Language：English   Publishing type：Research paper (scientific journal)   Publisher：Taylor & Francis  

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Language：English   Publishing type：Research paper (scientific journal)   Publisher：Taylor & Francis  

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Language：English   Publishing type：Research paper (scientific journal)   Publisher：Taylor & Trancis  

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Language：English   Publishing type：Research paper (scientific journal)   Publisher：JSciMed Central  

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Language：English   Publishing type：Research paper (scientific journal)   Publisher：Science Publications  

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Language：English   Publishing type：Research paper (scientific journal)   Publisher：Inderscience Enterprises Ltd.  

Prior empirical studies on the relationship between corporate diversification and firm performance have not considered data stationarity and have devoted little consideration to the dynamics of this relationship, the endogeneity problem, and causality factors. To overcome these econometric problems simultaneously, a panel vector autoregressive model is applied to product diversification data on Japanese firms. The empirical results suggest the followings. First, the panel unit-root test recommends the use of diversification, and not diversity. Second, product diversification measured by the Herfindahl index has no relationship with the other three firm performance variables, while product diversification measured by the entropy index marginally increases sales growth, leading to an increase in profitability. The empirical implications for business researchers are also provided.

DOI： 10.1504/IJAMS.2014.067188

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Language：English   Publishing type：Research paper (scientific journal)   Publisher：Inderscience  

Previous empirical studies on students' entrepreneurial intentions lack the viewpoint of career choice. This paper adopts a framework through which becoming an entrepreneur is the result of selecting from alternative careers by applying a multinomial logit model to survey data on 187 university students. The estimation results indicate that: 1) both entrepreneurial experience and the existence of an admired entrepreneur positively affect entrepreneurial intention
2) membership in the faculty of commerce positively affects entrepreneurial intention and negatively affects the intention to become a public employee
3) co-residence with family is negatively related to entrepreneurial intention. Copyright © 2014 Inderscience Enterprises Ltd.

DOI： 10.1504/IJESB.2014.059474

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Language：English   Publishing type：Research paper (scientific journal)   Publisher：SPRINGER  

Age effects and birth cohort effects have not been differentiated in happiness studies. In this paper, age-period-cohort decomposition is applied to happiness data in the US. Since the relationship is linear, such as age = period - cohort, it is not possible to identify the three effects. This paper considers four identification models: the polynomial age-effect model, the proxy-variable model, the orthogonal period-effect model, and the principal component model. Happiness data are obtained from the General Social Survey for 1972-2008. Except for the polynomial age-effect model, three alternative models provide similar results. In particular, there is little difference between the decomposition results obtained by the orthogonal period-effect model and by the principal component model. The age effect shows downward movements for 18-55 and for 80-89, an upward movement for 56-69, and an almost flat movement for 70-79. The period effect shows cyclical movements slightly similar to unemployment rates fluctuations. The cohort effect shows a downward movement for the birth cohorts of 1894-1936, a dip for 1945-1958 (baby boomers), an upward movement for 1959-1969, and an almost flat movement for 1970-1987.

DOI： 10.1007/s10902-011-9320-4

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Language：English   Publishing type：Research paper (scientific journal)   Publisher：Taylor & Francis  

Firm data are accumulated on a yearly basis. In view of the linear relationship of firm age+foundation year=survey year, the fluctuations of firm data classified by age and period cannot be decomposed into age, period and cohort (foundation year) effects. Three decomposition methods are briefly reviewed and applied to Japanese data on new ventures founded since 1995. Regarding sales and employment growth, the age effect is the largest with a downward trend, and the cohort effect is negligible. Regarding labour productivity, the age effect indicates upward movements, and the cohort effect is negligible. The reason of the negligible cohort effect is discussed. © 2013 Taylor &amp
Francis.

DOI： 10.1080/00036846.2011.589815

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Language：English   Publishing type：Research paper (scientific journal)   Publisher：ELSEVIER SCIENCE INC  

In this paper, the aggregate data on firm survival-classified by firm age and foundation year-are decomposed into age, period, and cohort effects. Since there is a linear relationship such that age = period - cohort, the three effects cannot be uniquely identified. A simple decomposition method is newly proposed and applied to aggregate data on the hazard rates of Japanese manufacturing firms. The performances of the proposed method are compared with those of four alternative methods via Monte Carlo simulations. (C) 2012 Elsevier Inc. All rights reserved.

