284,320 research outputs found
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
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
Addressing business agility challenges with enterprise systems
It is clear that systems agility (i.e., having a responsive IT infrastructure that can be changed quickly to meet changing business needs) has become a critical component of organizational agility. However, skeptics continue to suggest that, despite the benefits enterprise system packages provide, they are constraining choices for firms faced with agility challenges. The reason for this skepticism is that the tight integration between different parts of the business that enables many enterprise systems\u27 benefits also increases the systems\u27 complexity, and this increased complexity, say the skeptics, increases the difficulty of changing systems when business needs change. These persistent concerns motivated us to conduct a series of interviews with business and IT managers in 15 firms to identify how they addressed, in total, 57 different business agility challenges. Our analysis suggests that when the challenges involved an enterprise system, firms were able to address a high percentage of their challenges with four options that avoid the difficulties associated with changing the complex core system: capabilities already built-in to the package but not previously used, leveraging globally consistent integrated data already available, using add-on systems available on the market that easily interfaced with the existing enterprise system, and vendor provided patches that automatically updated the code. These findings have important implications for organizations with and without enterprise system architectures
Probing spin entanglement by gate-voltage-controlled interference of current correlation in quantum spin Hall insulators
We propose an entanglement detector composed of two quantum spin Hall
insulators and a side gate deposited on one of the edge channels. For an ac
gate voltage, the differential noise contributed from the entangled electron
pairs exhibits the nontrivial step structures, from which the spin entanglement
concurrence can be easily obtained. The possible spin dephasing effects in the
quantum spin Hall insulators are also included.Comment: Physics Letters A in pres
Accelerating Atomic Orbital-based Electronic Structure Calculation via Pole Expansion and Selected Inversion
We describe how to apply the recently developed pole expansion and selected
inversion (PEXSI) technique to Kohn-Sham density function theory (DFT)
electronic structure calculations that are based on atomic orbital
discretization. We give analytic expressions for evaluating the charge density,
the total energy, the Helmholtz free energy and the atomic forces (including
both the Hellman-Feynman force and the Pulay force) without using the
eigenvalues and eigenvectors of the Kohn-Sham Hamiltonian. We also show how to
update the chemical potential without using Kohn-Sham eigenvalues. The
advantage of using PEXSI is that it has a much lower computational complexity
than that associated with the matrix diagonalization procedure. We demonstrate
the performance gain by comparing the timing of PEXSI with that of
diagonalization on insulating and metallic nanotubes. For these quasi-1D
systems, the complexity of PEXSI is linear with respect to the number of atoms.
This linear scaling can be observed in our computational experiments when the
number of atoms in a nanotube is larger than a few hundreds. Both the wall
clock time and the memory requirement of PEXSI is modest. This makes it even
possible to perform Kohn-Sham DFT calculations for 10,000-atom nanotubes with a
sequential implementation of the selected inversion algorithm. We also perform
an accurate geometry optimization calculation on a truncated (8,0)
boron-nitride nanotube system containing 1024 atoms. Numerical results indicate
that the use of PEXSI does not lead to loss of accuracy required in a practical
DFT calculation
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