Arnaud Mehl
email: arnaud.mehl@ecb.int

Julien Reynaud
email: julien.reynaud@ecb.int

Julien Reynaud #
email: julien.reynaud@malix.univ-paris1.fr

Domestic Debt Structures in Emerging Markets : New Empirical Evidence

Keywords: JEL Classification: F34, F41, G15 public domestic debt, composition, risk, emerging economies Résumé F34, F41, G15 dette publique domestique, composition, risque, économies émergentes

This paper explains why public domestic debt composition in emerging economies can be risky, namely in foreign currency, with a short maturity or indexed. It analyses empirically the determinants of these risk sources separately, developing a new large dataset compiled from national sources for 33 emerging economies over 1994-2006. The paper finds that economic size, the breadth of the domestic investor base, inflation and fiscal soundness are all associated with risky public domestic debt compositions, yet to an extent that varies considerably in terms of magnitude and significance across sources of risk. Only inflation impacts all types of risky debt, underscoring the overarching importance of monetary credibility to make domestic debt compositions in emerging economies safer. Given local bond markets' rapid development, monitoring risky public domestic debt compositions in emerging economies becomes increasingly relevant to global financial stability.

Introduction

A major reason why emerging economies are more prone to financial crises than mature economies is the atypical composition of their debt. Thus far, the literature has largely focused on external debt, notably on the inability of emerging economies to borrow in international capital markets in their domestic currency, which is sometimes coined the external dimension of "original sin" (see e.g. Eichengreen andHausmann, 1999, 2005;[START_REF] Zettelmeyer | Original Sin, Balance Sheet Crises and the Role of International Lending[END_REF][START_REF] Tirole | Inefficient Foreign Borrowing: a Dual and Common Agency Perspective[END_REF][START_REF] Eichengreen | Currency Mismatches, Debt Intolerance and Original Sin: Why They are not the Same and Why It Matters[END_REF][START_REF] Hausmann | On the Determinants of Original Sin: an Empirical Investigation[END_REF][START_REF] Bordo | How 'Original Sin' was Overcome: the Evolution of External debt Denominated in Domestic Currencies in the United States and the British Dominions[END_REF][START_REF] Flandreau | Old Sins: Exchange Rate Clauses and European Foreign Lending in the 19 th Century[END_REF][START_REF] Mckinnon | The East Asian Dollar Standard, Fear of Floating, and Original Sin[END_REF][START_REF] Mehl | The determinants of 'domestic' original sin in emerging market economies[END_REF].

Since the turn of the millennium, however, many emerging economies have retired their external debt and substituted it with domestically issued debt (IMF, 2002(IMF, , 2003(IMF, , 2005(IMF, and 2006)).

Late 2007, the stock of domestic debt securities issued by residents of the emerging economies reporting data to the Bank for International Settlements (BIS) reached USD 5.6 trillion, which is seven times larger than the stock of international debt securities (USD 0.8 trillion). Domestic debt securities issued by emerging economies accounted for 46% of their combined GDP in 2007, twice the share of 1994.

The conscious nurturing of public domestic debt markets has become a major objective of financial policy in many emerging economies, an orientation that has been supported by international financial institutions (BIS, 2007). Domestic debt markets are seen as an alternative source of financing that helps soften the impact of "sudden stops" [START_REF] Calvo | When Capital Flows Come to Sudden Stop: Consequences and Policy[END_REF] in external funding (IMF, 2003). Local currency bond markets are further believed to contribute to financial stability by reducing currency mismatches and lengthening the duration of debt.1

In this new context, there is growing consensus that domestic debt has become equally, if not more, important to assess financial vulnerability in emerging economies than is external debt.

Illustrative of this, the Group of Seven, one of the highest fora for cooperation in international monetary and financial affairs, has acknowledged the role of public domestic debt markets as a key contributor to growth and financial stability in emerging economies (G7, 2007). 2 Likewise, the BIS has endeavoured to draw implications from the development of these markets for global financial stability (BIS, 2007).

A nascent line of research has provided evidence on the determinants of the development of domestic bond markets. For instance, [START_REF] Burger | Local Currency Bond Markets[END_REF] found that countries with stable inflation and strong creditor rights have larger domestic bond markets. [START_REF] Claessens | Government Bonds in Domestic and Foreign Currency: the Role of Macroeconomic and Institutional Factors[END_REF] found that large economies with a wide investor base have larger domestic bond markets; that less flexible exchange rate regimes are associated with more foreign currency issuance and that inflation, the fiscal burden, the origin of the legal system and capital account openness also matter.

One aspect which has received less attention in the literature, however, is that domestic debt itself is a potential source of risks, particularly when it comes to its composition. 3 Excessive reliance on short-term public domestic paper exposes borrowers to default risk, if debt cannot be rolled over, or to liquidity risk if assets are illiquid. The role of short-term public debt, namely the Tesobonos and the GKOs, was identified as a major source of vulnerability as early as in the Mexican crisis of 1995 and the Russian crisis of 1998. In addition, denomination in foreign currencies of public domestic debt may give rise to balance sheet mismatches if the bulk of assets 2 See the statement of the G7 Finance Ministers meeting in Essen on 9-10 February 2007 (G7, 2007): "We also met with Ministers of Finance from a number of key emerging market economies to discuss the role of local bond markets in fostering growth and financial stability. In this context developing local currency bond markets deserves higher priority to reduce emerging countries' vulnerability to external shocks and financial crises and to promote growth." 3 As the BIS put it, any financial innovation may involve new risks, and the swift development of domestic bond markets in emerging economies is "no exception" (BIS, 2007).

or revenues are in local currency. Last, indexation to an interest rate, a price index or a foreign currency, may render liabilities uncertain and prone to increase in bad times (IMF, 2003).

In this setting, fewer studies have tried to provide systematic evidence on the composition of public domestic debt in emerging economies and on the possible emergence of new risks, bar [START_REF] Jeanne | Government Debt in Emerging Market Countries: a New Dataset[END_REF], [START_REF] Cowan | Sovereign Debt in The Americas: New Data and Stylized Facts[END_REF] and [START_REF] Panizza | Domestic and External Public Debt in Developing Countries[END_REF]. None of these studies, however, provide an empirical analysis of the determinants of risky domestic debt compositions.

Along with [START_REF] Burger | Local Currency Bond Markets[END_REF] and [START_REF] Claessens | Government Bonds in Domestic and Foreign Currency: the Role of Macroeconomic and Institutional Factors[END_REF], closest to our paper is [START_REF] Hausmann | On the Determinants of Original Sin: an Empirical Investigation[END_REF] who examine financial vulnerabilities arising from the so-called "domestic original sin", namely the inability of emerging economies to borrow domestically in local currency at long maturities and fixed interest rates. 4 The empirical analysis therein is based, however, on a small sample of 21 country-observations.

The key contribution of our paper is therefore to explain why public domestic debt composition in emerging economies can be risky by analysing empirically the determinants of three major sources of risk separately, namely short maturities, foreign currency denomination and indexation. To this end, our paper relies on a new large dataset on the composition of public domestic government debt, which we carefully develop from national statistics for a broad set of 33 emerging market economies from the mid-1990s to 2006. The lack of high quality and internationally comparable data has been recognised as a key impediment to the understanding and development of domestic debt markets in emerging countries, leading to the launch of initiatives to improve data quality (BIS, 2007;[START_REF] G7 | Statement by G-7 Finance Ministers and Central Bank Governors[END_REF]G8, 2007). Our large dataset helps address some of the limitations of data used in previous literature, and is thereby another contribution of the paper.

To anticipate on the paper's main results, we find that sources of risky public domestic debt compositions vary greatly across emerging economies, although short-term maturities are the most common source of risky debt. In addition, our data indicate that public domestic debt compositions have become overall safer in the last fifteen years, notably because maturities have lengthened. Our empirical results suggest that economic size, the breadth of the domestic investor base, inflation and fiscal soundness are all associated with the riskiness of public domestic debt composition, yet to an extent that varies considerably in terms of magnitude and significance across sources of risk. Only inflation impacts all types of risky debt, underscoring the overarching importance of monetary credibility to make public domestic debt compositions in emerging economies safer.

The remainder of the paper is set out as follows. Section 2 presents the new data and evidence on risky public domestic debt compositions in emerging economies. Section 3 reviews the empirical methodology. Section 4 presents the results. Section 5 concludes.

Domestic debt composition: new data and evidence

The new dataset

The lack of high quality and internationally comparable bond market data has been a key impediment to analyse mismatches and other vulnerabilities arising from the rapid development of domestic debt markets in emerging countries. In reviewing some of the existing data sources, [START_REF] Panizza | Domestic and External Public Debt in Developing Countries[END_REF] recalls that about two-thirds of recent joint IMF-World Bank debt sustainability analyses discuss vulnerabilities linked to total -i.e. including domestic -public debt (see also IMF, 2003 and2006). However, few of these exercises have data on the composition (maturity, currency, indexation terms) of debt, and most of the policy conclusions are based on vulnerabilities arising from external debt only (ibid.).

One of the main international sources of data on domestic bond markets worldwide traditionally used in both official reports and the literature (see e.g. [START_REF] Burger | Local Currency Bond Markets[END_REF]Warnock, 2006, Claessens et al. 2007) is the data provided by individual central banks and published quarterly by the BIS. Beyond the traditional split between external and domestic debt, these data provide little or no information on characteristics relevant to financial stability analysis, such as currency of issuance, maturity or indexation terms (BIS, 2007). 5 These shortcomings inhibit comparisons across countries and tend to impede effective monitoring of potential mismatches and other vulnerabilities. Better data are therefore crucial to assess the risks associated with the rapid development of domestic debt in emerging economies.

To address some of the shortcomings of existing sources of data, we carefully develop a dataset on the composition of the stock of central government debt for 33 emerging economies on the basis of national sources. As can been seen from Table A in the annex, which reports the sources and definitions, extensive data collection work was needed, occasionally involving security-by-security checks. 6 Additional data quality checks were carried out using the BIS's databases on domestic debt securities. Relative to existing datasets available in the literature, our data have three characteristics.

First, the cross-section dimension is relatively broad. We have data for 33 emerging economies from all emerging market regions. This is more than most existing datasets (e.g.

Hausman and Panizza, 2003, have 21 emerging economies; against 27 in [START_REF] Burger | Local Currency Bond Markets[END_REF]19 in Jeanne and Guscina, 2006;22 in Cowan et al., 2006 and12 in Claessens et al., 2007).

