Abstract
This article studies the impact of international financial openness on the public debt-to-output ratio in a representative sample of 37 developing countries from 1970 to 2015. We find that it is important to distinguish between the financial openness in the home country and that in the rest of the world, and distinguish between the external and domestic component of public debt. Our result shows that financial openness in the home country reduces the external and total public debt. Differently, financial openness in foreign countries increases the external public debt in the home country. Further analysis shows that the effect of home country financial openness can be explained by the substitution between external public debt and alternative external financing channels of the country; the effect of foreign countries’ financial openness can be explained by the substitution between external and domestic public debt.
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Notes
Throughout this paper we define “financial openness” in the international context, as the reverse to “capital control.” In other words, the removal of any restriction on international capital movement is considered as financial openness. The terms of “financial openness”, “capital account openness,” “financial integration,” “financial globalization,” and “financial liberalization” all refer to the same thing in this paper. For the reduction of restrictions on domestic financial system, such as the relaxation of domestic residents’ collateral constraints, expansion of bank credits, and deepening of capital markets, we call it “financial development.” Financial openness is a comprehensive concept that involves many aspects such as the management on exchange rate and international capital inflow and outflow. Throughout the empirical part of this paper, financial openness is always measured aggregatively by some certain de jure indicators.
The covered sample of 37 countries is representative and intentionally selected. The reason and selection procedure will be discussed in detail in Sect. 3.
Azzimonti et al. (2014) actually have talked about the possibility that “domestic liberalization can still affect domestic issuance through an indirect channel.” But what they considered is whether in computing the global liberalization index we should exclude the country of reference. This is different from our study as we consider the liberalization in the home country as an independent explanatory variable, rather than just a part of world liberalization index.
In the literature, there are three definitions for external (and correspondingly, domestic) public debt. (1) The first is based on the residence of the creditor (i.e., external debt is debt held by foreigners). WDI data use this definition. (2) The second is based on the place of issuance and the legislation that regulates the debt (i.e., external debt is debt issued in and under the jurisdiction of foreign countries). Panizza (2008) dataset, which will be used for robustness analysis later, takes this definition. (3) In the third definition, currency is the criterion (i.e., external debt is foreign currency debt). Data show that the amount of external debts defined based on the first and second definition is highly consistent.
The original version of Panizza (2008) public debt dataset covers the period from 1990 to 2007. The updated version provides data for the period between 1970 and 2010. We greatly thank Ugo Panizza for sharing this updated dataset with us.
The values of these three indices are rescaled to facilitate comparison. (1) The Chinn-Ito index ranges between 0 and 1. But the ADT index is originally set between 0 and 3. We divide it by 3 to make it comparable to Chinn-Ito index. (2) The FKRSU index, which lies between 0 and 1, is constructed to measure the degree of capital control. We use one minus the value of FKRSU index to measure financial openness. (3) The KOF index is divided by 100, since its original value is between 0 and 100.
The time-fixed effect is intentionally excluded from our model because of the following reason. Many of our sample countries have small economic scales compared to the rest of the world. This causes a consequence that they often have very similar values of \(\Delta FOrow{}_{i,t-1}\), which is calculated based on the GDP weighted average over all other countries. The pairwise correlation coefficient of this variables for any two countries in our sample is never below 0.957. This results in an issue of multicollinearity with the time-fixed effect. Thus, excluding the time-fixed effect helps us to obtain a better estimate for the coefficient of \(\Delta FOrow{}_{i,t-1}\). Otherwise, the effect of \(\Delta FOrow{}_{i,t-1}\) will be absorbed by the time-fixed effect and cannot be identified. Admittedly, the absence of time-fixed effect in a panel data model raises the concern about the omitted variable bias. We will deal with this concern by controlling for additional time-variant global factors in the robustness analysis section.
Our sample contains a lot of missing values for the 1970s and 1980s. This property impedes the functioning of LSDVC, since the currently available algorithm does not allow too many missing values. Thus we dropped the data before 1990, and then obtain the results reported in column (2.9). Similarly, in Tables 3 and 4 we also drop the data before 1990 to obtain the LSDVC estimates.
In Eq. (4) we do not have the explanatory variable of \(I(\Delta FOrow_{i,t-1}<0)\). This is because there is no sample point that \(\Delta FOrow_{i,t-1}=0\). In other words, the dummy variable \(I(\Delta FOrow_{i,t-1}<0)\) is perfectly collinear with \(I(\Delta FOrow_{i,t-1}>0)\) and should be excluded from the regressors.
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Dong, D. The impact of financial openness on public debt in developing countries. Empir Econ 60, 2261–2291 (2021). https://doi.org/10.1007/s00181-020-01839-x
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DOI: https://doi.org/10.1007/s00181-020-01839-x