A fuzzy goal programming approach to analyse sustainable development goals of India

Energy policy, environmental planning and economic development play a key role in sustainable development. Sustainable development requires suitable and strategic policies satisfying multiple and conflicting objectives. Fuzzy goal programming (FGP) is a well-known approach in multi-criteria decision-making for its practical application. In this article, a FGP approach is proposed to analyse environmental, energy and sustainability goals of India by the year 2030 with reference to the key economic sectors of India. The presented model analyses the improvement opportunities, requirement of efforts and implementation of the sustainable development plans. Numerical illustration is also provided for validation and application of the proposed model.     

A Schumpeterian model of equilibrium unemployment and labor turnover

This paper constructs a general equilibrium model of equilibrium unemployment by combining an endogenous growth model with a variant of equilibrium search theory. The analysis offers two explanations for the causes of widening wage gap between skilled and less-skilled labor, and rising unemployment rate among the less skilled: technological change in the form of an increase in the size of innovations or skilled labor saving technological change in R&D activity. In addition, the model identifies two distinct effects of faster technological progress on the aggregate unemployment rate. First, it increases the rate of labor turnover and therefore increases the aggregate unemployment rate – the creative destruction effect. Second, it creates R&D jobs, which offer workers complete job security, and consequently reduces the aggregate unemployment rate – the resource reallocation effect.     

Real Incentive Effects of Soft Information

Both soft, noncontractible, and hard, contractible, information are informative about managerial ability and future firm performance. If a manager's future compensation depends on expectations of ability or future performance, then the manager has implicit incentives to affect the information. We examine the real incentive effects of soft information in a dynamic agency with limited commitment. When long-term contracts are renegotiated, the rewards for future performance inherent in long-term contracts allow the principal partial control over the implicit incentives. This is because the soft information affects the basis for contract renegotiation. With short-term contracts, the principal has no control over the basis for contract negotiation, and thus long-term contracts generally dominate short-term contracts. With long-term contracts, the principal's control over implicit incentives is characterized in terms of effective contracting on an implicit aggregation of the soft information that arises from predicting (forming expectations of) future performance. We provide sufficient conditions for soft information to have no real incentive effects. In general, implicit incentives not controllable by the principal include fixed effects, such as career concerns driven by labor markets external to the agency. When controllable incentives span the fixed effects of career concerns, the latter have no real effects with regard to total managerial incentives—they would optimally be the same with or without career concerns. Our analysis suggests empirical tests for estimating career concerns that should explicitly incorporate noncontractible information.     

Leveraging Information Across Categories

Companies are collecting increasing amounts of information about their customers. This effort is based on the assumption that more information is better and that this information can be leveraged to predict customers' behavior in a variety of situations and product categories. For example, information about a customer's purchase behavior in one category can be helpful in predicting his potential behavior in a related category, which in turn could help a firm in its cross-selling efforts. In this paper, we present a model to better understand and predict a consumer's purchases and preferences when we may have limited or no information about him in one or more product categories. Conceptually this involves leveraging information from purchases of other consumers in multiple categories as well as partial information (e.g., purchase in one of the categories) of the target consumer. Our approach builds on the pioneering work of (Rossi et al. (1996)) who demonstrate the value of purchase information in the context of a single product category. We present results from an extensive simulation as well as an application on scanner panel data. Our simulation shows many interesting and somewhat surprising results. Specifically, we find that compared to a single-category analysis, a cross-category analysis does not lead to any significant improvement in data likelihood in most cases. Therefore, the single-category analysis of (Rossi et al. (1996)) is even more powerful than previously thought. However, we also find that a cross-category analysis does improve parameter recovery in many situations as compared to a single-category analysis. It is in these conditions that retailers can use cross-category information to better implement micro marketing programs. We demonstrate the transfer of information across categories in an application of two grocery products—Breakfast Foods and Table Syrup. In spite of a reasonable correlation (0.21) in the price parameter across these two categories, our simulation guidelines predict very little benefit of cross-category analysis over single-category analysis. Our empirical results confirm this prediction.     

Business Cycle Synchronization of Turkey with the Eurozone and the United States: What Has Changed Since 2001?

Using wavelet methodology, we make a detailed spectral analysis of the business cycle synchronization of the Turkish economy with the eurozone and the United States. We take into account the dramatic change in the main economic indicators in the Turkish economy after the 2001 financial crisis. We find that the correlation of Turkish cycles with the cycles of the eurozone and the United States increased substantially after 2001. Moreover, the correlation of the Turkish cycles with the U.S. cycles is not lower than that with the euro cycles after 2001. Accordingly, analyzing the effect of international developments should not be confined to the trade channel. We submit that capital flows offer a reasonable explanation for the high correlation with the United States.     

Export Sophistication: A Dynamic Panel Data Approach

In this article, we analyze export sophistication based on a large panel dataset (2001–2015; 101 countries) and using various estimation algorithms. Using Monte Carlo simulations, we evaluate the bias properties of estimators and show that GMM-type estimators outperform instrumental-variable and fixed-effects estimators. Based on our analysis we document that GDP per capita and the size of the economy exhibit significant and positive effects on export sophistication; weak institutional quality exhibits negative effect. We also show that export sophistication is path-dependent and stable even during a major economic crisis, which is especially important for emerging and developing economies.     

Downward wage rigidity and job mobility

Using data from the German Socio-Economic Panel (GSOEP) we study whether being individually affected by downward wage rigidity has an effect on layoffs, quits and intra-firm mobility. Within a structural empirical model we estimate the individual extent of wage rigidity. This is expressed by the wage sweep-up, which measures by how much individual wage growth increases through the effect of downward wage rigidity when compared to a counterfactual labour market with flexible wage setting. We find robust negative effects of wage sweep-up on quits and layoffs and some evidence for a positive association of wage sweep-up and promotion opportunities. This is consistent with a core-periphery view of the labour force, where a core work force is protected from layoffs and wage cuts and at the same time enjoys good promotion opportunities. On the other side a peripheral work force provides a buffer for adjustment and suffers from both flexible wages, more insecure jobs and less internal promotion opportunities.      

The impact of capital market imperfections on investment–cash flow sensitivity

We examine the investment–cash flow sensitivity of US manufacturing firms in relation to five factors associated with capital market imperfections – fund flows, institutional ownership, analyst following, bond ratings, and an index of antitakeover amendments. We find a steady decline in the estimated sensitivity over time. Furthermore, we find that investment–cash flow sensitivity decreases with increasing fund flows, institutional ownership, analyst following, antitakeover amendments and with the existence of a bond rating. The overall evidence suggests that investment–cash flow sensitivity decreases with factors that reduce capital market imperfections.     

Choice and the Internet: From Clickstream to Research Stream

The authors discuss research progress and future opportunities for modeling consumer choice on the Internet using clickstream data (the electronic records of Internet usage recorded by company web servers and syndicated data services). The authors compare the nature of Internet choice (as captured by clickstream data) with supermarket choice (as captured by UPC scanner panel data), highlighting the differences relevant to choice modelers. Though the application of choice models to clickstream data is relatively new, the authors review existing early work and provide a two-by-two categorization of the applications studied to date (delineating search versus purchase on the one hand and within-site versus across-site choices on the other). The paper offers directions for further research in these areas and discusses additional opportunities afforded by clickstream information, including personalization, data mining, automation, and customer valuation. Notwithstanding the numerous challenges associated with clickstream data research, the authors conclude that the detailed nature of the information tracked about Internet usage and e-commerce transactions presents an enormous opportunity for empirical modelers to enhance the understanding and prediction of choice behavior.