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This chapter is a radical critique of the neoclassical growth theory, justifying ways out of mainstream economics. It has three parts. The first one analyzes growth theories from the Classical representation to the endogenous growth models. The second part demonstrates that the “new growth theory” is not a break with Solow's formalization. To prove it, we build an original Solowian endogenous growth model. Then, this neoclassical macrodynamic framework is technically, deeply critized in a third part. We show that both exogenous and endogenous neoclassical models prove to be incapable to explain growth in the long period. We concentrate on the ambiguities surrounding the hypothesis of single agent, as well as on the role of the state, in particular when it is considered as a “planner” by the neoclassicals. Endogenous growth models do not correspond to macrodynamization of the Walrasian general equilibrium, nor have solid microeconomic bases. We advocate in favor of rehabilitating state's intervention in social areas and of reactivating Marxist theoretical reflections regarding social planning and class analysis in the current time of structural crisis of the capitalist world system.

This paper aims to investigate the multi-faceted impact of host country risks on the success of private participation in infrastructure projects. The authors make a distinction between exogenous and endogenous risks, differentiating those that are completely beyond the control of the firm from those in which firms might exert some degree of influence to reduce the negative repercussions.

Drawing on logistic regression analyses, the authors analyze a sample of 10,350 private participation in infrastructure projects in 126 countries from 1997 to 2014.

The authors find that higher levels of exogenous risk are associated with a lower probability of project success, whereas they find no significant effect for endogenous risk.

By pointing to this differential effect, this study makes a contribution to the current debate in the literature on private participation projects.

This chapter proposes M-estimators of a fractional response model with an endogenous count variable under the presence of time-constant unobserved heterogeneity. To address the endogeneity of the right-hand-side count variable, I use instrumental variables and a two-step procedure estimation approach. Two methods of estimation are employed: quasi-maximum likelihood (QML) and nonlinear least squares (NLS). Using these methods, I estimate the average partial effects, which are shown to be comparable across linear and nonlinear models. Monte Carlo simulations verify that the QML and NLS estimators perform better than other standard estimators. For illustration, these estimators are used in a model of female labor supply with an endogenous number of children. The results show that the marginal reduction in women's working hours per week is less as women have one additional kid. In addition, the effect of the number of children on the fraction of hours that a woman spends working per week is statistically significant and more significant than the estimates in all other linear and nonlinear models considered in the chapter.

In the purview of stress–turnover relationship, the present study aims to explore the endogenous and exogenous aspects of stress and employees' turnover intentions. Further, it also intends to evaluate the mediating role of perceived employee's exploitation between stressors and employee turnover intentions. For that matter, antecedents of stressors were identified and classified into endogenous and exogenous stressors: endogenous stressors relate to the employees' negative psychological contact within an organization and exogenous stressors are various macro-economic factors which have a considerable influence on employees' workplace behavior.

For the purpose of this study, this study choses private school teachers as respondents working in the economically depressed state of India. Thus, data for the present study has been collected from 628 private school teachers of J&K (India) which were randomly selected. In order to ensure valid and reliable statistical inferences from the study, data collected has been validated using confirmatory factor analysis and hypothesis testing has been carried out through structural equation modeling.

It was found that both types of stressors were contributing negatively toward employee's psychological state resulting in undesirable employee organizational relationships manifested as turnover intentions among employees. Moreover, perceived employee's exploitation was found to intensify the relationship of employee turnover as a dependent variable regressed on endogenous, exogenous and occupational stress by fully mediating the stress–turnover intricacies.

The implications of the study include the identification of employees' stressor needs in order to gauge the understanding of the mechanism by which employees react to their environment and develop attitudes toward their jobs. The present study includes a small sample size obtained from private educational institutions only. Therefore, there is a need to take a geographically diverse sample that is inevitable for universal inferences and validity.

Very little research has been conducted to explore endogenous, exogenous and unique stressors such as economic stress and perceived external opportunities which constitute the overall stress. Moreover, to the best of the authors’ knowledge, this is the first study which tests the model empirically that examines the effect of stress–turnover relationship through perceived employee's exploitation in the teaching and educational sector.

The literature shows that e-commerce adoption brings many benefits to farmers and agricultural businesses. However, the literature offers very limited guidance on the most effective ways for them to utilize e-commerce platforms. In this study, we unfold how a farmer's choice between endogenous (their own) vs. exogenous (third-party) e-commerce platforms should be aligned with the external (support from agricultural cooperative) and internal (usage of quality labels) resources they can leverage and the performance goals they want to achieve (market expansion vs. price premium).

Our study draws on transaction cost economics (TCE) and resource-based theory (RBT) to test the conceptual model with data from a cross-sectional survey of 324 farmers from two provinces in PR China.

