کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
1891150 1533637 2016 13 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Bayesian estimation and entropy for economic dynamic stochastic models: An exploration of overconsumption
ترجمه فارسی عنوان
برآورد بیزی و آنتروپی برای مدل های تصادفی اقتصادی پویا: کشف بیش از حد مصرف
موضوعات مرتبط
مهندسی و علوم پایه فیزیک و نجوم فیزیک آماری و غیرخطی
چکیده انگلیسی
This paper examines psycho-induced overconsumption in a dynamic stochastic context. As emphasized by well-established psychological results, these psycho-distortions derive from a decision making based on simple rules-of-thumb, not on analytically sounded optimizations. To our end, we therefore compare two New Keynesian models. The first is populated by optimizing Muth-rational agents and acts as the normative benchmark. The other is a “psycho-perturbed” version of the benchmark that allows for the potential presence of overoptimism and, hence, of overconsumption. The parameters of these models are estimated through a Bayesian-type procedure, and performances are evaluated by employing an entropy measure. Such methodologies are particularly appropriate here since they take in full consideration the complexity generated by the randomness of the considered systems. In particular, they let to derive a not negligible information on the size and on the cyclical properties of the biases. In line with cognitive psychology suggestions our evidence shows that the overoptimism/overconsumption is: widespread-it is detected in nation-wide data; persistent-it emerges in full-sample estimations; it moves according to the expected cyclical behavior-larger in booms, and it disappears in crises. Moreover, by taking into account the effect of these psycho-biases, the model fits actual data better than the benchmark. All considered, then, enhancing the existing literature our findings: i) sustain the importance of inserting psychological distortions in macroeconomic models and ii) underline that system dynamics and psycho biases have statistically significant and economically important connections.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Chaos, Solitons & Fractals - Volume 88, July 2016, Pages 143-157
نویسندگان
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