دانلود مقاله ISI انگلیسی شماره 27202
عنوان فارسی مقاله

روش حکومت سیاست پولی در داده های اقتصاد کلان: استفاده از تجزیه و تحلیل فراکتال

کد مقاله سال انتشار مقاله انگلیسی ترجمه فارسی تعداد کلمات
27202 2011 11 صفحه PDF سفارش دهید محاسبه نشده
خرید مقاله
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عنوان انگلیسی
Monetary policy regimes in macroeconomic data: An application of fractal analysis
منبع

Publisher : Elsevier - Science Direct (الزویر - ساینس دایرکت)

Journal : The Quarterly Review of Economics and Finance, Volume 51, Issue 2, May 2011, Pages 201–211

کلمات کلیدی
رژیمهای سیاست پولی - تنظیم محدوده - توان هرست - تجزیه و تحلیل فراکتال - سیاست فعال - قوانین در برابر اختیار -
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پیش نمایش مقاله روش حکومت سیاست پولی در داده های اقتصاد کلان: استفاده از تجزیه و تحلیل فراکتال

چکیده انگلیسی

Macromonetary data are examined for behavioral stability over Alan Greenspan's tenure as chairman of the Federal Reserve System. Strong evidence of stochastic dependence is found using Lo's modified rescaled range tests, though not consistently over the earlier, as opposed to the later, subsample. This finding is suggestive of a change in fundamentals such as monetary policy. Then, five self-affine fractal analysis techniques for estimating the Hurst exponent, Mandelbrot-Lévy characteristic exponent, and fractal dimension are employed to explore the data's fractal properties. Techniques are rescaled-range, power-spectral density, roughness-length, variogram, and wavelet analysis. Formal hypothesis tests provide further evidence of a change in monetary policy between the 1989–1996 and 1997–2006 subperiods. This change is manifested both in the behavior and distribution of month-to-month changes in monetary aggregates, ratios, and multipliers, and in the behavior and distribution of macroeconomic data. Most series become significantly less antipersistent after the breakpoint than before. Strong evidence is presented that U.S. monetary policy became actively interventionist after December 1996, and that the effectiveness of the Federal Reserve System has been lowered compared to the earlier period.

مقدمه انگلیسی

This paper examines the distribution of changes in macromonetary data. Statistical tests for stochastic dependence (Lo, 1991) are supplemented with five alternative methods for estimating Hurst (1951) exponent H, fractal dimension D, and Mandelbrot-Lévy characteristic exponent α ( Lévy, 1925). Findings reveal a sharp change in U.S. monetary policy starting in December 1996, announced by Federal Reserve Board Chairman Alan Greenspan's now famous “irrational exuberance” speech ( Greenspan, 1996; see also Schiller, 2000). Mandelbrot, 1972, Mandelbrot, 1975 and Mandelbrot, 1977 and Mandelbrot and Wallis's (1969d)R/S or rescaled range analysis characterizes time series as one of four types: (1) persistent, trend-reinforcing, or serially correlated series, including biased random walks, random walks with drift, and fractional Brownian motion (H > 1/2), (2) true random walks (H = 1/2), (3) antipersistent series (H < 1/2), or Cauchy processes (H = 1). Mandelbrot-Lévy distributions are a general class of infinite-variance probability distributions derived from the generalized central limit theorem, and include the normal or Gaussian and Cauchy as limiting cases ( Gnedenko and Kolmogorov, 1954 and Lévy, 1925). The reciprocal of the Mandelbrot-Lévy characteristic exponent α is the Hurst exponent H, and estimates of H indicate the probability distribution of a time series. H is also related to the fractal dimension D by the relationship D = 2 − H. Series with different fractal statistics exhibit different properties as described in Table 1. Fractal analysis applies only to stationary time series, so non-stationary series must be differenced or rendered stationary by some other means.Fractal analysis has not typically been used to analyze monetary policy or macroeconomic performance. This methodology provides additional information not offered by more conventional studies and can be used to complement, complete, and more fully interpret earlier studies. This paper's findings are that virtually all macroeonomic series are strongly antiperisistent over the whole sample range and both subsamples. Virtually all tests indicate a sharp structural break at the end of 1996, and generally, the series are significantly less antipersistent after the break than before. Because this paper applies a radically different methodology from traditional econometric tests of structural change, its results should be viewed as complementary to applications of Chow (1960) tests and its refinements, such as those of Gregory and Hansen, 1996a and Gregory and Hansen, 1996b and Bai and Perron (1998) and Bai and Perron (2003). The paper is organized as follows. A literature review is provided in the second section. The data are documented in the third section. Methodology and results are presented in the fourth and fifth sections. Conclusions are provided in the sixth section.

نتیجه گیری انگلیسی

6. Conclusion Macroeconomic data for a stable and growing economy should have Hurst exponents approximately equal to 0.50, indicating these series change in a purely random, normally distributed manner. Series with long-term trends and non-periodic cycles should display time persistence with H > 0.50, unless economic efficiency imposes randomness and normality anyway. All the macroeconomic data in this study yield strong evidence of antipersistence, and that for nearly all variables, the level of antipersistence is higher before the break than after. The lowered antipersistence in the later subsample may have resulted from financial innovation and a transfer of wealth from monetary assets to interest-bearing non-monetary assets. This substitution between monetary and non-monetary assets was facilitated by lowered transactions costs and higher relative returns on non-monetary assets, some of which became progressively more liquid due to financial innovation. Antipersistence suggests decision makers are incapable of correctly evaluating economic data, persistently overreact to the arrival of new information, and never learn not to overreact. A possible scenario that renders this finding more intuitive is that information relevant to a nation's macroeconomic performance arrives frequently and seemingly at random. Policy makers and entrepreneurial planners habitually ignore the vast majority of this information, because the vast majority is unimportant or irrelevant, until it accumulates a critical mass they must finally recognize. Confirmation bias (Wason, 1960, Wason, 1966 and Wason, 1968) imposes persistence on policy and entrepreneurial expectations, even in the presence of a certain amount of disconfirmation. Then, perceiving they have ignored an accumulating body of relevant information, planners attempt to compensate for their history of informational sloth by overreacting. The expression “informational sloth” can just as validly be characterized as “filtering out noise.” The lowered antipersistence found in the later subsample, the period of policy discretion, suggests greater economic and informational efficiency. This outcome is somewhat puzzling—although statistical results distinguish sharply between the earlier, less activist period, and the later, more activist period, ordinarily more activist policy would result in Hurst exponents farther from 1/2, rather than closer, as found here. One possible explanation is the continued financial innovation in lowering transactions costs and clearing transactions more rapidly. Financial innovations arose as a response to activist policies as an attempt to mitigate artificially low asset returns by holding as much wealth as possible in highly liquid, higher-yielding, non-monetary assets. These innovations seem to have reduced the volatility and antipersistence which more activist policy would have imposed.

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