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This chapter develops robust panel estimation in the form of trimmed mean group estimation for potentially heterogenous panel regression models. It trims outlying individuals of which the sample variances of regressors are either extremely small or large. The limiting distribution of the trimmed estimator can be obtained in a similar way to the standard mean group (MG) estimator, provided the random coefficients are conditionally homoskedastic. The authors consider two trimming methods. The first one is based on the order statistic of the sample variance of each regressor. The second one is based on the Mahalanobis depth of the sample variances of regressors. The authors apply them to the MG estimation of the two-way fixed effects model with potentially heterogeneous slope parameters and to the common correlated effects regression, and the authors derive limiting distribution of each estimator. As an empirical illustration, the authors consider the effect of police on property crime rates using the US state-level panel data.

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.

This paper not only aims to validate the environment Kuznets curve concerning five Asian economies but also attempts to analyze the impact of some additional factors like financial development, energy consumption and foreign direct investment (FDI) on carbon emissions.

This paper applies pooled mean group approach on the variables of a panel of five Asian economies namely India, Pakistan, Bangladesh, Sri Lanka and Malaysia for a period of 35 years from 1980 to 2014.

This study finds that while moderate economic growth as well as moderate financial development increase carbon emissions, accelerated or exponential economic growth as well as exponential financial development eventually reduce the level of carbon emissions. Energy consumption was found to have a direct and significant relationship with carbon emissions. FDI inflows when analyzed on a stand-alone basis were observed to have an inverse relationship with carbon emissions, while FDI inflows when clubbed with financial development were observed to have a direct relationship with carbon emissions.

The findings of this study, which validate the environmental Kuznets curve, suggest striving for higher economic growth, even if it causes increased carbon emissions to begin with, as the effects on carbon emissions would eventually get reversed when the economic growth accelerates at a higher rate. This study also suggests the appropriate routing of FDI through a mature and developed financial sector to leverage its impact on the environment in a positive way.

To the best of the knowledge of the authors of this paper, there has not been any research carried out so far, which has analyzed the impact of the combination of variables selected for this study concerning the five Asian economies covered in this paper.

The widening income gap between rich and poor has gained worldwide recognition in recent decades. This income gap between rich and poor is defined as the extent of income unevenly distributed in a host country. This study provides an empirical view of the association between information and communication technology and the widening of the income gap.

The study used panel data from 2005 to 2019. To detect unit root issues, Levin and Lin (LL) and Im, Pesaran and Shin (IPS) tests were first employed. The pooled mean group and mean group estimators were employed to investigate the short and long -term impact of information and communication technology and other control factors on reducing the gap between rich and poor in South Asia.

The results showed that the Pooled mean group's findings are more efficient and consistent as compared to mean group estimators. The results of the paper showed that the greater penetration of information and communication technologies in the economy negatively and significantly affects income inequality. Moreover, the information and communication technology, foreign remittances and foreign direct investment (FDI) significantly reduce the gap between rich and poor in the long run.

At last, the findings of the study serve as an excellent roadmap for policymakers seeking to address the issue of growing income inequality in the South Asian regions and worldwide.

Based on the findings of this study, South Asia can reduce the gap between rich and poor by investing more in the information and communication technology sector.

The peer review history for this article is available at: https://publons.com/publon/10.1108/IJSE-10-2021-0638

For more than four decades, persistent economic activities and a focused growth strategy resulted in significant infrastructural and other favorable economic and institutional changes in the world's developing nations. High-quality growth is not just a function of sound economic policies but also implementing a broad range of social policies. The BRICS (Brazil, Russia, India, China and South Africa) nations have proven their testimony on both these factors. Following their path are some other emerging economies like N-11 (or Next Eleven propounded by Goldman Sachs (2005) Report), which this present study tries to examine as successors of BRICS.

Along with panel data regression modelling, the study has applied econometric procedures robust to heterogeneities across various nations and have been able to produce more reliable results that can be generalized for other similar groups of countries. 11 independent variables (both economic and institutional) have been used to meet the study's objective for a period of 34 years (1985–2018).

The findings of the study reveal that the governments of both the group of countries must work toward their macro-economic stability factors (external debt stocks), technological capabilities (mobile and fixed broadband subscriptions), human capital (health expenditure) and political conditions (mainly the rule of law) to enhance their sustainable economic growth.

