PREDICTION OF THE PREFECTURAL ECONOMY IN JAPAN USING A STOCHASTIC MODEL

Dr. Hiroshi SAKAMOTO

Research Associate Professor, The International Centre for the Study of East Asian Development (ICSEAD)

e-mail: sakamoto@icsead.or.jp

Abstract:

This study develops a simple forecasting model using Japanese prefectural data. The Markov chain, known as a stochastic model, corresponds to a first-order vector auto-regressive (VAR) model. If the transition probability matrix can be appropriately estimated, a forecasting model using the Markov chain can be constructed. This study introduces a methodology for estimating the transition probability matrix of the Markov chain using least-squares optimization. The model is used first to analyze economy-wide changes encompassing all Japanese prefectures up to 2020. Second, a shock emanating from one prefecture is inserted into the transition probability matrix to investigate its influence on the other prefectures. Finally, a Monte Carlo experiment is conducted to refine the model’s predicted outcomes. Although this study’s model is simple, we provide more sophisticated forecasting information for prefectural economies in Japan through the complicated extension.

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THE CHANGING ROLE OF GOVERNMENT LABS IN SCIENCE AND TECHNOLOGY POLICY

Rashid Nikzad

Industry Canada

50 Victoria st., Gatineau, QC, Canada

Rashid.Nikzad@ic.gc.ca and Rashid.Nikzad@uottawa.ca

Abstract

This paper discusses the role of government and government labs in the innovation system by looking at the content and context in which this role changed in industrialized countries in the past 40 years. The paper concludes that even though we observe a decreasing trend in the share of government performed R&D in all industrial countries, there is still a substantial role for government labs to play. Also, better measurement mechanisms should be designed to evaluate the effectiveness of science and technology (S&T) in government and higher education as main public S&T institutions.

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A METHOD FOR FORECASTING POPULATION CHANGES IN ALPINE, SEMI-ALPINE AND LOWLAND COMMUNITIES OF EPIRUS REGION IN GREECE

Georgios XANTHOS

Technological Education Institute of Crete, Greece

xanthosg@ret.forthnet.gr.

Christos Ap. LADIAS

University of Central Greece

caladias@otenet.gr

Christos GENITSAROPOULOS

University of Central Greece and

Technological Education Institute of Lamia, Greece.

cgenits@ucg.gr

Abstract

The prediction to the extent possible of the future size of the population of a region and its distribution among the settlements of the region is evidently significant for regional planning. In this paper, deriving data from population censuses, we attempted to predict the population of alpine, semi-alpine and lowland settlements of the Epirus Region. To perform the prediction, we applied a modified version of the shift and share method. In addition to applying the method, we evaluated its predictive ability in relation to a) the fixed share method, b) the fixed magnifications share method and c) the classical shift and share method, suggesting the relevant statistical tests.

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