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During the last few decades, there have been significant divergences in the flows of foreign direct investment (FDI) as per decisions taken by multinational companies (MNCs), and many of the developing nations in the Asia and Pacific region are most remarkable in this regard (UNCTAD, 2015). Apart from various economic factors, some sociopolitical issues have also been identified as influencing the FDI decisions. This study investigates the comovements of the standard measures of terrorist activities and MNCs’ decision on FDI in selected developing countries in the Asia and Pacific region by employing Generalized Method of Moment (GMM) estimation technique on constructing a balanced panel for 1990–2016. Results summarize that FDI inflows are negatively influenced by terrorist activities in the developing economies of the Asia and Pacific region.

The recent rise of nonperforming loans (NPLs) in some Asian economies calls for close analysis of the determinants, the potential macrofinancial feedback effects, and the implications for financial stability in the region. Using a dynamic panel model, we assess the determinants of the evolution of bank-specific NPLs in Asia and find that macroeconomic conditions and bank-specific factors – such as rapid credit growth and excessive bank lending – contribute to the buildup of NPLs. Further, a panel vector autoregression (VAR) analysis of macrofinancial implications of NPLs in emerging Asia offers significant evidence for feedback effects of NPLs on the real economy and financial variables. Impulse response functions demonstrate that a rising NPL ratio decreases the GDP growth, credit supply and increases the unemployment rate. Our findings underline the importance of considering policy options to swiftly and effectively manage and respond to a buildup of NPLs. The national and regional mechanisms underlying NPL resolution are important for safeguarding financial stability in an increasingly interconnected global financial system.

The greatest challenge facing most economies today is how to grow their economies and reduce over-dependence on imports in the midst of increasing integration of world economies. Addressing this challenge seems to be difficult despite all efforts by policymakers at different times to salvage the situation, the problem persists as evident in the global financial crisis of 2008 and the Eurozone crisis of 2012 which were generally viewed as a glaring illustration of limitless pursuit of economic integration and governance failure at the expense of carefulness, prudence, due diligence, and regulation. It also reflects the lack of proper coordination and lack of proper economic integration facing most emerging market economies of the world. Against this background, this study focuses on the reexamination of the impact of trade openness (TOP) and financial openness (FOP) on economic growth in emerging market economies. The direct and interaction effect of the both openness variables on economic growth in these markets is investigated using data from 2000 to 2017 adopted from World Development indicators of the World Bank. Over 30 emerging market economies covering Asia, Latin America, and Europe are included in the study. For empirical analysis, the study uses one measure of FOP: de facto (total capital flow) variables following Aizenman and Noy (2009) and a measure of TOP as total trade–GDP ratio. The study applies the Dynamic Panel Approach, that is, the Arellano–Bond GMM estimation technique and Granger Causality Test to address the objectives. The results of this study show that TOP has a positive and significant impact on all the countries studied, whereas FOP has positive but no significant impact on economic growth of these countries, implying that these countries have not harnessed the benefit of financial liberalization and integration. It is recommended that the emerging market economies should open not only their economies to trade but also open their economies to finance so as to reap the benefits of FOP and integration.

This chapter explores the major drivers of capital structure, which is measured by using two alternative measures (total debt/equity and total debt/total assets), for Romanian firms. By employing panel-data models for a sample of non-financial companies publicly traded on the Bucharest Stock Exchange, this research examines how capital structure of the Romanian firms are affected by CEO age and several firm-specific characteristics including free cash flow, return on assets (ROA), return on invested capital (ROIC), effective tax rate, dividend payout ratio, cash ratio, current ratio, and quick ratio, where firm-level controls (total assets and firm age) are adopted. Using fixed effects estimation on panel data, we find: (1) ROIC, dividend payout ratio and liquidity ratios all negatively affect capital structure; (2) whereas ROA provides evidence of its mixed role on capital structure. Robustness checks using the generalized method of moments reinforce the negative impact of dividend payout ratio and the mixed influence of ROA, and document the varied effects of liquidity measures on capital structure.

The authors propose a framework to estimate the probability of being poor in a dynamic setting based on a large information set that includes individual characteristics and macro-economic variables. The joint inclusion of personal characteristics along with contextual factors allows separation of idiosyncratic shocks from aggregate shocks affecting poverty. The authors combine data from different cross-sectional surveys and fit a dynamic logistic hierarchical model within a Bayesian framework using standard Markov chain Monte Carlo techniques. The authors’ approach is exemplified by estimating household poverty status in Kyrgyz Republic as a function of time, regions, country, regional level variables and household level socio-demographic characteristics.

