Considering Aquacultural Externality in Coastal Land Allocation Decisions in India

Commercial aquaculture in India has come under attack for having caused negative agricultural and environmental impacts. This paper formulates an interactive model of non-renewable and renewable resources to characterize land allocations between aquaculture and agriculture in ecologically and economically sustainable fashion. Through an empirical application, various economic and policy circumstances that affect the optimal land allocation mix are evaluated. The aquaculture industry must address two economic effects: off-site negative effects on renewable food and other coastal resources, and on-site self-pollution of shrimp ponds. Current regulatory and land-use policies are inadequate to address these effects.     

Accommodating spatial correlation across choice alternatives in discrete choice models: an application to modeling residential location choice behavior

This paper presents a modeling methodology capable of accounting for spatial correlation across choice alternatives in discrete choice modeling applications. Many location choice (e.g., residential location, workplace location, destination location) modeling contexts involve choice sets where alternatives are spatially correlated with one another due to unobserved factors. In the presence of such spatial correlation, traditional discrete choice modeling methods that are often based on the assumption of independence among choice alternatives are not appropriate. In this paper, a Generalized Spatially Correlated Logit (GSCL) model that allows one to represent the degree of spatial correlation as a function of a multi-dimensional vector of attributes characterizing each pair of location choice alternatives is formulated and presented. The formulation of the GSCL model allows one to accommodate alternative correlation mechanisms rather than pre-imposing restrictive correlation assumptions on the location choice alternatives. The model is applied to the analysis of residential location choice behavior using a sample of households drawn from the 2000 San Francisco Bay Area Travel Survey (BATS) data set. Model estimation results obtained from the GSCL are compared against those obtained using the standard multinomial logit (MNL) model and the spatially correlated logit (SCL) model where only correlations across neighboring (or adjacent) alternatives are accommodated. Model findings suggest that there is significant spatial correlation across alternatives that do not share a common boundary, and that the GSCL offers the ability to more accurately capture spatial location choice behavior.     

Recent Progress on Endogeneity in Choice Modeling

We describe recent progress in several areas related to endogeneity, including: choice set formation and attention to attributes; interactions among decision-makers; respondents' strategic behavior in answering stated preference choices; models of multiple discrete/continuous choice; distributions of willingness-to-pay; and methods for handling traditionally endogenous explanatory variables.     

Priority areas in demographic research

"This paper reviews...demographic development [in India] since the mid-1970s and highlights important data gaps in respect to (i) fertility and family planning (ii) mortality and morbidity along with priority areas for exploratory research. The paper notes that during the past two decades, [the] demographic data-base in India has improved considerably. Fertility levels have begun to fall in many places and mortality has continued its rapid downward course...."     

Hybrid Choice Models: Progress and Challenges

We discuss the development of predictive choice models that go beyond the random utility model in its narrowest formulation. Such approaches incorporate several elements of cognitive process that have been identified as important to the choice process, including strong dependence on history and context, perception formation, and latent constraints. A flexible and practical hybrid choice model is presented that integrates many types of discrete choice modeling methods, draws on different types of data, and allows for flexible disturbances and explicit modeling of latent psychological explanatory variables, heterogeneity, and latent segmentation. Both progress and challenges related to the development of the hybrid choice model are presented.     

Exploring the Effect of Store Characteristics and Interpersonal Trust on Purchase Intention in the Context of Online Social Media Marketing

This article explores the effect of store characteristics and interpersonal trust on formation of attitude and intention to purchase from online stores in the context of online social media marketing. Store Brand Knowledge, Store Reputation, Perceived Store Size, and Perceived Store Risk have been considered as antecedents of trust. Based on existing literature, a conceptual model is proposed and empirically tested with a sample (n = 424) of online social media users with the help of partial least square path modeling. This study is among the very few empirical investigations done in the context of trust in online social media marketing and focuses only on consumer-perceived store-controlled factors as antecedents of trust.     

Macroeconomic Response to Oil and Food Price Shocks: A Structural VAR Approach to the Indian Economy

The study analyzed the dynamic impact of oil and food price shocks on the macroeconomy of India, using the monthly time series data from April 1994 to May 2016 in a structural vector autoregression (SVAR) framework. Being a net food exporter and net oil importer, the economy is found to face deleterious impacts of global oil and food price shocks on its macroeconomic performance. Output responds negatively to oil and food price hikes along with their volatility and positively to the fall in these prices. Inflation responds positively to all the three transformations of shocks with no signs of coming down, highlighting the price downward inflexibility in India. The study could not establish any evidence of negative demand shocks in face of oil and food price volatility. Central bank responds with a contractionary policy stance to negate the influences of external shocks. Forecast error variance decomposition points out the dominance of external shocks in influencing the domestic variables after their own shocks. Finally, the inflation downward rigidity is observed even in the long run.     

Recent trends in age-specific mortality in India

"In this paper we have analyzed the data from the Sample Registration System [SRS] on mortality by age and sex [in India] since 1970. Some of the major conclusions emerging from this analysis are: (i) Mortality has declined more rapidly among infants, children under 15 years and women of reproductive ages....(ii) Among adults, mortality has declined more rapidly among females than among males, the differential gain being largest in the age span 25-49. But in ages under 15, there is no evidence to suggest a gender differential in mortality decline. (iii) Among children and women of reproductive ages, mortality has declined more rapidly in urban areas than in rural areas but the reverse is true in the case of adult men.... The paper also analyzes the trends in mortality in major states of India during 1970-86." The authors observe a significant shift in patterns between 1978 and 1979, and conclude that this may be limited to changes in SRS data collection techniques.     

Health and family welfare base-line survey in Gokak taluka, 1993: a brief report

"The Institute of Economic Research undertook [a] base line survey in Gokak taluka [India].... The major objective was to provide a data base for evaluating programme efforts, and developing strategies and plans for the future.... The main object of the study was to provide base-line information on the levels of fertility, family planning, and maternal [and] child health care for the project area...[and] aspects of mortality and morbidity."     

A New Utility‐Consistent Econometric Approach to Multivariate Count Data Modeling

In the current paper, we propose a new utility‐consistent modeling framework to explicitly link a count data model with an event‐type multinomial‐choice model. The proposed framework uses a multinomial probit kernel for the event‐type choice model and introduces unobserved heterogeneity in both the count and discrete‐choice components. Additionally, this paper establishes important new results regarding the distribution of the maximum of multivariate normally distributed variables, which form the basis to embed the multinomial probit model within a joint modeling system for multivariate count data. The model is applied to analyzing out‐of‐home non‐work episodes pursued by workers, using data from the National Household Travel Survey. Copyright © 2014 John Wiley & Sons, Ltd.