The Fiscal Responsibility and Budget Management (FRBM) Act, 2003 imposes fiscal discipline on governments by limiting the fiscal deficit to a manageable level of 3% of the GDP. With fiscal consolidation, a reduced fiscal deficit decreases interest payment and debt servicing and permits governments to prioritise spending on capital expenditure or social sector expenditure. By reducing the revenue deficit, falling interest payments further increases the scope of capital outlay. This paper examines the causal relationship between fiscal deficit, interest payment, social sector expenditure and capital outlay, using panel data on state finances of seventeen major states of India years over a time period 2000-2023. The panel data analysis, based on the Johansen cointegration test, Granger causality test and error correction mechanism shows that there is a long-run relationship between gross fiscal deficit, capital outlay and interest payment. And there is long-run causality running from interest payment to capital outlay. Though there is short-run causality, there is no long-run
causality running from aggregate social sector expenditure to gross fiscal deficit. The estimated results suggest that many state governments have increased their capital expenditure with a reduction in gross fiscal deficit and interest payment.

Keywords: Fiscal deficit, interest payment, government expenditure, causality, cointegration, error correction

This study addresses a critical gap in the literature by examining the impact of Nigeria's 2023 exchange rate unification on exchange rate volatility, a crucial factor for economic stability, particularly in emerging markets. The recent unification has introduced unprecedented challenges and complexities that have not been thoroughly investigated in existing research. Using EGARCH and event study methods, the analysis reveals significant and prolonged spikes in abnormal volatility surrounding the announcement, reflecting heightened market uncertainty in the face of these transformative changes. The findings underscore the urgent need for well-crafted
policies tailored to emerging market contexts, including clear communication, supportive fiscal and monetary strategies, and continuous monitoring of market conditions. Such measures are essential for managing the transition effectively and ensuring longterm economic stability. Ultimately, this study contributes valuable insights into the dynamics of exchange rate policies in emerging markets, providing a framework for policymakers to navigate the challenges associated with currency unification and its effects on volatility.

Keywords: Exchange rate unification, Volatility modeling, EGARCH model, Event study, Emerging markets
JEL Codes: C100, C580, E300

This paper analyzes the effect of Foreign Direct Investment (FDI) on industrialization in Sub-Saharan Africa. Using panel data on 30 countries over the period 1996-2019, we apply a dynamic spatial panel regression. The results show that FDI contributes positively to industrialization. Moreover, there is a spatial effect that improves the estimations. Thus, a country whose neighbors have received more FDI is more likely to industrialize than a country that does not have these assets.

Keywords: Foreign Direct Investment, Industrialization, Spatial effects, sub-Saharan Africa.
JEL: O140

The popularity of cryptocurrencies, such as Bitcoin, as an alternative payment method has increased due to their decentralized structure, potential for large returns, and immunity from government controls. Cryptocurrencies users manage the network, which comprises transaction information arranged chronologically within each block. To this end, this study aimed to examine the impact of Bitcoin prices on Nigeria’s exchange rate volatility using data from the Central Bank of Nigeria’s statistical bulletin and the US Finance Reference from the first quarter of 2015 to the fourth quarter of 2022. A Vector Autoregression model was used to analyse the data. The root of the character test finding reveals that the VAR model meets the stability criterion, because all roots lie within the unit circle, ensuring reliable forecasting and analysis. The impulse response function analyses revealed that Bitcoin prices (BITP) significantly impact the exchange rate (EXCR). Initially, BITP increases and peaks around period 11, indicating that an increase in Bitcoin price results in a rise in the
Naira/USD exchange rate. Electronic currency level (ELEC) reveals significant early fluctuations, with an initial negative impact on EXCR but later recovered to positive values by periods 13 to 16. The financial electronic level (FINC) displays substantial early negative values, implying that an increase in FINC appreciates EXCR. The inflation rate (INFL) starts at 0, quickly turning negative, peaking in period 12, indicating that an increase in INFL appreciates EXCR. The study conclusion is that, while BITP and FINC induce short-term EXCR volatility, mid-term stabilization and long-term stability are evident as conditions improve. The study recommends establishing clear regulations for the cryptocurrency market among others.

Keywords: Bitcoin Price, Exchange Rate Volatility, Cryptocurrencies,Vector Autoregression Model, Financial Electronic Level
JEL Classification Codes: F31, G15, E44

The paper investigates the impact of the external-induced shocked of COVID-19 pandemic on the stock market volatility for 15 African countries. Stock returns volatility is generated using the GARCH approach and is regressed on infection-induced shock and death-induced shock, respectively. The pooled Ordinary Least Squares (OLS) and System-GMM estimation procedures were adopted. The empirical findings show that these COVID-19 pandemic generated severe negative shocks that led to strong volatiles in the stock markets of the countries examined. The paper recommends strong economic interventionist policies and resilience to mitigate external shocks associated with uncertainties like the COVID-19.

Keywords: External-induced shock, COVID-19 pandemic, Stock market volatility, Economic vulnerability
JEL Classification: I10, I15, F1