DOI： 10.1016/j.amc.2012.06.067

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Language：English   Publishing type：Research paper (scientific journal)   Publisher：ELSEVIER SCIENCE BV  

Structural breaks in a trending variable have been specified as changes in the drift parameter in the trend component, but extraordinary shocks causing these breaks have not been explicitly formulated. In this paper, the Hodrick-Prescott filter is extended by assuming two kinds of variance for the system noise driving the trend component: the larger one adopted in a point of time causing a trend break, and the smaller one adopted for remaining sequences. The number and location of structural breaks are determined by information criteria. In the proposed method, extraordinary shocks themselves can be illustrated. A Monte Carlo study shows the efficacy of the proposed model. Empirical results suggest that except for the UK, extraordinary shocks in quarterly time series of industrial production are detected for remaining six developed countries. Finally, it is shown that the proposed method considerably outperforms the other competing methods in correctly detecting business cycles. (c) 2012 Elsevier B.V. All rights reserved.

DOI： 10.1016/j.econmod.2012.03.022

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Language：English   Publishing type：Research paper (scientific journal)   Publisher：ROUTLEDGE JOURNALS, TAYLOR & FRANCIS LTD  

The determinants of Japanese city population growth for the period 2000 to 2005 are empirically examined with particular attention to local public finance. The selection of one Fiscal Indicator (FI) from four alternatives ordinary balance ratio (OBR), ratio of outstanding borrowing (ROB) to the ordinary account, debt service payment ratio (DSPR) and financial power index (FPI) - and the consideration of spatial auto-correlation provide 12 regression models. In each regression, six additional explanatory variables are considered with reference to earlier empirical studies. Empirical results suggest that (1) three FIs, excluding DSPR, are significant; and (2) the number of local government officers and the ratio of graduates of not-less-than junior college are highly significant in all specifications.

DOI： 10.1080/00036846.2011.556592

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Language：English   Publishing type：Research paper (scientific journal)   Publisher：WILEY-BLACKWELL  

This paper proposes a new forecasting method in which the cointegration rank switches at unknown times. In this method, time series observations are divided into several segments, and a cointegrated vector autoregressive model is fitted to each segment. The goodness of fit of the global model, consisting of local models with different cointegration ranks, is evaluated using the information criterion (IC). The division that minimizes the IC defines the best model. The results of an empirical application to the US term structure of interest rates and a Monte Carlo simulation suggest the efficacy as well as the limitations of the proposed method. Copyright (C) 2010 John Wiley & Sons, Ltd.

DOI： 10.1002/for.1191

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Language：English   Publishing type：Research paper (scientific journal)   Publisher：Oxford University Press  

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Language：English   Publishing type：Research paper (scientific journal)   Publisher：Taylor & Francis  

Household life cycle has been widely used as a determinant of consumer behavior and a basis for market segmentation. Repeated cross-section data on the meat share in household consumption in the United States and Japan, classified by age and period, are decomposed into age, period, and birth cohort effects. Empirical evidence suggests the following: (a) the cohort effect is the largest in the United States, whereas the age effect is the largest in Japan
(b) the U.S. age effect increases for the age group 15-34, whereas the Japanese age effect decreases for the age group 25-34
(c) the Japanese period effect reveals a clear downward trend
and (d) the U.S. cohort effect decreases for the birth cohort 1900-1949. Furthermore, implications for meat producers and sellers are provided. © Taylor &amp
Francis Group, LLC.

DOI： 10.1080/08974438.2011.558765

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Language：English   Publishing type：Research paper (scientific journal)   Publisher：TAYLOR & FRANCIS LTD  

Age-period-cohort decomposition requires an identification assumption because there is a linear relationship between age, survey period, and birth cohort (age + cohort = period). This paper proposes new decomposition methods based on factor models such as principal components model and partial least squares model. Although factor models have been applied to overcome the problem of many observed variables with possible co-linearity, they are applied to overcome the perfect co-linearity among age, period, and cohort dummy variables. Since any unobserved factor in the factor model is represented as a linear combination of the observed variables, the parameter estimates for age, period, and cohort effects are automatically obtained after the application of these factor models. Simulation results suggest that in almost all cases, the performance of the proposed method is better than that of a conventional econometric method. Empirical examples are also provided.

