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This chapter revisits the Hausman (1978) test for panel data. It emphasizes that it is a general specification test and that rejection of the null signals misspecification and is not an endorsement of the fixed effects estimator as is done in practice. Non-rejection of the null provides support for the random effects estimator which is efficient under the null. The chapter offers practical tips on what to do in case the null is rejected including checking for endogeneity of the regressors, misspecified dynamics, and applying a nonparametric Hausman test, see Amini, Delgado, Henderson, and Parmeter (2012, chapter 16). Alternatively, for the fixed effects die hard, the chapter suggests testing the fixed effects restrictions before adopting this estimator. The chapter also recommends a pretest estimator that is based on an additional Hausman test based on the difference between the Hausman and Taylor estimator and the fixed effects estimator.

This study investigates the impact of US dollar volatility and oil rents on the performance of small and medium-sized enterprises (SMEs) in the Gulf Cooperation Council (GCC) region, with an emphasis on understanding how these factors influence SME financing constraints in economies with fixed currency regimes.

Employing a random effects panel regression analysis, this research considers US dollar volatility and oil rents as independent variables, with SME performance, measured through the financing gap, as the dependent variable. Controls such as trade balance, inflation deltas and gross domestic product (GDP) growth are included to isolate their effects on SME financing constraints.

The study reveals a significant positive relationship between dollar volatility and the financing gap, suggesting that increased volatility can exacerbate SME financing constraints. Conversely, oil rents did not show a significant direct influence on SME performance. The trade balance and inflation deltas were found to have significant effects, highlighting the multifaceted nature of economic variables affecting SMEs.

The study acknowledges potential biases due to omitted variables and the limitations inherent in the use of secondary data.

Findings offer pertinent guidance for SMEs and policymakers in the GCC region seeking to develop strategies that mitigate the impact of currency volatility and support SME financing.

The research provides new insights into the dynamics of SME performance within fixed currency regimes, which significantly contributes to the limited literature in this area. The paper further underscores the complex connections between global economic factors and SME financial health.

This paper aims to investigate the impact of political stability on corruption by drawing upon a sample encompassing both developed and developing European and Asian countries.

The dataset, sourced from the Refinitiv database, spans from July 2014 to May 2022. Panel data techniques, specifically pooled estimation and dynamic panel data [generalized method of moments (GMM)] are employed. The analysis encompasses both fixed and random effects models to capture country-specific cross-sectional effects. To validate our findings, we perform a robustness test by including in the investigation four control variables, namely poverty, type of governance, economic freedom and inflation. To test heterogeneity, the dataset is further divided into two distinct subsamples based on the countries’ locations.

Empirical findings substantiate that political stability (viewed as the risk of government destabilization) has a positive and significant impact on corruption in all analyzed samples of European and Asian countries, though some differences are observed in various subsamples. When we take into account the control variables, these analysis results are robust.

This research provided a panel data analysis with GMM, while other empirical methodologies could also be used, like the difference-in-difference approach. However, our results should be validated by extending the time and the sample to a worldwide sample and using alternative measures of corruption and political stability. Moreover, our focus was on a linear and unidirectional relationship between the considered variables, but it would be interesting to test in our further research a non-linear and bidirectional correlation between them. Furthermore, we have introduced in the robustness test only four economic variables, but to consolidate our findings, we plan to include socioeconomic and demographic variables in future studies.

These outcomes imply that authorities should be aware of the necessity of implementing anti-corruption policies designed to establish effective agencies and enforcement structures for combating systemic corruption, to improve the political environment and the quality of institutions and to apply coherent economic strategies to accelerate economic growth because higher political stability and sustainable development determine a decrease in levels of corruption.

At the microeconomic level, the survival of organizations may be in danger from new types of corruption and money laundering. Therefore, in order to prevent financial harm, the top businesses worldwide should respond to instances of corruption through strengthened supervisory procedures. This calls for the creation of a mechanism inside the code of conduct where correct reporting of suspected situations of corruption would have a prompt procedure to be notified of. To avoid corruption in operational procedures, national plans and policies should be developed by government officials, executives and legislators on a national level, as well as by senior management and the board of directors on an organizational level. This might lower organizations' extra corruption-related expenses, assure economic growth and improve global welfare.

A novel feature of our research resides in its broad examination of a sizable sample of European and Asian countries regarding the nexus between corruption and political stability. The paper also investigates a less explored topic in economic literature, namely the impact of political stability on corruption. Furthermore, the study depicts policy recommendations, outlining effective and reasonable measures aimed at improving the political landscape and combating corruption.

