metadata: authors: 0: author: Calderon, Cesar
1: author: Loayza, Norman
2: author: Schmidt-Hebbel, Klaus
count: World
docna: 0: docna: Does openness imply greater exposure ?
docty: Policy Research Working Paper
subtopic: Economic Theory & Research,Investment and Investment Climate,Industrial Economics,International Trade and Trade Rules,Economic Growth,Macroeconomic Management
abstracts: cdata!: External exposure can be measured by the
            sensitivity of first and second moments of economic growth
            to openness and foreign shocks. This paper provides an
            empirical evaluation of external exposure using panel data
            methods for a worldwide sample of countries. Controlling for
            domestic conditions, the paper examines the growth and
            volatility effects of outcome measures of trade and
            financial integration, as well as four types of foreign
            shocks: terms of trade changes, trading partners'
            growth rates, international real interest rate changes, and
            net regional capital inflows. The paper analyzes the
            possibility of nonlinearities by allowing the growth and
            volatility effects of openness to vary with the general
            level of economic development and by letting the effects of
            foreign shocks depend on the degree of trade and financial
            integration. The findings point toward strong non-monotonic
            effects of openness and external shocks on growth and
            volatility. Moreover, all in all, the results contradict the
            view that international integration increases external
            vulnerability by hurting growth and increasing volatility or
            by amplifying the adverse effect of external shocks.
repnme: repnme: Does openness imply greater exposure ?
display_title: Does openness imply greater exposure
listing_relative_url: /research/2005/10/6318232/openness-imply-greater-exposure
topicv3: Economic Growth m1326241 471,Capital Account m1326277 1134,Trade m1326924 698,Macroeconomic Performance m1327618 1106,Investment Entry m1504647 2544
publishtoextweb_dt: 2010-07-01T00:00:00Z
no_of_pages: 44
model_extractions: WPS3733

**Comments welcome**

# **DOES OPENNESS IMPLY GREATER EXPOSURE?***

**César Calderón Norman Loayza Klaus Schmidt-Hebbel**** The World Bank The World Bank Central Bank of Chile

## Abstract

External exposure can be measured by the sensitivity of first and second moments of economic growth to openness and foreign shocks. This paper provides an empirical evaluation of external exposure using panel data methods for a worldwide sample of countries. Controlling for domestic conditions, the paper examines the growth and volatility effects of outcome measures of trade and financial integration as well as four types of foreign shocks: terms of trade changes, trading partners' growth rates, international real interest rate changes, and net regional capital inflows. The paper analyzes the possibility of non-linearities by allowing the growth and volatility effects of openness to vary with the general level of economic development and by letting the effects of foreign shocks depend on the degree of trade and financial integration. The findings point toward strong non-monotonic effects of openness and external shocks on growth and volatility. Moreover, all in all, the results contradict the view that international integration increases external vulnerability by hurting growth and increasing volatility or by amplifying the adverse effect of external shocks.

**Key Words:** External Shocks, Openness, Volatility, Growth, Non-linearities **JEL Classification:** F36, F41, F43

## World Bank Policy Research Working Paper 3733, October 2005

_The Policy Research Working Paper Series disseminates the findings of work in progress to encourage the exchange of ideas about development issues. An objective of the series is to get the findings out quickly, even if the presentations are less than fully polished. The papers carry the names of the authors and should be cited accordingly. The findings, interpretations, and conclusions expressed in this paper are entirely those of the authors. They do not necessarily represent the view of the World Bank, its Executive Directors, or the countries they represent. Policy Research Working Papers are available online at http://econ.worldbank.org._

* For useful comments and discussion we thank Pierre-Richard Agénor, Ricardo Caballero, Luis Felipe Céspedes, William Easterly, Linda Kaltani, Mauricio Larraín, Claudio Raddatz, Luis Servén, Raimundo Soto, and participants at the IFPRI/Cornell Conference on Threshold Effects and Non-Linearities in Growth and Development, the Annual Conference of the Central Bank of Chile, the Econometric Society World Congress, the Latin American Meetings of the Econometric Society, the Annual Meetings of the Chilean Society of Economics, and seminars at the Bank of International Settlements, Catholic University of Chile, University of Chile, University of La Plata, and Central Bank of Portugal.

** Calderón: The World Bank. Address: 1818 H St. N.W., Washington, DC 20433. Email: ccalderon@worldbank.org. Loayza: The World Bank. Address: 1818 H St. N.W., Washington, DC 20433. Email: nloayza@worldbank.org. Schmidt-Hebbel: Central Bank of Chile, Economic Research Division. Address: Agustinas 1180, Santiago de Chile. E-mail: kschmidt@bcentral.cl.
# **I. Introduction**

A central dimension of globalization is the world trend toward larger financial and trade openness, observed in most industrial and developing economies. Financial openness has increased from a world median of 5% of GDP in 1970 to 45% of GDP in 2000 and trade openness has grown from a world median of 44% of GDP in 1970 to 70% of GDP in 2000 (see Figure 1 for annual data and definitions).

More openness implies higher integration of world goods and capital markets, contributing to potential gains in growth and welfare. However, more international integration could also lead to heightened external exposure, measured by the sensitivity of first and second moments of economic growth to openness and foreign shocks. This vulnerability may be particularly important in poor countries, due to their production specialization, non-diversified sources of income, unstable policies, incomplete financial markets, and/or weak institutions.

A growing empirical literature is addressing the links between openness and macroeconomic performance, uncovering complex relationships but offering only partial perspectives on them. In fact, the existing literature does not provide a systematic and symmetric empirical analysis of the relationship between financial and trade openness, financial- and trade-related foreign shocks, and macroeconomic performance as represented by the average and volatility of economic growth. This paper attempts to fill this void by analyzing the experience of a large sample of developed and developing countries in the decades spanning 1970-2000.

