This paper analyses the differential impact of several territorial determinants of the economic performance of Italian provinces (NUTS 3 level). as measured by per capita GDP, export and employment growth from 1999 to 2014. It covers both the pre‐crisis and the crisis period and stresses the role of geographical proximity in shaping local performance over a wide set of explanatory variables. In order to do so, we employ, firstly, a spatial Durbin model which enables us to discriminate between direct and indirect effects and to highlight the possible contagion or crowding‐out spatial effects for each territorial dimension affecting growth. Then, we extend the analysis by allowing for the possibility of two regimes (pre‐crisis and post‐crisis). The performance of the provinces before and during the crisis relates to specific territorial components and geographic proximity appears to influence differently the results and their interpretation.
Abstract. The conventional dyadic multiresolution analysis constructs a succession of frequency intervals in the form of (π/2 j , π/2 j−1 ); j = 1, 2, . . . , n of which the bandwidths are halved repeatedly in the descent from high frequencies to low frequencies. Whereas this scheme provides an excellent framework for encoding and transmitting signals with a high degree of data compression, it is less appropriate to statistical data analysis.This paper describes a non-dyadic mixed-radix wavelet analysis which allows the wave bands to be defined more flexibly than in the case of a conventional dyadic analysis. The wavelets that form the basis vectors for the wave bands are derived from the Fourier transforms of a variety of functions that specify the frequency responses of the filters corresponding to the sequences of wavelet coefficients.
In this paper, we are interested in detecting contagion from US to European stock market volatilities in the period immediately after the Lehman Brothers collapse. The analysis is based on a factor decomposition of the covariance matrix, in the time and frequency domain, using wavelets. The analysis aims to disentangle two components of volatility contagion (anticipated and unanticipated by the market). Once we focus on standardized factor loadings, the results show no evidence of contagion (from the US) in market expectations (coming from implied volatility) and evidence of unanticipated contagion (coming from the volatility risk premium) for almost any European country. Finally, the estimation of a three-factor model specification shows that a European common shock plays an important role in determining volatility co-movements mainly in the tranquil period, while in the period of financial turmoil, the US common shock is the main driver of volatility co-movements
The aim of the paper is to determine (endogenously) whether the volatility of the US output growth rate has changed since the late 1940s. By applying the discrete wavelet transform to the annualized quarter-toquarter output growth series, we test the homogeneity of the variance on a scale-by-scale basis. A version of the Normalized and Centered Cumulative Sum of Squares test, adapted to wavelets, leads us to reject the null of constant variance in the two levels of decomposition of the highest resolution and to locate a single break in 1982. The economic implications are explored.The signal can then be written as a sum of orthogonal components at resolutions 1 to J: f t d t d t d t d t s t J J J
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