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Empirical modelling of survey-based expectations for the design of economic indicators in five European regions

机译：五个欧洲地区经济指标设计的勘测预期实证建模

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摘要

In this study we use agents' expectations about the state of the economy to generate indicators of economic activity in twenty-six European countries grouped in five regions (Western, Eastern, and Southern Europe, and Baltic and Scandinavian countries). We apply a data-driven procedure based on evolutionary computation to transform survey variables in economic growth rates. In a first step, we design five independent experiments to derive a formula using survey variables that best replicates the evolution of economic growth in each region by means of genetic programming, limiting the integration schemes to the main mathematical operations. We then rank survey variables according to their performance in tracking economic activity, finding that agents' "perception about the overall economy compared to last year" is the survey variable with the highest predictive power. In a second step, we assess the out-of-sample forecast accuracy of the evolved indicators. Although we obtain different results across regions, Austria, Slovakia, Portugal, Lithuania and Sweden are the economies of each region that show the best forecast results. We also find evidence that the forecasting performance of the survey-based indicators improves during periods of higher growth.
机译：在这项研究中，我们使用代理人对经济状况的期望，以在五个地区（西部，东部和南欧和波罗的海和斯堪的纳维亚国家）中分组的二十六个欧洲国家的经济活动指标。我们根据进化计算应用数据驱动程序，以转换经济增长率的调查变量。在第一步中，我们设计五个独立实验，通过遗传编程将每个地区的经济增长的演变进行了最佳，将整合方案限制为主要数学运算的整合方案。然后，我们按照跟踪经济活动的表现等调查变量，发现代理商的“与去年相比整体经济的看法”是预测力最高的调查变量。在第二步中，我们评估了进化指标的样本超出预测精度。虽然我们在地区，奥地利，斯洛伐克，葡萄牙，立陶宛和瑞典获得了不同的结果，但是每个地区的经济都显示出最佳预测结果。我们还发现证据表明，在增长的增长期间，基于调查指标的预测性能提高了预测。

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