Standard theoretical models predict that financial integration should lead to a lower degree of business cycle synchronization. In the canonical two-country general equilibrium model with complete financial markets, the country hit by a positive productivity shock experiences an increase in the marginal product of capital and labor, and receives capital on net—a mechanism that leads to negative output correlations between the two countries (e.g. Backus, Kehoe, and Kydland (1992) and Baxter and Crucini (1995)). Obstfeld (1994) formalizes another mechanism that also yields a negative link between financial integration and business cycle synchronization. In his model, financial integration shifts investment towards risky projects, enabling countries to specialize according to their comparative advantage, which implies that output growth among financially integrated countries should be negatively correlated. There might also be the case, where causality runs the other way since diversification benefits become larger with less correlated shocks across countries. Heathcote and Perri (2004) develop a model, where less correlated cycles lead to an increase in the equilibrium level of financial integration. In their set-up, a higher level of financial integration further reduces the correlation of the business cycles.
Surprisingly, the empirical literature fails to find the theoretically predicted negative association between financial integration and business cycle synchronization in the data. If anything, cross-country studies find a significant positive correlation between financial integration and GDP co-movement. While one could reconcile the positive association between synchronization and integration introducing market imperfections such as information frictions, contagion and moral hazard (e.g. Calvo and Mendoza (2001); Morgan, Rime, and Strahan (2004)), it is not entirely clear why different cross-sectional studies focusing on different country samples and time periods, all find exactly the opposite prediction of the standard models. Our contribution, in this paper, is to document the theoretically predicted negative effect of financial integration on business cycle synchronization as a robust regularity.
Why do our results differ from those of the previous studies? We show that the main difference between our findings and those that are in the literature is due to the estimation method. Using cross-sectional techniques, the existing studies investigate whether countries with stronger financial ties have more similar business cycles. These estimates will be biased if there are latent country-pair factors and global shocks that affect both integration and synchronization between pair of countries. In contrast, we have a rich panel dataset that allows us to identify the link between integration and synchronization, by examining the impact of within country-pair changes in financial integration on output co-movement.
We investigate the effect of financial integration on business cycle synchronization utilizing confidential data from the Bank of International Settlements’ (BIS) Locational Banking Statistics Database. This database reports bilateral cross-country bank assets and liabilities (stocks and flows) over the past three decades for a group of twenty developed countries. Our data set gives us three main advantages over the previous studies and helps us to identify the effect of financial integration on business cycle synchronization. First, the rich panel structure allows us to control both for unobservable and hard-to-account-for time-invariant country-pair factors, such as distance, sociopolitical ties and differences in cultural norms. Recent research shows that informational frictions, cultural linkages and bilateral trust—to the extent that they can be measured—have strong effects on financial integration (e.g. Portes and Rey (2005); Guiso, Sapienza, and Zingales (2009); Ekinci, Kalemli-Ozcan and Sørensen (2008); Giannetti and Yafeh (2008); Mian (2006)). In addition by shaping preferences, trust and cultural norms might directly affect business cycle patterns (e.g. Stockman and Tesar (1995)).
Second, the considerable time dimension of the data allows us to control for global shocks over an extended period. Over the past decades cross-border financial integration has increased significantly (e.g. Lane and Milesi Ferretti (2004, 2007)). At the same time business cycles in industrial countries have become more alike (e.g. Kose, Otrok, and Prasad (2008); Otto, Voss, and Willard (2001); Rose (2009)). A mechanical interpretation based on the cross-country correlations will be that financial integration has contributed to the increased correlation of countries’ output cycles. Yet, financial globalization goes hand-in-hand with trade integration, where the latter can lead to increased synchronization of business cycles. In addition, monetary policy has increasingly been coordinated at a global level, which can also affect both integration and synchronization. For example, Rose (2009) shows that inflation targeting countries tend to have a higher degree of business cycle synchronization, while Rose and Engel (2002) present cross sectional evidence of a higher degree of synchronization among countries that share a common currency. In the same vein, Inklaar, Jong-A-Pin, and de Haan (2008) find that fiscal policy convergence has also an effect on the synchronicity of output growth in the OECD economies.
