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Classical unit root tests are known to suffer from potentially crippling size distortions, and a range of procedures have been proposed to attenuate this problem, including the use of bootstrap procedures. It is also known that the estimating equation’s functional form can affect the outcome of the test, and various model selection procedures have been proposed to overcome this limitation. In this chapter, the authors adopt a model averaging procedure to deal with model uncertainty at the testing stage. In addition, the authors leverage an automatic model-free dependent bootstrap procedure where the null is imposed by simple differencing (the block length is automatically determined using recent developments for bootstrapping dependent processes). Monte Carlo simulations indicate that this approach exhibits the lowest size distortions among its peers in settings that confound existing approaches, while it has superior power relative to those peers whose size distortions do not preclude their general use. The proposed approach is fully automatic, and there are no nuisance parameters that have to be set by the user, which ought to appeal to practitioners.

Tourism–economy relationship in India has been studied extensively in the past literature using a single equation approach. However, the present paper diverted from this trend and examined the tourism–economy relationship using the specific to general modelling approach over the 1990–2018 time period. The study also accounts for the influence of merchandise trade, capital formation, foreign investment inflows and inflation on economic growth to achieve the robustness of the coefficient estimates.

To achieve the objective, the study utilised a specific to general modelling strategy. First, the regression equation includes only three core variables: gross domestic product (GDP), international tourist receipts and international tourist expenditures. Next, the authors include other control variables in the regression equation one by one, leading us to test five model types for investigating the cointegration among the variables. As for the estimation technique, the authors employed autoregressive distributed lag (ARDL) approach.

The paper's findings highlight that tourism receipts and expenditures exert a positively significant impact on economic growth. Moreover, including the additional independent variables does not substantially change the tourism and economic growth relationship. The existence of one-way causality from tourism expenditures to economic growth supports the tourism-led growth hypothesis. These findings highlight the rationale for intervention by the government and policymakers to promote tourism potential and facilities to accelerate the overall growth performance of the country. While the existence of one-way causal effect from economic growth to tourism revenues supports the growth-led tourism development hypothesis, implying that economic expansion is necessary for tourism development.

This research article tried to present a comprehensive picture of India's tourism–economy relationship. However, the present study is organised as an aggregate economy-level analysis. It assumed that the aggregate tourism sector is homogenous. However, different tourism sectors exert different levels of influence on the economy. The authors expect future research can take the disaggregated analysis of the tourism–economy relationship.

This study provides valuable insights into the tourism-led growth hypothesis in India. The study highlights comprehensive intervention by the government and policymakers for accelerating tourism development to invigorate the overall growth performance of the country over the long run. The principal recommendation emerging from the present research is that the tourism growth potential can be depended upon to stimulate the economic performance of the Indian economy.

The present study diverted from the previous empirical studies by following a specific to general modelling strategy. First, the regression model includes only three core variables such as economic growth, tourism receipts and tourism expenditure. Next, the authors include other control variables in the regression equation one by one, leading us to test five model types for investigating the cointegrating relationship among the variables. GDP growth rate is used as a dependent variable in all five specifications. The idea is to expand the model to capture every feature of the data generating process.

This study aims to predict stock market crashes identified by the CMAX approach (current index level relative to historical maximum) during periods of global and local events, namely the subprime crisis of 2008, the political and social instability of 2011 and the COVID-19 pandemic.

Over the period 2004–2020, a log-periodic power law model (LPPL) has been employed which describes the price dynamics preceding the beginning dates of the crisis. In order to adjust the LPPL model, the Global Search algorithm was developed using the “fmincon” function.

By minimizing the sum of square errors between the observed logarithmic indices and the LPPL predicted values, the authors find that the estimated parameters satisfy all the constraints imposed in the literature. Moreover, the adjustment line of the LPPL models to the logarithms of the indices closely corresponds to the observed trend of the logarithms of the indices, which was overall bullish before the crashes. The most predicted dates correspond to the start dates of the stock market crashes identified by the CMAX approach. Therefore, the forecasted stock market crashes are the results of the bursting of speculative bubbles and, consequently, of the price deviation from their fundamental values.

The adoption of the LPPL model might be very beneficial for financial market participants in reducing their financial crash risk exposure and managing their equity portfolio risk.