In a very recent overview of the literature, [START_REF] Panizza | Domestic and External Public Debt in Developing Countries[END_REF] presents data drawn from various sources for as many as 130 countries, including mature, emerging and developing economies.

This is clearly more than our dataset, although our country dimension should be sufficient for our purpose, given that we are primarily interested in understanding financial vulnerabilities arising from risky domestic debt composition in emerging economies, not in mature or in developing economies.

Second, the time series dimension is relatively long. Many previous studies (Hausman and Panizza, 2003;[START_REF] Borensztein | Sovereign Debt Structure for Crisis Prevention[END_REF][START_REF] Eichengreen | Other People's Money -Debt Denomination and Financial Instability in Emerging Market Economies[END_REF][START_REF] Burger | Local Currency Bond Markets[END_REF] have data for a (occasionally small) cross-section of countries. We have data from 1994 to 2006. Admittedly, some papers [START_REF] Jeanne | Government Debt in Emerging Market Countries: a New Dataset[END_REF][START_REF] Cowan | Sovereign Debt in The Americas: New Data and Stylized Facts[END_REF]) have datasets with an even longer time dimension that stretches to the 1980s. We do not see this as a major shortcoming of our data, however, as the development of modern, bonded, debt markets in emerging economies started in earnest in the 1990s, if not after the turn of the millennium (BIS, 2007).

Third, and perhaps most importantly, the data can be disaggregated to obtain a systematic view of the main sources of risky domestic debt compositions. Many of the previous studies (e.g. [START_REF] Burger | Local Currency Bond Markets[END_REF][START_REF] Cowan | Sovereign Debt in The Americas: New Data and Stylized Facts[END_REF][START_REF] Claessens | Government Bonds in Domestic and Foreign Currency: the Role of Macroeconomic and Institutional Factors[END_REF] have breakdowns between external vs. domestic debt or between local currency vs. foreign currency debt. Our data allow for a more detailed analysis of mismatches and vulnerabilities related to domestic debt by providing breakdowns by currency of issuance (foreign vs. domestic), maturity (short term vs. long term)

and indexation terms (variable interest rate or price indexation vs. straight fixed interest rate). Our breakdowns are similar to those of [START_REF] Hausmann | On the Determinants of Original Sin: an Empirical Investigation[END_REF] and [START_REF] Jeanne | Government Debt in Emerging Market Countries: a New Dataset[END_REF], but for a longer time dimension and for a broader cross-section, respectively.

Specifically, we calculate the four following measures M of the riskiness of domestic debt

composition: ] 1 , 0 [ ∈ ≡ D d M i i , i = 1, 2, 3, 4
where D denotes total public domestic debt and d is one of the four following categories i of risky public domestic debt, namely (i=1) in foreign currency, (i=2) with a short maturity, (i=3) indexed and (i=4) combining all risk categories. Clearly, for a given measure, the higher is M, the riskier is public domestic debt composition.

Stylised facts

Risky public domestic debt compositions in emerging economies are characterised by four main features. As can be seen from Table 1, which reports the average share of risky public domestic debt in total public domestic debt, sources of risk (foreign currency denomination, short maturities and indexation, all risks combined) are unevenly widespread across emerging economies. Between 1994 and 2006, short-term maturities were the most common source of risk (accounting for 24% of domestic debt), followed by indexation (with 20%) and -only lastforeign currency denomination (with 12%). This comes somewhat unexpected given that much of the literature's attention has thus far focused on foreign currency debt as the main source of financial vulnerabilities in emerging economies (Eichengreen and[START_REF] Eichengreen | Exchange Rates and Financial Fragility[END_REF][START_REF] Jp Morgan | Introducing the JP Morgan Government Bond Index-Emerging Markets (GBI-EM)[END_REF][START_REF] Panizza | Domestic and External Public Debt in Developing Countries[END_REF]. These three sources of risk taken together, around half of public domestic debt in our 33 emerging economies could be considered as risky over 1994-2006. The averages hide marked differences across countries and time, as suggested by relatively large standard deviations (between 21% to 34%). Most of these differences arise from variation across (i.e. between) countries rather than from variation over time (i.e. within countries). Note: Given that a debt security can have different risk characteristics (e.g. being both short term and indexed to prices), the ratios reported in column (4) do not necessarily equal the sum of those reported in columns (1) , ( 2) and (3).

Public domestic debt composition has become overall safer in the last fifteen years, albeit with marked nuances across sources of risk. Between 1994 and 2006, the share of risky public debt has declined from about 60% to around one-third of total public domestic debt (Figure 1). Public domestic debt has become safer primarily because its maturity has lengthened: the share of short-term debt to total public debt has decreased from about 40% to less than 20%. The share of indexed public debt has also declined somewhat (from 20% to 14%). The share of foreign currency public debt has been perhaps the most volatile, increasing from about 9% in 1997 to 16% in 2002, after the Argentinean and Turkish crises, before decreasing to 6% in 2006.

Public domestic debt composition also varies greatly in terms of sources of risk across regions and countries. For each of the emerging regions in our dataset, Figure 2 plots the median of our four risk measures (dots) together with the respective inter-quartile range (rectangles).

Emerging Asia, together with the Middle-East and Africa, are the two emerging regions where public domestic debt composition is safest. Both regions have almost no debt in foreign currency and only a small share of their total public domestic debt (8-12%) is indexed. Admittedly, about one-fifth has a short maturity, which is similar to the share in other regions. Public debt is riskiest in Latin America: one-third is in foreign currency, 40% indexed and one-quarter short-term.

Differences are even stronger at the country level. For some countries (e.g. Brazil, Croatia, Mexico), public domestic debt is risky from virtually all sources. For other countries, some sources of risk are inexistent: for instance, South Korea has no foreign currency debt; Singapore and Thailand have no indexed debt; Israel has a high share of indexed debt, but a small share of foreign currency debt, etc.

Figure 2: Selected descriptive statistics on the sources of risky domestic debt compositions in emerging economies (country level, 1994-2006) 0 .2 .4 . Source: authors' own calculations. Note: The figure plots the median of our four risk measures (dots) together with the respective inter-quartile range (rectangles) for each of the emerging regions in our dataset; "fx" refers to foreign currency denominated debt, "ind" to indexed debt, "st" to short-term debt and "all" to all sources of risk combined.

Empirical methodology

Theoretical determinants of public domestic debt composition

Potential determinants of the composition of public domestic public debt in emerging economies are multifaceted. For our core specification, we draw from the literature on the development of local bond markets and 'domestic original sin', which typically include determinants such as the size of the economy, the breadth of the investor base and the soundness of macroeconomic policies both on the inflation and fiscal fronts.

To test the robustness of the results and extend then, we also consider other potential determinants, including: money supply growth, nonlinearities in inflation, the magnitude of the fiscal burden, the role of the banking sector, property right enforcement, foreign investor appetite, the exchange rate regime and capital account openness.

Size of the economy and breadth of the investor base

Claessens, Klingebiel and Schmukler (2007) found that large countries with broad domestic investor bases have larger local bond markets, while smaller economies rely more on foreign currency bonds. This suggests that scale effects exist in the development of local bond markets, for instance in terms of spreading fixed costs associated with the establishment of clearing and settlement systems, an appropriate legal framework or in terms of market liquidity.

A broader domestic investor base can also be expected to make domestic debt composition safer by contributing to support demand for domestic currency, unindexed, longdated debt instruments. Pension system and capital market reforms are of paramount importance in this respect (IMF, 2002 and2003). 7 In the empirical estimations, the size of the economy is proxied with the natural logarithm of GDP. The breadth of the investor base is proxied with the ratio of gross private savings to GDP, taken from the IMF's World Economic Outlook (WEO).

Inflation

Lower and less volatile inflation help deepen domestic debt markets [START_REF] Burger | Local Currency Bond Markets[END_REF]. But price stability can also change the composition of public debt and make it less risky. [START_REF] Hausmann | On the Determinants of Original Sin: an Empirical Investigation[END_REF] found indeed that monetary credibility, as measured by lower inflation and the imposition of capital controls are associated with lower 'domestic original sin' in emerging economies. 8 Persistent creditor fears that debt might be inflated away can prevent governments from issuing long-term bonds durably, thereby pointing to a potential "credibility barrier", however [START_REF] Jeanne | Why Do Emerging Market Economies Borrow in Foreign Currency[END_REF]. In the empirical estimations, monetary credibility and inflation are proxied with the annual growth rate of the GDP deflator, also taken from the IMF's WEO.

Soundness of public finances

It is especially debt maturity which can be affected by fiscal profligacy. [START_REF] Missale | The Debt Burden and Debt Maturity[END_REF] show that governments will tend to have a shorter debt maturity to enhance credibility when the debt burden is high, but not necessarily at low levels. 9 In a similar vein, [START_REF] Drudi | Default Risk and Optimal Debt Management[END_REF] develop a model where the relation between the level and maturity of debt depends on both inflation and default risk. The relation is negative at high levels of debt in particular, because the default risk premium becomes then too large for governments to issue long-term debt. In the empirical estimations, the level of the debt burden is proxied with the ratio of the central government fiscal balance to GDP, also taken from the IMF's WEO.

Core specification

The econometric analysis raises challenges relating to both our measures of risky openness domestic debt compositions and the nature of our dataset. First, given that our measures of risky domestic debt compositions are by construction bounded between zero and one, estimation has to resort to censored regression methods. This can be done by using the tobit model, which is well suited when the dependent variable takes values within fixed bounds, a solution retained in previous literature. Second, given the panel structure of our dataset, the possible existence of unobservable country effects has to be taken into account. Indeed, unobserved country heterogeneity would bias standard tobit estimations. To address these issues, we resort to randomeffects tobit estimation, which is defined as the following combination of linear and probabilistic regression:

⎪ ⎪ ⎪ ⎩ ⎪ ⎪ ⎪ ⎨ ⎧ < ≤ ≤ > = + + = 0 y 0 1 y 0 y 1 y 1 y ε ν βx y * t i, * t i, * t i, * t i, t i, t i, i t i, * t i, if if if : with (1)
where i and t are the country and time dimensions, respectively, y * t i, the measure of domestic original sin defined in (1),

t i,
x a vector of explanatory variables and β a vector of parameters to be estimated. The disturbances are split into both unobserved country effects, noted i υ , which are i.i.d. N(0, 2 σ υ ), and panel level effects, noted t i, ε , which are i.i.d. N(0, 2 σ ε ) and independent of i υ .

