Search results

This paper aims to investigate whether official development assistance (ODA) inflows to developing countries (lower-middle and low income) can cause the symptoms of Dutch disease or not.

This study applies the methodology of dynamic panel data estimation with a one-step system generalized methods of moment (GMM) for the sample of 59 developing countries from 2001 to 2019.

The results indicate that ODA (as a percentage of gross domestic product (GDP)) rises by 1%, the real effective exchange rate (REER) appreciates by 0.252%. This finding reveals that these selected developing countries have faced the symptoms of Dutch disease. The countries with the higher ODA ratio have a higher effect of the Dutch disease, and the managed floating exchange rate regime is the lowest impacted, when compared to the fixed and flexible exchange rate.

The selected countries are recommended to use ODA inflows right and efficiently. These ODA inflows should be invested in productive sectors or support for production rather than in consumption. The managed float exchange rate regime is applied to reduce the symptom of Dutch disease for the selected countries. The good cooperation of monetary and fiscal policies is important to absorb the huge ODA inflow and sterilize the adverse effects of the disease.

The paper contributes to the literature and empirical of the Dutch disease. An adverse effect of the huge ODA inflow to the developing countries appreciated of the real exchange rate and caused the symptom of the dutch disease.

The peer review history for this article is available at: https://publons.com/publon/10.1108/IJSE-12-2022-0777

This study assesses the probability of an OECD member country exhibiting high persistence in unemployment duration, considering income inequality, productivity, accumulation of human capital and labor income share in Gross Domestic Product (GDP) between the years 2013–2019.

To achieve the purpose of the study, a probabilistic analysis with panel data is employed, focusing on 20 OECD countries segmented into two groups: those with high persistence and low persistence in unemployment duration. Probit and Logit models are estimated, marginal changes are analyzed and the models are evaluated in terms of their classification accuracy. Finally, trends in probabilities over time are examined.

This paper exhibits that countries with higher human capital index, greater labor income share in GDP, and more relevant productivity for well-being reduce their probabilities of experiencing high persistence in unemployment duration. It is observed that Mexico (MEX), Greece (GRC), Italy (ITA), and Turkey (TUR) have elevated probabilities of experiencing high persistence in unemployment duration in the future, while Costa Rica (CRI), Estonia (EST), Slovakia (SVK), Czech Republic (CZE), Lithuania (LTU), Poland (POL), and Israel (ISR) show a marked downward trend in these probabilities. Lastly, countries like the United Kingdom (GBR), Denmark (DNK), Sweden (SWE), Norway (NOR), Netherlands (NLD), Germany (DEU), United States (USA), and Canada (CAN) present minimal risk of experiencing high persistence in unemployment duration in the future.

The measurement of the relationship between development outcomes and persistence in unemployment duration has been scarce. Generally, the literature has focused on the analysis of development and unemployment without delving into the duration of unemployment, let alone persistence in duration.

This paper provides a solid foundation for the formulation of policies aimed at promoting sustainable employment and inclusive economic growth.

Based on the findings of the study, two key development policies are proposed. Firstly, the implementation of investment programs in Human Capital to increase productivity is recommended. Resources should be directed towards initiatives that improve the necessary skills and competencies in the labor markets of OECD countries, especially in strategic economic sectors with higher production linkages. Additionally, incentivizing the application of active labor policies is proposed. This entails prioritizing policies aimed at increasing the labor income share in GDP through progressive fiscal reforms that strengthen social safety nets and ensure fair labor standards. Implementing employment programs targeted at vulnerable groups, such as long-term unemployed individuals, youth, female heads of households and marginalized communities, is also recommended to eliminate structural barriers to labor market participation and reduce disparities in unemployment persistence. Adopting these policies can help mitigate the risk of high unemployment duration persistence and foster sustainable and inclusive long-term economic growth.

This is the first study to analyze the probabilities of both developing and developed countries experiencing high persistence in unemployment duration. It specifically evaluates these probabilities over a period of time and also estimates potential outcomes if real investments were made to enhance their human capital, productivity and employability.

The present study reviews the theoretical and empirical literature about the significance of international migrants' remittance to empirically analyse the effect of remittance on the productivity growth of developing countries using a panel dataset from 1991 to 2021.

The study utilised the data envelopment analysis (DEA)-based Malmquist Productivity Index (MPI) to measure nationwide production efficiencies. It first performed a unit root test, cointegration test and pool mean group autoregressive distributed lag (PMG-ARDL) technique. To assess the robustness of the findings, the study also uses dynamic ordinary least squares (DOLS) and fully modified OLS (FMOLS) estimators.

The results demonstrated that remittances are a significant source of funding that promotes innovation [i.e. technological progress (TEC)] and hastens the country's total factor productivity (TFP) growth. However, the study needed to have established the effect of inward remittances on the nation's technical efficiency (EFF).

As remittances encourage innovation and TFP growth (TFPG), the concerned governments must create favourable and enabling economic environments to increase remittance inflows, which will have far-reaching growth repercussions.