In view of discussion of two crises, Asian Financial crisis, 1997 and global meltdown, 2008 spreading over more than two decades, the objective of this article is to present econometrically whether productivity growth across countries can be a remedial measure toward tackling global recession pervaded during recent two or three decades worldwide and also to shed light on the aspect of whether productivity can truly act as a driver of growth of selected six economies like Korea Republic, Japan, India, China, USA, UK, and world economy as a whole. The panel data for the six selected countries for the period 1990–2018 were constructed keeping eyes on the 1997 Asian financial crisis and then the 2008–09 global economic crisis and a random effects model was applied after Hausman test. The empirical findings disclosed that the impacts on the growth of economies (represented by growth of GDP) from the growth rates of the manufacturing sector, labor productivity of manufacturing sector, and labor quantity are positive and statistically significant; while the effects of growth of the capital deepening and labor composition on economic growth of those sampled countries are statistically significant but negative. Some key factors that are likely to affect future productivity performance are centered on some issues like facilitating global learning spillovers; allowing productive firms to thrive; and making the most of human capital that should be taken care of.

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.

The contributions of this chapter are to establish (a) simultaneous dependence between female labor force participation rate (FLFPR) and their health status measured by the life expectancy; (b) the roles of (i) air pollutants in explaining female life expectancy (FLE); and (ii) joint interactions of different explanatory variables in determining both FLFPR and FLE, by estimating a simultaneous panel model comprising equations of FLFPR and FLE, using Baltagi’s Instrumental-Variable EC2SLS method and 13 major Indian state-level data for urban sector, over 2004–2005 to 2011–2012. The air pollutants (measured by prevalence of SO₂ and NO₂) have significant negative impacts on FLE. The interaction effect of air pollutants with economic growth on FLE is negative implying that the partial effect of a change in growth depends on air pollution level. FLFPR can be improved by reducing air pollution through health, as FLE significantly affects FLFPR positively. The roles of other socioeconomic variables affecting FLFPR and FLE are also evident.

The economic growth of any country depends largely on the entrance to international capital inflows, that is, external investment and its optimum allotment to components of different economic sectors. In several ways, foreign direct investment (FDI) helps by creating employment opportunities and rapid economic growth in emerging countries through capital flows in the developed countries and under developed countries. Many factors are affecting the FDI inflows in emerging countries among such determinants environmental issues are play a crucial role. Pollution control, air cleaner, water cleanness, etc., are the part of the environmental regulation in any country. Carbon dioxide (CO₂) emission and sulphur dioxide (SO₂) emission are major components of air pollution that have been widely used in empirical studies. The study intends to explore the impact of environmental regulations on FDI inflows in emerging countries along with governance factors and the macroeconomic fundamentals like per capita power consumption, trade openness, per capita GDP, etc. Based on the statistical data of 15 emerging countries from 2000 to 2015, the study follows the static panel data approach to empirically find the impact of environmental issues on FDI inflows. The results reveal that significant bonding realise between environmental regulations and FDI inflows in emerging countries. Based on the statistical evaluation however best our knowledge FDI is more attractive where lower regulations are established. For sake of simplicity environmental regulations are crucial to the multinational corporations (MNCs) for investment.

There are many channels through which terrorism can influence macroeconomic variables, such as economic growth and international trade. However, the intensity of the consequences of terrorist events on the economy may be varied across countries based on the economic structure. Therefore, it is not unusual for the impacts of terrorism to vary across the developed and developing nations. Against this backdrop, this study assesses the influences of conflicts and terrorist activities on the growth of per capita gross domestic product (GDP) in 21 developed and 23 developing countries from 1970 to 2015. The stochastic properties of the variables are looked into by carrying out panel-specific Augmented Dicky-Fuller (ADF) and Phillips-Peron (PP) unit root test followed by estimating the dynamic regressions equations in structured balanced panel frameworks for selected developed and developing economies separately. This study draws on data from various sources namely, Global Terrorism Database (GTD) and World Development Indicators (WDI; World Bank). Our empirical findings imply that terrorist activities have a significant growth-limiting effect, and the extent and significance of impacts are higher in case of developing economies.