All regressions also include time dummies to control for e.g. global factors and regional dummies to capture fixed regional effects.

To gauge whether random-effects tobit estimation is required, it is useful to calculate the ρ -statistic, which measures the contribution of the variance of the disturbances due to country effects to the total variance of the disturbances:

2 υ 2 ε 2 υ σ σ σ ρ + =
When ρ is close to zero, random-effect tobit estimation is not significantly different from a standard tobit one. Formal comparison between the two models can be achieved by running a likelihood-ratio test, where the null hypothesis is that the standard tobit is better suited than the random-effect tobit. Moreover, a likelihood-ratio test of the nullity of i υ , also comparing the tobit estimator and the panel estimator, as well as Wald tests on nullity of the estimated parameters can be calculated.

Results

Core results

Baseline estimates are presented in Table 2, which reports marginal effects. The marginal effects of the explanatory variables are estimated at their sample means. The marginal effects of dummy variables are estimated for a change in these variables from 0 to 1. For the sake of comparability between the various specifications, we strive to ensure that the number of observations remains the same, however, due to data availability some models include fewer observations. The ρ- statistic is significantly positive, confirming that standard tobit estimation -which does not take into account unobserved country effects -would be inappropriate.

Overall, our results suggest that economic size, the breadth of the domestic investor base, inflation and fiscal soundness are all associated with the riskiness of public domestic debt composition, yet to an extent that varies considerably in terms of magnitude and significance across sources of risk.

Public domestic debt composition is found to be risky in small economies whose domestic investor base is narrow. However, depending on the sources of risk, the magnitude of the impact of economic size and of the breadth of the domestic investor base differs markedly.

Economic size matters for all categories of risk but does not matter significantly for short-term public debt in total public domestic debt. This suggests that scale effects exist, e.g. in terms of spreading the fixed costs of setting clearing and settlement systems or in terms of market liquidity, but not necessarily when it comes to issuing more public domestic debt with longer maturities specifically. We also have evidence that the relationship is causal, with the Wu- Public domestic debt composition becomes also safer when the domestic investor base broadens, as proxied by an increase in the private savings-to-GDP ratio. Financial deepening underpinned by heftier private savings is therefore important to increase the demand for, and tilt domestic debt composition towards, safer debt security instruments. However, this effect varies again sizeably across sources of risk and is statistically significant only as regards the share of foreign currency debt. In this respect, according to our median point estimates, an increase in the 10 The exception is when the share of foreign currency debt is the dependant variable.

investor base by 1 percentage point is associated with a decrease in the share of foreign currency debt by 0.1 percentage point The relationship is in this case also found to be causal according to the aforementioned test statistics.

Echoing previous literature on 'domestic original sin' and the development of local bond markets [START_REF] Hausmann | On the Determinants of Original Sin: an Empirical Investigation[END_REF][START_REF] Burger | Local Currency Bond Markets[END_REF][START_REF] Claessens | Government Bonds in Domestic and Foreign Currency: the Role of Macroeconomic and Institutional Factors[END_REF]), poor macroeconomic policies (monetary instability through high inflation and high fiscal deficits) are found to be associated with riskier domestic debt compositions. Only inflation impacts all types of risky debt, however. According to our median point estimates, a decrease in inflation by 1 percentage point is associated with a decrease in the share of foreign currency, of indexed and of short-term debt in total public domestic debt by about 0.05 percentage point each; when all sources of risky public domestic debt are combined together, the total decline is in the order of 0.2 percentage point. Progress towards price stability is therefore systematically important to alleviate creditor fears that domestic debt could be inflated away (as in [START_REF] Jeanne | Why Do Emerging Market Economies Borrow in Foreign Currency[END_REF] and to change its composition towards local currency, long-term and unindexed instruments. The relationship is also causal in most specifications, except when the share of indexed debt in total domestic debt is the dependant variable, which is probably due to the fact that part of debt indexation is to inflation.

Sounder public finances are also almost always associated with safer public domestic debt compositions, barring that they have no impact on the share of indexed debt in total public domestic debt. According to our median point estimates, an improvement in the fiscal balance-to-GDP ratio by 1 percentage point is associated with a decline in the share of foreign currency debt and in the share of short-term debt in total public domestic debt by about 0.25 percentage point each; when all sources of risky domestic debt are combined together, the total decline is in the order of 0.4 percentage point. As aforementioned, fiscal profligacy might prompt governments to make their commitment to price stability more credible by issuing debt with shorter maturities (as in [START_REF] Missale | The Debt Burden and Debt Maturity[END_REF] or prevent them from issuing long-term debt as the debt premium becomes overly large (as in [START_REF] Drudi | Default Risk and Optimal Debt Management[END_REF]. The relationship is causal in most specifications, except when the measure that combines all risks together is the dependant variable.

Overall, our results suggest that only inflation impacts all types of risky debt, underscoring the overarching importance of monetary credibility to make public domestic debt compositions in emerging economies safer. Moreover, the share of foreign currency and short term debt in total public domestic debt both decrease when the domestic investor base broadens, inflation declines and fiscal policy becomes sounder. This suggests that potential currency and maturity mismatches arising from risky public domestic debt compositions can mainly be alleviated through better policies. By contrast, the share of indexed debt specifically decreases in large countries and when inflation declines. This suggests that vulnerabilities arising from contingent interest payments can mainly be reduced by exploiting scale effects and through higher monetary credibility.

Robustness checks

To assess the robustness of our results, we first change the estimator and re-run regressions using a standard tobit estimator with country fixed effects (rather than random effects) and time effects.

The results are not fundamentally altered. 11 We then take alternative definitions of the variables and start by replacing inflation with the growth of M2 (Table 3) and by a dummy that equals 1 when inflation exceeds an ad-hoc threshold of 10% to capture potential non-linearities associated with high inflation levels (Table 4).

11 To save space, the results are not reported here but are available upon request from the authors. Shares M i of risky domestic debt in total domestic debt (broken down by source of risk)

Again, the lack of monetary credibility proxied by an acceleration in money supply growth is still associated with riskier public debt compositions, although not when it comes to indexed debt. High inflation levels also increases the riskiness of public domestic debt composition, but only as regards debt in foreign currency and when all sources of risk are combined.

Next we replace the fiscal balance-to-GDP ratio with an index of fiscal autonomy which measures the burden imposed by the government on economic activity, as in [START_REF] Claessens | Government Bonds in Domestic and Foreign Currency: the Role of Macroeconomic and Institutional Factors[END_REF].12 Again, our main results remain fundamentally unchanged (Table 5). A higher tax burden on the economy is associated with riskier public domestic debt compositions of all kinds, bar short-term public debt. Shares M i of risky domestic debt in total domestic debt

We then try to sharpen our results on the role of the investor base by focusing more on local banks. Local banks are the main investors in emerging local bond markets, which is a major difference relative to mature economies where the investor base is known to be more diverse. 13 Due to their prominent role as investors, local banks in emerging economies might also have a bearing on domestic debt composition. One rationale for this lies in bank ownership, with stateowned banks being possibly urged by governments to buy certain types of debt instruments that the latter would otherwise not be able to sell in the market (La [START_REF] Porta | Agency problems and dividend policies around the world[END_REF][START_REF] Hauner | Public debt and financial development[END_REF]. 14 Incentive distortions might provide another rationale: for instance, [START_REF] Hauner | Public debt and financial development[END_REF] found that banking sectors in emerging economies that hold large amounts of government debt also tend to develop more slowly. As he puts it, banks become then too complacent (the so-called "lazy banks" hypothesis) and have little incentives to develop deposits, private credit and other traditional financial products and, in this respect, "the consequences of large public sector borrowing from the domestic banking sector are also a timely policy issue, given the ongoing debate on optimal debt structures". We attempt to address these consequences by testing the impact of bank holdings of government bonds on the riskiness of domestic debt composition. To this end, we take from the Bank Regulation and Supervision Database (World Bank, 2007) a variable that accounts for the share of bank holdings in the total government bond market (Table 6). We also test the impact of banks ownership to reflect Hauner (2008)'s view that state owned banks could be required to hold government bonds (Table 7). Using the same database, we include a measure of bank ownership that we interact with the measure of banks holdings of government bonds.

The results reported in Table 6 suggest that economies where banks hold a large share of domestic bonds tend to have safer public domestic debt compositions in terms of most sources of risk. In particular, when interacting bank holdings with ownership (see Table 7), this effect seems 13 The share of local bonds held by banks in emerging economies is four times larger than in mature economies (40% against 11% in 2005, according to BIS, 2007). 14 More precisely, La [START_REF] Porta | Agency problems and dividend policies around the world[END_REF] find that more prevalent government ownership of banks tends to be associated with less efficient and less developed banking sectors. This argument is taken up by [START_REF] Hauner | Public debt and financial development[END_REF] who argues that "the banks would not hold public debt because they are "rationally lazy," but because they are coerced into it" (p. 2).