This research attempts to examine bank dividend policy in Indonesia by applying the life cycle theory of dividends.

This research used secondary data gotten from two sources: banks’ annual financial statements from 2005 to 2019 and the number of observation samples was 510 from 42 banks. Random Effects Logit Model (RELM) is used to detect the influence of independent variables on Propensity to Pay Dividends (PPD) and Random Effects Tobit Model (RETM) is used to test the influence of independent variables on Dividend Payout Ratio (DPR).

The RELM results show that Retained Earnings to Total Equity (RE/TE), Retained Earnings to Total Asset (RE/TA) and bank age have a positive impact on the propensity to pay dividends (PPD) while bank growth (GRW) has a negative impact. The RETM results reveal that RE/TE, ROA and bank size have a positive impact on the dividend payout ratio (DPR) while GRW has a negative impact. This analysis also discovers that the capital adequacy ratio (CAR) and Non-performing Loans (NPL) is one important factor considered by banks in Indonesia in determining their dividend policy.

This study contributes to enriching literature in finance, especially in the life cycle theory of dividends. Also, it can be a guide to consider by investors before deciding to put their shares in banks in Indonesia.

Research on bank-specific life cycle theory is very difficult to find, especially in the Indonesian context, so this research can enrich the body of knowledge on dividend decisions.

By using a wide range of macro and micro factors, this paper aims to provide a new assessment of the recent literature on inbound tourism demand models.

This study examines the determinants and spatial effects of inbound tourism using Hausman–Taylor and spatial econometric models.

Several important factors were identified, including local economic growth, openness to the outside world, regional size, geographic distance, foreign direct investment, level of innovation and average annual temperature. In addition, the study found strong cross-city competition effects on tourism resource endowment and hotel infrastructure.

Inbound tourism is a crucial link in achieving high-quality economic development. However, previous studies have mainly focused on the analysis of single influencing factors, ignoring the spatial spillover effects of factors.

In the context of investment decisions, the intricate interplay between exogenous shocks and their influence on investor confidence significantly shapes their behaviors and, consequently, their outcomes. Investment decisions are influenced by uncertainties, exogenous shocks as well as the sentiments and confidence of investors, factors typically overlooked by decision-makers. This study will meticulously examine these multifaceted influences and discern their intricate hierarchical nuances in the sentiments of industrial entrepreneurs during the COVID-19 pandemic.

Employing the robust framework of the generalized linear latent and mixed models (GLLAMM), this research will thoroughly investigate individual and group idiosyncrasies present in diverse data compilations. Additionally, it will delve deeply into the exogeneity of disturbances across different sectors and regions.

Relevant insights gleaned from this research elucidate the adverse influence of exogenous forces, including pandemics and financial crises, on the confidence of industrial entrepreneurs. Furthermore, a significant discovery emerges in the regional analysis, revealing a notable homogeneity in the propagation patterns of industrial entrepreneurs' perceptions within the sectoral and regional context. This finding suggests a mitigation of regional effects in situations of global exogenous shocks.

Within the realm of academic inquiry, this study offers an innovative perspective in unveiling the intricate interaction between external shocks and their significant impacts on the sentiment of industrial entrepreneurs. Furthermore, the utilization of the robust GLLAMM captures the hierarchical dimension of this relationship, enhancing the precision of analyses. This approach provides a significant impetus for data-informed strategic directions.

This study seeks to explore the intricate relationship among supply chain transparency, digitalization and idiosyncratic risk, with a specific focus on newly public firms. The objective is to determine whether supply chain transparency effectively mitigates idiosyncratic risk within this context and to understand the potential impact of digitalization on this dynamic interplay.

The study utilizes data from Initial Public Offerings (IPOs) on China’s Growth Enterprise Board (ChiNext) over the last five years, sourced from the CSMAR database and firms’ annual reports. The research covers the period from 2009 to 2021, observing each firm for five years post-IPO. The final sample comprises 2,645 observations from 529 firms. The analysis employs the Hausman test, considering the panel-data structure of the sample and favoring fixed effects over random effects. Additionally, it applies the high-dimensional fixed effects (HDFE) estimator to address unobserved heterogeneity.

