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Diverse understanding of corporate social responsibility (CSR) abounds among scholars and practitioners in Nigeria. The purpose of this chapter is to reinvent CSR in Nigeria through a deeper understanding of the meaning and theories of this nebulous concept for better application in the industry. The qualitative research approach is adopted, relying on critical review of scholarly articles on CSR, website information of selected companies and institutional documents. It was found that there are diverse meanings of CSR in the reviewed literature, but the philanthropic initiatives and corporate donations for social issues are the common CSR practices in Nigeria. Besides, the eight dominant theories of CSR that find relevance for applications in the industry are shareholder/agency, stakeholder, legitimacy, instrumental, social contract, conflict, green and communication theories. The implication of the discourse is that better understanding and application of CSR theories would strengthen conceptual, theoretical and empirical research in the field of CSR. Besides, CSR theories are useful sources of information for practitioners for designing social responsibility policies and practices as well as for providing scholars with sound theoretical framework for academic research.

The present century is an age of knowledge-based economy. Higher education is in the process of transformation and thereby challenging the traditional system of education in India. The present paper reviews the current conditions of ICT use by the students in higher education in India. The major objectives of the study are (1) assessment of the use of computer and Internet by the students of higher education in India and (2) to find the determinants of use of ICT by the students in India. The study uses the NSSO 71st Round Unit Level Data on Social Consumption: Education Survey (71st Round, 2014). The present paper is based on 6,035 students from all the regions in India out of which 3,127 students were from the rural area and 2,908 from the urban area. The findings from logit analysis suggest that the determinants of ICT use by the students in higher education in India are regional disparities, gender, education levels of households, type of courses pursued by the students, type of institutions, access to computer and Internet facility, consumption levels of households, and students' residence type.

The critical issue in the debate over the pollution haven hypothesis (PHH) is whether the location choice of international investment is influenced by the stringency of environmental regulation. So far previous empirical studies focused on the outward investment from developed countries, while little work has been done on the issue from developing countries. To fill the gap, this paper selects data from China enterprises, using a Logit estimation to determine whether there is a pollution haven effect in the location choice of developing countries’ outward investment. Our results show that Chinese enterprises are attracted by countries with lax environmental regulations; resource-intensive enterprises from China are more sensitive to the stringency of regulation than are technology-intensive enterprises. We contribute to the literature in two ways. First, we provide new evidence in support of the PHH by analyzing investment from developing countries. Further, we show that differences exist in the FDI behavior between resource-intensive and technology-intensive enterprises. Based on this finding, we explain why some previous studies have not found robust evidence of the PHH.

The most used spatial regression models for binary-dependent variable consider a symmetric link function, such as the logistic or the probit models. When the dependent variable represents a rare event, a symmetric link function can underestimate the probability that the rare event occurs. Following Calabrese and Osmetti (2013), we suggest the quantile function of the generalized extreme value (GEV) distribution as link function in a spatial generalized linear model and we call this model the spatial GEV (SGEV) regression model. To estimate the parameters of such model, a modified version of the Gibbs sampling method of Wang and Dey (2010) is proposed. We analyze the performance of our model by Monte Carlo simulations and evaluate the prediction accuracy in empirical data on state failure.

This chapter estimates the demand for flights in an international air travel market using a unique dataset with detailed information not only on flight choices but also on contemporaneous prices and characteristics of all the alternative non-booked flights. The estimation strategy employs a simple discrete choice random utility model that we use to analyze how choices and its response to prices depend on the departing airport, the identity of the carrier, and the departure date and time. The results show that a 10% increase in prices in a 100-seat aircraft throughout a 100-period selling season decreases quantity demanded by 7.7 seats. We also find that the quantity demanded is more responsive to prices for Delta and American, during morning and evening flights and that the response to prices changes significantly over different departure dates.

The authors examine whether or not applicants and recipients of federal disability insurance (DI) inflate their self-assessed health (SAH) problems relative to others. To do this, the authors employ a technique which uses anchoring vignettes. This approach allows them to examine how various cohorts of the population interpret survey questions associated with subjective self-assessments of health. The results of the analysis suggest that DI participants do inflate the severity of a given health problem, but by a small but significant degree. This tendency to exaggerate the severity of disability problems is much more apparent among those with more education (especially those with a college degree). In contrast, racial minorities tend to underestimate severity ratings for a given disability vignette when compared to their white peers.