The plan of the paper is the following. Section II provides a comprehensive review of the relevant literature. Section III presents the empirical contribution of the paper, including its methodology, worldwide data sample, and panel-data regression results for average growth and growth volatility. In this section we report first the simple linear effects of measures of trade and financial openness as well as four types of foreign shocks: terms of trade changes, trading partners’ growth rates, foreign real interest rate changes, and net regional capital inflows. Then we analyze empirically the possibility of non-linearities by assessing the dependence of the effects of trade and financial openness on the level of per 1
capita income. Third, we measure the amplification or dampening of the effects of external shocks depending on the degree of trade and financial openness. Section IV concludes.

# **II. Review of the Empirical Literature**

A growing empirical literature has analyzed the effects of financial openness, trade openness, and foreign shocks on growth levels and growth volatility. In this section we proceed to review briefly the analytical underpinnings and existing empirical results on the core relations that are the focus of this paper: those between financial openness, trade openness, foreign shocks, GDP growth, and GDP growth volatility.

## **A. Financial Openness and Growth**

The empirical literature on financial openness (FO) – as well as the research on trade openness (TO) reviewed below – is based on two classes of openness measures. Policy or legal measures reflect policy and regulatory restrictions or barriers imposed domestically on international trade volumes and financial flows and/or holdings. In contrast, outcome or _de facto_ measures reflect actual trade volumes and financial flows or stocks between the domestic economy and the rest of the world. On one hand, the strength of the first class of FO / TO measures is that it reflects policy restrictions while the second class is influenced by country-specific features – including size, distance, production specialization, and risk – in addition to domestic restrictions. Hence the first class may represent more exogenous policy conditions while the second class of FO/TO measures is likely to be endogenous to variables that are often explained by integration, including growth. On the other hand, outcome measures may reflect more truly country integration into world markets, while policy measures may not reflect binding policy restrictions and may be subject to measurement bias. Moreover, outcome indicators represent continuous variables that are more easily measured and are more widely available than the discrete measures of policy restrictions.

The policy measure of FO is largely based on information on capital controls in the IMF’s Annual Report on Exchange Arrangements and Exchange Restrictions, which has spawned construction of several discrete indicators of capital-flow restrictions on cross2
border or cross-residence flows.<sup>1</sup> The outcome measure reflects an actual measure of FO, based on cross-country capital flows or capital stocks, defined as ratios to GDP.<sup>23</sup> There is a growing literature on the effects of capital-account liberalization and FO on growth – Edison, Klein et al. (2002) provide an excellent survey. Here we discuss the previous work only briefly, in those dimensions that are relevant to this paper. (See Table 1 for a selective summary).

Preceding studies diverge significantly in FO measures, empirical methods, data samples, and results. The studies conducted during the past decade – most of them on measures based on the _de jure_ IMF restrictions – show mixed results. While Quinn (1997) and Edison, Klein et al. (2002) report positive significant growth effects of IFI for the world at large, many others do not find any evidence or reject robust evidence of FO growth effects, including Grilli and Milesi-Ferretti (1995), Kraay (1998), Rodrik (1998), O’Donnell (2001), Edison, Levine et al. (2002), and Razin and Rubinstein (2004).

Other studies have tested for FO measures and their interaction with third variables, in order to reflect non-linearities and non-monotonicities in the relationship between growth and FO. Here the general finding is that FO and external financial liberalization tend to reduce growth in countries that are either not industrialized (Klein and Olivei 2000), feature ethnic heterogeneity (Chanda 2001), have low income (Edwards 2001), or exhibit high black-market premiums (Arteta et al. 2001), while FO raises growth in countries with the opposite features. Klein (2003) reports quadratic interaction terms of FO with government quality and with per capita GDP, implying that FO only raises growth in middle-income countries and reduces growth in low- and high-income countries.

> 1 Policy or legal measures of capital-flow restrictions include a dummy variable based directly on the IMF measure, the Share measure reflecting the number of years of IMF-measured restrictions, and the Quinn index that allows varying degrees of restrictions based on the IMF information (Quinn 1997), all available for varying country and annual samples. In addition, the OECD computes a measure of capital-flow restrictions for 21 OECD countries. Finally, Montiel and Reinhart (1999) compute an index of restrictions for 15 emerging economies. For detailed discussion of legal and actual measures of capital restrictions see Edison, Klein et al. (2002).

> 2 Actual measures of FO include large country samples for capital flows (Kraay 1998) and stocks on gross capital flows accumulated from flows (Lane and Milesi-Ferretti 2001, 2003, Kose, Prasad and Terrones 2004).

> 3 More partial dimensions of financial restrictions and liberalization, even if they have some bearing for FO, are not considered in this paper. Among the latter are measures of stock market liberalization and the literature on the effects of the latter on growth, reviewed by Edison, Klein et al. (2002).

3
Therefore the latter evidence suggests strongly that FO and growth display a nonmonotonic relationship. At low levels of development – for several measures of development – financial liberalization and/or FO tend to lower growth, while the opposite is observed in developed nations, where FO contributes to growth. This result should not come as surprise. It reflects that international financial liberalization in non-OECD countries – frequently hampered by low-quality governments, poor institutions, or lack of effective banking regulation and supervision – takes place jointly with domestic financial liberalization. After the subsequent boom phase of massive credit growth, capital inflows, and domestic spending, frequently a hard landing ensues, reflected in a banking crisis and domestic recession, and hence depressing medium-term growth.