to be more due to state-owned banks than to privately-owned banks (they are not included here in the regression but their corresponding coefficient is insignificant). All in all, these results suggest that a growing role of local banks in the domestic investor base also help make public domestic debt composition safer. We next attempt to assess the impact of property right enforcement. As pointed out by [START_REF] Borensztein | Sovereign Debt Structure for Crisis Prevention[END_REF] and Burger and Warnock (2004), property rights enforcement is key to investors by contributing to inspire greater confidence in domestic financial markets. Allegedly, this would help in the development of domestic currency markets. We introduce a proxy for property right enforcement, which we take from the International Country Risk Guide database (Table 8). The results indicate that stronger property rights enforcement also tends to help reduce the riskiness of public domestic debt composition, albeit only with regard to indexed debt and when all sources of risk are combined. (Burger and Warnock, 2004). Data on foreign investor participation in local debt markets is often not readily available (BIS, 2007), however. We therefore use a standard proxy of foreign investor appetite, namely the spread between local money market rates and the US interest rate (see e.g. [START_REF] Kamin | The evolution and determinants of Emerging Market credit spreads in the 1990s[END_REF]. Our results indicate that greater foreign investor appetite is associated with a reduction in most categories of risky public domestic debt (Table 9). This further underscores that widening the investor base to domestic and foreign investors alike contributes to make public domestic debt composition safer. We then introduce a dummy to proxy the de facto exchange rate regime, which equals one when exchange rate movements vis-à-vis the US dollar exceed an ad-hoc cut-off of +/-5%, suggesting that the exchange rate then tends to be more flexible. We find that countries that have flexible exchange rate regimes also tend to have safer public domestic debt compositions, which are less titled toward foreign currency and short-term debt (Table 10). This echoes evidence in [START_REF] Claessens | Government Bonds in Domestic and Foreign Currency: the Role of Macroeconomic and Institutional Factors[END_REF] who found that countries with flexible exchange rates tend to have larger local currency bond markets, either because investors might be less fearful of sharp currency depreciations and large inflation spikes or because governments are less pressed to commit to a foreign anchor currency by issuing foreign currency bonds. Shares M i of risky domestic debt in total domestic debt Last, we consider the impact of financial openness. [START_REF] Hausmann | On the Determinants of Original Sin: an Empirical Investigation[END_REF] found that the imposition of capital controls helps lower domestic 'original sin', and tilt domestic debt composition towards safer, i.e. local currency, non-indexed, long-term, instruments. Such restrictions may force residents to hold long-term domestic currency denominated bonds by narrowing the range of alternative funding or investment opportunities. There might be opposite forces, however. For instance, the lifting of capital controls could also be expected to help reduce domestic debt riskiness, for instance, by contributing to a widening of the investor base to foreigners. To address the issue, we introduce a dummy for financial openness in the empirical specification, which we take from [START_REF] Fratzscher | Financial Openness and Growth: Short-Run Gain, Long-Run Pain? ECB Working Paper[END_REF]. Our results suggest that financial openness is associated with an increase in the riskiness of public domestic debt compositions (Table 11), in line with [START_REF] Hausmann | On the Determinants of Original Sin: an Empirical Investigation[END_REF]. Shares M i of risky domestic debt in total domestic debt

Conclusions

Our paper has endeavoured to explain why public domestic debt composition in emerging economies can be risky by analysing empirically the determinants of three major sources of risk, namely short maturities, foreign currency denomination and indexation. To that end, it has relied on a new large dataset on the composition of domestic government debt.

Looking at our evidence, we found that sources of risky public domestic debt compositions vary greatly across emerging economies. Short-term maturities are the most common source of risky debt, followed by indexation and -only last -foreign currency denomination, with sizeable differences among emerging economies. This comes somewhat unexpected given that much of the literature's attention has thus far focused on foreign currency debt as the main source of financial vulnerabilities in emerging economies. Domestic debt compositions have become overall safer in the last fifteen years, albeit also with marked nuances across sources of risk, given e.g. that it is notably debt maturities that have lengthened. Our empirical results suggest that economic size, the breadth of the domestic investor base, inflation and fiscal soundness are all associated with the riskiness of public domestic debt composition, but again to an extent that varies considerably in terms of magnitude and significance across sources of risk. There is evidence that the relationships are causal in most cases. Overall, our results

suggest that only inflation impacts all types of risky debt, underscoring the overarching importance of monetary credibility to make public domestic debt compositions in emerging economies safer. Moreover, the share of foreign currency and short term debt in total public domestic debt both decreases when the domestic investor base broadens, inflation declines and fiscal policy becomes sounder. The results therefore suggest that potential currency and maturity mismatches arising from risky public domestic debt compositions can mainly be alleviated through better policies. By contrast, the share of indexed debt decreases specifically in larger countries and when inflation declines. This suggests that vulnerabilities arising from contingent interest payments can mainly be reduced by exploiting scale effects and with higher monetary credibility.

The results are broadly robust to changes in the estimator, in the definitions of the variables and to additions of other potential determinants. In this respect, we find that the exchange rate regime, capital account openness, property right enforcement, foreign investor appetite and the role of local banking sectors also matter for some of the measures of risky public domestic debt.

From a policy perspective, monitoring risky public domestic debt compositions in emerging economies becomes increasingly relevant to global financial stability given the rapid development of local bond markets. Risk monitoring should increasingly focus on indicators of domestic rather than external debt sustainability. The set of indicators used to monitor financial vulnerabilities in emerging economies on a regular basis might therefore also need to evolve.

Measures of risk arising from public domestic debt composition might be one indicator to consider, in this new context.

Figure 1 :

 1 Figure 1: Evolution since 1994 of the main sources of risk affecting public domestic debt composition in emerging economies

Table 1 :

 1

		FX denominated domestic debt / total domestic debt	Indexed domestic debt / total domestic debt	Short term domestic debt / total domestic debt	All risky debt sources combined / total domestic debt
			(1)	(2)	(3)	(4)
	Average		11.8	20.0	23.9	47.4
	St. dev.	overall	25.6	25.7	21.4	34.1
		between	27.4	23.7	16.0	31.6
		within	7.5	9.8	13.5	13.9
	Source: authors' calculations.

Selected descriptive statistics on the sources of risky public domestic debt compositions in emerging economies

(pooled 33 countries, 1994-2006; %)

Table 2 :

 2 Hausmann F-test and the Durbin-Wu-Hausman χ 2 test suggesting that economic size is exogenous in most specifications.10 Core specification regression results

				Foreign currency	Indexed	Short-term	All risks combined
	Log(GDP)			-0.004 **	-0.007 **	0.004	-0.022 **
					(1.97)	(2.45)	(1.01)	(2.41)
	Domestic savings to GDP	-0.117 **	-0.007	-0.105	-0.086
					(2.16)	(0.11)	(1.28)	(0.57)
	Inflation			0.054 ***	0.028 *	0.070 ***	0.243 ***
					(3.68)	(1.65)	(2.69)	(3.20)
	Fiscal balance to GDP			-0.202 ***	-0.058	-0.260 **	-0.392 *
					(2.70)	(0.60)	(2.16)	(1.80)
	Constant			1.005 **	0.831 ***	0.285 *	0.757 ***
					(2.48)	(3.36)	(1.89)	(4.92)
	Log likelihood			-197.65	-258.26	-224.28	-160.38
	Wald test			112.19 ***	95.53 ***	163.55 ***	221.03 ***
	σ	2 υ			1.367 ***	0.897 ***	0.528 ***	0.318 ***
	σ	2 ε			0.582 ***	0.474 ***	0.329 ***	0.268 ***
	ρ				0.846 ***	0.781 ***	0.720 ***	0.584 ***
	Likelihood ratio test σ	2	υ = 0	315.23 ***	286.38 ***	215.08 ***	146.71 ***
	N umber of observations	426	426	426	426
	N u m b e r o f c o u n t r i e s			3 3	3 3	3 3	3 3
	N otes: Absolute value of z statistics in parentheses
	(* ) significant at 10%; (**) significant at 5%; (***) significant at 1%.

Shares M i of risky domestic debt in total domestic debt

Table 3 :

 3 Robustness checks on inflation: Broad money growth M i of risky domestic debt in total domestic debt

					Foreign currency	Indexed	Short-term	All risks combined
	Log(GDP)			0.003	-0.008 ***	-0.009 **	-0.027 ***
					(1.20)	(3.38)	(2.48)	(2.94)
	Domestic savings to GDP	-0.121 *	0.026	-0.154 **	-0.122
					(1.80)	(0.53)	(2.36)	(0.80)
	Broad money growth			0.023 *	0.002	0.017 **	0.078 *
					(1.65)	(0.46)	(2.28)	(1.87)
	Fiscal balance to GDP			-0.206 **	0.016	-0.320 ***	-0.722 ***
					(2.05)	(0.22)	(3.23)	(3.39)
	Constant			0.916 **	1.075 ***	0.587 ***	1.111 ***
					(2.49)	(4.74)	(4.63)	(8.88)
	Log likelihood			-204.19	-255.78	-217.93	-170.39
	Wald test			74.08 ***	98.30 ***	192.18 ***	243.55 ***
	σ	2 υ			1.156 ***	1.046 ***	0.602 ***	0.308 ***
	σ	2 ε			0.582 ***	0.501 ***	0.325 ***	0.275 ***
	ρ				0.797 ***	0.813 ***	0.773 ***	0.557 ***
	Likelihood ratio test σ	2	υ = 0	290.55 ***	285.43 ***	218.27 ***	146.45 ***
	N umber of observations	390	390	390	390
	N umber of countries			33	33	33	33

N otes: Absolute value of z statistics in parentheses (* ) significant at 10%; (**) significant at 5%; (***) significant at 1%.

Shares

Table 4 :

 4 Robustness checks on inflation: Non-linearities in inflation levels

				Foreign currency	Indexed	Short-term	All risks combined
	Log(GDP)			-0.003 *	-0.001	0.003	-0.023 ***
					(1.66)	(0.36)	(0.78)	(2.56)
	Domestic savings to GDP	-0.068 *	0.024	-0.078 **	0.013
	H igh inflation dummy #		(1.71) 0.010 **	(0.91) 0.004	(1.94) 0.010	(0.09) 0.063 ***
					(2.19)	(1.41)	(0.98)	(3.49)
	Fiscal balance to GDP			-0.173 **	-0.010	-0.339 ***	-0.555 ***
					(2.52)	(0.25)	(2.87)	(2.61)
	Constant			0.237	0.080	0.568 ***	0.922 ***
					(0.69)	(0.35)	(4.55)	(7.71)
	Log likelihood			-215.32	-257.83	-229.41	-163.55
	Wald test			116.38 ***	67.18 ***	169.21 ***	244.26 ***
	σ	2 υ			1.455 ***	1.473 ***	0.537 ***	0.340 ***
	σ	2 ε			0.581 ***	0.496 ***	0.333 ***	0.268 ***
	ρ				0.862 ***	0.898 ***	0.722 ***	0.617 ***
	Likelihood ratio test σ	2	υ = 0	286.34 ***	299.33 ***	208.94 ***	161.37 ***
	N umber of observations	390	390	390	390
	N umber of countries			33	33	33	33
	N otes: Absolute value of z statistics in parentheses
	(* ) significant at 10%; (**) significant at 5%; (***) significant at 1%.
	(#) Equals 1 when inflation > 10%.

