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The twin deficit hypothesis suggests that budget deficits are crucial factors leading to current account deficits, and substantial empirical evidence documents a significant positive statistical correlation between budget and current account deficits. However, such evidence generally suffers from endogeneity problems due to reverse causality, thereby making it difficult to provide solid evidence to support policy implementation. We use extensive cross-national panel data from developed and developing countries and military expenditure as an instrumental variable to reexamine the impact of budget deficits on the current account and test the validity of the twin deficit hypothesis. Our results demonstrate that budget deficits lead to current account deficits in both developed and developing countries, supporting the twin deficit hypothesis. After considering various factors that may affect the exogeneity of military expenditures, approximating the instrumental variable as exogenous, and performing multiple robustness tests, the hypothesis still holds. This study provides solid evidence supporting the use of fiscal policies to deal with current account imbalances. [ABSTRACT FROM AUTHOR]

This study examines the impact of fiscal deficits on stock returns. The sample covers emerging markets for the period 2016Q1-2021Q4. The analysis results using panel vector autoregression (PVAR) and Granger causality tests indicate that fiscal deficits cause stock returns. These results are confirmed for countries with low and medium levels of financial development and for European countries. However, in countries with high levels of financial development such as the BRICS and ASEAN countries, no effect is observed. It is also found that this effect disappears during the COVID-19 pandemic. The results of the study question the strong form of the efficient market hypothesis (EMH). According to the EMH, stock prices should fully reflect all available information. However, the impact of fiscal deficits on stock returns in low- and middle-income countries and European countries suggests that market participants may not fully reflect this information, addressing the existence possibility of markets that are not efficient in the strong form.

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Since the early 1980s, there have been a number of principally empirical studies of the impact of government budget deficits on interest rates that have typically tested the hypothesis that larger deficits raise interest rates. However, in more recent years, this topic has received far less attention. Accordingly, this study seeks to "update" the findings of such studies and to do so for the dominant North American economies of Canada and the U.S. Furthermore, in the pursuit of further insights into interest rates, the present study also investigates an effectively heretofore overlooked variable that arguably also might influence interest rates, namely, economic freedom. Finally, given the increased upward trend of government debt (relative to GDP) in recent years in Canada and the U.S., this study investigates the interest rate impact of rising national debt-to-GDP ratios. For the 1995–2024 period (and also in one estimate for the 1985–2001 period), this exploratory study finds compelling evidence (1) that the real interest rate yield on 10-year Treasuries in Canada and the real interest rate yield on 10-year U.S. Treasury notes are increasing functions of the central government budget deficits in both Canada and the U.S., respectively, and (2) the real interest rate yields on 10-year Treasuries in Canada and 10-year U.S. Treasury notes are both decreasing functions of economic freedom in Canada and the U.S., respectively. On the other hand, regarding the impact of a higher national debt-to-GDP ratio on the real ten-year Treasury yield, there is only very mixed support for an impact, with support for its impact coming from the Canadian estimates but no support whatsoever coming from the U.S. estimates. [ABSTRACT FROM AUTHOR]

Objective The Burundian emergency obstetric and neonatal care (EmONC) programme, which was initiated in 2017 and supported by a specific policy, does not appear to reverse maternal and newborn mortality trends. Our study examined the capacity challenges facing participating EmONC facilities and developed alternative investment proposals to improve their readiness paying particular attention to EmONC professionals, physical infrastructure, and capital equipment.Design Cross-sectional study.Setting Burundian EmONC facilities (n=112).Participants We examined EmONC policy documents, consulted 12 maternal and newborn health experts and 23 stakeholders and policymakers, surveyed all EmONC facilities (n=112), and collected cost data from the Ministry of Health and local suppliers in Burundi. We developed three context-specific EmONC resource benchmark standards by facility type; the Burundian policy norms and the expert minimum and maximum suggested thresholds; and used these alternatives to estimate EmONC resource gaps. We forecasted three corresponding budget estimates needed to address prevailing deficits taking a government perspective for a 5-year EmONC investment strategy. Additionally, we explored relationships between EmONC professionals and selected measures of service delivery using bivariate analyses and graphically.Results The lowest EmONC resource benchmark revealed that 95% of basic EmONC and all comprehensive EmONC facilities lack corresponding sets of human resources and 90% of all facilities need additional physical infrastructure and capital equipment. Assessed against the highest benchmark which proposes the most progressive set of standards for the prevailing workloads, Burundi would require 162 more medical doctors, 1005 midwives and nurses, 132 delivery rooms, 191 delivery tables, 678 and 156 maternity and newborn care beds, and 395 incubators amounting to US$32.9 million additional budget for 5 years.Conclusion We demonstrated that Burundian EmONC facilities face enormous capacity challenges equivalent to US$32.9 million funding gap for 5 years; averagely approximating to 5.96% total health budget increase annually.