Finally Kose et al. (2005) do not find robust growth effects of FO separately but, interestingly, show that FO interaction with growth volatility turns the negative effect of volatility on growth into a positive one. This suggests that FO may alleviate adverse growth effects stemming from high GDP volatility by strengthening access to external countercyclical lending and allowing for international portfolio diversification by domestic agents.

# **B. Trade Openness and Growth**

Like FO measures, policy or legal measures of TO are based on measures of trade policy or trade restrictions and the standard measure of outcome or _de facto_ TO is the GDP share of total trade (exports plus imports).

As compared to the empirical literature on FO and growth, there is a longer and broader cross-country growth literature on the effects of trade liberalization and TO.<sup>4</sup> Again, here we discuss the previous work only briefly, in those dimensions that are relevant to this paper. (See Table 1 for a selective summary.) Previous work differs strongly in many dimensions – dependent variable (GDP growth, per capita income level, per capita income convergence), TO measures, controls, data samples, and econometric techniques. Earlier work finds significant, positive, and often very large effects of TO on growth, income levels, or income convergence (Dollar 1992, Ben-David 1993, Sachs and Warner 1995, Edwards 1998, Frankel and Romer 1999). Much of the latter research has been subsequently criticized for possible bias stemming

> 4 Edwards (1993) provides a survey of the older literature.

4
from endogeneity of trade to income levels or GDP growth, lack of robustness due to exclusion of relevant controls and/or use of inadequate data samples and estimation techniques. Rodrik and Rodriguez (2000) report that TO effects on growth are not robust to inclusion of geographic latitude and Rodrik et al. (2004) find that TO is not robust to inclusion of institutional quality. Rigobon and Rodrik (2005), based on a technique of identification through heteroskedasticity, is the only recent study reporting negative significant effects of TO on per capita income levels, controlling for institutions and geography. A subsequent study based on the same technique, by Lee, Ricci, and Rigobon (2004), shows that TO has positive but small effects on growth.

In contrast to the latter studies, there is recent research that finds significant and robust effects of TO on growth or income levels (Wacziarg 2001, Irwin and Terviö 2002, Alcala and Ciccone 2004, Kose et al. 2005). Some other recent work reports more qualified results: TO effects are not robust in cross-section estimations but they are significant in panel studies and robust to inclusion of institutional variables (Dollar and Kraay 2003, Wacziarg and Welch 2003). The latter study, focusing on trade liberalization country episodes, shows that trade shares and growth increase significantly and substantially after trade is liberalized. Finally, two recent studies look at interaction effects between TO measures and other variables. Kose et al. (2005), complementing their research on FO and growth, report robust positive effects of TO on growth and find that TO turns the negative effect of volatility on growth into a positive one. Alesina et al. (2005), controlling for country size and interaction effects between TO and size, find that TO has large effects in small countries but these effects become zero as country size tends to maximum size.

# **C. Foreign Shocks and Growth**

Foreign variables relevant to open economies comprise financial and real variables associated to capital flows and trade flows, respectively. They include price variables (international interest rates, terms of trade) and quantity variables (capital flows to emerging economies). For truly small countries (those facing infinite demand/supply elasticities for their exports/imports of capital and goods), only price variables matter for determining domestic performance, including growth. For countries that have some monopolic or monopsonic power in international markets – reflecting their size and/or their 5
specialization in trading differentiated goods under conditions of monopolistic competition – quantities matter for domestic performance too. However, here it is important to isolate the exogenous determinant (or the instrument) of quantities as the relevant predetermined quantity variable. In this vein, the world or regional supply of capital could be an adequate instrument for the supply of capital to the domestic economy, while average growth of all trading partners could be an adequate instrument for the foreign demand of exports by the domestic economy.

Foreign shocks are measured in two ways: the rate of growth or deviation of a foreign variable from its preceding level and the standard deviation of the variable in a given time period. Most empirical growth studies include one or two foreign shock variables based on the first measure, typically as control variables. Here we refer only selectively to recent cross-country empirical studies that quantify the effects of terms of trade, the foreign interest rate, capital inflows, and trade partner growth on domestic growth and growth volatility (Table 1).

The rate of growth of the terms of trade is the most widely used measure of foreign shocks (among representative studies are Easterly, Loayza, and Montiel 1997, FernándezArias and Montiel 2002, Loayza, Fajnzylber, and Calderón 2004, Barro and Sala-i-Martin 2004). In most studies terms-of-trade shocks turn out to be significantly positive determinants of growth.

In a highly integrated world, open economies are also influenced by growth in the rest of the world. Arora and Vamvakidis (2005) find that a 1% increase in economic growth of the countries’ trading partners leads to higher domestic growth by 0.8 percentage points.<sup>5</sup> Other studies have included the ratio of private capital inflows to GDP as a growth determinant and have also evaluated the impact of different types of capital flows on growth (Calderón and Schmidt-Hebbel 2003). Most of these studies have found a positive impact of private capital inflows on growth, with a stronger effect in the case of foreign direct investment.<sup>6</sup>

> 5 They argue that this result is consistent with the literature on the impact of cross-country spillovers (Arora and Vamvakidis 2004, Ahmed and Loungani 1999).

> 6 Most of these studies instrumentalize capital inflows using lagged values, legal origin variables or investor protection measures in order to avoid endogeneity bias from the response of capital flows to growth.

6
# **D. Growth and Growth Volatility**

Since the influential work by Ramey and Ramey (1995) that pointed out the negative cross-country relation between average GDP growth and GDP volatility, research has focused on providing explanations and more evidence on this negative relation found for the world sample and among low-income countries but not among industrial economies (Table 2). Elbadawi and Schmidt-Hebbel (1998) provide evidence that measures of macroeconomic volatility and low macroeconomic performance have a negative effect on growth, hypothesizing that the latter is behind the changing sign in the volatility-growth relation between low-income and high-income countries. Hnatkovska and Loayza (2004) provide robust evidence for the negative effect of GDP volatility on growth. By including interaction effects between volatility and relevant variables, they report that the negative effect of growth volatility on output is larger in economies with low-income levels and weak institutions and policies, and that the negative effect has grown in recent decades due to deep recessions.