Table 5 :

 5 Robustness checks on fiscal balance: Fiscal burden

				Foreign currency	Indexed	Short-term	All risks combined
	Log(GDP)			-0.001	-0.009 ***	0.005	-0.003 ***
					(0.98)	(2.96)	(1.44)	(3.65)
	Domestic savings to GDP	-0.111 **	0.024	-0.107 *	0.041
					(2.06)	(0.39)	(1.61)	(0.25)
	Inflation			0.077 ***	0.049 **	0.080 ***	0.245 ***
					(4.90)	(2.42)	(3.39)	(3.30)
	H igher fiscal burden			0.059 **	0.148 ***	0.037	0.198 **
					(2.31)	(4.53)	(0.95)	(2.42)
	Constant			0.002	-0.325	0.155	0.530 **
					(0.00)	(0.83)	(0.65)	(2.54)
	Log likelihood			-177.40	-234.79	-199.83	-142.45
	Wald test			85.1 ***	70.89 ***	143.85 ***	180.59 ***
	σ	2 υ			1.442 ***	0.881 ***	0.592 ***	0.309 ***
	σ	2 ε			0.544 ***	0.461 ***	0.317 ***	0.258 ***
	ρ				0.875 ***	0.784 ***	0.777 ***	0.588 ***
	Likelihood ratio test σ	2	υ = 0	323.44 ***	291.57 ***	202.26 ***	137.06 ***
	N umber of observations	390	390	390	390
	N u m b e r o f c o u n t r i e s			3 3	3 3	3 3	3 3
	N otes: Absolute value of z statistics in parentheses
	(* ) significant at 10%; (**) significant at 5%; (***) significant at 1%.

Table 6 :

 6 Robustness checks on the investor base: Bank holdings of government bonds

					Shares M i of risky domestic debt in total domestic debt
				Foreign currency	Indexed	Short-term	All risks combined
	Log(GDP)			-0.003 ***	-0.006	0.005	0.002
					(2.61)	(1.43)	(1.39)	(0.39)
	Bank holdings of gov. bonds	-0.077 ***	-0.088 ***	-0.911 ***	-0.711 ***
					(3.21)	(3.51)	(12.13)	(7.87)
	Inflation			0.015 *	0.021 *	0.088 ***	0.287 ***
					(1.84)	(1.87)	(3.30)	(4.23)
	Fiscal balance to GDP		0.172 ***	0.017	-0.379 ***	-0.520 ***
					(3.20)	(0.34)	(3.17)	(3.36)
	Constant			0.929 ***	0.380 *	0.518 ***	0.772 ***
					(3.18)	(1.86)	(5.09)	(8.70)
	Log likelihood			-181.75	-228.55	-174.32	-110.17
	Wald test			62.19 ***	63.70 ***	279.35 ***	229.43 ***
	σ	2 υ			1.832 ***	1.379 ***	0.534 ***	0.389 ***
	σ	2 ε			0.59 ***	0.483 ***	0.296 ***	0.228 ***
	ρ				0.910 ***	0.891 ***	0.766 ***	0.743 ***
	Likelihood ratio test σ	2	υ = 0	330.65 ***	309.35 ***	294.59 ***	315.26 ***
	N umber of observations	387	387	387	387
	N umber of countries			30	30	30	30
	N otes: Absolute value of z statistics in parentheses
	(* ) significant at 10%; (**) significant at 5%; (***) significant at 1%.

Table 7 :

 7 Robustness checks on the investor base: Public banks holdings of government bonds

					Shares M i of risky domestic debt in total domestic debt
					Foreign currency	Indexed	Short-term	All risks combined
	Log(GDP)			0.004	0.005	0.006	0.004
					(0.78)	(1.43)	(1.39)	(0.57)
	Public banks holdings of gov. bonds	-0.004	-0.002 **	-0.005 *	-0.017 ***
					(1.09)	(2.02)	(1.73)	(3.06)
	Inflation			0.014 *	0.027 *	0.049 **	0.228 ***
					(1.66)	(1.87)	(2.05)	(3.49)
	Fiscal balance to GDP		-0.406 ***	-0.072	-0.416 **	-0.852 ***
					(4.11)	(0.88)	(2.32)	(4.53)
	Constant			-0.563 **	-0.164	0.374 ***	0.737 ***
					(2.15)	(0.86)	(3.18)	(8.69)
	Log likelihood			-97.67	-124.52	-86.27	-32.55
	Wald test			54.96 ***	52.87 ***	155.65 ***	171.22 ***
	σ	2 υ			1.342 ***	1.212 ***	0.605 ***	0.34 ***
	σ	2 ε			0.361 ***	0.377 ***	0.239 ***	0.169 ***
	ρ				0.932 ***	0.911 ***	0.864 ***	0.801 ***
	Likelihood ratio test σ	2	υ = 0	234.16 ***	221.39 ***	200.18 ***	258.43 ***
	N umber of observations	239	239	239	239
	N u m b e r o f c o u n t r i e s			3 0	3 0	3 0	3 0
	N otes: Absolute value of z statistics in parentheses
	(* ) significant at 10%; (**) significant at 5%; (***) significant at 1%.

Table 8 :

 8 Extensions: Property rights enforcement

					Shares M i of risky domestic debt in total domestic debt
				Foreign currency	Indexed	Short-term	All risks combined
	Log(GDP)			-0.004 *	0.016 ***	0.004	-0.028 ***
					(1,65)	(4,54)	(1,14)	(2,87)
	Domestic savings to GDP	-0.092 *	-0.035	-0.141 **	-0.007
					(1,67)	(0,44)	(1,98)	(0,04)
	Inflation			0.013	0.003 **	0.072 ***	0.237 ***
					(0,73)	(2,12)	(2,85)	(3,31)
	Fiscal balance to GDP		-0.141 *	-0.204 *	-0.216 **	-0.292
					(1,71)	(1,72)	(1,98)	(1,23)
	Property rights			0.003	-0.122 ***	-0.014	-0.138 **
					(0,19)	(4,77)	(0,50)	(2,35)
	Constant			0.946 **	2.173 ***	0.372 **	0.977 ***
					(2,13)	(7,19)	(2,16)	(5,91)
	Log likelihood			-237.60	-235.62	-198.90	-141.40
	Wald test			102.98 ***	98.27 ***	147.17 ***	258.80 ***
	σ	2 υ			1.287 ***	0.834 ***	0.574 ***	0.298 ***
	σ	2 ε			0.557 ***	0.458 ***	0.315 ***	0.258 ***
	ρ				0.842 ***	0.768 ***	0.768 ***	0.572 ***
	Likelihood ratio test σ	2	υ = 0	177.53 ***	268.09 ***	208.86 ***	141.12 ***
	N umber of observations	390	390	390	390
	N umber of countries			33	33	33	33
	N otes: Absolute value of z statistics in parentheses
	(* ) significant at 10%; (**) significant at 5%; (***) significant at 1%.
		Foreign investors, notably global investors, are reported to have shown increasingly
	growing interest in local currency bond markets of emerging economies in very recent years

Table 9 :

 9 Extensions: Foreign investor appetite

					Foreign currency	Indexed	Short-term	All risks combined
	Log(GDP)			-0.009 ***	-0.008 ***	0.002	-0.028 ***
					(3,97)	(2,56)	(0,56)	(3,14)
	Domestic savings to GDP	-0.080 *	0.033	-0.097 *	-0.139
					(1,72)	(0,47)	(1,71)	(0,89)
	Inflation			0.073 ***	0.070 **	0.097 ***	0.231 **
					(3,09)	(2,09)	(3,20)	(2,38)
	Fiscal balance to GDP		-0.178 **	-0.077	-0.236 **	-0.407 *
					(2,44)	(0,69)	(2,40)	(1,72)
	Foreign investor appetite	-0.035 *	-0.052 *	-0.023 **	0.001
					(1,82)	(1,71)	(1,80)	(1,02)
	Constant			1.188 ***	1.027 ***	0.358 **	0.888 ***
					(3,13)	(4,14)	(2,29)	(6,27)
	Log likelihood			-196.58	-255.18	-216.57	-154.84
	Wald test			83.61 ***	121.38 ***	170.18 ***	235.47 ***
	σ	2 υ			1.378 ***	0.874 ***	0.620 ***	0.301 ***
	σ	2 ε			0.563 ***	0.478 ***	0.333 ***	0.267 ***
	ρ				0.857 ***	0.770 ***	0.776 ***	0.559 ***
	Likelihood ratio test σ	2	υ = 0	256.81 ***	246.24 ***	213.31 ***	143.43 ***
	N umber of observations	410	410	410	410
	N u m b e r o f c o u n t r i e s			3 2	3 2	3 2	3 2

N otes: Absolute value of z statistics in parentheses (* ) significant at 10%; (**) significant at 5%; (***) significant at 1%. Shares M i of risky domestic debt in total domestic debt

Table 10 :

 10 Extensions: Exchange rate regime

					Foreign currency	Indexed	Short-term	All risks combined
	Log(GDP)			-0.009 ***	-0.008 **	-0.005	-0.020 ***
					(4,07)	(2,64)	(1,27)	(2,60)
	Domestic savings to GDP	-0.066	0.001	-0.168 **	-0.025
					(1,32)	(0,02)	(2,37)	(0,18)
	Inflation			0.045 ***	0.031 *	0.094 ***	0.295 ***
					(3,04)	(1,75)	(3,37)	(4,07)
	Fiscal balance to GDP		-0.154 **	-0.078	-0.297 ***	-0.375 **
					(2,27)	(0,80)	(2,68)	(1,98)
	Exchange rate regime			-0.006 *	-0.005	-0.013 *	-0.025 *
					(1,65)	(0,87)	(1,71)	(1,72)
	Constant			1.848 ***	0.784 ***	0.496 ***	0.861 ***
					(5,46)	(3,68)	(4,10)	(7,75)
	Log likelihood			-202.50 ***	-259.51 ***	-222.98 ***	-158.43 ***
	Wald test			85.4 ***	95.74 ***	202.8 ***	243.72 ***
	σ	2 υ			1.389 ***	0.890 ***	0.562 ***	0.353 ***
	σ	2 ε			0.563 ***	0.473 ***	0.331 ***	0.267 ***
	ρ				0.859	0.780	0.742	0.636
	Likelihood ratio test σ	2	υ = 0	305.87 ***	282.60 ***	212.55 ***	150.49 ***
	N umber of observations	410	410	410	410
	N umber of countries			32	32	32	32

N otes: Absolute value of z statistics in parentheses (* ) significant at 10%; (**) significant at 5%; (***) significant at 1%.