Our findings show that external and internal resources shed additional light on the effectiveness of endogenous vis-à-vis exogenous e-commerce platforms. For farmers who rely on exogenous e-commerce, support from an agricultural cooperative appears to be critical in increasing their market expansion. On the other hand, farmers seeking to earn a price premium should focus on developing their own e-commerce platforms, while at the same time emphasizing the quality labels of their agricultural products.

Farmers should pay close attention to the value-added benefits provisioned through farmers' cooperatives, as well as the benefits of acquiring quality labels for their agricultural products. However, the decision to utilize these resources should be aligned with the chosen e-commerce platform (endogenous vs. exogenous) as well as with the performance goal the farmer wants to achieve.

Our work goes beyond the traditional focus on transaction costs and efficiency of e-commerce channels and provides specific insights into when an endogenous or exogenous e-commerce model might provide benefits for farmers. On top of this, we argue and show that this decision should reside with the farmer's ability to leverage external and internal resources, envisioned through support from an agricultural cooperative and the quality labels of agricultural products.

The authors combine options logic with transaction cost economics to explain why firms maintain, divest or buy out their international joint ventures (IJVs). It is suggested that a decline in environmental risk and higher partner-related risk makes a firm more likely to acquire an IJV but less likely to divest an IJV. The study also investigates how IJV age moderates the effects of a decline in environmental risk and higher partner-related risk.

The study employs competing risks analyses to examine the drivers of different termination outcomes using a dataset consisting of 459 IJVs in the People's Republic of China, of which 110 were either acquired or divested by their foreign parent.

The study finds that changes in environmental risk and partner-related risk affect how firms terminate their IJVs in the People's Republic of China. Specifically, the authors find that the effect of exogenous and endogenous risk are more pronounced for the acquisition of IJVs than for the divestment of IJVs.

The study contributes to international marketing research by complementing options logic with transaction cost economics to provide a theoretical explanation of the different ways in which IJVs in the People's Republic of China are terminated.

IJVs continue to be an important yet often unstable method to serve international markets. Our findings increase managers' awareness of the effect that two important sources of risk may have on the termination of IJVs in the People's Republic of China.

The study provides novel insights into the effect that changes in exogenous and endogenous risk have on a firm's choice of termination mode drawing on novel data on the different ways in which foreign firms have terminated their IJVs in the Peoples' Republic of China.

This paper aims to investigate the effects of using poor-quality instruments to remedy endogeneity in logit-based demand models. Endogeneity problems in demand models occur when certain factors, unobserved by the researcher, affect both demand and the values of a marketing mix variable set by managers. For example, unobserved factors such as style, prestige or reputation might result in higher prices for a product and higher demand for that product. If not addressed properly, endogeneity can bias the elasticities of the endogenous variable and subsequent optimization of the marketing mix. In practice, instrumental variables (IV) estimation techniques are often used to remedy an endogeneity problem. It is well-known that, for linear regression models, the use of IV techniques with poor-quality instruments can produce very poor parameter estimates, in some circumstances even worse than those that result from ignoring the endogeneity problem altogether. The literature has not addressed the consequences of using poor-quality instruments to remedy endogeneity problems in non-linear models, such as logit-based demand models.

Using simulation methods, the authors investigate the effects of using poor-quality instruments to remedy endogeneity in logit-based demand models applied to finite-sample data sets. The results show that, even when the conditions for lack of parameter identification due to poor-quality instruments do not hold exactly, estimates of price elasticities can still be quite poor. That being the case, the authors investigate the relative performance of several non-linear IV estimation procedures utilizing readily available instruments in finite samples.

The study highlights the attractiveness of the control function approach (Petrin and Train, 2010) and readily available instruments, which together reduce the mean squared elasticity errors substantially for experimental conditions in which the theory-backed instruments are poor in quality. The authors find important effects for sample size, in particular for the number of brands, for which it is shown that endogeneity problems are exacerbated with increases in the number of brands, especially when poor-quality instruments are used. In addition, the number of stores is found to be important for likelihood ratio testing. The results of the simulation are shown to generalize to situations under Nash pricing in oligopolistic markets, to conditions in which cross-sectional preference heterogeneity exists and to nested logit and probit-based demand specifications as well. Based on the results of the simulation, the authors suggest a procedure for managing a potential endogeneity problem in logit-based demand models.

The literature on demand modeling has focused on deriving analytical results on the consequences of using poor-quality instruments to remedy endogeneity problems in linear models. Despite the widespread use of non-linear demand models such as logit, this study is the first to address the consequences of using poor-quality instruments in these models and to make practical recommendations on how to avoid poor outcomes.

