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This paper proposes a new model-based approach to small area estimation of general finite-population parameters based on grouped data or frequency data, often available from sample surveys. Grouped data contains information on frequencies of some pre-specified groups in each area, for example, the numbers of households in the income classes. Thus, grouped data provide more detailed insight into small areas than area-level aggregated data. A direct application of the widely used small area methods, such as the Fay–Herriot model for area-level data and nested error regression model for unit-level data, is not appropriate since they are not designed for grouped data. Our novel method adopts the multinomial likelihood function for the grouped data. In order to connect the group probabilities of the multinomial likelihood and the auxiliary variables within the framework of small area estimation, we introduce the unobserved unit-level quantities of interest. They follow a linear mixed model with random intercepts and dispersions after some transformation. Then the probabilities that a unit belongs to the groups can be derived and are used to construct the likelihood function for the grouped data given the random effects. The unknown model parameters (hyperparameters) are estimated by a newly developed Monte Carlo EM algorithm which uses an efficient importance sampling. The empirical best predicts (empirical Bayes estimates) of small area parameters are calculated by a simple Gibbs sampling algorithm. The numerical performance of the proposed method is illustrated based on the model-based and design-based simulations. In the application to the city-level grouped income data of Japan, we complete the patchy maps of the Gini coefficient as well as mean income across the country. [ABSTRACT FROM AUTHOR]

Abstract: The purpose of this paper is to explain variations in the divorce rates across prefectures in Japan over the 20-year period between 1982 and 2002. This paper examines the various factors which may affect divorce rates including: the effects of the generosity of social welfare; the income of females relative to males; the female employment rate; the vacancy rate; a shift to no-fault divorce; and social stigma. There are three major findings of this paper. First, the generosity of a particular prefecture in approving the livelihood protection benefits (LPBs) has a statistically negative impact on the divorce rate. Moreover, social stigma has negative impacts both on the divorce rate and the generosity of social security benefits. Finally, political conservatism has a negative impact on the proportion of needy people who receive LPB. The findings of this paper imply that in order to become eligible for the social security benefits, married couples may be more likely to dissolve their marriage in those prefectures where the provision of the LPB is not so generous. [Copyright &y& Elsevier]

Abstract: This paper undertakes a time series analysis of the Japanese divorce rate using annual data over the period 1964–2006. One of the key innovations of the paper is to use court decisions on divorce disputes to construct an index that seeks to measure how the probability of success in a divorce suit has changed over time. The computed index suggests that if it is the culpable party lodging the divorce suit, the probability of the suit being successful has clearly increased over time. The probability of winning a divorce suit appears to be an important factor in explaining the long-run rise in the Japanese divorce rate. The divorce rate also appears to be counter-cyclical. [Copyright &y& Elsevier]

This paper estimates models for the retail price of gasoline in Tokyo and Osaka based on recent game theory emphasizing the importance of forward-looking behaviour by firms. Using monthly data for the 1990s, this paper presents evidence consistent with the theory that future changes in the economic environment firms face do have an impact on the current retail price of gasoline. Some evidence is also presented that suggests the behaviour of retail prices has changed over the time period being examined. [Copyright &y& Elsevier]

Abstract: Fluctuations in the stock market follow the principle of volatility clustering in which changes are cataloged by similarity; as such, large changes tend to follow large changes, and small changes tend to follow small changes. This clustering is one of the major reasons why many generalized autoregression conditional heteroscedasticity (GARCH) models do not forecast the stock market well. In this paper, an adaptive Fuzzy-GARCH model with particle swarm optimization (PSO) is proposed to solve this problem. The adaptive Fuzzy-GARCH model refers to both GARCH models and the parameters of membership functions, which are determined by the characteristics of market itself. Here, we present an iterative algorithm based on PSO to estimate the parameters of the membership functions. The PSO method aims to achieve a global optimal solution with a rapid convergence rate. The three stock markets of Taiwan, Japan, and Germany were analyzed to illustrate the performance of the proposed method. [Copyright &y& Elsevier]

Abstract: As an application of mechatronics, this paper presents the advances in surface-adaptive ground penetrating radar (GPR)-based anti-personnel landmine detection project in Nagoya University. These advances can be summarized in three items: (1) GPR manipulation where a low-pressure-tire vehicle capable of moving inside a mine field, to facilitate machine-based sensing in place of manual sensing, is applied; (2) enhancement of underground landmine suspects’ images through geography adaptive scanning and measurements signal processing of a vector frequency modulated continuous wave (FMCW) GPR; (3) GPR fusion with metal detector (MD) for automatic decision making through experimental-based fuzzy learnt fusion rules. The state-of-art of these advances as well as directions for future research work is to be presented. [ABSTRACT FROM AUTHOR]