Table 11 -

 11 Extensions: Capital account openness

					Foreign currency	Indexed	Short-term	All risks combined
	Log(GDP)			-0.010 ***	-0.007 **	-0.008 *	-0.037 ***
					(5,17)	(2,18)	(1,71)	(2,96)
	Domestic savings to GDP	-0.097 **	-0.018	0.101	-0.021
					(2,25)	(0,26)	(1,27)	(0,09)
	Inflation			0.029 ***	0.035 *	0.068 ***	0.338 ***
					(3,24)	(1,73)	(2,66)	(3,63)
	Fiscal balance to GDP		-0.011	0.008	-0.438 ***	-1.336 ***
					(0,30)	(0,08)	(2,86)	(3,87)
	Capital account openess	0.016	0.066 ***	0.023 *	0.028
					(0,01)	(2,67)	(1,75)	(0,51)
	Constant			3.130	0.184	-0.255	1.122 ***
					(0,04)	(0,41)	(1,30)	(5,41)
	Log likelihood			-96.06 ***	-167.37 ***	-106.43 ***	-62.73 ***
	Wald test			100.81 ***	78.68 ***	243.58 ***	277.5 ***
	σ	2 υ			2.189 ***	0.968 ***	0.606 ***	0.277 ***
	σ	2 ε			0.379 ***	0.419 ***	0.257 ***	0.211 ***
	ρ				0.971	0.842	0.848	0.632
	Likelihood ratio test σ	2	υ = 0	247.43 ***	184.64 ***	178.84 ***	115.76 ***
	N umber of observations	410	410	410	410
	N u m b e r o f c o u n t r i e s			3 2	3 2	3 2	3 2

N otes: Absolute value of z statistics in parentheses (* ) significant at 10%; (**) significant at 5%; (***) significant at 1%.

Illustrative of the rising interest they create, investors worldwide have allocated a growing share of their assets in emerging market securities, notably local currency bonds (JP Morgan,

2005).

This study finds that monetary credibility, as measured by inflation and the imposition of capital controls, helps explain "domestic original sin".

In carrying out a survey of emerging market central banks, the BIS notes that comparatively few central banks regularly compute summary measures of these characteristics, although the underlying data are often publicly available.

Admittedly, our data -like those in most papers in the literature -do not include private bond issues. However, the resulting bias is unlikely to be large for most emerging economies, as debt security issuance by financial institutions and corporations has been traditionally limited in emerging markets, with the important exception of some of the emerging Asian economies.

For instance, pension funds have an interest in debt securities carrying low default risk and denominated in domestic currency[START_REF] Borensztein | Sovereign Debt Structure for Crisis Prevention[END_REF].

Exchange rate rigidity is also found to be positively correlated with domestic original sin, although the relationship is not robust to the inclusion of capital controls.[START_REF] Falcetti | Public Debt Indexation and Denomination with an Independent Central Bank[END_REF] attribute the rise in the share of fixed rate bonds and loans in central government debt of twenty OECD countries from the mid-1980s to increased central bank independence, in turn reflecting growing investor confidence in long-run price stability.

 9 In their theoretical set-up, the maximum debt maturity consistent with a credible pledge to price stability decreases with the level of debt.

This index published by The Heritage Foundation comprises, among other variables, the overall amount of tax revenues levied by government.

India

Long-term debt securities (GO Is), of which with a floating interest rate;


Alice Boudet

Olivier Henrotte

Ndrina Limani

Fatima El Orf

Frédéric Oswald

Bruno Jousselme

Renaud Cornut

Secm

SECM and AFM Characterizations for the Study of ORR Catalysts Electrocatalytic Activity at Agglomerate scale

 [START_REF] Limani | Local Probe Investigation of Electrocatalytic Activity[END_REF]. Thanks to its ability to study a very low amount of material with almost no additives such as a polymeric binder (Nafion), the intrinsic activity of catalysts gets accessible and characterizations can be performed at agglomerate scale. Herein, we propose to combine for the first time SECM with atomic force microscopy (AFM) characterizations to study the link between the catalytic activity and the agglomeration state of non-PGM (platinum group metal) ORR catalysts. SECM is performed with the redox competition mode in acidic media, following the protocol developed recently in our group [START_REF] Henrotte | Steady State Electrocatalytic Activity Evaluation with the Redox Competition Mode of Scanning Electrochemical Microscopy: A Gold Probe and a Boron Doped Diamond Substrate[END_REF]. AFM images are then used to determine the agglomeration state in the deposits of catalysts.

Different PGM-free ORR catalysts from the European project PEGASUS were investigated at different loadings [START_REF] Boudet | Unraveling the Link between Catalytic Activity and Agglomeration State with SECM and AFM[END_REF]. Differences in term of dispersion, stability of the inks and adherence on the substrate were observed, which highlights the importance of adapting the ink formulation to each ink. The agglomeration states of the deposits measured by AFM enabled to explain the differences in activity measured by SECM. The performances of the catalysts were compared and the contributions of the intrinsic activity and the agglomeration state were separated. These results illustrate that our approach is suitable for the characterization of catalysts at agglomerate scale, with various applications from the benchmarking of new catalysts to the optimization of an ink formulation.

SECM and AFM Characterizations for the Study of ORR Catalysts Electrocatalytic Activity at Agglomerate scale

  Alice Boudet, a Olivier Henrotte, a Ndrina Limani, a Fatima El Orf, a Frédéric Oswald, a Bruno Jousselme, a and Renaud Cornut a

	Current Trends in Electrochemistry
	6 -9 July 2021
	Paris, France
	a Université Paris-Saclay, CEA, CNRS, NIMBE, LICSEN, 91191, Gif-sur-Yvette, France
	alice.boudet@cea.fr
	Scanning electrochemical microscopy (SECM) is at the forefront of a new generation of
	tools enabling to investigate the local properties of catalysts


Théo Zimmermann

Jean-Rémy Falleri
email: falleri@labri.fr

A grounded theory of Community Package Maintenance Organizations-Registered Report

Keywords: Grounded theory, Package ecosystem, Software maintenance, Collaborative maintenance, Open source software, Software libraries

a) Context: In many programming language ecosystems, developers rely more and more on external open source dependencies, made available through package managers. Key ecosystem packages that go unmaintained create a health risk for the projects that depend on them and for the ecosystem as a whole. Therefore, community initiatives can emerge to alleviate the problem by adopting packages in need of maintenance.

b) Objective:

The goal of our study is to explore such community initiatives, that we will designate from now on as Community Package Maintenance Organizations (CPMOs) and to build a theory of how and why they emerge, how they function and their impact on the surrounding ecosystems. c) Method: To achieve this, we plan on using a qualitative methodology called Grounded Theory. We have begun applying this methodology, by relying on "extant" documents originating from several CPMOs. We present our preliminary results and the research questions that have emerged. We plan to answer these questions by collecting appropriate data (theoretical sampling), in particular by contacting CPMO participants and questioning them by e-mails, questionnaires or semi-structured interviews. d) Impact: Our theory should inform developers willing to launch a CPMO in their own ecosystem and help current CPMO participants to better understand the state of the practice and what they could do better.

I. INTRODUCTION

The state of the practice in many programming language ecosystems is for developers to heavily rely on third-party open source packages [START_REF] Klug | Open Source Is A-Changin': How Qualitative Research Can Help Us Adapt[END_REF]. For instance, Decan et al. found that a majority of packages depend on other packages in all seven ecosystems they studied [START_REF] Decan | An empirical comparison of dependency network evolution in seven software packaging ecosystems[END_REF]. This is made possible in large part by the advent of package managers, that have allowed developers to easily add third-party dependencies, but also to easily share reusable code with others. This large dependency of many software projects on graciously provided open source packages can lead to a risk that some of them will be abandoned and thus stop being maintained [START_REF] Avelino | On the abandonment and survival of open source projects: An empirical investigation[END_REF]. This is especially true for packages with a low truck-factor [START_REF] Avelino | A novel approach for estimating Truck Factors[END_REF], [START_REF] Avelino | What is the Truck Factor of popular GitHub applications? A first assessment[END_REF]. Reliance on an unmaintained software package may then create problems such as the inability to migrate to a newer version of the programming language or toolchain and reported bugs not being fixed. It can even lead to security issues as it was the case for the infamous event-stream npm package 1 .

When an open source package becomes unmaintained, it is possible for its users to take measures to keep maintaining it, such as pushing fixes to a fork [START_REF] Zhou | How Has Forking Changed in the Last 20 Years? A Study of Hard Forks on GitHub[END_REF], or vendoring the package in the project that depends on it, and pushing fixes to this copy [START_REF] Zimmermann | A first look at an emerging model of community organizations for the long-term maintenance of ecosystems' packages[END_REF]. However, it is only an individual and uncoordinated measure that will typically lead to inefficiencies, as soon as several users need to do the same [START_REF] Zhou | What the fork: a study of inefficient and efficient forking practices in social coding[END_REF].

To avoid this issue, ecosystem participants may decide to launch community initiatives to alleviate the problem of key packages being left unmaintained. During his PhD, the first author has observed an emerging model of "community organizations for the long-term maintenance of ecosystems' packages" and he has produced an informal analysis mostly based on the Elm Community example [START_REF] Zimmermann | A first look at an emerging model of community organizations for the long-term maintenance of ecosystems' packages[END_REF], [START_REF] Zimmermann | Challenges in the collaborative evolution of a proof language and its ecosystem[END_REF]. His key observations were that the existence of these organizations could: facilitate the creation of community forks for unmaintained packages; provide an exit strategy for authors of popular packages no longer willing to maintain them.

The goal of the present study is to refine or revise these initial findings by looking more in depth at several examples of these Community Package Maintenance Organizations (CP-MOs) and build an actual theory of how and why they emerge, what are their objectives and how they function.

To the best of our knowledge, this theory will be the first formal study of the CPMO model, which has not been studied by other researchers so far, and which also constitutes the first known collective model to alleviate the problem of unmaintained packages in open source ecosystems.

By providing a formal description abstracting over the many initiatives that have emerged independently from each other, our theory will highlight key components and processes of CPMOs, but also what works well and what does not. This should allow both practioners from ecosystems without a CPMO to launch such an initiative, by providing a clear model and justification for the associated processes, but also current CPMO participants to reflect on their practice and make them evolve. As a matter of fact, the first author did launch a CPMO for the Coq ecosystem based on his initial observations and, even if it has already been quite successful, it should also benefit from a better understanding of CPMOs in other ecosystems.

