2011
DOI: 10.1016/j.forpol.2011.03.001
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Wood import and export and its relation to major macroeconomics variables in Iran

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Cited by 16 publications
(5 citation statements)
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“…Emang et al (2010) used univariate time series models, including Holt-wintersseasonal, ARAR algorithm, and seasonal ARIMA modeling to forecast the future volume of exporting wooden products (including chipboard and moulding) in Malaysia. Mohammadi Limaei et al (2011) analyzed time series and an autoregressive procedure to predict the export and import of wood in Iran. Tajdini et al (2014) forecasted the consumption of wood-based panels in Iran using exponential smoothing and ARIMA models until 2014.…”
Section: Introductionmentioning
confidence: 99%
“…Emang et al (2010) used univariate time series models, including Holt-wintersseasonal, ARAR algorithm, and seasonal ARIMA modeling to forecast the future volume of exporting wooden products (including chipboard and moulding) in Malaysia. Mohammadi Limaei et al (2011) analyzed time series and an autoregressive procedure to predict the export and import of wood in Iran. Tajdini et al (2014) forecasted the consumption of wood-based panels in Iran using exponential smoothing and ARIMA models until 2014.…”
Section: Introductionmentioning
confidence: 99%
“…Similar papers examining the relationship between the volume of imported or exported goods and macroeconomic variables continue to be available, such as Limaei and Todshki and they all came to a positive conclusion [9,10]. This suggests that there is some relationship between import and export goods and macroeconomic variables, and relevant studies can be conducted.…”
Section: Introductionmentioning
confidence: 87%
“…However, one of the limitations of this approach is that it assumes the stationarity of the data, a condition that is usually violated for economic data (Tzanova 2017). For example, by using a multivariate regression model, Limaei et al (2011) investigated the relationship between Iranian wood import and export, and macroeconomic variables such as GDP, world oil prices, population size, and domestic wood production. Their results showed that while population size, GDP, and domestic wood production had an impact on wood exports, GDP had the highest influence on Iranian wood imports.…”
Section: Literature Reviewmentioning
confidence: 99%