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Artificial Neural Network Application in Gross Domestic Product Forecasting: An Indonesia Case

机译:人工神经网络在国内生产总值预测中的应用:印度尼西亚案例

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Gross Domestic Product (GDP) is a benchmark for economic production conditions of a country. Estimates of economic growth in the coming year in a country has important roles, among others as a benchmark in determining business plans for business entities, and the basis for devising government fiscal policy. Artificial Neural Network (ANN) has been increasingly recognized as a good forecasting tool in various fields. Its nature that can mimic the workings of the human brain makes it flexible for non-linear and non-parametric data. GDP growth forecasting techniques using ANN has been widely used in various countries, such as the United States, Canada, Germany, Austria, Iran, China, Japan and others. In Indonesia, forecasting of GDP is only done by government institutions, namely National Planning Board, using macroeconomic model. In this study, ANN is used as a tool for forecasting GDP growth in Indonesia, using some variables, such as GDP growth in the two previous periods, population growth rate, inflation, exchange rate and political stability and security conditions in Indonesia. Results from this study indicate that ANN forecasts GDP relatively better than the one issued by the government. Further study would be to use ANN to predict other economic indicators.
机译:国内生产总值(GDP)是一个国家经济生产条件的基准。一个国家未来一年的经济增长估算具有重要作用,其中包括作为确定企业实体业务计划的基准以及制定政府财政政策的基础。人工神经网络(ANN)在各个领域已被越来越多地认为是一种很好的预测工具。它的性质可以模仿人脑的工作原理,因此可以灵活地处理非线性和非参数数据。使用人工神经网络的GDP增长预测技术已在美国,加拿大,德国,奥地利,伊朗,中国,日本等其他国家广泛使用。在印度尼西亚,仅由政府机构(即国家计划委员会)使用宏观经济模型对GDP进行预测。在这项研究中,使用ANN作为预测印度尼西亚GDP增长的工具,它使用了一些变量,例如前两个时期的GDP增长,印度尼西亚的人口增长率,通货膨胀,汇率以及政治稳定与安全状况。这项研究的结果表明,人工神经网络预测的GDP相对优于政府发布的GDP。进一步的研究将是使用人工神经网络来预测其他经济指标。

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