The analysis initially uncovered an inverted U-shaped relationship between supply chain transparency and idiosyncratic risk, indicating a delicate equilibrium where detrimental effects diminish and beneficial effects accelerate with increased transparency. Moreover, this inverted U-shaped relationship was notably more pronounced in newly public firms with a heightened level of firm digitalization. This observation implies that firm digitalization amplifies the impact of transparency on a firm’s idiosyncratic risk.

This study distinguishes itself by providing distinctive insights into supply chain transparency and idiosyncratic risk. Initially, we introduce and substantiate an inverted U-shaped correlation between supply chain transparency and idiosyncratic risk, challenging the conventional linear perspective. Secondly, we pioneer the connection between supply chain transparency and idiosyncratic risk, especially for newly public firms, thereby enhancing comprehension of financial implications. Lastly, we pinpoint crucial digital conditions that influence the relationship between supply chain transparency and idiosyncratic risk management, offering a nuanced perspective on the role of technology in risk management.

This research investigates the Islamic banks’ intermediation role (e.g. branches and deposits) in financing. It also examines how financing contributes to the regions' economic growth and poverty alleviation as a predictor and mediator variable.

A total of 297 observations were extracted from 33 Indonesian districts and 14 Islamic banks during the period 2012–2020. Fixed-effect regression analysis was used to examine variable’s interactions.

The empirical results indicate that Islamic banks have adopted a channelling role towards redistributing capital from lender to borrower. Besides, there are crucial roles in developing economies and reducing poverty at the district level. This study also reinforces the critical role of financing in mediating the relationship between branches and deposits as predictor variables and GDP and poverty as outcome variables.

The current study was limited to Indonesian Islamic banks and the district’s perspective. Future research needs to cover sub-districts and other poverty measurements (e.g. human education and development perspectives), including conventional and Islamic banks. It can help practitioners, regulators and researchers observe the dynamic behaviour of the banking sector to understand its role in the economic and social fields.

Bank managers and regulators should promote branches, deposits and financing. It also enlightens people about the essential role of Islamic banks and their fundamental operations in business and economics.

This study contributes to economic literature, bank managers and local governments' decision-making processes by developing and testing an economic growth and poverty model.

This paper aims to investigate the impact of retrenchment strategy on firm performance in the context of Pakistani firms while considering the moderating role of chief executive officer (CEO) power. By examining the influence of CEO duality and CEO share ownership on the relationship, this study contributes to strategic management and corporate governance knowledge within the Pakistani business environment.

A quantitative approach was used to analyze the relationship using data from annual financial statements. The sample consisted of 76 companies from the KSE-100 index from the year 2015 to 2020. Random effects regression models were used, along with hierarchical regression to explore the moderating effect of CEO power.

The findings demonstrate that the implementation of a retrenchment strategy positively impacts firm performance in Pakistani firms. The study also reveals that CEO power plays a crucial role in strengthening the relationship between retrenchment strategy and firm performance. Moreover, the study highlights the importance of considering the temporal sequence, size and age of firms when examining the impact of CEO power and retrenchment strategy on firm performance.

The study enhances the understanding of the contingent nature of retrenchment strategies and the influence of CEO power in the Pakistani business context. Practically, the research contributes to strategic management and corporate governance dynamics, facilitating the development of strategies that enhance firm performance and sustainability in Pakistan.

This research provides original insights by specifically focusing on the Pakistani context and analyzing the interplay between retrenchment strategy, CEO power and firm performance. The study adds to the limited literature on the relationship between retrenchment and performance in the Pakistani business environment. Additionally, it highlights the significance of CEO power as a critical factor in determining the success of retrenchment.

Estimation of (in)efficiency became a popular practice that witnessed applications in virtually any sector of the economy over the last few decades. Many different models were deployed for such endeavors, with Stochastic Frontier Analysis (SFA) models dominating the econometric literature. Among the most popular variants of SFA are Aigner, Lovell, and Schmidt (1977), which launched the literature, and Kumbhakar, Ghosh, and McGuckin (1991), which pioneered the branch taking account of the (in)efficiency term via the so-called environmental variables or determinants of inefficiency. Focusing on these two prominent approaches in SFA, the goal of this chapter is to try to understand the production inefficiency of public hospitals in Queensland. While doing so, a recognized yet often overlooked phenomenon emerges where possible dramatic differences (and consequently very different policy implications) can be derived from different models, even within one paradigm of SFA models. This emphasizes the importance of exploring many alternative models, and scrutinizing their assumptions, before drawing policy implications, especially when such implications may substantially affect people’s lives, as is the case in the hospital sector.