Is ex-post credit risk affected by the cycles? The case of Italian banks

The objective of this research is to empirically examine if both credit and business cycle affect the ex-post credit risk (i.e. non-performing loans) in the banking system of Italy for the period 1995Q1–2014Q1. The increase in NPLs post-2008 has put into question the robustness of many European banks and the stability of the whole sector. It still remains a serious challenge, especially in Italy which is one of the countries that hit by the financial crisis. By employing fixed and random effects and a dynamic GMM estimation as econometric methodologies I find results that underline common causes for NPLs. Higher NPLs in Italy are mostly due to worse macroeconomic conditions (i.e. bad phase of business cycle) and due to excess credit. Through a Granger causality test, my arguments found even more support. Such findings can be helpful when designing macro-prudential as well as NPL resolution policies.     

On Some Characteristics of Gaussian Covariance Functions

The concepts of isotropy/anisotropy and separability/non‐separability of a covariance function are strictly related. If a covariance function is separable, it cannot be isotropic or geometrically anisotropic, except for the Gaussian covariance function, which is the only model both separable and isotropic. In this paper, some interesting results concerning the Gaussian covariance model and its properties related to isotropy and separability are given, and moreover, some examples are provided. Finally, a discussion on asymmetric models, with Gaussian marginals, is furnished and the strictly positive definiteness condition is discussed.     

Some Variants of Constrained Estimation in Finite Population Sampling

This is a review article that unifies several important examples using constrained optimisation techniques. The basic tools are three simple mathematical optimisation results subject to certain constraints. Applications include calibration, benchmarking in small area estimation and imputation. A final illustration is constrained optimisation under a general divergence loss.     

重叠滤波多音系统的频偏性能分析及优化

重叠滤波多音(O-FMT)是针对滤波多音(FMT)系统频谱利用率低的缺点而根据超奈奎斯特(FTN)概念引入子载波重叠得到的方案。鉴于O-FMT系统在频偏环境下的性能缺陷，理论分析了频偏对系统信号各部分的影响，比较了O-FMT与正交频分复用（OFDM）系统的抗频偏性能。针对频偏性能优化问题，提出了基于最佳线性无偏估计（BLUE）的改进盲估计算法，设计了基于频域滤波器系数的内嵌结构进行频偏补偿。仿真实验表明，O-FMT相比OFDM具有更好的抗频偏能力，改进的盲估计算法估计值精度更高，抗干扰、抗衰落能力更强，设计的频偏补偿结构可以使系统获得更好的性能。     

较差质量数据下的返回弹道计算及对落点影响的分析

针对某老式卫星返回时雷达跟踪数据曾发生的测量异常及质量较差等情况，为解决此类数据在返回弹道及落点计算中出现的实际困难以及给出应对措施，基于工程实际情况给出了三种不同建模类型下的弹道计算方法——当前统计解耦扩展卡尔曼滤波（EKF）、动力学建模无迹卡尔曼滤波（UKF）、多项式滑窗最小二乘估计算法，并应用该次质量较差的实际观测数据进行了算法应用效果分析与落点计算情况对比，对计算中的经验及教训进行了总结。研究结果表明，所给出的三种算法在面对较差质量数据时性能差异较大，在工程实际应用中可考虑将多种算法互为参考。研究结果及其经验教训对卫星返回弹道及落点的实时估计的工程实施有一定的参考价值。     

Bond Pricing with a Time‐Varying Price of Risk in an Estimated Medium‐Scale Bayesian DSGE Model

New Keynesian model in which households have Epstein–Zin preferences with time‐varying risk aversion and the central bank has a time‐varying inflation target can match the dynamics of nominal bond prices in the U.S. economy well. The model generates a large steady‐state term spread and its fitting errors for bond yields are comparable to those obtained from a nonstructural three‐factor model, and one‐third smaller than in models with a constant inflation target or risk aversion. Including data on interest rates has large effects on variance decompositions, making investment technology shocks much less important than found in other recent papers.     

Predictors of export performance in developing economies: a longitudinal analysis of Moroccan SMEs

Purpose: To help increase understanding of the export performance, we investigate the influence of firm size, research and development (R&D), advertising expenditures and network relationships, and develop a conceptual model to increase export intensity. Design/methodology/approach: The research involved a four-year longitudinal study of export performance of 168 exporting SMEs in Morocco (672 observations). The two-stage least square estimation (G2SLS) was used to test the hypotheses. Findings: The findings of the two-stage least square estimation (G2SLS) suggest that export sales and domestic sales are interdependent and influence each other. R&D expenditures and network affiliation have positive and significant impact on export sales, while advertising expenditure has a negative and significant influence on export sales. Research limitations/implications: Readers should use caution in generalizing the findings unless verified in other developing contexts. Practical implications: The findings of this study are useful for managers and export policy makers in developing countries. A proper understanding of the predictors of export performance may help them encourage the growth and diversification of exports that is so vital for developing countries. Originality/value: Export performance is a key element in the field of international marketing. Unfortunately, the literature exhibits a lack of empirical studies in developing countries, particularly in Maghreb regions. The empirical testing of the theoretical model in a developing economy is a significant contribution to fill the needed gap in the literature toward generalizing findings.     

一种改进的CPFSK信号频率估计方法

针对突发信号解调中多普勒频偏大的问题，提出了一种改进的连续相位移频键控信号(CPFSK)频率估计方法。首先接收信号平方运算使信号的调制指数加倍，再通过一次离散傅里叶变换(DFT)，用搜索信号平方谱谱峰的方法实现突发信号频率估计。仿真实验表明，在低信噪比条件下，该算法的频率估计精度比经典的相位差频率估计算法提高了20%；该算法与广泛用于高动态突发信号的频率插值估计算法相比，同道干扰信道下信干比改善可达4 dB，DFT长度缩短约1/3。     

Shrinkage Estimation Strategies in Generalised Ridge Regression Models: Low/High-Dimension Regime

In this study, we suggest pretest and shrinkage methods based on the generalised ridge regression estimation that is suitable for both multicollinear and high-dimensional problems. We review and develop theoretical results for some of the shrinkage estimators. The relative performance of the shrinkage estimators to some penalty methods is compared and assessed by both simulation and real-data analysis. We show that the suggested methods can be accounted as good competitors to regularisation techniques, by means of a mean squared error of estimation and prediction error. A thorough comparison of pretest and shrinkage estimators based on the maximum likelihood method to the penalty methods. In this paper, we extend the comparison outlined in his work using the least squares method for the generalised ridge regression.     

What is the major determinant of cross-border banking flows?

This study examines the major determinant of cross-border credit flows through global banks across 70 countries. Employing a Bayesian dynamic latent factor model, we decompose volatilities of banking flows into the contribution of a global common factor, regional common factor, and country-specific factor. The results indicate that the global and regional common factor explains about 40–50 percent of volatility in overall cross-border banking flows. In particular, the contribution of the global common factor increased in the 2000s. Simultaneously, main determinants are largely heterogeneous across countries: this implies that the desirable policy response to credit inflows may differ for each host country.