Claims and disputes are often unavoidable in the construction industry due to its unique and complex characteristics involving the massive investment of capital, lengthy project duration, and multiple project stakeholders. This chapter intends to identify the critical construction claims attributes, compare the perceptions of major stakeholders on different claim attributes, and investigate the contrast of the top five claim attributes between this study and previous ones. The literature review resulted in 48 claim attributes responsible for the construction project schedule delays. These attributes were then presented to Vietnam construction industry (VCI) practitioners in the form of a questionnaire survey. Data analysis was done based on the collected 113 qualified samples. Relative importance index (RII) was applied to determine the ranking of claim attributes. The results were that the top five causes of claims, that is, payment delays, mistakes by contractor during construction stage, delays in work progress by the contractor, financial failure of the contractor, and frequently changing requirements by the owner, lead to the schedule delays in VCI. These findings can assist the local industry practitioners and foreign companies seeking a share in the VCI market in understanding the causes of construction claims comprehensively and formulating the countermeasures to minimise their impacts and hence reduce the unnecessary losses and raise the likelihood of success as well as maintain sustainable relationships among stakeholders.

Regression discontinuity (RD) models are commonly used to nonparametrically identify and estimate a local average treatment effect. Dong and Lewbel (2015) show how a derivative of this effect, called treatment effect derivative (TED) can be estimated. We argue here that TED should be employed in most RD applications, as a way to assess the stability and hence external validity of RD estimates. Closely related to TED, we define the complier probability derivative (CPD). Just as TED measures stability of the treatment effect, the CPD measures stability of the complier population in fuzzy designs. TED and CPD are numerically trivial to estimate. We provide relevant Stata code, and apply it to some real datasets.

There is a rich literature which states that India did not suffer much from the impacts of the US financial crisis, but there is a school of thought which believes that the idea of India being insulated or decoupled from the contagion on account of limited integration into the world economy has been proved to be wrong. What is interesting is the focus has always been on the services sector and not on the manufacturing sector in India. In this background, this chapter tries to understand whether manufacturing sectors' productivity growth was one of the reasons that the crisis worsened in India or was it because of the crisis that India's manufacturing sector went into a deep recession. To look into the causality issue, the author estimates the productivity loss index (PLI) for the Indian industries during the period between July 2007 and July 2010 by estimating the fall in growth percentages in consecutive months for a total of 9,000 manufacturing, mining, and electricity industries. The data at monthly level have been retrieved from the Centre for Monitoring Indian Economy (CMIE) Prowess database. Based on the causality results, the chapter shows that it was because of the subprime crisis that India's manufacturing sector went into a deep recession. Using a probit model, the chapter also estimates the probability of the US subprime crisis being responsible for the productivity loss in India's manufacturing sector during the above-mentioned period.

This paper seeks to explain the serial persistence as well as the substantial number of zeros characterizing global bilateral investment holdings. We explore the different sources of serial persistence in the data (unobserved country pair effects, genuine state dependence, and transitory shocks) and examine the crucial factors affecting the decision to invest in a host country.

Based on a gravity setup, we consider investment behavior at the extensive (participation) margin and employ dynamic first-order Markov probit models, controlling for unobserved cross-sectional heterogeneity and serial correlation in the transitory error component, in order to explore the sources of persistence. Within this modeling framework we explore the importance of institutional quality of the host country in attracting foreign investment.

The data support that the strong persistence is driven by true state dependence, implying that past investment experiences strongly impact on the trajectory of future investment holdings. Institutional quality appears to play a significant role to attract foreign investment.

The empirical findings suggest that due to the existence of genuine state dependence, inward-investment stimulating policy measures could have a more pronounced effect since they are likely to induce a permanent change to the future trajectory of inward investment.

Both the substantial number of zeros and the salient persistence characterizing bilateral investment holdings decision have been previously overlooked in the literature. A study modeling jointly the levels and the selection mechanism could prove a fruitful direction for future research.