DOI： 10.1080/00949655.2010.507763

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Language：English   Publishing type：Research paper (scientific journal)   Publisher：PHYSICA-VERLAG GMBH & CO  

The purpose of this article is to provide three new empirical perspectives on the validity of the value of the smoothing parameter in the Hodrick-Prescott filter (HP filter): Bayesian smoothness perspective, output gap perspective, and forecasting perspective. The quarterly time series of industrial production and capacity utilization for developed countries are analyzed. The empirical results suggest that (1) from the Bayesian smoothness perspective, the HP filter with 1600 as the value of the smoothing parameter (HP1600 filter) is mostly unable to provide a sufficiently smooth trend component; (2) from the output gap perspective, the HP1600 filter provides a poor cycle component; (3) from the forecasting perspective, the HP1600 filter is most suitable for eight-step or nine-step ahead forecasting.

DOI： 10.1007/s00181-009-0332-4

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Language：English   Publishing type：Research paper (scientific journal)   Publisher：SPRINGER  

This paper shows the usefulness of cohort analysis for generational marketing. Aggregate data classified by age and period are decomposed into age, period, and generational cohort effects. We compare two cohort-analysis models, the constrained multiple regression model and the Bayesian cohort model. The empirical results that are common to the household vehicle expenditure ratio in the U.S. and Japan are as follows: (1) among a total of three effects, the period effect is the smallest; (2) with the exception of the latest birth cohort, the cohort effect shows a clear upward trend; (3) the age effect decreases in the 20s and 30s, and next increases with a peak detected in the late 50s, and finally decreases. We provide marketing implications for cohort segmentation and forecasting.

DOI： 10.1007/s11002-009-9077-2

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Language：English   Publishing type：Research paper (scientific journal)   Publisher：ROUTLEDGE JOURNALS, TAYLOR & FRANCIS LTD  

A new method for detecting the parameter changes in generalized autoregressive heteroskedasticity GARCH (1,1) model is proposed. In the proposed method, time series observations are divided into several segments and a GARCH (1,1) model is fitted to each segment. The goodness-of-fit of the global model composed of these local GARCH (1,1) models is evaluated using the corresponding information criterion (IC). The division that minimizes IC defines the best model. Furthermore, since the simultaneous estimation of all possible models requires huge computational time, a new time-saving algorithm is proposed. Simulation results and empirical results both indicate that the proposed method is useful in analysing financial data.

DOI： 10.1080/02664760902914524

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Language：English   Publishing type：Research paper (scientific journal)   Publisher：Springer  

Since population censuses are not annually implemented, population estimates are needed for the intercensal period. This paper describes simultaneous implementations of the temporal interpolation and forecasting of the population census data, aggregated by age and period. Since age equals period minus cohort, age-period-cohort decomposition suffers from the identification problem. In order to overcome this problem, the Bayesian cohort (BC) model is applied. The efficacy of the BC model for temporal interpolation is examined in comparison with official Japanese population estimates. Empirical results suggest that the BC model is expected to work well in temporal interpolation. Regarding the age-period-cohort decomposition of the Japanese census data, it is shown that the cohort effect is the largest while the other two effects are very small but not negligible. With regard to the forecasting of the Japanese population, the official population forecast considerably outperforms the BC forecast in most forecast horizons. However, the pace of increase in root mean square error for longer-term forecasting is larger in the official population forecast than in the BC forecasts. As a result, a variant of the BC forecast is best for 10-year forecast. © 2010 Springer Science &amp
Business Media B.V.

DOI： 10.1007/s12546-010-9028-z

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Language：English   Publishing type：Research paper (scientific journal)   Publisher：ELSEVIER SCIENCE BV  

The coexistence of cycles with different periods complicates the assessment of the current macroeconomic conditions. In order to overcome this problem, a modeling of multiple autoregressive processes in a univariate time series is presented. In the proposed model, individual autoregressive processes are assumed to be mutually uncorrelated, and the number of individual autoregressive processes is determined using information criteria. Simulation results show that the proposed procedure is sufficiently applicable for measuring major and minor cycles. Empirical applications suggest the usefulness and limitations of the proposed method. (C) 2009 Elsevier B.V. All rights reserved.

DOI： 10.1016/j.econmod.2009.04.006

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Language：English   Publishing type：Research paper (scientific journal)   Publisher：ELSEVIER SCIENCE BV  

This paper examines the usefulness of metaphors by comparing the assessments of the current economic conditions of the US and Japan made by the countries' respective monetary policy authorities. In particular, this paper compares the role played by metaphors in creating a technical lexicon for business cycle phases in each language, and presents three main empirical findings. First, in both the US and Japan, metaphors are used in keeping with the business cycle phases with which each economy is faced. Second, many of the verbal, adjectival and adverbial terms can be attributed solely to the mechanical metaphor in the US, while there is no incidence of this use in the case of Japan. Third, there are more metaphoric adjectives or adverbs in the assessments of the US economy than in those of the Japanese economy. These empirical findings can be useful for second language instruction in economics. (c) 2008 Elsevier B.V. All rights reserved.