# **E. Financial Openness, Trade Openness, and Growth Volatility**

Easterly, Islam, and Stiglitz (2000) explore the sources of GDP growth volatility in industrial and developing countries (Table 2). They find that higher TO leads to larger growth volatility, especially in developing countries. However they do not find a significant impact of FO on output volatility. O’Donnell (2001) finds that larger FO is associated with lower (higher) output volatility in OECD (non-OECD) countries. His results also suggest that countries with more developed financial sectors are able to reduce output volatility through financial integration.

Kose et al. (2003) reports that none of four FO and TO measures has any robust effect on GDP volatility. However terms of trade volatility, financial depth, and M2 volatility raise output volatility in the world. Bekaert et al. (2004) provide cross-section and time-series evidence of the relationship between FO and GDP growth volatility. Using two indicators of capital account openness, they find considerable evidence of lower GDP volatility after capital account liberalization in the world sample, with somewhat weaker results for developing countries.

7
Cavallo (2005) presents evidence that suggests that TO lowers output volatility in net terms. According to the author, this is due to two countervailing effects. Larger TO raises growth volatility through the terms-of-trade channel but this is more than offset by the finding that TO lowers growth volatility due to lower financial vulnerability to external shocks, sudden stops, and currency crushes.

Finally, regarding the influence of openness on the effect of growth volatility on growth levels, we mentioned above the result by Kose et al. (2005) that both FO and TO turn the latter negative effect into a positive one. Hnatkovska and Loayza (2004), however, reject an ameliorating influence of TO on the negative volatility-growth effect.

# **F. Foreign Shocks and Growth Volatility**

Foreign shocks – measured as deviation of a foreign variable from its trend or average level, or as the standard deviation of the variable – have been shown to be significant in determining business-cycle fluctuations of GDP or GDP volatility.

Kose (2002) evaluates the importance of fluctuations in world prices —fluctuations in the prices of primary, capital, and intermediate goods, and in the world interest rate— in driving business cycle fluctuations in small open developing countries (Table 2). He finds that roughly 88% of aggregate output fluctuations can be explained by world price shocks. Rodrik (2001) shows that GNP volatility in Latin America and the Caribbean is driven by both external shocks and domestic policy failures – with the terms of trade and capital flows as key contributors on the external front.

Mendoza (1995) was among the first attempts to evaluate the quantitative importance of terms of trade shocks in explaining business cycles, using a stochastic dynamic small open economy model. He found that terms of trade disturbances explain 56% of output variation.

Early research found that world interest rates do not have a significant role in explaining the dynamics of small open economies, including output fluctuations (Mendoza, 1991, Correia et al. 1992, 1995, Schmitt-Grohe 1998). However, using a dynamic stochastic small open economy model, Blankenau et al. (2001) find that world real interest rate shocks explain 33% of Canada’s output variation. The above mentioned research by Kose (2002) finds that world interest rate shocks account for roughly 1% of output 8
volatility in developing countries. Neumeyer and Perri (2004) report large effects of country risk fluctuations and small effects of world interest rate fluctuations on the high volatility of output in emerging economies.

Finally, Rodrik (2001) suggests that the instability of private capital flows has been the most important determinant of macroeconomic volatility in Latin America and the Caribbean during the 1990s. Together with per capita income, capital flow volatility accounts for close to half of the cross-national variation in GNP volatility in the region during the 1990s, compared to 20% in the 1980s.

# **G. Summing Up and Open Questions**

A rich empirical literature has developed on the relations between TO, FO, foreign shocks, growth, and growth volatility. At this stage of the cross-country and panel data research we conclude that neither FO nor TO does show a linear or even monotonic relation with economic growth and growth volatility. Financial liberalization and FO tend to lower growth at low levels of development while the opposite is observed in developed economies. In the case of TO and trade liberalization, the non-monotonicity with growth is not quite so strong as for FO and financial liberalization, as all studies, less one, show that the lower bound of growth effects of TO is zero. Non-monotonicities between openness and growth show up as strong interaction effects between measures of openness and various measures of development (per capita income, institutional quality, and growth volatility, among others) and country size. Yet the discussion about inclusion of adequate controls and their possible interaction with measures of openness, and their implications for the robustness of the role of the latter in determining growth, is still raging.

Regarding the behavior of growth volatility and cyclical output fluctuations, the evidence on the effects of FO and TO is contradictory and inconclusive. There is not even agreement on the intensifying or ameliorating effects that openness has on the traditionally negative relation between growth volatility and growth levels.

There is much more agreement regarding growth effects of foreign relevant variables, particularly the terms of trade. The latter variable is a frequently-used control variable in many empirical studies, and is typically found to be positive and significant in explaining growth. Some studies also report positive domestic growth gains from higher world growth and larger capital inflows.

9
The existing evidence on growth volatility and cyclical output fluctuations shows generally significant and large positive effects of volatility in relevant external variables.

Therefore, in the light of this review, we conclude that the existing literature does not provide a systematic and symmetrical empirical analysis of:

- relationships between average economic growth and both financial and trade openness,

- relationships between growth volatility and both financial and trade openness,

- foreign shocks (financial and real; exogenous price- and quantity-related) and their influence on growth and growth volatility, and

- interaction between openness and foreign shocks in their effect on average growth and growth volatility.