We plan on building this theory through a qualitative study following the principles of Grounded Theory (GT). GT is appropriate for this setting because it provides us a methodology for analyzing both existing data that we retrieve ("extant documents") and elicited data (such as through interviews with CPMO participants).

This study will be of a purely qualitative nature and the theory that we build will not be used to derive "predictions" that could be "tested". It is beyond the scope of this study to make and test such predictions. However, the generated theory could inform future research that will make and test predictions on specific aspects of CPMOs, by means of quantitative methods.

In the next section, we present the GT methodology and how we have chosen to apply it to conduct our study. The rest of the paper then presents our preliminary findings based on extant documents only, the research questions that have emerged and how we plan to collect more data to tackle them.

II. METHODOLOGY

Grounded Theory (GT) is a qualitative methodology for generating theories grounded in data. Several variations of this methodology exist. We base our work on the constructivist version of Charmaz [START_REF] Charmaz | Constructing Grounded Theory[END_REF], complemented by the perspectives brought by Stol et al. on GT applied to Software Engineering [START_REF] Stol | Grounded Theory in Software Engineering Research: A Critical Review and Guidelines[END_REF] and of Muller and Kogan on GT applied to Human-Computer Interactions and Computer-Supported Cooperative Work [START_REF] Muller | Grounded Theory Method in Human-Computer Interaction and Computer-Supported Cooperative Work[END_REF]. We also inspire from the SAGE Handbook chapter by Wiener about team work in GT [START_REF] Wiener | Making Teams Work in Conducting Grounded Theory[END_REF] and on the recommendations of Ralph et al. for contextual positioning of extant documents in GT [START_REF] Ralph | Contextual Positioning: Using Documents as Extant Data in Grounded Theory Research[END_REF].

One of the core characteristics of GT is that it is an incremental method. Analysis and theory building (using coding and memoing) start as soon as the researchers have gathered some initial data and the resulting theory is then refined by looking at additional data that will help address unanswered questions. Data are not sampled for representativity (statistical sampling) but for what they may bring to the theory under construction (theoretical sampling). Data collection only stops when the constructed theory is solid enough to fit new collected data (theoretical saturation).

A. Defining the scope of our study

In this paper, we explore a model of community organizations centering on package maintenance (CPMOs) that we have observed in several ecosystems. However, because this model is emergent, we have to define the limits of what we want to study. First, we study community initiatives that are rooted in an application-specific package ecosystem. Therefore, we exclude both general initiatives targeted at improving sustainability of open source projects and general-purpose package ecosystems (such as Arch Linux, Debian, Homebrew or Nixpkgs). We make this choice because application-specific package ecosystems are generally associated to an "upstream" project, that may become in need of maintenance, and this leaves the possibility for a CPMO to "adopt" the project. Second, we exclude organizations that do package maintenance without clearly communicating on their objectives nor their processes. Third, we exclude organizations that already encompass all community packages of an ecosystem (as we have sometimes observed in small ecosystems). If packages are already gathered like this, this does not leave any possibility to "adopt" an unmaintained package.

B. Initial data gathering

Our plan for this study has been to start with the data that were the most accessible, that is the documentation provided by the CPMOs we identified, and to defer contacting CPMO participants to a later theoretical sampling phase.

The reason for adopting this strategy is both ethical and practical. We know that open source software developers are over-sollicited by empirical software engineering researchers [START_REF] Baltes | Worse Than Spam: Issues In Sampling Software Developers[END_REF]. Therefore, contacting them too early would be both unethical (because we would be wasting their time with questions to which we could have found an answer by ourselves) and inefficient (because reaching out more personally to specific users is more likely to elicit answers and we should be able to ask questions which we are missing data to answer).

Our initial list of CPMOs to study comes from the thesis of the initial author [START_REF] Zimmermann | A first look at an emerging model of community organizations for the long-term maintenance of ecosystems' packages[END_REF], [START_REF] Zimmermann | Challenges in the collaborative evolution of a proof language and its ecosystem[END_REF]. The list was obtained by a systematic search of GitHub organizations using GitHub advanced search feature, starting from 75 keywords like "collective", "maintain", "participate" but also "library", "module" or "package", and followed by a series of filters regarding number of repositories, popularity, and presence of repositories predating the organization (and that were thus transferred to it). These filters were intended to keep the resulting list to a size that would be reasonable to explore manually. This list was then manually browsed for organizations fitting the scope described above, excluding in particular many organizations that did not provide sufficient information on their purpose.

To make sure we did not miss any important or newer CPMO, we completed this initial list by doing a manual GitHub search for repositories and organizations with the keywords "package maintenance" and "package community" and looking at the first 10 pages of results for each query. This did bring up additional organizations fitting the scope of our study, confirming that the list previously established was incomplete. Even if we still cannot claim to have identified all CPMOs, we have already obtained a list longer than what we will be able to study in depth, so we will have to select a subset to focus on.

To start with, we decided to code documents that would present the CPMO purposes and processes. We first explored the following four CPMO documents: README from the manifesto repository of Elm Community, README from the discussions repository of Dlang-community, README from the package-maintenance repository of Node.js Package Maintenance Team (PMT), governance document from the plumbing repository of Vox Pupuli. We ignored on purpose the coq-community manifesto (which has been initially drafted by the first author during his PhD work) and the ocaml-community meta repository README (which has been directly influenced by coqcommunity's). That being said, we do use the experience of the first author as a comparison point in the analysis process (when writing memos in particular) and we acknowledge it wherever it influences the theory under construction.

C. Coding and memoing process

Following Charmaz's presentation of GT [START_REF] Charmaz | Constructing Grounded Theory[END_REF], we have coded these documents in two phases. During the initial lineby-line coding phase, we devise codes that precisely represent the content of the document. During the follow-up focused coding phase, we abstract our initial codes and look for common patterns through constant comparison between codes and codes, codes and data, and data and data. The focused codes that seem to be the most important become the basis to form our categories. Whenever we observe a recurring pattern or gain insight throughout the coding process, we write memos to sketch the precise definition and characteristics of our categories.

GT is mainly described as a research methodology employed by individual researchers (e.g., in sociology). Guidance on how to employ it as a team of researchers is limited and it is also the role of the researchers to decide how to proceed. We decided to use a GitHub repository to collaborate, with issues being used for writing memos, and documents with codes being committed into the repository.

Data that are collected but not created for the purpose of the research are called "extant documents" [START_REF] Charmaz | Constructing Grounded Theory[END_REF]. Extant documents are harder to code because they do not only contain data that are relevant to our research (these data are typically burried under irrelevant ecosystem-specific technical considerations for instance). To alleviate this difficulty, we decided to code documents separately and compare our codes.

While such double-coding is generally conducted to obtain more "objective" results in empirical software engineering research (by measuring inter-rater reliability), it is typically not required from a constructivist perspective (where it is expected that different researchers will have different interpretations). However, this was still very useful to us because the differences in our codes raised interesting discussions during our meetings, and frequently led to memo-writing. This was especially true when comparing focused codes, so we quickly limited (after two documents) the double-coding and discussion to the focused coding phase only, or we adopted a strategy where one researcher would do the initial coding and another would do the focused coding (of the same document) then the two would discuss the focused codes. This strategy aligns with the observations of Wiener [START_REF] Wiener | Making Teams Work in Conducting Grounded Theory[END_REF] that team meetings can be used to code as a group and may spark new ideas leading to memos that will be written by individual researchers.

When coding extant documents, it is important to situate them with respect to their context, audience, etc. Ralph et al. call this "contextual positioning" and provide a list of questions to ask about the document [START_REF] Ralph | Contextual Positioning: Using Documents as Extant Data in Grounded Theory Research[END_REF]. In order to answer them, in particular with respect to community documents that are not attributed to a specific author but were committed to a GitHub repository, we rely on the git history to better understand who contributed to writing what parts and when. This is sometimes helpful to explain how different and apparently contradictory perspectives coexist in the same document, or how CPMO processes evolve.

D. Theoretical sampling

After our initial data gathering and analysis, we have already started theoretical sampling to answer questions that have emerged. We were especially interested in the package "adoption" process, so we have started coding adoption discussions in the context of one specific CPMO (Dlang-community) but we plan to expand this to other CPMOs.

The adoption process was not really discussed in Node.js PMT's document and while looking for adoption discussions, we figured out that it was still undecided if this organization (or Working Group as they sometimes describe themselves) would ever adopt packages. Currently, they are more focused on developing tooling and best practices, and helping projects outside the organization. While this initiative is also very interesting and would be worth studying, we have to set limits to what we include in our study, so we have decided to remove it from our study and reinspect our preliminary findings based on this decision.

Finally, when we reach the limits of what we can theorize from extant documents, we believe that we will need to contact CPMO participants. Contacting and interviewing participants is essential, not only to gain a deeper understanding of the studied processes, but also to get a reliability check [START_REF] Stol | Grounded Theory in Software Engineering Research: A Critical Review and Guidelines[END_REF] of our (intermediate) conclusions.

One strategy for contacting CPMO participants will be to e-mail them and ask them specific questions to clarify the data that we have found and analyzed. An example is asking why a package adoption did not happen even after it was discussed and approved, or if they can tell us under what circumstances the documented decision processes are deviated from.

When sending these e-mails, we will use the opportunity to ask about conducting an interview with them, but we will leave it open to have a purely written discussion for those who would not have time to allocate to a proper interview.

E. Interviewing process

During this study, we expect that we will conduct some semi-structured interviews. Given the incremental nature of GT, we plan to conduct interviews one by one, transcribe and code the interview, and reflect on the knowledge we gain from an interview before planning the next one. Therefore, the interview guide will evolve between each interview.

Whereas, as an open science committment we will publish all our codes for public documents, we will not be able to do the same for interview transcripts and codes. Indeed, we can expect participants to answer differently to our questions if we tell them that the interviews will not be made public. We plan to quote some interview participants in our paper, but we will seek consent from each quoted participant for the specific quotes, to make sure that they are comfortable making these quotes public (or if they want them sanitized and anonymized) and also that we interpret them correctly.

F. Expectations for the Registered Report

Registered Reports were initially invented to avoid HARKing (hypothesizing after the results are known). This issue is not really relevant for qualitative theory-generation studies. Nonetheless, preregistrations can still be useful in an open science perspective to state the plans and intents for a qualitative study. Revealing these will help future readers understand how the study was conducted and the theory was built, even though, in a GT setting, it is expected that there will be variations from the initial plan.