The present study emphasises the connection between remittances and productivity growth, the disintegration of TFP, advanced econometric techniques and contribution to research policy. Despite prior literature exploring the effect of remittances on economic growth, a dearth of literature exists on how remittances affect a country's productivity. The output-based MPI methodology used in this study offered a nuanced understanding of how remittances affect many facets of productivity growth in developing nations.

“The latest available cross-country data presented in the PEPPER V Report (Lowitzsch and Hashi, 2024) can be viewed by examining EFP in and of itself as an isolated subject or it can be viewed in a much wider set of contexts. Widening the lens in order to examine EFP in the context of the concentration of capital ownership and the concentration of capital income can help observers establish EFP’s span of relevance. In particular US data on capital income show that policy makers need to be aware that EFP can have an important role in narrowing the income and wealth gap for the working middle class when the concentration of capital ownership and capital income is high and when real wage growth is low.”

“Against this background, this article makes a very straightforward observation that the relevance of EFP in an economic system, in a country, and for the average employee in a country is related to the trend in the concentration of capital ownership and capital income. Interest in the idea is potentially increased or decreased by trends in real wages. Atkinson, who many consider the founder of modern wealth concentration scholarship, “focuses on the increasing share of capital incomes a source of income inequality among individuals” (Cirillo et al., 2017, p. 1). Indeed, we consider the difference between labour’s share and capital’s share to be a critically important fundamental problem of political economy. This essay asserts that when this concentration is high and real wages are flat, other things being equal, EFP may be more relevant. When the concentration of capital ownership and capital income is high, this means that ownership and income on that ownership is thinly spread in the population. When real wages are flat, this means that the rate at which fixed wages can replenish wealth is decreasing. As a result, both trends would make EFP more relevant.”

The conceptual model suggested for this article asserts that the relevance of EFP can be viewed as a function of narrowing income and wealth options for the working middle class when the concentration of capital ownership and capital income is high and when real wage growth is low. Does this relevance change across economic systems? There is no question that the future understanding of these issues requires adding metrics to the statistical methodologies of different regions and countries and adding to existing reports and analyses that focus on both the dynamics of and trends in capital income (property income in the EU) and on the EUR and USD value of EFP at the mean and at the median for different income levels of the population

This article presents – for the first time – a society-wide measure of the impact of EFP on one economy, namely, the US For further research, it makes sense to build on the comparable data available on the distribution of capital ownership and have similar research on the distribution of capital income for both the EU and the US along with measures of the EUR and USD values of EFP.

The research aims to provide empirical evidence on the relationship between financial statement comparability (FSC) and cost of equity (COE) in an emerging market.

Specifically, this study examines the relationship between FSC and COE of Vietnamese listed firms. The research uses the System Generalized Method of Moments regression techniques for a panel data set of 454 companies for the period 2015–2022.

The authors find that firms with high comparability of financial statements have lower COE. To confirm the research findings, the authors conduct the robustness test by using different proxies for the cost of equity. Consistent results are found.

The study contributes to the overall understanding of the relationship between FSC and COE, and suggests policy implications for relevant stakeholders such as managers, regulatory bodies and investors. Especially, regarding policymakers, this study could provide more insight into how the accounting convergence process impacts the effectiveness of a firm’s capital allocation.

This study aims to present an innovative predictive methodology that transitions from traditional efficiency assessment techniques to a forward-looking strategy for evaluating working capital management(WCM) and its determinants by integrating data envelopment analysis (DEA) with artificial neural networks (ANN).

A slack-based measure (SBM) within DEA was used to evaluate the WCME of 1,388 firms in the Indian manufacturing sector across nine industries over the period from April 2009 to March 2024. Subsequently, a fixed-effects model was used to determine the relationships between selected determinants and WCME. Moreover, the multi-layer perceptron method was applied to calculate the artificial neural network (ANN). Finally, sensitivity analysis was conducted to determine the relative significance of key predictors on WCME.

Manufacturing firms consistently operate at around 50% WCME throughout the study period. Furthermore, among the selected variables, ability to create internal resources, leverage, growth, total fixed assets and productivity are relatively significant vital predictors influencing WCME.

The integration of SBM-DEA and ANN represents the primary contribution of this research, introducing a novel approach to efficiency assessment. Unlike traditional models, the SBM-DEA model offers unit invariance and monotonicity for slacks, allowing it to handle zero and negative data, which overcomes the limitations of previous DEA models. This innovation leads to more accurate efficiency scores, enabling robust analysis. Furthermore, applying neural networks provides predictive insights by identifying critical predictors for WCME, equipping firms to address WCM challenges proactively.

The purpose of this paper is to examine the association between company reputation and dividend policy.

In this study, sample of 98,809 firm-year observations from 22 countries covering 2005–2016 were used.

