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This paper develops a cross-sectionally augmented distributed lag (CS-DL) approach to the estimation of long-run effects in large dynamic heterogeneous panel data models with cross-sectionally dependent errors. The asymptotic distribution of the CS-DL estimator is derived under coefficient heterogeneity in the case where the time dimension (T ) and the cross-section dimension (N ) are both large. The CS-DL approach is compared with more standard panel data estimators that are based on autoregressive distributed lag (ARDL) specifications. It is shown that unlike the ARDL-type estimator, the CS-DL estimator is robust to misspecification of dynamics and error serial correlation. The theoretical results are illustrated with small sample evidence obtained by means of Monte Carlo simulations, which suggest that the performance of the CS-DL approach is often superior to the alternative panel ARDL estimates, particularly when T is not too large and lies in the range of 30–50.

Purpose: The advent of the fintech revolution has brought a tremendous increase in the dissemination of digital financial services. Although digital financial services increase financial inclusion through financial intermediation, it also increases the chances of systematic risk.

Need: In the quest to satisfy the curious minds, the authors have examined the influence of digital financial services on banking stability and efficiency.

Methodology: To achieve the above objectives, the authors have used the Auto-Regressive Distribution Lag (ARDL) estimation technique on the annual data set of India and the United States from 2004 to 2018. In addition, to estimate the long-run cointegration, the ARDL bound approach is also used.

Findings: The empirical analysis concludes that in the short run, the expansion of digital financial services in India in the form of internet-based transactions and mobile money transactions creates a negative and significant impact on banking efficiency and stability. Meaning, banking sector efficiency and stability fall by 0.09% and 0.05% with a 1% increase in digital financial services. However, in the long run, digital financial services enhance banking stability and efficiency in India. Besides, the study also reveals that in a developed country like the United States, both in the short run and long run, expansion of digital financial services helps in improving banking efficiency and stability. Furthermore, in context to control variables, the findings suggest that in the short run, industrial productivity has a negative influence on the Indian banking sector efficiency and stability, compared to the positive impact in the long run. This is unlike the United States, where both in the long-run and short-run, industrial productivity has a positive influence on the banking sector’s efficiency and stability.

Practical implication: The findings reveal several policy implications and suggest policy synergies between digital financial services, banking stability and efficiency.

This study is motivated by the fact that even though many African countries have witnessed rapid growth, they have also experienced high volatility in the form of severe financial crises, especially in the last two decades. These developments naturally lead to the issue of whether, in a more integrated global economy, the relationship between growth and output volatility has changed. The phenomena have also raised questions on whether the growth–output volatility relationship can be linked to the growing pains seemingly associated with rising trade and financial integration. This chapter attempts to provide answer to these questions by providing insights on how trade and financial integration affect the relationship between growth and output volatility using data from selected Africa countries. The study explores in detail the relationship between growth and the volatility of output components (consumption and investment). Our main result is that there is a positive growth and output volatility impact of trade openness and integration with the international financial market. The relationship between growth and financial integration and investment volatility is stronger in the long run than in the short run, while the consumption volatility impact of trade openness is higher in the long run than in the short run, suggesting that countries that are more open to trade appear to face less severe trade-off between growth and volatility.

This chapter examines the effect of changes in the public debt–gross domestic product (GDP) ratio on long, 10 year, interest rates in a panel of 17 countries over the period 1870–2016 controlling for other variables, in particular the world interest rate. Over this long period, one can argue that most of the big changes in public debt were the product of factors largely exogenous to national interest rate determination, such as war, depression or financial crisis. The issue is of current relevance since the Covid-19 pandemic has caused large increases in the ratio of public debt to GDP in many countries. The estimates suggest that it is the change in debt, rather than the level of debt or the deficit that matters for long interest rates. World interest rates have long- and short-run effects on interest rates which are very well determined and close to one. Current inflation has a small but significant effect.

For the last two decades economics literature and debates have increasingly referred to institutions as the answers to the long-lasting queries regarding how stock market performance rises and what policies can be implement to encourage best outcomes in terms of stock market performances in Malaysia so that the analysis of the institutional basis under which any stock market functions has now converted an essential issue of investigation. This study attempts to capture the relationship between stock market movements and institutional quality (IQ) using autoregressive distributed lag bounds testing approach, over 33 years during the period of 1984–2016. The finding suggests that IQ positively and significantly affects stock market performance. Moreover, it is also showing that there is, in fact, a causal relationship between institutions and stock market performance. The findings are robust to changes in specification and a host of transparency measures.

The economic importance of palm oil produced by its producers in food requirement, income generation, production and consumption has led to a significant increase in its demand over the years. Thus, this chapter evaluates the effects of palm oil price fluctuations on the welfare of palm oil producers in Nigeria based on annual time series data (1980–2018). In achieving its objectives, the study employs Autoregressive distributed lag model (ARDL). The result establishes the presence of a long-run relationship in the welfare of palm oil producers. The long-run estimates show that palm oil prices had a positive but insignificant relationship with the welfare of palm oil producers. In the short-run estimates, palm oil price and the exchange rate had adverse and significant effects on the welfare of palm oil producers, while the inflation rate positively and significantly influenced welfare. Therefore, the welfare programme should adopt policies that will stabilise the palm oil price and other foodstuffs to increase the standard of living of palm oil producers and raise their literacy levels.

Recent evidences show that terrorism is becoming frequent in Nigeria, ranging from incessant Boko Haram activities in the North East; Independent People of Biafra (IPOB) activities in the South-East states, kidnapping and vandalizing oil pipes in the South-South, Fulani-herdsmen attacks in the Middle Belt, among others. In an attempt to tackle terrorism, the Federal Government at different times adopted military actions with little or no lasting solution. The Have and Have-nots hypothesis (Shahbaz, 2013) stresses the role of economic phenomenon in determining the causes of terrorism. It is on this note that this chapter investigates the linkages between economic growth proxy by gross domestic product per capita (GDPPC) and other fundamental variables such as inflation, unemployment, and inequality gaps, among others; and terrorism in Nigeria. We intend to know whether cointegration exists between the two constructs; and if it does, is there causality? The study employed both the autoregressive distributed lag (ARDL) and the vector error correction model (VECM) approaches to examine the existence of or otherwise a long-run relationship as well as causality among the constructs. Results reveal that a compelling cointegrating relationship exists among the variables. It is further revealed that unemployment, inequality, poverty, inflation, among others, Granger cause terrorism. It stresses that the Have-not hypothesis explained the causes of terrorism in Nigeria. The study therefore suggests that policy makers should, in order to prevent or combat terrorism, focus on improving the economy by creating job opportunities through provision of conducive environment that supports businesses and reduces inequality gaps.

This chapter empirically examines the relationship between defense expending, budget deficits, and income redistribution in India for the period 1970–2009. The analysis is based on an autoregressive distributed lag model (ARDL) popularized by Pesaran and Shin (1999). Empirical estimates reveal that military spending in India is indeed associated with income redistribution. The empirical approach indicates that there exists a long-run relationship between transfer payments as a percentage in GDP (TP), defense expenditures as a percentage in GDP (ME), and budget deficits as a percentage in GDP (DEF) in India. Defense expenditures as a percentage in GDP and the budget deficits as a percentage in GDP have positive and significant impacts on transfer payments in the same fiscal year. But the budget deficit as a percentage in GDP has a negative and significant impact on transfer payments as a percentage in GDP in the next fiscal year.