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This chapter examines the limit properties of information criteria (such as AIC, BIC, and HQIC) for distinguishing between the unit-root (UR) model and the various kinds of explosive models. The explosive models include the local-to-unit-root model from the explosive side the mildly explosive (ME) model, and the regular explosive model. Initial conditions with different orders of magnitude are considered. Both the OLS estimator and the indirect inference estimator are studied. It is found that BIC and HQIC, but not AIC, consistently select the UR model when data come from the UR model. When data come from the local-to-unit-root model from the explosive side, both BIC and HQIC select the wrong model with probability approaching 1 while AIC has a positive probability of selecting the right model in the limit. When data come from the regular explosive model or from the ME model in the form of 1 + n^α/n with α ∈ (0, 1), all three information criteria consistently select the true model. Indirect inference estimation can increase or decrease the probability for information criteria to select the right model asymptotically relative to OLS, depending on the information criteria and the true model. Simulation results confirm our asymptotic results in finite sample.

In this chapter, we document the growing importance of FDI from BRIC countries in relation to FDI from both developed and developing countries and investigate the types of firms that are responsible for BRIC FDI.

We follow a two-step empirical approach. First, we provide macro evidence on FDI from BRIC countries. We use UNCTAD data to highlight the patterns of FDI flows and stocks. Second, we provide firm-level evidence on FDI. Using ORBIS data, we elaborate a rich taxonomy of FDI that accounts for the decision to invest abroad and for the location, ownership, and number of foreign subsidiaries. Thus, we characterize BRIC multinationals’ involvement in FDI and examine the relationship between FDI and performance at the firm level.

We unveil new facts about BRIC multinationals. BRIC multinationals are in the minority in their home countries, but they outperform domestic enterprises. Within the group of BRIC investors, those firms that invest in developing countries, that operate in joint ventures, or that have more than five foreign subsidiaries are in the minority, but they outperform those firms that select other FDI strategies.

Our estimates document a positive and robust correlation between FDI and performance; however, the cross-sectional nature of our data does not permit a proper causality analysis.

Our work contributes to the International Economics literature on internationalization and firm performance as well as to the International Business literature on FDI from emerging economies. With respect to the former, we innovate by studying the relation between FDI strategies and firm performance. In relation to the latter, we innovate by introducing firm-level data and a cross-country approach that lets us illustrate the roles and features of FDI from BRIC countries.

We investigate the role of market uncertainties as determinants of the adoption of control and prediction in the internationalization of small- and medium-sized enterprises (SMEs). Building on the possibility that uncertain markets may lead to trade-offs between these strategies, as suggested by the convergence between effectuation and internationalization research, we differentiate between uncertainties originated in SMEs’ home and host countries. We test our hypotheses with a cross-country data set encompassing 597 SMEs surveyed in Brazil, China, Poland, and Italy. Our results indicate that home-country uncertainty is related to the adoption of control strategies, while host-country cultural uncertainty is related to prediction efforts. Moreover, internationalization knowledge emerged not as a moderator of these relationships but as a relevant antecedent of both control and prediction. Our findings have implications for the use of effectuation in the study of SME internationalization and also for the conceptualization of the effectuation process itself.

We investigate the effect of distance – political, economic, cultural and spatial, on developed-economy multinational enterprises’ (MNEs’) ownership decisions in cross-border (CB) acquisitions. We start with the premise that distance discourages full and majority ownership in CB acquisitions, and further investigate the moderating role of distance-reducing factors. We examine how the relationship between distance and acquisition ownership decision is moderated by firm-specific characteristics, such as firm size, general international experience, and specific host country experience. Our data sample consists of 1,041 CB acquisitions under taken by Finnish MNEs in 58 countries during the time period 1990–2010. We find substantial support for all our hypotheses and conclude that the negative effects of distance on CB acquisition equity stake are positively moderated by the three firm-specific resources but their individual importance is conditional on the host country type (developed or emerging).