The rest of the paper addresses these issues.

# **III. Empirical Analysis**

We conduct two analogous empirical analyses. The first focuses on economic growth and the second on growth volatility. In both cases, the dependent variable is constructed using the annual per capita real GDP growth rate as the main input. For economic growth, the dependent variable is the _average_ rate of growth over a medium-run time window; and for growth volatility, the dependent variable is the _standard deviation_ of the growth rate over the same time window.

For both empirical analyses, our objective is, first, to study the simple linear effects of trade and financial openness as well as of various external shocks; second, to examine how the effects of trade and financial opening vary with the level of per capita income; and third, to consider whether the effects of external shocks are amplified or reduced by the degree of trade and financial openness. By conducting these exercises, we aim to provide a comprehensive empirical assessment of openness and external conditions for macroeconomic performance.

## **A. Sample and Methodology**

We work with a pooled data set of cross-country and time-series observations. It consists of 76 countries and, for each of them, at most 6 non-overlapping five-year periods 10
spanning the 1970-2000 period. See Appendix 1 for the list of countries in the sample. Appendix 2 provides full definitions and sources of all variables used in the paper, and Appendixes 3 and 4 present basic descriptive statistics for the data used in the economic growth and growth volatility regressions, respectively.

We use an estimation method that is suited to panel data, deals with static or dynamic regression specifications, controls for unobserved time- and country-specific effects, and accounts for some endogeneity in the explanatory variables. This is the generalized method of moments (GMM) for dynamic models of panel data developed by Arellano and Bond (1991) and Arellano and Bover (1995).

The general regression equation to be estimated is the following ' _yi_ , _t_ = β _X i_ , _t_ + μ _t_ +η _i_ + ε _i_ , _t_ (1) where the subscripts _i,t_ represent country and time period, respectively. _y_ is the dependent variable of interest, that is, economic growth or growth volatility. _X_ is a set of time- and country-varying explanatory variables that may include a lagged dependent variable, proxies of trade and financial openness, measures of various external shocks, interaction terms, and control variables. Finally, μ _t_ is an unobserved time-specific effect, η _i_ is an unobserved country-specific effect, and ε _it_ is the error term.

The method deals with unobserved time effects through the inclusion of periodspecific intercepts. Dealing with unobserved country effects is not as simple given the possibility that the model is dynamic and contains endogenous explanatory variables. Unobserved country effects are controlled for by differencing and instrumentation. Likewise, the method relies on instrumentation to control for joint endogeneity. Specifically, it allows relaxing the assumption of strong exogeneity of the explanatory variables by allowing them to be correlated with current and previous realizations of the error term ε _._ Parameter identification is achieved by assuming that future realizations of the error term do not affect current values of the explanatory variables, that the error term ε is serially uncorrelated, and that _changes_ in the explanatory variables are uncorrelated with the unobserved country-specific effect. As Arellano and Bond (1991) and Arellano and Bover (1995) show, this set of assumptions generates moment conditions that allow estimation of the parameters of interest. The instruments corresponding to these moment 11
conditions are appropriately lagged values of both levels and differences of the explanatory and dependent variables (the latter if the model is dynamic). Since typically the moment conditions over-identify the regression model, they also allow for specification testing through a Sargan-type test.

# **B. Economic Growth Regressions**

As is standard in the literature, the dependent variable is the average rate of real per capita GDP growth. The regression equation is dynamic in the sense that it includes the initial level of per capita GDP as an explanatory variable. As additional control variables, the regression includes the average rate of secondary school enrollment to account for human capital investment, the average ratio of private credit to GDP as a measure of financial depth, the average inflation rate to account for monetary discipline, and the average ratio of government consumption to GDP as a measure of government burden. The regression equation also allows for both unobserved time-specific and country-specific effects.

The explanatory variables of interest are measures of trade and financial openness, measures of external shocks, and various interaction terms. Given that we want to evaluate the effects of the economy’s actual contact with international markets, we work with _outcome_ measures of trade and financial openness. These measures are related to policies but are also the result of structural characteristics of the economy, such as size, natural and social endowments, and public infrastructure. The outcome measures we use are the ratio of exports and imports to GDP in the case of trade, and the ratio of portfolio and FDI liabilities to GDP in the case of financial openness.

We consider four types of external shocks; the first two primarily related to trade in goods and the latter two mainly related to financial transactions. All of them are defined so that they can be considered as exogenous to the country in question. They are the average growth of the terms of trade, the average weighted output growth rate of trade partners, the average amount of capital flows to the region where the country is located, and the average change of the international interest rate. Whereas the first two variables vary by country and time period, the third varies only by _region_ and period, and the fourth varies only by time period. Because of its limited sample variation, the effect of the international interest 12
rate shock cannot be distinguished from the unobserved time-specific effect; however, it is still possible to evaluate the effect of its interaction with the measures of trade and financial openness.

# **_Linear Effects of Openness and External Shocks_**

In the basic case, the effects of openness and shocks on growth are independent from each other and independent from other characteristics of the economy. This corresponds to the most common treatment of growth determinants in the literature. The regression equation we estimate in this case is the following, ' ' ' _yi_ , _t_ = β 0 _CVi_ , _t_ + β 1 _OPEi_ , _t_ + β 2 _EXTi_ , _t_ + μ _t_ +η _i_ + ε _i_ , _t_ (2) where CV is the set of control variables, OPE is the set of openness variables, and EXT is the set of foreign-shock variables.