This study enhances knowledge of the determinants of economic growth in emerging countries. Firms from BRICS and N-11 may better understand the factors influencing their internationalization process (both economic and institutional). The study is significant not just for the researchers but also for the policymakers of the BRICS and N-11 to understand in which areas their country is leading or lagging. The study is useful even for the policymakers of other emerging countries of the world who might take lessons from these nations (especially BRICS) and follow their success path. This study helps the governments of other groups of emerging countries such as PIN (Pakistan, Indonesia and Nigeria); MINT (Mexico, Indonesia, Nigeria and Turkey); CIVETS (Colombia, Indonesia, Vietnam, Egypt, Turkey and South Africa), etc. which can follow the path of BRICS economies in growth and formulate policies to increase their economic growth accordingly. At the enterprise level, it helps MNCs understand BRICS and N-11 markets and formulating entry and growth strategies in these most emerging countries of the world.

The present study is unique. It tries to investigate the projections of the Goldman Sachs report after 15 years of its release. It tries to determine the factors responsible for the economic development in the N-11 countries with advanced econometric techniques. Majorly, the focus is to comparatively analyze the growth trajectory for BRICS and N-11 nations and suggest whether N-11 has the potential to become successors of BRICS. A concentrated effort to examine the most significant drivers (both economic and institutional), which may lead to economic progression, has been made in this study.

This paper is motivated by a concern about the ability of the average Malaysian income to catch up with the rapidly increasing house prices in Peninsular Malaysia. Financial innovation in financial system now regards houses as a financial asset and speculation vehicle. Therefore, a house purchase is made to acquire not merely a necessity but also a financial asset which can generate future returns. Given the problems in the housing market, this paper aims to examine the determinants of house prices in Malaysia, including those such as income, population, foreign inflow and speculation.

This study adopts panel data analyses, namely, the fixed effect model (FEM) and the pooled mean group (PMG), and uses data at state level in quarterly frequency, spanning from 2005Q1 to 2013Q4.

Based on the results of FEM, these determinants influence house prices significantly. Moreover, the PMG results suggest that there is convergence in the model, which are indicated by the significant and negative sign of the error correction term. In conclusion, the rapidly increasing house price is not caused by speculation activities in the housing market. More precisely, Malaysian income is capable of catching up with the increasing house prices.

As income remains to be one of the major drivers in influencing Malaysian house price, Malaysian Government shall continue the policies of supply low cost houses to the low-income groups and My First Home Scheme (SRP) by offering less stringent rules in applying house loan for the first-time house buyers.

This study used the actual data of foreign housing purchase obtained from Malaysia Valuation and Property Services Department to represent foreign inflow; therefore, the results will reflect the impact of foreign inflow in a better manner.

The continuous increase in the negative gap between biocapacity and ecological footprint has remained globally persistent since early 1970. The purpose of this study is to examine the effect of foreign capital, domestic capital formation, institutional quality and democracy on ecological footprint within a global panel of 101 countries from 1995 to 2017.

The empirical procedure is based on data mix. To this end, this study uses a battery of testing and estimation approaches both conventional (no cross-sectional dependence [CD]) and novel approaches (accounting for CD). Among the battery of estimation techniques used, there are the dynamic ordinary least square, the mean group, the common correlation effect mean group technique, the augmented mean group technique, the Pooled mean group and the dynamic common correlation effect technique with the desire to obtain outcomes robust to heteroskedasticity, endogeneity, cross-correlation and CD among others.

The estimated outcomes indicate that using different estimators’ domestic capital formation consistently degrades the environment through an increase in ecological footprint, while institutional quality consistently enhances the quality of the environment. Further, the outcome reveals that, though foreign capital inflow degrades the environment, the time period is essential, as it shows a short-run environmental improvement and a long-run environmental degradation. Democratic activities show a mixed outcome with short-run degrading effect and a long-run enhancement effect on environmental quality.

Green investment should be the policy target of all economies, and these policies should be adopted to target both domestic capital and foreign capital alike. Second, the adoption of democratic practices will produce good leaders that will not just design short-term policies to blindfold the populace temporary but those that will produce long-term-oriented practices that will better and enhance the quality of the environment through the reduction of the global footprint. Equally, enhancing the institutional framework like respect for the rule of law in matters of abatement should be encouraged.