DOI： 10.1016/j.pragma.2008.12.005

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Language：English   Publishing type：Research paper (scientific journal)   Publisher：WILEY-BLACKWELL  

Two related-variables selection methods for temporal disaggregation are proposed. In the first method, the hypothesis tests for a common feature (cointegration or serial correlation) are first performed. If there is a common feature between observed aggregated series and related variables, the conventional Chow-Lin procedure is applied. In the second method, alternative Chow-Lin disaggregating models with and without related variables are first estimated and the corresponding values of the Bayesian information criterion (BIC) are stored. It is determined on the basis of the selected model whether related variables should be included in the Chow-Lin model. The efficacy of these methods is examined via simulations and empirical applications. Copyright (C) 2008 John Wiley & Sons, Ltd.

DOI： 10.1002/for.1115

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Language：English   Publishing type：Research paper (scientific journal)   Publisher：PHYSICA-VERLAG GMBH & CO  

This paper examines the forecasting of growth cycle turning points by comparing the performances of US and Japanese professional forecasters with those of a simple time-series model, using real-time data. The empirical results, obtained after performing contingency table analyses and visual inspections, indicate that the US professional forecasters considerably outperform the simple time-series model; however, the Japanese professional forecaster is comparable to the simple time-series model in the visual inspections of major turning points.

DOI： 10.1007/s00181-008-0194-1

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Language：English   Publishing type：Research paper (scientific journal)   Publisher：ELSEVIER SCIENCE BV  

A new method for detecting regime switches between different probability distributions in financial time series is shown. In the proposed method, time series observations are divided into several segments, and a Gaussian model or a Cauchy model is fitted to each segment. The goodness of fit of the global model composed of these local models is evaluated using the Bayesian information criterion (BIC), and the division which minimizes this criterion defines the best model. Based on this method, for example, the specification with a Gaussian process in the first half and with a Cauchy process in the second half becomes applicable. Empirical applications and data-based simulations are presented to indicate the efficacy of the proposed method. (C) 2008 IMACS. Published by Elsevier B.V. All rights reserved.

DOI： 10.1016/j.matcom.2008.08.012

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Language：English   Publishing type：Research paper (scientific journal)   Publisher：Taylor & Francis  

This article considers six alternative models-the normal model, normal model with parameter change, t model, t model with parameter change, normal and t model and the t and normal model-and the best model is selected using the Bayesian information criterion. The simulation results suggest that the proposed method works well with regard to all the models, with the exception of the t model with parameter change, which is sometimes unidentified. Empirical results show that in two out of the six countries, the monthly time series of stock returns are generated from the normal distribution before the switch point and from the t distribution after the switch point. Both the switch points are caused by international economic crises such as the turmoil in the international monetary system in 1971 or the oil shock of 1974.

DOI： 10.1080/09603100701735920

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Language：English   Publishing type：Research paper (scientific journal)   Publisher：Elsevier  

Aggregate data of tax burdens in the U.S. and Japan, classified by period and by age, are decomposed into age, period, and cohort effects using the Bayesian cohort models which were developed to overcome the identification problem in cohort analysis. Main findings are that in both countries the age effects are the largest and the cohort effects are obscure or negligible and that in both countries significant intergenerational inequality is not observed. © 2008.

DOI： 10.1016/j.socec.2008.04.010

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Language：English   Publishing type：Research paper (scientific journal)   Publisher：SPRINGER  

Aggregate data on birth rates in the U.S. and Japan, classified by period and by age, are decomposed into age, period, and cohort effects using Bayesian cohort models that were developed to overcome the identification problem in cohort analysis. Main findings are fivefold. First, age, period, and cohort effects movements are all larger in Japan than in the U.S. Second, in both countries, age effects are the largest and are roughly consistent with the life-cycle movements showing an inverted U shape. Third, Easterlin's cohort size hypothesis roughly fits U.S. birth rates but not Japanese birth rates. Fourth, despite rapid decline of total fertility rates in Japan in last three decades, period effects have been on an upward trend since the early 1990s. Finally, upward and downward cohort effects movements in Japan are derived by rapid economic growth and the Equal Employment Opportunity Law, respectively.