The estimation results are presented in the first column of Table 3. We find that both financial and trade openness are positively related to economic growth. As mentioned in the introduction, the effect of financial and trade opening on growth is found to be ambiguous in the literature. However, ambiguity gives way to positive effects when the time-series dimension is taken into account: the beneficial impact of opening is most clearly seen in the experience of countries before and after liberalization (see, for instance, Wacziarg and Welch 2003). Our panel-data results confirm this finding as they are based not only on cross-country comparisons but also on over-time changes for individual countries. Furthermore, since our methodology controls for country-specific effects and the joint endogeneity of openness, our results are not subject to the criticism that the positive growth effect of openness is not robust to the inclusion of variables such as geographical location (see Rodrik and Rodríguez 2000 for the case of trade) or is due to reverse causation.

Regarding the growth effects of external shocks, they are all significant and carry the expected signs. That is, increases in favorable terms of trade, in the growth rate of trade partners, and in capital flows to the region produce a rise in average economic growth. These results together with the estimated size and significance of the period shifts confirm the substantial importance of external conditions as growth determinants.

13
All control variables carry significant coefficients of expected signs. The Sargan and serial-correlation specification tests do not reject the null hypothesis of correct specification, lending support to our estimation results. This is the case in all exercises presented below, and to avoid redundancy we only mention it here.

# **_The Effect of Openness Depending on the Level of Income_**

Increasingly there is the notion that the growth effect of openness may not be homogeneous across countries. Indeed, in part motivated by the work of Klein and Olivei (2000) in the case of financial openness, researchers have lately considered the possibility that the growth effect of opening the economy may depend on country characteristics such as income and institutional quality (see Edwards 2001 and Klein 2003). In the framework of our panel-data methodology, we now reassess this possibility by allowing the effect of each measure of openness to vary with the level of real per capita GDP, which serves as a proxy for overall development. We do this by interacting each openness measure with linear and quadratic per capita GDP ( _Inc_ ) in each country at the start of the corresponding period. The regression equation we estimate in this case is the following _yi_ , _t_ = β 0 ' _CVi_ , _t_ + β 1 ' _OPE i_ , _t_ + β 2 ' _EXTi_ , _t_ + β 3 ' _OPE i_ , _t_ * _Inci_ , _t_ + β 4 ' _OPE i_ , _t_ * _Inci_ 2, _t_ + μ _t_ +η _i_ + ε _i_ , _t_ (3) The last two columns of Table 3 present the estimation results. We consider the interaction between per capita GDP and the financial and trade openness variables one at a time; we do this in order to both simplify the interpretation of the results and do not overextend the parameter requirements on the data. Thus, column 2 shows the results when financial openness is interacted with income, and column 3, when trade openness is interacted with income. Interestingly, the regression results are _qualitatively_ similar whether we deal with financial or trade openness and can be summarized as follows. The coefficient on the corresponding openness indicator by itself is negative and significant, and the coefficients on the linear and quadratic interaction terms are significantly positive and negative, respectively. Therefore, the growth effect of opening the economy appears to depend on per capita income or, taking a broader interpretation, on the overall level of development. A corollary is that the net growth effect could in theory be positive or negative, and we should examine which is the case for the actual levels of per capita GDP found in our sample.

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Figure 2 (a and b) illustrates what the estimated pattern of coefficients implies for the change in growth produced by an increase in each openness measure. Specifically, Figure 2 uses the regression point estimates to plot the growth effect of a one-standarddeviation increase in openness as a function of per capita GDP for the full range of the sample. For both financial and trade opening, their growth effect is nearly zero for low levels of per capita GDP, it increases at a decreasing rate as income rises, and it reaches a maximum but only at high levels of income (higher in the case of trade openness). The growth effect of rising openness appears to be economically significant for middle- and high-income countries. In relation to the previous literature, we also find non-linear growth effects of opening, but we have some differences in the precise nature of the non-linearity. For instance, we differ from Edwards (2001) in that we do not find negative effects of increasing financial openness for low-income countries; and we differ from Klein (2003) in that we find that the growth effects of financial opening remain positive even for highincome countries. However, we agree with these papers that middle-income countries can expect to improve their growth performance as they become more integrated with the rest of the world.

Our coefficient estimates suggest significant economic effects. For instance, a onestandard-deviation increase in the degree of financial openness would lead to higher per capita growth rates by: (a) 0.67 percentage points for country observations at the 25th percentile of the sample distribution of output per capita during the 1970-2000 period (corresponding approximately to Pakistan in the mid 1990s), (b) 0.9 percentage points for observations at the 75th percentile (Malaysia around 1995), and (c) 0.8 percentage points for countries at the 95th percentile (Italy around 1995). The highest growth effect of larger international financial integration, 0.91 percentage points, is achieved by middle-income country observations at the 62th percentile (corresponding approximately to the levels of income per capita of Chile, Mexico, and Uruguay in 1995).

Similarly, an analogous increase in the degree of trade openness will generate an increase in the growth rate of GDP per capita of 0.33 percentage points for countries at the 25th percentile of the sample distribution of output per capita, 0.53 for the median country in the sample (Indonesia around 1995), 0.67 for countries at the 75th percentile, and 0.74 for countries at the 95th percentile of the world distribution of output per capita.

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# **_The Interaction between Openness and External Shocks_**

The previous exercises analyze the potential effect that openness can have on economic growth, controlling for various external shocks. Here we focus on whether openness makes the economy more or less responsive to external shocks. Ideally for the beneficial role of openness, it would amplify the growth effect of positive shocks and dampen the effect of negative ones. However, we find no evidence of asymmetric interaction effects (in results not presented here) and limit ourselves to the issue of whether the economic growth effect of shocks depends on the openness of the economy.

