Bayesian Fuzzy Regression Discontinuity Analysis and Returns to Compulsory Schooling

This paper is concerned with the use of a Bayesian approach to fuzzy regression discontinuity (RD) designs for understanding the returns to education. The discussion is motivated by the change in government policy in the UK in April of 1947, when the minimum school leaving age was raised from 14 to 15—a change that had a discontinuous impact on the probability of leaving school at age 14 for cohorts who turned 14 around the time of the policy change. We develop a Bayesian fuzzy RD framework that allows us to take advantage of this discontinuity to calculate the effect of an additional year of education on subsequent log earnings for the (latent) class of subjects that complied with the policy change. We illustrate this approach with a new dataset composed from the UK General Household Surveys. Copyright © 2015 John Wiley & Sons, Ltd.     

An empirical investigation of interregional production relations and comparative advantage in US manufacturing, 1960–70

Hypothesized differences in mean changes in shares of European Community (EC) import markets over the period 1976-84 are tested for each of 36 less-developed countries. Means are calculated for cases in which MFN tariffs are re-established and for cases in which duty-free treatment is restored under the EC generalized system of preferences. They are compared with means for cases in which tariffs remained constant. We attempt to control for both product-specific and cyclical influences on imports. In contrast to some previous results, our findings suggest that denial (restoration) of preferential treatment, i.e. a tariff increase (decrease), has its expected negative (positive) effect.     

The multi-market firm, transportation costs, and the separation of the output and allocation decisions

Despite the documented importance of transport costs for firmswith sales in geographically separated markets, theoreticalanalyses typically ignore such costs. This paper analyzes theeffects of transport costs for a risk averse, competitive firmselling a single good in a domestic (certain) and a foreign(uncertain) market, and shows that these effects are asymmetric.The effects on total output and the inter-market allocationof output depend on the behavior of marginal domestic transportcosts, but are largely independent of the form of the foreigntransport cost function. Moreover, regardless of the latter,if marginal transport costs in the domestic market are constant,the firm's total output is independent of its attitude towardsrisk and the parameters of the risky market. This suggests thatthe firm's activity can be insulated from foreign uncertaintiesby government policies that focus on the shape of the domestictransportation cost function.     

Allocating a hybrid retailer's assortment across retail stores: Bricks-and-mortar vs online

This paper develops an IP model to determine item allocation for a hybrid retailer's store network, comprising bricks-and-mortar and online stores. Products with low carrying costs are distributed between the bricks-and-mortar stores and the online store. Products with high carrying costs can be withdrawn from the bricks-and-mortar stores and made available exclusively at the online store where the inventory carrying costs are comparatively lower. This strategy assists the hybrid retailer to not only improve the profitability of its bricks- and-mortar stores but also to retain the custom of the market segment that is loyal to the items withdrawn from the traditional stores. In this framework, the online channel complements rather than competes with traditional channels. This model is used to conduct an extensive simulation study to analyze the impact of important business factors on system profitability.     

ExpertLens: A system for eliciting opinions from a large pool of non-collocated experts with diverse knowledge

The complexity of policy decision-making raises the need to elicit opinions from large and heterogeneous groups of stakeholders with broad and diverse sets of expertise. Existing options for elicitation include small face-to-face panels of experts by using the Nominal Group Technique (NGT), large Delphi panels whose members do not interact with each other face-to-face, and crowdsourcing, which involves an open call for input issued to a large community of people. In an attempt to close the gap between the practical needs of policy makers and the methodological challenges associated with eliciting opinions of large, diverse, and distributed groups, we have developed a new online elicitation system and methodology called ExpertLens. By optimizing the direct interactions of NGT with the larger number of Delphi participants and the wisdom of “selected crowds,” our approach is designed to save on the costs associated with traditional expert panels, while increasing accuracy in elicitation by reducing the potential for group process losses that can occur in large, diverse, and non-collocated panels whose members interact via asynchronous online discussion boards. The ExpertLens approach is iterative, does not require participants to develop consensus, and determines what the group “thinks” by statistically analyzing data collected in all rounds of the elicitation. This paper describes the ExpertLens system and methodology, briefly discusses recent ExpertLens trials, provides conceptual arguments for why it is an appropriate model for eliciting expert opinions, illustrates its main components and analytics by using an infrastructure investment example, and discusses a research agenda for testing the underlying tenets of the ExpertLens approach.     

