72.16 (0.001) 50.58 (0.002) Adj. R-squared2
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3-year averages (GLS estimates) Developed Countries (23 countries; N = 230) Emerging countries (18 countries, N = 180) Developing countries (21 countries, N = 210) 5-year average4 (GLS estimates) Developed countries (23 countries; N = 138) Emerging countries (18 countries; N = 108) Developing countries (21 countries; N = 126) Full sample average Developed countries, OLS (23 countries; N = 23) Emerging countries, GLS (18 countries; N = 18) Developing countries, OLS (21 countries; N = 21)
0.549 (b .001) 0.359 (b .001) 0.192 (b .001)
0.564 (0.001) 0.378 (0.001) 0.198 (0.032)
− 0.163 (0.018) −0.149 (0.495) −0.066 (0.843)
0.750 0.462 0.157
White's hetero test, p-value3 0.248 0.0094 0.750
Notes: N denotes the number of observations. 1. These LR test statistics refer to the correlation-adjusted FH regression. The results are similar for the standard FH regression. Null Hypothesis: no heteroskedasticity. Source:Wooldridge (2002). 2. These Adjusted R-square test statistics refer to the correlation-adjusted regression. The results are similar for the standard FH regression. 3. These White Hetero test statistics refer to the correlation-adjusted FH regression. The results are similar for the standard FH regression. Null hypothesis of no heteroskedasticity. Source: White (1980). 4. The regressions are undertaken using data averaged over 3-year periods, 5-year periods, and averaged over the entire sample. Regression results using the data averaged over 3 and 5-year sample periods include unreported country fixed effects.
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The regression results are reported in Table 2. For developed countries, the results indicate that the higher the correlation between outward and inward capital flows, the lower the home bias. This result is highly significant when the data are averaged over 3-year periods and over the entire 30-year period, and significant at the 10% level when the data are averaged over 5-year periods. For developing countries, the results indicate that the FH bias is unrelated to the correlation between inward and outward capital flows regardless of the empirical model used. The results for emerging economies indicate that at the 10% level, the home bias is negatively related to the correlation between inward and outward capital flows when the data are averaged over 3 and 5year periods, but no statistical relation is found when the data are averaged over the entire 30-year period. An extensive analysis was undertaken to measure whether the results are sensitive to the assumptions made on calculating the correlations. That is, rather than measure correlations over the 3 and 5-year periods when the data are averaged of 3 and 5 years respectively, we re-estimated those specifications using the correlation estimated over the entire 30-year period, and then again using the correlation estimated over 10-year sub-periods and using these correlations in the regressions. The results presented in the paper are robust to these alternative possibilities.5 The analysis presented here therefore supports our hypothesis that the presence of positively correlated inward and outward capital flows can result in an upward bias in the estimate of FH bias. In other words, accounting for the positive correlation between inward and outward capital flows reduces the estimated home-bias coefficient. This evidence is found to hold when using a sample of developed and emerging economies, but not for developing economies. 6. Conclusions and policy implications The FH result implying a low level of international capital mobility has perplexed economists since the seminal paper by Feldstein and Horioka in 1980. These results are in sharp contrast to the widely held view among policy makers and those in the private sector, as well as many academics, that there does indeed exists significant global integration of financial markets. After all, the financial crises in Latin America, East Asia, and elsewhere were driven (in large part) by foreign investors who moved capital to countries with highly productive investment opportunities in the case of FDI and high relative returns for portfolio investors, risk adjusted of course. Herding behavior has on several occasions resulted in an abrupt removal of large amounts of investments, thus reflecting the high level of international capital mobility. Furthermore, in the case of the U.S. and Europe and many other countries and regions, large parts of their government and private debt are held by foreign investors. There are also significant amounts of FDI among developed countries. That is, there is significant evidence of high levels of capital mobility across countries. The standard Feldstein–Horioka analysis indicates a large home bias in where savings are invested. We have argued that it is possible for there to appear to be a large home bias in a situation where there exist large movements of capital coupled with a high correlation between outward and inward flows. Taking this into account, we find that the home bias is much lower than that estimated in the standard framework. As such, our analysis makes more likely the possibility that international capital mobility is indeed much higher than what the FH (1980) empirical results suggested. Although our analysis does make an adjustment for capital inflows and outflows, more work needs to be done to understand why inward and outward capital flows are so highly correlated, and also why these correlations vary widely across countries. To do so, models that explain the movements of portfolio and direct investments, both into and out of countries, would need to be considered. In doing so, the correlations between outward and inward flows could then be attributed to FDI flows and portfolio flows, and hence shed light on why the correlations vary by country. We leave that for future research. Acknowledgements We would like to thank the referees at the International Review of Finance and Economics for helpful comment. We would also like to thank the Committee on Research at Atkinson, York University, for the financial support towards this project. References Alfaro, L., Kalemli-Ozcan, S., & Volosovych, V. (2005). Capital flows in a globalized world: The role of policies and institutions, Working paper 11696. Cambridge, Massachusetts National Bureau of Economic Research. Baxter, M., & Crucini, M. (1993). Explaining saving/investment correlations. The American Economic Review, V83(3), 416−436 June. Coakley, Jerry, Fuertes, Ana-Maria, & Spagnolo, Fabio (2004). Is the Feldstein–Horioka puzzle history? The Manchester School, 72(5), 569−590. Coakley, Jerry, Kulasi, Farida, & Smith, Ron (1998). The Feldstein–Horioka puzzle and capital mobility: A review. International Journal of Finance and Economics, V3, 169−188. Dooley, M., Frankel, J., & Mathieson, D. J. (1987). International capital mobility: What do saving–investment correlations tell us?IMF Staff Papers, 34(3), 503−531 September. 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These results are available upon request.
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