We address this question by considering interaction terms between each of the shocks and the openness variables. The regression equation we estimate in this case is the following, There are a large number of possibilities for these interactions, but in order to avoid overextending the parameter requirements on the data, we consider the interactions between financial and trade openness indicators with the external shocks _one shock at a time_ . This will also allow us to simulate the effect of each shock independently. The results are presented in Table 4, with each column devoted to the interactions with each of the four external shocks. An interesting pattern emerges. Larger trade openness decreases the economic growth effect of trade-related shocks --the growth of terms of trade and the GDP growth of trade partners-- while increasing the economic growth effect of financial market shocks --international interest rate changes and regional capital inflows. Conversely, larger financial openness increases the economic growth effect of trade-related shocks while reducing the impact of regional capital inflows, one of the financial market shocks. The exception to this pattern is that financial openness seems to increase the economic growth effect of international interest rate changes.

Since the growth effect of a shock now depends on three coefficients plus the levels of trade and financial openness, it is not immediately clear what the net effect is. Figure 3 helps to make this assessment by graphing the economic growth effect of one-standarddeviation _increase_ in each shock as a function of, first, trade openness and, then, financial 16
openness.<sup>7</sup> In the former case, we use the sample average of financial openness in the calculation of the partial effects; and in the latter, the sample average of trade openness.<sup>8</sup> The economic growth effect of an increase in terms of trade growth is positive for low and medium levels of trade openness; but as this increases further, the growth effect declines and may even become negative. The economic growth effect of the positive terms of trade shock increases with financial openness and is positive throughout the relevant range.

The economic growth effect of an increase in trade partners GDP growth is always positive, and, as noted above, it decreases with trade openness and increases with financial openness. In the case of the international interest rate shock, its direct impact on economic growth cannot be separated from the time effects; however, based on an exercise where we compare the period shifts with and without the interest rate shock interactions, we estimate that the direct impact of an increase in international interest rates is significantly negative. Once we take into account the interactions, the total economic growth effect of the interest rate jump continues to be negative, but it approaches zero as either type of openness rises. Finally, regarding the positive capital flow shock, its effect on economic growth is positive throughout most of the relevant ranges; but, as indicated above, larger trade openness increases its economic growth effect, while financial openness reduces it. All in all, these results challenge the conventional wisdom that trade openness increases the exposure to trade-related shocks and that financial openness magnifies financial-market shocks. The channels of transmission seem to be more complex.

We can use the numbers to draw several quantitative implications. Consider the following, for instance. First let’s consider the growth effects of external shocks at various levels of trade openness and given the sample average level of financial openness (corresponding approximately to that of India in the late 1990s). A one-standard-deviation decline in the terms of trade would lead to a fall of growth in real GDP per capita of 0.98 percentage points for country observations at the 25th percentile of the sample distribution of trade openness (approximately Pakistan in the late 1990s), 0.50 percentage points for the median country (Italy, 1996-2000), and nearly zero for country observations at the 75th

> 7 Considering their effect on growth, an increase in terms of trade, partners’ GDP, and capital inflows are regarded as beneficial shocks in the following discussion, while an increase in international interest rates is regarded as a detrimental shock.

> 8 For these simulations, we restrict the range of the financial openness indicator to values where the stock of foreign liabilities is positive.

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percentile (Paraguay, 1996-2000). Analogously, a one-standard-deviation decline in the growth rate of a country's trading partners would lead to a reduction in the growth rate of 0.96 percentage points for country observations at the 25th percentile of the sample distribution of trade openness and 0.78 percentage points for countries at the 75th percentile. Now let’s consider the growth effects of external shocks at various levels of financial openness and given the sample average level of trade openness (approximately corresponding to Indonesia and Ecuador in the late 1990s). A one-standard-deviation decline in regional capital inflows would generate a reduction in per capita GDP growth of 0.35 percentage points for country observations at the 25th percentile of the sample distribution of financial openness (approximately Algeria in the late 1990s), 0.28 percentage points for the median country (El Salvador, 1996-00), and 0.2 percentage points for countries at the 75th percentile (South Korea, 1990-00).

Finally, openness and external shocks may have a significant effect on macroeconomic volatility, and this in turn has been found to have a harmful influence on economic growth (see Fatás 2002, and Hnatkovska and Loayza 2003). Therefore, there is the possibility that the growth effects of openness and external shocks that we just described occur through their impact on macroeconomic volatility. To consider this possibility, we add the standard deviation of economic growth as an additional explanatory variable. The results are presented in Table 5, and although growth volatility carries the expected negative and significant coefficient, the coefficients on all other relevant variables retain their sign, significance, and, to a large extent, size. Therefore, the growth effects of openness, external shocks, and their interactions can be considered independently of their volatility effects, to which we turn next.

# **C. Volatility Regressions**

In this case, the dependent variable is the standard deviation of annual real per capita GDP growth, calculated over each 5-year period. The control variables represent some of the main sources of domestically induced volatility and are calculated over the same periods. They are the standard deviation of annual inflation, an average index of real exchange rate overvaluation, and the average number of years under systemic banking 18
crisis. The volatility regression equation also allows for both unobserved time-specific and country-specific effects.

The explanatory variables of interest are measures of trade and financial openness, the volatility of external shocks, and various interaction terms. The outcome measures of trade and financial openness are the same as those described above for the case of growth. Note, however, that for growth volatility regressions, the relevant indicator of the external shock is given by its volatility. For this reason, we use the _standard deviation_ of each external shock as the measure of interest (and not its _average_ value, as we did in the case of growth regressions).