Third, by focusing on a homogeneous group of twenty developed countries, we substantially reduce concerns of parameter heterogeneity. Although there are other studies that focus only on the OECD countries, most of the cross sectional studies pool developed, emerging market and under-developed countries into the estimation, due to limited degrees of freedom. However, theory and evidence so far suggest that the effect of integration on business cycle patterns can be quite different across the developed and the developing world (e.g. Kraay and Ventura (2000, 2007); Calderon, Chong, and Stein (2007); Kose, Otrok, and Prasad (2008); Rose (2009)).
We start our analysis by employing cross-sectional estimation to show that a higher degree of financial integration is associated with more synchronized output cycles. This result matches the results of previous studies (e.g. Imbs (2004, 2006)). Yet, once we move to the panel estimation and control for country-pair time-invariant characteristics by including country-pair fixed effects and global shocks by including time fixed effects, we find that a higher degree of financial integration is associated with more divergent, less synchronized, output cycles. We obtain similar results when we group the data at a longer frequency by splitting the sample into six non-overlapping 5-year periods. Controlling for bilateral goods trade and industrial specialization patterns does not alter the results either. Dynamic panel estimates that allows us to account for inertia in business cycle synchronization also yield a large negative effect of banking integration on output co-movement. Our results indicate an economically significant effect: a 10% increase in bilateral integration is associated with 1.9% (one standard deviation) fall in GDP growth co-movement.
As argued above, the finding of a negative association between integration and synchronization can be due to reverse causation. To the best of our knowledge, there has been no paper that estimates bilateral time-varying instrumental variable (IV) specifications for financial and/or trade integration. We estimate such models in an effort to identify the one way effect of financial integration on output co-movement.
Specifically we employ two distinct identification strategies. First, building on our parallel work on the effects of the European Union (EU) and the associated financial sector reforms on banking integration (Kalemli-Ozcan, Papaioannou, and Peydró (2009)), we use as an instrument a bilateral time-varying index that measures the degree of legislative-regulatory harmonization policies in financial services among EU countries. There is a strong positive relationship between implemented legislative harmonization policies in financial services and bilateral banking integration, conditional on the monetary unification. This result complements the findings of the law and finance literature (La Porta, Lopez-de-Silanes, Shleifer, and Vishny (1997, 1998); La Porta, Lopez-de-Silanes, and Shleifer (2008)) by showing that cross-country legal harmonization is associated with an increased degree of bilateral financial integration. The second stage estimates reveal that the component of banking integration predicted by legislative harmonization policies in the financial sector makes business cycles less alike.
Second, using data from Reinhart and Rogoff (2004) and Ilzetzki, Reinhart, and Rogoff (2008) we construct a time-varying instrument that reflects the bilateral flexibility of the exchange rate regime. The first-stage regression indicates that financial integration is significantly higher among pairs of countries with fixed-exchange rates. This result complements previous work documenting a similar pattern among emerging and under-developed economies (e.g. Calvo and Reinhart (2002) and Gelos and Wei (2005)). The second-stage estimates show that the component of banking integration predicted by the nature of the exchange rate regime is negatively associated with GDP fluctuations. While the exchange rate regime may affect business cycles through trade, we do not find such an effect in our data. In addition, using both instruments, where the over-identifying restriction is not rejected, implies that higher financial integration yields lower output correlations.
The paper is structured as follows. In the next section we present our econometric methodology and data. Section 3 presents our benchmark results on the effect of financial integration on business cycle synchronization. Section 4 presents the IV estimates that link exchange rate arrangements and financial legislation reforms with banking integration in the first-stage and banking integration with output synchronization in the second stage. Section 5 concludes.
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