Abstract: In this paper, we derive a new class of flexible threshold asymmetric Generalized Autoregression Conditional Heteroskedasticity (GARCH) models. We use this tool for analysis and modeling of the properties that are apparent in many financial time series. In general, the transmission of volatility in the stock market is time-varying, nonlinear, and asymmetric with respect to both positive and negative results. Given this fact, we adopt the method of fuzzy logic systems to modify the threshold values for an asymmetric GARCH model. Our simulations use stock market data from the Taiwan weighted index (Taiwan), the Nikkei 225 index (Japan), and the Hang Seng index (Hong Kong) to illustrate the performance of our proposed method. From the simulation results, we have determined that the forecasting of volatility performance is significantly improved if the leverage effect of clustering is considered along with the use of expert knowledge enabled by the GARCH model. [Copyright &y& Elsevier]

Abstract: Box–Jenkins (1970) models are often used to capture the autoregressive moving average of past observations of tourist arrivals from Japan to Taiwan and New Zealand. However, other explanatory variables, such as real income in the origin country, have also affected the demand for international travel. The purpose of this paper is to use the ARMAX model to investigate the dynamic relationship between tourism demand and real income of Japan, and to compare the findings with the single-equation model. Unit root tests and diagnostics are performed before estimating the income elasticity of travel demand by Japan for New Zealand and Taiwan based on seasonally unadjusted quarterly data for 1980(1) to 2004(2). The empirical results of the ARMAX model support the economic theory that the demand for international travel is positively related to income of the origin country. [Copyright &y& Elsevier]

Abstract: In this paper we present evidence of multifractality and herding behavior for a large set of Japanese stocks traded in the Tokyo Stock Exchange. We find evidence that herding behavior occurs in periods of extreme market movements. Therefore, based on the intuition behind the tests to detect herding phenomenon developed, for instance, in Christie and Huang [Christie W, Huang R. Following the pied pier: do individual returns herd around the market? Financ Analysts J 1995;51:31–7] and Chang et al. [Chang EC, Cheng JW, Khorana A. Examination of herd behavior in equity markets: an international perspective. J Bank Finance 2000;24:1651–99], we suggest that herding behavior may be one of the causes of multifractality. [Copyright &y& Elsevier]

Abstract: This paper employs a Markov Switching Panel model to measure business cycle turning points in Japan. This Markov Switching Panel model is simple and can easily be estimated following Hamilton''s [J.D. Hamilton, A new approach to the economic analysis of nonstationary time series and the business cycle, Econometrica 57 (1989) 357–384] method. We find that this model is highly capable of identifying Japanese recessionary dates, and it also has a forecast performance that is equal to that of the Markov Switching Vector Autoregressive model. The implication that emerges here is that governments, their agencies and other business leaders in Japan and elsewhere should also employ the Markov Switching Panel model to secure complementary data. [Copyright &y& Elsevier]

Abstract: The People''s Republic of China is one of the world''s most popular tourist destinations. This paper reviews the development of the Chinese inbound tourism industry after the cultural revolution and analyses tourist flows from Japan, which is the most important short-haul inbound market for China. Box-Jenkins univariate time series analysis facilitates an understanding of tourist arrival patterns in inbound tourism for China from Japan for the period 1986–2000. Tests for stationarity of tourist arrivals time series are also conducted. [Copyright &y& Elsevier]

This paper empirically analyzes the factors which determine the success of regional information policies. Based upon our field research on 36 local governments in Japan, we examine how each factor contributes to successful implementation of regional information policy by using the ordered probit analysis. Generally speaking, it appears reasonable to assume that economic and financial factors are most important. However, the most important was found to be human factors such as the leadership taken by the heads of local governments. We comprehensively analyze why this is the case, contrary to what the theory suggests. [Copyright &y& Elsevier]

One income distribution is preferable to another under any increasing and Schur-concave (S-concave) social welfare function (SWF) if and only if the generalized Lorenz (GL) curve of the first distribution lies above that of the second. Thus, testing for GL dominance of one distribution over another is of interest. The paper focuses on inference based on grouped data and makes two contributions: (i) it gives a new formula for the asymptotic variance–covariance matrix of a vector of sample GL curve ordinates, interpreting it as a method-of-moments (MM) estimator, and (ii) it proposes a new test for multivariate inequality restrictions, of which GL dominance is a special case. For the Japanese household income data grouped into deciles, the test accepts the null hypothesis that income distribution in Japan improved from 1979 to 1994. [Copyright &y& Elsevier]