Furthermore, early reviewer feedback, both on the methodology and the theory under construction, is essential to us before we actually start contacting participants and conduct interviews. Indeed, as we stated before, the time of open source maintainers (and thus CPMO participants) is precious and there is only so much time that they can allocate to researchers interviewing or surveying them. Therefore, it is important that we are as prepared as possible before we begin this step in our study.

III. PRELIMINARY RESULTS

In this section, we describe our preliminary categories, obtained after our initial and focused coding phases performed on the manifesto documents of the subjects we gathered.

A. Motivations for CPMOs

Avoiding ending-up with lagging useful packages is the main driver for the creation of CPMOs. Both the Elm Community and the Dlang-community manifestos express this idea (in words that come from the initial version of the documents by the CPMO founders):

"It sometimes happens that packages which are widely used need a bit of maintenance-for instance, to accommodate changes in Elm, or for other reasons. Normally, package authors will deal with that themselves, of course, possibly with the help of pull requests from interested community members etc. However, sometimes package authors may not be available, for one reason or another, and other work can be blocked until the maintenance is performed." "This organization was formed by annoyance of needing to fork popular repositories to get fixes merged. [...] However, small bug fixes don't need to wait in the queue for months, and in case the author is completely gone, the DLang community has one upstream repository instead of ten different forks containing the same fix."

The Vox Pupuli webpage also expresses this idea:

"One of the benefits we hope to achieve is that by a shared ownership of modules we no longer end up in situations where the original maintainer has moved on and a forest of disparate forks try to fill the void."

B. Package adoption

To avoid ending-up with lagging packages, CPMOs perform package adoptions, by transferring or forking the project of interest inside a CPMO-owned repository. However, we have seldomly encountered clear guidelines on how the packages to adopt are selected. The more informative description is perhaps the one found in Dlang-community, as follows.

"These question are intended to give a rough feeling on what packages might be considered for adoption. When in doubt, please open an issue! Popularity Q: Is there enough interest from the D community, i.e. is it "worth maintaining" Competition Q: Is there a similar library with active development out there? Maintainer/sponsor Q: Is at least one of the DLang community member competent for the domain covered by the project? If not, is there anyone willing to join?"

Here we can notice that the dimensions are popularity, competition and having a volunteer maintainer. Furthermore, there is an explicit will to ensure that adoption is to be discussed prior to any decision.

"Please don't create new packages without consulting other dlang-community members."

In the Elm Community CPMO, the guidelines are more fuzzy. It has a mention in the framing of the manifesto document:

"packages that are widely used"

Which indicates that popularity could be a criterion similarly to Dlang-community. Additionally, they state: "If you think there is a package that should be adopted here, feel free to open an issue in this repository. (And, to repeat, this is not to discourage you from adopting a package yourself, if you want to take that on)."

Which does seem very inclusive as every adoption proposal can be subjected to discussion.

No criteria for package adoption are explicitly mentioned in the Vox Pupuli CPMO (they only provide technical adoption guidelines). However, Vox Pupuli documentation hints that donations are a way to adopt packages, which could bear some similarity with the vision of Dlang-community (is there a volunteer maintainer out there?).

C. Maintenance objectives of CPMOs

The maintenance objectives of CPMOs with respect to the adopted packages are generally not clearly defined. A theoretical sensitizing concept here is the staged model of the software lifecycle by Rajlich and Bennett [START_REF] Rajlich | A staged model for the software life cycle[END_REF]. Do CPMO generally plan to do servicing only or do they also accept projects that are actively evolving or even in their initial development phase? The Elm Community manifesto is the most explicit on this aspect, but it is also self-contradicting as shown by these two excerpts:

"For the most part, we don't expect to do innovative work on packages here. That is, to the extent that innovative new features can be added to a package, that should mostly be done in people's individual accounts. What we'll do here is mostly maintenance." "Lead the direction of a repository. As a champion, you will need to make calls on API design. Don't let packages come to elm-community to die."

This apparent contradiction can be explained by the latter paragraph having been added by someone else than the original author, who probably had slightly differing views.

D. Decision protocols

CPMO processes require frequent decision making. Examples of important decisions to make are whether to "adopt" a package or whether to integrate a pull request.

CPMOs often strive to involve the community in the decisions as much as possible. On the other hand, they also want to be able to make decisions in a reasonable time-frame. One typical trade-off is the use of a lazy consensus protocol, as in Vox Pupuli. As written in the Vox Pupuli governance document:

"Lazy consensus is a very important concept within the project. It is this process that allows a large group of people to efficiently reach consensus, as someone with no objections to a proposal need not spend time stating their position, and others need not spend time reading such statements." By exploring the file history for this document, we have found out that this text comes verbatim from a template for open source project governance provided by OSS Watch [START_REF] Gardler | Meritocratic governance model[END_REF].

From our preliminary observation, it is not clear at all that the recommendations of this consensus mechanism are often followed, or for which type of decision they are applied.

Dlang-community does not explicitly provide a lazy consensus protocol, but does rather provide some criteria for when it is not required:

"When can I (self)-pull a PR?" Finally, Elm Community is more explicit on how individual hosted projects are managed: all projects have a primary maintainer that can take all decisions with respect to its projects. However, to ensure the liveliness of the maintenance, they state that unresponsive maintainers can be overriden (and even removed).

"if there's something that really needs to get merged, and the maintainer has taken more than 7 days to respond, we can merge things without their involvement."

"Unresponsive champions will be emailed. Lack of response will mean a new maintainer will be assigned to that repo." Even if it is not documented as clearly, a question is whether this principal maintainer model happens to be prevalent in CPMOs in practice. This may turn out to be true at least for projects whose original author is still active, as hinted by Dlang-community:

"projects are still driven by their original authors if they have the time"

E. CPMO membership

CPMOs generally encourage wide participation.

"How do I become a member of the DLang community? First of all, by reading this you most likely are already." "Contributors How to become one: Submit a pull request to a Vox Pupuli project" However, they also often have a trust-building process to get write permissions:

"You are already a well-known member of the D community, then simply ping us for merge rights. Otherwise, start contributing to one of the projects and earn your trust." "Collaborators are contributors who have shown wide dedication to the Vox Pupuli project in general or deep dedication to one project in particular, and the ability to work well with contributors and other users." Interestingly, while this last quote also originally comes from the governance template mentioned above, it was adapted to the specifics of a CPMO. Indeed, contrary to usual open source projects, involvement in a CPMO has several dimensions: it can be wide dedication to the CPMO, by helping maintain all packages or common tools, or it can be deep dedication to one or a selection of packages hosted by the CPMO.

Finally, our preliminary observations seem to indicate that the trust-building process can often be side-stepped when recruiting a new member to maintain a package being adopted (as shown by these quotes from Dlang-community, Vox Pupuli and Elm Community):

"If not, is there anyone willing to join?" "It is also common to give collaborator status to an individual who donates code to the project by migrating a repository to the github namespace" "this is not to discourage you from adopting a package yourself, if you want to take that on"

IV. NEXT STEPS

In this section, we describe our planned next iterations of data collection and coding, relatively to the categories described previously.

Motivations of CPMOs: The manifestos we coded are relatively scarce about the rationales and motivations that led to the creation of CPMOs. Therefore, we plan to collect more data about the creation context of CPMOs. For several subjects, we gathered some forum threads where the initial discussion regarding the CPMO creation was conducted. We plan to code these documents.

When we cannot find data on the creation context or if we need additional information, we plan to interview CPMO founders. In the case of Elm Community, we already have the recording of the informal interview of the founder conducted by the first author during his PhD. We will transcribe and code this interview.

Adoption of packages: As we previously described, CP-MOs are rarely explicit about the criteria for package adoption. Even for a CPMO that provides them, these criteria are very subjective. We feel like we do not have enough data to construct a comprehensive theory about this topic. During our inspection of the CPMO repositories, we found out that several CPMOs discuss package adoptions using GitHub issues or pull requests (or mailing lists). We think that coding these data is a great way to better analyze how the decision on a package adoption is done in practice. We already started coding five such issues for the Dlang-community CPMO, and we plan to conduct this coding effort for the other CPMOs where such data are available. When the data are not available, or when we need additional information, we will ask questions regarding the adoption criteria to current CPMO participants.

Maintenance objectives of CPMOs: We uncover contradictory visions inside CPMO manifestos regarding the kind of maintenance expected in adopted packages. We want to examine data closer to the projects to build a better understanding. Therefore, we plan to code commit logs of several adopted projects inside each CPMO. Because commit messages are usually quite explicit about the kind of maintenance activity, we think that this should help understand what kind of maintenance activities are undertaken in CPMOs, and if they vary across hosted projects. Contrary to what is commonly seen in research coding commit messages, we will not do this with quantitative / statistical objectives, but only to assess the diversity of undertaken maintenance activities.

Decision protocols: The studied CPMOs have defined two kinds of decision protocols: lazy consensus or principal maintainer lock. However, we have not yet examined how these protocols are used in practice, and for which reasons. To build a better understanding, we plan to code issues and pull requests of adopted projects' repositories as well as issues and pull requests of central documentation or coordination CPMO repositories. Additionally, some CPMOs have public discussion channels that are also used to make decisions. We plan to also code a subset of these discussions.

CPMO membership: Besides an expressed intent to favor wide participation, CPMOs generally do not precisely document the actual recruitment and trust building process. We will try to better understand how this happens in practice based on public data, but this will very likely need to be complemented by interviewing both recently recruited participants and CPMO administrators. We will also try to analyze the variety of (formal or informal) roles taken by CPMO participants, and to categorize them along the dimensions of involvement defined above.

TABLE I LIST

 I OF POTENTIAL CPMOS TO STUDY.

	CPMO name	GitHub name	Origin
	Dlang-community	dlang-community	Initial list
	Elm Community	elm-community	Initial list
	Flutter Community	fluttercommunity	Manual search
	LM Commons	LM-Commons	Manual search
	Meteor Community	Meteor-Community-Packages Manual search
	Node.js PMT	pkgjs	Manual search
	React-native-community	react-native-community	Initial list
	ReasonML-community	reasonml-community	Initial list
	Sous Chefs	sous-chefs	Initial list
	Vox Pupuli	voxpupuli	Initial list

https://blog.logrocket.com/the-latest-npm-breach-or-is-it-a427617a4185/