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Statistical analysis of mixed frequency data: Theory and macroeconomic applications

Research Project

Project/Area Number 16K17104
Research Category

Grant-in-Aid for Young Scientists (B)

Allocation TypeMulti-year Fund
Research Field Economic statistics
Research InstitutionKobe University

Principal Investigator

Motegi Kaiji  神戸大学, 経済学研究科, 講師 (60742848)

Research Collaborator GHYSELS Eric  
HILL Jonathan B.  
SADAHIRO Akira  
Project Period (FY) 2016-04-01 – 2019-03-31
Project Status Completed (Fiscal Year 2018)
Budget Amount *help
¥3,900,000 (Direct Cost: ¥3,000,000、Indirect Cost: ¥900,000)
Fiscal Year 2018: ¥1,040,000 (Direct Cost: ¥800,000、Indirect Cost: ¥240,000)
Fiscal Year 2017: ¥1,300,000 (Direct Cost: ¥1,000,000、Indirect Cost: ¥300,000)
Fiscal Year 2016: ¥1,560,000 (Direct Cost: ¥1,200,000、Indirect Cost: ¥360,000)
Keywords時系列分析 / Mixed Data Sampling / グランジャー因果性検定 / ホワイトノイズ検定 / 最大値検定 / マクロ経済分析 / 失われた10年 / 株式市場の効率性 / 計量経済学 / グランジャー因果性 / 応用マクロ経済学 / 経済統計学
Outline of Final Research Achievements

Time series are sampled at various frequencies including monthly, quarterly, and yearly. Mixed Data Sampling (MIDAS) econometrics is an innovative approach to analyze mixed frequency data without performing temporal aggregation. In the present research, I resolve three problems which are related with MIDAS. First, I propose a mixed frequency Granger causality test (i.e., test of incremental predictive ability) that operates well even when the ratio of sampling frequencies is relatively large. Second, I propose a white noise test (i.e., test of unpredictability) that can be applied to a residual from a regression model involving many parameters. Third, I revealed that the declined Japanese stock prices were a main cause of the sluggish private investment in Japan during the Lost Decade.

Academic Significance and Societal Importance of the Research Achievements

統計学や計量経済学において現在最も関心を集めている研究テーマのひとつは、推定すべきパラメータの数や検定すべき仮説の数がサンプルサイズに比べて大きいとき、推定や検定をどのように実行すべきかという問題である(高次元の問題)。本研究で提案したグランジャー因果性検定とホワイトノイズ検定は、MIDASに関する問題のみならず、高次元の問題全般に対する画期的な解決策であるといえる。さらに、本研究で行った日米のマクロ経済分析や世界の株式市場の効率性の検証は、資産運用、経営戦略、財政金融政策などの実務に対して極めて有用な知見を与えるものである。

Report

(4 results)
  • 2018 Annual Research Report   Final Research Report ( PDF )
  • 2017 Research-status Report
  • 2016 Research-status Report
  • Research Products

    (28 results)

All 2019 2018 2017 2016 Other

All Int'l Joint Research (3 results) Journal Article (3 results) (of which Int'l Joint Research: 2 results,  Peer Reviewed: 3 results) Presentation (17 results) (of which Int'l Joint Research: 10 results,  Invited: 7 results) Remarks (5 results)

  • [Int'l Joint Research] UNC Chapel Hill(米国)

    • Related Report
      2018 Annual Research Report
  • [Int'l Joint Research] UNC Chapel Hill(米国)

    • Related Report
      2017 Research-status Report
  • [Int'l Joint Research] Renmin University of China(China)

    • Related Report
      2017 Research-status Report
  • [Journal Article] Testing a large set of zero restrictions in regression models, with an application to mixed frequency Granger causality2019

    • Author(s)
      Eric Ghysels, Jonathan B. Hill, and Kaiji Motegi
    • Journal Title

      Journal of Econometrics

      Volume: forthcoming

    • Related Report
      2018 Annual Research Report
    • Peer Reviewed / Int'l Joint Research
  • [Journal Article] Testing the white noise hypothesis of stock returns2019

    • Author(s)
      Jonathan B. Hill and Kaiji Motegi
    • Journal Title

      Economic Modelling

      Volume: 76 Pages: 231-242

    • DOI

      10.1016/j.econmod.2018.08.003

    • Related Report
      2018 Annual Research Report
    • Peer Reviewed / Int'l Joint Research
  • [Journal Article] Sluggish private investment in Japan’s Lost Decade: Mixed frequency vector autoregression approach2018

    • Author(s)
      Kaiji Motegi; Akira Sadahiro
    • Journal Title

      North American Journal of Economics and Finance

      Volume: 43 Pages: 118-128

    • DOI

      10.1016/j.najef.2017.10.009

    • Related Report
      2017 Research-status Report
    • Peer Reviewed
  • [Presentation] A max-correlation white noise test for weakly dependent time series2019

    • Author(s)
      Kaiji Motegi
    • Organizer
      Essex Centre for Macro and Financial Econometrics Seminar Series
    • Related Report
      2018 Annual Research Report
    • Int'l Joint Research / Invited
  • [Presentation] A max-correlation white noise test for weakly dependent time series2019

    • Author(s)
      Kaiji Motegi
    • Organizer
      15th International Conference, Western Economic Association International
    • Related Report
      2018 Annual Research Report
    • Int'l Joint Research
  • [Presentation] A max-correlation white noise test for weakly dependent time series2019