This study differs from previous research in several ways. First of all, to the best of the authors' knowledge, the authors' paper is among the first to show stock market crises detection and prediction, specifically in African countries, since they generate recessionary economic and social dynamics on a large extent and on multiple regional and global scales. Second, in this manuscript, the authors employ the LPPL model, which can expect the most probable day of the beginning of the crash by analyzing excessive stock price volatility.

Most emerging economies have made conscious efforts through policy initiatives to attract foreign direct investment (FDI). However, a significant obstacle to FDI inflow has been the prevalence of corruption in the host country. This study, therefore, aims to examine whether there is an optimum corruption value that results in threshold effects of corruption on FDI.

To achieve this objective, this study used Hansen’s (1999) panel threshold regression (PTR) model by using a panel data of 30 sub-Saharan African (SSA) countries from 2000 to 2021.

This study finds that the nexus between corruption and FDI has a single threshold effect, with a 5.37% optimum corruption threshold value. At this threshold value, corruption affects FDI negatively. Any corruption value that is below the threshold value also elicits a negative corruption–FDI relationship. Despite having a negative relationship when the corruption value is above the optimum corruption threshold, it is not statistically significant.

The implication of the results is that it is deleterious to use corrupt practices to draw FDI to SSA nations.

To the best of the authors’ knowledge, this study is one of the first in the corruption–FDI nexus literature to use Hansen’s PTR model to estimate an optimal corruption threshold. The authors recommend that policymakers in the selected SSA countries reconsider the use of corruption to attract FDI because there is an optimal corruption threshold that could impact FDI in the host country.

The purpose of this study is to empirically investigate the asymmetric effects of financial risk on Sukuk market development for a sample of Malaysian countries over the period of 2010–2021.

This study refers to the International Country Risk Guide (ICRG) in determining the financial risk factors to be studied in addition to the Malaysia financial stress index (FSI) to capture changes in financial risk level. The authors use the nonlinear autoregressive distributed lag (NARDL) model to tackle the nonlinear relationships between identified financial risk variables and Sukuk market development.

The results suggest the existence of a long-run relationship between foreign debt service stability, international liquidity stability (ILS), exchange rate stability (ERS) and financial stress level with the Sukuk market development in Malaysia. Indeed, higher ILS and ERS will boost Sukuk market size, whereas higher foreign debt services and financial stress are negatively related to Sukuk market development. Findings also indicate that the long-run positive and negative impacts of identified financial risk components on Sukuk market development are statistically different. Taking into account the role of the Sukuk market in facilitating Malaysia’s economic growth, the country should aim to keep the foreign debt-to-GDP ratio at a sustainable level.

This study points to three possible directions for future research. The first is the differential impact of financial risk components on Sukuk issuance for different Sukuk structures. As more data becomes available in the future, this area could be further explored by conducting the above analysis for different combinations of Sukuk structures and currency denominations. In addition, future researchers could also consider exploring the variability of financial risk impacts through comparative studies of the leading Sukuk-issuing countries to account for differences in regulatory frameworks and supporting infrastructure.

This study provides valuable practical and policy implications for strengthening the growth of the Sukuk market. While benefiting from the diversification benefits of funding sources to finance private or government projects and developments, Malaysia should remain vigilant to global economic conditions, foreign exchange markets and financial stress levels, as all of these factors may significantly influence investor sentiment and the rate of return offered by Sukuk issuance.

The use of the NARDL approach, which investigates the long-run effects of financial risk factors on Sukuk market development in Malaysia, makes this study a valuable addition to the literature, as there has been little research into the asymmetric effects of those variables on Sukuk market development using samples from emerging Asian markets.

The purpose of the paper is to explore the long-run impact of board governance and bank performance on executive remuneration. More specifically, the study addresses two objectives. First, the authors investigate the long-run relationship between pay and performance hold for the Indian banking industry. Second, the authors explore the moderating role of the board in explaining the relationship between executive pay and performance.

The study uses multivariate panel co-integration approaches, i.e. fully modified and dynamic ordinary least square, to explain the co-integrating relationship between executive pay, governance and performance of Indian banks. The analysis is conducted for the period from 2005 to 2018.

The results of co-integration tests reveal a long-run relationship between executive pay, board governance and bank performance. The long-run estimates produce evidence in favour of the dynamic agency theory, suggesting that the implications of asymmetric information can be mitigated by associating the current executive pay with the bank performance in the previous periods. The finding of this study reveals that improvements in the board quality serve as a monitoring tool to constrain excessive pay and moderate the executives’ pay. Furthermore, the interaction of performance and board governance negatively impacts pay, supporting a substitution approach. It implies that setting optimal pay packages for executives necessitates enhanced and efficient board governance practices.