# **_Linear Effects of Openness and External Shocks_**

The regression we estimate in this case is analogous to equation (2). The estimation results are presented in the first column of Table 6. We find that whereas an increase in financial openness tends to reduce volatility, larger trade openness increases it. This would indicate that financial opening has an unambiguous beneficial impact on the economy by both increasing average growth and reducing its volatility. In contrast, the effect of larger trade openness would be ambiguous as it induces higher but also more volatile growth. Regarding external shocks, we find that an increase in the volatility of terms of trade changes, the growth rate of trade partners, and capital flows to the region produce an increase in the volatility of economic growth. As expected, then, countries facing a more volatile external environment would undergo higher volatility.

All control variables carry positive and significant coefficients, as expected. The Sargan and serial-correlation specification tests do not reject the null hypothesis of correct specification, lending support to our estimation results. This is also the case in all remaining volatility regressions presented below.

# **_The Effect of Openness Depending on the Level of Income_**

We consider now the possibility that the volatility effect of openness vary with the level of real per capita GDP in the country at the start of the corresponding period. As in the case of growth regressions, we do this by interacting each openness measure with linear 19
and quadratic per capita GDP. Then, the regression we estimate in this group of exercises is analogous to equation (3).

The estimation results are presented in the last two columns of Table 6. As with growth regressions, we consider the interaction between per capita GDP and the openness variables one at a time. Figure 4 (a and b) takes the regression point estimates to graph the volatility effect of each openness indicator as a function of per capita GDP. There is a remarkable degree of similarity in the pattern of coefficients related to financial and trade openness indicators. The coefficient on the corresponding measure of openness by itself is always negative, and the coefficients on the linear and quadratic interaction terms are positive and negative, respectively. All of them are statistically significant. The interaction coefficients indicate that the volatility effect of a change in both types of openness varies convexly with income. The total volatility effect of a change in openness can be positive or negative depending on the size of the coefficients, and in this regard the effect of financial openness is different from that of trade openness, as discussed next.

Figure 4 (a) illustrates that a rise in financial openness leads to a decrease in volatility at all income levels. The volatility reducing effect of financial opening is smallest in magnitude in medium-income countries and largest at the both ends of the cross-country income distribution. The case of trade openness is somewhat different (see Figure 4 (b)). A rise in trade openness leads to an increase in volatility at all levels of national income. Poorest countries are the most vulnerable to the volatility inducing impact of trade openness. This effect decreases gradually as national income rises. Regarding the size of the volatility effect, the beneficial impact of financial opening is considerably larger than the detrimental effect of trade opening. This is important to keep in mind when financial and trade opening are undertaken together and their joint effects on vulnerability are considered.

# **_The Interaction between Openness and External Shocks_**

The last exercise considers to what extent the volatility effect of external shocks depends on the economy’s trade and financial openness. To do so, we include interaction terms between each of the shocks and the openness variables in the volatility regression. Then, in this case the regression we estimate is analogous to equation (4).

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The estimation results are presented in Table 7, with each column devoted to the interactions with each of the four external shocks. Figure 5 illustrates how the volatility effects of each shock vary with the level of, first, trade openness and, then, financial openness. We find that the interaction between any shock and financial openness always carries a significantly negative coefficient. This implies that financial openness helps reduce the volatility effect of all shocks considered, possibly by helping diversify away risk. Trade openness also reduces the volatility effect of terms of trade shocks. However, it appears to increase increases the volatility effect of the growth rate of trade partners, while it has no significant interaction with interest rate and capital flow shocks.

# **IV. Conclusions**

This paper tries to shed light on the question as to whether international integration increases a country’s external vulnerability. There are two sides to this question. The first is whether openness by itself hurts macroeconomic performance by decreasing average economic growth and increasing its volatility. The second one is whether openness magnifies the impact of adverse foreign shocks and exacerbates the contagion of external volatility. The cross-country and over-time empirical evaluation conducted in the paper provides some answers to these questions, and around them we organize these concluding remarks.

First, we find no evidence that financial or trade openness by itself induces a decline in economic growth. On the contrary, there is strong indication that financial and trade opening lead to growth improvement. Granted, this positive impact appears to be small in poor countries, but it becomes substantial as the country develops.

Second, we find no evidence that higher financial openness increases growth volatility. In fact, it appears that financial opening helps a country reduce its growth volatility, particularly if its domestic financial system is not in the transitional turmoil that characterizes middle-income countries. Trade opening does seem to increase volatility, but the effect is small and only relevant for low-income countries. For poor and middleincome countries, financial and trade openness present some trade-offs, but they are mostly 21
in favor of international integration. Moreover, as countries develop, the beneficial impact of trade and financial openness becomes strong and unambiguous.

Third, on whether financial and trade openness magnify the growth effect of adverse external shocks, the evidence is mixed. On the positive side, financial openness dampens the harmful growth impact of financial market shocks (such as higher international interest rates and lower capital inflows) while trade openness limits the adverse effect of traderelated shocks (such as unfavorable terms of trade changes and lower foreign growth). On the negative side, financial openness tends to exacerbate the growth effect of trade-related shocks while trade openness magnifies the effect of falling capital flows.

Fourth, the evidence regarding the ability of financial and trade openness to limit the contagion of external volatility is quite in favor of openness. With only one exception, we find no evidence that openness leads to higher volatility contagion. It is quite the contrary. Trade openness attenuates the effect of terms-of-trade volatility on domestic volatility. More impressively, financial openness dampens the volatility inducing effect coming from all external shocks, both financial- and trade-related. It appears that financial openness (and to some extent trade openness) provides the means for the economy to diversify away the external sources of risk.

All in all, the results presented in the paper cast a favorable light on financial and trade openness as engines of growth and stability. They question the view that international integration increases external vulnerability by hurting growth and increasing volatility or by amplifying the adverse effect of external shocks. For future research, there remains to understand the mechanisms through which development affects the link between openness and growth and the channels by which integration prepares the economy to deal with external instability.

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