    • Author(s)
      Kaiji Motegi
    • Organizer
      The 15th International Symposium on Econometric Theory and Applications
    • Related Report
      2018 Annual Research Report
    • Int'l Joint Research
  • [Presentation] Calibration Estimation for Semiparametric Copula Models under Missing Data2018

    • Author(s)
      Kaiji Motegi
    • Organizer
      Economics and Economic Growth Centre Seminar Series, School of Social Sciences, Nanyang Technological University
    • Related Report
      2017 Research-status Report
    • Int'l Joint Research / Invited
  • [Presentation] Calibration Estimation for Semiparametric Copula Models under Missing Data"2018

    • Author(s)
      Kaiji Motegi
    • Organizer
      第12回日本統計学会春季集会
    • Related Report
      2017 Research-status Report
  • [Presentation] Testing for Weak Form Efficiency of Stock Markets2017

    • Author(s)
      Kaiji Motegi
    • Organizer
      50th Anniversary Seminar, Department of Statistics and Actuarial Science, University of Hong Kong
    • Related Report
      2017 Research-status Report
    • Int'l Joint Research / Invited
  • [Presentation] Testing for Weak Form Efficiency of Stock Markets2017

    • Author(s)
      Kaiji Motegi
    • Organizer
      1st International Conference on Econometrics and Statistics (EcoSta 2017)
    • Related Report
      2017 Research-status Report
    • Int'l Joint Research / Invited
  • [Presentation] Testing for Weak Form Efficiency of Stock Markets2017

    • Author(s)
      Kaiji Motegi
    • Organizer
      4th Annual Conference of the International Association for Applied Econometrics (IAAE)
    • Related Report
      2017 Research-status Report
    • Int'l Joint Research
  • [Presentation] Testing a Large Set of Zero Restrictions in Regression Models, with an Application to Mixed Frequency Granger Causality2017

    • Author(s)
      Kaiji Motegi
    • Organizer
      Workshop on Advances in Econometrics 2017
    • Related Report
      2017 Research-status Report
    • Invited
  • [Presentation] Testing for Weak Form Efficiency of Stock Markets2017

    • Author(s)
      Kaiji Motegi
    • Organizer
      2017年度統計関連学会連合大会
    • Related Report
      2017 Research-status Report
  • [Presentation] Testing for Weak Form Efficiency of Stock Markets2017

    • Author(s)
      Kaiji Motegi
    • Organizer
      3rd Annual International Conference on Applied Econometrics in Hawaii
    • Related Report
      2017 Research-status Report
    • Int'l Joint Research / Invited
  • [Presentation] Testing for Weak Form Efficiency of Stock Markets2017

    • Author(s)
      Kaiji Motegi
    • Organizer
      第24回関西計量経済学研究会
    • Place of Presentation
      広島大学(広島県広島市)
    • Related Report
      2016 Research-status Report
  • [Presentation] Testing for Weak Form Efficiency of Stock Markets2017

    • Author(s)
      Kaiji Motegi
    • Organizer
      第11回日本統計学会春季集会
    • Place of Presentation
      政策研究大学院大学(東京都・港区)
    • Related Report
      2016 Research-status Report
  • [Presentation] A Max-Correlation White Noise Test for Weakly Dependent Time Series2016

    • Author(s)
      Kaiji Motegi
    • Organizer
      Summer Workshop on Economic Theory
    • Place of Presentation
      小樽商科大学(北海道・小樽市)
    • Related Report
      2016 Research-status Report
    • Invited
  • [Presentation] A Max-Correlation White Noise Test for Weakly Dependent Time Series2016

    • Author(s)
      Kaiji Motegi
    • Organizer
      2016 Asian Meeting of the Econometric Society
    • Place of Presentation
      同志社大学(京都府・京都市)
    • Related Report
      2016 Research-status Report
    • Int'l Joint Research
  • [Presentation] A Max-Correlation White Noise Test for Weakly Dependent Time Series2016

    • Author(s)
      Kaiji Motegi
    • Organizer
      2016年度統計関連学会連合大会
    • Place of Presentation
      金沢大学(石川県・金沢市)
    • Related Report
      2016 Research-status Report
  • [Presentation] A Max-Correlation White Noise Test for Weakly Dependent Time Series2016

    • Author(s)
      Kaiji Motegi
    • Organizer
      2016 NBER-NSF Time Series Conference
    • Place of Presentation
      ニューヨーク(アメリカ合衆国)
    • Related Report
      2016 Research-status Report
    • Int'l Joint Research
  • [Remarks] Kaiji Motegi's Website

    • URL

      http://www2.kobe-u.ac.jp/~motegi/

    • Related Report
      2018 Annual Research Report
  • [Remarks] 神戸大学大学院経済学研究科 教員紹介

    • URL

      http://www.econ.kobe-u.ac.jp/faculty/fields/econometrics/motegi.html

    • Related Report
      2018 Annual Research Report
  • [Remarks] Kaiji Motegi's Personal Website

    • URL

      http://www2.kobe-u.ac.jp/~motegi/

    • Related Report
      2017 Research-status Report
  • [Remarks] 神戸大学大学院経済学研究科教員紹介ページ(和文)

    • URL

      http://www.econ.kobe-u.ac.jp/faculty/fields/econometrics/motegi.html

    • Related Report
      2017 Research-status Report
  • [Remarks] 神戸大学大学院経済学研究科教員紹介ページ(英文)

    • URL

      http://www.econ.kobe-u.ac.jp/en/people/course/econometrics/motegi.html

    • Related Report
      2017 Research-status Report

URL: 

Published: 2016-04-21   Modified: 2022-02-21  

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