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This article investigates the long-run impact of remittance inflows on agricultural productivity (AGP) in emerging Asian economies (Bangladesh, Sri Lanka, Malaysia, India, Nepal, Philippines, Pakistan, and Vietnam), employing a panel dataset from 2000 to 2018.

This study initially applies cross-sectional dependence (CSD), second-generation unit root, Pedroni, and Westerlund panel co-integration techniques. Next, it uses the augmented mean group (AMG) and common correlated effect mean group (CCEMG) methods to investigate the long-term impact of remittance inflows on AGP while controlling for several other important determinants of agricultural growth, such as cultivated area, fertilizers, temperature change, credit, and labor force.

The empirical findings are as follows: The results first revealed the existence of CSD and long-term co-integration between AGP and its determinants. Second, remittance inflows significantly boosted AGP, indicating that remittance inflows played a crucial role in improving AGP. Third, global warming (changes in temperature) negatively impacts AGP. Finally, additional critical elements, for instance, cultivated area, fertilizers, credit, and labor force, positively affect AGP.

This study suggests that policymakers of emerging Asian economies should develop an exclusive remittance-receiving system and introduce remittance investment products to utilize foreign funds and mitigate agricultural production risks effectively.

This is the first empirical examination of the long-term impact of remittance flows on agricultural output in emerging Asian economies. This study utilized robust estimation methods for panel data sets, such as the Pedroni, Westerlund, AMG, and CCEMG tests.

The purpose of this study is to examine the impact of paradoxical leader behavior (PLB) on leader effectiveness (LE). The authors propose an underlying mechanism of this relationship and examine if the stated relationship is moderated by job-related and structural uncertainty in the organization.

The authors draw on survey data from 127 employees working in public and privately owned organizations and analyze data using AMOS and SPSS.

Results offer partial support to the authors’ hypotheses indicating that paradoxical leader behavior is positively associated to LE. As expected, the relationship is negatively moderated by structural uncertainty indicating that LE is weakened where there is structural uncertainty in the organization. However, in contrast to our other assumption, the authors find a positive (rather than negative) moderating role of job-related uncertainty in the PLB–LE relationship.

Paradoxes are everywhere and inherently embedded in complex and dynamic organizational systems. To deal with paradoxes, organizational leaders often seek to act paradoxically. However, not every leader has a paradoxical mindset, and where a leader has such, it remains unclear if they will prove to be effective leaders. What can further influence the effectiveness of such leaders is the uncertainty that organizations face in the today’s dynamic environments. In this study, the authors contribute to paradox theory and the paradoxical leadership literature by unfolding the boundary conditions which can influence paradoxical leader’s effectiveness.

The purpose of this paper is twofold. The first is to explore the convergence of corporate governance (CG) codes of 11 Asian emerging economies with the United Nations (UN) CG guidelines (United Nations Conference on Trade and Development ISAR benchmark). The second is to find the compliance level of firms in each country with the UN CG guidelines.

Based on the 2017 GDP growth rate, the top 11 emerging economies were selected. CG codes of each country were then analyzed by using content analysis to find the convergence level with the UN CG guidelines. To find the compliance level of individual firms in each sample country, a sample of the top 15 non-financial listed firms were selected from each country, and their annual reports were analyzed. The binary scoring method was used.

After analyzing the 11 national CG codes, 1 UN CG guidelines and 150 annual reports, this study found that Pakistan and Philippines CG codes have the highest level of convergence toward the outsider model recommended by UN CG guidelines, whereas China and India have the lowest compliance score. The Indian, Chinese, Malaysian and Indonesian listed firms showed more compliance toward the UN CG guidelines than their respective national CG codes.

By analyzing the top 11 emerging economies, and top 15 listed enterprises in each country, this study offered a combined convergence and compliance evidence at two different levels, i.e. country and firm-level. This study’s findings would be equally helpful for regulators, policymakers and investors in assessing their country’s CG codes against the international recommended best practices.

The purpose of the paper is to examine the impact of infrastructure investment and development on economic growth in Brazil, Russia, India, China and South Africa (BRICS) countries. The effect is examined for each country separately and also collectively by combining each country.

Ordinary least square regression method is applied to examine the effects of infrastructure investment and development on economic growth for each country. Panel data techniques such as panel least square method, panel least square fixed-effect model and panel least square random effect model are used to examine the collective impact by combining all countries in BRICS. The dynamic panel model is also incorporated for analysis in the study.

The results of the study are mixed. The association between infrastructure investment and development and economic growth for countries within BRICS is not robust. There is an insignificant relationship between infrastructure investment and development and economic growth in Brazil and South Africa. Energy and transportation infrastructure investment and development lead to economic growth in Russia. Telecommunication infrastructure investment and development and economic growth have a negative relationship in India, whereas there is a negative association between transport infrastructure investment and development and economic growth in China. Panel data results conclude that energy infrastructure investment and development lead to economic growth, whereas telecommunication infrastructure investment and development are significant and negatively linked with economic growth.

The study is novel as time series analysis and panel data analysis are used, taking the time span for 38 years (1980–2017) to investigate the influence of infrastructure investment and development on economic growth in BRICS Countries. Time-series regression analysis is used to test the impact for individual countries separately, whereas panel data regression analysis is used to examine the impact collectively for all countries in BRICS.