APPLYING REGRESSION MODELS WITH MIXED FREQUENCY DATA IN MODELING AND PREDICTION OF IRAN'S WHEAT IMPORT VALUE (GENERALIZED OLS-BASED ARDL APPROACH)

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JALERAJABI M.; MOGHADDASI R.

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Journal: Journal of Agricultural Economics & Development Year:2014 | Volume:28 | Issue:2 Page(s): 138-148

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Information Journal Paper

Title

APPLYING REGRESSION MODELS WITH MIXED FREQUENCY DATA IN MODELING AND PREDICTION OF IRAN'S WHEAT IMPORT VALUE (GENERALIZED OLS-BASED ARDL APPROACH)

Author(s)

JALERAJABI M. | MOGHADDASI R. | Issue Writer Certificate

Keywords

PREDICTIONQ2

REGRESSIONS WITH MIXED DATAQ2

REGRESSION WITH ADJUSTED DATAQ2

WHEAT IMPORT VALUEQ2

Abstract

Due to the importance of the import management, this study applies generalized ARDL approach to estimate MIDAS regression for WHEAT IMPORT VALUE and to compare the accuracy of forecasts with those competed by the REGRESSION WITH ADJUSTED DATA model. Mixed frequency sampling models aim to extract information with high frequency indicators so that independent variables with lower frequencies are modeled and foorcasted. Due to amore precise identification of the relationships among the variables, more accurate PREDICTION is expected. Based on the results of both estimated regression with adjusted frequency models and MIDAS for the years 1978-2003 as a training period, WHEAT IMPORT VALUE with internal products and exchange rate was positively related, while the relative price variable had an adverse relation with the Iran's WHEAT IMPORT VALUE. Based on the results from the conventional statistics such as RMSE, MAD, MAPE and the statistical significance, MIDAS models using data sets of annual WHEAT IMPORT VALUE, internal products, relative price and seasonal exchange rate significantly improves PREDICTION of annual WHEAT IMPORT VALUE for the years 2004-2008 as a testing period. Hence, it is recommended that applying PREDICTION approaches with mixed data improves modeling and PREDICTION of agricultural import value, especially for strategic import products.

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الگوئی برای نمایش چشم اندازی از تراز تجاری کشور به روش رگرسیونی داده های ترکیبی با تواتر متفاوت

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APA: Copy

JALERAJABI, M., & MOGHADDASI, R.. (2014). APPLYING REGRESSION MODELS WITH MIXED FREQUENCY DATA IN MODELING AND PREDICTION OF IRAN'S WHEAT IMPORT VALUE (GENERALIZED OLS-BASED ARDL APPROACH). JOURNAL OF ECONOMICS AND AGRICULTURE DEVELOPMENT, 28(2), 138-148. SID. https://sid.ir/paper/142113/en

Vancouver: Copy

JALERAJABI M., MOGHADDASI R.. APPLYING REGRESSION MODELS WITH MIXED FREQUENCY DATA IN MODELING AND PREDICTION OF IRAN'S WHEAT IMPORT VALUE (GENERALIZED OLS-BASED ARDL APPROACH). JOURNAL OF ECONOMICS AND AGRICULTURE DEVELOPMENT[Internet]. 2014;28(2):138-148. Available from: https://sid.ir/paper/142113/en

IEEE: Copy

M. JALERAJABI, and R. MOGHADDASI, “APPLYING REGRESSION MODELS WITH MIXED FREQUENCY DATA IN MODELING AND PREDICTION OF IRAN'S WHEAT IMPORT VALUE (GENERALIZED OLS-BASED ARDL APPROACH),” JOURNAL OF ECONOMICS AND AGRICULTURE DEVELOPMENT, vol. 28, no. 2, pp. 138–148, 2014, [Online]. Available: https://sid.ir/paper/142113/en

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