DOI： 10.1007/s11113-008-9074-9

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Language：English   Publishing type：Research paper (scientific journal)   Publisher：BLACKWELL PUBLISHING  

Aggregate data on US earnings, classified by period and by age, are decomposed into age, period and cohort effects, using the Bayesian cohort models, which were developed to overcome the identification problem in cohort analysis. The main findings, obtained by comparing college and high school graduates, are threefold. First, the age effects show a downward trend for the age group of 45-49 onwards for high school graduates but do not show any such trend for college graduates. Second, the period effects show a downward trend for high school graduates but reveal no such trend for college graduates. Third, the cohort effects are negligible for both college and high school graduates.

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Language：English   Publishing type：Research paper (scientific journal)   Publisher：ROUTLEDGE JOURNALS, TAYLOR & FRANCIS LTD  

Growth cycles are often mistaken for business cycles, although these two have different statistical properties. In order to differentiate between them in a statistically satisfactory manner, the Bayesian information criterion-(BIC) based model-selection approach is presented. Business cycles are described by the cyclical trend model, and growth cycles are described by the trend-plus-cycle model. Whether the observed time series is derived from business cycles or from growth cycles is determined as a result of model selection. It is shown via data-based simulations that the proposed method works well in most situations. Empirical results obtained for 15 countries suggest that the business cycle model is selected for five countries, the growth cycle model is selected for two countries and the trend-plus-noise model is selected for eight countries.

DOI： 10.1080/00036840600749862

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Language：English   Publishing type：Research paper (scientific journal)   Publisher：ROUTLEDGE JOURNALS, TAYLOR & FRANCIS LTD  

A new method is developed for detecting regime switches between cointegration and no-cointegration at unknown times allowing for switching lag structure. In this method, time-series observations are divided into several segments, and a regression model with or without cointegration is fitted to each segment. The goodness of fit of the global model composed of these local models is evaluated using the corresponding modified information criterion, and the division which minimizes this criterion defines the best model. Simulation results suggest that the proposed method works well. Empirical results indicate that money demand is well described by the proposed method in Canada, UK and Japan.

DOI： 10.1080/00036840600843962

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Language：English   Publishing type：Research paper (scientific journal)   Publisher：TAYLOR & FRANCIS INC  

A method of information-criterion-based cointegration detection using dynamic factor models is proposed. The results of the data-based and non data-based Monte Carlo simulations suggest that this method is as effective as conventional hypothesis-testing methods. In the proposed method, an observed multivariate time series is described in terms of common stochastic trends plus stationary autoregressive cycles. Then the best model is selected from among alternative models obtained by changing the number of common stochastic trends, on the basis of information criteria. Consequently, the cointegration rank is determined on the basis of the selected model. Two advantages of the proposed method are also discussed.

DOI： 10.1080/03610910701723997

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Language：English   Publishing type：Research paper (scientific journal)   Publisher：TAYLOR & FRANCIS INC  

In the conventional hypothesis-testing approach to the detection of a unit root and a trend break, selections of the outlier type (additive or innovational) and of the break type (jump or kink) are carried out arbitrarily, because there is no generally accepted statistical technique. To overcome this problem, a model-selection approach using the modified Bayesian information criterion (MBIC) is proposed. Whether the observed time series contains a unit root and a trend break is determined as a result of model selection from among alternative models with and without unit root and trend break. The efficacy of the proposed approach is verified using comprehensive simulations.

DOI： 10.1080/03610910701724003

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Language：English   Publishing type：Research paper (scientific journal)   Publisher：ROUTLEDGE JOURNALS, TAYLOR & FRANCIS LTD  

A flexible method for the trend-cycle decomposition of nonstationary multivariate time series is proposed. In this method, each time series is decomposed into a common or individual stochastic trend, a common or individual stationary cycle, and observation noise components. The combination of variables for a common trend or for a common cycle and the introduction of economic-theory-based trend are flexible and determined using the Akaike information criterion. Simulation results suggest that the proposed method works well, and two examples are shown to illustrate the efficacy of the proposed method, particularly by investigating the predictive accuracy.