This paper revisits the discussion on the determinants of budget balances and investigates the change in their effect in the context of the COVID-19 crisis. The analysis uses data on 43 countries and a system generalised method of moments approach. The results show that the overall impact of the global pandemic has led to a disproportionate increase in the estimated effects of the macroeconomic determinants on the budget balance. We also find that more developed economies were able to implement higher stimulus packages for the same relative level of primary balance. We believe that one of the factors affecting this outcome is that more of their government debt is held in domestic currency.

Historically, the main behavior of fiscal policy is to distribute resources, income, and expenditures, which are interconnected functions of economic stability. Recently, the scope of public sector economics has expanded beyond budgetary components in parallel with the development of public finance. While the budget reached the economic division form of budget items based on program and performance theories, Budget monitoring, and financial risk management are currently challenging, particularly in the face of monetary policy uncertainty. Financial institutions are crucially concerned with the stability of public finance in low-income countries (LICs) as it contributes to improved investor confidence and fiscal decision-making. Hence, economists investigated uncertainty shocks and contributed to managing financial risks with global and energy uncertainty indices. Furthermore, the maturity of digital transformation and artificial intelligence financial applications catalyzed scholars to examine its contributions in the fiscal distress prediction field. Hence, this research aims to integrate artificial intelligence into financial performance analysis to bridge the gap in budget forecasting. The study was aimed at proposing an Economics Division Uncertainty approach (EDUA), which combined (ARIMA) and (LSTM) models for time series analysis of Nuclear Material Authority expenditures over the previous five years divided into quarterly periods, to achieve efficiency in spending. The (ARIMA) model's (ADF) results showed that uncertainty indicators are highly significant. The best (p-value) in the first and second differences in (ARIMA) models is (0.0001) for petroleum items, (0.0001) for solar price rates, (0.001) for the US exchange rate, and (0.003) for electricity price rates, when compared to (EDU_LSTM). Both models have similar accuracy rates, with the best being (EDU_ARIMA) (solar price 97%, USD exchange rate 84%). The second study proposed a composite model of four machine-learning tools to enhance financial performance during financial distress. The study collected (12) indicators from general financial literature and corporate studies, utilizing the (XGBOOST, Random Forest, KNN, and Naïve Bayes) models. Comparing the accuracy results for each model presented different accuracy results in the deep learning models over five years of data. The best accuracy score was for Random Forest at (69%), XGBOOT at (68%), and KNN at (68%). We recommended explainable AI as future research to interpret the budget deficit during the fiscal year period. [ABSTRACT FROM AUTHOR]

Objective: The Burundian emergency obstetric and neonatal care (EmONC) programme, which was initiated in 2017 and supported by a specific policy, does not appear to reverse maternal and newborn mortality trends. Our study examined the capacity challenges facing participating EmONC facilities and developed alternative investment proposals to improve their readiness paying particular attention to EmONC professionals, physical infrastructure, and capital equipment., Design: Cross-sectional study., Setting: Burundian EmONC facilities (n=112)., Participants: We examined EmONC policy documents, consulted 12 maternal and newborn health experts and 23 stakeholders and policymakers, surveyed all EmONC facilities (n=112), and collected cost data from the Ministry of Health and local suppliers in Burundi. We developed three context-specific EmONC resource benchmark standards by facility type; the Burundian policy norms and the expert minimum and maximum suggested thresholds; and used these alternatives to estimate EmONC resource gaps. We forecasted three corresponding budget estimates needed to address prevailing deficits taking a government perspective for a 5-year EmONC investment strategy. Additionally, we explored relationships between EmONC professionals and selected measures of service delivery using bivariate analyses and graphically., Results: The lowest EmONC resource benchmark revealed that 95% of basic EmONC and all comprehensive EmONC facilities lack corresponding sets of human resources and 90% of all facilities need additional physical infrastructure and capital equipment. Assessed against the highest benchmark which proposes the most progressive set of standards for the prevailing workloads, Burundi would require 162 more medical doctors, 1005 midwives and nurses, 132 delivery rooms, 191 delivery tables, 678 and 156 maternity and newborn care beds, and 395 incubators amounting to US$32.9 million additional budget for 5 years., Conclusion: We demonstrated that Burundian EmONC facilities face enormous capacity challenges equivalent to US$32.9 million funding gap for 5 years; averagely approximating to 5.96% total health budget increase annually., Competing Interests: Competing interests: None declared., (© Author(s) (or their employer(s)) 2024. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.)