Nonparametric IV estimation of shape-invariant Engel curves

This paper concerns the identification and estimation of a shape-invariant Engel curve system with endogenous total expenditure. The shape-invariant specification involves a common shift parameter for each demographic group in a pooled system of Engel curves. Our focus is on the identification and estimation of both the nonparametric shape of the Engel curve and the parametric specification of the demographic scaling parameters. We present a new identification condition, closely related to the concept of bounded completeness in statistics. The estimation procedure applies the sieve minimum distance estimation of conditional moment restrictions allowing for endogeneity. We establish a new root mean squared convergence rate for the nonparametric IV regression when the endogenous regressor has unbounded support. Root-n asymptotic normality and semiparametric efficiency of the parametric components are also given under a set of ‘low-level’ sufficient conditions. Monte Carlo simulations shed lights on the choice of smoothing parameters and demonstrate that the sieve IV estimator performs well. An application is made to the estimation of Engel curves using the UK Family Expenditure Survey and shows the importance of adjusting for endogeneity in terms of both the curvature and demographic parameters of systems of Engel curves

Semi-nonparametric IV estimation of shape-invariant Engel curves

This paper studies a shape-invariant Engel curve system with endogenous total expenditure, in which the shape-invariant specification involves a common shift parameter for each demographic group in a pooled system of nonparametric Engel curves. We focus on the identification and estimation of both the nonparametric shapes of the Engel curves and the parametric specification of the demographic scaling parameters. The identification condition relates to the bounded completeness and the estimation procedure applies the sieve minimum distance estimation of conditional moment restrictions, allowing for endogeneity. We establish a new root mean squared convergence rate for the nonparametric instrumental variable regression when the endogenous regressor could have unbounded support. Root-n asymptotic normality and semiparametric efficiency of the parametric components are also given under a set of "low-level" sufficient conditions. Our empirical application using the U.K. Family Expenditure Survey shows the importance of adjusting for endogeneity in terms of both the nonparametric curvatures and the demographic parameters of systems of Engel curves

Frontiers of parasitology research in the People's Republic of China : infection, diagnosis, protection and surveillance

ABSTRACT: Control and eventual elimination of human parasitic diseases in the People's Republic of China (P.R. China) requires novel approaches, particularly in the areas of diagnostics, mathematical modelling, monitoring, evaluation, surveillance and public health response. A comprehensive effort, involving the collaboration of 188 scientists (<85% from P.R. China) from 48 different institutions and universities (80% from P.R. China), covers this collection of 29 articles published in Parasites & Vectors. The research mainly stems from a research project entitled 'Surveillance and diagnostic tools for major parasitic diseases in P.R. China' (grant no. 2008ZX10004-011) and highlights the frontiers of research in parasitology. The majority of articles in this thematic series deals with the most important parasitic diseases in P.R. China, emphasizing Schistosoma japonicum, Plasmodium vivax and Clonorchis sinensis plus some parasites of emerging importance such as Angiostrongylus cantonensis. Significant achievements have been made through the collaborative research programme in the following three fields: (i) development of control strategies for the national control programme; (ii) updating the surveillance data of parasitic infections both in human and animals; and (iii) improvement of existing, and development of novel, diagnostic tools to detect parasitic infections. The progress is considerable and warrants broad validation efforts. Combined with the development of improved tools for diagnosis and surveillance, integrated and multi-pronged control strategies now pave the way for elimination of parasitic diseases in P.R. China. Experiences and lessons learned can stimulate control and elimination efforts of parasitic diseases in other parts of the world

Design of an instrumented smart cutting tool and its implementation and application perspectives

This paper presents an innovative design of a smart cutting tool, using two surface acoustic wave (SAW) strain sensors mounted onto the top and the side surface of the tool shank respectively, and its implementation and application perspectives. This surface acoustic wave-based smart cutting tool is capable of measuring the cutting force and the feed force in a real machining environment, after a calibration process under known cutting conditions. A hybrid dissimilar workpiece is then machined using the SAW-based smart cutting tool. The hybrid dissimilar material is made of two different materials, NiCu alloy (Monel) and steel, welded together to form a single bar; this can be used to simulate an abrupt change in material properties. The property transition zone is successfully detected by the tool; the sensor feedback can then be used to initiate a change in the machining parameters to compensate for the altered material properties.The UK Technology Strategy Board (TSB) for supporting this research (SEEM Project, contract No. BD266E