DOI： 10.1080/00036840600749573

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Language：English   Publishing type：Research paper (scientific journal)   Publisher：ROUTLEDGE JOURNALS, TAYLOR & FRANCIS LTD  

The validity of trend-cycle decomposition using the unobserved component model is examined via Monte Carlo simulations. It is shown that the nearer to the unit-root process the assumed cycle component and/or the larger the assumed innovation covariance, the more frequent the occurrence of the boundary estimate for the innovation covariance, that the nearer to the unit-root process the assumed cycle component in the case of applying the model with zero restriction on the innovation covariance, the more frequent the occurrence of a linear time trend in the trend estimation, and that a linear time trend cannot be obtained from the model without zero restriction.

DOI： 10.1080/13504850600706164

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Language：English   Publishing type：Research paper (scientific journal)   Publisher：Taylor & Francis  

Aggregate data of homeownership rates in the US and Japan, classified by period and by age, are decomposed into age, period, and cohort effects using the Bayesian cohort models which were developed to overcome the identification problem in cohort analysis. The main data-based findings are threefold. First, in both the countries, the age effects are the largest and the period effects are the smallest. Second, US and Japanese age effects are almost identical and consistent with some life cycle theories. Third, cohort effects are larger in the US than in Japan. In particular, the downward trend in the US cohort effects in the case of baby boomers is explained by two hypotheses. Furthermore, some policy implications are provided.

DOI： 10.1080/14616710802256702

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Language：English   Publishing type：Research paper (scientific journal)   Publisher：ROUTLEDGE JOURNALS, TAYLOR & FRANCIS LTD  

A model-selection-based unit-root detection by using the Bayesian information criterion is proposed. First, six alternative model classes are obtained considering the presence or absence of a unit root and considering three kinds of deterministic terms: no constant, constant, constant and trend. Second, given the selected model class, the best model is selected from the alternative models with different lags. Third, the best of the entire model set comprising the six models obtained in the preceding step is selected. Finally, whether an observed time series contains a unit root is determined on the basis of the selected model. Simulation results suggest that the proposed method is at least comparable to and often better than the sequential testing method provided by Dolado et al. (1990). Empirical results obtained by the proposed method are more convincing than those obtained by the sequential testing method and suggest that the hysteresis hypothesis can be applied to monthly time series of the unemployment rates for all the six countries under consideration.

DOI： 10.1080/00036840600970351

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Language：English   Publishing type：Research paper (scientific journal)   Publisher：SPRINGER  

An efficient treatment of practical issues on detecting multiple structural changes is presented. The efficacy of this method is examined by comparing the. conventional hypothesis-testing method via comprehensive simulations and empirical applications. The method recommended is a model-selection using the Bayesian information criterion and allowing for heteroscedasticity. Empirical results show that the first structural change of Japanese economic growth occurred in 1974Q2, which was detected in 1979Q4, and that the second structural change occurred in 1992Q2, which was detected in 1998Q1. Two advantages of the model-selection method compared to the hypothesis-testing method are also discussed.

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Language：English   Publishing type：Research paper (scientific journal)   Publisher：Springer  

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Language：English   Publishing type：Research paper (scientific journal)   Publisher：JOHN WILEY & SONS LTD  

A modeling approach to real-time forecasting that allows for data revisions is shown. In this approach, an observed time series is decomposed into stochastic trend, data revision, and observation noise in real time. It is assumed that the stochastic trend is defined such that its first difference is specified as an AR model, and that the data revision, obtained only for the latest part of the time series, is also specified as an AR model. The proposed method is applicable to the data set with one vintage. Empirical applications to real-time forecasting of quarterly time series of US real GDP and its eight components are shown to illustrate the usefulness of the proposed approach. Copyright (c) 2007 John Wiley & Sons, Ltd.

DOI： 10.1002/for.1032

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Language：English   Publishing type：Research paper (scientific journal)   Publisher：JOHN WILEY & SONS LTD  

Aggregate data on household health insurance expenditure in the US and Japan that are classified by period and age are decomposed into age, period, and cohort effects by using the Bayesian cohort models. These models are developed to overcome the identification problem involved in cohort analysis. Despite the differences between the health insurance systems of the two countries, three interesting empirical findings are obtained. First, in both the countries, the age effects are the most influential, and the cohort effects have negligible influence. The latter provides a striking policy implication since the generational imbalance in social security expenditures is widely recognized in developed countries. Second, in both the countries, the period effects show a roughly upward trend. Finally, the age effects exhibit a roughly upward movement for all age groups in the US; however, in Japan, these effects show a downward movement for the 55-59 age group due to the changes in the health insurance system on retirement. (C) 2006 John Wiley & Sons, Ltd.