Equity premium in a production economy: A parametric example

A simple Arrow-Debreu model with production and adjustment cost is developed and it is shown how the production parameters interact in determining the steady state equity premium. We also show that the equity premium is highest in exchange economy.     

Managing platform architectures and manufacturing processes for nonassembled products

The article presents methods for defining product platforms and measuring business performance in process intensive industries. We first show how process intensive product platforms can be defined using the products and processes of a film manufacturer. We then present an empirical method for understanding the dynamics of process intensive platform innovation, allocating engineering and sales data to specific platform and product development efforts within a product family. We applied this method to a major product line of a materials manufacturer. We gathered ten years of engineering and manufacturing cost data and allocated these to successive platforms and products, and then generated R&D performance measures. These data show the dynamic of heavy capital spending relative to product engineering as one might expect in a process intensive industries. The data also show how derivative products can be leveraged from underlying product platforms and processes for nonassembled products. Embedded within these data are strategies for creating reusable subsystems (comprising components, materials, etc.) and common production processes. Hard data on the degree to which subsystems and processes are shared across different products frequently are typically not maintained by corporations for the duration needed to understand the dynamics of evolving product families. For this reason, we developed and applied a second method to assess the degree of reuse of subsystems and processes. This method asks engineering managers to provide subjective ratings on an ordinal scale regarding the use of technology and processes from one product to the next in a cumulative manner. We find that high levels of reuse generally indicate that a product family was developed with a platform discipline. We applied this measure of platform intensity to two product lines of integrated circuits from another large manufacturer. We used this method to gather approximately ten years of information for each product family. Upon analysis, one product family showed substantial platform discipline, emphasizing a common architecture and processes across specific products within the product line. The other product family was developed with significantly less sharing and reuse of architecture, components, and processes. We then found that the platform centric product family outperformed the latter along a number of performance dimensions over the course of the decade under examination.     

Assessing the role of option grants to CEOs: How important is heterogeneity?

This paper revisits the question of whether CEO compensation practices are in keeping with those justified by agency theory. We develop and analyze a new panel Tobit model, estimated by modern Bayesian methods, in which the heterogeneity of covariate effects across firms is modeled in a hierarchical way. We find that our specification of heterogeneity provides a significantly improved fit to the data. Our results show support for the hypothesis that companies increase option awards to their CEOs when agency problems become more pronounced. We also find that liquidity constraints matter in defining the cash–option mix of CEO compensation.     

Stochastic Volatility: Likelihood Inference and Comparison with ARCH Models

In this paper, Markov chain Monte Carlo sampling methods are exploited to provide a unified, practical likelihood-based framework for the analysis of stochastic volatility models. A highly effective method is developed that samples all the unobserved volatilities at once using an approximating offset mixture model, followed by an importance reweighting procedure. This approach is compared with several alternative methods using real data. The paper also develops simulation-based methods for filtering, likelihood evaluation and model failure diagnostics. The issue of model choice using non-nested likelihood ratios and Bayes factors is also investigated. These methods are used to compare the fit of stochastic volatility and GARCH models. All the procedures are illustrated in detail.     

A framework to measure relative performance of Indian technical institutions using integrated fuzzy AHP and COPRAS methodology

There are many opportunities and challenges in area of Indian technical education due to liberalization and globalization of economy. One of these challenges is how to assess performance of technical institutions based on multiple criteria. This paper is focused on performance evaluation and ranking of seven Indian Institute of Technology (IITs) in respect to stakeholders’ preference using an integrated model consisting of fuzzy AHP and COPRAS. Findings based on 2007–2008 data show that performance of two IITs need considerable improvement. To the best of our knowledge it is one of few studies that evaluates performance of technical institutions in India.