arXiv subjects

Kazuhiko Kakamu

Publications and source records attributed to Kazuhiko Kakamu.

7 recordsLinked to original sources

arXiv2026

Bayesian State-Space Modeling and Model-Based Counterfactual Analysis of Dynamic Income Distributions from Grouped Data

Grouped income data contain only limited information about the evolution of income distributions over time. This paper develops a Bayesian state-space model for the generalized beta distribution of the second kind (GB2) to estimate dynamic income distributions using repeated grouped income data. By borrowing information across adjacent periods through the latent GB2 parameters, the proposed framework improves estimation precision relative to independent cross-sectional estimation. Building on the estimated latent-state dynamics, we further construct a model-based counterfactual framework that quantifies the contribution of demographic covariates while preserving the estimated evolution of the remaining model components. Using Japanese household income data from 1969--2007, we find that population aging and declining household size affect different parts of the income distribution through distinct channels, with population aging becoming an increasingly important driver of income inequality after around 2000. More generally, the proposed framework provides a unified Bayesian approach to dynamic distributional analysis and model-based counterfactual inference using repeated grouped income data.

econ.EM↗

arXiv2025

Bayesian analysis of mixtures of lognormal distribution with an unknown number of components from grouped data

This study proposes a reversible jump Markov chain Monte Carlo method for estimating parameters of lognormal distribution mixtures for income. Using simulated data examples, we examined the proposed algorithm's performance and the accuracy of posterior distributions of the Gini coefficients. Results suggest that the parameters were estimated accurately. Therefore, the posterior distributions are close to the true distributions even when the different data generating process is accounted for. Moreover, promising results for Gini coefficients encouraged us to apply our method to real data from Japan. The empirical examples indicate two subgroups in Japan (2020) and the Gini coefficients' integrity.

econ.EM↗

arXiv2025

Multilevel Decomposition of Generalized Entropy Measures Using Constrained Bayes Estimation: An Application to Japanese Regional Data

We propose a method for multilevel decomposition of generalized entropy (GE) measures that explicitly accounts for nested population structures such as national, regional, and subregional levels. Standard approaches that estimate GE separately at each level do not guarantee compatibility with multilevel decomposition. Our method constrains lower-level GE estimates to match higher-level benchmarks while preserving hierarchical relationships across layers. We apply the method to Japanese income data to estimate GE at the national, prefectural, and municipal levels, decomposing national inequality into between-prefecture and within-prefecture inequality, and further decomposing prefectural GE into between-municipality and within-municipality inequality.

econ.EM↗

arXiv2021

Is Bitcoin really a currency? A viewpoint of a stochastic volatility model

Using the asymmetric stochastic volatility model, this study investigates the day-of-the-week and holiday effects on the returns and volatility of Bitcoin from January 1, 2013 to August 31, 2019; in this context, we also discuss the characteristics of Bitcoin as a financial asset. The results of the estimation are threefold. First, the finding shows a small day-of-the week effect in volatility on Saturday and Sunday than in the rest of the week. Second, although the holiday effects are examined in active trading countries, namely Japan, China, Germany, and the United States, the positive post-holiday effect on the returns and weak positive pre-holiday effect on the volatility are only observed in the United States. Finally, the asymmetry effect is not observed. A comparison of Bitcoin to several assets such as stock, currency, and gold shows Bitcoin's positioning between stock, currency, and gold in relation to the week and holiday effects, its reaction to federal funds and medium of exchange characteristics, and the lack of asymmetry effect.

q-fin.ST↗

arXiv2021

How does monetary policy affect income inequality in Japan? Evidence from grouped data

We examine the effects of monetary policy on income inequality in Japan using a novel econometric approach that jointly estimates the Gini coefficient based on micro-level grouped data of households and the dynamics of macroeconomic quantities. Our results indicate different effects on income inequality for different types of households: A monetary tightening increases inequality when income data is based on households whose head is employed (workers' households), while the effect reverses over the medium term when considering a broader definition of households. Differences in the relative strength of the transmission channels can account for this finding. Finally we demonstrate that the proposed joint estimation strategy leads to more informative inference while results based on the frequently used two-step estimation approach yields inconclusive results.

econ.EM↗

arXiv2019

Bayesian approach to Lorenz curve using time series grouped data

This study is concerned with estimating the inequality measures associated with the underlying hypothetical income distribution from the times series grouped data on the Lorenz curve. We adopt the Dirichlet pseudo likelihood approach where the parameters of the Dirichlet likelihood are set to the differences between the Lorenz curve of the hypothetical income distribution for the consecutive income classes and propose a state space model which combines the transformed parameters of the Lorenz curve through a time series structure. Furthermore, the information on the sample size in each survey is introduced into the originally nuisance Dirichlet precision parameter to take into account the variability from the sampling. From the simulated data and real data on the Japanese monthly income survey, it is confirmed that the proposed model produces more efficient estimates on the inequality measures than the existing models without time series structures.

stat.ME↗

arXiv2017

Approximate Bayesian Computation for Lorenz Curves from Grouped Data

This paper proposes a new Bayesian approach to estimate the Gini coefficient from the Lorenz curve based on grouped data. The proposed approach assumes a hypothetical income distribution and estimates the parameter by directly working on the likelihood function implied by the Lorenz curve of the income distribution from the grouped data. It inherits the advantages of two existing approaches through which the Gini coefficient can be estimated more accurately and a straightforward interpretation about the underlying income distribution is provided. Since the likelihood function is implicitly defined, the approximate Bayesian computational approach based on the sequential Monte Carlo method is adopted. The usefulness of the proposed approach is illustrated through the simulation study and the Japanese income data.

stat.AP↗