DOI： 10.1002/hec.1179

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Language：English   Publishing type：Research paper (scientific journal)   Publisher：ELSEVIER SCIENCE BV  

This paper investigates two problems which a practitioner of Johansen's cointegration analysis faces: the pre-testing problem and the inconsistency problem. Johansen's cointegration analysis requires hypothesis testing at four stages, and thus Type I errors accumulate. In addition, it often occurs that the results of unit root tests and those of cointegration tests are inconsistent. In order to overcome these problems, an information-criterion-based model selection method for jointly detecting unit roots and cointegration is proposed. Through empirical applications and Monte Carlo simulations, the usefulness of this method is demonstrated. (C) 2006 IMACS. Published by Elsevier B.V. All rights reserved.

DOI： 10.1016/j.matcom.2006.08.007

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Language：English   Publishing type：Research paper (scientific journal)   Publisher：Taylor & Francis  

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Language：English   Publishing type：Research paper (scientific journal)   Publisher：ROUTLEDGE JOURNALS, TAYLOR & FRANCIS LTD  

The zero-correlation restriction for trend and cycle innovations is empirically examined using an international data set. Unlike the result obtained by Morley et al. (2003), a model with zero-correlation restriction is selected for all nine countries. Since the adequacy of zero-correlation restriction depends on the autoregressive (AR) order assumed, an information-criterion-based model-selection method is applied. In this method, first, possible alternative models are considered by changing the AR order and by including or excluding the zero-correlation restriction, and then the best model is selected from among them. Consequently, it is determined on the basis of the selected model whether the zero-correlation restriction should be imposed.

DOI： 10.1080/13504850600705893

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Language：English   Publishing type：Research paper (scientific journal)   Publisher：ROUTLEDGE JOURNALS, TAYLOR & FRANCIS LTD  

International evidence on the effects of monetary policy presented by Sims (1992) is reexamined by spectral decompositions as well as by impulse response functions. The results obtained using spectral decompositions suggest that money stock innovations can be regarded as monetary policy shocks, while the results obtained using impulse response functions show little clear evidence.

DOI： 10.1080/13504850600592606

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Language：English   Publishing type：Research paper (scientific journal)   Publisher：ELSEVIER SCIENCE INC  

A unit root is detected using the values of the Bayesian information criterion (BIC) of a battery of alternative models with and without a unit root. ARMA(1, 1)-based simulation results suggest that the proposed method generally outperforms influential unit-root tests except in the case of a small sample size with a large negative MA(1) parameter. (c) 2006 Elsevier Inc. All rights reserved.

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Language：English   Publishing type：Research paper (scientific journal)   Publisher：Springer  

Aggregate data of female labor participation rates in U.S. and Japan, classified by period and by age, are decomposed into age, period, and cohort effects using innovative Bayesian cohort models that were developed to overcome the identification problem in cohort analysis. The main findings are that in both countries, age effects are the largest and period effects are the smallest
in both countries, age effects are roughly consistent with life-cycle movements expected by labor economics, but the negative effects of marriage and/or childbearing on women's labor supply in Japan are much larger than those observed in the U.S.
and in both countries, upward movements of cohort effects during 1930-1960s were found. However, cohort effects are larger for the U.S. than for Japan. All the cohort results are roughly consistent with the marriage squeeze hypothesis and the Easterlin hypothesis. © Springer Science+Business Media, LLC 2006.

DOI： 10.1007/s11150-006-0013-4

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Language：English   Publishing type：Research paper (scientific journal)   Publisher：JOHN WILEY & SONS LTD  

This paper compares two methods of analyzing aggregate data that is classified by period and age. Because there is a linear relationship among age, period, and cohort, it is not possible to distinguish the separate effects without employing an identifying assumption. The first method, which is applied in the economics literature, assumes that period effects are orthogonal to a linear time trend. The second method, which is applied in the statistics literature, assumes that the effect parameters change gradually. Simulation results suggest that the performances of both methods are comparable. The results of applying the second method to household saving rates suggest that period effects had a negligible influence in the United States but considerable influence in Japan. Copyright (c) 2006 John Wiley & Sons, Ltd.

DOI： 10.1002/jae.906

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Language：English   Publishing type：Research paper (scientific journal)   Publisher：JOHN WILEY & SONS LTD  

The existence or non-existence of measurement error (ME) in observed time series is examined not by hypothesis testing but by model selection using the values of information criteria of a battery of alternative models with and without ME. Whether the time series contains ME is determined as a result of model selection. This method is compared with recently proposed hypothesis-testing method. Simulation results suggest that the performances of the proposed method are usually comparable to and sometimes better than those of the hypothesis-testing method. The proposed method is applied to monthly time series of industrial production for fifteen developed countries. Obtained results indicate that MEs are detected for at least one and at most seven countries. Copyright (c) 2006 John Wiley & Sons, Ltd.

