دانلود رایگان مقاله انگلیسی شکاف نرخ سیاست بر اساس مدیریت ریسک - الزویر 2018

عنوان فارسی
شکاف نرخ سیاست بر اساس مدیریت ریسک
عنوان انگلیسی
Risk management-driven policy rate gap
صفحات مقاله فارسی
0
صفحات مقاله انگلیسی
4
سال انتشار
2018
نشریه
الزویر - Elsevier
فرمت مقاله انگلیسی
PDF
نوع مقاله
ISI
نوع نگارش
Short communication
رفرنس
دارد
پایگاه
اسکوپوس
کد محصول
E10293
رشته های مرتبط با این مقاله
مدیریت
گرایش های مرتبط با این مقاله
مدیریت ریسک
مجله
اسناد اقتصادی - Economics Letters
دانشگاه
Monash University - Australia
کلمات کلیدی
شکاف نرخ سیاست بر اساس مدیریت ریسک، عدم قطعیت، سیاست های پولی، قانون تیلور، داده های زمان واقعی
doi یا شناسه دیجیتال
https://doi.org/10.1016/j.econlet.2018.08.003
۰.۰ (بدون امتیاز)
امتیاز دهید
چکیده

abstract


We employ real-time data available to the US monetary policy makers to estimate a Taylor rule augmented with a measure of financial uncertainty over the period 1969–2008. We find evidence in favor of a systematic response to financial uncertainty over and above that to expected inflation, output gap, and output growth. However, this evidence regards the Greenspan–Bernanke period only. Focusing on this period, the "risk-management" approach is found to be responsible for monetary policy easings for up to 75 basis points of the federal funds rate.

نتیجه گیری

Conclusions


We estimate augmented Taylor rules with real time data which feature a measure of financial uncertainty among the explanatory variables. We find evidence of a significant policy response to financial uncertainty during the Greenspan–Bernanke period. We then propose an estimate of the "risk management-driven policy rate gap", which is the gap between the actual rate and a counterfactual policy rate implemented in absence of risk management. Such a gap is negative, an evidence consistent with a cautious approach (i.e., a loose monetary policy) by the Federal Reserve in presence of financial uncertainty The median value of the policy rate gap is 30 basis points, i.e., close to one standard policy move by the Federal Reserve, but larger values are detected in correspondence of large jumps in financial uncertainty, in particular those occurred in correspondence of the Black Monday and the 2008 credit crunch. Our findings point to the need of understanding how optimal monetary policy should be conducted in presence of uncertainty shocks. Recent attempts along this line are Basu and Bundick (2015) and Seneca (2018).


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