技术变化模型适应性优度检验及预测精度检验

IF 1.1 Q3 STATISTICS & PROBABILITY Japanese Journal of Statistics and Data Science Pub Date : 2023-06-06 DOI:10.33369/jsds.v2i1.27257
Susiawati Susiawati, Budi Kurniawan
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引用次数: 0

摘要

技术系数投入产出作为技术系数矩阵(A)的一个要素,估计对今后几个时期有很好的预测。通过将该时期的最终需求(F)代入方程中的输入输出(IO)模型,可以从预测结果中获得该时期的总产出。然后将预测结果的总产出与实际总产出进行比较,以查看偏差的大小。在回归方程中,决定系数是“拟合优度”的度量,它说明回归线如何很好地解释自变量与因变量。检验方法是将当年投入产出的技术系数与第n年的技术系数用简单的线性回归方程进行回归。这个测试是为了看到技术系数在预测IO模型中的有效性。本研究是一项实证研究,使用了1998年、2007年和2016年占碑省投入产出表的数据,每个数据都收集在一个共同的集合中,以观察观察期之间的可比性。结果表明,在规划期内技术系数水平不变的假设下,技术变化模型可以很好地用于预测。同时,估计的输出偏差往往高于实际数据。
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Goodness Test of Adaptability to Model of Technical Changes and Test of Forecasting Accuracy
The technical coefficient input-output as an element of the technical coefficient matrix (A) is estimated to have good forecasts for the next several periods . By substituting the final demand (F) for the period into the Input Output (IO) model in the equation the total output for the period will be obtained from the forecasting results. The total output of forecasting results is then compared with the actual total output to see the magnitude of the deviation. In the regression equation, the coefficient of determination is a measure of “goodness of fit” which states how well the regression line explains the independent variable with the dependent variable. The test is carried out by regressing the technical coefficient of input-output in the year against the technical coefficient in the nth year in a simple linear regression equation . This test was conducted to see the validity of the technical coefficients in forecasting the IO model. This research is an empirical study that uses data from the Jambi Province Input Output Tables in 1998, 2007 and 2016, each of which has been collected in a common set to see the comparability between observation periods. The results show that the technical change model is quite well used for forecasting according to the assumption that the technical coefficient level is constant during the planning period. Meanwhile, the estimated output deviation tends to be higher than that of the actual data.
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来源期刊
CiteScore
2.00
自引率
15.40%
发文量
42
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