Firm reputation concerns are associated with higher propensities to pay dividends and payout ratios. Further, this positive effect is more pronounced for firms with high free cash flows, high information asymmetry and low institutional monitoring. The results are robust to an instrumental variable approach, propensity score matching and the Heckman two-stage correction approach while addressing endogeneity concerns.

These findings have significant implications for various stakeholders, such as existing and potential investors, managers, policymakers and regulators, by providing insights into the relationship between corporate reputation and firm dividend payout decisions. Corporate reputation is highlighted as crucial for accessing finance, emphasizing the role of national regulators and policymakers in facilitating firms' efforts to improve their reputation. The study highlights the dynamics of corporate reputation and dividend payout, calling for proactive engagement from regulators and policymakers. Crafting policies conducive to reputation-building can enhance firms' financial prospects, indicating the need for strategic interventions at managerial, regulatory and policy levels. Understanding the influence of economic context is crucial for firms to tailor reputation management strategies and optimize funding opportunities in different economic environments.

Overall, results suggest that reputation serves as a disciplining mechanism, where firms will pay dividends to maintain their reputations.

Prior research from transaction costs economics argued that central firms perform better because they have superior access to information to discipline their alliance partners. Central firms may also, however, face higher costs and risks of unintentional learning and weaken their competence through structural inertia. We propose that these costs and risks are influenced by the learning capacities of the firms in the network and can explain different outcomes for focal firm performance.

To test our predictions, we use instrumental variable–generalized method of moments estimation techniques on 15,517 firm-year observations from equity alliance portfolios in the global food industry across a 21-year window.

We find support for our predictions and show that the relationship between network degree centrality and firm performance is negatively influenced by partners’ learning capacity and positively influenced by focal firms’ learning capacity, while firms with low network degree centrality benefit less from their learning capacity.

Future developments in transaction cost economics may consider partner and focal firms’ learning capacity as moderators of the network degree centrality – firm performance relationship.

In alliance decisions, managers must consider that the combination of high network degree centrality and partners’ learning capacity can lead to high costs, risks of unintentional learning, and structural inertia, all of which have negative consequences for performance. In concentrated industries where network positions are controlled by a few large firms, policymakers must acknowledge that firms may face substantial barriers to collaboration with learning-intensive firms.

This study is the first to develop and test a comprehensive transaction cost analysis of the central firm’s unintended knowledge flows and structural inertia in alliance networks. It is also the first to incorporate theoretically and empirically the hazards of complex and unintended information flows on the relationship of network degree centrality to performance in equity alliance portfolios.

The current study immerses in the realm of bank mergers among prominent PSBs in India, focusing on the financial performance of six recently merged PSBs entities. Amidst the global impact of the COVID-19 pandemic on economies, the study aims to uncover the efficiency of these PSBs in navigating this unprecedented crisis.

The evaluation encompasses panel data on an annual basis spanning from 2020 to 2023. To assess the overall efficiency of merged PSBs, the advanced statistical technique like one-step system generalized method of moments has been applied to estimate its efficiency.

The study findings affirm that PSB mergers have bolstered financial metrics and efficiency. Enhanced return on equity (ROA) and net profit margin (NPM) signify improved profitability and efficiency. The consolidation also facilitates better asset management and utilization. Moreover, merged entities benefit from economies of scale, cost efficiencies, risk diversification, technological investments, and overall performance improvements.

The study's policy suggestions stress ongoing consolidation efforts to boost banking sector resilience, advocating for improved efficiency, governance, and asset quality management. These steps are crucial for successful bank mergers and fostering a robust, competitive banking landscape in India.

This study is a novel attempt to analyze Indian bank profitability and efficiency post PSB mergers amid COVID-19 pandemic. In a developing country like India, especially in PSBs has experienced significant structural changes over the previous 7 years just before pandemic, such a study necessitates a prompt empirical investigation.

This article aims to evaluate the informativeness of accruals on stock prices. Investors may misinterpret the information contained in accruals and produce accrual anomalies. Accruals accounting improves the quality of financial statements by providing useful information, although it also contains judgments and is less objective than operating cash-flows.

We employ data panel regression analysis to investigate the value relevance of financial information. Our study takes the object of companies listed on the Nasdaq stock exchange (NASDAQ) as the representative of the prominent stock exchange for technology-driven enterprises and entrepreneurs. Expanding the findings, we also use Shanghai Stock Exchange (SSE) data.

Our research finds that accruals are still relevant. However, firms with R&D expenditures reduce the ability of accruals to explain stock prices for non-technology firms and firms without intangible assets. After analyzing only tech firms (and firms with intangible assets), our tests show that R&D expenditures improve the relevancy of accruals. These findings apply to both Nasdaq and SSE.

Practitioners and the investment community get valuable insights into how the recognition and measurement of R&D expenditures affect the value relevance. Information about R&D increases relevancy only in firms with intangible assets and those that operate in the technology industry.

Our paper provides benefits by using R&D expenses to affect accruals' informativeness by comparing two countries with different recognition of R&D.