Although much research on the role of macroeconomic indicators on environmental quality has been done this far, democratic practices, intuitional quality and domestic capital have been given little attention. This research fills this gap by considering robust empirical techniques.

This paper explores whether data back the claim that imports of armaments are inherently bad for economic growth. Regardless of one's point of view, the production and trade of weaponry is a significant industry with serious economic implications that warrant investigation. The financial repercussions of military spending have been extensively studied, but the economic effects of arms importation remain unknown.

This study adopts a pooled mean group approach to investigate the nexus between arms imports, military expenditure and per capita GDP for a balanced panel of twenty-five of the top arms importers in the world from 2000 to 2021.

The authors find that arms imports and military spending negatively impact GDP per capita in the short run, but military spending is beneficial over the long run. The authors also used the Dumitrescu Hurlin Granger causality test, which revealed a unidirectional causation between per capita GDP and military expenditure, and a unidirectional causal relationship from military spending to arms imports.

This paper is deficient in a few aspects: first, it looks at only those countries comprising the top 70% of arms imports. Second, it omits many political, technological and legal factors that impact arms imports and military expenditures.

This paper looks into the impact of defense spending and arms imports on economic growth for twenty-five nations with the highest share of arms imports in recent times. It is a significant addition to the literature as it resolves the debate of whether or not the military expenditure is wasteful and whether arms imports significantly harm the nation's economic growth.

This paper aims to examine the influence of key macroeconomic factors on the inward and outward acquisition activities of six ASEAN (ASEAN: Association of Southeast Asian Nations) countries, namely, Indonesia, Malaysia, the Philippines, Singapore, Thailand and Vietnam, over the 1996-2015 period.

The study uses alternative panel data methods, including pooled mean group, mean group and dynamic fixed-effect estimators.

The results indicate that gross domestic product (GDP), interest rate, exchange rate, money supply and inflation rate are the most important macroeconomic factors explaining the trends of cross-border mergers and acquisition outflows of the ASEAN-6 countries. Specifically, GDP, money supply and inflation rate have significant positive relationships with acquisition outflows, while interest rate and exchange rate exert significant negative influence. On the other hand, the authors find four significant macroeconomic factors explaining the trends of the inward acquisitions. Essentially, GDP, money supply and inflation rate have significant positive impacts on inward acquisitions, while the impact of exchange rate is negatively significant.

Unavailability of data limits this study to pool six sample countries from ASEAN, instead of ten representative member countries.

The results of this study can signal to firms or investors, involving in cross-border mergers and acquisitions, where to direct foreign resources flows. Moreover, having the knowledge about the relative levels of market size and other macroeconomic factors in both home and host countries can be of great importance for investment decision. Therefore, policymakers of ASEAN countries should make appropriate macroeconomic policies that can stimulate inward and outward acquisitions.

The main contribution of this paper is that it is the first to present the analysis of macroeconomic influences on the trends of inward and outward merger and acquisition activities in six ASEAN countries.

This study aims to examine the relationship between exchange rate risk and export at commodity level for the Indian case.

The monthly panel data used for analysis are at a disaggregated level, which cover around 100 products, encompassing all merchandize sectors for the period spanning from 2012:12 to 2017:11. To measure the exchange rate volatility, the authors use real as well as nominal exchange rate concepts and predict the volatility of exchange rate using the autoregressive conditional heteroscedastic-based model. They use pooled mean group, mean group and common correlated effects mean group estimator that is suitable for the objectives and data frequency.

The empirical analysis indicates both short- and long-term negative effects of exchange rate variations on exporting. Specifically, in the long run, real exchange rate as well as nominal exchange rate volatility has significant effects on export performance, yet, the effects of uncertainty of nominal exchange rate is much severe and intense. In the short run, it is the nominal exchange rate uncertainty that hurts exports from India. Nevertheless, the short-run effect is much lesser than the long-run, supporting the argument that the short-term exchange rate risk can be hedged, at least partially, through financial instruments; however, uncertainty of the long-term horizon cannot be hedged easily and cost-effectively.

Reducing uncertainty and attaining stability in exchange rate and price level should be an important policy objective in developing countries such as India to achieve higher export growth, both in the short and long run.

Unlike previous studies, this paper tests the relationship using micro-level data and uses advanced econometric techniques that are likely to provide more precise information regarding the association between exchange rate volatility and trade flows.