The purpose of this paper is to provide further insights into understanding the finance‐growth nexus by verifying the hypothesis that financial development promotes economic growth through its capacity to attract increased international migrant remittances to Ghana.

A dynamic equilibrium‐correction mechanism model for the period 1987(3)‐2007(4) was estimated following the Johansen cointegration procedure. This approach produced maximum likelihood estimators of the unconstrained cointegrating vector, and suggested the number of cointegrating vectors without relying on an arbitrary normalization.

The findings reveal two stylized facts with reference to Ghana. First, although financial development Granger‐causes international migrant remittance inflows, it is in itself directly detrimental to endogenous growth. Second, international migrant remittance inflows are statistically significant in explaining variations in endogenous growth in the short run as well as in the long run.

Since directly, financial development hampers endogenous growth, but Granger‐causes increased inflows of migrant remittances, and these remittances impact positively but marginally on endogenous growth, it follows that the sequencing of implementing Ghana's financial reform programmes should be re‐examined, whilst an enabling environment is created to induce Ghanaians living abroad to remit home through official channels.

International migrant remittances were found to be statistically significant in promoting endogenous growth, albeit marginally. Financial development does not directly engender growth, unless it succeeds in attracting non‐debt foreign capital in the form of remittances through the formal sector. Financial development causes migrant remittance inflows which impact positively on growth.

This paper aims to study low adoption of modern technology for pearl millet in Rajasthan, India, from the perspective of social networks. The state has the lowest adoption of modern pearl millet seeds among Indian states. . In particular, this paper tries to identify the limitations of channels with endogenous effects, thereby limiting large-scale adoption of modern varieties that would require social multipliers.

Defining the network/reference groups in terms of social identity and geographical proximity, this paper utilizes the intensity of interaction with different network nodes to identify the presence of endogenous effects. In particular, this paper uses the interaction of intensity of social exchange with the group level adoptions to establish the presence of endogenous effects. With adequate controls, greater intensity of interaction having a bearing on technology choice can only happen when there exists social learning (endogenous effect) and cannot be associated with other forms of social effects (namely, exogenous and correlated effects).

This paper finds evidence for the existence of endogenous social effects in adoption but largely from exclusionary channels. A comprehensively mapped network is used with its intensity to explain the extremely low rate of adoption. Only close-knit networks that, with social fragmentation, limit benefits to few, affect adoption significantly. The non-functionality of less exclusionary information sources and services can be a factor underlying low adoption.

The main limitation of the study is inability to control for unobserved individual heterogeneity because of the cross-sectional nature of data. Further, although an extensive mapping of individual networks has been done, it still cannot be guaranteed to be exhaustive.

With fragmentation, large-scale adoption programs would require networks, sources of information and services that are less exclusionary. Based on the survey data, media and non-religious organizations play a focal role here in the adoption of modern technology. This finding is extremely crucial for policy, as these channels comprise direct policy levers in a fragmented society like India. Indeed, several government programs in India have relied on these channels to run large-scale adoption programs. Their ineffectiveness could be a prime factor for such limited dissemination of technology in Rajasthan.

In different settings, social fragmentation could be an important factor determining technology adoption outcomes. The evolving consensus in the literature based on several studies is that ethnic fragmentation has potentially negative consequences on macro-economic performance (Alesina and Tabellini, 1989 and Collier, 2000). In the literature on technology adoption, the role of fractionalization is somewhat under-studied. With fragmentation, there can be significant micro-level impacts (for instance, low technology adoption of a crop) if channels that are inclusive are not well developed. The finding that channels like extension services, media or organizations are not effective in determining choice of technology does not mean that they should not be tapped. The empirical findings suggest that, in their current form in the state of Rajasthan, the roles played by these are limited. The policy implications would be to develop these systems in a way that there is a greater uptake. Recall that less than 4 per cent of the respondents got information on seeds from media sources, an extremely low number. There is certainly scope for increasing the outreach of these channels that are much more important for spread of agricultural technology in a fragmented society.

This paper is an attempt to come up with an empirical strategy to mitigate the issues related to reflection problem. In the cross-sectional data itself, we use the interaction of group choices with intensity of interaction within the group to introduce a non-linearity that tries to bypass the identification issues as in reflection problem. This method of introducing non-linearity in cross-sectional data is a novel attempt to achieve identification of endogenous effects.

We show how to use a smoothed empirical likelihood approach to conduct efficient semiparametric inference in models characterized as conditional moment equalities when data are collected by variable probability sampling. Results from a simulation experiment suggest that the smoothed empirical likelihood based estimator can estimate the model parameters very well in small to moderately sized stratified samples.