• Title/Summary/Keyword: macroeconometrics model

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A Study on Estimation of Economic Effects on Mining Products Import Substitution Using Macroeconometric Input-Output Model (거시계량투입산출 모형을 이용한 광산품 수입대체의 경제적 효과 추정 연구)

  • Kim, Ji-Whan;Lee, Kyung-Han;Kim, Yoon Kyung
    • Economic and Environmental Geology
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    • v.47 no.3
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    • pp.237-246
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    • 2014
  • In this study, it is estimated how many changes of macroeconomic variables are happened under the proposition of import substitution of mining products 1% using macroeconometric input-output model. For this, used macroeconometric input-output model is composed of 141 behavioral equations representing the macroeconomy structure. In general, macroeconometrics models are constructed mainly on the side of the expenditure then it is not easy to estimate the effects of the shocks occurred from industry level. To mitigate that, this study tries to construct a macroeconometric input-output model. Macroeconometrics model which is useful to estimate the effects of macroeconomic shocks, economic policy and more, in this study, is linked with input-output table through the NDI(national disposable income) derived from compensation of employee. And this paper presents the estimation results of import substitution effects of mining products on Korean economy. As a results, GDP is increased 0.00073%, gross labor employed 0.00029%, current balanace 0.00010% and unemployment rate is mitigated 0.00233%.

Common Feature Analysis of Economic Time Series: An Overview and Recent Developments

  • Centoni, Marco;Cubadda, Gianluca
    • Communications for Statistical Applications and Methods
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    • v.22 no.5
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    • pp.415-434
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    • 2015
  • In this paper we overview the literature on common features analysis of economic time series. Starting from the seminal contributions by Engle and Kozicki (1993) and Vahid and Engle (1993), we present and discuss the various notions that have been proposed to detect and model common cyclical features in macroeconometrics. In particular, we analyze in details the link between common cyclical features and the reduced-rank regression model. We also illustrate similarities and differences between the common features methodology and other popular types of multivariate time series modelling. Finally, we discuss some recent developments in this area, such as the implications of common features for univariate time series models and the analysis of common autocorrelation in medium-large dimensional systems.