DOI： 10.1002/asmb.617

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Language：English   Publishing type：Research paper (scientific journal)   Publisher：Taylor & Francis  

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Language：English   Publishing type：Research paper (scientific journal)   Publisher：ELSEVIER SCIENCE INC  

A new method for differentiating between a coefficient break and a volatility break is proposed. In the proposed method, time series observations are divided into several segments, and an autoregressive model is fitted to each segment. The goodness of fit of the global model composed of these local models is evaluated using the Bayesian information criterion, and the division which minimizes this criterion defines the best model. The proposed method makes a mixture model, such as that with a volatility break in the first break and a coefficient break in the second break, applicable. Simulation results show the efficacy and limitations of the proposed method. Empirical applications to quarterly time series of industrial production for 19 countries provide interesting results. (c) 2005 Elsevier Inc. All rights reserved.

DOI： 10.1016/j.amc.2005.09.049

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Language：English   Publishing type：Research paper (scientific journal)   Publisher：ELSEVIER SCIENCE BV  

An information criterion-based model selection method is proposed for monitoring unit root and multiple structural changes. In this method, a battery of possible models is considered by changing the integration order (I(0) or I(1)) and the combinations of change points. Next, the best model is selected from among alternative models via a modified Bayesian information criterion (BIC). Accordingly, on the basis of the selected model, the process that generates the observed time series is determined. The BIC is modified in order to adjust the frequency count of incorrectly selecting stationary models via the conventional BIC. The simulation results of monitoring unit root and structural change suggest that the proposed method outperforms the conventional hypothesis testing method in terms of detection accuracy and detection speed. Furthermore, the empirical results suggest that the proposed method exhibits better performances with regard to detection stability and forecastability. (c) 2006 IMACS. Published by Elsevier B.V. All rights reserved.

DOI： 10.1016/j.matcom.2006.01.003

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Language：English   Publishing type：Research paper (scientific journal)   Publisher：ROUTLEDGE JOURNALS, TAYLOR & FRANCIS LTD  

Man), variables used in economic forecasting are recorded with measurement error (ME). It is therefore found that an autoregressive model without exclusion of ME from observed time series may fail to correctly detect any periodicity contained and this results in poor forecasting performances. The purpose of this paper is to propose a model-selection method for forecasting economic time series with ME. In this method the existence or nonexistence of ME is determined by evaluating the values of the Akaike information criterion (AIC) of a battery of alternative models with and without ME. The results of forecasting 26 business cycle indicators in Japan are shown in order to demonstrate the efficacy of the proposed method.

DOI： 10.1080/13504850500119161

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Language：English   Publishing type：Research paper (scientific journal)   Publisher：ELSEVIER SCIENCE BV  

This paper presents a model-selection method for unit-root detection allowing for measurement error. Simulation results show that the proposed method gives better performances than the filtered least-squares method. (c) 2005 Elsevier B.V. All rights reserved.

DOI： 10.1016/j.spl.2005.04.059

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Language：English   Publishing type：Research paper (scientific journal)   Publisher：JOHN WILEY & SONS LTD  

It often occurs that no model may be exactly right, and that different portions of the data may favour different models. The purpose of this paper is to propose a new procedure for the detection of regime switches between stationary and nonstationary processes in economic time series and to show its usefulness in economic forecasting. In the proposed procedure, time series observations are divided into several segments, and a stationary or nonstationary autoregressive model is fitted to each segment. The goodness of fit of the global model composed of these local models is evaluated using the corresponding information criterion, and the division which minimizes the information criterion defines the best model. Simulation and forecasting results show the efficacy and limitations of the proposed procedure. Copyright (c) 2005 John Wiley & Sons, Ltd.

DOI： 10.1002/for.941

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Language：English   Publishing type：Research paper (scientific journal)   Publisher：ROUTLEDGE TAYLOR & FRANCIS LTD  

This paper examines the existence of structural breaks in the output time series of 84 Japanese manufacturing industries. The main result is that the effect of the bubble burst in the early 1990s was so limited that on the basis of value added, only 28% of production had structural breaks.

DOI： 10.1080/13504850500044278

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