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Haruki Kono

Publications and source records attributed to Haruki Kono.

7 recordsLinked to original sources
arXiv2025

Untestability of Average Slutsky Symmetry

Slutsky symmetry and negative semidefiniteness are necessary and sufficient conditions for the rationality of demand functions. While the empirical implications of Slutsky negative semidefiniteness in repeated cross-sectional demand data are well understood, the empirical content of Slutsky symmetry remains largely unexplored. This paper takes an important first step toward addressing this gap. We show that the average Slutsky matrix is not identified and that its identified set always contains a symmetric matrix, implying that the symmetry of the average Slutsky matrix is untestable and that individual Slutsky symmetry cannot be tested through the average. Nevertheless, we demonstrate that, by imposing bounds on the income elasticity of demand, Slutsky symmetry implies a set of functional inequality constraints that are testable.

econ.EM↗
arXiv2024

Local Identification in Instrumental Variable Multivariate Quantile Regression Models

In the instrumental variable quantile regression (IVQR) model of Chernozhukov and Hansen (2005), a one-dimensional unobserved rank variable monotonically determines a single potential outcome. In practice, when researchers are interested in multiple outcomes, it is common to estimate separate IVQR models for each of them. This approach implicitly assumes that the rank variable in each regression affects only its associated outcome, without influencing others. In reality, however, outcomes are often jointly determined by multiple latent factors, inducing structural correlations across equations. To address this limitation, we propose a nonlinear instrumental variable model that accommodates multivariate unobserved heterogeneity, where each component of the latent vector acts as a rank variable corresponding to an observed outcome. When both the treatment and the instrument are discrete, we show that the structural function in our model is locally identified under a sufficiently strong positive correlation between the treatment and the instrument.

econ.EM↗
arXiv2023

Semiparametric Efficiency Gains From Parametric Restrictions on Propensity Scores

We explore how much knowing a parametric restriction on propensity scores improves semiparametric efficiency bounds in the potential outcome framework. For stratified propensity scores, considered as a parametric model, we derive explicit formulas for the efficiency gain from knowing how the covariate space is split. Based on these, we find that the efficiency gain decreases as the partition of the stratification becomes finer. For general parametric models, where it is hard to obtain explicit representations of efficiency bounds, we propose a novel framework that enables us to see whether knowing a parametric model is valuable in terms of efficiency even when it is high-dimensional. In addition to the intuitive fact that knowing the parametric model does not help much if it is sufficiently flexible, we discover that the efficiency gain can be nearly zero even though the parametric assumption significantly restricts the space of possible propensity scores.

econ.EM↗
arXiv2023

On Smithson's fixed point theorem for order preserving multifunctions

Fixed point theorems are ubiquitous in economic research. Many studies cite Smithson (1971) ``Fixed points of order preserving multifunctions,'' yet the original proof contains errors. This note presents a new, concise proof and explains why Smithson's argument is invalid. It also contains new results on the structure of the set of fixed points and monotone comparative statics.

math.CO↗
arXiv2023

Random Utility with Unobservable Alternatives

The random utility model, a cornerstone in economics, is axiomatized by Falmagne (1978) and McFadden and Richter (1990) with the assumption that if a menu is observable, the choice frequencies of all alternatives are also observable. However, in practice, it is common for choice frequencies of some alternatives to remain unobserved. To address this discrepancy, we obtain the testable implications of the random utility model when the choice frequencies of some alternatives are unobservable, which consist of nonredundant inequality constraints on observed choice frequencies. Our findings indicate that the widespread empirical practice of aggregating unobserved alternatives into a single "outside option" fails to capture significant implications of random utility models.

econ.TH↗
arXiv2022

Consistent Bayesian Information Criterion Based on a Mixture Prior for Possibly High-Dimensional Multivariate Linear Regression Models

In the problem of selecting variables in a multivariate linear regression model, we derive new Bayesian information criteria based on a prior mixing a smooth distribution and a delta distribution. Each of them can be interpreted as a fusion of the Akaike information criterion (AIC) and the Bayesian information criterion (BIC). Inheriting their asymptotic properties, our information criteria are consistent in variable selection in both the large-sample and the high-dimensional asymptotic frameworks. In numerical simulations, variable selection methods based on our information criteria choose the true set of variables with high probability in most cases.

math.ST↗