Sovereign Debt Crises in Latin America: A Market Pressure Approach

Boonman, Tjeerd M.; Jacobs, Jan; Kuper, Gerard H.

doi:10.1080/1540496x.2015.1080558

Cited by 4 publications

(8 citation statements)

References 27 publications

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“…Others use the signal extraction method to evaluate the performance of individual indicators, both in the form of noise to signal ratio, usefulness ratio, and by maximizing Youden's J-Statistic (Babecky et al, 2014;Fuertes and Kalotychou, 2007). The Bayesian Model Averaging (BMA) (Kamra, 2013), Principal Component Analysis (PCA) (Kamra, 2013), Event Analysis (Balteanu and Erce, 2014), K-means clustering (Fuertes and Kalotychou, 2007), machine learning algorithm such as Artificial Neural Networks (ANNs) (Anwar and Ali, 2018), market pressure approach (Boonman et al, 2015), binary recursive tree analysis (Schimmelpfennig, et.al, 2003), and extreme learning machine technology (Ping et al, 2019) are also used in the literature. (Dawood, et.al, 2017;Jedidi, 2013); and (viii) a sudden stop of the capital outflow which arised from the political issues (Basu, 1993;Warjiyo, 2016).…”

Section: Literature Reviewmentioning

confidence: 99%

Early Warning System for Government Debt Crisis in Developing Countries

Wijayanti

Rachmanira

2020

Journal of Central Banking Theory and Practice

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This study develops an early warning signal (EWS) of government debt crisis using a panel data consisting of 43 developing countries over the period of 1960 to 2017. It employs two different methods: the noise to signal ratio to capture the signaling power of individual indicators; and the binomial logistic regression to construct a more general model. The binomial logistic regression offers a better predictive power relative to the noise to signal ratio. The binomial logistic regression can predict 61.5% of the government debt crisis 2 years in advance. An increase in inflation, government and private debt exposures, external debt to exports, ratio of short-term external debt to foreign exchange reserves, and the ratio of external interest payments to gross national income can signal an upcoming debt crisis. Similarly, a continuous decline in the gross domestic product (GDP) and government consumption also increase the likelihood of government debt crisis.

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Section: Literature Reviewmentioning

confidence: 99%

Early Warning System for Government Debt Crisis in Developing Countries

Wijayanti

Rachmanira

2020

Journal of Central Banking Theory and Practice

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“…The existing literature on sovereign debt crisis prediction has focused mainly on emerging countries [7,10,11,[24][25][26][27][28]. For their part, some studies have addressed predictions of the sovereign debt crisis in emerging and developing countries [3,29,30].…”

Section: Sovereign Debt Crises Predictionmentioning

confidence: 99%

“…Regarding the methods used, a considerable number of researchers have applied statistical methods to predict the sovereign debt crisis, highlighting the logit model [5,10,[24][25][26]29,32]. On the other hand, the authors [3,7] develop regression models to forecast the sovereign debt crisis. For their part, [11] applies a non-parametric method based on artificial neural networks (ANN).…”

Section: Sovereign Debt Crises Predictionmentioning

confidence: 99%

“…For the trained and trained CART, they will try to mimic the level of residues thrown by the model in the training step. The objective function is optimized in step (t + 1) as defined in Equation (7).…”

Section: Extreme Gradient Boosting (Xgboost)mentioning

confidence: 99%

“…Recently, various so-called global models have also appeared that have used samples of economies from different regions of the world for their construction. Almost all of these global models have been built to predict situations in emerging economies, including some advanced economies [7].…”

Section: Introductionmentioning

confidence: 99%

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Sovereign Debt and Currency Crises Prediction Models Using Machine Learning Techniques

et al. 2021

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Sovereign debt and currencies play an increasingly influential role in the development of any country, given the need to obtain financing and establish international relations. A recurring theme in the literature on financial crises has been the prediction of sovereign debt and currency crises due to their extreme importance in international economic activity. Nevertheless, the limitations of the existing models are related to accuracy and the literature calls for more investigation on the subject and lacks geographic diversity in the samples used. This article presents new models for the prediction of sovereign debt and currency crises, using various computational techniques, which increase their precision. Also, these models present experiences with a wide global sample of the main geographical world zones, such as Africa and the Middle East, Latin America, Asia, Europe, and globally. Our models demonstrate the superiority of computational techniques concerning statistics in terms of the level of precision, which are the best methods for the sovereign debt crisis: fuzzy decision trees, AdaBoost, extreme gradient boosting, and deep learning neural decision trees, and for forecasting the currency crisis: deep learning neural decision trees, extreme gradient boosting, random forests, and deep belief network. Our research has a large and potentially significant impact on the macroeconomic policy adequacy of the countries against the risks arising from financial crises and provides instruments that make it possible to improve the balance in the finance of the countries.

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Public Debt Composition, Debt Policy Rules and Growth in Selected SADC Countries

Makoto¹,

Mumvuma²,

Kadenge³

2020

JBSEE

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Purpose: This study examined the relative effect of debt composition and debt reduction policy rule on economic growth in selected SADC countries which are Mauritius, Tanzania and Zimbabwe. Design/Methodology/Approach The Markov-switching method was used to estimate the debt growth model for the period 1990Q1-2016Q4 Findings:. The effects of debt proved to be regime dependent which supports the time effects of debt in all countries. High external debt relative to domestic debt had positive effect on growth in Tanzania which is a good reforming country and had negative effects in the case of Zimbabwe which is a debt distressed country. In comparison to Mauritius, a domestic debt dependent country, high domestic debt relative to external debt had negative impact on growth. The effects tend to rise with market pressure and government consumption behaviour. A negative real effect of debt reduction policy rule was confirmed for Zimbabwe and irrelevance in countries with less threat of debt distress. Implications/Originality/Value Therefore the study found support to the quantity-effect rather than type-effect of debt on growth. We recommended that countries should consider both time and quantity effects of debt in debt management; adopt explicit debt reduction rules which constrain fiscal behaviour and force policy commitment towards debt stabilization.

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Sovereign Debt Crises in Latin America: A Market Pressure Approach

Cited by 4 publications

References 27 publications

Early Warning System for Government Debt Crisis in Developing Countries

Early Warning System for Government Debt Crisis in Developing Countries

Sovereign Debt and Currency Crises Prediction Models Using Machine Learning Techniques

Public Debt Composition, Debt Policy Rules and Growth in Selected SADC Countries

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