Vector Autoregression (VAR) has been a standard empirical tool used in macroeconomics and finance. In this paper we discuss how to compare alternative VAR models after they are estimated by Bayesian MCMC methods. In particular we apply a robust version of deviance information criterion (RDIC) recently developed in Li, Zeng, and Yu (2014b) to determine the best candidate model. RDIC is a better information criterion than the widely used deviance information criterion (DIC) when latent variables are involved in candidate models. Empirical analysis using US data shows that the optimal model selected by RDIC can be different from that by DIC.

The victim’s rights movement and restorative justice (RJ) have gained momentum around the world. More laws and policies have focused on crime victims and their families. Western literature suggests that the victim’s family suffers physical, emotional, and financial tolls and that the power of the victim’s family in pursuing justice for their loved ones remains limited. This is particularly concerning within the political and legal context of the abolitionist movement, innocence project, and human rights groups’ campaigns against police torture. Grounded in the perspectives of RJ and Chinese legal culture, this study examines the victim’s family, represented by Ding and senior Yu, of the Nian Bin capital murder case. Drawing on published reports and using the thematic content analysis method, this study examines the following aspects of victim’s family in a death penalty case: 1) victim family’s physical, emotional, and financial tolls; 2) victims’ family and the criminal justice system; 3) victims’ family and the media; and 4) the relationship between the victims’ and the accused’s families. This study concludes with discussions of the competing goals of families impacted by a crime and RJ practices that would help mitigate the loss of the victim’s family and enhance their confidence in the criminal justice system.

This chapter is a comprehensive discussion of autism spectrum disorder (ASD) across the globe (e.g., United States, China, Brazil, Japan and Turkey). Topics that are discussed include the following: diagnostic criteria and approaches; international perspectives of ASD; western and eastern assessment practices; cultural considerations of assessment of ASD; educational and medical interventions; behavioral and emotional interventions; complementary and alternative medical interventions; variations in educational services among countries; early intervention practices; adult services; national and international resources; and current needs and future directions.

This chapter reviews the recent developments at the intersection of personalization and AI in marketing and related fields. We provide a formal definition of personalized policy and review the methodological approaches available for personalization. We discuss scalability, generalizability, and counterfactual validity issues and briefly touch upon advanced methods for online/interactive/dynamic settings. We then summarize the three evaluation approaches for static policies – the Direct method, the Inverse Propensity Score (IPS) estimator, and the Doubly Robust (DR) method. Next, we present a summary of the evaluation approaches for special cases such as continuous actions and dynamic settings. We then summarize the findings on the returns to personalization across various domains, including content recommendation, advertising, and promotions. Next, we discuss the work on the intersection between personalization and welfare. We focus on four of these welfare notions that have been studied in the literature: (1) search costs, (2) privacy, (3) fairness, and (4) polarization. We conclude with a discussion of the remaining challenges and some directions for future research.

Due to the increasing size and complexity of construction projects, construction engineering and management involves the coordination of many complex and dynamic processes and relies on the analysis of uncertain, imprecise and incomplete information, including subjective and linguistically expressed information. Various modelling and computing techniques have been used by construction researchers and applied to practical construction problems in order to overcome these challenges, including fuzzy hybrid techniques. Fuzzy hybrid techniques combine the human-like reasoning capabilities of fuzzy logic with the capabilities of other techniques, such as optimization, machine learning, multi-criteria decision-making (MCDM) and simulation, to capitalise on their strengths and overcome their limitations. Based on a review of construction literature, this chapter identifies the most common types of fuzzy hybrid techniques applied to construction problems and reviews selected papers in each category of fuzzy hybrid technique to illustrate their capabilities for addressing construction challenges. Finally, this chapter discusses areas for future development of fuzzy hybrid techniques that will increase their capabilities for solving construction-related problems. The contributions of this chapter are threefold: (1) the limitations of some standard techniques for solving construction problems are discussed, as are the ways that fuzzy methods have been hybridized with these techniques in order to address their limitations; (2) a review of existing applications of fuzzy hybrid techniques in construction is provided in order to illustrate the capabilities of these techniques for solving a variety of construction problems and (3) potential improvements in each category of fuzzy hybrid technique in construction are provided, as areas for future research.