The study recommends significant policy implications for regulators and the board of directors that executive pay significantly responds to the bank’s performance and good board governance practices in the long run.

This paper provides novel evidence of long-run pay-performance-governance relation using a panel co-integration approach.

The aim of the paper is to determine the asymmetric impact of tourism on the deficit in the balance of payments (BOPs).

The research uses the non-linear autoregressive distributed lag (ARDL) model to investigate the asymmetric impact of tourism on Pakistan's BOPs deficit using quarterly data from 1995 to 2019.

The finding reveals that due to the positive change in tourism, the BOPs deficit decreases by 27%, although due to the negative change in tourism, the BOPs deficit rises by 2.3%. In addition, the significance of F-statistics (10.609) confirms the existence of co-integration between tourism and the deficit in the BOPs. The Wald test confirms the asymmetric association between tourism and the deficit in the BOPs over the long term.

In order to improve tourism in Pakistan, policymakers must consider the following implications. First, there is a need for an adequate infrastructure that can help the tourist. Second, the Government must maintain a stable law and order situation as a whole and particularly at tourist destinations. Finally, the Government should develop tourism-friendly policies in order to boost tourism in Pakistan.

The research provides new evidence of the impact of tourism on the BOPs using the novel non-linear ARDL (NARDL) technique. The evidence will help policymakers to develop policies to improve tourism in order to reduce the BOPs deficit.

Socioeconomic development needs quality governance to provide and protect property rights and other economic means. In this regard, the current study examines the symmetric and asymmetric effect of composite governance index, unemployment rate (UR) and consumer price index on the crime rate (CR) in Pakistan.

The current study uses time series data (1996–2020) on CR, composite governance index, UR and consumer price index. In this study, the authors first constructed a composite governance index from six governance indicators using the principal component analysis (PCA) method. After that, the short-run and long-run symmetric and asymmetric effects were estimated through linear and non-linear autoregressive distributed lag (ARDL) models, respectively.

The authors found short-run and long-run symmetric and asymmetric effects of governance, unemployment and consumer prices (CPI) on the CR in Pakistan. For asymmetric effects, the findings show that high-quality governance diminishes and poor governance accelerates committed crimes in Pakistan. Interestingly, the asymmetric unemployment effect suggests that criminal behavior diminishes when people find job opportunities and do not adopt criminal behavior even if people lose employment. In other words, if unemployment decreases CR will fall, and when unemployment increases, the CR may not increase. Lastly, rising product prices lead to criminal behavior, while falling prices do not help to diminish the CR in Pakistan.

The study provides the first empirical evidence of symmetric and asymmetric responses of CR toward composite governance index, UR and consumer price index.

The peer review history for this article is available at: https://publons.com/publon/10.1108/IJSE-09-2022-0625

Despite the huge financial resources associated with oil, Nigeria has consistently recorded poor growth performance. Therefore, this study aims to examine how corruption and oil rent influence Nigeria’s economic performance during the 1996–2021 period.

Various estimation techniques were used. These include the bootstrap autoregressive distributed lag (ARDL) bounds-testing, dynamic ordinary least squares (DOLS), the fully modified OLS (FMOLS) and the canonical cointegration regression (CCR) estimators and the Toda–Yamamoto causality.

The bounds testing results provide evidence of a cointegrating relationship between the variables. In addition, the results of the ARDL, DOLS, CCR and FMOLS estimators demonstrate that oil rent and corruption have a significant positive impact on growth. Further, the results indicate that human capital and financial development enhance economic growth, whereas domestic investment and unemployment rates slow down long-term growth. Additionally, the causality test results illustrate the presence of a one-way causality from oil rent to economic growth and a bi-directional causal relationship between corruption and economic growth.

Existing studies focused on the effects of either oil rent or corruption on growth in Nigeria. Little attention has been paid to the exploration of how the rent from oil and the pervasiveness of corruption contribute to the performance of the Nigerian economy. Based on the outcome of this study, strategies and policies geared towards reducing oil dependence and the pervasiveness of corruption, enhancing human capital and financial development and reducing unemployment are recommended.