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We present the results of a questionnaire study with Belgian undergraduate students as respondents. We consider the relationship between people’s direct ethical preferences, their preferences behind a veil of ignorance, and their purely individual risk preferences over income distributions. The results reveal that, although there are important similarities between the three types of preferences, the first and third types form two extremes, while the second type lies in between the other two. Consistency of response patterns with the expected utility (EU) and rank-dependent expected utility (RDEU) models – natural analogues of the social welfare functions most frequently used in the literature on inequality and social welfare – is tested as well. For all three types of preferences the results reveal that, in the considered context, the RDEU model does not add explanatory power to the EU model. However, preferences appear to be relatively well described by some of the basic concepts from non-expected utility theory not usually considered in the income distribution literature.

This chapter examines factors that cause violations of regularity conditions and biases in estimates of substitution. In the context of the Fourier demand system, failing to impose curvature restrictions but correcting for serial correlation results in few violations of the curvature conditions. In contrast, imposing curvature restrictions without correcting for serial correlation biases substitution estimates and can cause violations of monotonicity. For serially correlated data, results suggest that correcting for serial correlation may be more important than imposing curvature. Furthermore, the artificially break-adjusted data that are inconsistent with consumer optimization can severely bias estimates. Results from the Bank of England's (BOE) preferred non-break-adjusted data establish that money and goods are substitutes in demand.

Continuum‐atomistic modeling denotes a mixed approach combining the usual framework of continuum mechanics with atomistic features like e.g. interaction potentials. Thereby, the kinematics are typically characterized by the so called Cauchy‐Born rule representing atomic distance vectors in the spatial configuration as an affine mapping of the atomic distance vectors in the material configuration in terms of the local deformation gradient. The application of the Cauchy‐Born rule requires sufficiently homogeneous deformations of the underlying crystal. The model is no more valid if the deformation becomes inhomogeneous. By virtue of the Cauchy‐Born hypothesis, a localization criterion has been derived in terms of the loss of infinitesimal rank‐1 convexity of the strain energy density. According to this criterion, a numerical yield condition has been computed for two different interatomic energy functions. Therewith, the range of the Cauchy‐Born rule validity has been defined, since the strain energy density remains quasiconvex only within the computed yield surface. To provide a possibility to continue the simulation of material response after the loss of quasiconvexity, a relaxation procedure proposed by Tadmor et al. [1] leading necessarily to the development of microstructures has been used. Alternatively to the above mentioned criterion, a stability criterion has been applied to detect the critical deformation. For the study in the postcritical region, the path‐change procedure proposed by Wagner and Wriggers [2] has been adapted for the continuum‐atomistics and modified.

China and India have made significant strides in transforming their agricultural sectors to cut hunger and poverty for the masses through improved agricultural productivity. Given limited land and shift of labor to non-agricultural sector, increasing productivity will continue to be central in agricultural growth in the twenty-first century. The purpose of this paper is to provide comparative analysis of the agricultural total factor productivity (TFP) growth in the two countries. It complements existing literature by examining the evolution and drivers of TFP at disaggregated sub-national level. Richer data allows a deeper understanding of the nature and drivers of TFP growth in the two countries.

This paper applies different analytical framework to address different research questions using data since 1980. China study estimates a parametric output-based distance function using a translog stochastic frontier function. Productivity growth index and its multiple components are calculated using parameters derived from the parametric approach to identify the characteristics of technology such as structural bias. India study first applies data envelopment analysis to estimate the aggregate productivity growth index, technical change (TC), and efficiency change. Next productivity indexes by for traditional crops are estimated using growth accounting framework at state level. Finally, a panel regression links TFP on its determinants.

Several common themes emerge from this comparative study. Faced with similar challenges of limited resources and growing demand, improving productivity is the only way to meet long-term food security. Agriculture sector has performed impressively with annual TFP growth beyond 2 percent in China and between 1 and 2 percent in India since the 1980s. The TFP growth is mainly propelled by technological advance but efficiency had been stagnant or even deteriorated. This study provides a granular picture of within country heterogeneity: fast growth in the North and Northeast part of China, South and East of India.

The study suggests some possible policy interventions to improve agricultural productivity, including investment in agricultural R & D to create advanced production technology, effective extension programs and supportive policies to increase efficiency, and diversification from staple crops for sector-wide growth. The India study suggests certain policies may not be contributing much to productivity growth in the long run due to a negative impact on environment. Further studies are needed to expand the productivity analysis to take into consideration of the negative externalities to the society. Data enhancement to account for quality-adjusted inputs could improve the estimation of productivity growth.

Each country study reveals certain prospects of the agricultural sector and production technology. China analysis statistically confirms the existence of technical inefficiency and technology progress, suggests the translog form is appropriate to capture the production technology and satisfies conditions stipulated in theoretical models. The results indicate TC does not influence the contribution of output or input to the production process. India study pinpoints the lagging productivity growth of traditional crops, which still derives growth from input expansion. Although different states benefited from different crops, sector-wide productivity gain is primarily the result of diversification to high-value crops and livestock products.

This chapter is an up-to-date survey of the state-of-the art in consumer demand analysis. We review (and evaluate) advances in a number of related areas, in the spirit of the recent survey paper by Barnett and Serletis (2008). In doing so, we only deal with consumer choice in a static framework, ignoring a number of important issues, such as, the effects of demographic or other variables that affect demand, welfare comparisons across households (equivalence scales), and the many issues concerning aggregation across consumers.

This paper proposes the use of a gauge function as a measure of technical efficiency. The measure of technical inefficiency from a gauge function is desirable as the estimation of a gauge function is not subject to the endogeneity problem under the behavioral assumption of profit maximization in the competitive market.

The authors address three important properties of a gauge function, i.e. linear homogeneity, monotonicity and convexity in inputs and outputs, and show how such properties are utilized in its estimation. Then, the authors apply the estimation of a gauge function to US Blacksmiths in 1850 and 1880 to show that a failure to satisfy such properties may lead to an incorrect inference on the technical efficiency.

The authors find that the Blacksmiths in the 1850s were technically more efficient than the ones in the 1880s, indicating technical regress in Blacksmithing when the properties are satisfied.

This paper introduces a measure of technical inefficiency from a gauge function and shows how to estimate the gauge function parametrically for the measure. The authors show McFadden's gauge function and its properties, which differ from the properties of other distance functions. The authors emphasize linear homogeneity as well as monotonicity and convexity in inputs and outputs, which must be satisfied in the estimation of a gauge function.